Articles | Volume 9, issue 7
https://doi.org/10.5194/gmd-9-2377-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-2377-2016
© 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
| 
12 Jul 2016
Development and technical paper |
| 12 Jul 2016
Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters – Part 2: Aerosols
NASA Goddard Space Flight Center, 8800 Greenbelt Rd.
Greenbelt, Maryland 20771, USA
SSAI, Inc. 10210 Greenbelt Road, Suite 600, Lanham,
Maryland 20706, USA
Arlindo M. da Silva
NASA Goddard Space Flight Center, 8800 Greenbelt Rd.
Greenbelt, Maryland 20771, USA
Peter M. Norris
NASA Goddard Space Flight Center, 8800 Greenbelt Rd.
Greenbelt, Maryland 20771, USA
Universities Space Research Association, 7178
Columbia Gateway Drive, Columbia, MD 21046, USA
Steven Platnick
NASA Goddard Space Flight Center, 8800 Greenbelt Rd.
Greenbelt, Maryland 20771, USA
Shana Mattoo
NASA Goddard Space Flight Center, 8800 Greenbelt Rd.
Greenbelt, Maryland 20771, USA
SSAI, Inc. 10210 Greenbelt Road, Suite 600, Lanham,
Maryland 20706, USA
Robert C. Levy
NASA Goddard Space Flight Center, 8800 Greenbelt Rd.
Greenbelt, Maryland 20771, USA
Related authors
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.
Frank Werner, Nathaniel J. Livesey, Michael J. Schwartz, William G. Read, Michelle L. Santee, and Galina Wind
Atmos. Meas. Tech., 14, 7749–7773, https://doi.org/10.5194/amt-14-7749-2021, https://doi.org/10.5194/amt-14-7749-2021, 2021
Short summary
Short summary
In this study we present an improved cloud detection scheme for the Microwave Limb Sounder, which is based on a feedforward artificial neural network. This new algorithm is shown not only to reliably detect high and mid-level convection containing even small amounts of cloud water but also to distinguish between high-reaching and mid-level to low convection.
Hong Chen, Sebastian Schmidt, Michael D. King, Galina Wind, Anthony Bucholtz, Elizabeth A. Reid, Michal Segal-Rozenhaimer, William L. Smith, Patrick C. Taylor, Seiji Kato, and Peter Pilewskie
Atmos. Meas. Tech., 14, 2673–2697, https://doi.org/10.5194/amt-14-2673-2021, https://doi.org/10.5194/amt-14-2673-2021, 2021
Short summary
Short summary
In this paper, we accessed the shortwave irradiance derived from MODIS cloud optical properties by using aircraft measurements. We developed a data aggregation technique to parameterize spectral surface albedo by snow fraction in the Arctic. We found that undetected clouds have the most significant impact on the imagery-derived irradiance. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach that would make it more dependable in the Arctic.
Benjamin Marchant, Steven Platnick, Kerry Meyer, and Galina Wind
Atmos. Meas. Tech., 13, 3263–3275, https://doi.org/10.5194/amt-13-3263-2020, https://doi.org/10.5194/amt-13-3263-2020, 2020
Short summary
Short summary
Multilayer cloud scenes (such as an ice cloud overlapping a liquid cloud) are common in the Earth's atmosphere and are quite difficult to detect from space. The detection of multilayer clouds is important to better understand how they interact with the light and their impact on the climate. So, for the instrument MODIS an algorithm has been developed to detect those clouds, and this paper presents an evaluation of this algorithm by comparing it with
other instruments.
Frank Werner, Galina Wind, Zhibo Zhang, Steven Platnick, Larry Di Girolamo, Guangyu Zhao, Nandana Amarasinghe, and Kerry Meyer
Atmos. Meas. Tech., 9, 5869–5894, https://doi.org/10.5194/amt-9-5869-2016, https://doi.org/10.5194/amt-9-5869-2016, 2016
Short summary
Short summary
A research–level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. This yields reliable estimates of important cloud variables at a horizontal resolution of 30 m. Comparisons of the ASTER retrieval results with the operational cloud products from the Moderate Resolution Imaging Spectroradiometer (MODIS) show a high agreement for 48 example cloud fields.
U. Hamann, A. Walther, B. Baum, R. Bennartz, L. Bugliaro, M. Derrien, P. N. Francis, A. Heidinger, S. Joro, A. Kniffka, H. Le Gléau, M. Lockhoff, H.-J. Lutz, J. F. Meirink, P. Minnis, R. Palikonda, R. Roebeling, A. Thoss, S. Platnick, P. Watts, and G. Wind
Atmos. Meas. Tech., 7, 2839–2867, https://doi.org/10.5194/amt-7-2839-2014, https://doi.org/10.5194/amt-7-2839-2014, 2014
G. Wind, A. M. da Silva, P. M. Norris, and S. Platnick
Geosci. Model Dev., 6, 2049–2062, https://doi.org/10.5194/gmd-6-2049-2013, https://doi.org/10.5194/gmd-6-2049-2013, 2013
Peng Xian, Jeffrey S. Reid, Melanie Ades, Angela Benedetti, Peter R. Colarco, Arlindo da Silva, Tom F. Eck, Johannes Flemming, Edward J. Hyer, Zak Kipling, Samuel Rémy, Tsuyoshi Thomas Sekiyama, Taichu Tanaka, Keiya Yumimoto, and Jianglong Zhang
Atmos. Chem. Phys., 24, 6385–6411, https://doi.org/10.5194/acp-24-6385-2024, https://doi.org/10.5194/acp-24-6385-2024, 2024
Short summary
Short summary
The study compares and evaluates monthly AOD of four reanalyses (RA) and their consensus (i.e., ensemble mean). The basic verification characteristics of these RA versus both AERONET and MODIS retrievals are presented. The study discusses the strength of each RA and identifies regions where divergence and challenges are prominent. The RA consensus usually performs very well on a global scale in terms of how well it matches the observational data, making it a good choice for various applications.
Mijin Kim, Robert C. Levy, Lorraine A. Remer, Shana Mattoo, and Pawan Gupta
Atmos. Meas. Tech., 17, 1913–1939, https://doi.org/10.5194/amt-17-1913-2024, https://doi.org/10.5194/amt-17-1913-2024, 2024
Short summary
Short summary
The study focused on evaluating and modifying the surface reflectance parameterization (SRP) of the Dark Target (DT) algorithm for geostationary observation. When using the DT SRP with the ABIs sensor on GOES-R, artificial diurnal signatures were present in AOD retrieval. To overcome this issue, a new SRP was developed, incorporating solar zenith angle and land cover type. The revised SRP resulted in improved AOD retrieval, demonstrating reduced bias around local noon.
Adriana Rocha-Lima, Peter R. Colarco, Anton S. Darmenov, Edward P. Nowottnick, Arlindo M. da Silva, and Luke D. Oman
Atmos. Chem. Phys., 24, 2443–2464, https://doi.org/10.5194/acp-24-2443-2024, https://doi.org/10.5194/acp-24-2443-2024, 2024
Short summary
Short summary
Observations show an increasing aerosol optical depth trend in the Middle East between 2003–2012. We evaluate the NASA Goddard Earth Observing System (GEOS) model's ability to capture these trends and examine the meteorological and surface parameters driving dust emissions. Our results highlight the importance of data assimilation for long-term trends of atmospheric aerosols and support the hypothesis that vegetation cover loss may have contributed to increasing dust emissions in the period.
Lorraine A. Remer, Robert C. Levy, and J. Vanderlei Martins
Atmos. Chem. Phys., 24, 2113–2127, https://doi.org/10.5194/acp-24-2113-2024, https://doi.org/10.5194/acp-24-2113-2024, 2024
Short summary
Short summary
Aerosols are small liquid or solid particles suspended in the atmosphere, including smoke, particulate pollution, dust, and sea salt. Today, we rely on satellites viewing Earth's atmosphere to learn about these particles. Here, we speculate on the future to imagine how satellite viewing of aerosols will change. We expect more public and private satellites with greater capabilities, better ways to infer information from satellites, and merging of data with models.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
Short summary
Short summary
This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine Remer, Zhaohui Zhang, Virginia Sawyer, Jennifer Wei, Sally Zhao, Min Oo, V. Praju Kiliyanpilakkil, and Xiaohua Pan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-259, https://doi.org/10.5194/amt-2023-259, 2024
Revised manuscript under review for AMT
Short summary
Short summary
In this study, for the first time, we combined aerosol data from six satellites using a unified algorithm. The global datasets are generated at a high spatial resolution of about 25 km with an interval of 30 minutes. The new datasets are compared against ground truth and verified. They will be useful for various applications such as air quality monitoring, climate research, pollution diurnal variability, long-range smoke and dust transport, and evaluation of regional and global models.
Amanda Gumber, Jeffrey S. Reid, Robert E. Holz, Thomas F. Eck, N. Christina Hsu, Robert C. Levy, Jianglong Zhang, and Paolo Veglio
Atmos. Meas. Tech., 16, 2547–2573, https://doi.org/10.5194/amt-16-2547-2023, https://doi.org/10.5194/amt-16-2547-2023, 2023
Short summary
Short summary
The purpose of this study is to create and evaluate a gridded dataset composed of multiple satellite instruments and algorithms to be used for data assimilation. An important part of aerosol data assimilation is having consistent measurements, especially for severe aerosol events. This study evaluates 4 years of data from MODIS, VIIRS, and AERONET with a focus on aerosol severe event detection from a regional and global perspective.
Ian Chang, Lan Gao, Connor J. Flynn, Yohei Shinozuka, Sarah J. Doherty, Michael S. Diamond, Karla M. Longo, Gonzalo A. Ferrada, Gregory R. Carmichael, Patricia Castellanos, Arlindo M. da Silva, Pablo E. Saide, Calvin Howes, Zhixin Xue, Marc Mallet, Ravi Govindaraju, Qiaoqiao Wang, Yafang Cheng, Yan Feng, Sharon P. Burton, Richard A. Ferrare, Samuel E. LeBlanc, Meloë S. Kacenelenbogen, Kristina Pistone, Michal Segal-Rozenhaimer, Kerry G. Meyer, Ju-Mee Ryoo, Leonhard Pfister, Adeyemi A. Adebiyi, Robert Wood, Paquita Zuidema, Sundar A. Christopher, and Jens Redemann
Atmos. Chem. Phys., 23, 4283–4309, https://doi.org/10.5194/acp-23-4283-2023, https://doi.org/10.5194/acp-23-4283-2023, 2023
Short summary
Short summary
Abundant aerosols are present above low-level liquid clouds over the southeastern Atlantic during late austral spring. The model simulation differences in the proportion of aerosol residing in the planetary boundary layer and in the free troposphere can greatly affect the regional aerosol radiative effects. This study examines the aerosol loading and fractional aerosol loading in the free troposphere among various models and evaluates them against measurements from the NASA ORACLES campaign.
Allison B. Marquardt Collow, Virginie Buchard, Peter R. Colarco, Arlindo M. da Silva, Ravi Govindaraju, Edward P. Nowottnick, Sharon Burton, Richard Ferrare, Chris Hostetler, and Luke Ziemba
Atmos. Chem. Phys., 22, 16091–16109, https://doi.org/10.5194/acp-22-16091-2022, https://doi.org/10.5194/acp-22-16091-2022, 2022
Short summary
Short summary
Biomass burning aerosol impacts aspects of the atmosphere and Earth system through radiative forcing, serving as cloud condensation nuclei, and air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in models. Field campaign observations from CAMP2Ex are used to evaluate the mass and extinction of aerosols in the GEOS model. Notable biases in the model illuminate areas of future development with GEOS and the underlying GOCART aerosol module.
Samuel E. LeBlanc, Michal Segal-Rozenhaimer, Jens Redemann, Connor Flynn, Roy R. Johnson, Stephen E. Dunagan, Robert Dahlgren, Jhoon Kim, Myungje Choi, Arlindo da Silva, Patricia Castellanos, Qian Tan, Luke Ziemba, Kenneth Lee Thornhill, and Meloë Kacenelenbogen
Atmos. Chem. Phys., 22, 11275–11304, https://doi.org/10.5194/acp-22-11275-2022, https://doi.org/10.5194/acp-22-11275-2022, 2022
Short summary
Short summary
Airborne observations of atmospheric particles and pollution over Korea during a field campaign in May–June 2016 showed that the smallest atmospheric particles are present in the lowest 2 km of the atmosphere. The aerosol size is more spatially variable than optical thickness. We show this with remote sensing (4STAR), in situ (LARGE) observations, satellite measurements (GOCI), and modeled properties (MERRA-2), and it is contrary to the current understanding.
Sudip Chakraborty, Bin Guan, Duane E. Waliser, and Arlindo M. da Silva
Atmos. Chem. Phys., 22, 8175–8195, https://doi.org/10.5194/acp-22-8175-2022, https://doi.org/10.5194/acp-22-8175-2022, 2022
Short summary
Short summary
This study explores extreme aerosol transport events by aerosol atmospheric rivers (AARs) and shows the characteristics of individual AARs such as length, width, length-to-width ratio, transport strength, and dominant transport direction, the seasonal variations, the relationship to the spatial distribution of surface emissions, the vertical profiles of wind, aerosol mixing ratio, and aerosol mass fluxes, and the major planetary-scale aerosol transport pathways.
Pawan Gupta, Prakash Doraiswamy, Jashwanth Reddy, Palak Balyan, Sagnik Dey, Ryan Chartier, Adeel Khan, Karmann Riter, Brandon Feenstra, Robert C. Levy, Nhu Nguyen Minh Tran, Olga Pikelnaya, Kurinji Selvaraj, Tanushree Ganguly, and Karthik Ganesan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-140, https://doi.org/10.5194/amt-2022-140, 2022
Revised manuscript not accepted
Short summary
Short summary
The use of low-cost sensors in air quality monitoring has been gaining interest across all walks of society. We present the results of evaluations of the PurpleAir against regulatory-grade PM2.5. The results indicate that with proper calibration, we can achieve bias-corrected PM2.5 data using PA sensors. Our study also suggests that pre-deployment calibrations developed at local or regional scales are required for the PA sensors to correct data from the field for scientific data analysis.
Sujung Go, Alexei Lyapustin, Gregory L. Schuster, Myungje Choi, Paul Ginoux, Mian Chin, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, Arlindo da Silva, Brent Holben, and Jeffrey S. Reid
Atmos. Chem. Phys., 22, 1395–1423, https://doi.org/10.5194/acp-22-1395-2022, https://doi.org/10.5194/acp-22-1395-2022, 2022
Short summary
Short summary
This paper presents a retrieval algorithm of iron-oxide species (hematite, goethite) content in the atmosphere from DSCOVR EPIC observations. Our results display variations within the published range of hematite and goethite over the main dust-source regions but show significant seasonal and spatial variability. This implies a single-viewing satellite instrument with UV–visible channels may provide essential information on shortwave dust direct radiative effects for climate modeling.
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.
Sarah J. Doherty, Pablo E. Saide, Paquita Zuidema, Yohei Shinozuka, Gonzalo A. Ferrada, Hamish Gordon, Marc Mallet, Kerry Meyer, David Painemal, Steven G. Howell, Steffen Freitag, Amie Dobracki, James R. Podolske, Sharon P. Burton, Richard A. Ferrare, Calvin Howes, Pierre Nabat, Gregory R. Carmichael, Arlindo da Silva, Kristina Pistone, Ian Chang, Lan Gao, Robert Wood, and Jens Redemann
Atmos. Chem. Phys., 22, 1–46, https://doi.org/10.5194/acp-22-1-2022, https://doi.org/10.5194/acp-22-1-2022, 2022
Short summary
Short summary
Between July and October, biomass burning smoke is advected over the southeastern Atlantic Ocean, leading to climate forcing. Model calculations of forcing by this plume vary significantly in both magnitude and sign. This paper compares aerosol and cloud properties observed during three NASA ORACLES field campaigns to the same in four models. It quantifies modeled biases in properties key to aerosol direct radiative forcing and evaluates how these biases propagate to biases in forcing.
Frank Werner, Nathaniel J. Livesey, Michael J. Schwartz, William G. Read, Michelle L. Santee, and Galina Wind
Atmos. Meas. Tech., 14, 7749–7773, https://doi.org/10.5194/amt-14-7749-2021, https://doi.org/10.5194/amt-14-7749-2021, 2021
Short summary
Short summary
In this study we present an improved cloud detection scheme for the Microwave Limb Sounder, which is based on a feedforward artificial neural network. This new algorithm is shown not only to reliably detect high and mid-level convection containing even small amounts of cloud water but also to distinguish between high-reaching and mid-level to low convection.
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
Short summary
Short summary
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.
Huisheng Bian, Eunjee Lee, Randal D. Koster, Donifan Barahona, Mian Chin, Peter R. Colarco, Anton Darmenov, Sarith Mahanama, Michael Manyin, Peter Norris, John Shilling, Hongbin Yu, and Fanwei Zeng
Atmos. Chem. Phys., 21, 14177–14197, https://doi.org/10.5194/acp-21-14177-2021, https://doi.org/10.5194/acp-21-14177-2021, 2021
Short summary
Short summary
The study using the NASA Earth system model shows ~2.6 % increase in burning season gross primary production and ~1.5 % increase in annual net primary production across the Amazon Basin during 2010–2016 due to the change in surface downward direct and diffuse photosynthetically active radiation by biomass burning aerosols. Such an aerosol effect is strongly dependent on the presence of clouds. The cloud fraction at which aerosols switch from stimulating to inhibiting plant growth occurs at ~0.8.
Hongbin Yu, Qian Tan, Lillian Zhou, Yaping Zhou, Huisheng Bian, Mian Chin, Claire L. Ryder, Robert C. Levy, Yaswant Pradhan, Yingxi Shi, Qianqian Song, Zhibo Zhang, Peter R. Colarco, Dongchul Kim, Lorraine A. Remer, Tianle Yuan, Olga Mayol-Bracero, and Brent N. Holben
Atmos. Chem. Phys., 21, 12359–12383, https://doi.org/10.5194/acp-21-12359-2021, https://doi.org/10.5194/acp-21-12359-2021, 2021
Short summary
Short summary
This study characterizes a historic African dust intrusion into the Caribbean Basin in June 2020 using satellites and NASA GEOS. Dust emissions in West Africa were large albeit not extreme. However, a unique synoptic system accumulated the dust near the coast for about 4 d before it was ventilated. Although GEOS reproduced satellite-observed plume tracks well, it substantially underestimated dust emissions and did not lift up dust high enough for ensuing long-range transport.
Kristina Pistone, Paquita Zuidema, Robert Wood, Michael Diamond, Arlindo M. da Silva, Gonzalo Ferrada, Pablo E. Saide, Rei Ueyama, Ju-Mee Ryoo, Leonhard Pfister, James Podolske, David Noone, Ryan Bennett, Eric Stith, Gregory Carmichael, Jens Redemann, Connor Flynn, Samuel LeBlanc, Michal Segal-Rozenhaimer, and Yohei Shinozuka
Atmos. Chem. Phys., 21, 9643–9668, https://doi.org/10.5194/acp-21-9643-2021, https://doi.org/10.5194/acp-21-9643-2021, 2021
Short summary
Short summary
Using aircraft-based measurements off the Atlantic coast of Africa, we found the springtime smoke plume was strongly correlated with the amount of water vapor in the atmosphere (more smoke indicated more humidity). We see the same general feature in satellite-assimilated and free-running models. Our analysis suggests this relationship is not caused by the burning but originates due to coincident continental meteorology plus fires. This air is transported over the ocean without further mixing.
Yingxi R. Shi, Robert C. Levy, Leiku Yang, Lorraine A. Remer, Shana Mattoo, and Oleg Dubovik
Atmos. Meas. Tech., 14, 3449–3468, https://doi.org/10.5194/amt-14-3449-2021, https://doi.org/10.5194/amt-14-3449-2021, 2021
Short summary
Short summary
Due to fast industrialization and development, China has been experiencing haze pollution episodes with both high frequencies and severity over the last 3 decades. This study improves the accuracy and data coverage of measured aerosol from satellites, which help quantify, characterize, and understand the impact of the haze phenomena over the entire East Asia region.
Kirk Knobelspiesse, Amir Ibrahim, Bryan Franz, Sean Bailey, Robert Levy, Ziauddin Ahmad, Joel Gales, Meng Gao, Michael Garay, Samuel Anderson, and Olga Kalashnikova
Atmos. Meas. Tech., 14, 3233–3252, https://doi.org/10.5194/amt-14-3233-2021, https://doi.org/10.5194/amt-14-3233-2021, 2021
Short summary
Short summary
We assessed atmospheric aerosol and ocean surface wind speed remote sensing capability with NASA's Multi-angle Imaging SpectroRadiometer (MISR), using synthetic data and a Bayesian inference technique called generalized nonlinear retrieval analysis (GENRA). We found success using three aerosol parameters plus wind speed. This shows that MISR can perform an atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same spacecraft (Terra).
Hong Chen, Sebastian Schmidt, Michael D. King, Galina Wind, Anthony Bucholtz, Elizabeth A. Reid, Michal Segal-Rozenhaimer, William L. Smith, Patrick C. Taylor, Seiji Kato, and Peter Pilewskie
Atmos. Meas. Tech., 14, 2673–2697, https://doi.org/10.5194/amt-14-2673-2021, https://doi.org/10.5194/amt-14-2673-2021, 2021
Short summary
Short summary
In this paper, we accessed the shortwave irradiance derived from MODIS cloud optical properties by using aircraft measurements. We developed a data aggregation technique to parameterize spectral surface albedo by snow fraction in the Arctic. We found that undetected clouds have the most significant impact on the imagery-derived irradiance. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach that would make it more dependable in the Arctic.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
Short summary
Short summary
Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Cheng Chen, Oleg Dubovik, David Fuertes, Pavel Litvinov, Tatyana Lapyonok, Anton Lopatin, Fabrice Ducos, Yevgeny Derimian, Maurice Herman, Didier Tanré, Lorraine A. Remer, Alexei Lyapustin, Andrew M. Sayer, Robert C. Levy, N. Christina Hsu, Jacques Descloitres, Lei Li, Benjamin Torres, Yana Karol, Milagros Herrera, Marcos Herreras, Michael Aspetsberger, Moritz Wanzenboeck, Lukas Bindreiter, Daniel Marth, Andreas Hangler, and Christian Federspiel
Earth Syst. Sci. Data, 12, 3573–3620, https://doi.org/10.5194/essd-12-3573-2020, https://doi.org/10.5194/essd-12-3573-2020, 2020
Short summary
Short summary
Aerosol products obtained from POLDER/PARASOL processed by the GRASP algorithm have been released. The entire archive of PARASOL/GRASP aerosol products is evaluated against AERONET and compared with MODIS (DT, DB and MAIAC), as well as PARASOL/Operational products. PARASOL/GRASP aerosol products provide spectral 443–1020 nm AOD correlating well with AERONET with a maximum bias of 0.02. Finally, GRASP shows capability to derive detailed spectral properties, including aerosol absorption.
Nick Schutgens, Andrew M. Sayer, Andreas Heckel, Christina Hsu, Hiren Jethva, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen, Virginia Sawyer, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 20, 12431–12457, https://doi.org/10.5194/acp-20-12431-2020, https://doi.org/10.5194/acp-20-12431-2020, 2020
Short summary
Short summary
We intercompare 14 different datasets of satellite observations of aerosol. Such measurements are challenging but also provide the best opportunity to globally observe an atmospheric component strongly related to air pollution and climate change. Our study shows that most datasets perform similarly well on a global scale but that locally errors can be quite different. We develop a technique to estimate satellite errors everywhere, even in the absence of surface reference data.
Yohei Shinozuka, Pablo E. Saide, Gonzalo A. Ferrada, Sharon P. Burton, Richard Ferrare, Sarah J. Doherty, Hamish Gordon, Karla Longo, Marc Mallet, Yan Feng, Qiaoqiao Wang, Yafang Cheng, Amie Dobracki, Steffen Freitag, Steven G. Howell, Samuel LeBlanc, Connor Flynn, Michal Segal-Rosenhaimer, Kristina Pistone, James R. Podolske, Eric J. Stith, Joseph Ryan Bennett, Gregory R. Carmichael, Arlindo da Silva, Ravi Govindaraju, Ruby Leung, Yang Zhang, Leonhard Pfister, Ju-Mee Ryoo, Jens Redemann, Robert Wood, and Paquita Zuidema
Atmos. Chem. Phys., 20, 11491–11526, https://doi.org/10.5194/acp-20-11491-2020, https://doi.org/10.5194/acp-20-11491-2020, 2020
Short summary
Short summary
In the southeast Atlantic, well-defined smoke plumes from Africa advect over marine boundary layer cloud decks; both are most extensive around September, when most of the smoke resides in the free troposphere. A framework is put forth for evaluating the performance of a range of global and regional atmospheric composition models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016.
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
Short summary
Short summary
The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign is a resource for the next generation of spaceborne multi-angle polarimeter (MAP) and lidar missions. Conducted in the fall of 2017 from the Armstrong Flight Research Center in Palmdale, California, four MAP instruments and two lidars were flown on the high-altitude ER-2 aircraft over a variety of scene types and ground assets. Data are freely available to the public and useful for algorithm development and testing.
Alexander Ukhov, Suleiman Mostamandi, Arlindo da Silva, Johannes Flemming, Yasser Alshehri, Illia Shevchenko, and Georgiy Stenchikov
Atmos. Chem. Phys., 20, 9281–9310, https://doi.org/10.5194/acp-20-9281-2020, https://doi.org/10.5194/acp-20-9281-2020, 2020
Short summary
Short summary
The data assimilation products MERRA2 and CAMS are tested over the Middle East (ME) against in situ and satellite observations. For the first time, we compared the new MODIS aerosol optical depth (AOD) retrieval, MAIAC, with the Deep Blue and Dark Target MODIS AOD. We conducted 2-year high-resolution WRF-Chem simulations with the most accurate OMI-HTAP SO2 emissions to estimate the contribution of natural and anthropogenic aerosols to the PM pollution in the ME.
Benjamin Marchant, Steven Platnick, Kerry Meyer, and Galina Wind
Atmos. Meas. Tech., 13, 3263–3275, https://doi.org/10.5194/amt-13-3263-2020, https://doi.org/10.5194/amt-13-3263-2020, 2020
Short summary
Short summary
Multilayer cloud scenes (such as an ice cloud overlapping a liquid cloud) are common in the Earth's atmosphere and are quite difficult to detect from space. The detection of multilayer clouds is important to better understand how they interact with the light and their impact on the climate. So, for the instrument MODIS an algorithm has been developed to detect those clouds, and this paper presents an evaluation of this algorithm by comparing it with
other instruments.
Therese S. Carter, Colette L. Heald, Jose L. Jimenez, Pedro Campuzano-Jost, Yutaka Kondo, Nobuhiro Moteki, Joshua P. Schwarz, Christine Wiedinmyer, Anton S. Darmenov, Arlindo M. da Silva, and Johannes W. Kaiser
Atmos. Chem. Phys., 20, 2073–2097, https://doi.org/10.5194/acp-20-2073-2020, https://doi.org/10.5194/acp-20-2073-2020, 2020
Short summary
Short summary
Fires and the smoke they emit impact air quality, health, and climate, but the abundance and properties of smoke remain uncertain and poorly constrained. To explore this, we compare model simulations driven by four commonly-used fire emission inventories with surface, aloft, and satellite observations. We show that across inventories smoke emissions differ by factors of 4 to 7 over North America, challenging our ability to accurately characterize the impact of smoke on air quality and climate.
Larisa Sogacheva, Thomas Popp, Andrew M. Sayer, Oleg Dubovik, Michael J. Garay, Andreas Heckel, N. Christina Hsu, Hiren Jethva, Ralph A. Kahn, Pekka Kolmonen, Miriam Kosmale, Gerrit de Leeuw, Robert C. Levy, Pavel Litvinov, Alexei Lyapustin, Peter North, Omar Torres, and Antti Arola
Atmos. Chem. Phys., 20, 2031–2056, https://doi.org/10.5194/acp-20-2031-2020, https://doi.org/10.5194/acp-20-2031-2020, 2020
Short summary
Short summary
The typical lifetime of a single satellite platform is on the order of 5–15 years; thus, for climate studies the usage of multiple satellite sensors should be considered.
Here we introduce and evaluate a monthly AOD merged product and AOD global and regional time series for the period 1995–2017 created from 12 individual satellite AOD products, which provide a long-term perspective on AOD changes over different regions of the globe.
Guangliang Fu, Otto Hasekamp, Jeroen Rietjens, Martijn Smit, Antonio Di Noia, Brian Cairns, Andrzej Wasilewski, David Diner, Felix Seidel, Feng Xu, Kirk Knobelspiesse, Meng Gao, Arlindo da Silva, Sharon Burton, Chris Hostetler, John Hair, and Richard Ferrare
Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, https://doi.org/10.5194/amt-13-553-2020, 2020
Short summary
Short summary
In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON (the Netherlands Institute for Space Research). We perform aerosol retrievals from different multi-angle polarimeters employed during the ACEPOL campaign and evaluate them against ground-based AERONET measurements and High Spectral Resolution Lidar-2 (HSRL-2) measurements.
Xiaohua Pan, Charles Ichoku, Mian Chin, Huisheng Bian, Anton Darmenov, Peter Colarco, Luke Ellison, Tom Kucsera, Arlindo da Silva, Jun Wang, Tomohiro Oda, and Ge Cui
Atmos. Chem. Phys., 20, 969–994, https://doi.org/10.5194/acp-20-969-2020, https://doi.org/10.5194/acp-20-969-2020, 2020
Short summary
Short summary
The differences between these six BB emission datasets are large. Our study found that (1) most current biomass burning (BB) aerosol emission datasets derived from satellite observations lead to the underestimation of aerosol optical depth (AOD) in this model in the biomass-burning-dominated regions and (2) it is important to accurately estimate both the magnitudes and spatial patterns of regional BB emissions in order for a model using these emissions to reproduce observed AOD levels.
Hongbin Yu, Yang Yang, Hailong Wang, Qian Tan, Mian Chin, Robert C. Levy, Lorraine A. Remer, Steven J. Smith, Tianle Yuan, and Yingxi Shi
Atmos. Chem. Phys., 20, 139–161, https://doi.org/10.5194/acp-20-139-2020, https://doi.org/10.5194/acp-20-139-2020, 2020
Short summary
Short summary
Emissions and long-range transport of mineral dust and
combustion-related aerosol from burning fossil fuels and biomass vary from year to year, driven by the evolution of the economy and changes in meteorological conditions and environmental regulations. This study offers both satellite and model perspectives on interannual variability and possible trends in combustion aerosol and dust in major continental outflow regions over the past 15 years (2003–2017).
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, Robert E. Holz, and Andrew K. Heidinger
Atmos. Meas. Tech., 12, 6557–6577, https://doi.org/10.5194/amt-12-6557-2019, https://doi.org/10.5194/amt-12-6557-2019, 2019
Short summary
Short summary
Aerosol optical depth (AOD) from a geostationary satellite has been retrieved, and validated and diurnal cycles of aerosols are discussed over the eastern hemisphere and a 2-month period of May–June 2016. The new AOD product matches well with AERONET as well as with the standard MODIS product. Future work to make this algorithm operational will need to re-examine masking including snow masks, re-evaluate assumed aerosol models for geosynchronous geometry and address the surface characterization.
Huisheng Bian, Karl Froyd, Daniel M. Murphy, Jack Dibb, Anton Darmenov, Mian Chin, Peter R. Colarco, Arlindo da Silva, Tom L. Kucsera, Gregory Schill, Hongbin Yu, Paul Bui, Maximilian Dollner, Bernadett Weinzierl, and Alexander Smirnov
Atmos. Chem. Phys., 19, 10773–10785, https://doi.org/10.5194/acp-19-10773-2019, https://doi.org/10.5194/acp-19-10773-2019, 2019
Short summary
Short summary
We address the GEOS-GOCART sea salt simulations constrained by NASA EVS ATom measurements, as well as those by MODIS and the AERONET MAN. The study covers remote regions over the Pacific, Atlantic, and Southern oceans from near the surface to ~ 12 km altitude and covers both summer and winter seasons. Important sea salt fields, e.g., mass mixing ratio, vertical distribution, size distribution, and marine aerosol AOD, as well as their relationship to relative humidity and emissions, are examined.
Yingxi R. Shi, Robert C. Levy, Thomas F. Eck, Brad Fisher, Shana Mattoo, Lorraine A. Remer, Ilya Slutsker, and Jianglong Zhang
Atmos. Chem. Phys., 19, 259–274, https://doi.org/10.5194/acp-19-259-2019, https://doi.org/10.5194/acp-19-259-2019, 2019
Short summary
Short summary
The Indonesian fire and smoke event of 2015 was an extreme episode that affected public health and caused severe economic and environmental damage. We managed to retrieve data over very thick smoke plumes and produce a lot more high aerosol loading data that were previously missed by other satellite products. These results will benefit varieties of downstream research that use the satellite aerosol data and will influence the future development of the global satellite aerosol algorithm.
Fei Liu, Sungyeon Choi, Can Li, Vitali E. Fioletov, Chris A. McLinden, Joanna Joiner, Nickolay A. Krotkov, Huisheng Bian, Greet Janssens-Maenhout, Anton S. Darmenov, and Arlindo M. da Silva
Atmos. Chem. Phys., 18, 16571–16586, https://doi.org/10.5194/acp-18-16571-2018, https://doi.org/10.5194/acp-18-16571-2018, 2018
Short summary
Short summary
Sulfur dioxide measurements from space have been used to detect emissions from large sources. We developed a new emission inventory by combining the satellite-based emission estimates and the conventional bottom-up inventory for smaller sources. The new inventory improves the model agreement with in situ observations and offers the possibility of rapid updates to emissions.
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
Short summary
Short summary
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.
Angela Benedetti, Jeffrey S. Reid, Peter Knippertz, John H. Marsham, Francesca Di Giuseppe, Samuel Rémy, Sara Basart, Olivier Boucher, Ian M. Brooks, Laurent Menut, Lucia Mona, Paolo Laj, Gelsomina Pappalardo, Alfred Wiedensohler, Alexander Baklanov, Malcolm Brooks, Peter R. Colarco, Emilio Cuevas, Arlindo da Silva, Jeronimo Escribano, Johannes Flemming, Nicolas Huneeus, Oriol Jorba, Stelios Kazadzis, Stefan Kinne, Thomas Popp, Patricia K. Quinn, Thomas T. Sekiyama, Taichu Tanaka, and Enric Terradellas
Atmos. Chem. Phys., 18, 10615–10643, https://doi.org/10.5194/acp-18-10615-2018, https://doi.org/10.5194/acp-18-10615-2018, 2018
Short summary
Short summary
Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation authorities, solar energy plant managers, climate service providers, and health professionals. This paper describes the advances in the field and sets out requirements for observations for the sustainability of these activities.
Robert C. Levy, Shana Mattoo, Virginia Sawyer, Yingxi Shi, Peter R. Colarco, Alexei I. Lyapustin, Yujie Wang, and Lorraine A. Remer
Atmos. Meas. Tech., 11, 4073–4092, https://doi.org/10.5194/amt-11-4073-2018, https://doi.org/10.5194/amt-11-4073-2018, 2018
Short summary
Short summary
Global aerosol data sets are essential for assessing climate-related questions. When comparing data sets derived from twin satellite sensors, we find consistent global offsets between morning and afternoon observations. Applying satellite-like sampling to a global model derives much weaker morning/afternoon offsets, suggesting that the observational differences are due to calibration. However, applying additional calibration corrections appears to reduce (but not remove) the global offsets.
Jun Wang, Partha S. Bhattacharjee, Vijay Tallapragada, Cheng-Hsuan Lu, Shobha Kondragunta, Arlindo da Silva, Xiaoyang Zhang, Sheng-Po Chen, Shih-Wei Wei, Anton S. Darmenov, Jeff McQueen, Pius Lee, Prabhat Koner, and Andy Harris
Geosci. Model Dev., 11, 2315–2332, https://doi.org/10.5194/gmd-11-2315-2018, https://doi.org/10.5194/gmd-11-2315-2018, 2018
Short summary
Short summary
The NEMS GFS Aerosol Component (NGAC) version 2.0 for global multispecies aerosol forecast was developed at NCEP. Additional sea salt, sulfate, organic carbon, and black carbon aerosol species were included. This implementation advanced the global aerosol forecast capability and made a step forward toward developing a global aerosol data assimilation system. The aerosol products from this system have been provided to meet the stakeholder's needs.
Falguni Patadia, Robert C. Levy, and Shana Mattoo
Atmos. Meas. Tech., 11, 3205–3219, https://doi.org/10.5194/amt-11-3205-2018, https://doi.org/10.5194/amt-11-3205-2018, 2018
Short summary
Short summary
Satellite-measured radiance from an Earth scene comprises light scattered and absorbed by gases, clouds and aerosols in the atmosphere and by the Earth surface. To retrieve aerosol information, the signal from clouds, gases and the surface must be separated from the aerosol signal. This paper highlights the gas absorption correction method used by the MODIS dark-target aerosol retrieval algorithm and demonstrates that aerosol retrieval accuracy depends on accurate gas absorption correction.
Pawan Gupta, Lorraine A. Remer, Robert C. Levy, and Shana Mattoo
Atmos. Meas. Tech., 11, 3145–3159, https://doi.org/10.5194/amt-11-3145-2018, https://doi.org/10.5194/amt-11-3145-2018, 2018
Short summary
Short summary
In this study, we perform global validation of MODIS high-resolution (3 km) AOD over global land by comparing against AERONET measurements. The MODIS–AERONET collocated data sets consist of 161 410 high-confidence AOD pairs from 2000 to 2015 for Terra MODIS and 2003 to 2015 for Aqua MODIS. We find that 62.5 and 68.4 % of AODs retrieved from Terra MODIS and Aqua MODIS, respectively, fall within previously published expected error.
Antti Lipponen, Tero Mielonen, Mikko R. A. Pitkänen, Robert C. Levy, Virginia R. Sawyer, Sami Romakkaniemi, Ville Kolehmainen, and Antti Arola
Atmos. Meas. Tech., 11, 1529–1547, https://doi.org/10.5194/amt-11-1529-2018, https://doi.org/10.5194/amt-11-1529-2018, 2018
Short summary
Short summary
Atmospheric aerosols are small solid or liquid particles suspended in the atmosphere and they have a significant effect on the climate. Satellite data are used to get global estimates of atmospheric aerosols. In this work, a statistics-based Bayesian aerosol retrieval algorithm was developed to improve the accuracy and quantify the uncertainties related to the aerosol estimates. The algorithm is tested with NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data.
Igor Veselovskii, Philippe Goloub, Thierry Podvin, Didier Tanre, Arlindo da Silva, Peter Colarco, Patricia Castellanos, Mikhail Korenskiy, Qiaoyun Hu, David N. Whiteman, Daniel Pérez-Ramírez, Patrick Augustin, Marc Fourmentin, and Alexei Kolgotin
Atmos. Meas. Tech., 11, 949–969, https://doi.org/10.5194/amt-11-949-2018, https://doi.org/10.5194/amt-11-949-2018, 2018
Short summary
Short summary
Observations of multiwavelength Mie–Raman lidar during smoke episode over West Africa are compared with the vertical distribution of aerosol parameters provided by the MERRA-2 model. The values of modeled and observed extinctions at both 355 nm and 532 nm are also rather close. The model predicts significant concentration of dust particles inside the smoke layer. This is supported by a high depolarization ratio of 15 % observed in the center of this layer.
Peter R. Colarco, Santiago Gassó, Changwoo Ahn, Virginie Buchard, Arlindo M. da Silva, and Omar Torres
Atmos. Meas. Tech., 10, 4121–4134, https://doi.org/10.5194/amt-10-4121-2017, https://doi.org/10.5194/amt-10-4121-2017, 2017
Short summary
Short summary
We need satellite observations to characterize the properties of atmospheric aerosols. Those observations have uncertainties associated with them because of assumptions made in their algorithms. We test the assumptions on a part of the aerosol algorithms used with the Ozone Monitoring Instrument (OMI) flying on the NASA Aura spacecraft. We simulate the OMI observations using a global aerosol model, and then compare what OMI tells us about the simulated aerosols with the model results directly.
Frank Werner, Galina Wind, Zhibo Zhang, Steven Platnick, Larry Di Girolamo, Guangyu Zhao, Nandana Amarasinghe, and Kerry Meyer
Atmos. Meas. Tech., 9, 5869–5894, https://doi.org/10.5194/amt-9-5869-2016, https://doi.org/10.5194/amt-9-5869-2016, 2016
Short summary
Short summary
A research–level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. This yields reliable estimates of important cloud variables at a horizontal resolution of 30 m. Comparisons of the ASTER retrieval results with the operational cloud products from the Moderate Resolution Imaging Spectroradiometer (MODIS) show a high agreement for 48 example cloud fields.
Aristeidis K. Georgoulias, Georgia Alexandri, Konstantinos A. Kourtidis, Jos Lelieveld, Prodromos Zanis, Ulrich Pöschl, Robert Levy, Vassilis Amiridis, Eleni Marinou, and Athanasios Tsikerdekis
Atmos. Chem. Phys., 16, 13853–13884, https://doi.org/10.5194/acp-16-13853-2016, https://doi.org/10.5194/acp-16-13853-2016, 2016
Short summary
Short summary
In this work, single pixel observations from MODIS Terra and Aqua are analyzed together with data from other satellite sensors, reanalysis projects and a chemistry–aerosol-transport model to study the spatiotemporal variability of different aerosol types. The results are in accordance with previous works and are a good reference for future studies in the area focusing on aerosols, clouds, radiation and the effects of particle pollution on human health.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, and Leigh A. Munchak
Atmos. Meas. Tech., 9, 3293–3308, https://doi.org/10.5194/amt-9-3293-2016, https://doi.org/10.5194/amt-9-3293-2016, 2016
Short summary
Short summary
A new surface scheme inside MODIS dark target aerosol retrieval algorithm has been developed to improve the accuracy of aerosol optical depth data over cities. The new scheme integrates the MODIS land surface reflectance and land cover type information into the surface parameterization for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region. The improved aerosols data sets will be useful for air quality applications over cities.
Souichiro Hioki, Ping Yang, Bryan A. Baum, Steven Platnick, Kerry G. Meyer, Michael D. King, and Jerome Riedi
Atmos. Chem. Phys., 16, 7545–7558, https://doi.org/10.5194/acp-16-7545-2016, https://doi.org/10.5194/acp-16-7545-2016, 2016
Short summary
Short summary
The degree of surface roughness of ice particles within thick, cold ice clouds is inferred from multi-directional, multi-spectral satellite polarimetric observations over oceans, assuming a column-aggregate particle habit. An improved roughness inference scheme is employed, which provides a more noise-resilient roughness estimate than the conventional approach. A global one-month data sample shows the use and the limit of a severely roughened ice habit to simulate the polarized reflectivity.
Cheng-Hsuan Lu, Arlindo da Silva, Jun Wang, Shrinivas Moorthi, Mian Chin, Peter Colarco, Youhua Tang, Partha S. Bhattacharjee, Shen-Po Chen, Hui-Ya Chuang, Hann-Ming Henry Juang, Jeffery McQueen, and Mark Iredell
Geosci. Model Dev., 9, 1905–1919, https://doi.org/10.5194/gmd-9-1905-2016, https://doi.org/10.5194/gmd-9-1905-2016, 2016
Short summary
Short summary
Aerosols have an important effect on the Earth's climate and implications for public health. NASA has partnered with NOAA to transfer GOCART aerosol model to NCEP, enabling the first global aerosol forecasting system at NOAA/NCEP. This collaboration reflects an effective research-to-operation transition, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders and to allow the effects of aerosols on weather and climate prediction to be considered.
Kerry Meyer, Yuekui Yang, and Steven Platnick
Atmos. Meas. Tech., 9, 1785–1797, https://doi.org/10.5194/amt-9-1785-2016, https://doi.org/10.5194/amt-9-1785-2016, 2016
Short summary
Short summary
This paper presents the expected uncertainties of a single-channel cloud opacity retrieval technique and a temperature-based cloud phase approach in support of the Deep Space Climate Observatory (DSCOVR) mission; DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations. Results show that, for ice clouds, retrieval errors are minimal (< 2 %), while for liquid clouds the error is limited to within 10 %, although for thin clouds the error can be higher.
Robert E. Holz, Steven Platnick, Kerry Meyer, Mark Vaughan, Andrew Heidinger, Ping Yang, Gala Wind, Steven Dutcher, Steven Ackerman, Nandana Amarasinghe, Fredrick Nagle, and Chenxi Wang
Atmos. Chem. Phys., 16, 5075–5090, https://doi.org/10.5194/acp-16-5075-2016, https://doi.org/10.5194/acp-16-5075-2016, 2016
Kerry Meyer, Steven Platnick, G. Thomas Arnold, Robert E. Holz, Paolo Veglio, John Yorks, and Chenxi Wang
Atmos. Meas. Tech., 9, 1743–1753, https://doi.org/10.5194/amt-9-1743-2016, https://doi.org/10.5194/amt-9-1743-2016, 2016
Short summary
Short summary
Cirrus cloud optical and microphysical properties are retrieved from remote sensing solar reflectance measurements at two narrow wavelength channels within the broader water vapor absorption band at 1.88 µm. Results from this technique compare well with other solar reflectance, IR, and lidar-based retrievals. This approach is complementary to traditional remote sensing techniques and can extend cloud retrieval capabilities for thin cirrus clouds.
Benjamin Marchant, Steven Platnick, Kerry Meyer, G. Thomas Arnold, and Jérôme Riedi
Atmos. Meas. Tech., 9, 1587–1599, https://doi.org/10.5194/amt-9-1587-2016, https://doi.org/10.5194/amt-9-1587-2016, 2016
Short summary
Short summary
The current paper presents the new MODIS Collection 6 (C6) cloud thermodynamic phase classification algorithm. To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.
Zhibo Zhang, Kerry Meyer, Hongbin Yu, Steven Platnick, Peter Colarco, Zhaoyan Liu, and Lazaros Oreopoulos
Atmos. Chem. Phys., 16, 2877–2900, https://doi.org/10.5194/acp-16-2877-2016, https://doi.org/10.5194/acp-16-2877-2016, 2016
Short summary
Short summary
The frequency of occurrence and shortwave direct radiative effects (DRE) of above-cloud aerosols (ACAs) over global oceans are investigated using 8 years of collocated CALIOP and MODIS observations. We estimated that ACAs have a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m−2 (range of −0.03 to 0.06 W m−2) at TOA. The DREs at surface and within atmosphere are −0.15 W m−2 (range of −0.09 to −0.21 W m−2), and 0.17 W m−2 (range of 0.11 to 0.24 W m−2), respectively.
Q. Xiao, H. Zhang, M. Choi, S. Li, S. Kondragunta, J. Kim, B. Holben, R. C. Levy, and Y. Liu
Atmos. Chem. Phys., 16, 1255–1269, https://doi.org/10.5194/acp-16-1255-2016, https://doi.org/10.5194/acp-16-1255-2016, 2016
Short summary
Short summary
Using ground AOD measurements from AERONET, DRAGON-Asia Campaign, and handheld sunphotometers, we evaluated emerging aerosol products from VIIRS, GOCI, and Terra and Aqua MODIS (Collection 6) in East Asia in 2012–2013. We found that satellite aerosol products performed better in tracking the day-to-day variability than the high-resolution spatial variability. VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3 km products had positive biases.
E. Jäkel, B. Mey, R. Levy, X. Gu, T. Yu, Z. Li, D. Althausen, B. Heese, and M. Wendisch
Atmos. Meas. Tech., 8, 5237–5249, https://doi.org/10.5194/amt-8-5237-2015, https://doi.org/10.5194/amt-8-5237-2015, 2015
R. C. Levy, L. A. Munchak, S. Mattoo, F. Patadia, L. A. Remer, and R. E. Holz
Atmos. Meas. Tech., 8, 4083–4110, https://doi.org/10.5194/amt-8-4083-2015, https://doi.org/10.5194/amt-8-4083-2015, 2015
Short summary
Short summary
Aerosol optical depth (AOD) is an essential climate variable, so we seek to create a long-term AOD record. From MODIS, we have 15+ years, which we want to continue with VIIRS. Accounting for instrumental difference, we have developed a MODIS-like algorithm for VIIRS, and applied it to overlapping 2-year time period. In general, the two data sets are similar, except for VIIRS being high-biased over ocean. We discuss the impacts of calibration, resolution, and sampling on the results.
V. Buchard, A. M. da Silva, P. R. Colarco, A. Darmenov, C. A. Randles, R. Govindaraju, O. Torres, J. Campbell, and R. Spurr
Atmos. Chem. Phys., 15, 5743–5760, https://doi.org/10.5194/acp-15-5743-2015, https://doi.org/10.5194/acp-15-5743-2015, 2015
Short summary
Short summary
MERRAero is an aerosol reanalysis based on the GEOS-5 earth system model that incorporates an online aerosol module and assimilation of AOD from MODIS sensors. This study assesses the quality of MERRAero absorption using independent OMI observations. In addition to comparisons to OMI absorption AOD, we have developed a radiative transfer interface to simulate the UV aerosol index from assimilated aerosol fields at OMI footprint. Also, we fully diagnose the model using MISR, AERONET and CALIPSO.
W. R. Sessions, J. S. Reid, A. Benedetti, P. R. Colarco, A. da Silva, S. Lu, T. Sekiyama, T. Y. Tanaka, J. M. Baldasano, S. Basart, M. E. Brooks, T. F. Eck, M. Iredell, J. A. Hansen, O. C. Jorba, H.-M. H. Juang, P. Lynch, J.-J. Morcrette, S. Moorthi, J. Mulcahy, Y. Pradhan, M. Razinger, C. B. Sampson, J. Wang, and D. L. Westphal
Atmos. Chem. Phys., 15, 335–362, https://doi.org/10.5194/acp-15-335-2015, https://doi.org/10.5194/acp-15-335-2015, 2015
Short summary
A. Lyapustin, Y. Wang, X. Xiong, G. Meister, S. Platnick, R. Levy, B. Franz, S. Korkin, T. Hilker, J. Tucker, F. Hall, P. Sellers, A. Wu, and A. Angal
Atmos. Meas. Tech., 7, 4353–4365, https://doi.org/10.5194/amt-7-4353-2014, https://doi.org/10.5194/amt-7-4353-2014, 2014
P. Kishcha, A. M. da Silva, B. Starobinets, C. N. Long, O. Kalashnikova, and P. Alpert
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-23309-2014, https://doi.org/10.5194/acpd-14-23309-2014, 2014
Revised manuscript not accepted
U. Hamann, A. Walther, B. Baum, R. Bennartz, L. Bugliaro, M. Derrien, P. N. Francis, A. Heidinger, S. Joro, A. Kniffka, H. Le Gléau, M. Lockhoff, H.-J. Lutz, J. F. Meirink, P. Minnis, R. Palikonda, R. Roebeling, A. Thoss, S. Platnick, P. Watts, and G. Wind
Atmos. Meas. Tech., 7, 2839–2867, https://doi.org/10.5194/amt-7-2839-2014, https://doi.org/10.5194/amt-7-2839-2014, 2014
P. R. Colarco, R. A. Kahn, L. A. Remer, and R. C. Levy
Atmos. Meas. Tech., 7, 2313–2335, https://doi.org/10.5194/amt-7-2313-2014, https://doi.org/10.5194/amt-7-2313-2014, 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
Z. Zhang, K. Meyer, S. Platnick, L. Oreopoulos, D. Lee, and H. Yu
Atmos. Meas. Tech., 7, 1777–1789, https://doi.org/10.5194/amt-7-1777-2014, https://doi.org/10.5194/amt-7-1777-2014, 2014
M. Chin, T. Diehl, Q. Tan, J. M. Prospero, R. A. Kahn, L. A. Remer, H. Yu, A. M. Sayer, H. Bian, I. V. Geogdzhayev, B. N. Holben, S. G. Howell, B. J. Huebert, N. C. Hsu, D. Kim, T. L. Kucsera, R. C. Levy, M. I. Mishchenko, X. Pan, P. K. Quinn, G. L. Schuster, D. G. Streets, S. A. Strode, O. Torres, and X.-P. Zhao
Atmos. Chem. Phys., 14, 3657–3690, https://doi.org/10.5194/acp-14-3657-2014, https://doi.org/10.5194/acp-14-3657-2014, 2014
J. M. Livingston, J. Redemann, Y. Shinozuka, R. Johnson, P. B. Russell, Q. Zhang, S. Mattoo, L. Remer, R. Levy, L. Munchak, and S. Ramachandran
Atmos. Chem. Phys., 14, 2015–2038, https://doi.org/10.5194/acp-14-2015-2014, https://doi.org/10.5194/acp-14-2015-2014, 2014
V. Buchard, A. M. da Silva, P. Colarco, N. Krotkov, R. R. Dickerson, J. W. Stehr, G. Mount, E. Spinei, H. L. Arkinson, and H. He
Atmos. Chem. Phys., 14, 1929–1941, https://doi.org/10.5194/acp-14-1929-2014, https://doi.org/10.5194/acp-14-1929-2014, 2014
G. Wind, A. M. da Silva, P. M. Norris, and S. Platnick
Geosci. Model Dev., 6, 2049–2062, https://doi.org/10.5194/gmd-6-2049-2013, https://doi.org/10.5194/gmd-6-2049-2013, 2013
R. C. Levy, S. Mattoo, L. A. Munchak, L. A. Remer, A. M. Sayer, F. Patadia, and N. C. Hsu
Atmos. Meas. Tech., 6, 2989–3034, https://doi.org/10.5194/amt-6-2989-2013, https://doi.org/10.5194/amt-6-2989-2013, 2013
P. E. Saide, G. R. Carmichael, Z. Liu, C. S. Schwartz, H. C. Lin, A. M. da Silva, and E. Hyer
Atmos. Chem. Phys., 13, 10425–10444, https://doi.org/10.5194/acp-13-10425-2013, https://doi.org/10.5194/acp-13-10425-2013, 2013
L. A. Remer, S. Mattoo, R. C. Levy, and L. A. Munchak
Atmos. Meas. Tech., 6, 1829–1844, https://doi.org/10.5194/amt-6-1829-2013, https://doi.org/10.5194/amt-6-1829-2013, 2013
L. A. Munchak, R. C. Levy, S. Mattoo, L. A. Remer, B. N. Holben, J. S. Schafer, C. A. Hostetler, and R. A. Ferrare
Atmos. Meas. Tech., 6, 1747–1759, https://doi.org/10.5194/amt-6-1747-2013, https://doi.org/10.5194/amt-6-1747-2013, 2013
Related subject area
Atmospheric sciences
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
RoadSurf 1.1: open-source road weather model library
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
The ddeq Python library for point source quantification from remote sensing images (version 1.0)
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
A general comprehensive evaluation method for cross-scale precipitation forecasts
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
An objective identification technique for potential vorticity structures associated with African easterly waves
Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2
Assessment of surface ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4
Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta)
FUME 2.0 – Flexible Universal processor for Modeling Emissions
DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties
Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent
Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands
Balloon drift estimation and improved position estimates for radiosondes
Emission ensemble approach to improve the development of multi-scale emission inventories
What is the relative impact of nudging and online coupling on meteorological variables, pollutant concentrations and aerosol optical properties?
Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Assessing acetone for the GISS ModelE2.1 Earth system model
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
TAMS: A Tracking, Classifying, and Variable-Assigning Algorithm for Mesoscale Convective Systems in Simulated and Satellite-Derived Datasets
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary
Short summary
Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
Short summary
Short summary
RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
Short summary
Short summary
The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
Short summary
Short summary
We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
Short summary
Short summary
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
Short summary
Short summary
By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
Short summary
Short summary
We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
Short summary
Short summary
This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
Short summary
Short summary
Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
Short summary
Short summary
The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
Short summary
Short summary
The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
Short summary
Short summary
There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
Short summary
Short summary
This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
Short summary
Short summary
This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
Short summary
Short summary
We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
Short summary
Short summary
This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
Short summary
Short summary
Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
Short summary
Short summary
In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
Short summary
Short summary
We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
Short summary
Short summary
For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
Short summary
Short summary
Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
Short summary
Short summary
This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
Short summary
Short summary
This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
Short summary
Short summary
An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
Short summary
Short summary
This study is about the modelling of the atmospheric composition in Europe during the summer of 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impacts of two modelling processes that are able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
Short summary
Short summary
Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM2.5, a typical air pollutant. The results will help to improve numerical models.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Short summary
Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
Short summary
Short summary
This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
Short summary
Short summary
Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
Short summary
Short summary
Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
Short summary
Short summary
Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
Short summary
Short summary
Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
Short summary
Short summary
An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
Short summary
Short summary
Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
Short summary
Short summary
In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
Short summary
Short summary
A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
Short summary
Short summary
The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
Short summary
Short summary
In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
Short summary
Short summary
The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
EGUsphere, https://doi.org/10.22541/essoar.169903618.82717612/v2, https://doi.org/10.22541/essoar.169903618.82717612/v2, 2024
Short summary
Short summary
Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate of the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
Short summary
Short summary
In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
Short summary
Short summary
Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
Short summary
Short summary
This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
Short summary
Short summary
PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Kelly M. Núñez Ocasio and Zachary L. Moon
EGUsphere, https://doi.org/10.5194/egusphere-2024-259, https://doi.org/10.5194/egusphere-2024-259, 2024
Short summary
Short summary
TAMS is an open-source mesoscale convective system tracking and classifying Python-based package that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
Short summary
Short summary
Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
Short summary
Short summary
Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Cited articles
Ackerman, A., Strabala, K., Menzel, P., Frey, R., Moeller, C., Gumley, L., Baum, B., Seemann, S. W., and Zhang, H.: Discriminating clear-sky from cloud with MODIS Algorithm Theoretical Basis Document (MOD35), ATBD Reference Number: ATBD-MOD-35, available at: http://modis-atmos.gsfc.nasa.gov/reference_atbd.html, LAD:07.06.2016, 2006.
Ackerman, S. A., Holz, R. E., Frey, R., Eloranta, E. W., Maddux, B. C., and McGill, M.: Cloud Detection with MODIS. Part II: Validation, J. Atmos. Ocean. Tech., 25, 1073–1086, https://doi.org/10.1175/2007JTECHA1053.1, 2008.
Barnes, W. L., Pagano, T. S., and Salomonson, V. V.: Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1, IEEE Trans. Geosci. Remote Sens., 36, 1088–1100, 1998.
Buchard, V., da Silva, A. M., Colarco, P., Krotkov, N., Dickerson, R. R., Stehr, J. W., Mount, G., Spinei, E., Arkinson, H. L., and He, H.: Evaluation of GEOS-5 sulfur dioxide simulations during the Frostburg, MD 2010 field campaign, Atmos. Chem. Phys., 14, 1929–1941, https://doi.org/10.5194/acp-14-1929-2014, 2014.
Chin, M., Ginoux, P., Kinne, S., Torres, O., Holben, B. N., Duncan, B. N., Martin, R. V., Logan, J. A., Higurashi, A., and Nakajima, T.: Tropospheric Aerosol Optical Thickness from the GOCART Model and Comparisons with Satellite and Sun Photometer Measurements, J. Atmos. Sci., 59, 461–483, 2002.
Colarco, P., da Silva, A., Chin, M., and Diehl, T.: Online simulations of global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth. J. Geophys. Res., 115, D14207, https://doi.org/10.1029/2009JD012820, 2010.
Colarco, P. R., Nowottnick, E. P., Randles, C. A., Yi, B., Yang, P., Kim, K.-M., Smith, J. A., and Bardeen, C. G.: Impact of Radiatively Interactive Dust Aerosols in the NASA GEOS-5 Climate Model: Sensitivity to Dust Particle Shape and Refractive Index, J. Geophys. Res., 119, 753–786, https://doi.org/10.1002/2013JD020046, 2013.
Correia, A. and Pires, C.: Validation of aerosol optical depth retrievals by remote sensing over Brazil and South America using MODIS, Anais do XIV Congresso Brasileiro de Meteorologia, 2006.
Darmenov, A. and da Silva, A.: The Quick Fire Emissions Dataset (QFED): Documentation of versions 2.1, 2.2 and 2.4. NASA/TM–2015–104606, 38, 1–212, 2015.
Diehl, T., Heil, A., Chin, M., Pan, X., Streets, D., Schultz, M., and Kinne, S.: Anthropogenic, biomass burning, and volcanic emissions of black carbon, organic carbon, and SO2 from 1980 to 2010 for hindcast model experiments, Atmos. Chem. Phys. Discuss., 12, 24895–24954, https://doi.org/10.5194/acpd-12-24895-2012, 2012.
Dubovik, O. and King, M. D.: A flexible inversion algorithm for retrieval of aerosol optical properties from sun and sky radiance measurements, J. Geophys. Res., 105, 20673–20696, 2000.
Dubovik, O., Holben, B. N., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D., Tanré, D., and Slutsker, I.: Variability of absorption and optical properties of key aerosol types observed in worldwide locations, J. Atmos. Sci., 59, 590–608, 2002.
Freitas, S., da Silva, A., Benedetti, A., Grell, G., Jorba, O., and Mokhtari, M.: Evaluating Aerosol Impacts on Numerical Weather Prediction: A WGNE Initiative, Symposium on Coupled Chemistry-Meteorology/Climate Modeling, Switzerland, 23–25 February 2015.
Hess, M., Koepke, P., and Schult, I.: Optical properties of aerosols and clouds: The software package OPAC, B. Am. Meteorol. Soc., 79, 831–844, 1998.
Hill, C., DeLuca, C., Balaji, V., Suarez, M., and da Silva, A.: The architecture of the Earth System Modeling Framework, Comp. Sci. Engr., 6, 18–28, 2004.
Holben, B. N., Eck, T. F., Slutsker, I., Tanre, D., Buis, J. P., Setzer, A., Vermote, E. F., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F., Jankowiak, I., and Smirnov, A.: AERONET – A federated instrument network and data archive for aerosol characterization, Remote Sens. Environ., 66, 1–16, 1998.
Kahn, R. A., Garay, M. J., Nelson, D. L., Yau, K. K., Bull, M. A., Gaitley, B. J., Martonchik, J. V., and Levy, R. C.: Satellite-derived aerosol optical depth over dark water from MISR and MODIS: Comparisons with AERONET and implications for climatological studies, J. Geophys. Res., 112, D18205, https://doi.org/10.1029/2006JD008175, 2007.
Kaufman, Y. J., Wald, A. E., Remer, L. A., Gao, B. C., Li, R. R., and Flynn, L.: The MODIS 2.1 µm channel – Correlation with visible reflectance for use in remote sensing of aerosol, IEEE Trans. Geosci. Remote Sens., 35, 1286–1298, 1997.
Kleist, D. T., Parrish, D. F., Derber, J. C., Treadon, R., Wu, W.-S., and Lord, S.: Introduction of the GSI into the NCEP Global Data Assimilation System, Weather Forecast., 24, 1691–1705, https://doi.org/10.1175/2009WAF2222201.1, 2009.
Levy, R. C., Remer, L. A., Mattoo, S., Vermote, E. F., and Kaufman, Y. J.: Second-generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance, J. Geophys. Res.-Atmos., 112, D13211, https://doi.org/10.1029/2006JD007811, 2007.
Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia, F., and Hsu, N. C.: The Collection 6 MODIS aerosol products over land and ocean, Atmos. Meas. Tech., 6, 2989–3034, https://doi.org/10.5194/amt-6-2989-2013, 2013.
Meng, Z., Yang, P., Kattawar, G. W., Bi, L., Liou, K. N., and Laszlo, I.: Single-scattering properties of tri-axial ellipsoidal mineral dust aerosols: A database for application to radiative transfer calculations, J. Aerosol Sci., 41, 501–512, 2010.
Meyer, K. G. and Platnick, S. E.: Simultaneously inferring above-cloud absorbing aerosol optical thickness and underlying liquid phase cloud optical and microphysical properties using MODIS, J. Geophys. Res. Atmos., 120, 5524–5547, 2015.
Meyer, K. G., Platnick, S. E., Oreopoulos, L., and Lee, D.: Estimating the direct radiative effect of absorbing aerosols overlying marine boundary layer clouds in the southeast Atlantic using MODIS and CALIOP, J. Geophys. Res. Atmos., 118, 4801–4815, 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, Tech. Rep. S. Gl. Mod. Data Assim., 28, 2012.
Moody, E. G., King, M. D., Schaaf, C. B., Hall, D. K., and Platnick, S.: Northern Hemisphere five-year average (2000–2004) spectral albedos of surfaces in the presence of snow: Statistics computed from Terra MODIS land products, Remote Sens. Environ., 111, 337–345, 2007.
Moody, E. G., King, M. D., Schaaf, C. B., and Platnick, S.: MODIS-derived spatially complete surface albedo products: Spatial and temporal pixel distribution and zonal averages, J. Appl. Meteor. Climatol., 47, 2879–2894, 2008.
Norris, P. M. and da Silva, A. M.: Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part I: Method, Q. J. Roy. Meteor. Soc., accepted, 2016.
Norris, P. M., Oreopoulos, L., Hou, A. Y., Tao, W.-K., and Zeng, X.: Representation of 3D heterogeneous cloud fields using copulas: Theory for water clouds, Q. J. Roy. Meteor. Soc., 134, 1843–1864, https://doi.org/10.1002/qj.321, 2008.
Notarnicola, C., Di Rosa, D., and Posa, F.: Cross-Comparison of MODIS and CloudSat Data as a Tool to Validate Local Cloud Cover Masks, Atmos., 2, 242–255, https://doi.org/10.3390/atmos2030242, 2011.
Pincus, R., Platnick, S., Ackerman, S. A., Hemler, R. S., and Hofmann, R. J. P.: Reconciling simulated and observed views of clouds: MODIS, ISCCP, and the limits of instrument simulators, J. Climate, 25, 4699–4720, https://doi.org/10.1175/JCLI-D-11-00267.1, 2012.
Platnick, S., King, M. D., Ackerman, S. A., Menzel, W. P., Baum, B. A., Riedi, J. C., and Frey, R. A.: The MODIS cloud products: Algorithms and examples from Terra, IEEE Trans. Geosci. Remote Sens., 41, 459–473, 2003.
Remer, L. A., Kaufman, Y. J., Tanre, D., Mattoo, S., Chu, D. A., and Martins, J. V.: The MODIS aerosol algorithm, products, and validation, J. Atmos. Sci., 62, 947–973, https://doi.org/10.1175/JAS3385.1, 2005.
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. Tech. Rep. S. Gl. Mod. Data Assim., 27, 2008.
Stamnes, K., Tsay, S. C., Wiscombe, W., and Jayaweera, K.: Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media, Appl. Optics, 27, 2502–2509, 1988.
Wind, G., da Silva, A. M., Norris, P. M., and Platnick, S.: Multi-sensor cloud retrieval simulator and remote sensing from model parameters – Part 1: Synthetic sensor radiance formulation, Geosci. Model Dev., 6, 2049–2062, https://doi.org/10.5194/gmd-6-2049-2013, 2013.
Wu, W. S., Purser, R. J., and Parrish, D. F.: Three-dimensional variational analysis with spatially inhomogeneous covariances, Mon. Weather Rev., 130, 2905–2916, 2002.
Zhang, Z. and Platnick, S.: An assessment of differences between cloud effective particle radius for marine water clouds from three MODIS spectral bands, J. Geophys. Res., 116, D20215, https://doi.org/10.1029/2011JD016216, 2011.
Short summary
The MCARS code creates sensor radiances using model-generated atmospheric columns and actual sensor and solar geometry. MCARS output looks like real data, so it is usable by any code that reads MODIS data. MCARS output can be used to test remote-sensing retrieval algorithms. Users know what went into creating the radiance: atmosphere, surface, clouds, and aerosols. Models can use MCARS output to create new parameterizations of relations of atmospheric physical quantities and measured radiances.
The MCARS code creates sensor radiances using model-generated atmospheric columns and actual...
