Articles | Volume 14, issue 9
Geosci. Model Dev., 14, 5487–5506, 2021
https://doi.org/10.5194/gmd-14-5487-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 14, 5487–5506, 2021
https://doi.org/10.5194/gmd-14-5487-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
06 Sep 2021
Model description paper
| 06 Sep 2021
Harmonized Emissions Component (HEMCO) 3.0 as a versatile emissions component for atmospheric models: application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS models
Haipeng Lin et al.
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Xiaotian Xu, Xu Feng, Haipeng Lin, Peng Zhang, Shaojian Huang, Zhengcheng Song, Yiming Peng, Tzung-May Fu, and Yanxu Zhang
Geosci. Model Dev., 15, 3845–3859, https://doi.org/10.5194/gmd-15-3845-2022, https://doi.org/10.5194/gmd-15-3845-2022, 2022
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Mercury is one of the most toxic pollutants in the environment, and wet deposition is a major process for atmospheric mercury to enter, causing ecological and human health risks. High-mercury wet deposition in the southeastern US has been a problem for many years. Here we employed a newly developed high-resolution WRF-GC model with the capability to simulate mercury to study this problem. We conclude that deep convection caused enhanced mercury wet deposition in the southeastern US.
Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Haipeng Lin, Elizabeth W. Lundgren, Steve Goldhaber, Steven R. H. Barrett, and Daniel J. Jacob
EGUsphere, https://doi.org/10.5194/egusphere-2022-226, https://doi.org/10.5194/egusphere-2022-226, 2022
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We bring the state-of-the-science chemistry module GEOS-Chem into the Community Earth System Model (CESM). We show that some known differences between results from GEOS-Chem and CESM’s CAM-chem chemistry module may be due to the configuration of model meteorology rather than inherent differences in the model chemistry. This is a significant step towards a truly modular ESM and allows two strong but currently separate research communities to benefit from each other’s advances.
Xu Feng, Haipeng Lin, Tzung-May Fu, Melissa P. Sulprizio, Jiawei Zhuang, Daniel J. Jacob, Heng Tian, Yaping Ma, Lijuan Zhang, Xiaolin Wang, Qi Chen, and Zhiwei Han
Geosci. Model Dev., 14, 3741–3768, https://doi.org/10.5194/gmd-14-3741-2021, https://doi.org/10.5194/gmd-14-3741-2021, 2021
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WRF-GC is an online coupling of the WRF meteorological model and GEOS-Chem chemical transport model for regional atmospheric chemistry and air quality modeling. In WRF-GC v2.0, we implemented the aerosol–radiation interactions and aerosol–cloud interactions, as well as the capability to nest multiple domains for high-resolution simulations based on the modular framework of WRF-GC v1.0. This allows the GEOS-Chem users to investigate the meteorology–atmospheric chemistry interactions.
Haipeng Lin, Xu Feng, Tzung-May Fu, Heng Tian, Yaping Ma, Lijuan Zhang, Daniel J. Jacob, Robert M. Yantosca, Melissa P. Sulprizio, Elizabeth W. Lundgren, Jiawei Zhuang, Qiang Zhang, Xiao Lu, Lin Zhang, Lu Shen, Jianping Guo, Sebastian D. Eastham, and Christoph A. Keller
Geosci. Model Dev., 13, 3241–3265, https://doi.org/10.5194/gmd-13-3241-2020, https://doi.org/10.5194/gmd-13-3241-2020, 2020
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Online coupling of meteorology and chemistry models often presents maintenance issues with hard-wired coding. We present WRF-GC, an one-way online coupling of the WRF meteorological model and GEOS-Chem atmospheric chemistry model for regional atmospheric chemistry and air quality modeling. Our coupling structure allows future versions of either parent model to be immediately integrated into WRF-GC. The WRF-GC model was able to well reproduce regional PM2.5 with greater computational efficiency.
Xiaotian Xu, Xu Feng, Haipeng Lin, Peng Zhang, Shaojian Huang, Zhengcheng Song, Yiming Peng, Tzung-May Fu, and Yanxu Zhang
Geosci. Model Dev., 15, 3845–3859, https://doi.org/10.5194/gmd-15-3845-2022, https://doi.org/10.5194/gmd-15-3845-2022, 2022
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Mercury is one of the most toxic pollutants in the environment, and wet deposition is a major process for atmospheric mercury to enter, causing ecological and human health risks. High-mercury wet deposition in the southeastern US has been a problem for many years. Here we employed a newly developed high-resolution WRF-GC model with the capability to simulate mercury to study this problem. We conclude that deep convection caused enhanced mercury wet deposition in the southeastern US.
Zichong Chen, Daniel Jacob, Hannah Nesser, Melissa Sulprizio, Alba Lorente, Daniel Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-303, https://doi.org/10.5194/acp-2022-303, 2022
Preprint under review for ACP
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We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current ‘coal-to-gas’ energy transition in China. However, this small loss rate can be misleading given China’s high gas imports.
Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Haipeng Lin, Elizabeth W. Lundgren, Steve Goldhaber, Steven R. H. Barrett, and Daniel J. Jacob
EGUsphere, https://doi.org/10.5194/egusphere-2022-226, https://doi.org/10.5194/egusphere-2022-226, 2022
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We bring the state-of-the-science chemistry module GEOS-Chem into the Community Earth System Model (CESM). We show that some known differences between results from GEOS-Chem and CESM’s CAM-chem chemistry module may be due to the configuration of model meteorology rather than inherent differences in the model chemistry. This is a significant step towards a truly modular ESM and allows two strong but currently separate research communities to benefit from each other’s advances.
William Atkinson, Sebastian D. Eastham, Y.-H. Henry Chen, Jennifer Morris, Sergey Paltsev, C. Adam Schlosser, and Noelle Eckley Selin
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-103, https://doi.org/10.5194/gmd-2022-103, 2022
Preprint under review for GMD
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Understanding policy effects on human-caused air pollutant emissions is key for assessing related health impacts. We develop a flexible scenario tool that combines updated emissions data sets, long-term economic modeling, and comprehensive technology pathways to clarify the impacts of climate and air quality policies. Results show the importance of both policy levers in the future – to prevent long-term emission increases from offsetting near-term air quality improvements from existing policies.
Patrick C. Campbell, Youhua Tang, Pius Lee, Barry Baker, Daniel Tong, Rick Saylor, Ariel Stein, Jianping Huang, Ho-Chun Huang, Edward Strobach, Jeff McQueen, Li Pan, Ivanka Stajner, Jamese Sims, Jose Tirado-Delgado, Youngsun Jung, Fanglin Yang, Tanya L. Spero, and Robert C. Gilliam
Geosci. Model Dev., 15, 3281–3313, https://doi.org/10.5194/gmd-15-3281-2022, https://doi.org/10.5194/gmd-15-3281-2022, 2022
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NOAA's National Air Quality Forecast Capability (NAQFC) continues to protect Americans from the harmful effects of air pollution, while saving billions of dollars per year. Here we describe and evaluate the development of the most advanced version of the NAQFC to date, which became operational at NOAA on 20 July 2021. The new NAQFC is based on a coupling of NOAA's operational Global Forecast System (GFS) version 16 with the Community Multiscale Air Quality (CMAQ) model version 5.3.1.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-246, https://doi.org/10.5194/acp-2022-246, 2022
Preprint under review for ACP
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We review the capability of current and planned satellite observations of atmospheric methane to quantify methane emissions from the global scale down to point sources.
Tia R. Scarpelli, Daniel J. Jacob, Shayna Grossman, Xiao Lu, Zhen Qu, Melissa P. Sulprizio, Yuzhong Zhang, Frances Reuland, Deborah Gordon, and John R. Worden
Atmos. Chem. Phys., 22, 3235–3249, https://doi.org/10.5194/acp-22-3235-2022, https://doi.org/10.5194/acp-22-3235-2022, 2022
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We present a spatially explicit version of the national inventories of oil, gas, and coal methane emissions as submitted by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. We then use atmospheric modeling to compare our inventory emissions to atmospheric methane observations with the goal of identifying potential under- and overestimates of oil–gas methane emissions in the national inventories.
Lu Shen, Ritesh Gautam, Mark Omara, Daniel Zavala-Araiza, Joannes Maasakkers, Tia Scarpelli, Alba Lorente, David Lyon, Jianxiong Sheng, Daniel Varon, Hannah Nesser, Zhen Qu, Xiao Lu, Melissa Sulprizio, Steven Hamburg, and Daniel Jacob
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-155, https://doi.org/10.5194/acp-2022-155, 2022
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We use 22 months of TROPOMI satellite observations to quantity methane emissions from the oil and natural gas sector in the US and Canada at the scale of both individual basins as well as country-wide aggregates. We find that O/G related methane emissions are underestimated in these inventories by 80 % for the US and 40 % for Canada, and 70 % of the underestimate in the US is from 5 O/G basins, including Permian, Haynesville, Anadarko, Eagle Ford and Barnett.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091, https://doi.org/10.5194/amt-15-1075-2022, https://doi.org/10.5194/amt-15-1075-2022, 2022
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This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-45, https://doi.org/10.5194/gmd-2022-45, 2022
Preprint under review for GMD
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Reducing atmospheric methane emissions is critical to abating near-term climate change. Global-surveying satellite instruments like the TROPOspheric Monitoring Instrument (TROPOMI) have unique capabilities for monitoring atmospheric methane around the world. Here we present a user-friendly cloud-computing tool that enables researchers and stakeholders to easily map methane emissions across user-selected regions of interest using TROPOMI satellite observations.
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Kelvin Bates, Jiawei Zhuang, and Wei Chen
Geosci. Model Dev., 15, 1677–1687, https://doi.org/10.5194/gmd-15-1677-2022, https://doi.org/10.5194/gmd-15-1677-2022, 2022
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The high computational cost of chemical integration is a long-standing limitation in global atmospheric chemistry models. Here we present an adaptive and efficient algorithm that can reduce the computational time of atmospheric chemistry by 50 % and maintain the error below 2 % for important species, inspired by machine learning clustering techniques and traditional asymptotic analysis ideas.
Longlei Li, Natalie Mahowald, Jasper Kok, Xiaohong Liu, Mingxuan Wu, Danny Leung, Douglas Hamilton, Louisa Emmons, Yue Huang, Jun Meng, Neil Sexton, and Jessica Wan
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-31, https://doi.org/10.5194/gmd-2022-31, 2022
Preprint under review for GMD
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This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust-climate interactions using CAM, such as the dust-radiation and dust-cloud interactions.
Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-42, https://doi.org/10.5194/gmd-2022-42, 2022
Preprint under review for GMD
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Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as stand-alone models. The widely-used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the off-line high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores including on the cloud with improved access, performance, and accuracy.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
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We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Kelvin H. Bates, Daniel J. Jacob, Ke Li, Peter D. Ivatt, Mat J. Evans, Yingying Yan, and Jintai Lin
Atmos. Chem. Phys., 21, 18351–18374, https://doi.org/10.5194/acp-21-18351-2021, https://doi.org/10.5194/acp-21-18351-2021, 2021
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Simple aromatic compounds (benzene, toluene, xylene) have complex gas-phase chemistry that is inconsistently represented in atmospheric models. We compile recent experimental and theoretical insights to develop a new mechanism for gas-phase aromatic oxidation that is sufficiently compact for use in multiscale models. We compare our new mechanism to chamber experiments and other mechanisms, and implement it in a global model to quantify the impacts of aromatic oxidation on tropospheric chemistry.
Sabour Baray, Daniel J. Jacob, Joannes D. Maasakkers, Jian-Xiong Sheng, Melissa P. Sulprizio, Dylan B. A. Jones, A. Anthony Bloom, and Robert McLaren
Atmos. Chem. Phys., 21, 18101–18121, https://doi.org/10.5194/acp-21-18101-2021, https://doi.org/10.5194/acp-21-18101-2021, 2021
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We use 2010–2015 surface and satellite observations to disentangle methane from anthropogenic and natural sources in Canada. Using a chemical transport model (GEOS-Chem), the mismatch between modelled and observed methane concentrations can be used to infer emissions according to Bayesian statistics. Compared to prior knowledge, we show higher anthropogenic emissions attributed to energy and/or agriculture in Western Canada and lower natural emissions from Boreal wetlands.
John Worden, Daniel Cusworth, Zhen Qu, Yi Yin, Yuzhong Zhang, A. Anthony Bloom, Shuang Ma, Brendan Byrne, Tia R. Scarpelli, Joannes Maasakkers, David Crisp, Riley Duren, and Daniel Jacob
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-955, https://doi.org/10.5194/acp-2021-955, 2021
Revised manuscript accepted for ACP
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This paper is intended to accomplish two goals 1) describe a new algorithm by which remotely sensed measurements of methane or other tracers can be used to not just quantify methane fluxes but attribute these fluxes to specific sources and regions and characterize their uncertainties and 2) use this new algorithm to provide methane emissions by sector and country in support of the Global Stock Take.
Li Zhang, Raffaele Montuoro, Stuart A. McKeen, Barry Baker, Partha S. Bhattacharjee, Georg A. Grell, Judy Henderson, Li Pan, Gregory J. Frost, Jeff McQueen, Rick Saylor, Haiqin Li, Ravan Ahmadov, Jun Wang, Ivanka Stajner, Shobha Kondragunta, Xiaoyang Zhang, and Fangjun Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-378, https://doi.org/10.5194/gmd-2021-378, 2021
Preprint under review for GMD
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NOAA’s air quality predictions contribute to protect lives and health in the US, which requires sustainable development and improvement of forecast system. GEFS-Aerosols v1 was developed in a collaboration between the NOAA research laboratories for operational forecast since September 2020 in the NCEP. The predictions demonstrate substantial improvements for both composition and variability of aerosol distributions over those from the former operational system.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
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Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Siqi Ma, Daniel Tong, Lok Lamsal, Julian Wang, Xuelei Zhang, Youhua Tang, Rick Saylor, Tianfeng Chai, Pius Lee, Patrick Campbell, Barry Baker, Shobha Kondragunta, Laura Judd, Timothy A. Berkoff, Scott J. Janz, and Ivanka Stajner
Atmos. Chem. Phys., 21, 16531–16553, https://doi.org/10.5194/acp-21-16531-2021, https://doi.org/10.5194/acp-21-16531-2021, 2021
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Predicting high ozone gets more challenging as urban emissions decrease. How can different techniques be used to foretell the quality of air to better protect human health? We tested four techniques with the CMAQ model against observations during a field campaign over New York City. The new system proves to better predict the magnitude and timing of high ozone. These approaches can be extended to other regions to improve the predictability of high-O3 episodes in contemporary urban environments.
Liam Bindle, Randall V. Martin, Matthew J. Cooper, Elizabeth W. Lundgren, Sebastian D. Eastham, Benjamin M. Auer, Thomas L. Clune, Hongjian Weng, Jintai Lin, Lee T. Murray, Jun Meng, Christoph A. Keller, William M. Putman, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 14, 5977–5997, https://doi.org/10.5194/gmd-14-5977-2021, https://doi.org/10.5194/gmd-14-5977-2021, 2021
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Atmospheric chemistry models like GEOS-Chem are versatile tools widely used in air pollution and climate studies. The simulations used in such studies can be very computationally demanding, and thus it is useful if the model can simulate a specific geographic region at a higher resolution than the rest of the globe. Here, we implement, test, and demonstrate a new variable-resolution capability in GEOS-Chem that is suitable for simulations conducted on supercomputers.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
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Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
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The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
Lee T. Murray, Eric M. Leibensperger, Clara Orbe, Loretta J. Mickley, and Melissa Sulprizio
Geosci. Model Dev., 14, 5789–5823, https://doi.org/10.5194/gmd-14-5789-2021, https://doi.org/10.5194/gmd-14-5789-2021, 2021
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Chemical-transport models are tools used to study air pollution and inform public policy. However, they are limited by the availability of archived meteorology. Here, we describe how the GEOS-Chem chemical-transport model may now be driven by meteorology archived from a state-of-the-art general circulation model for past and future climates, allowing it to be used to explore the impact of climate change on air pollution and atmospheric composition.
Xuan Wang, Daniel J. Jacob, William Downs, Shuting Zhai, Lei Zhu, Viral Shah, Christopher D. Holmes, Tomás Sherwen, Becky Alexander, Mathew J. Evans, Sebastian D. Eastham, J. Andrew Neuman, Patrick R. Veres, Theodore K. Koenig, Rainer Volkamer, L. Gregory Huey, Thomas J. Bannan, Carl J. Percival, Ben H. Lee, and Joel A. Thornton
Atmos. Chem. Phys., 21, 13973–13996, https://doi.org/10.5194/acp-21-13973-2021, https://doi.org/10.5194/acp-21-13973-2021, 2021
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Halogen radicals have a broad range of implications for tropospheric chemistry, air quality, and climate. We present a new mechanistic description and comprehensive simulation of tropospheric halogens in a global 3-D model and compare the model results with surface and aircraft measurements. We find that halogen chemistry decreases the global tropospheric burden of ozone by 11 %, NOx by 6 %, and OH by 4 %.
Hao Guo, Clare M. Flynn, Michael J. Prather, Sarah A. Strode, Stephen D. Steenrod, Louisa Emmons, Forrest Lacey, Jean-Francois Lamarque, Arlene M. Fiore, Gus Correa, Lee T. Murray, Glenn M. Wolfe, Jason M. St. Clair, Michelle Kim, John Crounse, Glenn Diskin, Joshua DiGangi, Bruce C. Daube, Roisin Commane, Kathryn McKain, Jeff Peischl, Thomas B. Ryerson, Chelsea Thompson, Thomas F. Hanisco, Donald Blake, Nicola J. Blake, Eric C. Apel, Rebecca S. Hornbrook, James W. Elkins, Eric J. Hintsa, Fred L. Moore, and Steven Wofsy
Atmos. Chem. Phys., 21, 13729–13746, https://doi.org/10.5194/acp-21-13729-2021, https://doi.org/10.5194/acp-21-13729-2021, 2021
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The NASA Atmospheric Tomography (ATom) mission built a climatology of the chemical composition of tropospheric air parcels throughout the middle of the Pacific and Atlantic oceans. The level of detail allows us to reconstruct the photochemical budgets of O3 and CH4 over these vast, remote regions. We find that most of the chemical heterogeneity is captured at the resolution used in current global chemistry models and that the majority of reactivity occurs in the
hottest20 % of parcels.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
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The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Tia R. Scarpelli, Melissa P. Sulprizio, Yuzhong Zhang, and Chris H. Rycroft
Atmos. Meas. Tech., 14, 5521–5534, https://doi.org/10.5194/amt-14-5521-2021, https://doi.org/10.5194/amt-14-5521-2021, 2021
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Analytical inversions of satellite observations of atmospheric composition can improve emissions estimates and quantify errors but are computationally expensive at high resolutions. We propose two methods to decrease this cost. The methods reproduce a high-resolution inversion at a quarter of the cost. The reduced-dimension method creates a multiscale grid. The reduced-rank method solves the inversion where information content is highest.
Hyun Cheol Kim, Soontae Kim, Mark Cohen, Changhan Bae, Dasom Lee, Rick Saylor, Minah Bae, Eunhye Kim, Byeong-Uk Kim, Jin-Ho Yoon, and Ariel Stein
Atmos. Chem. Phys., 21, 10065–10080, https://doi.org/10.5194/acp-21-10065-2021, https://doi.org/10.5194/acp-21-10065-2021, 2021
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Global outbreaks of COVID-19 offer rare opportunities of natural experiments in emission control and corresponding responses of tropospheric chemistry. This study's novel approach investigates (1) isolating the pandemic's impact from natural and anthropogenic variations, (2) emission adjustment to reproduce real-time emissions, and (3) brute-force modeling to investigate Chinese economic activities. Results provide characteristics of the region's chemistry and emissions.
Jun Meng, Randall V. Martin, Paul Ginoux, Melanie Hammer, Melissa P. Sulprizio, David A. Ridley, and Aaron van Donkelaar
Geosci. Model Dev., 14, 4249–4260, https://doi.org/10.5194/gmd-14-4249-2021, https://doi.org/10.5194/gmd-14-4249-2021, 2021
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Dust emissions in models, for example, GEOS-Chem, have a strong nonlinear dependence on meteorology, which means dust emission strengths calculated from different resolution meteorological fields are different. Offline high-resolution dust emissions with an optimized global dust strength, presented in this work, can be implemented into GEOS-Chem as offline emission inventory so that it could promote model development by harmonizing dust emissions across simulations of different resolutions.
Xiaoyang Chen, Yang Zhang, Kai Wang, Daniel Tong, Pius Lee, Youhua Tang, Jianping Huang, Patrick C. Campbell, Jeff Mcqueen, Havala O. T. Pye, Benjamin N. Murphy, and Daiwen Kang
Geosci. Model Dev., 14, 3969–3993, https://doi.org/10.5194/gmd-14-3969-2021, https://doi.org/10.5194/gmd-14-3969-2021, 2021
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The continuously updated National Air Quality Forecast Capability (NAQFC) provides air quality forecasts. To support the development of the next-generation NAQFC, we evaluate a prototype of GFSv15-CMAQv5.0.2. The performance and the potential improvements for the system are discussed. This study can provide a scientific basis for further development of NAQFC and help it to provide more accurate air quality forecasts to the public over the contiguous United States.
Wenfu Tang, David P. Edwards, Louisa K. Emmons, Helen M. Worden, Laura M. Judd, Lok N. Lamsal, Jassim A. Al-Saadi, Scott J. Janz, James H. Crawford, Merritt N. Deeter, Gabriele Pfister, Rebecca R. Buchholz, Benjamin Gaubert, and Caroline R. Nowlan
Atmos. Meas. Tech., 14, 4639–4655, https://doi.org/10.5194/amt-14-4639-2021, https://doi.org/10.5194/amt-14-4639-2021, 2021
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We use high-resolution airborne mapping spectrometer measurements to assess sub-grid variability within satellite pixels over urban regions. The sub-grid variability within satellite pixels increases with increasing satellite pixel sizes. Temporal variability within satellite pixels decreases with increasing satellite pixel sizes. This work is particularly relevant and useful for future satellite design, satellite data interpretation, and point-grid data comparisons.
Xu Feng, Haipeng Lin, Tzung-May Fu, Melissa P. Sulprizio, Jiawei Zhuang, Daniel J. Jacob, Heng Tian, Yaping Ma, Lijuan Zhang, Xiaolin Wang, Qi Chen, and Zhiwei Han
Geosci. Model Dev., 14, 3741–3768, https://doi.org/10.5194/gmd-14-3741-2021, https://doi.org/10.5194/gmd-14-3741-2021, 2021
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WRF-GC is an online coupling of the WRF meteorological model and GEOS-Chem chemical transport model for regional atmospheric chemistry and air quality modeling. In WRF-GC v2.0, we implemented the aerosol–radiation interactions and aerosol–cloud interactions, as well as the capability to nest multiple domains for high-resolution simulations based on the modular framework of WRF-GC v1.0. This allows the GEOS-Chem users to investigate the meteorology–atmospheric chemistry interactions.
Yaman Liu, Xinyi Dong, Minghuai Wang, Louisa K. Emmons, Yawen Liu, Yuan Liang, Xiao Li, and Manish Shrivastava
Atmos. Chem. Phys., 21, 8003–8021, https://doi.org/10.5194/acp-21-8003-2021, https://doi.org/10.5194/acp-21-8003-2021, 2021
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Secondary organic aerosol (SOA) is considered one of the most important uncertainties in climate modeling. We evaluate SOA performance in the Community Earth System Model version 2.1 (CESM2.1) configured with the Community Atmosphere Model version 6 with chemistry (CAM6-Chem) through a long-term simulation (1988–2019) with observations in the United States, which indicates monoterpene-formed SOA contributes most to the overestimation of SOA at the surface and underestimation in the upper air.
David R. Lyon, Benjamin Hmiel, Ritesh Gautam, Mark Omara, Katherine A. Roberts, Zachary R. Barkley, Kenneth J. Davis, Natasha L. Miles, Vanessa C. Monteiro, Scott J. Richardson, Stephen Conley, Mackenzie L. Smith, Daniel J. Jacob, Lu Shen, Daniel J. Varon, Aijun Deng, Xander Rudelis, Nikhil Sharma, Kyle T. Story, Adam R. Brandt, Mary Kang, Eric A. Kort, Anthony J. Marchese, and Steven P. Hamburg
Atmos. Chem. Phys., 21, 6605–6626, https://doi.org/10.5194/acp-21-6605-2021, https://doi.org/10.5194/acp-21-6605-2021, 2021
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The Permian Basin (USA) is the world’s largest oil field. We use tower- and aircraft-based approaches to measure how methane emissions in the Permian Basin changed throughout 2020. In early 2020, 3.3 % of the region’s gas was emitted; then in spring 2020, the loss rate temporarily dropped to 1.9 % as oil price crashed. We find this short-term reduction to be a result of reduced well development, less gas flaring, and fewer abnormal events despite minimal reductions in oil and gas production.
Fernando Chouza, Thierry Leblanc, Mark Brewer, Patrick Wang, Sabino Piazzolla, Gabriele Pfister, Rajesh Kumar, Carl Drews, Simone Tilmes, Louisa Emmons, and Matthew Johnson
Atmos. Chem. Phys., 21, 6129–6153, https://doi.org/10.5194/acp-21-6129-2021, https://doi.org/10.5194/acp-21-6129-2021, 2021
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The tropospheric ozone lidar at the JPL Table Mountain Facility (TMF) was used to investigate the impact of Los Angeles (LA) Basin pollution transport and stratospheric intrusions in the planetary boundary layer on the San Gabriel Mountains. The results of this study indicate a dominant role of the LA Basin pollution on days when high ozone levels were observed at TMF (March–October period).
Daniel J. Varon, Dylan Jervis, Jason McKeever, Ian Spence, David Gains, and Daniel J. Jacob
Atmos. Meas. Tech., 14, 2771–2785, https://doi.org/10.5194/amt-14-2771-2021, https://doi.org/10.5194/amt-14-2771-2021, 2021
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Satellites can detect methane emissions by measuring sunlight reflected from the Earth's surface and atmosphere. Here we show that the European Space Agency's Sentinel-2 twin satellites can be used to monitor anomalously large methane point sources around the world, with global coverage every 2–5 days and 20 m spatial resolution. We demonstrate this previously unreported capability through high-frequency Sentinel-2 monitoring of two strong methane point sources in Algeria and Turkmenistan.
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, https://doi.org/10.5194/acp-21-4637-2021, 2021
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We use an analytical solution to the Bayesian inverse problem to quantitatively compare and combine the information from satellite and in situ observations, and to estimate global methane budget and their trends over the 2010–2017 period. We find that satellite and in situ observations are to a large extent complementary in the inversion for estimating global methane budget, and reveal consistent corrections of regional anthropogenic and wetland methane emissions relative to the prior inventory.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jianxiong Sheng, Yuzhong Zhang, Xiao Lu, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, and Robert J. Parker
Atmos. Chem. Phys., 21, 4339–4356, https://doi.org/10.5194/acp-21-4339-2021, https://doi.org/10.5194/acp-21-4339-2021, 2021
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We use 2010–2015 GOSAT satellite observations of atmospheric methane over North America in a high-resolution inversion to estimate methane emissions. We find general consistency with the gridded EPA inventory but higher oil and gas production emissions, with oil production emissions twice as large as in the latest EPA Greenhouse Gas Inventory. We find lower wetland emissions than predicted by WetCHARTs and a small increasing trend in the eastern US, apparently related to unconventional oil/gas.
Paul T. Griffiths, Lee T. Murray, Guang Zeng, Youngsub Matthew Shin, N. Luke Abraham, Alexander T. Archibald, Makoto Deushi, Louisa K. Emmons, Ian E. Galbally, Birgit Hassler, Larry W. Horowitz, James Keeble, Jane Liu, Omid Moeini, Vaishali Naik, Fiona M. O'Connor, Naga Oshima, David Tarasick, Simone Tilmes, Steven T. Turnock, Oliver Wild, Paul J. Young, and Prodromos Zanis
Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, https://doi.org/10.5194/acp-21-4187-2021, 2021
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We analyse the CMIP6 Historical and future simulations for tropospheric ozone, a species which is important for many aspects of atmospheric chemistry. We show that the current generation of models agrees well with observations, being particularly successful in capturing trends in surface ozone and its vertical distribution in the troposphere. We analyse the factors that control ozone and show that they evolve over the period of the CMIP6 experiments.
Yuzhong Zhang, Daniel J. Jacob, Xiao Lu, Joannes D. Maasakkers, Tia R. Scarpelli, Jian-Xiong Sheng, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Jinfeng Chang, A. Anthony Bloom, Shuang Ma, John Worden, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, https://doi.org/10.5194/acp-21-3643-2021, 2021
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We use 2010–2018 satellite observations of atmospheric methane to interpret the factors controlling atmospheric methane and its accelerating increase during the period. The 2010–2018 increase in global methane emissions is driven by tropical and boreal wetlands and tropical livestock (South Asia, Africa, Brazil), with an insignificant positive trend in emissions from the fossil fuel sector. The peak methane growth rates in 2014–2015 are also contributed by low OH and high fire emissions.
Christoph A. Keller, Mathew J. Evans, K. Emma Knowland, Christa A. Hasenkopf, Sruti Modekurty, Robert A. Lucchesi, Tomohiro Oda, Bruno B. Franca, Felipe C. Mandarino, M. Valeria Díaz Suárez, Robert G. Ryan, Luke H. Fakes, and Steven Pawson
Atmos. Chem. Phys., 21, 3555–3592, https://doi.org/10.5194/acp-21-3555-2021, https://doi.org/10.5194/acp-21-3555-2021, 2021
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This study combines surface observations and model simulations to quantify the impact of COVID-19 restrictions on air quality across the world. The presented methodology removes the confounding impacts of meteorology on air pollution. Our results indicate that surface concentrations of nitrogen dioxide, an important air pollutant emitted during the combustion of fossil fuels, declined by up to 60 % following the implementation of COVID-19 containment measures.
Duseong S. Jo, Alma Hodzic, Louisa K. Emmons, Simone Tilmes, Rebecca H. Schwantes, Michael J. Mills, Pedro Campuzano-Jost, Weiwei Hu, Rahul A. Zaveri, Richard C. Easter, Balwinder Singh, Zheng Lu, Christiane Schulz, Johannes Schneider, John E. Shilling, Armin Wisthaler, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 3395–3425, https://doi.org/10.5194/acp-21-3395-2021, https://doi.org/10.5194/acp-21-3395-2021, 2021
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Secondary organic aerosol (SOA) is a major component of submicron particulate matter, but there are a lot of uncertainties in the future prediction of SOA. We used CESM 2.1 to investigate future IEPOX SOA concentration changes. The explicit chemistry predicted substantial changes in IEPOX SOA depending on the future scenario, but the parameterization predicted weak changes due to simplified chemistry, which shows the importance of correct physicochemical dependencies in future SOA prediction.
Youhua Tang, Huisheng Bian, Zhining Tao, Luke D. Oman, Daniel Tong, Pius Lee, Patrick C. Campbell, Barry Baker, Cheng-Hsuan Lu, Li Pan, Jun Wang, Jeffery McQueen, and Ivanka Stajner
Atmos. Chem. Phys., 21, 2527–2550, https://doi.org/10.5194/acp-21-2527-2021, https://doi.org/10.5194/acp-21-2527-2021, 2021
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Chemical lateral boundary condition (CLBC) impact is essential for regional air quality prediction during intrusion events. We present a model mapping Goddard Earth Observing System (GEOS) to Community Multi-scale Air Quality (CMAQ) CB05–AERO6 (Carbon Bond 5; version 6 of the aerosol module) species. Influence depends on distance from the inflow boundary and species and their regional characteristics. We use aerosol optical thickness to derive CLBCs, achieving reasonable prediction.
Bo Zhang, Hongyu Liu, James H. Crawford, Gao Chen, T. Duncan Fairlie, Scott Chambers, Chang-Hee Kang, Alastair G. Williams, Kai Zhang, David B. Considine, Melissa P. Sulprizio, and Robert M. Yantosca
Atmos. Chem. Phys., 21, 1861–1887, https://doi.org/10.5194/acp-21-1861-2021, https://doi.org/10.5194/acp-21-1861-2021, 2021
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We simulate atmospheric 222Rn using the GEOS-Chem model to improve understanding of 222Rn emissions and characterize convective transport in the model. We demonstrate the potential of a customized global 222Rn emission scenario to improve simulated surface 222Rn concentrations and seasonality. We assess convective transport using observed 222Rn vertical profiles. Results have important implications for using chemical transport models to interpret the transport of trace gases and aerosols.
Inés Sanz-Morère, Sebastian D. Eastham, Florian Allroggen, Raymond L. Speth, and Steven R. H. Barrett
Atmos. Chem. Phys., 21, 1649–1681, https://doi.org/10.5194/acp-21-1649-2021, https://doi.org/10.5194/acp-21-1649-2021, 2021
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Contrails cause ~50 % of aviation climate impacts, but this is highly uncertain. This is partly due to the effect of overlap between contrails and other cloud layers. We developed a model to quantify this effect, finding that overlap with natural clouds increased contrails' radiative forcing in 2015. This suggests that cloud avoidance may help in reducing aviation's climate impacts. We also find that contrail–contrail overlap reduces impacts by ~3 %, increasing non-linearly with optical depth.
Gillian D. Thornhill, William J. Collins, Ryan J. Kramer, Dirk Olivié, Ragnhild B. Skeie, Fiona M. O'Connor, Nathan Luke Abraham, Ramiro Checa-Garcia, Susanne E. Bauer, Makoto Deushi, Louisa K. Emmons, Piers M. Forster, Larry W. Horowitz, Ben Johnson, James Keeble, Jean-Francois Lamarque, Martine Michou, Michael J. Mills, Jane P. Mulcahy, Gunnar Myhre, Pierre Nabat, Vaishali Naik, Naga Oshima, Michael Schulz, Christopher J. Smith, Toshihiko Takemura, Simone Tilmes, Tongwen Wu, Guang Zeng, and Jie Zhang
Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, https://doi.org/10.5194/acp-21-853-2021, 2021
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This paper is a study of how different constituents in the atmosphere, such as aerosols and gases like methane and ozone, affect the energy balance in the atmosphere. Different climate models were run using the same inputs to allow an easy comparison of the results and to understand where the models differ. We found the effect of aerosols is to reduce warming in the atmosphere, but this effect varies between models. Reactions between gases are also important in affecting climate.
Susan S. Kulawik, John R. Worden, Vivienne H. Payne, Dejian Fu, Steven C. Wofsy, Kathryn McKain, Colm Sweeney, Bruce C. Daube Jr., Alan Lipton, Igor Polonsky, Yuguang He, Karen E. Cady-Pereira, Edward J. Dlugokencky, Daniel J. Jacob, and Yi Yin
Atmos. Meas. Tech., 14, 335–354, https://doi.org/10.5194/amt-14-335-2021, https://doi.org/10.5194/amt-14-335-2021, 2021
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This paper shows comparisons of a new single-footprint methane product from the AIRS satellite to aircraft-based observations. We show that this AIRS methane product provides useful information to study seasonal and global methane trends of this important greenhouse gas.
Benjamin Gaubert, Louisa K. Emmons, Kevin Raeder, Simone Tilmes, Kazuyuki Miyazaki, Avelino F. Arellano Jr., Nellie Elguindi, Claire Granier, Wenfu Tang, Jérôme Barré, Helen M. Worden, Rebecca R. Buchholz, David P. Edwards, Philipp Franke, Jeffrey L. Anderson, Marielle Saunois, Jason Schroeder, Jung-Hun Woo, Isobel J. Simpson, Donald R. Blake, Simone Meinardi, Paul O. Wennberg, John Crounse, Alex Teng, Michelle Kim, Russell R. Dickerson, Hao He, Xinrong Ren, Sally E. Pusede, and Glenn S. Diskin
Atmos. Chem. Phys., 20, 14617–14647, https://doi.org/10.5194/acp-20-14617-2020, https://doi.org/10.5194/acp-20-14617-2020, 2020
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This study investigates carbon monoxide pollution in East Asia during spring using a numerical model, satellite remote sensing, and aircraft measurements. We found an underestimation of emission sources. Correcting the emission bias can improve air quality forecasting of carbon monoxide and other species including ozone. Results also suggest that controlling VOC and CO emissions, in addition to widespread NOx controls, can improve ozone pollution over East Asia.
Steven T. Turnock, Robert J. Allen, Martin Andrews, Susanne E. Bauer, Makoto Deushi, Louisa Emmons, Peter Good, Larry Horowitz, Jasmin G. John, Martine Michou, Pierre Nabat, Vaishali Naik, David Neubauer, Fiona M. O'Connor, Dirk Olivié, Naga Oshima, Michael Schulz, Alistair Sellar, Sungbo Shim, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 20, 14547–14579, https://doi.org/10.5194/acp-20-14547-2020, https://doi.org/10.5194/acp-20-14547-2020, 2020
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A first assessment is made of the historical and future changes in air pollutants from models participating in the 6th Coupled Model Intercomparison Project (CMIP6). Substantial benefits to future air quality can be achieved in future scenarios that implement measures to mitigate climate and involve reductions in air pollutant emissions, particularly methane. However, important differences are shown between models in the future regional projection of air pollutants under the same scenario.
Junfeng Wang, Jianhuai Ye, Dantong Liu, Yangzhou Wu, Jian Zhao, Weiqi Xu, Conghui Xie, Fuzhen Shen, Jie Zhang, Paul E. Ohno, Yiming Qin, Xiuyong Zhao, Scot T. Martin, Alex K. Y. Lee, Pingqing Fu, Daniel J. Jacob, Qi Zhang, Yele Sun, Mindong Chen, and Xinlei Ge
Atmos. Chem. Phys., 20, 14091–14102, https://doi.org/10.5194/acp-20-14091-2020, https://doi.org/10.5194/acp-20-14091-2020, 2020
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We compared the organics in total submicron matter and those coated on BC cores during summertime in Beijing and found large differences between them. Traffic-related OA was associated significantly with BC, while cooking-related OA did not coat BC. In addition, a factor likely originated from primary biomass burning OA was only identified in BC-containing particles. Such a unique BBOA requires further field and laboratory studies to verify its presence and elucidate its properties and impacts.
David S. Stevenson, Alcide Zhao, Vaishali Naik, Fiona M. O'Connor, Simone Tilmes, Guang Zeng, Lee T. Murray, William J. Collins, Paul T. Griffiths, Sungbo Shim, Larry W. Horowitz, Lori T. Sentman, and Louisa Emmons
Atmos. Chem. Phys., 20, 12905–12920, https://doi.org/10.5194/acp-20-12905-2020, https://doi.org/10.5194/acp-20-12905-2020, 2020
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We present historical trends in atmospheric oxidizing capacity (OC) since 1850 from the latest generation of global climate models and compare these with estimates from measurements. OC controls levels of many key reactive gases, including methane (CH4). We find small model trends up to 1980, then increases of about 9 % up to 2014, disagreeing with (uncertain) measurement-based trends. Major drivers of OC trends are emissions of CH4, NOx, and CO; these will be important for future CH4 trends.
Viral Shah, Daniel J. Jacob, Jonathan M. Moch, Xuan Wang, and Shixian Zhai
Atmos. Chem. Phys., 20, 12223–12245, https://doi.org/10.5194/acp-20-12223-2020, https://doi.org/10.5194/acp-20-12223-2020, 2020
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Cloud water pH affects atmospheric chemistry, and acid rain damages ecosystems. We use model simulations along with observations to present a global view of cloud water and precipitation pH. Sulfuric acid, nitric acid, and ammonia control the pH in the northern midlatitudes, but carboxylic acids and dust cations are important in the tropics and subtropics. The acid inputs to many nitrogen-saturated ecosystems are high enough to cause acidification, with ammonium as the main acidifying species.
Ke Li, Daniel J. Jacob, Lu Shen, Xiao Lu, Isabelle De Smedt, and Hong Liao
Atmos. Chem. Phys., 20, 11423–11433, https://doi.org/10.5194/acp-20-11423-2020, https://doi.org/10.5194/acp-20-11423-2020, 2020
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Surface summer ozone increased in China from 2013 to 2019 despite new governmental efforts targeting ozone pollution. We find that the ozone increase is mostly due to anthropogenic drivers, although meteorology also plays a role. Further analysis for the North China Plain shows that PM2.5 continued to decrease through 2019, while emissions of volatile organic compounds (VOCs) stayed flat. This could explain the anthropogenic increase in ozone, as PM2.5 scavenges the radical precursors of ozone.
Xiao Lu, Lin Zhang, Tongwen Wu, Michael S. Long, Jun Wang, Daniel J. Jacob, Fang Zhang, Jie Zhang, Sebastian D. Eastham, Lu Hu, Lei Zhu, Xiong Liu, and Min Wei
Geosci. Model Dev., 13, 3817–3838, https://doi.org/10.5194/gmd-13-3817-2020, https://doi.org/10.5194/gmd-13-3817-2020, 2020
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This study presents the development and evaluation of a new climate chemistry model, BCC-GEOS-Chem v1.0, which couples the GEOS-Chem chemical transport model as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model. A 3-year (2012–2014) simulation of BCC-GEOS-Chem v1.0 shows that the model captures well the spatiotemporal distributions of tropospheric ozone, other gaseous pollutants, and aerosols.
Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Yonghoon Choi, Joshua P. DiGangi, Glenn S. Diskin, Xiaomei Xu, Cenlin He, Helen Worden, Simone Tilmes, Rebecca Buchholz, Hannah S. Halliday, and Avelino F. Arellano
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-864, https://doi.org/10.5194/acp-2020-864, 2020
Revised manuscript not accepted
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A specific demonstration of the potential use of correlative information from carbon monoxide to refine estimates of regional carbon dioxide emissions from fossil fuel combustion.
Robert J. Allen, Steven Turnock, Pierre Nabat, David Neubauer, Ulrike Lohmann, Dirk Olivié, Naga Oshima, Martine Michou, Tongwen Wu, Jie Zhang, Toshihiko Takemura, Michael Schulz, Kostas Tsigaridis, Susanne E. Bauer, Louisa Emmons, Larry Horowitz, Vaishali Naik, Twan van Noije, Tommi Bergman, Jean-Francois Lamarque, Prodromos Zanis, Ina Tegen, Daniel M. Westervelt, Philippe Le Sager, Peter Good, Sungbo Shim, Fiona O'Connor, Dimitris Akritidis, Aristeidis K. Georgoulias, Makoto Deushi, Lori T. Sentman, Jasmin G. John, Shinichiro Fujimori, and William J. Collins
Atmos. Chem. Phys., 20, 9641–9663, https://doi.org/10.5194/acp-20-9641-2020, https://doi.org/10.5194/acp-20-9641-2020, 2020
Sarah A. Strode, James S. Wang, Michael Manyin, Bryan Duncan, Ryan Hossaini, Christoph A. Keller, Sylvia E. Michel, and James W. C. White
Atmos. Chem. Phys., 20, 8405–8419, https://doi.org/10.5194/acp-20-8405-2020, https://doi.org/10.5194/acp-20-8405-2020, 2020
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The 13C : 12C isotopic ratio in methane (CH4) provides information about CH4 sources, but loss of CH4 by reaction with OH and chlorine (Cl) also affects this ratio. Tropospheric Cl provides a small and uncertain sink for CH4 but has a large effect on its isotopic ratio. We use the GEOS model with several different Cl fields to test the sensitivity of methane's isotopic composition to tropospheric Cl. Cl affects the global mean, hemispheric gradient, and seasonal cycle of the isotopic ratio.
Haipeng Lin, Xu Feng, Tzung-May Fu, Heng Tian, Yaping Ma, Lijuan Zhang, Daniel J. Jacob, Robert M. Yantosca, Melissa P. Sulprizio, Elizabeth W. Lundgren, Jiawei Zhuang, Qiang Zhang, Xiao Lu, Lin Zhang, Lu Shen, Jianping Guo, Sebastian D. Eastham, and Christoph A. Keller
Geosci. Model Dev., 13, 3241–3265, https://doi.org/10.5194/gmd-13-3241-2020, https://doi.org/10.5194/gmd-13-3241-2020, 2020
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Online coupling of meteorology and chemistry models often presents maintenance issues with hard-wired coding. We present WRF-GC, an one-way online coupling of the WRF meteorological model and GEOS-Chem atmospheric chemistry model for regional atmospheric chemistry and air quality modeling. Our coupling structure allows future versions of either parent model to be immediately integrated into WRF-GC. The WRF-GC model was able to well reproduce regional PM2.5 with greater computational efficiency.
Pablo E. Saide, Meng Gao, Zifeng Lu, Daniel L. Goldberg, David G. Streets, Jung-Hun Woo, Andreas Beyersdorf, Chelsea A. Corr, Kenneth L. Thornhill, Bruce Anderson, Johnathan W. Hair, Amin R. Nehrir, Glenn S. Diskin, Jose L. Jimenez, Benjamin A. Nault, Pedro Campuzano-Jost, Jack Dibb, Eric Heim, Kara D. Lamb, Joshua P. Schwarz, Anne E. Perring, Jhoon Kim, Myungje Choi, Brent Holben, Gabriele Pfister, Alma Hodzic, Gregory R. Carmichael, Louisa Emmons, and James H. Crawford
Atmos. Chem. Phys., 20, 6455–6478, https://doi.org/10.5194/acp-20-6455-2020, https://doi.org/10.5194/acp-20-6455-2020, 2020
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Air quality forecasts over the Korean Peninsula captured aerosol optical depth but largely overpredicted surface PM during a Chinese haze transport event. Model deficiency was related to the calculation of optical properties. In order to improve it, aerosol size representation needs to be refined in the calculations, and the representation of aerosol properties, such as size distribution, chemical composition, refractive index, hygroscopicity parameter, and density, needs to be improved.
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Xuan Wang, and Wei Chen
Geosci. Model Dev., 13, 2475–2486, https://doi.org/10.5194/gmd-13-2475-2020, https://doi.org/10.5194/gmd-13-2475-2020, 2020
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Chemical mechanisms in air quality models tend to get more complicated with time, reflecting both increasing knowledge and the need for greater scope. This objectively improves the models but increases the computational burden. In this work, we present an approach that can reduce the computational cost of chemical integration by 30–40 % while maintaining an accuracy better than 1 %. It retains the complexity of the full mechanism where it is needed and preserves full diagnostic information.
Thibaud M. Fritz, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Atmos. Chem. Phys., 20, 5697–5727, https://doi.org/10.5194/acp-20-5697-2020, https://doi.org/10.5194/acp-20-5697-2020, 2020
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Aircraft exhaust drives formation of ozone and is a dominant anthropogenic influence in the upper troposphere. These impacts are mitigated by non-linear chemistry inside the aircraft plume, which cuts off part of the ozone production pathway and reduces the long-term impact of aircraft in a way which is not captured by current models. The ice clouds which form in aircraft exhaust ("contrails") also play a role, converting emitted nitrogen oxides into more stable forms such as nitric acid.
Li Pan, HyunCheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
Geosci. Model Dev., 13, 2169–2184, https://doi.org/10.5194/gmd-13-2169-2020, https://doi.org/10.5194/gmd-13-2169-2020, 2020
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Compared to anthropogenic emissions, emissions from wildfires are largely uncontrolled and unpredictable. Quantitatively describing wildfire emissions and their contributions to air pollution remains a substantial challenge for air quality forecasting efforts. In this study, we test the wildfire calculation algorithm used by the National Air Quality Forecasting Capability (NAQFC) by comparison with ground, satellite and flight measurements during the Southeast Nexus (SENEX) field experiment.
Rebecca H. Schwantes, Louisa K. Emmons, John J. Orlando, Mary C. Barth, Geoffrey S. Tyndall, Samuel R. Hall, Kirk Ullmann, Jason M. St. Clair, Donald R. Blake, Armin Wisthaler, and Thao Paul V. Bui
Atmos. Chem. Phys., 20, 3739–3776, https://doi.org/10.5194/acp-20-3739-2020, https://doi.org/10.5194/acp-20-3739-2020, 2020
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Ozone is a greenhouse gas and air pollutant that is harmful to human health and plants. During the summer in the southeastern US, many regional and global models are biased high for surface ozone compared to observations. Here adding more complex and updated chemistry for isoprene and terpenes, which are biogenic hydrocarbons emitted from trees and vegetation, into an earth system model greatly reduces the simulated surface ozone bias compared to aircraft and monitoring station data.
Wenfu Tang, Helen M. Worden, Merritt N. Deeter, David P. Edwards, Louisa K. Emmons, Sara Martínez-Alonso, Benjamin Gaubert, Rebecca R. Buchholz, Glenn S. Diskin, Russell R. Dickerson, Xinrong Ren, Hao He, and Yutaka Kondo
Atmos. Meas. Tech., 13, 1337–1356, https://doi.org/10.5194/amt-13-1337-2020, https://doi.org/10.5194/amt-13-1337-2020, 2020
Tia R. Scarpelli, Daniel J. Jacob, Joannes D. Maasakkers, Melissa P. Sulprizio, Jian-Xiong Sheng, Kelly Rose, Lucy Romeo, John R. Worden, and Greet Janssens-Maenhout
Earth Syst. Sci. Data, 12, 563–575, https://doi.org/10.5194/essd-12-563-2020, https://doi.org/10.5194/essd-12-563-2020, 2020
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Methane, a potent greenhouse gas, is emitted through the exploitation of oil, gas, and coal resources, and many efforts to reduce emissions have targeted these sources. We have created a global inventory of oil, gas, and coal methane emissions based on country reporting to the United Nations. The inventory can be used along with satellite observations of methane to better understand the contribution of these sources to global emissions and to identify potential biases in emissions reporting.
Viral Shah, Daniel J. Jacob, Ke Li, Rachel F. Silvern, Shixian Zhai, Mengyao Liu, Jintai Lin, and Qiang Zhang
Atmos. Chem. Phys., 20, 1483–1495, https://doi.org/10.5194/acp-20-1483-2020, https://doi.org/10.5194/acp-20-1483-2020, 2020
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We analyze 15 years of satellite observations of nitrogen dioxide (NO2) and use an atmospheric chemistry model to understand the seasonal changes and trends in nitrogen oxides (NOx) over China. We show that the seasonal changes in NO2 occur due to changes in the NOx oxidation lifetime. We find that Chinese NOx emissions peaked in 2011 and had decreased by about 25 % by 2018. But the decrease in NO2 in winter was larger, likely because of a simultaneous decrease in the NOx oxidation lifetime.
Daniel H. Cusworth, Daniel J. Jacob, Daniel J. Varon, Christopher Chan Miller, Xiong Liu, Kelly Chance, Andrew K. Thorpe, Riley M. Duren, Charles E. Miller, David R. Thompson, Christian Frankenberg, Luis Guanter, and Cynthia A. Randles
Atmos. Meas. Tech., 12, 5655–5668, https://doi.org/10.5194/amt-12-5655-2019, https://doi.org/10.5194/amt-12-5655-2019, 2019
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We examine the potential for global detection of methane plumes from individual point sources with the new generation of spaceborne imaging spectrometers scheduled for launch in 2019–2025. We perform methane retrievals on simulated scenes with varying surfaces and atmospheric methane concentrations. Our results suggest that imaging spectrometers in space could play a transformative role in the future for quantifying methane emissions from point sources on a global scale.
Shixian Zhai, Daniel J. Jacob, Xuan Wang, Lu Shen, Ke Li, Yuzhong Zhang, Ke Gui, Tianliang Zhao, and Hong Liao
Atmos. Chem. Phys., 19, 11031–11041, https://doi.org/10.5194/acp-19-11031-2019, https://doi.org/10.5194/acp-19-11031-2019, 2019
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Observed annual mean PM2.5 decreased by 30–50 % in China from 2013–2018. However, meteorologically PM2.5 variability complicates trend attribution. We used a stepwise multiple linear regression model to quantitatively separate contributions from anthropogenic emissions and meteorology. Results show that 88 % of the PM2.5 decrease across China is attributable to anthropogenic emission changes, and 12 % is attributable to meteorology.
Katherine R. Travis and Daniel J. Jacob
Geosci. Model Dev., 12, 3641–3648, https://doi.org/10.5194/gmd-12-3641-2019, https://doi.org/10.5194/gmd-12-3641-2019, 2019
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Models of ozone air pollution are often evaluated with the policy metric set by the EPA of the maximum daily 8 h average ozone concentration. These models may be used in policy settings to evaluate air quality regulations. However, most models have difficulty simulating how ozone varies over the course of the day, and thus the use of this metric in model evaluation is problematic. Improved representation of mixed layer dynamics and ozone loss to the surface is needed to resolve this issue.
Kelvin H. Bates and Daniel J. Jacob
Atmos. Chem. Phys., 19, 9613–9640, https://doi.org/10.5194/acp-19-9613-2019, https://doi.org/10.5194/acp-19-9613-2019, 2019
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Isoprene is a highly reactive chemical released to the atmosphere by plants. Its gas-phase reactions and interactions with chemicals released by human activity have far-reaching atmospheric consequences, contributing to ozone and particulate pollution and prolonging the lifetime of methane, a potent greenhouse gas. We use global simulations with a new isoprene reaction scheme to quantify those effects and to show how recently discovered aspects of isoprene chemistry play out on a global scale.
Duseong S. Jo, Alma Hodzic, Louisa K. Emmons, Eloise A. Marais, Zhe Peng, Benjamin A. Nault, Weiwei Hu, Pedro Campuzano-Jost, and Jose L. Jimenez
Geosci. Model Dev., 12, 2983–3000, https://doi.org/10.5194/gmd-12-2983-2019, https://doi.org/10.5194/gmd-12-2983-2019, 2019
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We developed a parameterization method for IEPOX-SOA based on the detailed chemical mechanism. Our parameterizations were tested using a box model and 3-D chemical transport model, which accurately captured the spatiotemporal distribution and response to changes in emissions compared to the explicit full chemistry, while being more computationally efficient. The method developed in this study can be applied to global climate models for long-term studies with a lower computational cost.
Rachel F. Silvern, Daniel J. Jacob, Loretta J. Mickley, Melissa P. Sulprizio, Katherine R. Travis, Eloise A. Marais, Ronald C. Cohen, Joshua L. Laughner, Sungyeon Choi, Joanna Joiner, and Lok N. Lamsal
Atmos. Chem. Phys., 19, 8863–8878, https://doi.org/10.5194/acp-19-8863-2019, https://doi.org/10.5194/acp-19-8863-2019, 2019
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The US EPA reports a steady decrease in nitrogen oxide (NOx) emissions from fuel combustion over the 2005–2017 period, while satellite observations show a leveling off after 2009, suggesting emission reductions and related air quality gains have halted. We show the sustained decrease in NOx emissions is in fact consistent with observed trends in surface NO2 and ozone concentrations and that the flattening of the satellite trend reflects a growing influence from the non-anthropogenic background.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jian-Xiong Sheng, Yuzhong Zhang, Monica Hersher, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, Greet Janssens-Maenhout, and Robert J. Parker
Atmos. Chem. Phys., 19, 7859–7881, https://doi.org/10.5194/acp-19-7859-2019, https://doi.org/10.5194/acp-19-7859-2019, 2019
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We use 2010–2015 satellite observations of atmospheric methane to improve estimates of methane emissions and their trends, as well as the concentration and trend of tropospheric OH (hydroxyl radical, methane's main sink). We find overestimates of Chinese coal and Middle East oil/gas emissions in the prior estimate. The 2010–2015 growth in methane is attributed to an increase in emissions from India, China, and areas with large tropical wetlands. The contribution from OH is small in comparison.
Lu Shen, Daniel J. Jacob, Xiong Liu, Guanyu Huang, Ke Li, Hong Liao, and Tao Wang
Atmos. Chem. Phys., 19, 6551–6560, https://doi.org/10.5194/acp-19-6551-2019, https://doi.org/10.5194/acp-19-6551-2019, 2019
Lei Zhu, Daniel J. Jacob, Sebastian D. Eastham, Melissa P. Sulprizio, Xuan Wang, Tomás Sherwen, Mat J. Evans, Qianjie Chen, Becky Alexander, Theodore K. Koenig, Rainer Volkamer, L. Gregory Huey, Michael Le Breton, Thomas J. Bannan, and Carl J. Percival
Atmos. Chem. Phys., 19, 6497–6507, https://doi.org/10.5194/acp-19-6497-2019, https://doi.org/10.5194/acp-19-6497-2019, 2019
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We quantify the effect of sea salt aerosol on tropospheric bromine chemistry with a new mechanistic description of the halogen chemistry in a global atmospheric chemistry model. For the first time, we are able to reproduce the observed levels of bromide activation from the sea salt aerosol in a manner consistent with bromine oxide radical measured from various platforms. Sea salt aerosol plays a far more complex role in global tropospheric chemistry than previously recognized.
Meghana Velegar, N. Benjamin Erichson, Christoph A. Keller, and J. Nathan Kutz
Geosci. Model Dev., 12, 1525–1539, https://doi.org/10.5194/gmd-12-1525-2019, https://doi.org/10.5194/gmd-12-1525-2019, 2019
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We introduce a new set of algorithmic tools capable of producing scalable, low-rank decompositions of global spatiotemporal atmospheric chemistry data. By exploiting emerging randomized linear algebra algorithms, a suite of decompositions are proposed that efficiently extract the dominant features from global atmospheric chemistry at longitude, latitude, and elevation with improved interpretability. The algorithms provide a strategy for the global monitoring of atmospheric chemistry.
Christoph A. Keller and Mat J. Evans
Geosci. Model Dev., 12, 1209–1225, https://doi.org/10.5194/gmd-12-1209-2019, https://doi.org/10.5194/gmd-12-1209-2019, 2019
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Computer simulations of atmospheric chemistry are a central tool to study the impact of air pollutants on the environment. These models are highly complex and require a lot of computing resources. In this study we show that machine learning can be used to predict air pollution with an accuracy that is comparable to the traditional, computationally expensive method. Such a machine-learning-based model has the potential to be orders of magnitude faster.
Xuan Wang, Daniel J. Jacob, Sebastian D. Eastham, Melissa P. Sulprizio, Lei Zhu, Qianjie Chen, Becky Alexander, Tomás Sherwen, Mathew J. Evans, Ben H. Lee, Jessica D. Haskins, Felipe D. Lopez-Hilfiker, Joel A. Thornton, Gregory L. Huey, and Hong Liao
Atmos. Chem. Phys., 19, 3981–4003, https://doi.org/10.5194/acp-19-3981-2019, https://doi.org/10.5194/acp-19-3981-2019, 2019
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Chlorine radicals have a broad range of implications for tropospheric chemistry, air quality, and climate. We present a comprehensive simulation of tropospheric chlorine in a global 3-D model, which includes explicit accounting of chloride mobilization from sea salt aerosol. We find the chlorine chemistry contributes 1.0 % of the global oxidation of methane and decreases global burdens of tropospheric ozone by 7 % and OH by 3 % through the associated bromine radical chemistry.
Kai-Lan Chang, Owen R. Cooper, J. Jason West, Marc L. Serre, Martin G. Schultz, Meiyun Lin, Virginie Marécal, Béatrice Josse, Makoto Deushi, Kengo Sudo, Junhua Liu, and Christoph A. Keller
Geosci. Model Dev., 12, 955–978, https://doi.org/10.5194/gmd-12-955-2019, https://doi.org/10.5194/gmd-12-955-2019, 2019
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We developed a new method for combining surface ozone observations from thousands of monitoring sites worldwide with the output from multiple atmospheric chemistry models. The result is a global surface ozone distribution with greater accuracy than any single model can achieve. We focused on an ozone metric relevant to human mortality caused by long-term ozone exposure. Our method can be applied to studies that quantify the impacts of ozone on human health and mortality.
Shaojie Song, Meng Gao, Weiqi Xu, Yele Sun, Douglas R. Worsnop, John T. Jayne, Yuzhong Zhang, Lei Zhu, Mei Li, Zhen Zhou, Chunlei Cheng, Yibing Lv, Ying Wang, Wei Peng, Xiaobin Xu, Nan Lin, Yuxuan Wang, Shuxiao Wang, J. William Munger, Daniel J. Jacob, and Michael B. McElroy
Atmos. Chem. Phys., 19, 1357–1371, https://doi.org/10.5194/acp-19-1357-2019, https://doi.org/10.5194/acp-19-1357-2019, 2019
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Chemistry responsible for sulfate production in northern China winter haze remains mysterious. We propose a potentially key pathway through the reaction of formaldehyde and sulfur dioxide that has not been accounted for in previous studies. The special atmospheric conditions favor the formation and existence of their complex, hydroxymethanesulfonate (HMS).
Lu Shen, Daniel J. Jacob, Loretta J. Mickley, Yuxuan Wang, and Qiang Zhang
Atmos. Chem. Phys., 18, 17489–17496, https://doi.org/10.5194/acp-18-17489-2018, https://doi.org/10.5194/acp-18-17489-2018, 2018
Eloise A. Marais, Daniel J. Jacob, Sungyeon Choi, Joanna Joiner, Maria Belmonte-Rivas, Ronald C. Cohen, Steffen Beirle, Lee T. Murray, Luke D. Schiferl, Viral Shah, and Lyatt Jaeglé
Atmos. Chem. Phys., 18, 17017–17027, https://doi.org/10.5194/acp-18-17017-2018, https://doi.org/10.5194/acp-18-17017-2018, 2018
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We intercompare two new products of global upper tropospheric nitrogen dioxide (NO2) retrieved from the Ozone Monitoring Instrument (OMI). We evaluate these products with aircraft observations from NASA DC8 aircraft campaigns and interpret the useful information these products can provide about nitrogen oxides (NOx) in the global upper troposphere using the GEOS-Chem chemical transport model.
Jian-Xiong Sheng, Daniel J. Jacob, Joannes D. Maasakkers, Yuzhong Zhang, and Melissa P. Sulprizio
Atmos. Meas. Tech., 11, 6379–6388, https://doi.org/10.5194/amt-11-6379-2018, https://doi.org/10.5194/amt-11-6379-2018, 2018
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We conduct Observing System Simulation Experiments to compare the ability of future satellite measurements of atmospheric methane columns for constraining methane emissions at the 25 km scale. We find that the geostationary instruments can do much better than TROPOMI and are less sensitive to cloud cover. GeoCARB observing twice a day would provide 70 % of the information from the nominal GEO-CAPE mission considered by NASA in response to the Decadal Survey of the US National Research Council.
Daniel H. Cusworth, Daniel J. Jacob, Jian-Xiong Sheng, Joshua Benmergui, Alexander J. Turner, Jeremy Brandman, Laurent White, and Cynthia A. Randles
Atmos. Chem. Phys., 18, 16885–16896, https://doi.org/10.5194/acp-18-16885-2018, https://doi.org/10.5194/acp-18-16885-2018, 2018
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Methane emissions from oil/gas fields originate from a large number of small and densely clustered point sources. We examine the potential of recently launched or planned satellites to locate these high-mode emitters through measurements of atmospheric methane. We find that the recently launched TROPOMI and the planned GeoCARB instruments are successful at locating high-emitting sources for fields of 20-50 emitters within the 50 × 50 km2 geographic domain but are unsuccessful for denser fields.
Lu Hu, Christoph A. Keller, Michael S. Long, Tomás Sherwen, Benjamin Auer, Arlindo Da Silva, Jon E. Nielsen, Steven Pawson, Matthew A. Thompson, Atanas L. Trayanov, Katherine R. Travis, Stuart K. Grange, Mat J. Evans, and Daniel J. Jacob
Geosci. Model Dev., 11, 4603–4620, https://doi.org/10.5194/gmd-11-4603-2018, https://doi.org/10.5194/gmd-11-4603-2018, 2018
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We present a full-year online global simulation of tropospheric chemistry at 12.5 km resolution. To the best of our knowledge, such a resolution in a state-of-the-science global simulation of tropospheric chemistry is unprecedented. This simulation will serve as the Nature Run for observing system simulation experiments to support the future geostationary satellite constellation for tropospheric chemistry, and can also be used for various air quality applications.
Yuzhong Zhang, Daniel J. Jacob, Joannes D. Maasakkers, Melissa P. Sulprizio, Jian-Xiong Sheng, Ritesh Gautam, and John Worden
Atmos. Chem. Phys., 18, 15959–15973, https://doi.org/10.5194/acp-18-15959-2018, https://doi.org/10.5194/acp-18-15959-2018, 2018
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We assess the potential of using satellite observations of atmospheric methane to monitor global mean tropospheric OH concentration, a key parameter for the oxidizing power of the atmosphere.
Xinyi Dong, Joshua S. Fu, Qingzhao Zhu, Jian Sun, Jiani Tan, Terry Keating, Takashi Sekiya, Kengo Sudo, Louisa Emmons, Simone Tilmes, Jan Eiof Jonson, Michael Schulz, Huisheng Bian, Mian Chin, Yanko Davila, Daven Henze, Toshihiko Takemura, Anna Maria Katarina Benedictow, and Kan Huang
Atmos. Chem. Phys., 18, 15581–15600, https://doi.org/10.5194/acp-18-15581-2018, https://doi.org/10.5194/acp-18-15581-2018, 2018
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We have applied the HTAP phase II multi-model data to investigate the long-range transport impacts on surface concentration and column density of PM from Europe and Russia, Belarus, and Ukraine to eastern Asia, with a special focus on the long-range transport contribution during haze episodes in China. We found that long-range transport plays a more important role in elevating the background concentration of surface PM during the haze days.
Daniel J. Varon, Daniel J. Jacob, Jason McKeever, Dylan Jervis, Berke O. A. Durak, Yan Xia, and Yi Huang
Atmos. Meas. Tech., 11, 5673–5686, https://doi.org/10.5194/amt-11-5673-2018, https://doi.org/10.5194/amt-11-5673-2018, 2018
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Methane is a powerful greenhouse gas emitted from numerous human activities. Space-based observation of point sources would be a cost-effective monitoring solution, but the resolution of most current and planned methane-observing satellites is too coarse to resolve individual emitters. We simulate fine-resolution (50 m) satellite observations of methane plumes as would be measured by GHGSat (to be launched in 2019) and show that such data can usefully quantify large methane point sources.
Benjamin Brown-Steiner, Noelle E. Selin, Ronald Prinn, Simone Tilmes, Louisa Emmons, Jean-François Lamarque, and Philip Cameron-Smith
Geosci. Model Dev., 11, 4155–4174, https://doi.org/10.5194/gmd-11-4155-2018, https://doi.org/10.5194/gmd-11-4155-2018, 2018
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We conduct three simulations of atmospheric chemistry using chemical mechanisms of different levels of complexity and compare their results to observations. We explore situations in which the simplified mechanisms match the output of the most complex mechanism, as well as when they diverge. We investigate how concurrent utilization of chemical mechanisms of different complexities can further our atmospheric-chemistry understanding at various scales and give some strategies for future research.
Jan Eiof Jonson, Michael Schulz, Louisa Emmons, Johannes Flemming, Daven Henze, Kengo Sudo, Marianne Tronstad Lund, Meiyun Lin, Anna Benedictow, Brigitte Koffi, Frank Dentener, Terry Keating, Rigel Kivi, and Yanko Davila
Atmos. Chem. Phys., 18, 13655–13672, https://doi.org/10.5194/acp-18-13655-2018, https://doi.org/10.5194/acp-18-13655-2018, 2018
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Focusing on Europe, this HTAP 2 study computes ozone in several global models when reducing anthropogenic emissions by 20 % in different world regions. The differences in model results are explored
by use of a novel stepwise approach combining a tracer, CO and ozone. For ozone the contributions from the rest of the world are larger than from Europe, with the largest contributions from North America and eastern Asia. Contributions do, however, depend on the choice of ozone metric.
Jian-Xiong Sheng, Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Joshua Benmergui, A. Anthony Bloom, Claudia Arndt, Ritesh Gautam, Daniel Zavala-Araiza, Hartmut Boesch, and Robert J. Parker
Atmos. Chem. Phys., 18, 12257–12267, https://doi.org/10.5194/acp-18-12257-2018, https://doi.org/10.5194/acp-18-12257-2018, 2018
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Analysis of 7 years (2010–2016) of GOSAT methane trends over Canada, the contiguous US, and Mexico suggests that US methane emissions increased by 2.5 ± 1.4 % a−1 over the 7-year period, with contributions from both oil–gas systems and livestock in the Midwest. Mexican emissions show a decrease that can be attributed to a decreasing cattle population. Canadian emissions show year-to-year variability driven by wetland emissions and correlated with wetland areal extent.
Jiani Tan, Joshua S. Fu, Frank Dentener, Jian Sun, Louisa Emmons, Simone Tilmes, Johannes Flemming, Toshihiko Takemura, Huisheng Bian, Qingzhao Zhu, Cheng-En Yang, and Terry Keating
Atmos. Chem. Phys., 18, 12223–12240, https://doi.org/10.5194/acp-18-12223-2018, https://doi.org/10.5194/acp-18-12223-2018, 2018
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Have contributions of hemispheric air pollution to deposition at global scale been overlooked in the past years? How do we assess the critical load for the acid deposition when we look for the demand of forest and crop? This study highlights the significant impact of hemispheric transport on deposition in coastal regions, open ocean and low-emission regions. Further research is proposed for improving ecosystem and human health in these regions, with regards to the enhanced hemispheric transport.
Prasad Kasibhatla, Tomás Sherwen, Mathew J. Evans, Lucy J. Carpenter, Chris Reed, Becky Alexander, Qianjie Chen, Melissa P. Sulprizio, James D. Lee, Katie A. Read, William Bloss, Leigh R. Crilley, William C. Keene, Alexander A. P. Pszenny, and Alma Hodzic
Atmos. Chem. Phys., 18, 11185–11203, https://doi.org/10.5194/acp-18-11185-2018, https://doi.org/10.5194/acp-18-11185-2018, 2018
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Recent measurements of NOx and HONO suggest that photolysis of particulate nitrate in sea-salt aerosols is important in terms of marine boundary layer oxidant chemistry. We present the first global-scale assessment of the significance of this new chemical pathway for NOx, O3, and OH in the marine boundary layer. We also present a preliminary assessment of the potential impact of photolysis of particulate nitrate associated with other aerosol types on continental boundary layer chemistry.
Sebastian D. Eastham, Michael S. Long, Christoph A. Keller, Elizabeth Lundgren, Robert M. Yantosca, Jiawei Zhuang, Chi Li, Colin J. Lee, Matthew Yannetti, Benjamin M. Auer, Thomas L. Clune, Jules Kouatchou, William M. Putman, Matthew A. Thompson, Atanas L. Trayanov, Andrea M. Molod, Randall V. Martin, and Daniel J. Jacob
Geosci. Model Dev., 11, 2941–2953, https://doi.org/10.5194/gmd-11-2941-2018, https://doi.org/10.5194/gmd-11-2941-2018, 2018
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Global atmospheric chemical transport models are crucial tools in atmospheric science, used to address problems ranging from climate change to acid rain. GEOS-Chem High Performance (GCHP) is a new implementation of the widely used GEOS-Chem model, designed for massively parallel architectures. GCHP v11-02c is shown to be highly scalable from 6 to over 500 cores, enabling the routine simulation of global atmospheric chemistry from the surface to the stratopause at resolutions of ~50 km or finer.
Ciao-Kai Liang, J. Jason West, Raquel A. Silva, Huisheng Bian, Mian Chin, Yanko Davila, Frank J. Dentener, Louisa Emmons, Johannes Flemming, Gerd Folberth, Daven Henze, Ulas Im, Jan Eiof Jonson, Terry J. Keating, Tom Kucsera, Allen Lenzen, Meiyun Lin, Marianne Tronstad Lund, Xiaohua Pan, Rokjin J. Park, R. Bradley Pierce, Takashi Sekiya, Kengo Sudo, and Toshihiko Takemura
Atmos. Chem. Phys., 18, 10497–10520, https://doi.org/10.5194/acp-18-10497-2018, https://doi.org/10.5194/acp-18-10497-2018, 2018
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Emissions from one continent affect air quality and health elsewhere. Here we quantify the effects of intercontinental PM2.5 and ozone transport on human health using a new multi-model ensemble, evaluating the health effects of emissions from six world regions and three emission source sectors. Emissions from one region have significant health impacts outside of that source region; similarly, foreign emissions contribute significantly to air-pollution-related deaths in several world regions.
Steven T. Turnock, Oliver Wild, Frank J. Dentener, Yanko Davila, Louisa K. Emmons, Johannes Flemming, Gerd A. Folberth, Daven K. Henze, Jan E. Jonson, Terry J. Keating, Sudo Kengo, Meiyun Lin, Marianne Lund, Simone Tilmes, and Fiona M. O'Connor
Atmos. Chem. Phys., 18, 8953–8978, https://doi.org/10.5194/acp-18-8953-2018, https://doi.org/10.5194/acp-18-8953-2018, 2018
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A simple parameterisation was developed in this study to provide a rapid assessment of the impacts and uncertainties associated with future emission control strategies by predicting changes to surface ozone air quality and near-term climate forcing of ozone. Future emissions scenarios based on currently implemented legislation are shown to worsen surface ozone air quality and enhance near-term climate warming, with changes in methane becoming increasingly important in the future.
Benjamin Brown-Steiner, Noelle E. Selin, Ronald G. Prinn, Erwan Monier, Simone Tilmes, Louisa Emmons, and Fernando Garcia-Menendez
Atmos. Chem. Phys., 18, 8373–8388, https://doi.org/10.5194/acp-18-8373-2018, https://doi.org/10.5194/acp-18-8373-2018, 2018
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Detecting signals in observations and simulations of atmospheric chemistry is difficult due to the underlying variability in the chemistry, meteorology, and climatology. Here we examine the scale dependence of ozone variability and explore strategies for reducing or averaging this variability and thereby enhancing ozone signal detection capabilities. We find that 10–15 years of temporal averaging, and some level of spatial averaging, reduces the risk of overconfidence in ozone signals.
Alexander J. Turner, Daniel J. Jacob, Joshua Benmergui, Jeremy Brandman, Laurent White, and Cynthia A. Randles
Atmos. Chem. Phys., 18, 8265–8278, https://doi.org/10.5194/acp-18-8265-2018, https://doi.org/10.5194/acp-18-8265-2018, 2018
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We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 km spatial resolution and hourly temporal resolution over the Barnett Shale. We find that a week of TROPOMI observations should provide regional (~30 km) information on temporally invariant sources and GeoCARB should provide information on temporally invariant sources at 2–7 km spatial resolution. An instrument precision better than 6 ppb is an important threshold for achieving fine resolution of emissions.
Jiani Tan, Joshua S. Fu, Frank Dentener, Jian Sun, Louisa Emmons, Simone Tilmes, Kengo Sudo, Johannes Flemming, Jan Eiof Jonson, Sylvie Gravel, Huisheng Bian, Yanko Davila, Daven K. Henze, Marianne T. Lund, Tom Kucsera, Toshihiko Takemura, and Terry Keating
Atmos. Chem. Phys., 18, 6847–6866, https://doi.org/10.5194/acp-18-6847-2018, https://doi.org/10.5194/acp-18-6847-2018, 2018
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We study the distributions of sulfur and nitrogen deposition, which are associated with current environmental issues such as formation of acid rain and ecosystem eutrophication and result in widespread problems such as loss of environmental diversity, harming the crop yield and even food insecurity. According to our study, both the amount and distribution of sulfate and nitrogen deposition have changed significantly in the last decade, particularly in East Asia, South Asia and Southeast Asia.
Jian-Xiong Sheng, Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Melissa P. Sulprizio, A. Anthony Bloom, Arlyn E. Andrews, and Debra Wunch
Atmos. Chem. Phys., 18, 6483–6491, https://doi.org/10.5194/acp-18-6483-2018, https://doi.org/10.5194/acp-18-6483-2018, 2018
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We use observations of boundary layer methane from the SEAC4RS aircraft campaign over the Southeast US to estimate methane emissions in that region. Our results suggest that the EPA inventory is regionally unbiased but there are large local biases, suggesting variable emission factors. Our results also suggest that the choice of landcover map is the dominant source of error for wetland emission estimates.
Jiawei Zhuang, Daniel J. Jacob, and Sebastian D. Eastham
Atmos. Chem. Phys., 18, 6039–6055, https://doi.org/10.5194/acp-18-6039-2018, https://doi.org/10.5194/acp-18-6039-2018, 2018
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Our work explains why current model simulations are unable to capture the intercontinental influences of pollution plumes that are often observed over some regions like California. Due to inadequate vertical grid resolution in these models, the plumes get diffused too rapidly during intercontinental transport. Increasing the vertical grid resolution greatly improves the simulation of plumes and considerably increases the estimate of local surface pollution influence.
Jennifer Kaiser, Daniel J. Jacob, Lei Zhu, Katherine R. Travis, Jenny A. Fisher, Gonzalo González Abad, Lin Zhang, Xuesong Zhang, Alan Fried, John D. Crounse, Jason M. St. Clair, and Armin Wisthaler
Atmos. Chem. Phys., 18, 5483–5497, https://doi.org/10.5194/acp-18-5483-2018, https://doi.org/10.5194/acp-18-5483-2018, 2018
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Isoprene emissions from vegetation have a large effect on atmospheric chemistry and air quality. Here we use the adjoint of GEOS-Chem in an inversion of OMI formaldehyde observations to produce top-down estimates of isoprene emissions in the southeast US during the summer of 2013. We find that MEGAN v2.1 is biased high on average by 40 %. Our downward correction of isoprene emissions leads to a small reduction in modeled surface O3 and decreases the contribution of isoprene to organic aerosol.
Karen Yu, Christoph A. Keller, Daniel J. Jacob, Andrea M. Molod, Sebastian D. Eastham, and Michael S. Long
Geosci. Model Dev., 11, 305–319, https://doi.org/10.5194/gmd-11-305-2018, https://doi.org/10.5194/gmd-11-305-2018, 2018
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Global simulations of atmospheric chemistry are generally conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it is unable to reproduce the GCM transport exactly. We investigate the cascade of errors associated with the off-line approach using the GEOS-5 GCM and GEOS-Chem CTM and discuss improvements in the use of archived meteorology.
Theodore K. Koenig, Rainer Volkamer, Sunil Baidar, Barbara Dix, Siyuan Wang, Daniel C. Anderson, Ross J. Salawitch, Pamela A. Wales, Carlos A. Cuevas, Rafael P. Fernandez, Alfonso Saiz-Lopez, Mathew J. Evans, Tomás Sherwen, Daniel J. Jacob, Johan Schmidt, Douglas Kinnison, Jean-François Lamarque, Eric C. Apel, James C. Bresch, Teresa Campos, Frank M. Flocke, Samuel R. Hall, Shawn B. Honomichl, Rebecca Hornbrook, Jørgen B. Jensen, Richard Lueb, Denise D. Montzka, Laura L. Pan, J. Michael Reeves, Sue M. Schauffler, Kirk Ullmann, Andrew J. Weinheimer, Elliot L. Atlas, Valeria Donets, Maria A. Navarro, Daniel Riemer, Nicola J. Blake, Dexian Chen, L. Gregory Huey, David J. Tanner, Thomas F. Hanisco, and Glenn M. Wolfe
Atmos. Chem. Phys., 17, 15245–15270, https://doi.org/10.5194/acp-17-15245-2017, https://doi.org/10.5194/acp-17-15245-2017, 2017
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Tropospheric inorganic bromine (BrO and Bry) shows a C-shaped profile over the tropical western Pacific Ocean, and supports previous speculation that marine convection is a source for inorganic bromine from sea salt to the upper troposphere. The Bry profile in the tropical tropopause layer (TTL) is complex, suggesting that the total Bry budget in the TTL is not closed without considering aerosol bromide. The implications for atmospheric composition and bromine sources are discussed.
Youhua Tang, Mariusz Pagowski, Tianfeng Chai, Li Pan, Pius Lee, Barry Baker, Rajesh Kumar, Luca Delle Monache, Daniel Tong, and Hyun-Cheol Kim
Geosci. Model Dev., 10, 4743–4758, https://doi.org/10.5194/gmd-10-4743-2017, https://doi.org/10.5194/gmd-10-4743-2017, 2017
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In order to evaluate the data assimilation tools for regional real-time PM2.5 forecasts, we applied a 3D-Var assimilation tool to adjust the aerosol initial condition by assimilating satellite-retrieved aerosol optical depth and surface PM2.5 observations for a regional air quality model, which is compared to another assimilation method, optimal interpolation. We discuss the pros and cons of these two assimilation methods based on the comparison of their 1-month four-cycles-per-day runs.
Li Pan, Hyun Cheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-207, https://doi.org/10.5194/gmd-2017-207, 2017
Revised manuscript not accepted
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In this study, a system accounting for fire emissions in a chemical transport model is described. The focus of this work is to qualitatively evaluate the system's capability to capture fire signals identified by multiple observation data sets. We discuss how to use observational data correctly to filter out fire signals and synergistic use of multiple data sets together. We also address the limitations of each of the observation data sets and of the evaluation methods.
Jihyun Han, Meehye Lee, Xiaona Shang, Gangwoong Lee, and Louisa K. Emmons
Atmos. Chem. Phys., 17, 10619–10631, https://doi.org/10.5194/acp-17-10619-2017, https://doi.org/10.5194/acp-17-10619-2017, 2017
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Peroxyacetyl nitrate (PAN) was first measured at Gosan Climate Observatory during the fall of 2010, when PAN was better correlated with PM10 than with O3. In particular, PAN and O3 concentrations were greatly elevated in haze and the Beijing plume and much higher than those from model simulation. This study highlights the decoupling of PAN from O3 in Chinese outflows and suggests PAN as a potential indicator of overall aerosol formation in aged air masses impacted by biomass burning.
Katherine R. Travis, Daniel J. Jacob, Christoph A. Keller, Shi Kuang, Jintai Lin, Michael J. Newchurch, and Anne M. Thompson
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-596, https://doi.org/10.5194/acp-2017-596, 2017
Preprint retracted
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Models severely overestimate surface ozone in the Southeast US during summertime which has implications for the design of air quality regulations. We use a model (GEOS-Chem) to interpret ozone observations from a suite of observations taken during August–September 2013. The model is unbiased relative to observations below 1 km but is biased high at the surface. We attribute this bias to model representation error, an underestimate in low-cloud, and insufficient treatment of vertical mixing.
Christopher Chan Miller, Daniel J. Jacob, Eloise A. Marais, Karen Yu, Katherine R. Travis, Patrick S. Kim, Jenny A. Fisher, Lei Zhu, Glenn M. Wolfe, Thomas F. Hanisco, Frank N. Keutsch, Jennifer Kaiser, Kyung-Eun Min, Steven S. Brown, Rebecca A. Washenfelder, Gonzalo González Abad, and Kelly Chance
Atmos. Chem. Phys., 17, 8725–8738, https://doi.org/10.5194/acp-17-8725-2017, https://doi.org/10.5194/acp-17-8725-2017, 2017
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The use of satellite glyoxal observations for estimating isoprene emissions has been limited by knowledge of the glyoxal yield from isoprene. We use SENEX aircraft observations over the southeast US to evaluate glyoxal yields from isoprene in a 3-D atmospheric model. The SENEX observations support a pathway for glyoxal formation in pristine regions that we propose here, which may have implications for improving isoprene emissions estimates from upcoming high-resolution geostationary satellites.
A. Anthony Bloom, Kevin W. Bowman, Meemong Lee, Alexander J. Turner, Ronny Schroeder, John R. Worden, Richard Weidner, Kyle C. McDonald, and Daniel J. Jacob
Geosci. Model Dev., 10, 2141–2156, https://doi.org/10.5194/gmd-10-2141-2017, https://doi.org/10.5194/gmd-10-2141-2017, 2017
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Wetland emissions are a principal source of uncertainty in the global atmospheric methane budget due to poor knowledge of wetland processes. We construct a wetland methane emission and uncertainty dataset for use in global atmospheric methane models. Our wetland model ensemble is based on static wetland maps, satellite-derived inundation and carbon cycle models. The ensemble performs favourably against regional flux estimates and atmospheric methane measurements relative to previous studies.
Hannah M. Horowitz, Daniel J. Jacob, Yanxu Zhang, Theodore S. Dibble, Franz Slemr, Helen M. Amos, Johan A. Schmidt, Elizabeth S. Corbitt, Eloïse A. Marais, and Elsie M. Sunderland
Atmos. Chem. Phys., 17, 6353–6371, https://doi.org/10.5194/acp-17-6353-2017, https://doi.org/10.5194/acp-17-6353-2017, 2017
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Mercury is a toxic, global pollutant released to the air from human activities like coal burning. Chemical reactions in air determine how far mercury is transported before it is deposited to the environment, where it may be converted to a form that accumulates in fish. We use a 3-D atmospheric model to evaluate a new set of chemical reactions and its effects on mercury deposition. We find it is consistent with observations and leads to increased deposition to oceans, especially in the tropics.
Min Huang, Gregory R. Carmichael, R. Bradley Pierce, Duseong S. Jo, Rokjin J. Park, Johannes Flemming, Louisa K. Emmons, Kevin W. Bowman, Daven K. Henze, Yanko Davila, Kengo Sudo, Jan Eiof Jonson, Marianne Tronstad Lund, Greet Janssens-Maenhout, Frank J. Dentener, Terry J. Keating, Hilke Oetjen, and Vivienne H. Payne
Atmos. Chem. Phys., 17, 5721–5750, https://doi.org/10.5194/acp-17-5721-2017, https://doi.org/10.5194/acp-17-5721-2017, 2017
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In support of the HTAP phase 2 experiment, we conducted a number of regional-scale Sulfur Transport and dEposition Model base and sensitivity simulations over North America during May–June 2010. The STEM chemical boundary conditions were downscaled from three (GEOS-Chem, RAQMS, and ECMWF C-IFS) global chemical transport models' simulations. Analyses were performed on large spatial–temporal scales relative to HTAP1 and also on subcontinental and event scales including the use of satellite data.
Rachel F. Silvern, Daniel J. Jacob, Patrick S. Kim, Eloise A. Marais, Jay R. Turner, Pedro Campuzano-Jost, and Jose L. Jimenez
Atmos. Chem. Phys., 17, 5107–5118, https://doi.org/10.5194/acp-17-5107-2017, https://doi.org/10.5194/acp-17-5107-2017, 2017
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We identify a fundamental discrepancy between thermodynamic equilibrium theory and observations of inorganic aerosol composition in the eastern US in summer that shows low ammonium sulfate aerosol ratios. In addition, from 2003 to 2013, while SO2 emissions have declined due to US emission controls, aerosols have become more acidic in the southeastern US. To explain these observations, we suggest that the large and increasing source of organic aerosol may be affecting thermodynamic equilibrium.
Sebastian D. Eastham and Daniel J. Jacob
Atmos. Chem. Phys., 17, 2543–2553, https://doi.org/10.5194/acp-17-2543-2017, https://doi.org/10.5194/acp-17-2543-2017, 2017
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Intercontinental atmospheric transport can disrupt local chemistry and cause air quality issues thousands of kilometers from the source, complicating correct attribution of air quality exceedances. This transport occurs in long, thin plumes which current-generation models consistently fail to reproduce. Our study investigates the cause of this failure, finding that greater vertical resolution than is currently available is required to reliably resolve the plumes and their effects.
Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Jianxiong Sheng, Kang Sun, Xiong Liu, Kelly Chance, Ilse Aben, Jason McKeever, and Christian Frankenberg
Atmos. Chem. Phys., 16, 14371–14396, https://doi.org/10.5194/acp-16-14371-2016, https://doi.org/10.5194/acp-16-14371-2016, 2016
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Methane is a greenhouse gas emitted by a range of natural and anthropogenic sources. Atmospheric methane has been measured continuously from space since 2003, and new instruments are planned to launch in the near future that will greatly expand the capabilities of space-based observations. We review the value of current, future, and proposed satellite observations to better quantify methane emissions from the global scale down to the scale of point sources.
Lei Zhu, Daniel J. Jacob, Patrick S. Kim, Jenny A. Fisher, Karen Yu, Katherine R. Travis, Loretta J. Mickley, Robert M. Yantosca, Melissa P. Sulprizio, Isabelle De Smedt, Gonzalo González Abad, Kelly Chance, Can Li, Richard Ferrare, Alan Fried, Johnathan W. Hair, Thomas F. Hanisco, Dirk Richter, Amy Jo Scarino, James Walega, Petter Weibring, and Glenn M. Wolfe
Atmos. Chem. Phys., 16, 13477–13490, https://doi.org/10.5194/acp-16-13477-2016, https://doi.org/10.5194/acp-16-13477-2016, 2016
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HCHO column data are widely used as a proxy for VOCs emissions, but validation of the data has been extremely limited. We use accurate aircraft observations to validate and intercompare 6 HCHO retrievals with GEOS-Chem as the intercomparison platform. Retrievals are interconsistent in spatial variability over the SE US and in daily variability, but are biased low by 20–51 %. Our work supports the use of HCHO column as a quantitative proxy for isoprene emission after correction of the low bias.
Katherine R. Travis, Daniel J. Jacob, Jenny A. Fisher, Patrick S. Kim, Eloise A. Marais, Lei Zhu, Karen Yu, Christopher C. Miller, Robert M. Yantosca, Melissa P. Sulprizio, Anne M. Thompson, Paul O. Wennberg, John D. Crounse, Jason M. St. Clair, Ronald C. Cohen, Joshua L. Laughner, Jack E. Dibb, Samuel R. Hall, Kirk Ullmann, Glenn M. Wolfe, Illana B. Pollack, Jeff Peischl, Jonathan A. Neuman, and Xianliang Zhou
Atmos. Chem. Phys., 16, 13561–13577, https://doi.org/10.5194/acp-16-13561-2016, https://doi.org/10.5194/acp-16-13561-2016, 2016
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Ground-level ozone pollution in the Southeast US involves complex chemistry driven by anthropogenic emissions of nitrogen oxides (NOx) and biogenic emissions of isoprene. We find that US NOx emissions are overestimated nationally by as much as 50 % and that reducing model emissions by this amount results in good agreement with SEAC4RS aircraft measurements in August and September 2013. Observations of nitrate wet deposition fluxes and satellite NO2 columns further support this result.
Camilla Weum Stjern, Bjørn Hallvard Samset, Gunnar Myhre, Huisheng Bian, Mian Chin, Yanko Davila, Frank Dentener, Louisa Emmons, Johannes Flemming, Amund Søvde Haslerud, Daven Henze, Jan Eiof Jonson, Tom Kucsera, Marianne Tronstad Lund, Michael Schulz, Kengo Sudo, Toshihiko Takemura, and Simone Tilmes
Atmos. Chem. Phys., 16, 13579–13599, https://doi.org/10.5194/acp-16-13579-2016, https://doi.org/10.5194/acp-16-13579-2016, 2016
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Air pollution can reach distant regions through intercontinental transport. Here we first present results from the Hemispheric Transport of Air Pollution Phase 2 exercise, where many models performed the same set of coordinated emission-reduction experiments. We find that mitigations have considerable extra-regional effects, and show that this is particularly true for black carbon emissions, as long-range transport elevates aerosols to higher levels where their radiative influence is stronger.
Tomás Sherwen, Johan A. Schmidt, Mat J. Evans, Lucy J. Carpenter, Katja Großmann, Sebastian D. Eastham, Daniel J. Jacob, Barbara Dix, Theodore K. Koenig, Roman Sinreich, Ivan Ortega, Rainer Volkamer, Alfonso Saiz-Lopez, Cristina Prados-Roman, Anoop S. Mahajan, and Carlos Ordóñez
Atmos. Chem. Phys., 16, 12239–12271, https://doi.org/10.5194/acp-16-12239-2016, https://doi.org/10.5194/acp-16-12239-2016, 2016
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We present a simulation of tropospheric Cl, Br, I chemistry within the GEOS-Chem CTM. We find a decrease in tropospheric ozone burden of 18.6 % and a 8.2 % decrease in global mean OH concentrations. Cl oxidation of some VOCs range from 15 to 27 % of the total loss. Bromine plays a small role in oxidising oVOCs. Surface ozone, ozone sondes, and methane lifetime are in general improved by the inclusion of halogens. We argue that simulated bromine and chlorine represent a lower limit.
Sarah A. Strode, Helen M. Worden, Megan Damon, Anne R. Douglass, Bryan N. Duncan, Louisa K. Emmons, Jean-Francois Lamarque, Michael Manyin, Luke D. Oman, Jose M. Rodriguez, Susan E. Strahan, and Simone Tilmes
Atmos. Chem. Phys., 16, 7285–7294, https://doi.org/10.5194/acp-16-7285-2016, https://doi.org/10.5194/acp-16-7285-2016, 2016
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We use global models to interpret trends in MOPITT observations of CO. Simulations with time-dependent emissions reproduce the observed trends over the eastern USA and Europe, suggesting that the emissions are reasonable for these regions. The simulations produce a positive trend over eastern China, contrary to the observed negative trend. This may indicate that the assumed emission trend over China is too positive. However, large variability in the overhead ozone column also contributes.
Simone Tilmes, Jean-Francois Lamarque, Louisa K. Emmons, Doug E. Kinnison, Dan Marsh, Rolando R. Garcia, Anne K. Smith, Ryan R. Neely, Andrew Conley, Francis Vitt, Maria Val Martin, Hiroshi Tanimoto, Isobel Simpson, Don R. Blake, and Nicola Blake
Geosci. Model Dev., 9, 1853–1890, https://doi.org/10.5194/gmd-9-1853-2016, https://doi.org/10.5194/gmd-9-1853-2016, 2016
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The state of the art Community Earth System Model, CESM1 CAM4-chem has been used to perform reference and sensitivity simulations as part of the Chemistry Climate Model Initiative (CCMI). Specifics of the model and details regarding the setup of the simulations are described. In additions, the main behavior of the model, including selected chemical species have been evaluated with climatological datasets. This paper is therefore a references for studies that use the provided model results.
Jenny A. Fisher, Daniel J. Jacob, Katherine R. Travis, Patrick S. Kim, Eloise A. Marais, Christopher Chan Miller, Karen Yu, Lei Zhu, Robert M. Yantosca, Melissa P. Sulprizio, Jingqiu Mao, Paul O. Wennberg, John D. Crounse, Alex P. Teng, Tran B. Nguyen, Jason M. St. Clair, Ronald C. Cohen, Paul Romer, Benjamin A. Nault, Paul J. Wooldridge, Jose L. Jimenez, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Paul B. Shepson, Fulizi Xiong, Donald R. Blake, Allen H. Goldstein, Pawel K. Misztal, Thomas F. Hanisco, Glenn M. Wolfe, Thomas B. Ryerson, Armin Wisthaler, and Tomas Mikoviny
Atmos. Chem. Phys., 16, 5969–5991, https://doi.org/10.5194/acp-16-5969-2016, https://doi.org/10.5194/acp-16-5969-2016, 2016
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We use new airborne and ground-based observations from two summer 2013 campaigns in the southeastern US, interpreted with a chemical transport model, to understand the impact of isoprene and monoterpene chemistry on the atmospheric NOx budget via production of organic nitrates (RONO2). We find that a diversity of species contribute to observed RONO2. Our work implies that the NOx sink to RONO2 production is only sensitive to NOx emissions in regions where they are already low.
Catherine Wespes, Daniel Hurtmans, Louisa K. Emmons, Sarah Safieddine, Cathy Clerbaux, David P. Edwards, and Pierre-François Coheur
Atmos. Chem. Phys., 16, 5721–5743, https://doi.org/10.5194/acp-16-5721-2016, https://doi.org/10.5194/acp-16-5721-2016, 2016
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In this paper, we assess how daily ozone measurements from the Infrared Atmospheric Sounding Interferometer (IASI/MetOp) can contribute to the analyses of the processes driving O3 variability in the troposphere and the stratosphere with a set of parameterized geophysical variables, and we demonstrate the added value of IASI exceptional frequency sampling for monitoring medium- to long-term changes in global ozone concentrations in the future.
Christopher Chan Miller, Daniel J. Jacob, Gonzalo González Abad, and Kelly Chance
Atmos. Chem. Phys., 16, 4631–4639, https://doi.org/10.5194/acp-16-4631-2016, https://doi.org/10.5194/acp-16-4631-2016, 2016
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Volatile organic compounds (VOCs) are important precursors for photochemical smog.
Glyoxal is an organic compound produced in the atmosphere from reactions of larger VOCs. OMI satellite observations of glyoxal show a large hotspot over the Pearl River delta. The hotspot can be explained by industrial paint and solvent emissions of aromatic VOCs. Our work shows OMI observations are consistent with current VOC emissions estimates, whereas previous work has suggested large underestimates.
Karen Yu, Daniel J. Jacob, Jenny A. Fisher, Patrick S. Kim, Eloise A. Marais, Christopher C. Miller, Katherine R. Travis, Lei Zhu, Robert M. Yantosca, Melissa P. Sulprizio, Ron C. Cohen, Jack E. Dibb, Alan Fried, Tomas Mikoviny, Thomas B. Ryerson, Paul O. Wennberg, and Armin Wisthaler
Atmos. Chem. Phys., 16, 4369–4378, https://doi.org/10.5194/acp-16-4369-2016, https://doi.org/10.5194/acp-16-4369-2016, 2016
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Increasing the spatial resolution of a chemical transport model may improve simulations but can be computationally expensive. Using observations from the SEAC4RS aircraft campaign, we find that at higher spatial resolutions, models are better able to simulate the chemical pathways of ozone precursors, but the overall effect on regional mean concentrations is small. This implies that for continental boundary layer applications, coarse resolution models are adequate.
E. A. Marais, D. J. Jacob, J. L. Jimenez, P. Campuzano-Jost, D. A. Day, W. Hu, J. Krechmer, L. Zhu, P. S. Kim, C. C. Miller, J. A. Fisher, K. Travis, K. Yu, T. F. Hanisco, G. M. Wolfe, H. L. Arkinson, H. O. T. Pye, K. D. Froyd, J. Liao, and V. F. McNeill
Atmos. Chem. Phys., 16, 1603–1618, https://doi.org/10.5194/acp-16-1603-2016, https://doi.org/10.5194/acp-16-1603-2016, 2016
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Isoprene secondary organic aerosol (SOA) is a dominant aerosol component in the southeast US, but models routinely underestimate isoprene SOA with traditional schemes based on chamber studies operated under conditions not representative of isoprene-emitting forests. We develop a new irreversible uptake mechanism to reproduce isoprene SOA yields (3.3 %) and composition, and find a factor of 2 co-benefit of SO2 emission controls on reducing sulfate and organic aerosol in the southeast US.
H.-M. Lee, F. Paulot, D. K. Henze, K. Travis, D. J. Jacob, L. H. Pardo, and B. A. Schichtel
Atmos. Chem. Phys., 16, 525–540, https://doi.org/10.5194/acp-16-525-2016, https://doi.org/10.5194/acp-16-525-2016, 2016
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Sources of nitrogen deposition (Ndep) in Federal Class I areas in the US are investigated, identifying unique features in contributions from different species, sectors and locations. Ndep in many parks is impacted by emissions several hundred km away; the role of oxidized vs reduced sources varies regionally. Emissions reductions in the western US most effectively reduce the extent of areas in critical load exceedance, while reductions in the east most effectively reduce exceedance magnitudes.
J. He, Y. Zhang, S. Tilmes, L. Emmons, J.-F. Lamarque, T. Glotfelty, A. Hodzic, and F. Vitt
Geosci. Model Dev., 8, 3999–4025, https://doi.org/10.5194/gmd-8-3999-2015, https://doi.org/10.5194/gmd-8-3999-2015, 2015
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The global simulations with CB05_GE and MOZART-4x predict similar chemical profiles for major gases compared to aircraft measurements, with better agreement for the NOy profile by CB05_GE. The SOA concentrations of SOA at four sites in CONUS and organic carbon over the IMPROVE sites are better predicted by MOZART-4x. The two simulations result in a global average difference of 0.5W m-2 in simulated shortwave cloud radiative forcing, with up to 13.6W m-2 over subtropical regions.
Y. Zheng, N. Unger, A. Hodzic, L. Emmons, C. Knote, S. Tilmes, J.-F. Lamarque, and P. Yu
Atmos. Chem. Phys., 15, 13487–13506, https://doi.org/10.5194/acp-15-13487-2015, https://doi.org/10.5194/acp-15-13487-2015, 2015
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Nitrogen oxides (NOx) play an important but complex role in secondary organic aerosol (SOA) formation. In this study we update the SOA scheme in a global 3-D chemistry-climate model by implementing a 4-product volatility basis set (VBS) framework with NOx-dependent yields and simplified aging parameterizations. We find that the SOA decrease in response to a 50% reduction in anthropogenic NOx emissions is limited due to the buffering in different chemical pathways.
P. S. Kim, D. J. Jacob, J. A. Fisher, K. Travis, K. Yu, L. Zhu, R. M. Yantosca, M. P. Sulprizio, J. L. Jimenez, P. Campuzano-Jost, K. D. Froyd, J. Liao, J. W. Hair, M. A. Fenn, C. F. Butler, N. L. Wagner, T. D. Gordon, A. Welti, P. O. Wennberg, J. D. Crounse, J. M. St. Clair, A. P. Teng, D. B. Millet, J. P. Schwarz, M. Z. Markovic, and A. E. Perring
Atmos. Chem. Phys., 15, 10411–10433, https://doi.org/10.5194/acp-15-10411-2015, https://doi.org/10.5194/acp-15-10411-2015, 2015
J. Kaiser, G. M. Wolfe, K. E. Min, S. S. Brown, C. C. Miller, D. J. Jacob, J. A. deGouw, M. Graus, T. F. Hanisco, J. Holloway, J. Peischl, I. B. Pollack, T. B. Ryerson, C. Warneke, R. A. Washenfelder, and F. N. Keutsch
Atmos. Chem. Phys., 15, 7571–7583, https://doi.org/10.5194/acp-15-7571-2015, https://doi.org/10.5194/acp-15-7571-2015, 2015
G. Zeng, J. E. Williams, J. A. Fisher, L. K. Emmons, N. B. Jones, O. Morgenstern, J. Robinson, D. Smale, C. Paton-Walsh, and D. W. T. Griffith
Atmos. Chem. Phys., 15, 7217–7245, https://doi.org/10.5194/acp-15-7217-2015, https://doi.org/10.5194/acp-15-7217-2015, 2015
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We assess the impact of biogenic emissions on CO and HCHO in the Southern Hemisphere (SH), with simulations using different emission inventories. Differences in biogenic emissions result in large differences on modelled CO in the source and the remote regions. Substantial inter-model differences exist. Models significantly underestimate observed HCHO columns in the SH, suggesting missing sources in the models. Differences in the CO/OH/CH4 chemistry lead to differences in HCHO in remote regions.
A. J. Turner and D. J. Jacob
Atmos. Chem. Phys., 15, 7039–7048, https://doi.org/10.5194/acp-15-7039-2015, https://doi.org/10.5194/acp-15-7039-2015, 2015
A. J. Turner, D. J. Jacob, K. J. Wecht, J. D. Maasakkers, E. Lundgren, A. E. Andrews, S. C. Biraud, H. Boesch, K. W. Bowman, N. M. Deutscher, M. K. Dubey, D. W. T. Griffith, F. Hase, A. Kuze, J. Notholt, H. Ohyama, R. Parker, V. H. Payne, R. Sussmann, C. Sweeney, V. A. Velazco, T. Warneke, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 15, 7049–7069, https://doi.org/10.5194/acp-15-7049-2015, https://doi.org/10.5194/acp-15-7049-2015, 2015
L. K. Emmons, S. R. Arnold, S. A. Monks, V. Huijnen, S. Tilmes, K. S. Law, J. L. Thomas, J.-C. Raut, I. Bouarar, S. Turquety, Y. Long, B. Duncan, S. Steenrod, S. Strode, J. Flemming, J. Mao, J. Langner, A. M. Thompson, D. Tarasick, E. C. Apel, D. R. Blake, R. C. Cohen, J. Dibb, G. S. Diskin, A. Fried, S. R. Hall, L. G. Huey, A. J. Weinheimer, A. Wisthaler, T. Mikoviny, J. Nowak, J. Peischl, J. M. Roberts, T. Ryerson, C. Warneke, and D. Helmig
Atmos. Chem. Phys., 15, 6721–6744, https://doi.org/10.5194/acp-15-6721-2015, https://doi.org/10.5194/acp-15-6721-2015, 2015
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Eleven 3-D tropospheric chemistry models have been compared and evaluated with observations in the Arctic during the International Polar Year (IPY 2008). Large differences are seen among the models, particularly related to the model chemistry of volatile organic compounds (VOCs) and reactive nitrogen (NOx, PAN, HNO3) partitioning. Consistency among the models in the underestimation of CO, ethane and propane indicates the emission inventory is too low for these compounds.
S. R. Arnold, L. K. Emmons, S. A. Monks, K. S. Law, D. A. Ridley, S. Turquety, S. Tilmes, J. L. Thomas, I. Bouarar, J. Flemming, V. Huijnen, J. Mao, B. N. Duncan, S. Steenrod, Y. Yoshida, J. Langner, and Y. Long
Atmos. Chem. Phys., 15, 6047–6068, https://doi.org/10.5194/acp-15-6047-2015, https://doi.org/10.5194/acp-15-6047-2015, 2015
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The extent to which forest fires produce the air pollutant and greenhouse gas ozone (O3) in the atmosphere at high latitudes in not well understood. We have compared how fire emissions produce O3 and its precursors in several models of atmospheric chemistry. We find enhancements in O3 in air dominated by fires in all models, which increase on average as fire emissions age. We also find that in situ O3 production in the Arctic is sensitive to details of organic chemistry and vertical lifting.
S. Tilmes, J.-F. Lamarque, L. K. Emmons, D. E. Kinnison, P.-L. Ma, X. Liu, S. Ghan, C. Bardeen, S. Arnold, M. Deeter, F. Vitt, T. Ryerson, J. W. Elkins, F. Moore, J. R. Spackman, and M. Val Martin
Geosci. Model Dev., 8, 1395–1426, https://doi.org/10.5194/gmd-8-1395-2015, https://doi.org/10.5194/gmd-8-1395-2015, 2015
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The Community Atmosphere Model (CAM), version 5, is now coupled to extensive tropospheric and stratospheric chemistry, called CAM5-chem, and is available in addition to CAM4-chem in the Community Earth System Model (CESM) version 1.2. Both configurations are well suited as tools for atmospheric chemistry modeling studies in the troposphere and lower stratosphere.
S. A. Monks, S. R. Arnold, L. K. Emmons, K. S. Law, S. Turquety, B. N. Duncan, J. Flemming, V. Huijnen, S. Tilmes, J. Langner, J. Mao, Y. Long, J. L. Thomas, S. D. Steenrod, J. C. Raut, C. Wilson, M. P. Chipperfield, G. S. Diskin, A. Weinheimer, H. Schlager, and G. Ancellet
Atmos. Chem. Phys., 15, 3575–3603, https://doi.org/10.5194/acp-15-3575-2015, https://doi.org/10.5194/acp-15-3575-2015, 2015
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Multi-model simulations of Arctic CO, O3 and OH are evaluated using observations. Models show highly variable concentrations but the relative importance of emission regions and types is robust across the models, demonstrating the importance of biomass burning as a source. Idealised tracer experiments suggest that some of the model spread is due to variations in simulated transport from Europe in winter and from Asia throughout the year.
J. A. Fisher, S. R. Wilson, G. Zeng, J. E. Williams, L. K. Emmons, R. L. Langenfelds, P. B. Krummel, and L. P. Steele
Atmos. Chem. Phys., 15, 3217–3239, https://doi.org/10.5194/acp-15-3217-2015, https://doi.org/10.5194/acp-15-3217-2015, 2015
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The Southern Hemisphere (SH) serves as an important test bed for evaluating our understanding of the processes that drive the composition of the clean background atmosphere. Using data from two aircraft campaigns, combined with four atmospheric chemistry models, we find a large sensitivity in the remote SH to biogenic emissions and their subsequent chemistry and transport. Future model evaluation and measurement campaigns should prioritize reducing uncertainties in these processes.
M. S. Long, R. Yantosca, J. E. Nielsen, C. A. Keller, A. da Silva, M. P. Sulprizio, S. Pawson, and D. J. Jacob
Geosci. Model Dev., 8, 595–602, https://doi.org/10.5194/gmd-8-595-2015, https://doi.org/10.5194/gmd-8-595-2015, 2015
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This paper presents results from the modularization of the GEOS-Chem chemical transport model, and its coupling as the chemical operator within the NASA-GMAO GEOS-5 Earth system model (ESM). The key findings are that chemistry within the modular GEOS-Chem system shows consistent, high strong-scaling properties across the range of distributed processors, transport is the limiting component prohibiting efficient scalability, and GEOS-Chem is able to generate suitable chemical results in an ESM.
M. Val Martin, C. L. Heald, J.-F. Lamarque, S. Tilmes, L. K. Emmons, and B. A. Schichtel
Atmos. Chem. Phys., 15, 2805–2823, https://doi.org/10.5194/acp-15-2805-2015, https://doi.org/10.5194/acp-15-2805-2015, 2015
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We present for the first time the relative effect of climate, emissions, and land use change on ozone and PM25 over the United States, focusing on the national parks. Air quality in 2050 will likely be dominated by emission patterns, but climate and land use changes alone can lead to a substantial increase in air pollution over most of the US, with important implications for O3 air quality, visibility and ecosystem health degradation in the national parks.
C. Viatte, K. Strong, J. Hannigan, E. Nussbaumer, L. K. Emmons, S. Conway, C. Paton-Walsh, J. Hartley, J. Benmergui, and J. Lin
Atmos. Chem. Phys., 15, 2227–2246, https://doi.org/10.5194/acp-15-2227-2015, https://doi.org/10.5194/acp-15-2227-2015, 2015
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Seven tropospheric species (CO, HCN, C2H6, C2H2, CH3OH, HCOOH, and H2CO) released by biomass burning events transported to the high Arctic were monitored with two sets of FTIR measurements, located at Eureka (Nunavut, Canada) and Thule (Greenland), from 2008 to 2012. We compared these data sets with the MOZART-4 chemical transport model to help improve its simulations in the Arctic. Emission factors of these biomass burning products were derived and compared to the literature.
T. Amnuaylojaroen, M. C. Barth, L. K. Emmons, G. R. Carmichael, J. Kreasuwun, S. Prasitwattanaseree, and S. Chantara
Atmos. Chem. Phys., 14, 12983–13012, https://doi.org/10.5194/acp-14-12983-2014, https://doi.org/10.5194/acp-14-12983-2014, 2014
F. L. Herron-Thorpe, G. H. Mount, L. K. Emmons, B. K. Lamb, D. A. Jaffe, N. L. Wigder, S. H. Chung, R. Zhang, M. D. Woelfle, and J. K. Vaughan
Atmos. Chem. Phys., 14, 12533–12551, https://doi.org/10.5194/acp-14-12533-2014, https://doi.org/10.5194/acp-14-12533-2014, 2014
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Wildfire season simulations from an air quality forecast system for the Pacific Northwest were compared to surface monitor observations across the region and NASA Earth Observing System satellite retrievals of plume top, nitrogen dioxide, aerosol optical depth, and carbon monoxide. This study discusses why the Community Multi-scale Air Quality model predictions under-predicted secondary organic aerosol (SOA) production for events when fire emissions were transported large distances.
C. Chan Miller, G. Gonzalez Abad, H. Wang, X. Liu, T. Kurosu, D. J. Jacob, and K. Chance
Atmos. Meas. Tech., 7, 3891–3907, https://doi.org/10.5194/amt-7-3891-2014, https://doi.org/10.5194/amt-7-3891-2014, 2014
M. N. Deeter, S. Martínez-Alonso, D. P. Edwards, L. K. Emmons, J. C. Gille, H. M. Worden, C. Sweeney, J. V. Pittman, B. C. Daube, and S. C. Wofsy
Atmos. Meas. Tech., 7, 3623–3632, https://doi.org/10.5194/amt-7-3623-2014, https://doi.org/10.5194/amt-7-3623-2014, 2014
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The MOPITT Version 6 product for carbon monoxide (CO) incorporates several enhancements. First, a geolocation bias has been eliminated. Second, the new variable a priori for CO concentrations is based on simulations performed with the CAM-Chem chemical transport model for the years 2000-2009. Third, required meteorological fields are extracted from the MERRA reanalysis. Finally, a retrieval bias in the upper troposphere was substantially reduced. Validation results are presented.
J. D. Fast, J. Allan, R. Bahreini, J. Craven, L. Emmons, R. Ferrare, P. L. Hayes, A. Hodzic, J. Holloway, C. Hostetler, J. L. Jimenez, H. Jonsson, S. Liu, Y. Liu, A. Metcalf, A. Middlebrook, J. Nowak, M. Pekour, A. Perring, L. Russell, A. Sedlacek, J. Seinfeld, A. Setyan, J. Shilling, M. Shrivastava, S. Springston, C. Song, R. Subramanian, J. W. Taylor, V. Vinoj, Q. Yang, R. A. Zaveri, and Q. Zhang
Atmos. Chem. Phys., 14, 10013–10060, https://doi.org/10.5194/acp-14-10013-2014, https://doi.org/10.5194/acp-14-10013-2014, 2014
K. J. Wecht, D. J. Jacob, M. P. Sulprizio, G. W. Santoni, S. C. Wofsy, R. Parker, H. Bösch, and J. Worden
Atmos. Chem. Phys., 14, 8173–8184, https://doi.org/10.5194/acp-14-8173-2014, https://doi.org/10.5194/acp-14-8173-2014, 2014
C. A. Keller, M. S. Long, R. M. Yantosca, A. M. Da Silva, S. Pawson, and D. J. Jacob
Geosci. Model Dev., 7, 1409–1417, https://doi.org/10.5194/gmd-7-1409-2014, https://doi.org/10.5194/gmd-7-1409-2014, 2014
P. Zoogman, D. J. Jacob, K. Chance, X. Liu, M. Lin, A. Fiore, and K. Travis
Atmos. Chem. Phys., 14, 6261–6271, https://doi.org/10.5194/acp-14-6261-2014, https://doi.org/10.5194/acp-14-6261-2014, 2014
M. Li, Q. Zhang, D. G. Streets, K. B. He, Y. F. Cheng, L. K. Emmons, H. Huo, S. C. Kang, Z. Lu, M. Shao, H. Su, X. Yu, and Y. Zhang
Atmos. Chem. Phys., 14, 5617–5638, https://doi.org/10.5194/acp-14-5617-2014, https://doi.org/10.5194/acp-14-5617-2014, 2014
L. Zhang, D. J. Jacob, X. Yue, N. V. Downey, D. A. Wood, and D. Blewitt
Atmos. Chem. Phys., 14, 5295–5309, https://doi.org/10.5194/acp-14-5295-2014, https://doi.org/10.5194/acp-14-5295-2014, 2014
E. V. Fischer, D. J. Jacob, R. M. Yantosca, M. P. Sulprizio, D. B. Millet, J. Mao, F. Paulot, H. B. Singh, A. Roiger, L. Ries, R.W. Talbot, K. Dzepina, and S. Pandey Deolal
Atmos. Chem. Phys., 14, 2679–2698, https://doi.org/10.5194/acp-14-2679-2014, https://doi.org/10.5194/acp-14-2679-2014, 2014
P. S. Kim, D. J. Jacob, X. Liu, J. X. Warner, K. Yang, K. Chance, V. Thouret, and P. Nedelec
Atmos. Chem. Phys., 13, 9321–9335, https://doi.org/10.5194/acp-13-9321-2013, https://doi.org/10.5194/acp-13-9321-2013, 2013
J. L. Thomas, J.-C. Raut, K. S. Law, L. Marelle, G. Ancellet, F. Ravetta, J. D. Fast, G. Pfister, L. K. Emmons, G. S. Diskin, A. Weinheimer, A. Roiger, and H. Schlager
Atmos. Chem. Phys., 13, 3825–3848, https://doi.org/10.5194/acp-13-3825-2013, https://doi.org/10.5194/acp-13-3825-2013, 2013
R. D. Saylor
Atmos. Chem. Phys., 13, 693–715, https://doi.org/10.5194/acp-13-693-2013, https://doi.org/10.5194/acp-13-693-2013, 2013
J. Mao, S. Fan, D. J. Jacob, and K. R. Travis
Atmos. Chem. Phys., 13, 509–519, https://doi.org/10.5194/acp-13-509-2013, https://doi.org/10.5194/acp-13-509-2013, 2013
L. K. Emmons, P. G. Hess, J.-F. Lamarque, and G. G. Pfister
Geosci. Model Dev., 5, 1531–1542, https://doi.org/10.5194/gmd-5-1531-2012, https://doi.org/10.5194/gmd-5-1531-2012, 2012
Related subject area
Atmospheric sciences
Description and evaluation of the community aerosol dynamics model MAFOR v2.0
Modeling the high-mercury wet deposition in the southeastern US with WRF-GC-Hg v1.0
Development of a deep neural network for predicting 6 h average PM2.5 concentrations up to 2 subsequent days using various training data
Chemistry Across Multiple Phases (CAMP) version 1.0: an integrated multiphase chemistry model
An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application
Earth system modeling of mercury using CESM2 – Part 1: Atmospheric model CAM6-Chem/Hg v1.0
Conservation laws in a neural network architecture: enforcing the atom balance of a Julia-based photochemical model (v0.2.0)
On the application and grid-size sensitivity of the urban dispersion model CAIRDIO v2.0 under real city weather conditions
Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16
Estimating aerosol emission from SPEXone on the NASA PACE mission using an ensemble Kalman smoother: observing system simulation experiments (OSSEs)
An ensemble-based statistical methodology to detect differences in weather and climate model executables
Multiphase processes in the EC-Earth model and their relevance to the atmospheric oxalate, sulfate, and iron cycles
Sensitivity of precipitation in the highlands and lowlands of Peru to physics parameterization options in WRFV3.8.1
Coupling a weather model directly to GNSS orbit determination – case studies with OpenIFS
Implementation of an ensemble Kalman filter in the Community Multiscale Air Quality model (CMAQ model v5.1) for data assimilation of ground-level PM2.5
Massive-Parallel Trajectory Calculations version 2.2 (MPTRAC-2.2): Lagrangian transport simulations on graphics processing units (GPUs)
Bedymo: a combined quasi-geostrophic and primitive equation model in σ coordinates
Simulation of organics in the atmosphere: evaluation of EMACv2.54 with the Mainz Organic Mechanism (MOM) coupled to the ORACLE (v1.0) submodel
An update on the 4D-LETKF data assimilation system for the whole neutral atmosphere
Determining the sensitive parameters of the Weather Research and Forecasting (WRF) model for the simulation of tropical cyclones in the Bay of Bengal using global sensitivity analysis and machine learning
A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models
Multiple same-level and telescoping nesting in GFDL's dynamical core
Implementation of aerosol data assimilation in WRFDA (v4.0.3) for WRF-Chem (v3.9.1) using the RACM/MADE-VBS scheme
Representing low-intensity fire sensible heat output in a mesoscale atmospheric model with a canopy submodel: a case study with ARPS-CANOPY (version 5.2.12)
A machine-learning-guided adaptive algorithm to reduce the computational cost of integrating kinetics in global atmospheric chemistry models: application to GEOS-Chem versions 12.0.0 and 12.9.1
Deep-learning spatial principles from deterministic chemical transport models for chemical reanalysis: an application in China for PM2.5
Model development in practice: a comprehensive update to the boundary layer schemes in HARMONIE-AROME cycle 40
A parameterization of long-continuing-current (LCC) lightning in the lightning submodel LNOX (version 3.0) of the Modular Earth Submodel System (MESSy, version 2.54)
Air Control Toolbox (ACT_v1.0): a flexible surrogate model to explore mitigation scenarios in air quality forecasts
The Aerosol Module in the Community Radiative Transfer Model (v2.2 and v2.3): accounting for aerosol transmittance effects on the radiance observation operator
RAP-Net: Region Attention Predictive Network for Precipitation Nowcasting
The Flexible Modelling Framework for the Met Office Unified Model (Flex-UM, using UM 12.0 release)
Integration-based extraction and visualization of jet stream cores
Particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0
Evaluating the assimilation of S5P/TROPOMI near real-time SO2 columns and layer height data into the CAMS integrated forecasting system (CY47R1), based on a case study of the 2019 Raikoke eruption
A comparative analysis for deep learning model (hyDL-CO v1.0) and Kalman Filter to predict CO in China
Effects of vertical ship exhaust plume distributions on urban pollutant concentration – a sensitivity study with MITRAS v2.0 and EPISODE-CityChem v1.4
Improvement of stomatal resistance and photosynthesis mechanism of Noah-MP-WDDM (v1.42) in simulation of NO2 dry deposition velocity in forests
Representation of the autoconversion from cloud to rain using a weighted ensemble approach: a case study using WRF v4.1.3
EuLerian Identification of ascending AirStreams (ELIAS 2.0) in numerical weather prediction and climate models – Part 1: Development of deep learning model
EuLerian Identification of ascending AirStreams (ELIAS 2.0) in numerical weather prediction and climate models – Part 2: Model application to different datasets
The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at km-scale
A new exponentially decaying error correlation model for assimilating OCO-2 column-average CO2 data using a length scale computed from airborne lidar measurements
Numerically consistent budgets of potential temperature, momentum, and moisture in Cartesian coordinates: application to the WRF model
An aerosol classification scheme for global simulations using the K-means machine learning method
Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in the WRF (v4.1.3) model during the ICE-POP 2018 field campaign
Parameterization of the collision–coalescence process using series of basis functions: COLNETv1.0.0 model development using a machine learning approach
Inline coupling of simple and complex chemistry modules within the global weather forecast model FIM (FIM-Chem v1)
Downscaling of air pollutants in Europe using uEMEP_v6
Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties
Matthias Karl, Liisa Pirjola, Tiia Grönholm, Mona Kurppa, Srinivasan Anand, Xiaole Zhang, Andreas Held, Rolf Sander, Miikka Dal Maso, David Topping, Shuai Jiang, Leena Kangas, and Jaakko Kukkonen
Geosci. Model Dev., 15, 3969–4026, https://doi.org/10.5194/gmd-15-3969-2022, https://doi.org/10.5194/gmd-15-3969-2022, 2022
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The community aerosol dynamics model MAFOR includes several advanced features: coupling with an up-to-date chemistry mechanism for volatile organic compounds, a revised Brownian coagulation kernel that takes into account the fractal geometry of soot particles, a multitude of nucleation parameterizations, size-resolved partitioning of semi-volatile inorganics, and a hybrid method for the formation of secondary organic aerosols within the framework of condensation and evaporation.
Xiaotian Xu, Xu Feng, Haipeng Lin, Peng Zhang, Shaojian Huang, Zhengcheng Song, Yiming Peng, Tzung-May Fu, and Yanxu Zhang
Geosci. Model Dev., 15, 3845–3859, https://doi.org/10.5194/gmd-15-3845-2022, https://doi.org/10.5194/gmd-15-3845-2022, 2022
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Mercury is one of the most toxic pollutants in the environment, and wet deposition is a major process for atmospheric mercury to enter, causing ecological and human health risks. High-mercury wet deposition in the southeastern US has been a problem for many years. Here we employed a newly developed high-resolution WRF-GC model with the capability to simulate mercury to study this problem. We conclude that deep convection caused enhanced mercury wet deposition in the southeastern US.
Jeong-Beom Lee, Jae-Bum Lee, Youn-Seo Koo, Hee-Yong Kwon, Min-Hyeok Choi, Hyun-Ju Park, and Dae-Gyun Lee
Geosci. Model Dev., 15, 3797–3813, https://doi.org/10.5194/gmd-15-3797-2022, https://doi.org/10.5194/gmd-15-3797-2022, 2022
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The predication of PM2.5 has been carried out using a numerical air quality model in South Korea. Despite recent progress of numerical air quality models, accurate prediction of PM2.5 is still challenging. In this study, we developed a data-based model using a deep neural network (DNN) to overcome the limitations of numerical air quality models. The results showed that the DNN model outperformed the CMAQ when it was trained by using observation and forecasting data from the numerical models.
Matthew L. Dawson, Christian Guzman, Jeffrey H. Curtis, Mario Acosta, Shupeng Zhu, Donald Dabdub, Andrew Conley, Matthew West, Nicole Riemer, and Oriol Jorba
Geosci. Model Dev., 15, 3663–3689, https://doi.org/10.5194/gmd-15-3663-2022, https://doi.org/10.5194/gmd-15-3663-2022, 2022
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Progress in identifying complex, mixed-phase physicochemical processes has resulted in an advanced understanding of the evolution of atmospheric systems but has also introduced a level of complexity that few atmospheric models were designed to handle. We present a flexible treatment for multiphase chemical processes for models of diverse scale, from box up to global models. This enables users to build a customized multiphase mechanism that is accessible to a much wider community.
Haibo Wang, Ting Yang, Zifa Wang, Jianjun Li, Wenxuan Chai, Guigang Tang, Lei Kong, and Xueshun Chen
Geosci. Model Dev., 15, 3555–3585, https://doi.org/10.5194/gmd-15-3555-2022, https://doi.org/10.5194/gmd-15-3555-2022, 2022
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In this paper, we develop an online data coupled assimilation system (NAQPMS-PDAF) with the Eulerian atmospheric chemistry-transport model. NAQPMS-PDAF allows efficient use of large computational resources. The application and performance of the system are investigated by assimilating 1 month of vertical aerosol observations. The results show that NAQPMS-PDAF can significantly improve the performance of aerosol vertical structure simulation and reduce the uncertainty to a large extent.
Peng Zhang and Yanxu Zhang
Geosci. Model Dev., 15, 3587–3601, https://doi.org/10.5194/gmd-15-3587-2022, https://doi.org/10.5194/gmd-15-3587-2022, 2022
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Mercury is a global pollutant that can be transported over long distance through the atmosphere. We develop a new online global model for atmospheric mercury. The model reproduces the observed global atmospheric mercury concentrations and deposition distributions by simulating the emissions, transport, and physicochemical processes of atmospheric mercury. And we find that the seasonal variations of atmospheric Hg are the result of multiple processes and have obvious regional characteristics.
Patrick Obin Sturm and Anthony S. Wexler
Geosci. Model Dev., 15, 3417–3431, https://doi.org/10.5194/gmd-15-3417-2022, https://doi.org/10.5194/gmd-15-3417-2022, 2022
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Large air quality and climate models require vast amounts of computational power. Machine learning tools like neural networks can be used to make these models more efficient, with the downside that their results might not make physical sense or be easy to interpret. This work develops a physically interpretable neural network that obeys scientific laws like conservation of mass and models atmospheric composition more accurately than a traditional neural network.
Michael Weger, Holger Baars, Henriette Gebauer, Maik Merkel, Alfred Wiedensohler, and Bernd Heinold
Geosci. Model Dev., 15, 3315–3345, https://doi.org/10.5194/gmd-15-3315-2022, https://doi.org/10.5194/gmd-15-3315-2022, 2022
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Numerical models are an important tool to assess the air quality in cities,
as they can provide near-continouos data in time and space. In this paper,
air pollution for an entire city is simulated at a high spatial resolution of 40 m.
At this spatial scale, the effects of buildings on the atmosphere,
like channeling or blocking of the air flow, are directly represented by diffuse obstacles in the used model CAIRDIO. For model validation, measurements from air-monitoring sites are used.
Patrick C. Campbell, Youhua Tang, Pius Lee, Barry Baker, Daniel Tong, Rick Saylor, Ariel Stein, Jianping Huang, Ho-Chun Huang, Edward Strobach, Jeff McQueen, Li Pan, Ivanka Stajner, Jamese Sims, Jose Tirado-Delgado, Youngsun Jung, Fanglin Yang, Tanya L. Spero, and Robert C. Gilliam
Geosci. Model Dev., 15, 3281–3313, https://doi.org/10.5194/gmd-15-3281-2022, https://doi.org/10.5194/gmd-15-3281-2022, 2022
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NOAA's National Air Quality Forecast Capability (NAQFC) continues to protect Americans from the harmful effects of air pollution, while saving billions of dollars per year. Here we describe and evaluate the development of the most advanced version of the NAQFC to date, which became operational at NOAA on 20 July 2021. The new NAQFC is based on a coupling of NOAA's operational Global Forecast System (GFS) version 16 with the Community Multiscale Air Quality (CMAQ) model version 5.3.1.
Athanasios Tsikerdekis, Nick A. J. Schutgens, Guangliang Fu, and Otto P. Hasekamp
Geosci. Model Dev., 15, 3253–3279, https://doi.org/10.5194/gmd-15-3253-2022, https://doi.org/10.5194/gmd-15-3253-2022, 2022
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In our study we quantify the ability of the future satellite sensor SPEXone, part of the NASA PACE mission, to estimate aerosol emissions. The sensor will be able to retrieve accurate information of aerosol light extinction and most importantly light absorption. We simulate SPEXone spatial coverage and combine it with an aerosol model. We found that SPEXone will be able to estimate species-specific (e.g. dust, sea salt, organic or black carbon, sulfates) aerosol emissions very accurately.
Christian Zeman and Christoph Schär
Geosci. Model Dev., 15, 3183–3203, https://doi.org/10.5194/gmd-15-3183-2022, https://doi.org/10.5194/gmd-15-3183-2022, 2022
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Our atmosphere is a chaotic system, where even a tiny change can have a big impact. This makes it difficult to assess if small changes, such as the move to a new hardware architecture, will significantly affect a weather and climate model. We present a methodology that allows to objectively verify this. The methodology is applied to several test cases, showing a high sensitivity. Results also show that a major system update of the underlying supercomputer did not significantly affect our model.
Stelios Myriokefalitakis, Elisa Bergas-Massó, María Gonçalves-Ageitos, Carlos Pérez García-Pando, Twan van Noije, Philippe Le Sager, Akinori Ito, Eleni Athanasopoulou, Athanasios Nenes, Maria Kanakidou, Maarten C. Krol, and Evangelos Gerasopoulos
Geosci. Model Dev., 15, 3079–3120, https://doi.org/10.5194/gmd-15-3079-2022, https://doi.org/10.5194/gmd-15-3079-2022, 2022
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We here describe the implementation of atmospheric multiphase processes in the EC-Earth Earth system model. We provide global budgets of oxalate, sulfate, and iron-containing aerosols, along with an analysis of the links among atmospheric composition, aqueous-phase processes, and aerosol dissolution, supported by comparison to observations. This work is a first step towards an interactive calculation of the deposition of bioavailable atmospheric iron coupled to the model’s ocean component.
Santos J. González-Rojí, Martina Messmer, Christoph C. Raible, and Thomas F. Stocker
Geosci. Model Dev., 15, 2859–2879, https://doi.org/10.5194/gmd-15-2859-2022, https://doi.org/10.5194/gmd-15-2859-2022, 2022
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Different configurations of physics parameterizations of a regional climate model are tested over southern Peru at fine resolution. The most challenging regions compared to observational data are the slopes of the Andes. Model configurations for Europe and East Africa are not perfectly suitable for southern Peru. The experiment with the Stony Brook University microphysics scheme and the Grell–Freitas cumulus parameterization provides the most accurate results over Madre de Dios.
Angel Navarro Trastoy, Sebastian Strasser, Lauri Tuppi, Maksym Vasiuta, Markku Poutanen, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev., 15, 2763–2771, https://doi.org/10.5194/gmd-15-2763-2022, https://doi.org/10.5194/gmd-15-2763-2022, 2022
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Production of satellite products relies on information from different centers. By coupling a weather model and an orbit determination solver we eliminate the dependence on one of the centers. The coupling has proven to be possible in the first stage, where no formatting has been applied to any of the models involved. This opens a window for further development and improvement to a coupling that has proven to be as good as the predecessor model.
Soon-Young Park, Uzzal Kumar Dash, Jinhyeok Yu, Keiya Yumimoto, Itsushi Uno, and Chul Han Song
Geosci. Model Dev., 15, 2773–2790, https://doi.org/10.5194/gmd-15-2773-2022, https://doi.org/10.5194/gmd-15-2773-2022, 2022
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An EnKF was applied to CMAQ for assimilating ground PM2.5 observations from China and South Korea. The EnKF performed better than that without assimilation and even superior to 3D-Var. The reduced MBs in 24 h predictions were 48 % and 27 % by improving ICs and BCs, respectively.
Lars Hoffmann, Paul F. Baumeister, Zhongyin Cai, Jan Clemens, Sabine Griessbach, Gebhard Günther, Yi Heng, Mingzhao Liu, Kaveh Haghighi Mood, Olaf Stein, Nicole Thomas, Bärbel Vogel, Xue Wu, and Ling Zou
Geosci. Model Dev., 15, 2731–2762, https://doi.org/10.5194/gmd-15-2731-2022, https://doi.org/10.5194/gmd-15-2731-2022, 2022
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We describe the new version (2.2) of the Lagrangian transport model MPTRAC, which has been ported for application on GPUs. The model was verified by comparing kinematic trajectories and synthetic tracer simulations for the free troposphere and stratosphere from GPUs and CPUs. Benchmarking showed a speed-up of a factor of 16 of GPU-enabled simulations compared to CPU-only runs, indicating the great potential of applying GPUs for Lagrangian transport simulations on upcoming HPC systems.
Clemens Spensberger, Trond Thorsteinsson, and Thomas Spengler
Geosci. Model Dev., 15, 2711–2729, https://doi.org/10.5194/gmd-15-2711-2022, https://doi.org/10.5194/gmd-15-2711-2022, 2022
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In order to understand the atmosphere, we rely on a hierarchy of models ranging from very simple to very complex. Comparing different steps in this hierarchy usually entails comparing different models. Here we combine two such steps that are commonly used in one modelling framework. This makes comparisons both much easier and much more direct.
Andrea Pozzer, Simon F. Reifenberg, Vinod Kumar, Bruno Franco, Matthias Kohl, Domenico Taraborrelli, Sergey Gromov, Sebastian Ehrhart, Patrick Jöckel, Rolf Sander, Veronica Fall, Simon Rosanka, Vlassis Karydis, Dimitris Akritidis, Tamara Emmerichs, Monica Crippa, Diego Guizzardi, Johannes W. Kaiser, Lieven Clarisse, Astrid Kiendler-Scharr, Holger Tost, and Alexandra Tsimpidi
Geosci. Model Dev., 15, 2673–2710, https://doi.org/10.5194/gmd-15-2673-2022, https://doi.org/10.5194/gmd-15-2673-2022, 2022
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A newly developed setup of the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) is evaluated here. A comprehensive organic degradation mechanism is used and coupled with a volatility base model.
The results show that the model reproduces most of the tracers and aerosols satisfactorily but shows discrepancies for oxygenated organic gases. It is also shown that this model configuration can be used for further research in atmospheric chemistry.
Dai Koshin, Kaoru Sato, Masashi Kohma, and Shingo Watanabe
Geosci. Model Dev., 15, 2293–2307, https://doi.org/10.5194/gmd-15-2293-2022, https://doi.org/10.5194/gmd-15-2293-2022, 2022
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The 4D ensemble Kalman filter data assimilation system for the whole neutral atmosphere has been updated. The update includes the introduction of a filter to reduce the generation of spurious waves, change in the order of horizontal diffusion of the forecast model to reproduce more realistic tidal amplitudes, and use of additional satellite observations. As a result, the analysis performance has been greatly improved, even for disturbances with periods of less than 1 d.
Harish Baki, Sandeep Chinta, C Balaji, and Balaji Srinivasan
Geosci. Model Dev., 15, 2133–2155, https://doi.org/10.5194/gmd-15-2133-2022, https://doi.org/10.5194/gmd-15-2133-2022, 2022
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WRF model accuracy relies on numerous aspects, and the model parameters are one of them. By calibrating the model parameters, we can improve the model forecast. However, there exist hundreds of parameters, and calibrating all of them is unimaginably expensive. Thus, there is a need to identify the sensitive parameters that influence the model output variables to reduce the parameter dimensionality. This study addresses the different methods and outcomes of parameter sensitivity analysis.
Jessica Keune, Dominik L. Schumacher, and Diego G. Miralles
Geosci. Model Dev., 15, 1875–1898, https://doi.org/10.5194/gmd-15-1875-2022, https://doi.org/10.5194/gmd-15-1875-2022, 2022
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Air transports moisture and heat, shaping the weather we experience. When and where was this air moistened and warmed by the surface? To address this question, atmospheric models trace the history of air parcels in space and time. However, their uncertainties remain unexplored, which hinders their utility and application. Here, we present a framework that sheds light on these uncertainties. Our approach sets a new standard in the assessment of atmospheric moisture and heat trajectories.
Joseph Mouallem, Lucas Harris, and Rusty Benson
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-442, https://doi.org/10.5194/gmd-2021-442, 2022
Revised manuscript accepted for GMD
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The single nest capability in GFDL's dynamical core, FV3, is upgraded to support multiple same-level and telescoping nests. Grid nesting adds a refined grid over an area of interest to better resolve small scale flow features necessary to accurately predict special weather events such as severe storms and hurricanes. This work allow concurrent execution of multiple same level and telescoping multi level nested grids in both global and regional setups.
Soyoung Ha
Geosci. Model Dev., 15, 1769–1788, https://doi.org/10.5194/gmd-15-1769-2022, https://doi.org/10.5194/gmd-15-1769-2022, 2022
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In an effort to improve air quality forecasting, the WRFDA 3D-Var system is newly extended for the assimilation of surface PM2.5 and PM10 using the RACM/MADE-VBS chemistry in the WRF-Chem model. Through a case study during the Korea–United States Air Quality (KORUS-AQ) period, it is demonstrated that the analysis can lead to improving the prediction of surface PM concentrations up to 26 % for 24 h, diminishing most bias errors.
Michael T. Kiefer, Warren E. Heilman, Shiyuan Zhong, Joseph J. Charney, Xindi Bian, Nicholas S. Skowronski, Kenneth L. Clark, Michael R. Gallagher, John L. Hom, and Matthew Patterson
Geosci. Model Dev., 15, 1713–1734, https://doi.org/10.5194/gmd-15-1713-2022, https://doi.org/10.5194/gmd-15-1713-2022, 2022
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We examine methods used to represent wildland fire sensible heat release in atmospheric models. A set of simulations are evaluated using observations from a low-intensity prescribed fire in the New Jersey Pine Barrens. The comparison is motivated by the need for guidance regarding the representation of low-intensity fire sensible heating in atmospheric models. Such fires are prevalent during prescribed fire operations and can impact the health and safety of fire personnel and the public.
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Kelvin Bates, Jiawei Zhuang, and Wei Chen
Geosci. Model Dev., 15, 1677–1687, https://doi.org/10.5194/gmd-15-1677-2022, https://doi.org/10.5194/gmd-15-1677-2022, 2022
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The high computational cost of chemical integration is a long-standing limitation in global atmospheric chemistry models. Here we present an adaptive and efficient algorithm that can reduce the computational time of atmospheric chemistry by 50 % and maintain the error below 2 % for important species, inspired by machine learning clustering techniques and traditional asymptotic analysis ideas.
Baolei Lyu, Ran Huang, Xinlu Wang, Weiguo Wang, and Yongtao Hu
Geosci. Model Dev., 15, 1583–1594, https://doi.org/10.5194/gmd-15-1583-2022, https://doi.org/10.5194/gmd-15-1583-2022, 2022
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Data fusion is used to estimate spatially completed and smooth reanalysis fields from multiple data sources of observations and model simulations. We developed a well-designed deep-learning model framework to embed spatial correlation principles of atmospheric physics and chemical models. The deep-learning model has very high accuracy to predict reanalysis data fields from isolated observation data points. It is also feasible for operational applications due to computational efficiency.
Wim C. de Rooy, Pier Siebesma, Peter Baas, Geert Lenderink, Stephan R. de Roode, Hylke de Vries, Erik van Meijgaard, Jan Fokke Meirink, Sander Tijm, and Bram van 't Veen
Geosci. Model Dev., 15, 1513–1543, https://doi.org/10.5194/gmd-15-1513-2022, https://doi.org/10.5194/gmd-15-1513-2022, 2022
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This paper describes a comprehensive model update to the boundary layer schemes. Because the involved parameterisations are all built on widely applied frameworks, the here-described modifications are applicable to many NWP and climate models. The model update contains substantial modifications to the cloud, turbulence, and convection schemes and leads to a substantial improvement of several aspects of the model, especially low cloud forecasts.
Francisco J. Pérez-Invernón, Heidi Huntrieser, Patrick Jöckel, and Francisco J. Gordillo-Vázquez
Geosci. Model Dev., 15, 1545–1565, https://doi.org/10.5194/gmd-15-1545-2022, https://doi.org/10.5194/gmd-15-1545-2022, 2022
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This study reports the first parameterization of long-continuing-current lightning in a climate model. Long-continuing-current lightning is proposed to be the main precursor of lightning-ignited wildfires and sprites, a type of transient luminous event taking place in the mesosphere. This parameterization can significantly contribute to improving the implementation of wildfires in climate models.
Augustin Colette, Laurence Rouïl, Frédérik Meleux, Vincent Lemaire, and Blandine Raux
Geosci. Model Dev., 15, 1441–1465, https://doi.org/10.5194/gmd-15-1441-2022, https://doi.org/10.5194/gmd-15-1441-2022, 2022
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We introduce the first toolbox that allows exploration of the benefits of air pollution mitigation scenarios in the every-day air quality forecasts through a web interface. The toolbox relies on the joint use of chemistry-transport models (CTMs) and surrogate modelling techniques.
Cheng-Hsuan Lu, Quanhua Liu, Shih-Wei Wei, Benjamin T. Johnson, Cheng Dang, Patrick G. Stegmann, Dustin Grogan, Guoqing Ge, Ming Hu, and Michael Lueken
Geosci. Model Dev., 15, 1317–1329, https://doi.org/10.5194/gmd-15-1317-2022, https://doi.org/10.5194/gmd-15-1317-2022, 2022
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This article is a technical note on the aerosol absorption and scattering calculations of the Community Radiative Transfer Model (CRTM) v2.2 and v2.3. It also provides guidance for prospective users of the CRTM aerosol option and Gridpoint Statistical Interpolation (GSI) aerosol-aware radiance assimilation. Scientific aspects of aerosol-affected BT in atmospheric data assimilation are also briefly discussed.
Zheng Zhang, Chuyao Luo, Shanshan Feng, Rui Ye, Yunming Ye, and Xutao Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-19, https://doi.org/10.5194/gmd-2022-19, 2022
Revised manuscript accepted for GMD
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In this paper, we develop a model to predict radar echo sequences and apply it in the precipitation nowcasting field. Different from existed models, we propose two new attention modules. By introducing them, the performance of RAP-Net outperforms other models especially in those regions with middle and high-intensity rainfall. Considering these regions would cause more threats to human activity, the research in our manuscript is significant to prevent natural disasters caused by heavy rainfall.
Penelope Maher and Paul Earnshaw
Geosci. Model Dev., 15, 1177–1194, https://doi.org/10.5194/gmd-15-1177-2022, https://doi.org/10.5194/gmd-15-1177-2022, 2022
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Climate models do a pretty good job. But they are far from perfect. Fixing these imperfections is really hard because the models are complicated. One way to make progress is to create simpler models: think impressionism rather than realism in the art world. We changed the Met Office model to be intentionally simple and it still does a pretty good job. This will help to identify sources of model imperfections, develop new methods and improve our understanding of how the climate works.
Lukas Bösiger, Michael Sprenger, Maxi Boettcher, Hanna Joos, and Tobias Günther
Geosci. Model Dev., 15, 1079–1096, https://doi.org/10.5194/gmd-15-1079-2022, https://doi.org/10.5194/gmd-15-1079-2022, 2022
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Jet streams are coherent air flows that interact with atmospheric structures such as warm conveyor belts (WCBs) and the tropopause. Individually, these structures have a significant impact on the weather evolution. A first step towards a deeper understanding of the meteorological processes is to extract jet stream core lines, for which we develop a novel feature extraction algorithm. Based on the line geometry, we automatically detect and visualize potential interactions between WCBs and jets.
Philipp Franke, Anne Caroline Lange, and Hendrik Elbern
Geosci. Model Dev., 15, 1037–1060, https://doi.org/10.5194/gmd-15-1037-2022, https://doi.org/10.5194/gmd-15-1037-2022, 2022
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The paper proposes an ensemble-based analysis framework (ESIAS-chem) for time- and altitude-resolved volcanic ash emission fluxes and their uncertainty. The core of the algorithm is an ensemble Nelder–Mead optimization algorithm accompanied by a particle filter update. The performed notional experiments demonstrate the high accuracy of ESIAS-chem in analyzing the vertically resolved volcanic ash in the atmosphere. Further, the system is in general able to estimate the emission fluxes properly.
Antje Inness, Melanie Ades, Dimitris Balis, Dmitry Efremenko, Johannes Flemming, Pascal Hedelt, Maria-Elissavet Koukouli, Diego Loyola, and Roberto Ribas
Geosci. Model Dev., 15, 971–994, https://doi.org/10.5194/gmd-15-971-2022, https://doi.org/10.5194/gmd-15-971-2022, 2022
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This paper describes the way that the Copernicus Atmosphere Monitoring Service (CAMS) produces forecasts of volcanic SO2. These forecasts are provided routinely every day. They are created by blending SO2 data from satellite instruments (TROPOMI and GOME-2) with the CAMS model. We show that the quality of the CAMS SO2 forecasts can be improved if additional information about the height of volcanic plumes is provided in the satellite data.
Weichao Han, Tai-Long He, Zhaojun Tang, Min Wang, Dylan Jones, and Zhe Jiang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-420, https://doi.org/10.5194/gmd-2021-420, 2022
Revised manuscript accepted for GMD
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We present an application of a hybrid deep learning (DL) model on prediction of surface CO in China from 2015 to 2020, which utilizes both convolutional neural networks and long short-term memory neural networks. The performance of DL model is better than a Kalman Filter (KF) system in the training period (2005–2018). Furthermore, DL model demonstrates good temporal extensibility: the mean bias and correlation coefficients are 95.7 ppb and 0.93 in the test period (2019–2020) over E. China.
Ronny Badeke, Volker Matthias, Matthias Karl, and David Grawe
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-376, https://doi.org/10.5194/gmd-2021-376, 2022
Revised manuscript accepted for GMD
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For air quality modeling studies it is very important to distribute pollutants correctly into the model system. This has not yet been done for shipping pollution in a high detail. We studied the effect of different vertical distributions of shipping pollutants on the urban air quality and derived advanced formulas for it. These formulas take weather conditions and ship-specific parameters like the exhaust gas temperature into account.
Ming Chang, Jiachen Cao, Qi Zhang, Weihua Chen, Guotong Wu, Liping Wu, Weiwen Wang, and Xuemei Wang
Geosci. Model Dev., 15, 787–801, https://doi.org/10.5194/gmd-15-787-2022, https://doi.org/10.5194/gmd-15-787-2022, 2022
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Despite the importance of nitrogen deposition, its simulation is still insufficiently represented in current atmospheric chemistry models. In this study, the improvement of the canopy stomatal resistance mechanism and the nitrogen-limiting schemes in Noah-MP-WDDM v1.42 give new options for simulating nitrogen dry deposition velocity. This study finds that the combined BN-23 mechanism agrees better with the observed NO2 dry deposition velocity, with the mean bias reduced by 50.1 %.
Jinfang Yin, Xudong Liang, Hong Wang, and Haile Xue
Geosci. Model Dev., 15, 771–786, https://doi.org/10.5194/gmd-15-771-2022, https://doi.org/10.5194/gmd-15-771-2022, 2022
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An ensemble (EN) approach was designed to improve autoconversion (ATC) from cloud water to rainwater in cloud microphysics schemes. One unique feature of the EN approach is that the ATC rate is a mean value based on the calculations from several widely used ATC schemes. The ensemble approach proposed herein appears to help improve the representation of cloud and precipitation processes in weather and climate models.
Julian F. Quinting and Christian M. Grams
Geosci. Model Dev., 15, 715–730, https://doi.org/10.5194/gmd-15-715-2022, https://doi.org/10.5194/gmd-15-715-2022, 2022
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Physical processes in weather systems importantly affect the midlatitude large-scale circulation. This study introduces an artificial-intelligence-based framework which allows the identification of an important weather system – the so-called warm conveyor belt (WCB) – at comparably low computational costs and from data at low spatial and temporal resolution. The framework thus newly enables the systematic investigation of WCBs in large data sets such as climate model projections.
Julian F. Quinting, Christian M. Grams, Annika Oertel, and Moritz Pickl
Geosci. Model Dev., 15, 731–744, https://doi.org/10.5194/gmd-15-731-2022, https://doi.org/10.5194/gmd-15-731-2022, 2022
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This study applies novel artificial-intelligence-based models that allow the identification of one specific weather system which affects the midlatitude circulation. We show that the models yield similar results as their trajectory-based counterpart, which requires data at higher spatiotemporal resolution and is computationally more expensive. Overall, we aim to show how deep learning methods can be used efficiently to support process understanding of biases in weather prediction models.
Juan Manuel Castillo, Huw Lewis, Akhilesh Mishra, Ashis Mitra, Jeff Polton, Ashley Brereton, Andrew Saulter, Alex Arnold, Segolene Berthou, Douglas Clark, Julia Crook, Ananda Das, John Edwards, Xiangbo Feng, Ankur Gupta, Sudheer Joseph, Nicholas Klingaman, Imranali Momin, Christine Pequignet, Claudio Sanchez, Jennifer Saxby, and Maria Valdivieso da Costa
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-7, https://doi.org/10.5194/gmd-2022-7, 2022
Revised manuscript accepted for GMD
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A new environmental modelling system has been developed to represent the effect of feedbacks between atmosphere, land and ocean in the Indian region. Different approaches to simulating tropical cyclones Titli and Fani are demonstrated. It is shown that results are sensitive to the way in which the ocean response to cyclone evolution is captured in the system. Notably, we show how a more rigorous formulation for the near-surface energy budget can be included when air-sea coupling is included.
David F. Baker, Emily Bell, Kenneth J. Davis, Joel F. Campbell, Bing Lin, and Jeremy Dobler
Geosci. Model Dev., 15, 649–668, https://doi.org/10.5194/gmd-15-649-2022, https://doi.org/10.5194/gmd-15-649-2022, 2022
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The OCO-2 satellite measures many closely spaced column-averaged CO2 values around its orbit. To give these data proper weight in flux inversions, their error correlations must be accounted for. Here we lay out a 1-D error model with correlations that die out exponentially along-track to do so. A correlation length scale of ∼20 km is derived from column CO2 measurements from an airborne lidar flown underneath OCO-2 for use in this model. The model's performance is compared to previous ones.
Matthias Göbel, Stefano Serafin, and Mathias W. Rotach
Geosci. Model Dev., 15, 669–681, https://doi.org/10.5194/gmd-15-669-2022, https://doi.org/10.5194/gmd-15-669-2022, 2022
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We present WRFlux, an open-source software that allows numerically consistent, time-averaged budget evaluation of prognostic variables for the numerical weather prediction model WRF as well as the transformation of the budget equations from the terrain-following grid of the model to the Cartesian coordinate system. We demonstrate the performance and a possible application of WRFlux and illustrate the detrimental effects of approximations that are inconsistent with the model numerics.
Jingmin Li, Johannes Hendricks, Mattia Righi, and Christof G. Beer
Geosci. Model Dev., 15, 509–533, https://doi.org/10.5194/gmd-15-509-2022, https://doi.org/10.5194/gmd-15-509-2022, 2022
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The growing complexity of global aerosol models results in a large number of parameters that describe the aerosol number, size, and composition. This makes the analysis, evaluation, and interpretation of the model results a challenge. To overcome this difficulty, we apply a machine learning classification method to identify clusters of specific aerosol types in global aerosol simulations. Our results demonstrate the spatial distributions and characteristics of these identified aerosol clusters.
Jeong-Su Ko, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, Gregory Thompson, and Alexis Berne
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-417, https://doi.org/10.5194/gmd-2021-417, 2022
Revised manuscript accepted for GMD
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This study evaluates the performance of the four microphysics parameterizations, WDM6, WDM7, Thompson, and Morrison, in simulating snowfall events during the ICE-POP 2018 field campaign. Eight snowfall events, classified into three categories (cold-low, warm-low, and air-sea interaction), depending on the synoptic characteristics, are selected. The evaluation is conducted focusing on the simulated hydrometeors, microphysics budgets, wind fields, and precipitation using the measurement data.
Camilo Fernando Rodríguez Genó and Léster Alfonso
Geosci. Model Dev., 15, 493–507, https://doi.org/10.5194/gmd-15-493-2022, https://doi.org/10.5194/gmd-15-493-2022, 2022
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The representation of the collision–coalescence process in models of different scales has been a great source of uncertainty for many years. The aim of this paper is to show that machine learning techniques can be a useful tool in order to incorporate this process by emulating the explicit treatment of microphysics. Our results show that the machine learning parameterization mimics the evolution of actual droplet size distributions very well.
Li Zhang, Georg A. Grell, Stuart A. McKeen, Ravan Ahmadov, Karl D. Froyd, and Daniel Murphy
Geosci. Model Dev., 15, 467–491, https://doi.org/10.5194/gmd-15-467-2022, https://doi.org/10.5194/gmd-15-467-2022, 2022
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Applying the chemistry package from WRF-Chem into the Flow-following finite-volume Icosahedra Model, we essentially make it possible to explore the importance of different levels of complexity in gas and aerosol chemistry, as well as in physics parameterizations, for the interaction processes in global modeling systems. The model performance validated by the Atmospheric Tomography Mission aircraft measurements in summer 2016 shows good performance in capturing the aerosol and gas-phase tracers.
Qing Mu, Bruce Rolstad Denby, Eivind Grøtting Wærsted, and Hilde Fagerli
Geosci. Model Dev., 15, 449–465, https://doi.org/10.5194/gmd-15-449-2022, https://doi.org/10.5194/gmd-15-449-2022, 2022
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Our study has achieved air quality modelling down to 100 m for all of Europe. This solves the current problem that street-level air quality modelling is usually limited to individual cities. With publicly available downscaling proxy data, even regions without their own high-resolution proxy data can obtain air quality maps at 100 m. The work is of significance for air quality mitigation strategies and human health exposure studies.
Clara Betancourt, Timo T. Stomberg, Ann-Kathrin Edrich, Ankit Patnala, Martin G. Schultz, Ribana Roscher, Julia Kowalski, and Scarlet Stadtler
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-2, https://doi.org/10.5194/gmd-2022-2, 2022
Revised manuscript accepted for GMD
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Ozone is a toxic greenhouse gas with high spatial variability. We present a machine learning-based ozone mapping workflow generating a transparent and reliable product. Going beyond standard mapping methods, this work combines explainable machine learning with uncertainty assessment to increase the integrity of the produced map.
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Short summary
Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to select, add, and scale emissions from different sources through a configuration file with no change to the model source code. We demonstrate the implementation of HEMCO in several models, all sharing the same HEMCO core code and database library.
Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions...
