Articles | Volume 9, issue 2
Geosci. Model Dev., 9, 799–822, 2016
https://doi.org/10.5194/gmd-9-799-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 9, 799–822, 2016
https://doi.org/10.5194/gmd-9-799-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
26 Feb 2016
Development and technical paper
| 26 Feb 2016
The description and validation of the computationally Efficient CH4–CO–OH (ECCOHv1.01) chemistry module for 3-D model applications
Yasin F. Elshorbany et al.
Related authors
Hannah Meusel, Yasin Elshorbany, Uwe Kuhn, Thorsten Bartels-Rausch, Kathrin Reinmuth-Selzle, Christopher J. Kampf, Guo Li, Xiaoxiang Wang, Jos Lelieveld, Ulrich Pöschl, Thorsten Hoffmann, Hang Su, Markus Ammann, and Yafang Cheng
Atmos. Chem. Phys., 17, 11819–11833, https://doi.org/10.5194/acp-17-11819-2017, https://doi.org/10.5194/acp-17-11819-2017, 2017
Short summary
Short summary
In this study we investigated protein nitration and decomposition by light in the presence of NO2 via flow tube measurements. Nitrated proteins have an enhanced allergenic potential but so far nitration was only studied in dark conditions. Under irradiated conditions we found that proteins predominantly decompose while forming nitrous acid (HONO) an important precursor of the OH radical. Unlike other studies on heterogeneous NO2 conversion we found a stable HONO formation over a long period.
Y. F. Elshorbany, P. J. Crutzen, B. Steil, A. Pozzer, H. Tost, and J. Lelieveld
Atmos. Chem. Phys., 14, 1167–1184, https://doi.org/10.5194/acp-14-1167-2014, https://doi.org/10.5194/acp-14-1167-2014, 2014
Daniel C. Anderson, Melanie B. Follette-Cook, Sarah A. Strode, Julie M. Nicely, Junhua Liu, Peter D. Ivatt, and Bryan N. Duncan
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-44, https://doi.org/10.5194/gmd-2022-44, 2022
Preprint under review for GMD
Short summary
Short summary
The hydroxyl radical (OH) is the most important chemical in the atmosphere for removing certain pollutants, including methane, the second most important greenhouse gas. We present a methodology to create an easily modifiable parameterization that can calculate OH concentrations in a computationally efficient way. The parameterization, which predicts OH within 5 %, can be integrated into larger climate models to allow for calculation of the interactions between OH, methane, and other chemicals.
Daniel C. Anderson, Bryan N. Duncan, Arlene M. Fiore, Colleen B. Baublitz, Melanie B. Follette-Cook, Julie M. Nicely, and Glenn M. Wolfe
Atmos. Chem. Phys., 21, 6481–6508, https://doi.org/10.5194/acp-21-6481-2021, https://doi.org/10.5194/acp-21-6481-2021, 2021
Short summary
Short summary
We demonstrate that large-scale climate features are the primary driver of year-to-year variability in simulated values of the hydroxyl radical, the primary atmospheric oxidant, over 1980–2018. The El Niño–Southern Oscillation is the dominant mode of hydroxyl variability, resulting in large-scale global decreases in OH during El Niño events. Other climate modes, such as the Australian monsoon and the North Atlantic Oscillation, have impacts of similar magnitude but on on more localized scales.
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
Short summary
Short summary
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.
Julie M. Nicely, Bryan N. Duncan, Thomas F. Hanisco, Glenn M. Wolfe, Ross J. Salawitch, Makoto Deushi, Amund S. Haslerud, Patrick Jöckel, Béatrice Josse, Douglas E. Kinnison, Andrew Klekociuk, Michael E. Manyin, Virginie Marécal, Olaf Morgenstern, Lee T. Murray, Gunnar Myhre, Luke D. Oman, Giovanni Pitari, Andrea Pozzer, Ilaria Quaglia, Laura E. Revell, Eugene Rozanov, Andrea Stenke, Kane Stone, Susan Strahan, Simone Tilmes, Holger Tost, Daniel M. Westervelt, and Guang Zeng
Atmos. Chem. Phys., 20, 1341–1361, https://doi.org/10.5194/acp-20-1341-2020, https://doi.org/10.5194/acp-20-1341-2020, 2020
Short summary
Short summary
Differences in methane lifetime among global models are large and poorly understood. We use a neural network method and simulations from the Chemistry Climate Model Initiative to quantify the factors influencing methane lifetime spread among models and variations over time. UV photolysis, tropospheric ozone, and nitrogen oxides drive large model differences, while the same factors plus specific humidity contribute to a decreasing trend in methane lifetime between 1980 and 2015.
Fei Liu, Bryan N. Duncan, Nickolay A. Krotkov, Lok N. Lamsal, Steffen Beirle, Debora Griffin, Chris A. McLinden, Daniel L. Goldberg, and Zifeng Lu
Atmos. Chem. Phys., 20, 99–116, https://doi.org/10.5194/acp-20-99-2020, https://doi.org/10.5194/acp-20-99-2020, 2020
Short summary
Short summary
We present a novel method to infer CO2 emissions from individual power plants, based on satellite observations of co-emitted NO2. We find that the CO2 emissions estimated by our satellite-based method during 2005–2017 are in reasonable agreement with the CEMS measurements for US power plants. The broader implication of our methodology is that it has the potential to provide an additional constraint on CO2 emissions from power plants in regions of the world without reliable emissions accounting.
Paul I. Palmer, Emily L. Wilson, Geronimo L. Villanueva, Giuliano Liuzzi, Liang Feng, Anthony J. DiGregorio, Jianping Mao, Lesley Ott, and Bryan Duncan
Atmos. Meas. Tech., 12, 2579–2594, https://doi.org/10.5194/amt-12-2579-2019, https://doi.org/10.5194/amt-12-2579-2019, 2019
Short summary
Short summary
We describe the potential impact of a new, low-cost, portable ground instrument (the mini-LHR) that measures methane and carbon dioxide in the atmospheric column. This region is key in quantifying the global carbon budget but has geographical gaps in measurements left by ground-based networks and space-based observations. A deployment of 50 mini-LHRs would add new data products in the Amazon, the Arctic, and southern Asia and significantly improve knowledge of regional and global carbon budgets.
Arlene M. Fiore, Emily V. Fischer, George P. Milly, Shubha Pandey Deolal, Oliver Wild, Daniel A. Jaffe, Johannes Staehelin, Olivia E. Clifton, Dan Bergmann, William Collins, Frank Dentener, Ruth M. Doherty, Bryan N. Duncan, Bernd Fischer, Stefan Gilge, Peter G. Hess, Larry W. Horowitz, Alexandru Lupu, Ian A. MacKenzie, Rokjin Park, Ludwig Ries, Michael G. Sanderson, Martin G. Schultz, Drew T. Shindell, Martin Steinbacher, David S. Stevenson, Sophie Szopa, Christoph Zellweger, and Guang Zeng
Atmos. Chem. Phys., 18, 15345–15361, https://doi.org/10.5194/acp-18-15345-2018, https://doi.org/10.5194/acp-18-15345-2018, 2018
Short summary
Short summary
We demonstrate a proof-of-concept approach for applying northern midlatitude mountaintop peroxy acetyl nitrate (PAN) measurements and a multi-model ensemble during April to constrain the influence of continental-scale anthropogenic precursor emissions on PAN. Our findings imply a role for carefully coordinated multi-model ensembles in helping identify observations for discriminating among widely varying (and poorly constrained) model responses of atmospheric constituents to changes in emissions.
James S. Wang, S. Randolph Kawa, G. James Collatz, Motoki Sasakawa, Luciana V. Gatti, Toshinobu Machida, Yuping Liu, and Michael E. Manyin
Atmos. Chem. Phys., 18, 11097–11124, https://doi.org/10.5194/acp-18-11097-2018, https://doi.org/10.5194/acp-18-11097-2018, 2018
Short summary
Short summary
We used measurements of CO2 in the atmosphere from the GOSAT satellite and from surface sites around the world, together with a transport model and a unique estimation technique, to quantify CO2 sources and removals over a recent period. We find that climate variations can strongly influence uptake by vegetation and release in decay and fires. However, regional gaps in observations and inaccuracies to which current satellite technology is susceptible result in important estimation biases.
Pieternel F. Levelt, Joanna Joiner, Johanna Tamminen, J. Pepijn Veefkind, Pawan K. Bhartia, Deborah C. Stein Zweers, Bryan N. Duncan, David G. Streets, Henk Eskes, Ronald van der A, Chris McLinden, Vitali Fioletov, Simon Carn, Jos de Laat, Matthew DeLand, Sergey Marchenko, Richard McPeters, Jerald Ziemke, Dejian Fu, Xiong Liu, Kenneth Pickering, Arnoud Apituley, Gonzalo González Abad, Antti Arola, Folkert Boersma, Christopher Chan Miller, Kelly Chance, Martin de Graaf, Janne Hakkarainen, Seppo Hassinen, Iolanda Ialongo, Quintus Kleipool, Nickolay Krotkov, Can Li, Lok Lamsal, Paul Newman, Caroline Nowlan, Raid Suleiman, Lieuwe Gijsbert Tilstra, Omar Torres, Huiqun Wang, and Krzysztof Wargan
Atmos. Chem. Phys., 18, 5699–5745, https://doi.org/10.5194/acp-18-5699-2018, https://doi.org/10.5194/acp-18-5699-2018, 2018
Short summary
Short summary
The aim of this paper is to highlight the many successes of the Ozone Monitoring Instrument (OMI) spanning more than 13 years. Data from OMI have been used in a wide range of applications. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. OMI data continue to be used for new research and applications.
Hannah Meusel, Yasin Elshorbany, Uwe Kuhn, Thorsten Bartels-Rausch, Kathrin Reinmuth-Selzle, Christopher J. Kampf, Guo Li, Xiaoxiang Wang, Jos Lelieveld, Ulrich Pöschl, Thorsten Hoffmann, Hang Su, Markus Ammann, and Yafang Cheng
Atmos. Chem. Phys., 17, 11819–11833, https://doi.org/10.5194/acp-17-11819-2017, https://doi.org/10.5194/acp-17-11819-2017, 2017
Short summary
Short summary
In this study we investigated protein nitration and decomposition by light in the presence of NO2 via flow tube measurements. Nitrated proteins have an enhanced allergenic potential but so far nitration was only studied in dark conditions. Under irradiated conditions we found that proteins predominantly decompose while forming nitrous acid (HONO) an important precursor of the OH radical. Unlike other studies on heterogeneous NO2 conversion we found a stable HONO formation over a long period.
Hyun-Deok Choi, Hongyu Liu, James H. Crawford, David B. Considine, Dale J. Allen, Bryan N. Duncan, Larry W. Horowitz, Jose M. Rodriguez, Susan E. Strahan, Lin Zhang, Xiong Liu, Megan R. Damon, and Stephen D. Steenrod
Atmos. Chem. Phys., 17, 8429–8452, https://doi.org/10.5194/acp-17-8429-2017, https://doi.org/10.5194/acp-17-8429-2017, 2017
Short summary
Short summary
We evaluate global ozone–carbon monoxide (O3–CO) correlations in a chemistry and transport model during July–August with TES-Aura satellite observations and examine the sensitivity of model simulations to input meteorological data and emissions. Results show that O3–CO correlations may be used effectively to constrain the sources of regional tropospheric O3 in global 3-D models, especially for those regions where convective transport of pollution plays an important role.
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
Short summary
Short summary
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.
Hongyu Liu, David B. Considine, Larry W. Horowitz, James H. Crawford, Jose M. Rodriguez, Susan E. Strahan, Megan R. Damon, Stephen D. Steenrod, Xiaojing Xu, Jules Kouatchou, Claire Carouge, and Robert M. Yantosca
Atmos. Chem. Phys., 16, 4641–4659, https://doi.org/10.5194/acp-16-4641-2016, https://doi.org/10.5194/acp-16-4641-2016, 2016
Short summary
Short summary
We assess the utility of cosmogenic beryllium-7, a natural aerosol tracer, for evaluating cross-tropopause transport in global models. We show that model excessive cross-tropopause transport of beryllium-7 corresponds to overestimated stratospheric contribution to tropospheric ozone. We conclude that the observational constraints for beryllium-7 and observed beryllium-7 total deposition fluxes can be used routinely as a first-order assessment of cross-tropopause transport in global models.
Nickolay A. Krotkov, Chris A. McLinden, Can Li, Lok N. Lamsal, Edward A. Celarier, Sergey V. Marchenko, William H. Swartz, Eric J. Bucsela, Joanna Joiner, Bryan N. Duncan, K. Folkert Boersma, J. Pepijn Veefkind, Pieternel F. Levelt, Vitali E. Fioletov, Russell R. Dickerson, Hao He, Zifeng Lu, and David G. Streets
Atmos. Chem. Phys., 16, 4605–4629, https://doi.org/10.5194/acp-16-4605-2016, https://doi.org/10.5194/acp-16-4605-2016, 2016
Short summary
Short summary
We examine changes in SO2 and NO2 over the world's most polluted regions during the first decade of Aura OMI observations. Over the eastern US, both NO2 and SO2 levels decreased by 40 % and 80 %, respectively. OMI confirmed large reductions in SO2 over eastern Europe's largest coal power plants. The North China Plain has the world's most severe SO2 pollution, but a decreasing trend been observed since 2011, with a 50 % reduction in 2012–2014. India's SO2 and NO2 levels are growing at a fast pace.
S. A. Strode, B. N. Duncan, E. A. Yegorova, J. Kouatchou, J. R. Ziemke, and A. R. Douglass
Atmos. Chem. Phys., 15, 11789–11805, https://doi.org/10.5194/acp-15-11789-2015, https://doi.org/10.5194/acp-15-11789-2015, 2015
Short summary
Short summary
A low bias in carbon monoxide (CO) at northern latitudes is a common feature of chemistry climate models. We find that increasing Northern Hemisphere (NH) CO emissions or reducing NH OH concentrations improves the agreement with CO surface observations, but reducing NH OH leads to a better comparison with MOPITT. Removing model biases in ozone and water vapor increases the simulated methane lifetime, but it does not give the 20% reduction in NH OH suggested by our analysis of the CO bias.
Z. Lu, D. G. Streets, B. de Foy, L. N. Lamsal, B. N. Duncan, and J. Xing
Atmos. Chem. Phys., 15, 10367–10383, https://doi.org/10.5194/acp-15-10367-2015, https://doi.org/10.5194/acp-15-10367-2015, 2015
Short summary
Short summary
Using an exponentially modified Gaussian method and taking into account the effect of wind on NO2 distributions, we estimate 3-year moving-average emissions of summertime NOx from 35 US urban areas directly from NO2 retrievals of the OMI during 2005−2014. Total OMI-derived NOx emissions over US urban areas decreased by 49%, consistent with reductions of 43, 49, and 44% in the bottom-up NOx emissions, the weak-wind OMI NO2 burdens, and the averaged NO2 concentrations, respectively.
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
Short summary
Short summary
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
Short summary
Short summary
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. 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
Short summary
Short summary
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. S. Wang, S. R. Kawa, J. Eluszkiewicz, D. F. Baker, M. Mountain, J. Henderson, T. Nehrkorn, and T. S. Zaccheo
Atmos. Chem. Phys., 14, 12897–12914, https://doi.org/10.5194/acp-14-12897-2014, https://doi.org/10.5194/acp-14-12897-2014, 2014
Short summary
Short summary
Our simulations suggest that CO2 measurements by the planned ASCENDS satellite could improve estimates of emissions and uptake by up to 50% at the weekly 1° by 1° scale, 40-75% at the annual biome scale, and 65-85% for the whole of North America. The results depend on the laser wavelength used and the assumed precision of the measurements. The resulting biome flux uncertainties, 0.01-0.06 billion tons of C per year, would satisfy one definition of mission success.
S. Choi, J. Joiner, Y. Choi, B. N. Duncan, A. Vasilkov, N. Krotkov, and E. Bucsela
Atmos. Chem. Phys., 14, 10565–10588, https://doi.org/10.5194/acp-14-10565-2014, https://doi.org/10.5194/acp-14-10565-2014, 2014
Y. F. Elshorbany, P. J. Crutzen, B. Steil, A. Pozzer, H. Tost, and J. Lelieveld
Atmos. Chem. Phys., 14, 1167–1184, https://doi.org/10.5194/acp-14-1167-2014, https://doi.org/10.5194/acp-14-1167-2014, 2014
J. X. Warner, R. Yang, Z. Wei, F. Carminati, A. Tangborn, Z. Sun, W. Lahoz, J.-L. Attié, L. El Amraoui, and B. Duncan
Atmos. Chem. Phys., 14, 103–114, https://doi.org/10.5194/acp-14-103-2014, https://doi.org/10.5194/acp-14-103-2014, 2014
Related subject area
Atmospheric sciences
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
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
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
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
WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America
Evaluation of the COSMO model (v5.1) in polarimetric radar space – impact of uncertainties in model microphysics, retrievals and forward operators
Development of aerosol optical properties for improving the MESSy photolysis module in the GEM-MACH v2.4 air quality model and application for calculating photolysis rates in a biomass burning plume
The sensitivity of simulated aerosol climatic impact to domain size using regional model (WRF-Chem v3.6)
WOMBAT v1.0: a fully Bayesian global flux-inversion framework
Modelling the High Mercury Wet deposition in the Southeastern US by WRF-GC
Analysis of the MODIS above-cloud aerosol retrieval algorithm using MCARS
A novel method for objective identification of 3-D potential vorticity anomalies
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Almudena García-García, Francisco José Cuesta-Valero, Hugo Beltrami, J. Fidel González-Rouco, and Elena García-Bustamante
Geosci. Model Dev., 15, 413–428, https://doi.org/10.5194/gmd-15-413-2022, https://doi.org/10.5194/gmd-15-413-2022, 2022
Short summary
Short summary
We study the sensitivity of a regional climate model to resolution and soil scheme changes. Our results show that the use of finer resolutions mainly affects precipitation outputs, particularly in summer due to changes in convective processes. Finer resolutions are associated with larger biases compared with observations. Changing the land surface model scheme affects the simulation of near-surface temperatures, yielding the lowest biases in mean temperature with the most complex soil scheme.
Prabhakar Shrestha, Jana Mendrok, Velibor Pejcic, Silke Trömel, Ulrich Blahak, and Jacob T. Carlin
Geosci. Model Dev., 15, 291–313, https://doi.org/10.5194/gmd-15-291-2022, https://doi.org/10.5194/gmd-15-291-2022, 2022
Short summary
Short summary
The article focuses on the exploitation of radar polarimetry for model evaluation of stratiform precipitation. The model exhibited a low bias in simulated polarimetric moments at lower levels above the melting layer where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g. fragmentation due to ice–ice collisions) and use of more reliable snow-scattering models in the forward operator to draw valid conclusions.
Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen
Geosci. Model Dev., 15, 219–249, https://doi.org/10.5194/gmd-15-219-2022, https://doi.org/10.5194/gmd-15-219-2022, 2022
Short summary
Short summary
A new lookup table for aerosol optical properties based on a Mie scattering code was calculated and adopted within an improved version of the photolysis module in the GEM-MACH in-line chemical transport model. The modified version of the photolysis module makes use of online interactive aerosol feedback and applies core-shell parameterizations to the black carbon absorption efficiency based on Bond et al. (2006) to the size bins with black carbon mass fraction of less than 40 %.
Xiaodong Wang, Chun Zhao, Mingyue Xu, Qiuyan Du, Jianqiu Zheng, Yun Bi, Shengfu Lin, and Yali Luo
Geosci. Model Dev., 15, 199–218, https://doi.org/10.5194/gmd-15-199-2022, https://doi.org/10.5194/gmd-15-199-2022, 2022
Short summary
Short summary
Regional models are widely used to investigate aerosol climatic impacts. However, there are few studies examining the sensitivities of modeling results to regional domain size. In this study, the regional model is used to study the aerosol impacts on the East Asian summer monsoon system and focus on the modeling sensitivities to domain size. This study highlights the important impacts of domain size on regional modeling results of aerosol climatic impacts, which may not be limited to East Asia.
Andrew Zammit-Mangion, Michael Bertolacci, Jenny Fisher, Ann Stavert, Matthew Rigby, Yi Cao, and Noel Cressie
Geosci. Model Dev., 15, 45–73, https://doi.org/10.5194/gmd-15-45-2022, https://doi.org/10.5194/gmd-15-45-2022, 2022
Short summary
Short summary
We present a framework for estimating the sources and sinks (flux) of carbon dioxide from satellite data. The framework is statistical and yields measures of uncertainty alongside all estimates of flux and other parameters in the underlying model. It also allows us to generate other insights, such as the size of errors and biases in the data. The primary aim of this research was to develop a fully statistical flux inversion framework for use by atmospheric scientists.
Xiaotian Xu, Xu Feng, Haipeng Lin, Peng Zhang, Shaojian Huang, Zhengcheng Song, Yiming Peng, Tzung-May Fu, and Yanxu Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-404, https://doi.org/10.5194/gmd-2021-404, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
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 mode with capability of mercury simulation to study this problem. In this research, we conclude that it is the deep convection caused enhanced mercury wet deposition in the southeastern United States.
Galina Wind, Arlindo M. da Silva, Kerry G. Meyer, Steven Platnick, and Peter M. Norris
Geosci. Model Dev., 15, 1–14, https://doi.org/10.5194/gmd-15-1-2022, https://doi.org/10.5194/gmd-15-1-2022, 2022
Short summary
Short summary
This is the third paper in series about the Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In this paper we use MCARS to create a set of constraints that might be used to assimilate a new above-cloud aerosol retrieval product developed for the MODIS instrument into a general circulation model. We executed the above-cloud aerosol retrieval over a series of synthetic MODIS granules and found the product to be of excellent quality.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Roderick van der Linden, Michael Maier-Gerber, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-424, https://doi.org/10.5194/gmd-2021-424, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
Potential vorticity (PV) analysis plays a central role in studying atmospheric dynamics. For example, anomalies in the PV field near the tropopause are linked to extreme weather events. In this study, an objective strategy to identify these anomalies is presented and evaluated. As novel concept, it can be applied to three-dimensional (3-D) data sets. Supported by 3-D visualizations, we illustrate and showcase upsides and potential of this new analysis over existing studies along a case study.
Cited articles
Amnuaylojaroen, T., Barth, M. C., Emmons, L. K., Carmichael, G. R., Kreasuwun, J., Prasitwattanaseree, S., and Chantara, S.: Effect of different emission inventories on modeled
ozone and carbon monoxide in Southeast Asia, Atmos. Chem. Phys., 14, 12983–13012, https://doi.org/10.5194/acp-14-12983-2014, 2014.
Bousquet, P., Ciais, P., Miller, J. B., Dlugokencky, E. J., Hauglustaine,
D. A., Prigent, C., Van der Werf, G. R., Peylin, P., Brunke, E. G., Carouge,
C., Langenfelds, R. L., Lathiere, J., Papa, F., Ramonet, M., Schmidt, M.,
Steele, L. P., Tyler, S. C., and White, J.: Contribution of anthropogenic and
natural sources to atmospheric methane variability, Nature, 443, 439–443,
2006.
Bovensmann, H., Burrows, J. P., Buchwitz, M., Frerick, J., Noël, S., Rozanov, V. V., Chance, K. V., and Goede, A.: SCIAMACHY – Mission Objectives and measurement Modes, J. Atmos. Sci., 56,
127–150, 1999.
Chameides, W., Liu, S. C., and Cicerone, R. J.: Possible variations in
atmospheric methane, J. Geophys. Res., 81, 4997–5001, 1976.
Chen, Y.-H. and Prinn, R. G.: Estimation of atmospheric methane emissions between 1996 and 2001 using a three-dimensional global chemical transport model, J. Geophys. Res., 111, D10307, https://doi.org/10.1029/2005JD006058, 2006.
Deeter, M. N.: MOPITT (Measurement of Pollution in the Troposphere) Version6
Product User's Guide, available at:
http://www2.acd.ucar.edu/sites/default/files/mopitt/v6_users_guide_201309.pdf
(last access: 28 May 2015), 2013.
Deeter, M. N., Worden, H. M., Edwards, D. P., Gille, J. C., and Andrews, A.
E.: Evaluation of MOPITT retrievals of lower tropospheric carbon monoxide
over the United States, J. Geophys. Res., 117, D13306,
https://doi.org/10.1029/2012JD017553, 2012.
Dlugokencky, E. J., Lang, P. M., and Masarie, K. A.: Atmospheric Methane Dry
Air Mole Fractions from the NOAA ESRL Carbon Cycle Cooperative Global Air
Sampling Network, 1983–2014, Version: 2015-08-03, available at: ftp://aftp.cmdl.noaa.gov/data/trace_gases/ch4/flask/surface, last access: 22 February 2016.
Dlugokencky, E. J., Lang, P. M., Crotwell, A. M., Masarie, K. A., and Crotwell,
M. J.: Atmospheric Methane Dry Air Mole Fractions from the NOAA ESRL Carbon
Cycle, Cooperative Global Air Sampling Network, 1983–2013, Version:
2014-06-24, 2014.
Duncan, B. N. and Logan, J. A.: Model analysis of the factors regulating the
trends and variability of carbon monoxide between 1988 and 1997, Atmos. Chem.
Phys., 8, 7389–7403, https://doi.org/10.5194/acp-8-7389-2008, 2008.
Duncan, B. N., Martin, R. V., Staudt, A. C., Yevich, R. M., and Logan, J.
A.: Interannual and Seasonal Variability of Biomass Burning Emissions
Constrained by Satellite Observations, J. Geophys. Res., 108, 4040,
https://doi.org/10.1029/2002JD002378, 2003a.
Duncan, B. N., Bey, I., Chin, M., Mickley, L. J., Fairlie, T. D., Martin, R. V., and
Matsueda, H.: Indonesian Wildfires of 1997: Impact on Tropospheric Chemistry,
J. Geophys. Res., 108, 4458, https://doi.org/10.1029/2002JD003195, 2003b.
Duncan, B. N., Logan, J. A., Bey, I., Megretskaia, I. A., Yantosca, R. M.,
Novelli, P. C., Jones, N. B., and Rinsland, C. P.: Global budget of CO,
1988–1997: Source estimates and validation with a global model, J. Geophys.
Res., 112, D22301, https://doi.org/10.1029/2007JD008459, 2007a.
Elshorbany, Y. F., Kleffmann, J., Hofzumahaus, A., Kurtenbach, R., Wiesen,
P., Dorn,H.-P., Schlosser, E., Brauers, T., Fuchs, H., Rohrer, F., Wahner,
A., Kanaya, Y., Yoshino, A., Nishida, S., Kajii, Y., Martinez, M., Rudolf,
M., Harder, H., Lelieveld, J., Elste, T., Plass-Dülmer, C., Stange, G.,
and Berresheim, H.: HOx Budgets during HOxComp: a Case Study of HOx
Chemistry under NOx limited Conditions, J. Geoophys. Res., 117, D03307,
https://doi.org/10.1029/2011JD017008, 2012a.
Elshorbany, Y. F., Steil, B., Brühl, C., and Lelieveld, J.: Impact of HONO
on global atmospheric chemistry calculated with an empirical parameterization
in the EMAC model, Atmos. Chem. Phys., 12, 9977–10000,
https://doi.org/10.5194/acp-12-9977-2012, 2012b.
Elshorbany, Y. F., Crutzen, P. J., Steil, B., Pozzer, A., Tost, H., and
Lelieveld, J.: Global and regional impacts of HONO on the chemical
composition of clouds and aerosols, Atmos. Chem. Phys., 14, 1167–1184,
https://doi.org/10.5194/acp-14-1167-2014, 2014.
Fiore, A. M., Jacob, D. J., Field, B. D., Streets, D. G., Fernandes, S. D.,
and Jang, C.: Linking air pollution and climate change: The case for
controlling methane, Geophys. Res. Lett., 29, 1919, https://doi.org/10.1029/2002GL015601,
2002.
Fiore, A. M., Horowitz, L. W., Dlugokencky, E. J., and West, J. J.: Impact of
meteorology and emissions on methane trends, 1990–2004, Geophys. Res. Lett.,
33, L12809, https://doi.org/10.1029/2006GL026199, 2006.
Fiore, A. M., Dentener, F. J., Wild, O., Cuvelier, C., Schultz, M. G., Hess,
P., Textor, C., Schulz, M., Doherty, R. M., Horowitz, L. W., MacKenzie, I.
A., Sanderson, M. G., Shindell, D. T., Stevenson, D. S., Szopa, S., Van
Dingenen, R., Zeng, G., Atherton, C., Bergmann, D., Bey, I., Carmichael, G.,
Collins, W. J., Duncan, B. N., Faluvegi, G., Folberth, G., Gauss, M., Gong,
S., Hauglustaine, D., Holloway, T., Isaksen, I. S. A., Jacob, D. J., Jonson,
J. E., Kaminski, J. W., Keating, T. J., Lupu, A., Marmer, E., Montanaro, V.,
Park, R. J., Pitari, G., Pringle, K. J., Pyle, J. A., Schroeder, S., Vivanco,
M. G., Wind, P., Wojcik, G., Wu, S., and Zuber, A.: Multimodel estimates of
intercontinental source-receptor relationships for ozone pollution, J.
Geophys. Res., 114, D04301, https://doi.org/10.1029/2008JD010816, 2009.
Frankenberg, C., Aben, I., Bergamaschi, P., Dlugokencky, E. J., van Hees,
R., Houweling, S., van der Meer, P., Snel, R., and Tol, P.: Global
column-averaged methane mixing ratios from 2003 to 2009 as derived from
SCIAMACHY: Trends and variability, J. of Geophys. Res., 116, D04302,
https://doi.org/10.1029/2010JD014849, 2011.
Fuchs, H., Hofzumahaus, A., Rohrer, F., Bohn, B., Brauers, T., Dorn, H.-P.,
Hasseler, R., Holland, F., Kaminski, M., Li, X., Lu, K., Nehr, S.,
Tillmann, R., Wegener, R., and Wahner, A.: Experimental evidence for
efficient hydroxyl radical regeneration in isoprene oxidation, Nat. Geosci.
6, 1023–1026, https://doi.org/10.1038/ngeo1964, 2013.
Fujino, J., Nair, R., Kainuma, M., Masui, T., and Matsuoka, Y.: Multigas mitigation
analysis on stabilization scenarios using aim global model, Energy J.,
Special issue, 3, 343–354, 2006.
Giglio, L., Randerson, J. T., van der Werf, G. R., Kasibhatla, P. S.,
Collatz, G. J., Morton, D. C., and DeFries, R. S.: Assessing variability and
long-term trends in burned area by merging multiple satellite fire products,
Biogeosciences, 7, 1171–1186, https://doi.org/10.5194/bg-7-1171-2010, 2010.
Gloudemans, A. M. S., Schrijver, H., Hasekamp, O. P., and Aben, I.: Error
analysis for CO and CH4 total column retrievals from SCIAMACHY
2.3 µm spectra, Atmos. Chem. Phys., 8, 3999–4017,
https://doi.org/10.5194/acp-8-3999-2008, 2008.
Hijioka, Y., Matsuoka, Y., Nishimoto, H., Masui, T., and Kainuma, M.: Global GHG emission
scenarios under GHG concentration stabilization targets, J. Glob. Environ.
Eng., 13, 97–108, 2008.
Ho, S.-P., Edwards, D. P., Gille, J. C., Luo, M., Osterman, G. B., Kulawik,
S. S., and Worden, H.: A global comparison of carbon monoxide profiles and
column amounts from Tropospheric Emission Spectrometer (TES) and Measurements
of Pollution in the Troposphere (MOPITT), J. Geophys. Res., 114, D21307,
https://doi.org/10.1029/2009JD012242, 2009.
Holmes, C. D., Prather, M. J., Søvde, O. A., and Myhre, G.: Future methane,
hydroxyl, and their uncertainties: key climate and emission parameters for
future predictions, Atmos. Chem. Phys., 13, 285–302,
https://doi.org/10.5194/acp-13-285-2013, 2013.
Houweling, S., Krol, M., Bergamaschi, P., Frankenberg, C., Dlugokencky, E.
J., Morino, I., Notholt, J., Sherlock, V., Wunch, D., Beck, V., Gerbig, C.,
Chen, H., Kort, E. A., Röckmann, T., and Aben, I.: A multi-year methane
inversion using SCIAMACHY, accounting for systematic errors using TCCON
measurements, Atmos. Chem. Phys., 14, 3991–4012,
https://doi.org/10.5194/acp-14-3991-2014, 2014.
Kirschke, S., Bousquet, P., Ciais, P., Saunois, M., Canadell, J. G., Dlugokencky, E. J., Bergamaschi,
P., Bergmann, D., Blake, D. R., Bruhwiler, L., Cameron-Smith, P., Castaldi, S., Chevallier,
F., Feng, L., Fraser, A., Heimann, M., Hodson, E. L., Houweling, S., Josse, B., Fraser, P.
J., Krummel, P. B., Lamarque, J.-F., Langenfelds, R. L., Le Quéré, C., Naik, V., O'Doherty, S.,
15 Palmer, P. I., Pison, I., Plummer, D., Poulter, B., Prinn, R. G., Rigby, M., Ringeval, B., Santini,
M., Schmidt, M., Shindell, D. T., Simpson, I. J., Spahni, R., Steele, L. P., Strode, S. A., Sudo,
K., Szopa, S., van der Werf, G. R., Voulgarakis, A., van Weele, M., Weiss, R. F., Williams,
J. E., and Zeng, G.: Three decades of global methane sources and sinks, Nat. Geosci., 6,
813–823, https://doi.org/10.1038/ngeo1955, 2013.
Lamarque, J.-F., Shindell, D. T., Josse, B., Young, P. J., Cionni, I.,
Eyring, V., Bergmann, D., Cameron-Smith, P., Collins, W. J., Doherty, R.,
Dalsoren, S., Faluvegi, G., Folberth, G., Ghan, S. J., Horowitz, L. W., Lee,
Y. H., MacKenzie, I. A., Nagashima, T., Naik, V., Plummer, D., Righi, M.,
Rumbold, S. T., Schulz, M., Skeie, R. B., Stevenson, D. S., Strode, S., Sudo,
K., Szopa, S., Voulgarakis, A., and Zeng, G.: The Atmospheric Chemistry and
Climate Model Intercomparison Project (ACCMIP): overview and description of
models, simulations and climate diagnostics, Geosci. Model Dev., 6, 179–206,
https://doi.org/10.5194/gmd-6-179-2013, 2013.
Lawrence, M. G., Jöckel, P., and von Kuhlmann, R.: What does the global
mean OH concentration tell us?, Atmos. Chem. Phys., 1, 37–49,
https://doi.org/10.5194/acp-1-37-2001, 2001.
Lelieveld, J., Peters, W., Dentener, F. J., and Krol, M. C.: Stability of
tropospheric hydroxyl chemistry, J. Geophys. Res., 107, 4715,
https://doi.org/10.1029/2002JD002272, 2002.
Lin, S.-J.: A “vertically Lagrangian” finite-volume dynamical core for
global models, Mon. Weather Rev., 132, 2293–2307, 2004.
Luo, M., Read, W., Kulawik, S., Worden, J., Livesey, N., Bowman, K., and
Herman, R.: Carbon monoxide (CO) vertical profiles derived from joined TES
and MLS measurements, J. Geophys. Res. Atmos., 118, 10601–10613,
https://doi.org/10.1002/jgrd.50800, 2013.
Molod, A., Takacs, L., Suarez, M., Bacmeister, J., Song, I.-S., and
Eichmann, A.: The GEOS-5 Atmospheric General Circulation Model: Mean Climate
and Development from MERRA to Fortuna, NASA/TM–2012-104606, Technical Report
Series on Global Modeling and Data Assimilation, edited by: Suarez, M., Vol.
28, available at: http://gmao.gsfc.nasa.gov/pubs/docs/tm28.pdf (last
access: 27 October 2015), 2012.
Monks, S. A., Arnold, S. R., Emmons, L. K., Law, K. S., Turquety, S., Duncan,
B. N., Flemming, J., Huijnen, V., Tilmes, S., Langner, J., Mao, J., Long, Y.,
Thomas, J. L., Steenrod, S. D., Raut, J. C., Wilson, C., Chipperfield, M. P.,
Diskin, G. S., Weinheimer, A., Schlager, H., and Ancellet, G.: Multi-model
study of chemical and physical controls on transport of anthropogenic and
biomass burning pollution to the Arctic, Atmos. Chem. Phys., 15, 3575–3603,
https://doi.org/10.5194/acp-15-3575-2015, 2015.
Montzka, S. A., Krol, M., Dlugokencky, E., Hall, B., Joeckel, P., and
Lelieveld, J.: Small interannual variability of global atmospheric hydroxyl,
Science, 331, 67–69, https://doi.org/10.1126/science.1197640, 2011.
Murray, L. T., Logan, J. A., and Jacob, D. J.: Interannual variability in
tropical tropospheric ozone and OH: The role of lightning, J. Geophys. Res.
Atmos., 118, 11468–11480, https://doi.org/10.1002/jgrd.50857, 2013.
Myhre, G., Shindell, D., Breìon, F.-M., Collins, W., Fuglestvedt, J.,
Huang, J., Koch, D., Lamarque, J.-F., Lee, D.,
Mendoza, B., Nakajima, T., Robock, A., Stephens, G., Takemura, T., and Zhang,
H.: Anthropogenic and natural radiative forcing, in: Climate Change 2013: The
Physical Science Basis. Contribution of Working Group I to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change, edited
by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K.,
Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., availa1able
at: http://www.climatechange2013.org/images/report/WG1AR5_ALL_FINAL.pdf
(last access: 27 October 2015), 2013.
Naik, V., Voulgarakis, A., Fiore, A. M., Horowitz, L. W., Lamarque, J.-F.,
Lin, M., Prather, M. J., Young, P. J., Bergmann, D., Cameron-Smith, P. J.,
Cionni, I., Collins, W. J., Dalsøren, S. B., Doherty, R., Eyring, V.,
Faluvegi, G., Folberth, G. A., Josse, B., Lee, Y. H., MacKenzie, I. A.,
Nagashima, T., van Noije, T. P. C., Plummer, D. A., Righi, M., Rumbold, S.
T., Skeie, R., Shindell, D. T., Stevenson, D. S., Strode, S., Sudo, K.,
Szopa, S., and Zeng, G.: Preindustrial to present-day changes in tropospheric
hydroxyl radical and methane lifetime from the Atmospheric Chemistry and
Climate Model Intercomparison Project (ACCMIP), Atmos. Chem. Phys., 13,
5277–5298, https://doi.org/10.5194/acp-13-5277-2013, 2013.
Novelli, P., Steele, P., and Tans, P. P.: Mixing ratios of carbon monoxide in
the troposphere, J. Geophys. Res., 102, 12855–12861, https://doi.org/10.1029/92JD02010,
1992.
Novelli, P., Masarie, K. A., and Lang, P. M.: Distributions and recent changes
in carbon monoxide in the lower troposphere, J. Geosphys. Res., 103,
19015–19033, 1998.
Oman, L. D., Ziemke, J. R., Douglass, A. R., Waugh, D. W., Lang, C.,
Rodriguez, J. M., and Nielsen, J. E.: The response of tropical tropospheric
ozone to ENSO, Geophys. Res. Lett., 38, L13706, https://doi.org/10.1029/2011GL047865,
2011.
Ott, L., Duncan, B., Pawson, S., Colarco, P., Chin, M., Randles, C., Diehl,
T., and Nielsen, E.: Influence of the 2006 Indonesian biomass burning
aerosols on tropical dynamics studied with the GEOS5 AGCM, J. Geophys. Res.,
115, D14121, https://doi.org/10.1029/2009JD013181, 2010.
Patra, P. K., Houweling, S., Krol, M., Bousquet, P., Belikov, D., Bergmann,
D., Bian, H., Cameron-Smith, P., Chipperfield, M. P., Corbin, K.,
Fortems-Cheiney, A., Fraser, A., Gloor, E., Hess, P., Ito, A., Kawa, S. R.,
Law, R. M., Loh, Z., Maksyutov, S., Meng, L., Palmer, P. I., Prinn, R. G.,
Rigby, M., Saito, R., and Wilson, C.: TransCom model simulations of CH4 and
related species: linking transport, surface flux and chemical loss with
CH4
variability in the troposphere and lower stratosphere, Atmos. Chem. Phys.,
11, 12813–12837, https://doi.org/10.5194/acp-11-12813-2011, 2011.
Patra, P. K., Krol, M. C., Montzka, S. A., Arnold, T., Atlas, E. L.,
Lintner, B. R., Xiang, B., Elkins, J. W., Fraser, P. J., Ghosh, A., Hintsa,
E. J., Hurst, D. F., Ishijima, K., Krummel, P. B., Miller, B. R., Miyazaki,
K., Moore, F. L., Mühle, J., O'Doherty, S., Prinn, R. G., Steele, L. P.,
Takigawa, M., Wang, H. J., Weiss, R. F., Wofsy, S. C., and Young, D.:
Observational evidence for interhemispheric hydroxyl-radical parity, Nature,
513, 219–223, https://doi.org/10.1038/nature13721, 2014.
Pawson, S. R., Stolarski, S., Douglass, A. R., Newman, P. A., Nielsen, J.
E., Frith, S. M., and Gupta, M. L.: Goddard Earth Observing System
chemistry-climate model simulations of stratospheric ozone-temperature
coupling between 1950 and 2005, J. Geophys. Res., 113, D12103,
https://doi.org/10.1029/2007JD009511, 2008.
Prather, M.: Lifetimes and Eigen states in atmospheric chemistry, Geophys.
Res. Lett., 21, 801–804, 1994.
Prather, M.: Time scales in atmospheric chemistry: Theory, GWPs for CH4
and CO, and runaway growth, Geophys. Res. Lett., 23, 2597–2600,
https://doi.org/10.1029/96GL02371, 1996.
Prather, M. and Spivakovsky, C. M.: Tropospheric OH and the lifetimes of
hydrochlorofluorocarbons, J. Geophys. Res., 95, 18723–18729,
https://doi.org/10.1029/JD095iD11p18723, 1990.
Prather, M. J., Holmes, C. D., and Hsu, J.: Reactive greenhouse gas
scenarios: Systematic exploration of uncertainties and the role of
atmospheric chemistry, Geophys. Res. Lett., 39, L09803,
https://doi.org/10.1029/2012GL051440, 2012.
Prinn, R. G., Huang, J., Weiss, R. F., Cunnold, D. M., Fraser, P. J.,
Simmonds, P. G., McCulloch, A., Harth, C., Reimann, S., Salameh, P.,
O'Doherty, S., Wang, R. H. J., Porter, L. W., Miller, B. R., and Krummel, P.
B.: Evidence for variability of atmospheric hydroxyl radicals over the past
quarter century, Geophys. Res. Lett., 32, L07809, https://doi.org/10.1029/2004GL022228,
2005.
Randerson, J. T., van der Werf, G. R., Giglio, L., Collatz, G. J., and
Kasibhatl, P. S.: Global Fire Emissions Database, Version 3 (GFEDv3.1), Data
set, Oak Ridge National Laboratory Distributed Active Archive Center, Oak
Ridge, Tennessee, USA, available at: http://daac.ornl.gov (last access:
27 October 2015), https://doi.org/10.3334/ORNLDAAC/1191, 2013.
Rienecker, M. M., Suarez, M. J., Todling, R., Bacmeister, J., Takacs, L.,
Liu, H.-C., Gu, W., Sienkiewicz, M., Koster, R. D., Gelaro, R., Stajner, I.,
and Nielsen, J. E.: The GEOS-5 data assimilation system – Documentation of
Versions 5.0.1, 5.1.0, and 5.2.0, Technical Report Series on Global Modeling
and Data Assimilation, Vol. 27, available at:
http://gmao.gsfc.nasa.gov/pubs/docs/GEOS5_104606-Vol27.pdf (last
access: 27 October 2015), 2008.
Rohrer, F. and Berresheim, H.: Strong correlations between levels of
tropospheric hydroxyl radicals and solar ultraviolet radiation, Nature, 442,
184–187, https://doi.org/10.1038/nature04924, 2006.
Rohrer, F., Lu, K., Hofzumahaus, A., Bohn, B., Brauers, T., Chang, C.-C.,
Fuchs, H., Häseler, R., Holland, F., Hu, M., Kita, K., Kondo, Y., Li, X.,
Lou, S., Oebel, A., Shao, M., Zeng, L., Zhu, T., Zhang, Y., and Wahner, A.:
Maximum efficiency in the hydroxyl-radical-based self-cleansing of the
troposphere, Nat. Geosci. 7, 559–563, https://doi.org/10.1038/ngeo2199, 2014.
Sander, S. P., Abbatt, J., Barker, J. R., Burkholder, J. B., Friedl, R. R.,
Golden, D. M., Huie, R. E., Kolb, C. E., Kurylo, M. J., Moortgat, G. K.,
Orkin, V. L., and Wine, P. H.: Chemical Kinetics and Photochemical Data for
Use in Atmospheric Studies, Evaluation No. 17, JPL Publication 10-6, Jet
Propulsion Laboratory, Pasadena, available at:
http://jpldataeval.jpl.nasa.gov (last access: 27 October 2015), 2011.
Schneising, O., Buchwitz, M., Burrows, J. P., Bovensmann, H., Bergamaschi,
P., and Peters, W.: Three years of greenhouse gas column-averaged dry air
mole fractions retrieved from satellite – Part 2: Methane, Atmos. Chem.
Phys., 9, 443–465, https://doi.org/10.5194/acp-9-443-2009, 2009.
Schneising, O., Buchwitz, M., Reuter, M., Heymann, J., Bovensmann, H., and
Burrows, J. P.: Long-term analysis of carbon dioxide and methane
column-averaged mole fractions retrieved from SCIAMACHY, Atmos. Chem. Phys.,
11, 2863–2880, https://doi.org/10.5194/acp-11-2863-2011, 2011.
Schultz, M., Rast, S., van het Bolscher, M., Pulles, T., Brand, R.,
Pereira, J., Mota, B., Spessa, A., Dalsøren, S., van Nojie, T., and Szopa,
S.: Emission data sets and methodologies for estimating emissions, RETRO
project report D1-6, Hamburg, 26 February 2007, available at:
http://gcmd.gsfc.nasa.gov/records/GCMD_GEIA_RETRO.html (last access:
27 October 2015), 2007.
Shindell, D. T., Faluvegi, G., Stevenson, D. S., Krol, M. C., Emmons, L. K.,
Lamarque, J.-F., Petron, G., Dentener, F. J., Ellingsne, K., Schultz, M. G.,
Wild, O., Amann, M., Atherton, C. S., Bergmann, D. J., Bey, I., Butler, T.,
Cofala, J., Collins, W. J., Derwent, R. G., Doherty, R. M., Drevet, J.,
Eskes, H. J., Fiore, A. M., Gauss, M., Hauglustaine, D. A., Horowitz, L. W.,
Isaksen, I. S. A., Lawrence, M. G., Montanaro, V., Müller, J.-F., Pitari,
G., Prather, M. J., Pyle, J. A., Rast, S., Rodriguez, J. M., Sanderson, M.
G., Savage, N. H., Strahan, S. E., Sudo, K., Szopa, S., Unger, N., van Noije,
T. P. C., and Zeng, G.: Multimodel simulations of carbon monoxide: Comparison
with observations and projected near-future changes, J. Geophys. Res., 111,
D19306, https://doi.org/10.1029/2006JD007100, 2006.
Spivakovsky, C., Wofsy, S., and Prather, M.: A numerical method for the
parameterization of atmospheric chemistry: Computation of tropospheric OH, J.
Geophys. Res., 95, 18433–18439, 1990a.
Spivakovsky, C. M., Yevich, R., Logan, J. A., Wofsy, S. C., McElroy, M. B., and
Prather, M. J.: Tropospheric OH in a three-dimensional chemical tracer model:
An assessment based on observations of CH3CC13, J. Geophys. Res.,
95, 18441–18471, https://doi.org/10.1029/JD095iD11p18441, 1990b.
Spivakovsky, C. M., Logan, J. A., Montzka, S. A., Balkanski, Y.
J., Foreman-Fowler, M., Jones, D. B. A., Horowitz, L. W., Fusco, A. C.,
Brenninkmeijer, C. A. M., Prather, M. J., Wofsy, S. C., and McElroy, M. B.:
Three-dimensional climatological distribution of tropospheric OH: Update and
evaluation, J. Geophys. Res., 105, 8931–8980, https://doi.org/10.1029/1999JD901006,
2000.
Stone, D., Whalley, L. K., and Heard, D. E.: Tropospheric OH and HO2 radicals:
field measurements and model comparisons, Chem. Soc. Rev., 41, 6348,
https://doi.org/10.1039/c2cs35140d, 2012.
Strahan, S. E., Duncan, B. N., and Hoor, P.: Observationally derived
transport diagnostics for the lowermost stratosphere and their application to
the GMI chemistry and transport model, Atmos. Chem. Phys., 7, 2435–2445,
https://doi.org/10.5194/acp-7-2435-2007, 2007.
Strode, S. A., Duncan, B. N., Yegorova, E. A., Kouatchou, J., Ziemke, J. R.,
and Douglass, A. R.: Implications of carbon monoxide bias for methane
lifetime and atmospheric composition in chemistry climate models, Atmos.
Chem. Phys., 15, 11789–11805, https://doi.org/10.5194/acp-15-11789-2015,
2015.
Voulgarakis, A., Naik, V., Lamarque, J.-F., Shindell, D. T., Young, P. J.,
Prather, M. J., Wild, O., Field, R. D., Bergmann, D., Cameron-Smith, P.,
Cionni, I., Collins, W. J., Dalsøren, S. B., Doherty, R. M., Eyring, V.,
Faluvegi, G., Folberth, G. A., Horowitz, L. W., Josse, B., MacKenzie, I. A.,
Nagashima, T., Plummer, D. A., Righi, M., Rumbold, S. T., Stevenson, D. S.,
Strode, S. A., Sudo, K., Szopa, S., and Zeng, G.: Analysis of present day and
future OH and methane lifetime in the ACCMIP simulations, Atmos. Chem. Phys.,
13, 2563–2587, https://doi.org/10.5194/acp-13-2563-2013, 2013.
Voulgarakis, A., Marlier, M. E., Faluvegi, G., Shindell, D. T.,
Tsigaridis, K., and Mangeon, S.: Interannual variability of tropospheric
trace gases and aerosols: The role of biomass burning emissions, J. Geophys.
Res. Atmos., 120, 7157–7173, https://doi.org/10.1002/2014JD022926, 2015.
Wang, J. S., Logan, J. A., McElroy, M. B., Duncan, B. N., Megretskaia, I.
A., and Yantosca, R. M.: A 3-D model analysis of the slowdown and interannual
variability in the methane growth rate from 1988 to 1997, Global Biogeochem.
Cy., 18, GB3011, https://doi.org/10.1029/2003GB002180, 2004.
Wang, J. S., McElroy, M. B., Logan, J. A., Palmer, P. I., Chameides, W. L.,
Wang, Y., and Megretskaia, I. A.: A quantitative assessment of uncertainties
affecting estimates of global mean OH derived from methyl chloroform
observations, J. Geophys. Res., 113, D12302, https://doi.org/10.1029/2007JD008496, 2008.
Wild, O. and Palmer, P. I.: How sensitive is tropospheric oxidation to
anthropogenic emissions?, Geophys. Res. Lett., 35, L22802,
https://doi.org/10.1029/2008GL035718, 2008.
Wolter, K. and Timlin, M. S.: El Niño/Southern Oscillation behaviour
since 1871 as diagnosed in an extended multivariate ENSO index (MEI.ext),
Int. J. Climatol., 31, 1074–1087, https://doi.org/10.1002/joc.2336, 2011.
Worden, H. M., Deeter, M. N., Edwards, D. P., Gille, J. C., Drummond, J. R.,
and Nédélec, P.: Observations of near-surface carbon monoxide from
space using MOPITT multispectral retrievals, J. Geophys., Res., 115, D18314,
https://doi.org/10.1029/2010JD014242, 2010.
Short summary
The ECCOH (pronounced "echo") chemistry module interactively simulates the photochemistry of the CH4–CO–OH system within a chemistry climate model, carbon cycle model, or Earth system model. The computational efficiency of the module allows many multi-decadal sensitivity simulations of the CH4–CO–OH system. This capability is important for capturing nonlinear feedbacks of the CH4–CO–OH system and understanding the perturbations to methane, CO, and OH and the concomitant climate impacts.
The ECCOH (pronounced "echo") chemistry module interactively simulates the photochemistry of the...
