Articles | Volume 9, issue 1
https://doi.org/10.5194/gmd-9-17-2016
© 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-9-17-2016
© 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
| 
15 Jan 2016
Development and technical paper |
| 15 Jan 2016
GIST-PM-Asia v1: development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia
School of Environmental Science and Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 500-712,
South Korea
C. H. Song
CORRESPONDING AUTHOR
School of Environmental Science and Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 500-712,
South Korea
R. S. Park
School of Environmental Science and Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 500-712,
South Korea
Numerical Model Team, Korea Institute of Atmospheric
Prediction Systems (KIAPS), Seoul, 156-849, South Korea
M. E. Park
School of Environmental Science and Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 500-712,
South Korea
Asian Dust Research Division, National Institute of
Meteorological Research (NIMR), Jeju-do, 697-845, South Korea
K. M. Han
School of Environmental Science and Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 500-712,
South Korea
Department of Atmospheric Sciences, Yonsei University,
Seoul, 120-749, South Korea
Department of Atmospheric Sciences, Yonsei University,
Seoul, 120-749, South Korea
Y. S. Ghim
Department of Environmental Science, Hankuk University of
Foreign Studies, Yongin, 449-791, South Korea
J.-H. Woo
Department of Advanced Technology Fusion, Konkuk
University, Seoul, 143-701, South Korea
Related authors
Sojin Lee, Chul Han Song, Kyung Man Han, Daven K. Henze, Kyunghwa Lee, Jinhyeok Yu, Jung-Hun Woo, Jia Jung, Yunsoo Choi, Pablo E. Saide, and Gregory R. Carmichael
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-116, https://doi.org/10.5194/gmd-2020-116, 2020
Revised manuscript not accepted
K. M. Han, S. Lee, L. S. Chang, and C. H. Song
Atmos. Chem. Phys., 15, 1913–1938, https://doi.org/10.5194/acp-15-1913-2015, https://doi.org/10.5194/acp-15-1913-2015, 2015
R. S. Park, S. Lee, S.-K. Shin, and C. H. Song
Atmos. Chem. Phys., 14, 2185–2201, https://doi.org/10.5194/acp-14-2185-2014, https://doi.org/10.5194/acp-14-2185-2014, 2014
M. E. Park, C. H. Song, R. S. Park, J. Lee, J. Kim, S. Lee, J.-H. Woo, G. R. Carmichael, T. F. Eck, B. N. Holben, S.-S. Lee, C. K. Song, and Y. D. Hong
Atmos. Chem. Phys., 14, 659–674, https://doi.org/10.5194/acp-14-659-2014, https://doi.org/10.5194/acp-14-659-2014, 2014
Yujin J. Oak, Daniel J. Jacob, Drew C. Pendergrass, Ruijun Dang, Nadia K. Colombi, Heesung Chong, Seoyoung Lee, Su Keun Kuk, and Jhoon Kim
Atmos. Chem. Phys., 25, 3233–3252, https://doi.org/10.5194/acp-25-3233-2025, https://doi.org/10.5194/acp-25-3233-2025, 2025
Short summary
Short summary
We analyze 2015–2023 air quality trends in South Korea using surface and satellite observations. Primary pollutants have decreased, consistent with emissions reductions. Surface O3 continues to increase and PM2.5 has decreased overall, but the nitrate component has not. O3 and PM2.5 nitrate depend on nonlinear responses from precursor emissions. Satellite data indicate a recent shift to NOx-sensitive O3 and nitrate formation, where further NOx reductions will benefit both O3 and PM2.5 pollution.
Diego Guizzardi, Monica Crippa, Tim Butler, Terry Keating, Rosa Wu, Jacek W. Kamiński, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Rachel Hoesly, Marilena Muntean, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Annie Duhamel, Tabish Ansari, Kristen Foley, Guannan Geng, Yifei Chen, and Qiang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-601, https://doi.org/10.5194/essd-2024-601, 2025
Preprint under review for ESSD
Short summary
Short summary
The global air pollution emission mosaic HTAP_v3.1 is the state-of-the-art database for addressing the evolution of a set of policy-relevant air pollutants over the past 2 decades. The inventory is made by the harmonization and blending of seven regional inventories, gapfilled using the most recent release of EDGAR (EDGARv8). By incorporating the best available local information, the HTAP_v3.1 mosaic inventory can be used for policy-relevant studies at both regional and global levels.
Hyerim Kim, Xi Chen, Jun Wang, Zhendong Lu, Meng Zhou, Gregory R. Carmichael, Sang Seo Park, and Jhoon Kim
Atmos. Meas. Tech., 18, 327–349, https://doi.org/10.5194/amt-18-327-2025, https://doi.org/10.5194/amt-18-327-2025, 2025
Short summary
Short summary
We compare passive aerosol layer height (ALH) retrievals from the Earth Polychromatic Imaging Camera (EPIC), TROPOspheric Monitoring Instrument (TROPOMI), and Geostationary Environment Monitoring Spectrometer (GEMS) with lidar. GEMS shows a lower correlation (R = 0.64) than EPIC and TROPOMI (R > 0.7) but with minimal bias (0.1 km vs. overestimated by ~0.8 km). GEMS performance is improved for an ultraviolet aerosol index ≥ 3. EPIC and GEMS ALH diurnal variation differs slightly.
Chengxin Zhang, Xinhan Niu, Hongyu Wu, Zhipeng Ding, Ka Lok Chan, Jhoon Kim, Thomas Wagner, and Cheng Liu
Atmos. Chem. Phys., 25, 759–770, https://doi.org/10.5194/acp-25-759-2025, https://doi.org/10.5194/acp-25-759-2025, 2025
Short summary
Short summary
This research utilizes hourly air pollution observations from the world’s first geostationary satellite to develop a spatiotemporal neural network model for full-coverage surface NO2 pollution prediction over the next 24 hours, achieving outstanding forecasting performance and efficacy. These results highlight the profound impact of geostationary satellite observations in advancing air quality forecasting models, thereby contributing to future models for health exposure to air pollution.
Kiyeon Kim, Chul Han Song, Kyung Man Han, Greg Yarwood, Ross Beardsley, and Saewung Kim
EGUsphere, https://doi.org/10.5194/egusphere-2025-23, https://doi.org/10.5194/egusphere-2025-23, 2025
Short summary
Short summary
Despite the crucial role of halogen radicals in the atmosphere, the current CMAQ model does not account for multi-phase halogen processes. To address this issue, we incorporated 177 halogen reactions, together with anthropogenic and natural halogen emissions into the CMAQ model. Our findings reveal that incorporation of these halogen processes significantly improves model performances compared to ground observations. In addition, we emphasize the influence of halogen radicals on air quality.
Seunghwan Seo, Si-Wan Kim, Kyoung-Min Kim, Andreas Richter, Kezia Lange, John P. Burrows, Junsung Park, Hyunkee Hong, Hanlim Lee, Ukkyo Jeong, Jung-Hun Woo, and Jhoon Kim
Atmos. Meas. Tech., 18, 115–128, https://doi.org/10.5194/amt-18-115-2025, https://doi.org/10.5194/amt-18-115-2025, 2025
Short summary
Short summary
Over the Seoul metropolitan area, tropospheric NO2 vertical column densities from the Geostationary Environment Monitoring Spectrometer show distinct seasonal features. Also, varying a priori data have substantial impacts on the observed NO2 columns. The a priori data from different chemical transport models resulted in differences of up to −18.3 %. Notably, diurnal patterns of observed NO2 columns are similar for all datasets, although their a priori data exhibit contrasting diurnal patterns.
Kiyeon Kim, Kyung Man Han, Chul Han Song, Hyojun Lee, Ross Beardsley, Jinhyeok Yu, Greg Yarwood, Bonyoung Koo, Jasper Madalipay, Jung-Hun Woo, and Seogju Cho
Atmos. Chem. Phys., 24, 12575–12593, https://doi.org/10.5194/acp-24-12575-2024, https://doi.org/10.5194/acp-24-12575-2024, 2024
Short summary
Short summary
We incorporated each HONO process into the current CMAQ modeling framework to enhance the accuracy of HONO mixing ratio predictions. These results expand our understanding of HONO photochemistry and identify crucial sources of HONO that impact the total HONO budget in Seoul, South Korea. Through this investigation, we contribute to resolving discrepancies in understanding chemical transport models, with implications for better air quality management and environmental protection in the region.
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024, https://doi.org/10.5194/amt-17-6163-2024, 2024
Short summary
Short summary
In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability for monitoring diurnal variability with a high spatial resolution.
Myungje Choi, Alexei Lyapustin, Gregory L. Schuster, Sujung Go, Yujie Wang, Sergey Korkin, Ralph Kahn, Jeffrey S. Reid, Edward J. Hyer, Thomas F. Eck, Mian Chin, David J. Diner, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, and Hans Moosmüller
Atmos. Chem. Phys., 24, 10543–10565, https://doi.org/10.5194/acp-24-10543-2024, https://doi.org/10.5194/acp-24-10543-2024, 2024
Short summary
Short summary
This paper introduces a retrieval algorithm to estimate two key absorbing components in smoke (black carbon and brown carbon) using DSCOVR EPIC measurements. Our analysis reveals distinct smoke properties, including spectral absorption, layer height, and black carbon and brown carbon, over North America and central Africa. The retrieved smoke properties offer valuable observational constraints for modeling radiative forcing and informing health-related studies.
Sooyon Kim, Yeseul Cho, Hanjeong Ki, Seyoung Park, Dagun Oh, Seungjun Lee, Yeonghye Cho, Jhoon Kim, Wonjin Lee, Jaewoo Park, Ick Hoon Jin, and Sangwook Kang
Atmos. Meas. Tech., 17, 5221–5241, https://doi.org/10.5194/amt-17-5221-2024, https://doi.org/10.5194/amt-17-5221-2024, 2024
Short summary
Short summary
This paper describes new work that improves the processing of GEMS AOD data. First, we enhance the inverse-distance-weighting algorithm by incorporating quality flag information, assigning weights that are inversely proportional to the number of unreliable grids. Second, we leverage a spatiotemporal merging method to address both spatial and temporal variability. Finally, we estimate the mean field values for GEMS AOD data, enhancing our understanding of the impact of aerosols on climate change.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
Short summary
Short summary
We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Naveed Ahmad, Changqing Lin, Alexis K. H. Lau, Jhoon Kim, Tianshu Zhang, Fangqun Yu, Chengcai Li, Ying Li, Jimmy C. H. Fung, and Xiang Qian Lao
Atmos. Chem. Phys., 24, 9645–9665, https://doi.org/10.5194/acp-24-9645-2024, https://doi.org/10.5194/acp-24-9645-2024, 2024
Short summary
Short summary
This study developed a nested machine learning model to convert the GEMS NO2 column measurements into ground-level concentrations across China. The model directly incorporates the NO2 mixing height (NMH) into the methodological framework. The study underscores the importance of considering NMH when estimating ground-level NO2 from satellite column measurements and highlights the significant advantages of new-generation geostationary satellites in air quality monitoring.
Zhenyu Zhang, Jing Li, Huizheng Che, Yueming Dong, Oleg Dubovik, Thomas Eck, Pawan Gupta, Brent Holben, Jhoon Kim, Elena Lind, Trailokya Saud, Sachchida Nand Tripathi, and Tong Ying
EGUsphere, https://doi.org/10.5194/egusphere-2024-2533, https://doi.org/10.5194/egusphere-2024-2533, 2024
Short summary
Short summary
We used ground-based remote sensing data from the Aerosol Robotic Network to examine long-term trends in aerosol characteristics. We found aerosol loadings generally decreased globally, and aerosols became more scattering. These changes are closely related to variations in aerosol compositions, such as decreased anthropogenic emissions over East Asia, Europe, and North America, increased anthropogenic source over North India, increased dust activities over the Arabian Peninsula, etc.
David P. Edwards, Sara Martínez-Alonso, Duseong S. Jo, Ivan Ortega, Louisa K. Emmons, John J. Orlando, Helen M. Worden, Jhoon Kim, Hanlim Lee, Junsung Park, and Hyunkee Hong
Atmos. Chem. Phys., 24, 8943–8961, https://doi.org/10.5194/acp-24-8943-2024, https://doi.org/10.5194/acp-24-8943-2024, 2024
Short summary
Short summary
Until recently, satellite observations of atmospheric pollutants at any location could only be obtained once a day. New geostationary satellites stare at a region of the Earth to make hourly measurements, and the Geostationary Environment Monitoring Spectrometer is the first looking at Asia. These data and model simulations show how the change seen for one important pollutant that determines air quality depends on a combination of pollution emissions, atmospheric chemistry, and meteorology.
Yeseul Cho, Jhoon Kim, Sujung Go, Mijin Kim, Seoyoung Lee, Minseok Kim, Heesung Chong, Won-Jin Lee, Dong-Won Lee, Omar Torres, and Sang Seo Park
Atmos. Meas. Tech., 17, 4369–4390, https://doi.org/10.5194/amt-17-4369-2024, https://doi.org/10.5194/amt-17-4369-2024, 2024
Short summary
Short summary
Aerosol optical properties have been provided by the Geostationary Environment Monitoring Spectrometer (GEMS), the world’s first geostationary-Earth-orbit (GEO) satellite instrument designed for atmospheric environmental monitoring. This study describes improvements made to the GEMS aerosol retrieval algorithm (AERAOD) and presents its validation results. These enhancements aim to provide more accurate and reliable aerosol-monitoring results for Asia.
Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Yun-Gon Lee, Sujung Go, and Kyunghwa Lee
Atmos. Meas. Tech., 17, 4317–4335, https://doi.org/10.5194/amt-17-4317-2024, https://doi.org/10.5194/amt-17-4317-2024, 2024
Short summary
Short summary
Information about aerosol loading in the atmosphere can be collected from various satellite instruments. Aerosol products from various satellite instruments have their own error characteristics. This study statistically merged aerosol optical depth datasets from multiple instruments aboard geostationary satellites considering uncertainties. Also, a deep neural network technique is adopted for aerosol data merging.
Laura Hyesung Yang, Daniel J. Jacob, Ruijun Dang, Yujin J. Oak, Haipeng Lin, Jhoon Kim, Shixian Zhai, Nadia K. Colombi, Drew C. Pendergrass, Ellie Beaudry, Viral Shah, Xu Feng, Robert M. Yantosca, Heesung Chong, Junsung Park, Hanlim Lee, Won-Jin Lee, Soontae Kim, Eunhye Kim, Katherine R. Travis, James H. Crawford, and Hong Liao
Atmos. Chem. Phys., 24, 7027–7039, https://doi.org/10.5194/acp-24-7027-2024, https://doi.org/10.5194/acp-24-7027-2024, 2024
Short summary
Short summary
The Geostationary Environment Monitoring Spectrometer (GEMS) provides hourly measurements of NO2. We use the chemical transport model to find how emissions, chemistry, and transport drive the changes in NO2 observed by GEMS at different times of the day. In winter, the chemistry plays a minor role, and high daytime emissions dominate the diurnal variation in NO2, balanced by transport. In summer, emissions, chemistry, and transport play an important role in shaping the diurnal variation in NO2.
Drew C. Pendergrass, Daniel J. Jacob, Yujin J. Oak, Jeewoo Lee, Minseok Kim, Jhoon Kim, Seoyoung Lee, Shixian Zhai, Hitoshi Irie, and Hong Liao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-172, https://doi.org/10.5194/essd-2024-172, 2024
Preprint withdrawn
Short summary
Short summary
Fine particles suspended in the atmosphere are a major form of air pollution and an important public health burden. However, measurements of particulate matter are sparse in space and in places like East Asia monitors are established after regulatory policies to improve pollution have changed. In this paper, we use machine learning to fill in the gaps. We train an algorithm to predict pollution at the surface from the atmosphere’s opacity, then produce high resolution maps of data without gaps.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
Atmos. Meas. Tech., 17, 2873–2916, https://doi.org/10.5194/amt-17-2873-2024, https://doi.org/10.5194/amt-17-2873-2024, 2024
Short summary
Short summary
We present a new bromine monoxide (BrO) product derived using radiances measured from OMPS-NM on board the Suomi-NPP satellite. This product provides nearly a decade of global stratospheric and tropospheric column retrievals, a feature that is currently rare in publicly accessible datasets. Both stratospheric and tropospheric columns from OMPS-NM demonstrate robust performance, exhibiting good agreement with ground-based observations collected at three stations (Lauder, Utqiagvik, and Harestua).
Gitaek T. Lee, Rokjin J. Park, Hyeong-Ahn Kwon, Eunjo S. Ha, Sieun D. Lee, Seunga Shin, Myoung-Hwan Ahn, Mina Kang, Yong-Sang Choi, Gyuyeon Kim, Dong-Won Lee, Deok-Rae Kim, Hyunkee Hong, Bavo Langerock, Corinne Vigouroux, Christophe Lerot, Francois Hendrick, Gaia Pinardi, Isabelle De Smedt, Michel Van Roozendael, Pucai Wang, Heesung Chong, Yeseul Cho, and Jhoon Kim
Atmos. Chem. Phys., 24, 4733–4749, https://doi.org/10.5194/acp-24-4733-2024, https://doi.org/10.5194/acp-24-4733-2024, 2024
Short summary
Short summary
This study evaluates the Geostationary Environment Monitoring Spectrometer (GEMS) HCHO product by comparing its vertical column densities (VCDs) with those of TROPOMI and ground-based observations. Based on some sensitivity tests, obtaining radiance references under clear-sky conditions significantly improves HCHO retrieval quality. GEMS HCHO VCDs captured seasonal and diurnal variations well during the first year of observation, showing consistency with TROPOMI and ground-based observations.
Bo-Ram Kim, Gyuyeon Kim, Minjeong Cho, Yong-Sang Choi, and Jhoon Kim
Atmos. Meas. Tech., 17, 453–470, https://doi.org/10.5194/amt-17-453-2024, https://doi.org/10.5194/amt-17-453-2024, 2024
Short summary
Short summary
This study introduces the GEMS cloud algorithm and validates its results using data from GEMS and other environmental satellites. The GEMS algorithm is able to detect the lowest cloud heights among the four satellites, and its effective cloud fraction and cloud centroid pressure are well reflected in the retrieval results. The study highlights the algorithm's usefulness in correcting errors in trace gases caused by clouds in the East Asian region.
Haklim Choi, Xiong Liu, Ukkyo Jeong, Heesung Chong, Jhoon Kim, Myung Hwan Ahn, Dai Ho Ko, Dong-Won Lee, Kyung-Jung Moon, and Kwang-Mog Lee
Atmos. Meas. Tech., 17, 145–164, https://doi.org/10.5194/amt-17-145-2024, https://doi.org/10.5194/amt-17-145-2024, 2024
Short summary
Short summary
GEMS is the first geostationary satellite to measure the UV--Vis region, and this paper reports the polarization characteristics of GEMS and an algorithm. We develop a polarization correction algorithm optimized for GEMS based on a look-up-table approach that simultaneously considers the polarization of incoming light and polarization sensitivity characteristics of the instrument. Pre-launch polarization error was adjusted close to zero across the spectral range after polarization correction.
Chi-Tsan Wang, Bok H. Baek, William Vizuete, Lawrence S. Engel, Jia Xing, Jaime Green, Marc Serre, Richard Strott, Jared Bowden, and Jung-Hun Woo
Earth Syst. Sci. Data, 15, 5261–5279, https://doi.org/10.5194/essd-15-5261-2023, https://doi.org/10.5194/essd-15-5261-2023, 2023
Short summary
Short summary
Hazardous air pollutant (HAP) human exposure studies usually rely on local measurements or dispersion model methods, but those methods are limited under spatial and temporal conditions. We processed the US EPA emission data to simulate the hourly HAP emission patterns and applied the chemical transport model to simulate the HAP concentrations. The modeled HAP results exhibit good agreement (R is 0.75 and NMB is −5.6 %) with observational data.
Yuhang Zhang, Jintai Lin, Jhoon Kim, Hanlim Lee, Junsung Park, Hyunkee Hong, Michel Van Roozendael, Francois Hendrick, Ting Wang, Pucai Wang, Qin He, Kai Qin, Yongjoo Choi, Yugo Kanaya, Jin Xu, Pinhua Xie, Xin Tian, Sanbao Zhang, Shanshan Wang, Siyang Cheng, Xinghong Cheng, Jianzhong Ma, Thomas Wagner, Robert Spurr, Lulu Chen, Hao Kong, and Mengyao Liu
Atmos. Meas. Tech., 16, 4643–4665, https://doi.org/10.5194/amt-16-4643-2023, https://doi.org/10.5194/amt-16-4643-2023, 2023
Short summary
Short summary
Our tropospheric NO2 vertical column density product with high spatiotemporal resolution is based on the Geostationary Environment Monitoring Spectrometer (GEMS) and named POMINO–GEMS. Strong hotspot signals and NO2 diurnal variations are clearly seen. Validations with multiple satellite products and ground-based, mobile car and surface measurements exhibit the overall great performance of the POMINO–GEMS product, indicating its capability for application in environmental studies.
Serin Kim, Daewon Kim, Hyunkee Hong, Lim-Seok Chang, Hanlim Lee, Deok-Rae Kim, Donghee Kim, Jeong-Ah Yu, Dongwon Lee, Ukkyo Jeong, Chang-Kuen Song, Sang-Woo Kim, Sang Seo Park, Jhoon Kim, Thomas F. Hanisco, Junsung Park, Wonei Choi, and Kwangyul Lee
Atmos. Meas. Tech., 16, 3959–3972, https://doi.org/10.5194/amt-16-3959-2023, https://doi.org/10.5194/amt-16-3959-2023, 2023
Short summary
Short summary
A first evaluation of the Geostationary Environmental Monitoring Spectrometer (GEMS) NO2 was carried out via comparison with the NO2 data obtained from the ground-based Pandora direct-sun measurements at four sites in Seosan, Republic of Korea. Comparisons between GEMS NO2 and Pandora NO2 were performed according to GEMS cloud fraction. GEMS NO2 showed good agreement with that of Pandora NO2 under less cloudy conditions.
Sang Seo Park, Jhoon Kim, Yeseul Cho, Hanlim Lee, Junsung Park, Dong-Won Lee, Won-Jin Lee, and Deok-Rae Kim
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-136, https://doi.org/10.5194/amt-2023-136, 2023
Revised manuscript accepted for AMT
Short summary
Short summary
An AEH retrieval algorithm for GEMS operational product was developed that solely uses the O2-O2 absorption band with considering aerosol and surface properties. To ensure significant sensitivity of AEH retrieval, only AEH retrieval results with AOD larger than 0.3 were shown, and the retrieval results show significant estimations by comparing the aerosol height from CALIOP and aerosol layer height product from TROPOMI.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
Short summary
Short summary
This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
Jincheol Park, Jia Jung, Yunsoo Choi, Hyunkwang Lim, Minseok Kim, Kyunghwa Lee, Yun Gon Lee, and Jhoon Kim
Atmos. Meas. Tech., 16, 3039–3057, https://doi.org/10.5194/amt-16-3039-2023, https://doi.org/10.5194/amt-16-3039-2023, 2023
Short summary
Short summary
In response to the recent release of new geostationary platform-derived observational data generated by the Geostationary Environment Monitoring Spectrometer (GEMS) and its sister instruments, this study utilized the GEMS data fusion product and its proxy data in adjusting aerosol precursor emissions over East Asia. The use of spatiotemporally more complete observation references in updating the emissions resulted in more promising model performances in estimating aerosol loadings in East Asia.
Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Huidong Yeo, and Sang-Woo Kim
Atmos. Meas. Tech., 16, 2673–2690, https://doi.org/10.5194/amt-16-2673-2023, https://doi.org/10.5194/amt-16-2673-2023, 2023
Short summary
Short summary
Aerosol height information is important when seeking an understanding of the vertical structure of the aerosol layer and long-range transport. In this study, a geometrical aerosol top height (ATH) retrieval using a parallax of two geostationary satellites is investigated. With sufficient longitudinal separation between the two satellites, a decent ATH product could be retrieved.
Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
Atmos. Chem. Phys., 23, 4271–4281, https://doi.org/10.5194/acp-23-4271-2023, https://doi.org/10.5194/acp-23-4271-2023, 2023
Short summary
Short summary
Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Laura Hyesung Yang, Daniel J. Jacob, Nadia K. Colombi, Shixian Zhai, Kelvin H. Bates, Viral Shah, Ellie Beaudry, Robert M. Yantosca, Haipeng Lin, Jared F. Brewer, Heesung Chong, Katherine R. Travis, James H. Crawford, Lok N. Lamsal, Ja-Ho Koo, and Jhoon Kim
Atmos. Chem. Phys., 23, 2465–2481, https://doi.org/10.5194/acp-23-2465-2023, https://doi.org/10.5194/acp-23-2465-2023, 2023
Short summary
Short summary
A geostationary satellite can now provide hourly NO2 vertical columns, and obtaining the NO2 vertical columns from space relies on NO2 vertical distribution from the chemical transport model (CTM). In this work, we update the CTM to better represent the chemistry environment so that the CTM can accurately provide NO2 vertical distribution. We also find that the changes in NO2 vertical distribution driven by a change in mixing depth play an important role in the NO2 column's diurnal variation.
Ukkyo Jeong, Si-Chee Tsay, N. Christina Hsu, David M. Giles, John W. Cooper, Jaehwa Lee, Robert J. Swap, Brent N. Holben, James J. Butler, Sheng-Hsiang Wang, Somporn Chantara, Hyunkee Hong, Donghee Kim, and Jhoon Kim
Atmos. Chem. Phys., 22, 11957–11986, https://doi.org/10.5194/acp-22-11957-2022, https://doi.org/10.5194/acp-22-11957-2022, 2022
Short summary
Short summary
Ultraviolet (UV) measurements from satellite and ground are important for deriving information on several atmospheric trace and aerosol characteristics. Simultaneous retrievals of aerosol and trace gases in this study suggest that water uptake by aerosols is one of the important phenomena affecting aerosol properties over northern Thailand, which is important for regional air quality and climate. Obtained aerosol properties covering the UV are also important for various satellite algorithms.
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.
Bok H. Baek, Rizzieri Pedruzzi, Minwoo Park, Chi-Tsan Wang, Younha Kim, Chul-Han Song, and Jung-Hun Woo
Geosci. Model Dev., 15, 4757–4781, https://doi.org/10.5194/gmd-15-4757-2022, https://doi.org/10.5194/gmd-15-4757-2022, 2022
Short summary
Short summary
The Comprehensive Automobile Research System (CARS) is an open-source Python-based automobile emissions inventory model designed to efficiently estimate high-quality emissions. The CARS is designed to utilize the local vehicle activity database, such as vehicle travel distance, road-link-level network information, and vehicle-specific average speed by road type, to generate a temporally and spatially enhanced inventory for policymakers, stakeholders, and the air quality modeling community.
Katherine R. Travis, James H. Crawford, Gao Chen, Carolyn E. Jordan, Benjamin A. Nault, Hwajin Kim, Jose L. Jimenez, Pedro Campuzano-Jost, Jack E. Dibb, Jung-Hun Woo, Younha Kim, Shixian Zhai, Xuan Wang, Erin E. McDuffie, Gan Luo, Fangqun Yu, Saewung Kim, Isobel J. Simpson, Donald R. Blake, Limseok Chang, and Michelle J. Kim
Atmos. Chem. Phys., 22, 7933–7958, https://doi.org/10.5194/acp-22-7933-2022, https://doi.org/10.5194/acp-22-7933-2022, 2022
Short summary
Short summary
The 2016 Korea–United States Air Quality (KORUS-AQ) field campaign provided a unique set of observations to improve our understanding of PM2.5 pollution in South Korea. Models typically have errors in simulating PM2.5 in this region, which is of concern for the development of control measures. We use KORUS-AQ observations to improve our understanding of the mechanisms driving PM2.5 and the implications of model errors for determining PM2.5 that is attributable to local or foreign sources.
Soon-Young Park, Uzzal Kumar Dash, Jinhyeok Yu, Keiya Yumimoto, Itsushi Uno, and Chul Han Song
Geosci. Model Dev., 15, 2773–2790, https://doi.org/10.5194/gmd-15-2773-2022, https://doi.org/10.5194/gmd-15-2773-2022, 2022
Short summary
Short summary
An EnKF was applied to CMAQ for assimilating ground PM2.5 observations from China and South Korea. The EnKF performed better than that without assimilation and even superior to 3D-Var. The reduced MBs in 24 h predictions were 48 % and 27 % by improving ICs and BCs, respectively.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091, https://doi.org/10.5194/amt-15-1075-2022, https://doi.org/10.5194/amt-15-1075-2022, 2022
Short summary
Short summary
This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
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.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
Short summary
Short summary
Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Hyunkwang Lim, Sujung Go, Jhoon Kim, Myungje Choi, Seoyoung Lee, Chang-Keun Song, and Yasuko Kasai
Atmos. Meas. Tech., 14, 4575–4592, https://doi.org/10.5194/amt-14-4575-2021, https://doi.org/10.5194/amt-14-4575-2021, 2021
Short summary
Short summary
Aerosol property observations by satellites from geostationary Earth orbit (GEO) in particular have advantages of frequent sampling better than 1 h in addition to broader spatial coverage. This study provides data fusion products of aerosol optical properties from four different algorithms for two different GEO satellites: GOCI and AHI. The fused aerosol products adopted ensemble-mean and maximum-likelihood estimation methods. The data fusion provides improved results with better accuracy.
Yan Yu, Olga V. Kalashnikova, Michael J. Garay, Huikyo Lee, Myungje Choi, Gregory S. Okin, John E. Yorks, James R. Campbell, and Jared Marquis
Atmos. Chem. Phys., 21, 1427–1447, https://doi.org/10.5194/acp-21-1427-2021, https://doi.org/10.5194/acp-21-1427-2021, 2021
Short summary
Short summary
Given the current uncertainties in the simulated diurnal variability of global dust mobilization and concentration, observational characterization of the variations in dust mobilization and concentration will provide a valuable benchmark for evaluating and constraining such model simulations. The current study investigates the diurnal cycle of dust loading across the global tropics, subtropics, and mid-latitudes by analyzing aerosol observations from the International Space Station.
Benjamin Gaubert, Louisa K. Emmons, Kevin Raeder, Simone Tilmes, Kazuyuki Miyazaki, Avelino F. Arellano Jr., Nellie Elguindi, Claire Granier, Wenfu Tang, Jérôme Barré, Helen M. Worden, Rebecca R. Buchholz, David P. Edwards, Philipp Franke, Jeffrey L. Anderson, Marielle Saunois, Jason Schroeder, Jung-Hun Woo, Isobel J. Simpson, Donald R. Blake, Simone Meinardi, Paul O. Wennberg, John Crounse, Alex Teng, Michelle Kim, Russell R. Dickerson, Hao He, Xinrong Ren, Sally E. Pusede, and Glenn S. Diskin
Atmos. Chem. Phys., 20, 14617–14647, https://doi.org/10.5194/acp-20-14617-2020, https://doi.org/10.5194/acp-20-14617-2020, 2020
Short summary
Short summary
This study investigates carbon monoxide pollution in East Asia during spring using a numerical model, satellite remote sensing, and aircraft measurements. We found an underestimation of emission sources. Correcting the emission bias can improve air quality forecasting of carbon monoxide and other species including ozone. Results also suggest that controlling VOC and CO emissions, in addition to widespread NOx controls, can improve ozone pollution over East Asia.
Baozhu Ge, Syuichi Itahashi, Keiichi Sato, Danhui Xu, Junhua Wang, Fan Fan, Qixin Tan, Joshua S. Fu, Xuemei Wang, Kazuyo Yamaji, Tatsuya Nagashima, Jie Li, Mizuo Kajino, Hong Liao, Meigen Zhang, Zhe Wang, Meng Li, Jung-Hun Woo, Junichi Kurokawa, Yuepeng Pan, Qizhong Wu, Xuejun Liu, and Zifa Wang
Atmos. Chem. Phys., 20, 10587–10610, https://doi.org/10.5194/acp-20-10587-2020, https://doi.org/10.5194/acp-20-10587-2020, 2020
Short summary
Short summary
Performances of the simulated deposition for different reduced N (Nr) species in China were conducted with the Model Inter-Comparison Study for Asia. Results showed that simulated wet deposition of oxidized N was overestimated in northeastern China and underestimated in south China, but Nr was underpredicted in all regions by all models. Oxidized N has larger uncertainties than Nr, indicating that the chemical reaction process is one of the most importance factors affecting model performance.
Amir H. Souri, Caroline R. Nowlan, Gonzalo González Abad, Lei Zhu, Donald R. Blake, Alan Fried, Andrew J. Weinheimer, Armin Wisthaler, Jung-Hun Woo, Qiang Zhang, Christopher E. Chan Miller, Xiong Liu, and Kelly Chance
Atmos. Chem. Phys., 20, 9837–9854, https://doi.org/10.5194/acp-20-9837-2020, https://doi.org/10.5194/acp-20-9837-2020, 2020
Short summary
Short summary
For the first time, we provide a joint nonlinear optimal estimate of NOx and NMVOC emissions during the KORUS-AQ campaign by simultaneously incorporating SAO's new product of HCHO columns from OMPS and OMI tropospheric NO2 columns into a regional model. Results demonstrate a promising improvement in the performance of the model in terms of HCHO and NO2 concentrations, which in turn enables us to quantify the impact of the emission changes on different pathways of ozone formation and loss.
Teruyuki Nakajima, Monica Campanelli, Huizheng Che, Victor Estellés, Hitoshi Irie, Sang-Woo Kim, Jhoon Kim, Dong Liu, Tomoaki Nishizawa, Govindan Pandithurai, Vijay Kumar Soni, Boossarasiri Thana, Nas-Urt Tugjsurn, Kazuma Aoki, Sujung Go, Makiko Hashimoto, Akiko Higurashi, Stelios Kazadzis, Pradeep Khatri, Natalia Kouremeti, Rei Kudo, Franco Marenco, Masahiro Momoi, Shantikumar S. Ningombam, Claire L. Ryder, Akihiro Uchiyama, and Akihiro Yamazaki
Atmos. Meas. Tech., 13, 4195–4218, https://doi.org/10.5194/amt-13-4195-2020, https://doi.org/10.5194/amt-13-4195-2020, 2020
Short summary
Short summary
This paper overviews the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone. The paper also discusses current issues of SKYNET to provide better information for the community.
Arman Pouyaei, Yunsoo Choi, Jia Jung, Bavand Sadeghi, and Chul Han Song
Geosci. Model Dev., 13, 3489–3505, https://doi.org/10.5194/gmd-13-3489-2020, https://doi.org/10.5194/gmd-13-3489-2020, 2020
Short summary
Short summary
This paper introduces a novel Lagrangian model (Concentration Trajectory of Air pollution with an Integrated Lagrangian model, C-TRAIL) for showing the source and receptor areas by following polluted air masses. To investigate the concentrations and trajectories of air masses simultaneously, we use the trajectory-grid (TG) Lagrangian advection model. The TG model follows the concentrations of representative air
packetsof species along trajectories determined by the wind field.
Pablo E. Saide, Meng Gao, Zifeng Lu, Daniel L. Goldberg, David G. Streets, Jung-Hun Woo, Andreas Beyersdorf, Chelsea A. Corr, Kenneth L. Thornhill, Bruce Anderson, Johnathan W. Hair, Amin R. Nehrir, Glenn S. Diskin, Jose L. Jimenez, Benjamin A. Nault, Pedro Campuzano-Jost, Jack Dibb, Eric Heim, Kara D. Lamb, Joshua P. Schwarz, Anne E. Perring, Jhoon Kim, Myungje Choi, Brent Holben, Gabriele Pfister, Alma Hodzic, Gregory R. Carmichael, Louisa Emmons, and James H. Crawford
Atmos. Chem. Phys., 20, 6455–6478, https://doi.org/10.5194/acp-20-6455-2020, https://doi.org/10.5194/acp-20-6455-2020, 2020
Short summary
Short summary
Air quality forecasts over the Korean Peninsula captured aerosol optical depth but largely overpredicted surface PM during a Chinese haze transport event. Model deficiency was related to the calculation of optical properties. In order to improve it, aerosol size representation needs to be refined in the calculations, and the representation of aerosol properties, such as size distribution, chemical composition, refractive index, hygroscopicity parameter, and density, needs to be improved.
Sojin Lee, Chul Han Song, Kyung Man Han, Daven K. Henze, Kyunghwa Lee, Jinhyeok Yu, Jung-Hun Woo, Jia Jung, Yunsoo Choi, Pablo E. Saide, and Gregory R. Carmichael
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-116, https://doi.org/10.5194/gmd-2020-116, 2020
Revised manuscript not accepted
Kyunghwa Lee, Jinhyeok Yu, Sojin Lee, Mieun Park, Hun Hong, Soon Young Park, Myungje Choi, Jhoon Kim, Younha Kim, Jung-Hun Woo, Sang-Woo Kim, and Chul H. Song
Geosci. Model Dev., 13, 1055–1073, https://doi.org/10.5194/gmd-13-1055-2020, https://doi.org/10.5194/gmd-13-1055-2020, 2020
Short summary
Short summary
For the purpose of providing reliable and robust air quality predictions, an operational air quality prediction system was developed for the main air quality criteria species in South Korea (PM10, PM2.5, CO, O3 and SO2) by preparing the initial conditions for model simulations via data assimilation using satellite- and ground-based observations. The performance of the developed air quality prediction system was evaluated using ground in situ data during the KORUS-AQ campaign period.
Meng Gao, Zhiwei Han, Zhining Tao, Jiawei Li, Jeong-Eon Kang, Kan Huang, Xinyi Dong, Bingliang Zhuang, Shu Li, Baozhu Ge, Qizhong Wu, Hyo-Jung Lee, Cheol-Hee Kim, Joshua S. Fu, Tijian Wang, Mian Chin, Meng Li, Jung-Hun Woo, Qiang Zhang, Yafang Cheng, Zifa Wang, and Gregory R. Carmichael
Atmos. Chem. Phys., 20, 1147–1161, https://doi.org/10.5194/acp-20-1147-2020, https://doi.org/10.5194/acp-20-1147-2020, 2020
Short summary
Short summary
Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative feedbacks. This paper discusses the estimates of aerosol radiative forcing, aerosol feedbacks, and possible causes for the differences among the models.
Yan Yu, Olga V. Kalashnikova, Michael J. Garay, Huikyo Lee, Myungje Choi, Gregory S. Okin, John E. Yorks, and James R. Campbell
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-975, https://doi.org/10.5194/acp-2019-975, 2019
Preprint withdrawn
Short summary
Short summary
Given the current uncertainties in the simulated diurnal variability of global dust mobilization and concentration, observational characterization of the variations in dust mobilization and concentration will provide a valuable benchmark for evaluating and constraining such model simulations. The current study investigates the diurnal cycle of dust loading across the global tropics, sub-tropics, and mid-latitudes by analyzing aerosol observations from the International Space Station.
Jay Herman, Nader Abuhassan, Jhoon Kim, Jae Kim, Manvendra Dubey, Marcelo Raponi, and Maria Tzortziou
Atmos. Meas. Tech., 12, 5593–5612, https://doi.org/10.5194/amt-12-5593-2019, https://doi.org/10.5194/amt-12-5593-2019, 2019
Short summary
Short summary
Total column NO2 (TCNO2) from the Ozone Measuring Instrument (OMI) is compared for 14 sites with ground-based PANDORA spectrometer instruments making direct-sun measurements. These sites have high TCNO2, causing significant air quality problems that can affect human health. OMI almost always underestimates the amount of TCNO2 by 50 to 100 %. OMI's large field of view (FOV) is the most likely factor when comparing OMI TCNO2 to retrievals with PANDORA. OMI misses higher afternoon values of TCNO2.
Hyun S. Kim, Inyoung Park, Chul H. Song, Kyunghwa Lee, Jae W. Yun, Hong K. Kim, Moongu Jeon, Jiwon Lee, and Kyung M. Han
Atmos. Chem. Phys., 19, 12935–12951, https://doi.org/10.5194/acp-19-12935-2019, https://doi.org/10.5194/acp-19-12935-2019, 2019
Short summary
Short summary
In this study, a deep recurrent neural network system based on a long short-term memory (LSTM) model was developed for daily PM10 and PM2.5 predictions in South Korea. In general, the accuracies of the LSTM-based predictions were superior to the 3-D CTM-based predictions. Based on this, we concluded that the LSTM-based system could be applied to daily operational PM forecasts in South Korea. We expect that similar AI systems can be applied to the predictions of other atmospheric pollutants.
Juseon Bak, Kang-Hyeon Baek, Jae-Hwan Kim, Xiong Liu, Jhoon Kim, and Kelly Chance
Atmos. Meas. Tech., 12, 5201–5215, https://doi.org/10.5194/amt-12-5201-2019, https://doi.org/10.5194/amt-12-5201-2019, 2019
Short summary
Short summary
GEMS will be launched in late 2019 on board the GeoKOMPSAT (Geostationary Korea Multi-Purpose Satellite) to measure O3, NO2, SO2, H2CO, CHOCHO, and aerosols in East Asia. To support the development of the GEMS ozone profile algorithm, we perform the cross-evaluation of simulated GEMS ozone profile retrievals based on optimal estimation and ozonesonde measurements within the GEMS domain.
Myungje Choi, Hyunkwang Lim, Jhoon Kim, Seoyoung Lee, Thomas F. Eck, Brent N. Holben, Michael J. Garay, Edward J. Hyer, Pablo E. Saide, and Hongqing Liu
Atmos. Meas. Tech., 12, 4619–4641, https://doi.org/10.5194/amt-12-4619-2019, https://doi.org/10.5194/amt-12-4619-2019, 2019
Short summary
Short summary
Satellite-based aerosol optical depth (AOD) products have been improved continuously and available from multiple low Earth orbit sensors, such as MODIS, MISR, and VIIRS, and geostationary sensors, such as GOCI and AHI, over East Asia. These multi-satellite AOD products are validated, intercompared, analyzed, and integrated to understand different characteristics, such as quality and spatio-temporal coverage, focused on several aerosol transportation cases during the 2016 KORUS-AQ campaign.
Hyeong-Ahn Kwon, Rokjin J. Park, Gonzalo González Abad, Kelly Chance, Thomas P. Kurosu, Jhoon Kim, Isabelle De Smedt, Michel Van Roozendael, Enno Peters, and John Burrows
Atmos. Meas. Tech., 12, 3551–3571, https://doi.org/10.5194/amt-12-3551-2019, https://doi.org/10.5194/amt-12-3551-2019, 2019
Short summary
Short summary
The Geostationary Environment Monitoring Spectrometer (GEMS) will be launched by South Korea in 2019, and it will measure radiances ranging from 300 to 500 nm every hour with a fine spatial resolution of 7 km x 8 km over Seoul in South Korea to monitor column concentrations of air pollutants including O3, NO2, SO2, and HCHO, as well as aerosol optical properties. This paper describes a GEMS formaldehyde retrieval algorithm including a number of sensitivity tests for algorithm evaluation.
Wenjing Su, Cheng Liu, Qihou Hu, Shaohua Zhao, Youwen Sun, Wei Wang, Yizhi Zhu, Jianguo Liu, and Jhoon Kim
Atmos. Chem. Phys., 19, 6717–6736, https://doi.org/10.5194/acp-19-6717-2019, https://doi.org/10.5194/acp-19-6717-2019, 2019
Short summary
Short summary
For a better understanding of HCHO pollution and atmospheric chemistry, we evaluated primary and secondary sources of HCHO in the Yangtze River Delta based on HCHO column density from OMPS and combined this with in situ surface measurements. We found that secondary formation contributed most to ambient HCHO over longer timescales, but primary emission could be dominant in the winter. Hence, the usability of total HCHO as a proxy of VOC reactivity depends on the timescale of interest.
Daniel L. Goldberg, Pablo E. Saide, Lok N. Lamsal, Benjamin de Foy, Zifeng Lu, Jung-Hun Woo, Younha Kim, Jinseok Kim, Meng Gao, Gregory Carmichael, and David G. Streets
Atmos. Chem. Phys., 19, 1801–1818, https://doi.org/10.5194/acp-19-1801-2019, https://doi.org/10.5194/acp-19-1801-2019, 2019
Short summary
Short summary
Using satellite data, we are able to estimate the emissions of NOx (NOx=NO+NO2), a toxic group of air pollutants, in the Seoul metropolitan area. We first develop an enhanced satellite product that better observes NO2 in urban regions. Using this new product, we derive NOx emissions to be twice as large as the emissions reported by the South Korean government. The implication is that the measures taken to reduce NOx emissions in South Korea have not been as effective as regulators have thought.
Seohui Park, Minso Shin, Jungho Im, Chang-Keun Song, Myungje Choi, Jhoon Kim, Seungun Lee, Rokjin Park, Jiyoung Kim, Dong-Won Lee, and Sang-Kyun Kim
Atmos. Chem. Phys., 19, 1097–1113, https://doi.org/10.5194/acp-19-1097-2019, https://doi.org/10.5194/acp-19-1097-2019, 2019
Short summary
Short summary
This study proposed machine-learning-based models to estimate ground-level particulate matter concentrations using satellite observations and numerical model-derived data. Aerosol optical depth was identified as the most significant for estimating ground-level PM concentrations, followed by wind speed and solar radiation. The results show that the proposed models produced better performance than the existing approaches, particularly in improving on the biases of the process-based models.
Benjamin A. Nault, Pedro Campuzano-Jost, Douglas A. Day, Jason C. Schroder, Bruce Anderson, Andreas J. Beyersdorf, Donald R. Blake, William H. Brune, Yonghoon Choi, Chelsea A. Corr, Joost A. de Gouw, Jack Dibb, Joshua P. DiGangi, Glenn S. Diskin, Alan Fried, L. Gregory Huey, Michelle J. Kim, Christoph J. Knote, Kara D. Lamb, Taehyoung Lee, Taehyun Park, Sally E. Pusede, Eric Scheuer, Kenneth L. Thornhill, Jung-Hun Woo, and Jose L. Jimenez
Atmos. Chem. Phys., 18, 17769–17800, https://doi.org/10.5194/acp-18-17769-2018, https://doi.org/10.5194/acp-18-17769-2018, 2018
Short summary
Short summary
Aerosol impacts visibility and human health in large cities. Sources of aerosols are still highly uncertain, especially for cities surrounded by numerous other cities. We use observations collected during the Korea–United States Air Quality study to determine sources of organic aerosol (OA). We find that secondary OA (SOA) is rapidly produced over Seoul, South Korea, and that the sources of the SOA originate from short-lived hydrocarbons, which originate from local emissions.
Elizabeth M. Lennartson, Jun Wang, Juping Gu, Lorena Castro Garcia, Cui Ge, Meng Gao, Myungje Choi, Pablo E. Saide, Gregory R. Carmichael, Jhoon Kim, and Scott J. Janz
Atmos. Chem. Phys., 18, 15125–15144, https://doi.org/10.5194/acp-18-15125-2018, https://doi.org/10.5194/acp-18-15125-2018, 2018
Short summary
Short summary
This paper is among the first to study the diurnal variations of AOD, PM2.5, and their relationships in South Korea. We show that the PM2.5–AOD relationship has strong diurnal variations, and, hence, using AOD data retrieved from geostationary satellite can improve the monitoring of surface PM2.5 air quality on a daily basis as well as constrain the diurnal variation of aerosol emission.
Jay Herman, Elena Spinei, Alan Fried, Jhoon Kim, Jae Kim, Woogyung Kim, Alexander Cede, Nader Abuhassan, and Michal Segal-Rozenhaimer
Atmos. Meas. Tech., 11, 4583–4603, https://doi.org/10.5194/amt-11-4583-2018, https://doi.org/10.5194/amt-11-4583-2018, 2018
Short summary
Short summary
Nine Pandora Spectrometer Instruments were installed at 8 sites for KORUS-AQ (Korea U.S.-Air Quality) field study from ground, aircraft, and satellite measurements. The quantities retrieved were total column measurements of ozone, nitrogen dioxide, and formaldehyde. We show the distribution of NO2 and HCHO air pollutants vs location and time of day and comparisons with aircraft and satellite data. For some of the sites, long-term time series are available to asses changes.
Wenfu Tang, Avelino F. Arellano, Joshua P. DiGangi, Yonghoon Choi, Glenn S. Diskin, Anna Agustí-Panareda, Mark Parrington, Sebastien Massart, Benjamin Gaubert, Youngjae Lee, Danbi Kim, Jinsang Jung, Jinkyu Hong, Je-Woo Hong, Yugo Kanaya, Mindo Lee, Ryan M. Stauffer, Anne M. Thompson, James H. Flynn, and Jung-Hun Woo
Atmos. Chem. Phys., 18, 11007–11030, https://doi.org/10.5194/acp-18-11007-2018, https://doi.org/10.5194/acp-18-11007-2018, 2018
Si-Wan Kim, Vijay Natraj, Seoyoung Lee, Hyeong-Ahn Kwon, Rokjin Park, Joost de Gouw, Gregory Frost, Jhoon Kim, Jochen Stutz, Michael Trainer, Catalina Tsai, and Carsten Warneke
Atmos. Chem. Phys., 18, 7639–7655, https://doi.org/10.5194/acp-18-7639-2018, https://doi.org/10.5194/acp-18-7639-2018, 2018
Short summary
Short summary
Formaldehyde (HCHO) is a hazardous air pollutant and is associated with tropospheric ozone production. HCHO has been monitored from space. In this study, to acquire high-quality satellite-based HCHO observations, we utilize fine-resolution atmospheric chemistry model results as an input to the computer code for satellite retrievals over the Los Angeles Basin. Our study indicates that the use of fine-resolution profile shapes helps to identify HCHO plumes from space.
Jungbin Mok, Nickolay A. Krotkov, Omar Torres, Hiren Jethva, Zhanqing Li, Jhoon Kim, Ja-Ho Koo, Sujung Go, Hitoshi Irie, Gordon Labow, Thomas F. Eck, Brent N. Holben, Jay Herman, Robert P. Loughman, Elena Spinei, Seoung Soo Lee, Pradeep Khatri, and Monica Campanelli
Atmos. Meas. Tech., 11, 2295–2311, https://doi.org/10.5194/amt-11-2295-2018, https://doi.org/10.5194/amt-11-2295-2018, 2018
Short summary
Short summary
Measuring aerosol absorption from the shortest ultraviolet (UV) to the near-infrared (NIR) wavelengths is important for studies of climate, tropospheric photochemistry, human health, and agricultural productivity. We estimate the accuracy and demonstrate consistency of aerosol absorption retrievals from different instruments, after accounting for spectrally varying surface albedo and gaseous absorption.
Meng Gao, Zhiwei Han, Zirui Liu, Meng Li, Jinyuan Xin, Zhining Tao, Jiawei Li, Jeong-Eon Kang, Kan Huang, Xinyi Dong, Bingliang Zhuang, Shu Li, Baozhu Ge, Qizhong Wu, Yafang Cheng, Yuesi Wang, Hyo-Jung Lee, Cheol-Hee Kim, Joshua S. Fu, Tijian Wang, Mian Chin, Jung-Hun Woo, Qiang Zhang, Zifa Wang, and Gregory R. Carmichael
Atmos. Chem. Phys., 18, 4859–4884, https://doi.org/10.5194/acp-18-4859-2018, https://doi.org/10.5194/acp-18-4859-2018, 2018
Short summary
Short summary
Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative and microphysical feedbacks. A comprehensive overview of the MICS-ASIA III Topic 3 study design is presented.
Brent N. Holben, Jhoon Kim, Itaru Sano, Sonoyo Mukai, Thomas F. Eck, David M. Giles, Joel S. Schafer, Aliaksandr Sinyuk, Ilya Slutsker, Alexander Smirnov, Mikhail Sorokin, Bruce E. Anderson, Huizheng Che, Myungje Choi, James H. Crawford, Richard A. Ferrare, Michael J. Garay, Ukkyo Jeong, Mijin Kim, Woogyung Kim, Nichola Knox, Zhengqiang Li, Hwee S. Lim, Yang Liu, Hal Maring, Makiko Nakata, Kenneth E. Pickering, Stuart Piketh, Jens Redemann, Jeffrey S. Reid, Santo Salinas, Sora Seo, Fuyi Tan, Sachchida N. Tripathi, Owen B. Toon, and Qingyang Xiao
Atmos. Chem. Phys., 18, 655–671, https://doi.org/10.5194/acp-18-655-2018, https://doi.org/10.5194/acp-18-655-2018, 2018
Short summary
Short summary
Aerosol particles, such as smoke, vary over space and time. This paper describes a series of very high-resolution ground-based aerosol measurement networks and associated studies that contributed new understanding of aerosol processes and detailed comparisons to satellite aerosol validation. Significantly, these networks also provide an opportunity to statistically relate grab samples of an aerosol parameter to companion satellite observations, a step toward air quality assessment from space.
Myungje Choi, Jhoon Kim, Jaehwa Lee, Mijin Kim, Young-Je Park, Brent Holben, Thomas F. Eck, Zhengqiang Li, and Chul H. Song
Atmos. Meas. Tech., 11, 385–408, https://doi.org/10.5194/amt-11-385-2018, https://doi.org/10.5194/amt-11-385-2018, 2018
Short summary
Short summary
This study is a major version upgrade of the aerosol product from GOCI, the first and unique ocean color imager in geostationary earth orbit. It describes the improvement of version 2 of the GOCI Yonsei aerosol retrieval algorithm for near-real-time processing with improved accuracy from the modification of cloud masking, surface reflectance, etc. The product is validated against AERONET/SONET over East Asia with analyses of various errors features, and a pixel-level uncertainty is calculated.
Jiyoung Kim, Jhoon Kim, Hi-Ku Cho, Jay Herman, Sang Seo Park, Hyun Kwang Lim, Jae-Hwan Kim, Koji Miyagawa, and Yun Gon Lee
Atmos. Meas. Tech., 10, 3661–3676, https://doi.org/10.5194/amt-10-3661-2017, https://doi.org/10.5194/amt-10-3661-2017, 2017
Short summary
Short summary
Total column ozone (TCO) has been obtained by various ground-based and spaceborne instruments (OMI) with high accuracy. Here, daily TCO measured by a Pandora spectrophotometer (no. 19) installed since the (DRAGON)-NE Asia campaign (2012) was intercompared using Dobson (no. 124), Brewer (no. 148), and OMI measurements from March 2012 to March 2014 at Yonsei University, Seoul, Korea. The results showed that Pandora TCO is in very good agreement with other measurements.
Meng Li, Qiang Zhang, Jun-ichi Kurokawa, Jung-Hun Woo, Kebin He, Zifeng Lu, Toshimasa Ohara, Yu Song, David G. Streets, Gregory R. Carmichael, Yafang Cheng, Chaopeng Hong, Hong Huo, Xujia Jiang, Sicong Kang, Fei Liu, Hang Su, and Bo Zheng
Atmos. Chem. Phys., 17, 935–963, https://doi.org/10.5194/acp-17-935-2017, https://doi.org/10.5194/acp-17-935-2017, 2017
Short summary
Short summary
An anthropogenic emission inventory for Asia is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) projects by a mosaic of up-to-date regional emission inventories. The total Asian emissions in 2010 are estimated as follows: 51.3 Tg SO2, 52.1 Tg NOx, 336.5 Tg CO, 67.0 Tg NMVOC, 28.7 Tg NH3, 31.7 Tg PM10, 22.7 Tg PM2.5, 3.5 Tg BC, 8.3 Tg OC, and 17.3 Pg CO2.
Wonbae Jeon, Yunsoo Choi, Peter Percell, Amir Hossein Souri, Chang-Keun Song, Soon-Tae Kim, and Jhoon Kim
Geosci. Model Dev., 9, 3671–3684, https://doi.org/10.5194/gmd-9-3671-2016, https://doi.org/10.5194/gmd-9-3671-2016, 2016
Short summary
Short summary
This study suggests a new hybrid Lagrangian–Eulerian modeling tool (the Screening Trajectory Ozone Prediction System, STOPS) for an accurate/fast prediction of Asian dust events. The STOPS is a moving nest (Lagrangian approach) between the source and the receptor inside Eulerian model. We run STOPS, instead of running a time-consuming Eulerian model, using constrained PM concentration from remote sensing aerosol optical depth, reflecting real-time dust particles. STOPS is for unexpected events.
Myungje Choi, Jhoon Kim, Jaehwa Lee, Mijin Kim, Young-Je Park, Ukkyo Jeong, Woogyung Kim, Hyunkee Hong, Brent Holben, Thomas F. Eck, Chul H. Song, Jae-Hyun Lim, and Chang-Keun Song
Atmos. Meas. Tech., 9, 1377–1398, https://doi.org/10.5194/amt-9-1377-2016, https://doi.org/10.5194/amt-9-1377-2016, 2016
Short summary
Short summary
The Geostationary Ocean Color Imager (GOCI) is the first ocean color sensor in geostationary orbit. It enables hourly aerosol optical properties to be observed in high spatial resolution. This study presents improvements of the GOCI Yonsei Aerosol Retrieval (YAER) algorithm and its validation results using ground-based and other satellite-based observation products during DRAGON-NE Asia 2012 Campaign. Retrieval errors are also analyzed according to various factors through the validation studies.
Sang Seo Park, Jhoon Kim, Hanlim Lee, Omar Torres, Kwang-Mog Lee, and Sang Deok Lee
Atmos. Chem. Phys., 16, 1987–2006, https://doi.org/10.5194/acp-16-1987-2016, https://doi.org/10.5194/acp-16-1987-2016, 2016
Short summary
Short summary
The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using simulated radiances by a linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT) model, and the differential optical absorption spectroscopy (DOAS) technique. A new algorithm is developed and tested to derive the aerosol effective height for cases over East Asia using radiance data from the Ozone Monitoring Instrument (OMI).
M. Kim, J. Kim, U. Jeong, W. Kim, H. Hong, B. Holben, T. F. Eck, J. H. Lim, C. K. Song, S. Lee, and C.-Y. Chung
Atmos. Chem. Phys., 16, 1789–1808, https://doi.org/10.5194/acp-16-1789-2016, https://doi.org/10.5194/acp-16-1789-2016, 2016
Short summary
Short summary
An aerosol model optimized for East Asia is improved by applying inversion data from the DRAGON-NE Asia 2012 campaign, and is applied to an AOD retrieval algorithm using single visible measurements from a GEO satellite. In sensitivity tests, a 4 % overestimation in SSA can cause an underestimation in AOD of over 20 %. In accordance with the test, the overestimating tendency of AOD was improved by 8 % after the modification of the aerosol model.
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.
U. Jeong, J. Kim, C. Ahn, O. Torres, X. Liu, P. K. Bhartia, R. J. D. Spurr, D. Haffner, K. Chance, and B. N. Holben
Atmos. Chem. Phys., 16, 177–193, https://doi.org/10.5194/acp-16-177-2016, https://doi.org/10.5194/acp-16-177-2016, 2016
Short summary
Short summary
An aerosol retrieval and error analysis algorithm using OMI measurements based on an optimal-estimation method was developed in this study. The aerosol retrievals were validated using the DRAGON campaign products. The estimated errors of the retrievals represented the actual biases between retrieval and AERONET measurements well. The retrievals, with their estimated uncertainties, are expected to be valuable for relevant studies, such as trace gas retrieval and data assimilation.
J.-W. Xu, R. V. Martin, A. van Donkelaar, J. Kim, M. Choi, Q. Zhang, G. Geng, Y. Liu, Z. Ma, L. Huang, Y. Wang, H. Chen, H. Che, P. Lin, and N. Lin
Atmos. Chem. Phys., 15, 13133–13144, https://doi.org/10.5194/acp-15-13133-2015, https://doi.org/10.5194/acp-15-13133-2015, 2015
Short summary
Short summary
1. GOCI (Geostationary Ocean Color Imager) retrieval of AOD is consistent with AERONET AOD (RMSE=0.08-0.1)
2. GOCI-derived PM2.5 is in significant agreement with in situ observations (r2=0.66, rRMSE=18.3%)
3. Population-weighted GOCI-derived PM2.5 over eastern China for 2013 is 53.8 μg/m3, threatening the health of its more than 400 million residents
4. Secondary inorganics (SO42-, NO3-, NH4+) & organic matter are the most significant components of GOCI-derived PM2.5.
K. M. Han, S. Lee, L. S. Chang, and C. H. Song
Atmos. Chem. Phys., 15, 1913–1938, https://doi.org/10.5194/acp-15-1913-2015, https://doi.org/10.5194/acp-15-1913-2015, 2015
S. Seo, J. Kim, H. Lee, U. Jeong, W. Kim, B. N. Holben, S.-W. Kim, C. H. Song, and J. H. Lim
Atmos. Chem. Phys., 15, 319–334, https://doi.org/10.5194/acp-15-319-2015, https://doi.org/10.5194/acp-15-319-2015, 2015
Short summary
Short summary
The estimation of PM10 from optical measurement of AERONET and MODIS by various empirical models was evaluated for the DRAGON-Asia campaign. The results showed the importance of boundary layer height (BLH) and effective radius (Reff) in estimating PM10. The highest correlation between the estimated and measured values was found to be 0.81 in winter due to the stagnant air mass and low BLH, while the poorest values were 0.54 in spring due to the influence of long-range transport above BLH.
R. J. Park, S. K. Hong, H.-A. Kwon, S. Kim, A. Guenther, J.-H. Woo, and C. P. Loughner
Atmos. Chem. Phys., 14, 7929–7940, https://doi.org/10.5194/acp-14-7929-2014, https://doi.org/10.5194/acp-14-7929-2014, 2014
H.-K. Kim, J.-H. Woo, R. S. Park, C. H. Song, J.-H. Kim, S.-J. Ban, and J.-H. Park
Atmos. Chem. Phys., 14, 7461–7484, https://doi.org/10.5194/acp-14-7461-2014, https://doi.org/10.5194/acp-14-7461-2014, 2014
S. X. Wang, B. Zhao, S. Y. Cai, Z. Klimont, C. P. Nielsen, T. Morikawa, J. H. Woo, Y. Kim, X. Fu, J. Y. Xu, J. M. Hao, and K. B. He
Atmos. Chem. Phys., 14, 6571–6603, https://doi.org/10.5194/acp-14-6571-2014, https://doi.org/10.5194/acp-14-6571-2014, 2014
R. S. Park, S. Lee, S.-K. Shin, and C. H. Song
Atmos. Chem. Phys., 14, 2185–2201, https://doi.org/10.5194/acp-14-2185-2014, https://doi.org/10.5194/acp-14-2185-2014, 2014
M. E. Park, C. H. Song, R. S. Park, J. Lee, J. Kim, S. Lee, J.-H. Woo, G. R. Carmichael, T. F. Eck, B. N. Holben, S.-S. Lee, C. K. Song, and Y. D. Hong
Atmos. Chem. Phys., 14, 659–674, https://doi.org/10.5194/acp-14-659-2014, https://doi.org/10.5194/acp-14-659-2014, 2014
Y. Choi, Y. S. Ghim, and B. N. Holben
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-26627-2013, https://doi.org/10.5194/acpd-13-26627-2013, 2013
Revised manuscript not accepted
J. Bak, J. H. Kim, X. Liu, K. Chance, and J. Kim
Atmos. Meas. Tech., 6, 239–249, https://doi.org/10.5194/amt-6-239-2013, https://doi.org/10.5194/amt-6-239-2013, 2013
Related subject area
Atmospheric sciences
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Impact of Multiple Radar Wind Profilers Data Assimilation on Convective Scale Short-Term Rainfall Forecasts: OSSE Studies over the Beijing-Tianjin-Hebei region
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
Short summary
Short summary
This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
Short summary
Short summary
The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
Short summary
Short summary
To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Short summary
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Short summary
Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Short summary
The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
Short summary
Short summary
Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
Short summary
This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary
Short summary
It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Short summary
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
Short summary
Short summary
Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
Short summary
Short summary
As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
Short summary
Short summary
Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Short summary
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary
Short summary
The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
Short summary
Short summary
We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
Short summary
We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
Short summary
A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
Short summary
Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Short summary
Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary
Short summary
Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
Short summary
In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-194, https://doi.org/10.5194/gmd-2024-194, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing-Tianjin-Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
Short summary
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Cited articles
Al-Saadi, J., Szykman, J., Pierce, R. B., Kittaka, C., Neil, D., Chu, D. A.,
Remer, L., Gumley, L., Prins, E., Weinstock, L., MacDonald, C., Wayland, R.,
Dimmick, F., and Fishman, J.: Improving National Air Quality Forecasts with
Satellite Aerosol Observations, B. Am. Meteorol. Soc., 86, 1249–1261,
https://doi.org/10.1175/BAMS-86-9-1249, 2005.
Archibald, A. T., Cooke, M. C., Utembe, S. R., Shallcross, D. E., Derwent, R.
G., and Jenkin, M. E.: Impacts of mechanistic changes on HOx
Bassett, M. and Seinfeld, J. H.: Atmospheric equilibrium model of sulfate
and nitrate aerosols, Atmos. Environ., 17, 2237–2252,
https://doi.org/10.1016/0004-6981(83)90221-4, 1983.
Benedetti, A., Morcrette, J.-J., Boucher, O., Dethof, A., Engelen, R. J.,
Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S.,
Mangold, A., Razinger, M., Simmons, A. J., and Suttie, M.: Aerosol analysis
and forecast in the European Centre for Medium-Range Weather Forecasts
Integrated Forecast System: 2. Data assimilation, J. Geophys. Res.-Atmos.,
114, D13205, https://doi.org/10.1029/2008JD011115, 2009.
Brook, R. D., Rajagopalan, S., Pope, C. A., Brook, J. R., Bhatnagar, A.,
Diez-Roux, A. V., Holguin, F., Hong, Y., Luepker, R. V., Mittleman, M. A.,
Peters, A., Siscovick, D., Smith, S. C., Whitsel, L., and Kaufman, J. D.:
Particulate Matter Air Pollution and Cardiovascular Disease An Update to the
Scientific Statement From the American Heart Association, Circulation, 121,
2331–2378, https://doi.org/10.1161/CIR.0b013e3181dbece1, 2010.
Brunekreef, B. and Holgate, S. T.: Air pollution and health, The Lancet,
360, 1233–1242, https://doi.org/10.1016/S0140-6736(02)11274-8, 2002.
Byun, D. W. and Ching, J. K. S.: Science algorithms of the EPA Models-3
community multiscale air quality (CMAQ) modeling system, US Environmental Protection Agency Report, EPA-600/R-99/030, 727 p.,
1999.
Byun, D. W. and Schere, K. L.: Review of the governing equations, computational
algorithms, and other components of the models-3 Community Multiscale Air
Quality (CMAQ) modeling system, Appl. Mech. Rev., 59, 51–76,
https://doi.org/10.1115/1.2128636, 2006.
Carlton, A. G., Turpin, B. J., Altieri, K. E., Seitzinger, S. P., Mathur,
R., Roselle, S. J., and Weber, R. J.: CMAQ Model Performance Enhanced When
In-Cloud Secondary Organic Aerosol is Included: Comparisons of Organic Carbon
Predictions with Measurements, Environ. Sci. Technol., 42, 8798–8802,
https://doi.org/10.1021/es801192n, 2008.
Carlton, A. G., Bhave, P. V., Napelenok, S. L., Edney, E. O., Sarwar, G.,
Pinder, R. W., Pouliot, G. A., and Houyoux, M.: Model Representation of
Secondary Organic Aerosol in CMAQv4.7, Environ. Sci. Technol., 44,
8553–8560, https://doi.org/10.1021/es100636q, 2010.
Chai, T. and Draxler, R. R.: Root mean square error (RMSE) or mean absolute
error (MAE)? – Arguments against avoiding RMSE in the literature, Geosci.
Model Dev., 7, 1247–1250, https://doi.org/10.5194/gmd-7-1247-2014, 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. Atmospheric Sci., 59, 461–483,
https://doi.org/10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2,
2002.
Choi, M., Kim, J., Lee, J., Kim, M., Je Park, Y., Jeong, U., Kim, W., Holben,
B., Eck, T. F., Lim, J. H., and Song, C. K.: GOCI Yonsei Aerosol Retrieval
(YAER) algorithm and validation during DRAGON-NE Asia 2012 campaign, Atmos.
Meas. Tech. Discuss., 8, 9565–9609, https://doi.org/10.5194/amtd-8-9565-2015, 2015.
Cressie, N.: Statistics for Spatial Data, Terra Nova, 4, 613–617,
https://doi.org/10.1111/j.1365-3121.1992.tb00605.x, 1992.
Denby, B., Schaap, M., Segers, A., Builtjes, P., and Horálek, J.:
Comparison of two data assimilation methods for assessing PM10
exceedances on the European scale, Atmos. Environ., 42, 7122–7134,
https://doi.org/10.1016/j.atmosenv.2008.05.058, 2008.
Donahue, N. M., Robinson, A. L., Stanier, C. O., and Pandis, S. N.: Coupled
Partitioning, Dilution, and Chemical Aging of Semivolatile Organics, Environ.
Sci. Technol., 40, 2635–2643, https://doi.org/10.1021/es052297c, 2006.
Donahue, N. M., Epstein, S. A., Pandis, S. N., and Robinson, A. L.: A
two-dimensional volatility basis set: 1. organic-aerosol mixing
thermodynamics, Atmos. Chem. Phys., 11, 3303–3318,
https://doi.org/10.5194/acp-11-3303-2011, 2011.
Dzepina, K., Volkamer, R. M., Madronich, S., Tulet, P., Ulbrich, I. M.,
Zhang, Q., Cappa, C. D., Ziemann, P. J., and Jimenez, J. L.: Evaluation of
recently-proposed secondary organic aerosol models for a case study in Mexico
City, Atmos. Chem. Phys., 9, 5681–5709, https://doi.org/10.5194/acp-9-5681-2009, 2009.
Fishman, J., Iraci, L. T., Al-Saadi, J., Chance, K., Chavez, F., Chin, M.,
Coble, P., Davis, C., DiGiacomo, P. M., Edwards, D., Eldering, A., Goes, J.,
Herman, J., Hu, C., Jacob, D. J., Jordan, C., Kawa, S. R., Key, R., Liu, X.,
Lohrenz, S., Mannino, A., Natraj, V., Neil, D., Neu, J., Newchurch, M.,
Pickering, K., Salisbury, J., Sosik, H., Subramaniam, A., Tzortziou, M.,
Wang, J., and Wang, M.: The United States' Next Generation of Atmospheric
Composition and Coastal Ecosystem Measurements: NASA's Geostationary Coastal
and Air Pollution Events (GEO-CAPE) Mission, B. Am. Meteorol. Soc., 93,
1547–1566, https://doi.org/10.1175/BAMS-D-11-00201.1, 2012.
Friedl, M. A., McIver, D. K., Hodges, J. C. F., Zhang, X. Y., Muchoney, D.,
Strahler, A. H., Woodcock, C. E., Gopal, S., Schneider, A., Cooper, A.,
Baccini, A., Gao, F., and Schaaf, C.: Global land cover mapping from MODIS:
algorithms and early results, Remote Sens. Environ., 83, 287–302,
https://doi.org/10.1016/S0034-4257(02)00078-0, 2002.
Gräler, B., Gerharz, L., and Pebesma, E.: Spatio-temporal analysis and
interpolation of PM10 measurements in Europe, available at:
https://doi.org/http://acm.eionet.europa.eu/reports/ETCACM_TP_2011_10_spatio-temp_AQinterpolation (last access: 26 December 2015),
2012.
Guenther, A., Baugh, B., Brasseur, G., Greenberg, J., Harley, P., Klinger,
L., Serça, D., and Vierling, L.: Isoprene emission estimates and
uncertainties for the central African EXPRESSO study domain, J. Geophys.
Res.-Atmos., 104, 30625–30639, https://doi.org/10.1029/1999JD900391, 1999.
Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron,
C.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of
Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6,
3181–3210, https://doi.org/10.5194/acp-6-3181-2006, 2006.
Han, K. M., Park, R. S., Kim, H. K., Woo, J. H., Kim, J., and Song, C. H.:
Uncertainty in biogenic isoprene emissions and its impacts on tropospheric
chemistry in East Asia, Sci. Total Environ., 463–464, 754–771,
https://doi.org/10.1016/j.scitotenv.2013.06.003, 2013.
Han, K. M., Lee, S., Chang, L. S., and Song, C. H.: A comparison study
between CMAQ-simulated and OMI-retrieved NO2 columns over East Asia for
evaluation of NOx
He, L.-Y., Huang, X.-F., Xue, L., Hu, M., Lin, Y., Zheng, J., Zhang, R., and
Zhang, Y.-H.: Submicron aerosol analysis and organic source apportionment in
an urban atmosphere in Pearl River Delta of China using high-resolution
aerosol mass spectrometry, J. Geophys. Res., 116, D12304,
https://doi.org/10.1029/2010JD014566, 2011.
Hodzic, A., Jimenez, J. L., Madronich, S., Canagaratna, M. R., DeCarlo, P.
F., Kleinman, L., and Fast, J.: Modeling organic aerosols in a megacity:
potential contribution of semi-volatile and intermediate volatility primary
organic compounds to secondary organic aerosol formation, Atmos. Chem. Phys.,
10, 5491–5514, https://doi.org/10.5194/acp-10-5491-2010, 2010.
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer,
A., Vermote, E., 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,
https://doi.org/10.1016/S0034-4257(98)00031-5, 1998.
Huang, X.-F., He, L.-Y., Hu, M., Canagaratna, M. R., Sun, Y., Zhang, Q., Zhu,
T., Xue, L., Zeng, L.-W., Liu, X.-G., Zhang, Y.-H., Jayne, J. T., Ng, N. L.,
and Worsnop, D. R.: Highly time-resolved chemical characterization of
atmospheric submicron particles during 2008 Beijing Olympic Games using an
Aerodyne High-Resolution Aerosol Mass Spectrometer, Atmos. Chem. Phys., 10,
8933–8945, https://doi.org/10.5194/acp-10-8933-2010, 2010.
Karamchandani, P., Santos, L., Sykes, I., Zhang, Y., Tonne, C., and Seigneur,
C.: Development and Evaluation of a State-of-the-Science Reactive Plume
Model, Environ. Sci. Technol., 34, 870–880, https://doi.org/10.1021/es990611v, 2000.
Kim, H. S., Song, C. H., Park, R. S., Huey, G., and Ryu, J. Y.: Investigation
of ship-plume chemistry using a newly-developed photochemical/dynamic
ship-plume model, Atmos. Chem. Phys., 9, 7531–7550,
https://doi.org/10.5194/acp-9-7531-2009, 2009.
Kim, H. S., Kim, Y. H., and Song, C. H.: Ship-plume sulfur chemistry: ITCT
2K2 case study, Sci. Total Environ., 450–451, 178–187,
https://doi.org/10.1016/j.scitotenv.2013.01.099, 2013.
Kubistin, D., Harder, H., Martinez, M., Rudolf, M., Sander, R., Bozem, H.,
Eerdekens, G., Fischer, H., Gurk, C., Klüpfel, T., Königstedt, R.,
Parchatka, U., Schiller, C. L., Stickler, A., Taraborrelli, D., Williams, J.,
and Lelieveld, J.: Hydroxyl radicals in the tropical troposphere over the
Suriname rainforest: comparison of measurements with the box model MECCA,
Atmos. Chem. Phys., 10, 9705–9728, https://doi.org/10.5194/acp-10-9705-2010, 2010.
Lahoz, W. A., Peuch, V.-H., Orphal, J., Attié, J.-L., Chance, K., Liu,
X., Edwards, D., Elbern, H., Flaud, J.-M., Claeyman, M., and Amraoui, L. E.:
Monitoring Air Quality from Space: The Case for the Geostationary Platform,
B. Am. Meteorol. Soc., 93, 221–233, https://doi.org/10.1175/BAMS-D-11-00045.1, 2011.
Lee, J., Kim, J., Song, C. H., Ryu, J.-H., Ahn, Y.-H., and Song, C. K.:
Algorithm for retrieval of aerosol optical properties over the ocean from the
Geostationary Ocean Color Imager, Remote Sens. Environ., 114, 1077–1088,
https://doi.org/10.1016/j.rse.2009.12.021, 2010.
Lee, J., Kim, J., Yang, P., and Hsu, N. C.: Improvement of aerosol optical
depth retrieval from MODIS spectral reflectance over the global ocean using
new aerosol models archived from AERONET inversion data and tri-axial
ellipsoidal dust database, Atmos. Chem. Phys., 12, 7087–7102,
https://doi.org/10.5194/acp-12-7087-2012, 2012.
Lee, S., Ghim, Y. S., Kim, S.-W., and Yoon, S.-C.: Seasonal characteristics
of chemically apportioned aerosol optical properties at Seoul and Gosan,
Korea, Atmos. Environ., 43, 1320–1328, https://doi.org/10.1016/j.atmosenv.2008.11.044,
2009.
Lee, Y. H., Choi, Y., and Ghim, Y. S.: Classification of diurnal patterns of
particulate inorganic ions downwind of metropolitan Seoul, submitted,
2015.
Lelieveld, J., Butler, T. M., Crowley, J. N., Dillon, T. J., Fischer, H.,
Ganzeveld, L., Harder, H., Lawrence, M. G., Martinez, M., Taraborrelli, D.,
and Williams, J.: Atmospheric oxidation capacity sustained by a tropical
forest, Nature, 452(7188), 737–740, https://doi.org/10.1038/nature06870, 2008.
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: NEW MODIS RETRIEVAL OF AEROSOL OVER LAND, J. Geophys.
Res.-Atmos., 112, D13211, https://doi.org/10.1029/2006JD007811, 2007.
Liu, Z., Liu, Q., Lin, H.-C., Schwartz, C. S., Lee, Y.-H., and Wang, T.:
Three-dimensional variational assimilation of MODIS aerosol optical depth:
Implementation and application to a dust storm over East Asia, J. Geophys.
Res.-Atmos., 116, D23206, https://doi.org/10.1029/2011JD016159, 2011.
Lu, Z., Streets, D. G., Zhang, Q., Wang, S., Carmichael, G. R., Cheng, Y. F.,
Wei, C., Chin, M., Diehl, T., and Tan, Q.: Sulfur dioxide emissions in China
and sulfur trends in East Asia since 2000, Atmos. Chem. Phys., 10,
6311–6331, https://doi.org/10.5194/acp-10-6311-2010, 2010.
Malm, W. C. and Hand, J. L.: An examination of the physical and optical
properties of aerosols collected in the IMPROVE program, Atmos. Environ., 41,
3407–3427, https://doi.org/10.1016/j.atmosenv.2006.12.012, 2007.
Martin, R. V., Jacob, D. J., Yantosca, R. M., Chin, M., and Ginoux, P.:
Global and regional decreases in tropospheric oxidants from photochemical
effects of aerosols, J. Geophys. Res.-Atmos., 108, 4097,
https://doi.org/10.1029/2002JD002622, 2003.
Matsui, H., Koike, M., Kondo, Y., Takami, A., Fast, J. D., Kanaya, Y., and
Takigawa, M.: Volatility basis-set approach simulation of organic aerosol
formation in East Asia: implications for anthropogenic–biogenic interaction
and controllable amounts, Atmos. Chem. Phys., 14, 9513–9535,
https://doi.org/10.5194/acp-14-9513-2014, 2014.
Munchak, L. A., Levy, R. C., Mattoo, S., Remer, L. A., Holben, B. N.,
Schafer, J. S., Hostetler, C. A., and Ferrare, R. A.: MODIS 3 km aerosol
product: applications over land in an urban/suburban region, Atmos. Meas.
Tech., 6, 1747–1759, https://doi.org/10.5194/amt-6-1747-2013, 2013.
Myneni, R. B., Hoffman, S., Knyazikhin, Y., Privette, J. L., Glassy, J.,
Tian, Y., Wang, Y., Song, X., Zhang, Y., Smith, G. R., Lotsch, A., Friedl,
M., Morisette, J. T., Votava, P., Nemani, R. R., and Running, S. W.: Global
products of vegetation leaf area and fraction absorbed PAR from year one of
MODIS data, Remote Sens. Environ., 83, 214–231,
https://doi.org/10.1016/S0034-4257(02)00074-3, 2002.
NCL: The NCAR Command Language (Version 6.2.1) [Software], Boulder Colo.
UCARNCARCISLVETS, https://doi.org/10.5065/D6WD3XH5, 2014.
Otte, T. L. and Pleim, J. E.: The Meteorology-Chemistry Interface Processor
(MCIP) for the CMAQ modeling system: updates through MCIPv3.4.1, Geosci.
Model Dev., 3, 243–256, https://doi.org/10.5194/gmd-3-243-2010, 2010.
Park, M. E., Song, C. H., Park, R. S., Lee, J., Kim, J., Lee, S., Woo, J.-H.,
Carmichael, G. R., Eck, T. F., Holben, B. N., Lee, S.-S., Song, C. K., and
Hong, Y. D.: New approach to monitor transboundary particulate pollution over
Northeast Asia, Atmos. Chem. Phys., 14, 659–674,
https://doi.org/10.5194/acp-14-659-2014, 2014.
Park, R. S., Song, C. H., Han, K. M., Park, M. E., Lee, S.-S., Kim, S.-B.,
and Shimizu, A.: A study on the aerosol optical properties over East Asia
using a combination of CMAQ-simulated aerosol optical properties and
remote-sensing data via a data assimilation technique, Atmos. Chem. Phys.,
11, 12275–12296, https://doi.org/10.5194/acp-11-12275-2011, 2011.
Park, R. S., Lee, S., Shin, S.-K., and Song, C. H.: Contribution of ammonium
nitrate to aerosol optical depth and direct radiative forcing by aerosols
over East Asia, Atmos. Chem. Phys., 14, 2185–2201,
https://doi.org/10.5194/acp-14-2185-2014, 2014.
Pebesma, E. J.: Multivariable geostatistics in S: the gstat package, Comput.
Geosci., 30, 683–691, https://doi.org/10.1016/j.cageo.2004.03.012, 2004.
Pebesma, E. J.: spacetime: Spatio-Temporal Data in R, J. Stat. Softw.,
51, https://doi.org/10.18637/jss.v051.i07, 2012.
Pope, C. A. and Dockery, D. W.: Health Effects of Fine Particulate Air
Pollution: Lines that Connect, J. Air Waste Manage., 56, 709–742, https://doi.org/10.1080/10473289.2006.10464485, 2006.
R Development Core Team: R: A Language and Environment for Statistical
Computing, R Foundation for Statistical Computing, Vienna, Austria, available
at: https://doi.org/http://www.R-project.org/ (last access: 26 December 2015), 2011.
Reff, A., Bhave, P. V., Simon, H., Pace, T. G., Pouliot, G. A., Mobley, J.
D., and Houyoux, M.: Emissions Inventory of PM2.5 Trace Elements across
the United States, Environ. Sci. Technol., 43, 5790–5796,
https://doi.org/10.1021/es802930x, 2009.
Remer, L. A., Kaufman, Y. J., Tanré, D., Mattoo, S., Chu, D. A.,
Martins, J. V., Li, R.-R., Ichoku, C., Levy, R. C., Kleidman, R. G., Eck, T.
F., Vermote, E., and Holben, B. N.: The MODIS Aerosol Algorithm, Products,
and Validation, J. Atmos. Sci., 62, 947–973, https://doi.org/10.1175/JAS3385.1, 2005.
Saide, P. E., Carmichael, G. R., Liu, Z., Schwartz, C. S., Lin, H. C., da
Silva, A. M., and Hyer, E.: Aerosol optical depth assimilation for a
size-resolved sectional model: impacts of observationally constrained,
multi-wavelength and fine mode retrievals on regional scale analyses and
forecasts, Atmos. Chem. Phys., 13, 10425–10444,
https://doi.org/10.5194/acp-13-10425-2013, 2013.
Sakulyanontvittaya, T., Duhl, T., Wiedinmyer, C., Helmig, D., Matsunaga, S.,
Potosnak, M., Milford, J., and Guenther, A.: Monoterpene and Sesquiterpene
Emission Estimates for the United States, Environ. Sci. Technol., 42,
1623–1629, https://doi.org/10.1021/es702274e, 2008.
Savage, N. H., Agnew, P., Davis, L. S., Ordóñez, C., Thorpe, R.,
Johnson, C. E., O'Connor, F. M., and Dalvi, M.: Air quality modelling using
the Met Office Unified Model (AQUM OS24-26): model description and initial
evaluation, Geosci. Model Dev., 6, 353–372, https://doi.org/10.5194/gmd-6-353-2013,
2013.
Saxena, P., Belle Hudischewskyj, A., Seigneur, C., and Seinfeld, J. H.: A
comparative study of equilibrium approaches to the chemical characterization
of secondary aerosols, Atmos. Environ., 20, 1471–1483,
https://doi.org/10.1016/0004-6981(86)90019-3, 1986.
Schwartz, C. S., Liu, Z., Lin, H.-C., and McKeen, S. A.: Simultaneous
three-dimensional variational assimilation of surface fine particulate matter
and MODIS aerosol optical depth, J. Geophys. Res.-Atmos., 117, D13202,
https://doi.org/10.1029/2011JD017383, 2012.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric chemistry and physics: from
air pollution to climate change, John Wiley & Sons, 2012.
Shi, Y., Zhang, J., Reid, J. S., Holben, B., Hyer, E. J., and Curtis, C.: An
analysis of the collection 5 MODIS over-ocean aerosol optical depth product
for its implication in aerosol assimilation, Atmos. Chem. Phys., 11,
557–565, https://doi.org/10.5194/acp-11-557-2011, 2011.
Skamarock, W. C. and Klemp, J. B.: A time-split nonhydrostatic atmospheric
model for weather research and forecasting applications, J. Comput. Phys.,
227, 3465–3485, https://doi.org/10.1016/j.jcp.2007.01.037, 2008.
Slowik, J. G., Stroud, C., Bottenheim, J. W., Brickell, P. C., Chang, R.
Y.-W., Liggio, J., Makar, P. A., Martin, R. V., Moran, M. D., Shantz, N. C.,
Sjostedt, S. J., van Donkelaar, A., Vlasenko, A., Wiebe, H. A., Xia, A. G.,
Zhang, J., Leaitch, W. R., and Abbatt, J. P. D.: Characterization of a large
biogenic secondary organic aerosol event from eastern Canadian forests,
Atmos. Chem. Phys., 10, 2825–2845, https://doi.org/10.5194/acp-10-2825-2010, 2010.
Smith, S. J., van Aardenne, J., Klimont, Z., Andres, R. J., Volke, A., and
Delgado Arias, S.: Anthropogenic sulfur dioxide emissions: 1850–2005, Atmos.
Chem. Phys., 11, 1101–1116, https://doi.org/10.5194/acp-11-1101-2011, 2011.
Song, C. H. and Carmichael, G. R.: The aging process of naturally emitted
aerosol (sea-salt and mineral aerosol) during long range transport, Atmos.
Environ., 33, 2203–2218, https://doi.org/10.1016/S1352-2310(98)00301-X, 1999.
Song, C. H. and Carmichael, G. R.: Gas-Particle Partitioning of Nitric Acid
Modulated by Alkaline Aerosol, J. Atmos. Chem., 40, 1–22, 2001.
Song, C. H., Chen, G., Hanna, S. R., Crawford, J., and Davis, D. D.:
Dispersion and chemical evolution of ship plumes in the marine boundary
layer: Investigation of O3 /NOy x
Song, C. H., Park, M. E., Lee, K. H., Ahn, H. J., Lee, Y., Kim, J. Y., Han,
K. M., Kim, J., Ghim, Y. S., and Kim, Y. J.: An investigation into seasonal
and regional aerosol characteristics in East Asia using model-predicted and
remotely-sensed aerosol properties, Atmos. Chem. Phys., 8, 6627–6654,
https://doi.org/10.5194/acp-8-6627-2008, 2008.
Song, C. H., Kim, H. S., von Glasow, R., Brimblecombe, P., Kim, J., Park, R.
J., Woo, J. H., and Kim, Y. H.: Source identification and budget analysis on
elevated levels of formaldehyde within the ship plumes: a ship-plume
photochemical/dynamic model analysis, Atmos. Chem. Phys., 10, 11969–11985,
https://doi.org/10.5194/acp-10-11969-2010, 2010.
Sörgel, M., Regelin, E., Bozem, H., Diesch, J.-M., Drewnick, F., Fischer,
H., Harder, H., Held, A., Hosaynali-Beygi, Z., Martinez, M., and Zetzsch, C.:
Quantification of the unknown HONO daytime source and its relation to NO2 ,
Atmos. Chem. Phys., 11, 10433–10447, https://doi.org/10.5194/acp-11-10433-2011, 2011.
Stelson, A. W., Bassett, M. E., and Seinfeld, J. H.: Thermodynamic
equilibrium properties of aqueous solutions of nitrate, sulfate and ammonium,
ACID PRECIP SER 1984, 1984.
Stemmler, K., Ammann, M., Donders, C., Kleffmann, J., and George, C.:
Photosensitized reduction of nitrogen dioxide on humic acid as a source of
nitrous acid, Nature, 440, 195–198, https://doi.org/10.1038/nature04603, 2006.
Tang, Y., Chai, T., Pan, L., Lee, P., Tong, D., Kim, H.-C., and Chen, W.:
Using optimal interpolation to assimilate surface measurements and satellite
AOD for ozone and PM2.5 : A case study for July 2011, J. Air Waste
Manage., 65(10), 1206–1216, https://doi.org/10.1080/10962247.2015.1062439, 2015.
Tsimpidi, A. P., Karydis, V. A., Zavala, M., Lei, W., Molina, L., Ulbrich, I.
M., Jimenez, J. L., and Pandis, S. N.: Evaluation of the volatility basis-set
approach for the simulation of organic aerosol formation in the Mexico City
metropolitan area, Atmos. Chem. Phys., 10, 525–546,
https://doi.org/10.5194/acp-10-525-2010, 2010.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J.
A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a
high resolution global model to estimate the emissions from open burning,
Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
Willmott, C. J.: On the Validation of Models, Phys. Geogr., 2, 184–194,
https://doi.org/10.1080/02723646.1981.10642213, 1981.
Willmott, C. J. and Matsuura, K.: Advantages of the mean absolute error (MAE)
over the root mean square error (RMSE) in assessing average model
performance, Clim. Res., 30, 79–82, https://doi.org/10.3354/cr030079, 2005.
Willmott, C. J., Matsuura, K., and Robeson, S. M.: Ambiguities inherent in
sums-of-squares-based error statistics, Atmos. Environ., 43, 749–752,
https://doi.org/10.1016/j.atmosenv.2008.10.005, 2009.
Woo, J.-H., Choi, K.-C., Kim, H. K., Baek, B. H., Jang, M., Eum, J.-H.,
Song, C. H., Ma, Y.-I., Sunwoo, Y., Chang, L.-S., and Yoo, S. H.: Development
of an anthropogenic emissions processing system for Asia using SMOKE, Atmos.
Environ., 58, 5–13, https://doi.org/10.1016/j.atmosenv.2011.10.042, 2012.
Wyat Appel, K., Bhave, P. V., Gilliland, A. B., Sarwar, G., and Roselle, S.
J.: Evaluation of the community multiscale air quality (CMAQ) model version
4.5: Sensitivities impacting model performance; Part II – particulate
matter, Atmos. Environ., 42, 6057–6066, https://doi.org/10.1016/j.atmosenv.2008.03.036,
2008.
Zhang, Q., Jimenez, J. L., Canagaratna, M. R., Allan, J. D., Coe, H.,
Ulbrich, I., Alfarra, M. R., Takami, A., Middlebrook, A. M., Sun, Y. L.,
Dzepina, K., Dunlea, E., Docherty, K., DeCarlo, P. F., Salcedo, D., Onasch,
T., Jayne, J. T., Miyoshi, T., Shimono, A., Hatakeyama, S., Takegawa, N.,
Kondo, Y., Schneider, J., Drewnick, F., Borrmann, S., Weimer, S., Demerjian,
K., Williams, P., Bower, K., Bahreini, R., Cottrell, L., Griffin, R. J.,
Rautiainen, J., Sun, J. Y., Zhang, Y. M., and Worsnop, D. R.: Ubiquity and
dominance of oxygenated species in organic aerosols in
anthropogenically-influenced Northern Hemisphere midlatitudes, Geophys. Res.
Lett., 34, L13801, https://doi.org/10.1029/2007GL029979, 2007.
Zhang, X. Y., Wang, Y. Q., Niu, T., Zhang, X. C., Gong, S. L., Zhang, Y. M.,
and Sun, J. Y.: Atmospheric aerosol compositions in China: spatial/temporal
variability, chemical signature, regional haze distribution and comparisons
with global aerosols, Atmos. Chem. Phys., 12, 779–799,
https://doi.org/10.5194/acp-12-779-2012, 2012.
Zhou, X., Zhang, N., TerAvest, M., Tang, D., Hou, J., Bertman, S.,
Alaghmand, M., Shepson, P. B., Carroll, M. A., Griffith, S., Dusanter, S.,
and Stevens, P. S.: Nitric acid photolysis on forest canopy surface as a
source for tropospheric nitrous acid, Nat. Geosci., 4, 440–443,
https://doi.org/10.1038/ngeo1164, 2011.
Zoogman, P., Jacob, D. J., Chance, K., Liu, X., Lin, M., Fiore, A., and
Travis, K.: Monitoring high-ozone events in the US Intermountain West using
TEMPO geostationary satellite observations, Atmos. Chem. Phys., 14,
6261–6271, https://doi.org/10.5194/acp-14-6261-2014, 2014.
Short summary
We developed an integrated air quality modeling system using AOD data retrieved from a geostationary satellite sensor, GOCI (Geostationary Ocean Color Imager), over Northeast Asia with an application of the spatiotemporal-kriging (STK) method and conducted short-term hindcast runs using the developed system. It appears that the STK approach can greatly reduce not only the errors and biases of AOD and PM10 predictions but also the computational burden of a chemical weather forecast (CWF).
We developed an integrated air quality modeling system using AOD data retrieved from a...
