Articles | Volume 12, issue 11
https://doi.org/10.5194/gmd-12-4603-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-4603-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Multimodel simulations of a springtime dust storm over northeastern China: implications of an evaluation of four commonly used air quality models (CMAQ v5.2.1, CAMx v6.50, CHIMERE v2017r4, and WRF-Chem v3.9.1)
Siqi Ma
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
University of Chinese Academy of Sciences, Beijing 100049, China
Air Resources Laboratory, National Oceanic & Atmospheric Administration, College Park, MD 20740, USA
Xuelei Zhang
CORRESPONDING AUTHOR
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
Center for Spatial Information Science and Systems, George Mason
University, Fairfax, VA 22030, USA
Chao Gao
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
University of Chinese Academy of Sciences, Beijing 100049, China
Center for Spatial Information Science and Systems, George Mason
University, Fairfax, VA 22030, USA
Aijun Xiu
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
Guangjian Wu
Key Laboratory of Tibetan Environment Changes and Land Surface
Processes, Institute of Tibetan Plateau Research, Chinese Academy of
Sciences, Beijing 100101, China
CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing
100101, China
Xinyuan Cao
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
University of Chinese Academy of Sciences, Beijing 100049, China
Ling Huang
School of Environmental and Chemical Engineering, Shanghai
University, Shanghai 200444, China
Hongmei Zhao
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
Shichun Zhang
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
Department of Marine, Earth, and Atmospheric Sciences, North Carolina
State University, Raleigh, NC 27695, USA
Sergio Ibarra-Espinosa
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102,
China
Department of Atmospheric Sciences, Universidade de São Paulo,
São Paulo, SP, Brazil
Key Laboratory for Semi-Arid Climate Change of the Ministry of
Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou
730000, China
Xiaolan Li
Institute of Atmospheric Environment, China Meteorological
Administration, Shenyang 110166, China
School of Meteorology, University of Oklahoma, Norman, OK 73072, USA
Mo Dan
Beijing Municipal Institute of Labor Protection, Beijing 100054,
China
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Jiecan Cui, Tenglong Shi, Yue Zhou, Dongyou Wu, Xin Wang, and Wei Pu
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We make the first quantitative, remote-sensing-based, and hemisphere-scale assessment of radiative forcing (RF) due to light-absorbing particles (LAPs) in snow. We observed significant spatial variations in snow albedo reduction and RF due to LAPs throughout the Northern Hemisphere, with the lowest values occurring in the Arctic and the highest in northeastern China. We determined that the LAPs in snow play a critical role in spatial variability in Northern Hemisphere albedo reduction and RF.
Rui Li, Qiongqiong Wang, Xiao He, Shuhui Zhu, Kun Zhang, Yusen Duan, Qingyan Fu, Liping Qiao, Yangjun Wang, Ling Huang, Li Li, and Jian Zhen Yu
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Li Pan, HyunCheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
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Dandan Zhao, Guangjing Liu, Jinyuan Xin, Jiannong Quan, Yuesi Wang, Xin Wang, Lindong Dai, Wenkang Gao, Guiqian Tang, Bo Hu, Yongxiang Ma, Xiaoyan Wu, Lili Wang, Zirui Liu, and Fangkun Wu
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Under strong atmospheric oxidization capacity, haze pollution in the summer in Beijing was the result of the synergistic effect of the physicochemical process in the atmospheric boundary layer (ABL). With the premise of an extremely stable ABL structure, the formation of secondary aerosols dominated by nitrate was quite intense, driving the outbreak of haze pollution.
Hao He, Xin-Zhong Liang, Chao Sun, Zhining Tao, and Daniel Q. Tong
Atmos. Chem. Phys., 20, 3191–3208, https://doi.org/10.5194/acp-20-3191-2020, https://doi.org/10.5194/acp-20-3191-2020, 2020
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We studied the trend of US ozone pollution from 1990 to 2015 using EPA observations and computer simulations. Observations indicated a decrease in peak ozone at noon due to regulations and a slight increase in ozone in early morning and late afternoon possibly. Our modeling system confirmed these findings and provided detailed information about ozone photochemistry. These results revealed the success of previous control measures and provide scientific evidence for the future regulations.
Xin Wang, Xueying Zhang, and Wenjing Di
Atmos. Meas. Tech., 13, 39–52, https://doi.org/10.5194/amt-13-39-2020, https://doi.org/10.5194/amt-13-39-2020, 2020
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We developed an improved two-sphere integration (TSI) technique to quantify black carbon (BC) concentrations in the atmosphere and seasonal snow. The major advantage of this system is that it combines two distinct integrated spheres to reduce the scattering effect due to light-absorbing particles and thus provides accurate determinations of total light absorption from BC collected on Nuclepore filters.
Jun Zhu, Xiangao Xia, Huizheng Che, Jun Wang, Zhiyuan Cong, Tianliang Zhao, Shichang Kang, Xuelei Zhang, Xingna Yu, and Yanlin Zhang
Atmos. Chem. Phys., 19, 14637–14656, https://doi.org/10.5194/acp-19-14637-2019, https://doi.org/10.5194/acp-19-14637-2019, 2019
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The long-term temporal–spatial variations of the aerosol optical properties over the Tibetan Plateau (TP) based on the multiple ground-based sun photometer sites and the MODIS product are presented. Besides, the aerosol pollution and aerosol transport processes over the TP are also analyzed by the observations and models. The results in this region could help reduce the assessment uncertainties of aerosol radiative forcing and provide more information on aerosol transportation.
Ling Huang, Jingyu An, Bonyoung Koo, Greg Yarwood, Rusha Yan, Yangjun Wang, Cheng Huang, and Li Li
Atmos. Chem. Phys., 19, 14311–14328, https://doi.org/10.5194/acp-19-14311-2019, https://doi.org/10.5194/acp-19-14311-2019, 2019
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Severe haze events characterized by extremely high concentrations of particulate matter occurred frequently in the Yangtze River Delta (YRD) region, China. Rapid sulfate production during these severe haze episodes was observed via atmospheric measurements but air quality models tend to underestimated sulfate. Our study suggests that the SO2+NO2 heterogeneous reactions could be potentially important for sulfate formation in the YRD region and ammonia emissions need to be carefully estimated.
Wei Pu, Jiecan Cui, Tenglong Shi, Xuelei Zhang, Cenlin He, and Xin Wang
Atmos. Chem. Phys., 19, 9949–9968, https://doi.org/10.5194/acp-19-9949-2019, https://doi.org/10.5194/acp-19-9949-2019, 2019
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LAPs (light-absorbing particles) deposited on snow can decrease snow albedo and increase the absorption of solar radiation. Radiative forcing by LAPs will affect the regional hydrological cycle and climate. We use MODIS observations to retrieve the radiative forcing by LAPs in snow across northeastern China (NEC). The results of radiative forcing present distinct spatial variability. We find that the biases are negatively correlated with LAP concentrations and range from
~ 5 % to ~ 350 %.
Li Li, Shuhui Zhu, Jingyu An, Min Zhou, Hongli Wang, Rusha Yan, Liping Qiao, Xudong Tian, Lijuan Shen, Ling Huang, Yangjun Wang, Cheng Huang, Jeremy C. Avise, and Joshua S. Fu
Atmos. Chem. Phys., 19, 9037–9060, https://doi.org/10.5194/acp-19-9037-2019, https://doi.org/10.5194/acp-19-9037-2019, 2019
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Heavy haze usually occurs in winter in eastern China. To control the severe air pollution during the season, comprehensive regional joint-control strategies were implemented throughout a campaign. To evaluate the effectiveness of these strategies and to provide some insight into strengthening the joint-control mechanism, the influence of control measures on levels of air pollution was estimated in this paper.
Xin Wang, Hailun Wei, Jun Liu, Baiqing Xu, Mo Wang, Mingxia Ji, and Hongchun Jin
The Cryosphere, 13, 309–324, https://doi.org/10.5194/tc-13-309-2019, https://doi.org/10.5194/tc-13-309-2019, 2019
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A large survey on measuring optical and chemical properties of insoluble light-absorbing impurities (ILAPs) from seven glaciers was conducted on the Tibetan Plateau (TP) during 2013–2015. The results indicated that the mixing ratios of black carbon (BC), organic carbon (OC), and iron (Fe) all showed a tendency to decrease from north to south, and the industrial pollution (33.1 %), biomass and biofuel burning (29.4 %), and soil dust (37.5 %) were the major sources of the ILAPs on the TP.
Yue Zhou, Hui Wen, Jun Liu, Wei Pu, Qingcai Chen, and Xin Wang
The Cryosphere, 13, 157–175, https://doi.org/10.5194/tc-13-157-2019, https://doi.org/10.5194/tc-13-157-2019, 2019
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We first investigated the optical characteristics and potential sources of chromophoric dissolved organic matter (CDOM) in seasonal snow over northwestern China. The abundance of CDOM showed regional variation. At some sites strongly influenced by local soil, the absorption of CDOM cannot be neglected compared to black carbon. We found two humic-like and one protein-like fluorophores in snow. The major sources of snow CDOM were soil, biomass burning, and anthropogenic pollution.
Zhiyuan Cong, Shaopeng Gao, Wancang Zhao, Xin Wang, Guangming Wu, Yulan Zhang, Shichang Kang, Yongqin Liu, and Junfeng Ji
The Cryosphere, 12, 3177–3186, https://doi.org/10.5194/tc-12-3177-2018, https://doi.org/10.5194/tc-12-3177-2018, 2018
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Cryoconites from glaciers on the Tibetan Plateau and surrounding area were studied for iron oxides. We found that goethite is the predominant iron oxide form. Using the abundance, speciation and optical properties of iron oxides, the total light absorption was quantitatively attributed to goethite, hematite, black carbon and organic matter. Such findings are essential to understand the relative significance of anthropogenic and natural impacts.
Yunhua Chang, Yanlin Zhang, Chongguo Tian, Shichun Zhang, Xiaoyan Ma, Fang Cao, Xiaoyan Liu, Wenqi Zhang, Thomas Kuhn, and Moritz F. Lehmann
Atmos. Chem. Phys., 18, 11647–11661, https://doi.org/10.5194/acp-18-11647-2018, https://doi.org/10.5194/acp-18-11647-2018, 2018
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We demonstrate that it is imperative that future studies, making use of isotope mixing models to gain conclusive constraints on the source partitioning of atmospheric NOx, consider this N isotope fractionation. Future assessments of NOx emissions in China (and elsewhere) should involve simultaneous δ15N and δ18O measurements of atmospheric nitrate and NOx at high spatiotemporal resolution, allowing former N-isotope-based NOx source partitioning estimates to be reevaluated more quantitatively.
Sergio Ibarra-Espinosa, Rita Ynoue, Shane O'Sullivan, Edzer Pebesma, María de Fátima Andrade, and Mauricio Osses
Geosci. Model Dev., 11, 2209–2229, https://doi.org/10.5194/gmd-11-2209-2018, https://doi.org/10.5194/gmd-11-2209-2018, 2018
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An emissions inventory is a compilation of the mass of pollutants released by different sources. The quantification of vehicular emissions is difficult because these sources are in movement across streets. Also, emissions processes are multiple and complex. In this paper, we present an open-source software for calculating spatial vehicular emissions, including exhaust, evaporation and wear, named VEIN. The software is an R package available at
https://github.com/atmoschem/vein.
Xin Wang, Hui Wen, Jinsen Shi, Jianrong Bi, Zhongwei Huang, Beidou Zhang, Tian Zhou, Kaiqi Fu, Quanliang Chen, and Jinyuan Xin
Atmos. Chem. Phys., 18, 2119–2138, https://doi.org/10.5194/acp-18-2119-2018, https://doi.org/10.5194/acp-18-2119-2018, 2018
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A ground-based mobile laboratory was deployed near the dust source regions over northwestern China.
We not only captured natural dust but also characterized the properties of anthropogenic soil dust produced by agricultural cultivations.
The results indicate that large differences were found between the optical and microphysical properties of anthropogenic and natural dust.
Youhua Tang, Mariusz Pagowski, Tianfeng Chai, Li Pan, Pius Lee, Barry Baker, Rajesh Kumar, Luca Delle Monache, Daniel Tong, and Hyun-Cheol Kim
Geosci. Model Dev., 10, 4743–4758, https://doi.org/10.5194/gmd-10-4743-2017, https://doi.org/10.5194/gmd-10-4743-2017, 2017
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In order to evaluate the data assimilation tools for regional real-time PM2.5 forecasts, we applied a 3D-Var assimilation tool to adjust the aerosol initial condition by assimilating satellite-retrieved aerosol optical depth and surface PM2.5 observations for a regional air quality model, which is compared to another assimilation method, optimal interpolation. We discuss the pros and cons of these two assimilation methods based on the comparison of their 1-month four-cycles-per-day runs.
Li Pan, Hyun Cheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-207, https://doi.org/10.5194/gmd-2017-207, 2017
Revised manuscript not accepted
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In this study, a system accounting for fire emissions in a chemical transport model is described. The focus of this work is to qualitatively evaluate the system's capability to capture fire signals identified by multiple observation data sets. We discuss how to use observational data correctly to filter out fire signals and synergistic use of multiple data sets together. We also address the limitations of each of the observation data sets and of the evaluation methods.
Chaopeng Hong, Qiang Zhang, Yang Zhang, Youhua Tang, Daniel Tong, and Kebin He
Geosci. Model Dev., 10, 2447–2470, https://doi.org/10.5194/gmd-10-2447-2017, https://doi.org/10.5194/gmd-10-2447-2017, 2017
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A regional coupled climate–chemistry modeling system using the dynamical downscaling technique was established and evaluated. The modeling system performed well for both the climatological and the short-term air quality applications over east Asia. Regional models outperformed global models in regional climate and air quality predictions. The coupled modeling system improved the model performance, although some biases remained in the aerosol–cloud–radiation variables.
Jianrong Bi, Jianping Huang, Jinsen Shi, Zhiyuan Hu, Tian Zhou, Guolong Zhang, Zhongwei Huang, Xin Wang, and Hongchun Jin
Atmos. Chem. Phys., 17, 7775–7792, https://doi.org/10.5194/acp-17-7775-2017, https://doi.org/10.5194/acp-17-7775-2017, 2017
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We conducted a field campaign on exploring dust aerosol in Dunhuang farmland nearby Gobi deserts. The anthropogenic dust produced by agricultural cultivations exerted a significant superimposed effect on elevated dust loadings. Strong south wind in daytime scavenged the pollution and weak northeast wind at night favorably accumulated air pollutants near the surface. The local emissions remarkably modified the absorptive and optical characteristics of mineral dust in desert source region.
Ling Qi, Qinbin Li, Cenlin He, Xin Wang, and Jianping Huang
Atmos. Chem. Phys., 17, 7459–7479, https://doi.org/10.5194/acp-17-7459-2017, https://doi.org/10.5194/acp-17-7459-2017, 2017
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Black carbon (BC) is the second only to CO2 in heating the planet, but the simulation of BC is associated with large uncertainties. BC burden is largely underestimated over land and overestimated over ocean. Our study finds that a missing process in current Wegener–Bergeron–Findeisen models largely explains the discrepancy in BC simulation over land. We call for more observations of BC in mixed-phase clouds to understand this process and improve the simulation of global BC.
Wei Pu, Xin Wang, Hailun Wei, Yue Zhou, Jinsen Shi, Zhiyuan Hu, Hongchun Jin, and Quanliang Chen
The Cryosphere, 11, 1213–1233, https://doi.org/10.5194/tc-11-1213-2017, https://doi.org/10.5194/tc-11-1213-2017, 2017
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We conducted a large field campaign to collect snow samples in Xinjiang. We measured insoluble light-absorbing particles with estimated black carbon concentrations of 10–150 ngg-1. We found a probable shift in emission sources with the progression of winter and dominated contributions of BC and OC to light absorption. A PMF model indicated an optimal three-factor/source solution that included industrial pollution, biomass burning, and soil dust.
Xin Wang, Wei Pu, Yong Ren, Xuelei Zhang, Xueying Zhang, Jinsen Shi, Hongchun Jin, Mingkai Dai, and Quanliang Chen
Atmos. Chem. Phys., 17, 2279–2296, https://doi.org/10.5194/acp-17-2279-2017, https://doi.org/10.5194/acp-17-2279-2017, 2017
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A 2014 snow survey was performed across northeastern China to analyze light absorption of ILAPs in seasonal snow, and modeling studies were conducted to compare snow albedo reduction due to assumptions of internal–external mixing of BC in snow and different snow grain shapes. The results show that the simulated snow albedos from both SAMDS and SNICAR agree well with the observed values at low ILAP mixing ratios, but they tend to be higher than surface observations at high ILAP mixing ratios.
Xuelei Zhang, Daniel Q. Tong, Guangjian Wu, Xin Wang, Aijun Xiu, Yongxiang Han, Tianli Xu, Shichun Zhang, and Hongmei Zhao
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-681, https://doi.org/10.5194/acp-2016-681, 2016
Revised manuscript has not been submitted
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More detailed knowledge regarding recent variations in the characteristics of East Asian dust events and dust sources can effectively improve regional dust modeling and forecasts. Here we reassess the accuracy of previous predictions of trends in dust variations in East Asia, and establish a relatively detailed inventory of dust events based on satellite observations from 2000 to 2015.
Xinyi Dong, Joshua S. Fu, Kan Huang, Daniel Tong, and Guoshun Zhuang
Atmos. Chem. Phys., 16, 8157–8180, https://doi.org/10.5194/acp-16-8157-2016, https://doi.org/10.5194/acp-16-8157-2016, 2016
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The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust aerosols. Evaluation with observations suggested improved model performance by correcting the double counting of soil moisture impact, applying source-dependent speciation profile, and implementing heterogeneous chemitry.
Xuezhe Xu, Weixiong Zhao, Qilei Zhang, Shuo Wang, Bo Fang, Weidong Chen, Dean S. Venables, Xinfeng Wang, Wei Pu, Xin Wang, Xiaoming Gao, and Weijun Zhang
Atmos. Chem. Phys., 16, 6421–6439, https://doi.org/10.5194/acp-16-6421-2016, https://doi.org/10.5194/acp-16-6421-2016, 2016
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We report on the field measurement of the optical properties and chemical composition of PM1.0 particles in a suburban environment in Beijing during the winter coal heating season. Organic mass was the largest contributor to the total extinction of PM1.0, while EC, owing to its high absorption efficiency, contributed appreciably to PM1.0 extinction and should be a key target to air quality controls. Non-BC absorption from secondary organic aerosol also contributes to particle absorption.
M. Huang, D. Tong, P. Lee, L. Pan, Y. Tang, I. Stajner, R. B. Pierce, J. McQueen, and J. Wang
Atmos. Chem. Phys., 15, 12595–12610, https://doi.org/10.5194/acp-15-12595-2015, https://doi.org/10.5194/acp-15-12595-2015, 2015
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We developed Arizona dust records in 2005-2013 using multiple surface and remote sensing observation data sets. The inter-annual variability of dust events was anticorrelated with three drought indicators (PDSI, satellite NDVI and soil moisture), and stronger dust activity was found in the afternoon than in the morning due to stronger winds and drier soil. Impact of a recent dust event accompanied by a stratospheric ozone intrusion was evaluated with various observational and modeling data sets.
X. L. Zhang, G. J. Wu, C. L. Zhang, T. L. Xu, and Q. Q. Zhou
Atmos. Chem. Phys., 15, 12159–12177, https://doi.org/10.5194/acp-15-12159-2015, https://doi.org/10.5194/acp-15-12159-2015, 2015
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Three different continuous datasets for complex refractive indices of hematite are employed in climate models, the real role of iron-oxides in the optical properties of dust aerosols becomes a key scientific question, and we address this problem by considering different refractive indices, size distributions, and more logical weight fractions and mixing states of hematite. More laboratory measurements should be taken into account when assessing the effect of mineral dust on climate forcing.
T. Chai, H.-C. Kim, P. Lee, D. Tong, L. Pan, Y. Tang, J. Huang, J. McQueen, M. Tsidulko, and I. Stajner
Geosci. Model Dev., 6, 1831–1850, https://doi.org/10.5194/gmd-6-1831-2013, https://doi.org/10.5194/gmd-6-1831-2013, 2013
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Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure facilitating further processing to allow emission processing from continental to street scale.
Najmeh Kaffashzadeh and Abbas Ali Aliakbari Bidokhti
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-226, https://doi.org/10.5194/gmd-2023-226, 2024
Revised manuscript accepted for GMD
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Reanalysis data have been widely used as an initial condition for the daily forecast of the atmosphere or boundary conditions in regional models, for the study of climate change, and as proxies to complement insufficient in situ measurements. This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-202, https://doi.org/10.5194/gmd-2023-202, 2023
Revised manuscript accepted for GMD
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Global Navigation Satellite Systems provide moisture observations through its densely distributed ground station network. In this research, we assimilated a new type of observation called tropospheric gradient observations, which was never incorporated into a weather model. Here, we have developed a forward operator for gradient observations and performed impact studies. Promising improvements were observed in the humidity fields of the model in the assimilation study.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
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The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
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We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
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The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Cited articles
Alfaro, S. C. and Gomes, L.: Modeling mineral aerosol production by wind erosion: Emission intensities and aerosol size
distributions in source areas, J. Geophys. Res.-Atmos., 106, 18075–18084, https://doi.org/10.1029/2000JD900339, 2001.
Alfaro, S. C., Gaudichet, A., Gomes, L., and Maillé, M.: Modeling the
size distribution of a soil aerosol produced by sandblasting, J. Geophys.
Res.-Atmos., 102, 11239–11249, https://doi.org/10.1029/97JD00403, 1997.
Astitha, M., Lelieveld, J., Abdel Kader, M., Pozzer, A., and de Meij, A.: Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties, Atmos. Chem. Phys., 12, 11057–11083, https://doi.org/10.5194/acp-12-11057-2012, 2012.
Bagnold, R. A.: The physics of blown sand and desert dunes, Chapmann and
Hall, Methuen, London, 265 pp., 1941.
Basart, S., Pérez, C., Nickovic, S., Cuevas, E., and Baldasano, J.:
Development and evaluation of the BSC-DREAM8b dust regional model over
Northern Africa, the Mediterranean and the Middle East, Tellus B, 64, 18539, https://doi.org/10.3402/tellusb.v64i0.18539, 2012.
Bessagnet, B., Menut, L., Colette, A., Couvidat, F., Dan, M., Mailler, S.,
Létinois, L., Pont, V., and Rouïl, L.: An Evaluation of the CHIMERE
Chemistry Transport Model to Simulate Dust Outbreaks across the Northern
Hemisphere in March 2014, Atmosphere, 8, 251,
https://doi.org/10.3390/atmos8120251, 2017.
Byun, D. 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, 51–77,
https://doi.org/10.1115/1.2128636, 2006.
Cakmur, R. V., Miller, R. L., and Torres, O.: Incorporating the effect of
small-scale circulations upon dust emission in an atmospheric general
circulation model, J. Geophys. Res., 109, D07201, https://doi.org/10.1029/2003JD004067,
2004.
CAMx: A multi-scale photochemical modeling system for gas and particulate air pollution, available at: http://www.camx.com/, last access: July 2019.
Callebaut, F., Gabriels, D., Minjauw, W., and De Boodt, M.: Determination of
soil surface strength with a needle-type penetrometer, Soil Till. Res.,
5, 227–245, https://doi.org/10.1016/0167-1987(85)90017-0, 1985.
Cao, H., Amiraslani, F., Liu, J., and Zhou, N.: Identification of dust storm
source areas in West Asia using multiple environmental datasets, Sci. Total
Environ., 502, 224–235, https://doi.org/10.1016/j.scitotenv.2014.09.025, 2015.
Chappell, A., Webb, N. P., Viscarra Rossel, R. A., and Bui, E.: Australian net (1950s–1990) soil organic carbon erosion: implications for CO2 emission and land–atmosphere modelling, Biogeosciences, 11, 5235–5244, https://doi.org/10.5194/bg-11-5235-2014, 2014.
Chimere: A multi-scale chemistry-transport model for atmospheric composition analysis and forecast, available at: http://www.lmd.polytechnique.fr/chimere/, last access: July 2018.
Darmenova, K., Sokolik, I. N., Shao, Y., Marticorena, B., and Bergametti, G.:
Development of a physically based dust emission module within the Weather
Research and Forecasting (WRF) model: Assessment of dust emission
parameterizations and input parameters for source regions in Central and
East Asia, J. Geophys. Res.-Atmos., 114, 1–28, https://doi.org/10.1029/2008JD011236,
2009.
Dickerson, R. R., Li, C., Li, Z., Marufu, L. T., Stehr, J. W., Mcclure, B., Krotkov, N., Chen, H., Wang, P., Xia, X., Ban, X.,
Gong, F., Yuan, J. and Yang, J.: Aircraft observations of dust and pollutants over northeast China: Insight into the
meteorological mechanisms of transport, J. Geophys. Res.-Atmos., 112, 1–13, https://doi.org/10.1029/2007JD008999, 2007.
Dong, X., Fu, J. S., Huang, K., Tong, D., and Zhuang, G.: Model development of dust emission and heterogeneous chemistry within the Community Multiscale Air Quality modeling system and its application over East Asia, Atmos. Chem. Phys., 16, 8157–8180, https://doi.org/10.5194/acp-16-8157-2016, 2016.
Evan, A. T., Fiedler, S., Zhao, C., Menut, L., Schepanski, K., Flamant, C.,
and Doherty, O.: Derivation of an observation-based map of North African
dust emission, Aeolian Res., 16, 153–162, https://doi.org/10.1016/j.aeolia.2015.01.001,
2015.
Fan, R., Liang, A., Yang, X., Zhang, X., Shen, Y., and Shi, X.: Effects of
tillage on soil aggregates in black soils in Northeast China, Sci. Agric.
Sin., 43, 3767–3775, 2010.
Fécan, F., Marticorena, B., and Bergametti, G.: Parametrization of the
increase of the aeolian erosion threshold wind friction velocity due to soil
moisture for arid and semi-arid areas, Ann. Geophys., 17, 149–157,
https://doi.org/10.1007/s00585-999-0149-7, 1999.
Flaounas, E., Kotroni, V., Lagouvardos, K., Klose, M., Flamant, C., and Giannaros, T. M.: Sensitivity of the WRF-Chem (V3.6.1) model to different dust emission parametrisation: assessment in the broader Mediterranean region, Geosci. Model Dev., 10, 2925–2945, https://doi.org/10.5194/gmd-10-2925-2017, 2017.
Formenti, P., Schütz, L., Balkanski, Y., Desboeufs, K., Ebert, M., Kandler, K., Petzold, A., Scheuvens, D., Weinbruch, S., and Zhang, D.: Recent progress in understanding physical and chemical properties of African and Asian mineral dust, Atmos. Chem. Phys., 11, 8231–8256, https://doi.org/10.5194/acp-11-8231-2011, 2011.
Foroutan, H., Young, J., Napelenok, S., Ran, L., Appel, K. W., Gilliam, R.
C., and Pleim, J. E.: Development and evaluation of a physics-based
windblown dust emission scheme implemented in the CMAQ modeling system, J.
Adv. Model. Earth Sy., 9, 585–608, https://doi.org/10.1002/2016MS000823, 2017.
Giannadaki, D., Pozzer, A., and Lelieveld, J.: Modeled global effects of airborne desert dust on air quality and premature mortality, Atmos. Chem. Phys., 14, 957–968, https://doi.org/10.5194/acp-14-957-2014, 2014.
Gillette, D. A.: Fine particulate emissions due to wind erosion, T.
ASAE, 20, 890–897, 1977.
Gillette, D. A. and Passi, R.: Modeling dust emission caused by wind
erosion, J. Geophys. Res.-Atmos., 93, 14233–14242,
https://doi.org/10.1029/JD093iD11p14233, 1988.
Gillette, D. A., Fryrear, D. W., Gill, T. E., Ley, T., Cahill, T. A., and
Gearhart, E. A.: Relation of vertical flux of particles smaller than 10 µm to total aeolian horizontal mass flux at Owens Lake, J. Geophys. Res.-Atmos., 102, 26009–26015, https://doi.org/10.1029/97JD02252, 1997.
Gillette, D. A., Herbert, G., Stockton, P. H., and Owen, P. R.: Causes of the
fetch effect in wind erosion, Earth Surf. Process. Land., 21,
641–659, https://doi.org/10.1002/(SICI)1096-9837(199607), 1996.
Ginoux, P., Chin, M., Tegen, I., Prospero, J. M., Holben, B., Dubovik, O.,
and Lin, S.: Sources and distributions of dust aerosols simulated with the
GOCART model, J. Geophys. Res.-Atmos., 106, 20255–20273,
https://doi.org/10.1029/2000JD000053, 2001.
Ginoux, P., Prospero, J. M., Gill, T. E., Hsu, N. C., and Zhao, M.:
Global-scale attribution of anthropogenic and natural dust sources and
their emission rates based on MODIS Deep Blue aerosol products, Rev.
Geophys., 50, 1–36, https://doi.org/10.1029/2012RG000388, 2012.
Gomes, L., Rajot, J. L., Alfaro, S. C., and Gaudichet, A.: Validation of a
dust production model from measurements performed in semi-arid agricultural
areas of Spain and Niger, Catena, 52, 257–271,
https://doi.org/10.1016/S0341-8162(03)00017-1, 2003.
Goudie, A. S.: Desert dust and human health disorders, Environ. Int., 63,
101–113, https://doi.org/10.1016/j.envint.2013.10.011, 2014.
Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G.,
Skamarock, W. C., and Eder, B.: Fully coupled “online” chemistry within the
WRF model, Atmos. Environ., 39, 6957–6975,
https://doi.org/10.1016/j.atmosenv.2005.04.027, 2005.
Guan, X., Huang, J., Zhang, Y., Xie, Y., and Liu, J.: The relationship between anthropogenic dust and population over global semi-arid regions, Atmos. Chem. Phys., 16, 5159–5169, https://doi.org/10.5194/acp-16-5159-2016, 2016.
Hodzic, A., Bessagnet, B., and Vautard, R.: A model evaluation of coarse-mode
nitrate heterogeneous formation on dust particles, Atmos. Environ., 40,
4158–4171, https://doi.org/10.1016/j.atmosenv.2006.02.015, 2006.
Huneeus, N., Schulz, M., Balkanski, Y., Griesfeller, J., Prospero, J., Kinne, S., Bauer, S., Boucher, O., Chin, M., Dentener, F., Diehl, T., Easter, R., Fillmore, D., Ghan, S., Ginoux, P., Grini, A., Horowitz, L., Koch, D., Krol, M. C., Landing, W., Liu, X., Mahowald, N., Miller, R., Morcrette, J.-J., Myhre, G., Penner, J., Perlwitz, J., Stier, P., Takemura, T., and Zender, C. S.: Global dust model intercomparison in AeroCom phase I, Atmos. Chem. Phys., 11, 7781–7816, https://doi.org/10.5194/acp-11-7781-2011, 2011.
Huneeus, N., Basart, S., Fiedler, S., Morcrette, J.-J., Benedetti, A., Mulcahy, J., Terradellas, E., Pérez García-Pando, C., Pejanovic, G., Nickovic, S., Arsenovic, P., Schulz, M., Cuevas, E., Baldasano, J. M., Pey, J., Remy, S., and Cvetkovic, B.: Forecasting the northern African dust outbreak towards Europe in April 2011: a model intercomparison, Atmos. Chem. Phys., 16, 4967–4986, https://doi.org/10.5194/acp-16-4967-2016, 2016.
Iversen, J. D. and White, B. R.: Saltation threshold on earth, mars and
venus, Sedimentology, 29, 111–119,
https://doi.org/10.1111/j.1365-3091.1982.tb01713.x, 1982.
Jickells, T. D., An, Z. S., Andersen, K. K., Baker, A. R., Bergametti, G., Brooks, N., Cao, J. J., Boyd, P. W., Duce, R. A. and
Hunter, K. A.: Global iron connections between desert dust, ocean biogeochemistry, and climate, Science, 308, 67–71,
https://doi.org/10.1126/science.1105959, 2005.
Jish Prakash, P., Stenchikov, G., Kalenderski, S., Osipov, S., and Bangalath, H.: The impact of dust storms on the Arabian Peninsula and the Red Sea, Atmos. Chem. Phys., 15, 199–222, https://doi.org/10.5194/acp-15-199-2015, 2015.
Ju, T., Li, X., Zhang, H., Cai, X., and Song, Y.: Comparison of two different
dust emission mechanisms over the Horqin Sandy Land area: Aerosols
contribution and size distributions, Atmos. Environ., 176, 82–90,
https://doi.org/10.1016/j.atmosenv.2017.12.017, 2018.
Kang, J., Yoon, S., Shao, Y., and Kim, S.: Comparison of vertical dust flux
by implementing three dust emission schemes in WRF/Chem, J. Geophys. Res.-Atmos., 116, D09202, https://doi.org/10.1029/2010JD014649, 2011.
Kim, D., Kemp, E., and Chin, M.: A brief description of new dust source
functions in NU-WRF version 7, NASA Goddard Sp. Flight Center, 4 pp., 2014.
Klingmüller, K., Metzger, S., Abdelkader, M., Karydis, V. A., Stenchikov, G. L., Pozzer, A., and Lelieveld, J.: Revised mineral dust emissions in the atmospheric chemistry–climate model EMAC (MESSy 2.52 DU_Astitha1 KKDU2017 patch), Geosci. Model Dev., 11, 989–1008, https://doi.org/10.5194/gmd-11-989-2018, 2018.
Klose, M., Shao, Y., Li, X., Zhang, H., Ishizuka, M., Mikami, M., and Leys,
J. F.: Further development of a parameterization for convective turbulent
dust emission and evaluation based on field observations, J. Geophys.
Res.-Atmos., 119, 10441–10457, https://doi.org/10.1002/2014JD021688, 2014.
Kok, J. F., Mahowald, N. M., Fratini, G., Gillies, J. A., Ishizuka, M., Leys, J. F., Mikami, M., Park, M.-S., Park, S.-U., Van Pelt, R. S., and Zobeck, T. M.: An improved dust emission model – Part 1: Model description and comparison against measurements, Atmos. Chem. Phys., 14, 13023–13041, https://doi.org/10.5194/acp-14-13023-2014, 2014a.
Kok, J. F., Albani, S., Mahowald, N. M., and Ward, D. S.: An improved dust emission model – Part 2: Evaluation in the Community Earth System Model, with implications for the use of dust source functions, Atmos. Chem. Phys., 14, 13043–13061, https://doi.org/10.5194/acp-14-13043-2014, 2014b.
Koven, C. D. and Fung, I.: Identifying global dust source areas using
high-resolution land surface form, J. Geophys. Res.-Atmos., 113, D22204,
https://doi.org/10.1029/2008JD010195, 2008.
Lattuati, M.: Contribution à l'étude du bilan de l'ozone troposphérique à l'interface del'Europe et de l'Atlantique Nord: modélisation lagrangienne et mesures en altitude, Phd thesis, Université P.M. Curie, Paris, France, 1997.
Laurent, B., Marticorena, B., Bergametti, G., Chazette, P., Maignan, F., and
Schmechtig, C.: Simulation of the mineral dust emission frequencies from
desert areas of China and Mongolia using an aerodynamic roughness length map
derived from the POLDER/ADEOS 1 surface products, J. Geophys. Res.-Atmos.,
110, D18S04, https://doi.org/10.1029/2004JD005013, 2005.
LeGrand, S. L., Polashenski, C., Letcher, T. W., Creighton, G. A., Peckham, S. E., and Cetola, J. D.: The AFWA dust emission scheme for the GOCART aerosol model in WRF-Chem v3.8.1, Geosci. Model Dev., 12, 131–166, https://doi.org/10.5194/gmd-12-131-2019, 2019.
Li, J., Wang, Z., Zhuang, G., Luo, G., Sun, Y., and Wang, Q.: Mixing of Asian mineral dust with anthropogenic pollutants over East Asia: a model case study of a super-duststorm in March 2010, Atmos. Chem. Phys., 12, 7591–7607, https://doi.org/10.5194/acp-12-7591-2012, 2012.
Li, X. L., Klose, M., Shao, Y., and Zhang, H. S.: Convective turbulent dust
emission (CTDE) observed over Horqin Sandy Land area and validation of a
CTDE scheme, J. Geophys. Res.-Atmos., 119, 9980–9992,
https://doi.org/10.1002/2014JD021572, 2014.
Liora, N., Poupkou, A., Giannaros, T. M., Kakosimos, K. E., Stein, O., and
Melas, D.: Impacts of natural emission sources on particle pollution levels
in Europe, Atmos. Environ., 137, 171–185,
https://doi.org/10.1016/j.atmosenv.2016.04.040, 2016.
Lu, H. and Shao, Y.: A new model for dust emission by saltation bombardment,
J. Geophys. Res.-Atmos., 104, 16827–16842, https://doi.org/10.1029/1999JD900169,
1999.
Ma, S., Zhang, X., Gao, C., Tong, D. Q., Xiu, A., Wu, G, and Dan, M.: Multi-model simulations of a springtime dust storms over Northeastern China: Implications of an evaluation of four commonly used air quality models (CMAQ v5.2.1, CAMx v6.50, CHIMERE v2017r4, and WRF-Chem v3.9.1) (Version V1.0), Zenodo, https://doi.org/10.5281/zenodo.3376774, 2019.
Macpherson, T., Nickling, W. G., Gillies, J. A., and Etyemezian, V.: Dust
emissions from undisturbed and disturbed supply-limited desert surfaces, J.
Geophys. Res.-Earth, 113, https://doi.org/10.1029/2007JF000800, 2008.
Mahowald, N. M., Ballantine, J. A., Feddema, J., and Ramankutty, N.: Global trends in visibility: implications for dust sources, Atmos. Chem. Phys., 7, 3309–3339, https://doi.org/10.5194/acp-7-3309-2007, 2007.
Mailler, S., Menut, L., Khvorostyanov, D., Valari, M., Couvidat, F., Siour, G., Turquety, S., Briant, R., Tuccella, P., Bessagnet, B., Colette, A., Létinois, L., Markakis, K., and Meleux, F.: CHIMERE-2017: from urban to hemispheric chemistry-transport modeling, Geosci. Model Dev., 10, 2397–2423, https://doi.org/10.5194/gmd-10-2397-2017, 2017.
Manders-Groot, A. M. M., Segers, A. J., Jonkers, S., Schaap, M., Timmermans,
R., Hendriks, C., Sauter, F., Kruit, R. W., van der Swaluw, E., and Eskes,
H.: LOTOS-EUROS v2.0 reference guide, TNO Rep. TNO2016, 10898, 2016.
Marticorena, B. and Bergametti, G.: Modeling the atmospheric dust cycle: 1.
Design of a soil-derived dust emission scheme, J. Geophys. Res.-Atmos., 100,
16415–16430, https://doi.org/10.1029/95JD00690, 1995.
Marticorena, B., Bergametti, G., Aumont, B., Callot, Y., N'doumé, C.,
and Legrand, M.: Modeling the atmospheric dust cycle: 2. Simulation of
Saharan dust sources, J. Geophys. Res.-Atmos., 102, 4387–4404,
https://doi.org/10.1029/96JD02964, 1997.
Mendez, M. J. and Buschiazzo, D. E.: Wind erosion risk in agricultural soils
under different tillage systems in the semiarid Pampas of Argentina, Soil
Till. Res., 106, 311–316, https://doi.org/10.1016/j.still.2009.10.010, 2010.
Menut, L., Schmechtig, C., and Marticorena, B.: Sensitivity of the
sandblasting flux calculations to the soil size distribution accuracy, J.
Atmos. Ocean. Tech., 22, 1875–1884, https://doi.org/10.1175/JTECH1825.1, 2005.
Menut, L., Bessagnet, B., Khvorostyanov, D., Beekmann, M., Blond, N., Colette, A., Coll, I., Curci, G., Foret, G., Hodzic, A., Mailler, S., Meleux, F., Monge, J.-L., Pison, I., Siour, G., Turquety, S., Valari, M., Vautard, R., and Vivanco, M. G.: CHIMERE 2013: a model for regional atmospheric composition modelling, Geosci. Model Dev., 6, 981–1028, https://doi.org/10.5194/gmd-6-981-2013, 2013a.
Menut, L., Pérez, C., Haustein, K., Bessagnet, B., Prigent, C., and
Alfaro, S.: Impact of surface roughness and soil texture on mineral dust
emission fluxes modeling, J. Geophys. Res.-Atmos., 118, 6505–6520,
https://doi.org/10.1002/jgrd.50313, 2013b.
Mokhtari, M., Gomes, L., Tulet, P., and Rezoug, T.: Importance of the surface size distribution of erodible material: an improvement on the Dust Entrainment And Deposition (DEAD) Model, Geosci. Model Dev., 5, 581–598, https://doi.org/10.5194/gmd-5-581-2012, 2012.
Munkhtsetseg, E., Shinoda, M., Ishizuka, M., Mikami, M., Kimura, R., and Nikolich, G.: Anthropogenic dust emissions due to livestock trampling in a Mongolian temperate grassland, Atmos. Chem. Phys., 17, 11389–11401, https://doi.org/10.5194/acp-17-11389-2017, 2017.
Nabavi, S. O., Haimberger, L., and Samimi, C.: Sensitivity of WRF-chem
predictions to dust source function specification in West Asia, Aeolian
Res., 24, 115–131, https://doi.org/10.1016/j.aeolia.2016.12.005, 2017.
Nickling, W. G., McTainsh, G. H., and Leys, J. F.: Dust emissions from the
Channel Country of western Queensland, Australia, Z.
Geomorphol. Suppl., 1–17, 1999.
Owen, P. R.: Saltation of uniform grains in air, J. Fluid Mech., 20,
225–242, https://doi.org/10.1017/S0022112064001173, 1964.
Panebianco, J. E., Mendez, M. J., and Buschiazzo, D. E.: PM10 emission,
sandblasting efficiency and vertical entrainment during successive
wind-erosion events: a wind-tunnel approach, Bound.-Lay. Meteorol.,
161, 335–353, https://doi.org/10.1007/s10546-016-0172-7, 2016.
Parajuli, S. P., Zobeck, T. M., Kocurek, G., Yang, Z., and Stenchikov, G. L.:
New insights into the wind-dust relationship in sandblasting and direct
aerodynamic entrainment from wind tunnel experiments, J. Geophys. Res.-Atmos., 121, 1776–1792, https://doi.org/10.1002/2015JD024424, 2016.
Prospero, J. M. and Lamb, P. J.: African droughts and dust transport to the
Caribbean: Climate change implications, Science, 302,
1024–1027, https://doi.org/10.1126/science.1089915, 2003.
Pryor, S., Schoof, J., and Barthelmie, R.: Empirical downscaling of wind speed
probability distributions, J. Geophys. Res., 110, D19109, https://doi.org/10.1029/2005JD005899, 2005.
Rajot, J. L., Alfaro, S. C., Gomes, L., and Gaudichet, A.: Soil crusting on
sandy soils and its influence on wind erosion, Catena, 53, 1–16,
https://doi.org/10.1016/S0341-8162(02)00201-1, 2003.
Raupach, M.: Drag and drag partition on rough surfaces, Bound-Lay. Meteorol.,
60, 375–395, https://doi.org/10.1007/BF00155203,
1992.
Revel-Rolland, M., De Deckker, P., Delmonte, B., Hesse, P. P., Magee,
J. W., Basile-Doelsch, I., Grousset, F., and Bosch, D.: Eastern Australia: a
possible source of dust in East Antarctica interglacial ice, Earth Planet.
Sc. Lett., 249, 1–13, https://doi.org/10.1016/j.epsl.2006.06.028, 2006.
Rice, M. A., Mullins, C. E. and McEwan, I. K.: An analysis of soil crust strength in relation to potential abrasion by saltat
ing
particles, Earth Surf. Process. Landforms, 22, 869–883, https://doi.org/10.1002/(SICI)1096-9837(199709)22:9<869::AID-ESP785>3.0.CO;2-P, 1998.
Ridley, D. A., Heald, C. L., Kok, J. F., and Zhao, C.: An observationally constrained estimate of global dust aerosol optical depth, Atmos. Chem. Phys., 16, 15097–15117, https://doi.org/10.5194/acp-16-15097-2016, 2016.
Rizza, U., Anabor, V., Mangia, C., Miglietta, M. M., Degrazia, G. A., and
Passerini, G.: WRF-Chem Simulation of a saharan dust outbreak over the
mediterranean regions, Ciência e
Natura, Vol. 38, Special Edition, 330–336, https://doi.org/10.5902/2179460X20249, 2016.
Rizza, U., Barnaba, F., Miglietta, M. M., Mangia, C., Di Liberto, L., Dionisi, D., Costabile, F., Grasso, F., and Gobbi, G. P.: WRF-Chem model simulations of a dust outbreak over the central Mediterranean and comparison with multi-sensor desert dust observations, Atmos. Chem. Phys., 17, 93–115, https://doi.org/10.5194/acp-17-93-2017, 2017.
Roney, J. A. and White, B. R.: Estimating fugitive dust emission rates using
an environmental boundary layer wind tunnel, Atmos. Environ., 40,
7668–7685, https://doi.org/10.1016/j.atmosenv.2006.08.015, 2006.
Sabre, M., Lopez, M. V, Alfaro, S. C., Rajot, J. L., and Gomes, L.:
Characterization of the fine dust particle production process by wind
erosion for two types of bare soil surfaces, in: Proceedings of Wind Erosion:
An International Symposium/Workshop, 3–5, https://doi.org/10.1007/s00254-006-0363-5,
1997.
Schmechtig, C., Marticorena, B., Chatenet, B., Bergametti, G., Rajot, J. L., and Coman, A.: Simulation of the mineral dust content over Western Africa from the event to the annual scale with the CHIMERE-DUST model, Atmos. Chem. Phys., 11, 7185–7207, https://doi.org/10.5194/acp-11-7185-2011, 2011.
Schulz, M., Prospero, J. M., Baker, A. R., Dentener, F., Ickes, L., Liss, P.
S., Mahowald, N. M., Nickovic, S., Garcia-Pando, C. P., and Rodríguez,
S.: Atmospheric transport and deposition of mineral dust to the ocean:
implications for research needs, Environ. Sci. Technol., 46,
10390–10404, https://doi.org/10.1021/es300073u, 2012.
Shao, Y.: A model for mineral dust emission, J. Geophys. Res.-Atmos.,
106, 20239–20254, https://doi.org/10.1029/2001JD900171, 2001.
Shao, Y.: Simplification of a dust emission scheme and comparison with data,
J. Geophys. Res.-Atmos., 109, D10202, https://doi.org/10.1029/2003JD004372, 2004.
Shao, Y. and Lu, H.: A simple expression for wind erosion threshold friction
velocity, J. Geophys. Res.-Atmos., 105, 22437–22443,
https://doi.org/10.1029/2000JD900304, 2000.
Shao, Y., Ishizuka, M., Mikami, M., and Leys, J. F.: Parameterization of
size-resolved dust emission and validation with measurements, J. Geophys.
Res.-Atmos., 116, D08203, https://doi.org/10.1029/2010JD014527, 2011.
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., and Wind, P.: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 7825–7865, https://doi.org/10.5194/acp-12-7825-2012, 2012.
Singh, P., Sharratt, B., and Schillinger, W. F.: Wind erosion and PM10
emission affected by tillage systems in the world's driest rainfed wheat
region, Soil Till. Res., 124, 219–225, https://doi.org/10.1016/j.still.2012.06.009,
2012.
Su, L. and Fung, J. C. H.: Sensitivities of WRF-Chem to dust emission
schemes and land surface properties in simulating dust cycles during
springtime over East Asia, J. Geophys. Res.-Atmos., 120, 11–215,
https://doi.org/10.1002/2015JD023446, 2015.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single diagram, J. Geophys. Res., 106, 7183–7192,
https://doi.org/10.1029/2000JD900719, 2001.
Todd, M. C., Karam, D. B., Cavazos, C., Bouet, C., Heinold, B., Baldasano,
J. M., Cautenet, G., Koren, I., Perez, C., and Solmon, F.: Quantifying
uncertainty in estimates of mineral dust flux: An intercomparison of model
performance over the Bodélé Depression, northern Chad, J. Geophys.
Res.-Atmos., 113, D24107, https://doi.org/10.1029/2008JD010476, 2008.
Tong, D. Q., Dan, M., Wang, T., and Lee, P.: Long-term dust climatology in the western United States reconstructed from routine aerosol ground monitoring, Atmos. Chem. Phys., 12, 5189–5205, https://doi.org/10.5194/acp-12-5189-2012, 2012.
Tong, D. Q., Wang, J. X. L., Gill, T. E., Lei, H., and Wang, B.: Intensified
dust storm activity and Valley fever infection in the southwestern United
States, Geophys. Res. Lett., 44, 4304–4312, https://doi.org/10.1002/2017GL073524,
2017.
Uno, I., Wang, Z., Chiba, M., Chun, Y. S., Gong, S. L., Hara, Y., Jung, E.,
Lee, S., Liu, M., and Mikami, M.: Dust model intercomparison (DMIP) study
over Asia: Overview, J. Geophys. Res.-Atmos., 111, D12213,
https://doi.org/10.1029/2005JD006575, 2006.
US EPA: CMAQ model documentation and released versions of the source code, available at: https://www.cmascenter.org/, last access: July 2019.
Varga, G.: Spatio-temporal distribution of dust storms – a global coverage
using NASA TOMS aerosol measurements, Hung. Geogr. Bull., 61,
275–298, 2012.
Vautard, R., Bessagnet, B., Chin, M., and Menut, L.: On the contribution of
natural Aeolian sources to particulate matter concentrations in Europe:
testing hypotheses with a modelling approach, Atmos. Environ., 39,
3291–3303, https://doi.org/10.1016/j.atmosenv.2005.01.051, 2005.
Wang, H., Xue, M., Zhang, X. Y., Liu, H. L., Zhou, C. H., Tan, S. C., Che, H. Z., Chen, B., and Li, T.: Mesoscale modeling study of the interactions between aerosols and PBL meteorology during a haze episode in Jing–Jin–Ji (China) and its nearby surrounding region – Part 1: Aerosol distributions and meteorological features, Atmos. Chem. Phys., 15, 3257–3275, https://doi.org/10.5194/acp-15-3257-2015, 2015.
Wang, K., Zhang, Y., Nenes, A., and Fountoukis, C.: Implementation of dust emission and chemistry into the Community Multiscale Air Quality modeling system and initial application to an Asian dust storm episode, Atmos. Chem. Phys., 12, 10209–10237, https://doi.org/10.5194/acp-12-10209-2012, 2012.
Wang, R., Chang, C., Peng, S., and Wang, L.: Estimation on farmland
wind-erosion and dust emission amount in Bashang of Hebei province by grain
composition contrast, Trans. Chinese Soc. Agric. Eng., 29, 108–114,
2013.
White, B. R.: Soil transport by winds on Mars, J. Geophys. Res.-Sol. Ea.,
84, 4643–4651, https://doi.org/10.1029/JB084iB09p04643, 1979.
White, B. R.: Encyclopedia of fluid mechanics, Gulf Publishing, Houston,
Tex, USA, 239–282, 1986.
WRF Users page: WRF Source Codes and Graphics Software Downloads, available at: http://www2.mmm.ucar.edu/wrf/users/download/get_source.html, last access: July 2018.
Xi, X. and Sokolik, I. N.: Seasonal dynamics of threshold friction velocity
and dust emission in Central Asia, J. Geophys. Res.-Atmos., 120,
1536–1564, https://doi.org/10.1002/2014JD022471, 2015.
Xi, X. and Sokolik, I. N.: Quantifying the anthropogenic dust emission from
agricultural land use and desiccation of the Aral Sea in Central Asia, J.
Geophys. Res.-Atmos., 121, 12270–12281, https://doi.org/10.1002/2016JD025556, 2016.
Zender, C. S., Miller, R. L., and Tegen, I.: Quantifying mineral dust mass budgets : Terminology, constraints, and current
estimates, Eos (Washington, DC), 85, https://doi.org/10.1029/2004EO480002, 2004.
Zhang, J., Teng, Z., Huang, N., Guo, L., and Shao, Y.: Surface renewal as a significant mechanism for dust emission, Atmos. Chem. Phys., 16, 15517–15528, https://doi.org/10.5194/acp-16-15517-2016, 2016.
Zhang, X., Zhou, Q., Chen, W., Wang, Y., and Tong, D. Q.: Observation and
modeling of black soil wind-blown erosion from cropland in Northeastern
China, Aeolian Res., 19, 153–162, https://doi.org/10.1016/j.aeolia.2015.07.009, 2015.
Zhang, X., Zhao, L., Tong, D. Q., Wu, G., Dan, M., and Teng, B.: A systematic
review of global desert dust and associated human health effects, Atmosphere, 7, 158, https://doi.org/10.3390/atmos7120158, 2016.
Zhao, C., Liu, X., and Leung, L. R.: Impact of the Desert dust on the summer monsoon system over Southwestern North America, Atmos. Chem. Phys., 12, 3717–3731, https://doi.org/10.5194/acp-12-3717-2012, 2012.
Short summary
Dust storms are thought to be a worldwide societal issue, and numerical modeling is an effective way to help us to predict dust events. Here we present the first comprehensive evaluation of dust emission modules in four commonly used air quality models for northeastern China. The results showed that most of these models were able to capture this dust event and indicated the dust source maps should be carefully selected or replaced with a new one that is constructed with local data.
Dust storms are thought to be a worldwide societal issue, and numerical modeling is an effective...