Articles | Volume 18, issue 3
https://doi.org/10.5194/gmd-18-651-2025
© Author(s) 2025. 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-18-651-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China
School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, Anhui, China
National Key Laboratory of Deep Space Exploration, Deep Space Exploration Laboratory, Hefei 230088, Anhui, China
Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Xueyin Ruan
School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, Anhui, China
Shanna Yue
Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Jing Wang
Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Chun Zhao
CORRESPONDING AUTHOR
School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, Anhui, China
National Key Laboratory of Deep Space Exploration, Deep Space Exploration Laboratory, Hefei 230088, Anhui, China
CAS Center for Excellence in Comparative Planetology, University of Science and Technology of China, Hefei 230026, Anhui, China
School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, Anhui, China
National Key Laboratory of Deep Space Exploration, Deep Space Exploration Laboratory, Hefei 230088, Anhui, China
CAS Center for Excellence in Comparative Planetology, University of Science and Technology of China, Hefei 230026, Anhui, China
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Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev., 18, 5373–5396, https://doi.org/10.5194/gmd-18-5373-2025, https://doi.org/10.5194/gmd-18-5373-2025, 2025
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This study provides a comprehensive evaluation of unstructured meshes using the integrated Atmospheric Model Across Scales (iAMAS) over Antarctica, encompassing both surface and upper-level meteorological fields. Comparisons with the fifth-generation reanalysis (ERA5) from the European Centre for Medium-Range Weather Forecasts and observational data indicate that iAMAS performs well in simulating the Antarctic atmosphere.
Zining Yang, Qiuyan Du, Qike Yang, Chun Zhao, Gudongze Li, Zihan Xia, Mingyue Xu, Renmin Yuan, Yubin Li, Kaihui Xia, Jun Gu, and Jiawang Feng
Atmos. Chem. Phys., 25, 8831–8857, https://doi.org/10.5194/acp-25-8831-2025, https://doi.org/10.5194/acp-25-8831-2025, 2025
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This study investigates the impact of turbulent mixing on black carbon (BC) concentrations in urban areas simulated at 25, 5, and 1 km resolutions. Significant variations in BC and turbulent mixing occur mainly at night. Higher resolutions reduce BC overestimation due to enhanced mixing coefficients and vertical wind fluxes. Small-scale eddies at higher resolutions increase the BC lifetime and column concentrations. Land use and terrain variations across multiple resolutions affect turbulent mixing.
Zihan Xia, Chun Zhao, Zining Yang, Qiuyan Du, Jiawang Feng, Chen Jin, Jun Shi, and Hong An
Atmos. Chem. Phys., 25, 6197–6218, https://doi.org/10.5194/acp-25-6197-2025, https://doi.org/10.5194/acp-25-6197-2025, 2025
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Traditional numerical schemes of aerosol chemistry and interactions (ACI) in atmospheric models are computationally costly and are often simplified or omitted, introducing uncertainties. We use an AI scheme to achieve fast, accurate, and stable end-to-end simulation for full ACI within an atmospheric model, replacing numerical schemes. This innovation is expected to enhance the accuracy and efficiency of ACI simulations in climate models that would otherwise neglect or simplify ACI processes.
Zhao Wei, Shohei Hattori, Asuka Tsuruta, Zhuang Jiang, Sakiko Ishino, Koji Fujita, Sumito Matoba, Lei Geng, Alexis Lamothe, Ryu Uemura, Naohiro Yoshida, Joel Savarino, and Yoshinori Iizuka
Atmos. Chem. Phys., 25, 5727–5742, https://doi.org/10.5194/acp-25-5727-2025, https://doi.org/10.5194/acp-25-5727-2025, 2025
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Nitrate isotope records in ice cores reveal changes in NOₓ emissions and atmospheric oxidation chemistry driven by human activity. However, UV-driven postdepositional processes can alter nitrate in snow, making snow accumulation rates critical for preserving these records. This study examines nitrate isotopes in a southeastern Greenland ice core, where high snow accumulation minimizes these effects, providing a reliable archive of atmospheric nitrogen cycling.
Kai Man, Xichen Li, Jürg Luterbacher, Lei Geng, Naiming Yuan, Yurong Hou, Yonghao Wang, and Yujie Miao
EGUsphere, https://doi.org/10.5194/egusphere-2025-1381, https://doi.org/10.5194/egusphere-2025-1381, 2025
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The West Antarctic Ice Sheet shows opposing snow accumulation trends: decreasing in the west and increasing in the east. Our study reveals that tropical ocean temperature shifts – Pacific cooling and Atlantic warming – drive changes in winds and moisture, boosting snowfall in the east while reducing it in the west. Using ice cores and models, we highlight how distant ocean changes shape Antarctic Ice Sheet, crucial for predicting future sea level rise.
Xufeng Wang, Tao Che, Jingfeng Xiao, Tonghong Wang, Junlei Tan, Yang Zhang, Zhiguo Ren, Liying Geng, Haibo Wang, Ziwei Xu, Shaomin Liu, and Xin Li
Earth Syst. Sci. Data, 17, 1329–1346, https://doi.org/10.5194/essd-17-1329-2025, https://doi.org/10.5194/essd-17-1329-2025, 2025
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In this study, carbon flux and auxiliary meteorological data are post-processed to create an analysis-ready dataset for 34 sites across six ecosystems in the Heihe River basin. Overall, 18 sites have multi-year observations, while 16 were observed only during the 2012 growing season, totaling 1513 site months. This dataset can be used to explore carbon exchange, assess ecosystem responses to climate change, support upscaling studies, and evaluate carbon cycle models.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Jiawang Feng, Chun Zhao, Jun Gu, Gudongze Li, Mingyue Xu, Shengfu Lin, and Jie Feng
EGUsphere, https://doi.org/10.5194/egusphere-2024-4037, https://doi.org/10.5194/egusphere-2024-4037, 2025
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Climate models help study aerosol impacts on regional climate. However, the atmosphere's chaotic nature makes it hard to separate true aerosol impacts from chaotic effects. Our ensemble experiments show that while large-scale aerosol effects are consistent, regional aerosol impacts vary significantly among experiments. We give a formula showing the relationship between chaotic effects and ensemble sizes, emphasizing the necessity of adequate ensemble members to capture reliable aerosol impacts.
Zhongyi Zhang, Chunxiang Ye, Yichao Wu, Tao Zhou, Pengfei Chen, Shichang Kang, Chong Zhang, Zhuang Jiang, and Lei Geng
EGUsphere, https://doi.org/10.5194/egusphere-2024-4165, https://doi.org/10.5194/egusphere-2024-4165, 2025
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This study reveals unexpectedly high levels of particulate nitrite at the Base Camp of Mt. Qomolangma, which overwhelmingly exists in coarse mode, and demonstrates that lofted surface soil contributes to the high levels of nitrite. Once lofted into atmosphere, the soil-derived nitrite is likely to participate in atmospheric reactive nitrogen cycling through gas-particle partitioning or photolysis, leading to the production of HONO, OH and NO and thereby influencing oxidation chemistry.
Tianming Ma, Zhuang Jiang, Minghu Ding, Pengzhen He, Yuansheng Li, Wenqian Zhang, and Lei Geng
The Cryosphere, 18, 4547–4565, https://doi.org/10.5194/tc-18-4547-2024, https://doi.org/10.5194/tc-18-4547-2024, 2024
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We constructed a box model to evaluate the isotope effects of atmosphere–snow water vapor exchange at Dome A, Antarctica. The results show clear and invisible diurnal changes in surface snow isotopes under summer and winter conditions, respectively. The model also predicts that the annual net effects of atmosphere–snow water vapor exchange would be overall enrichments in snow isotopes since the effects in summer appear to be greater than those in winter at the study site.
Yaoming Ma, Zhipeng Xie, Yingying Chen, Shaomin Liu, Tao Che, Ziwei Xu, Lunyu Shang, Xiaobo He, Xianhong Meng, Weiqiang Ma, Baiqing Xu, Huabiao Zhao, Junbo Wang, Guangjian Wu, and Xin Li
Earth Syst. Sci. Data, 16, 3017–3043, https://doi.org/10.5194/essd-16-3017-2024, https://doi.org/10.5194/essd-16-3017-2024, 2024
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Current models and satellites struggle to accurately represent the land–atmosphere (L–A) interactions over the Tibetan Plateau. We present the most extensive compilation of in situ observations to date, comprising 17 years of data on L–A interactions across 12 sites. This quality-assured benchmark dataset provides independent validation to improve models and remote sensing for the region, and it enables new investigations of fine-scale L–A processes and their mechanistic drivers.
Zhuang Jiang, Becky Alexander, Joel Savarino, and Lei Geng
Atmos. Chem. Phys., 24, 4895–4914, https://doi.org/10.5194/acp-24-4895-2024, https://doi.org/10.5194/acp-24-4895-2024, 2024
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Ice-core nitrate could track the past atmospheric NOx and oxidant level, but its interpretation is hampered by the post-depositional processing. In this work, an inverse model was developed and tested against two polar sites and was shown to well reproduce the observed nitrate signals in snow and atmosphere, suggesting that the model can properly correct for the effect of post-depositional processing. This model offers a very useful tool for future studies on ice-core nitrate records.
Shaomin Liu, Ziwei Xu, Tao Che, Xin Li, Tongren Xu, Zhiguo Ren, Yang Zhang, Junlei Tan, Lisheng Song, Ji Zhou, Zhongli Zhu, Xiaofan Yang, Rui Liu, and Yanfei Ma
Earth Syst. Sci. Data, 15, 4959–4981, https://doi.org/10.5194/essd-15-4959-2023, https://doi.org/10.5194/essd-15-4959-2023, 2023
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We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
Koichi Sakaguchi, L. Ruby Leung, Colin M. Zarzycki, Jihyeon Jang, Seth McGinnis, Bryce E. Harrop, William C. Skamarock, Andrew Gettelman, Chun Zhao, William J. Gutowski, Stephen Leak, and Linda Mearns
Geosci. Model Dev., 16, 3029–3081, https://doi.org/10.5194/gmd-16-3029-2023, https://doi.org/10.5194/gmd-16-3029-2023, 2023
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We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique in that it follows a standard protocol designed for coordinated experiments of regional models. We found negligible influence of post-processing on statistical analysis, importance of simulation quality outside of the target region, and computational challenges that our model code faced due to rapidly changing super computer systems.
Hongxia Zhu, Rui Li, Shuping Yang, Chun Zhao, Zhe Jiang, and Chen Huang
Atmos. Chem. Phys., 23, 2421–2437, https://doi.org/10.5194/acp-23-2421-2023, https://doi.org/10.5194/acp-23-2421-2023, 2023
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The impacts of atmospheric dust aerosols and cloud dynamic conditions on precipitation vertical development in southeastern China were studied using multiple satellite observations. It was found that the precipitating drops under dusty conditions grow faster in the middle layer but slower in the upper and lower layers compared with their pristine counterparts. Quantitative estimation of the sensitivity of the precipitation top temperature to the dust aerosol optical depth is also provided.
Huadong Wang, Xueliang Zhang, Pengfeng Xiao, Tao Che, Zhaojun Zheng, Liyun Dai, and Wenbo Luan
The Cryosphere, 17, 33–50, https://doi.org/10.5194/tc-17-33-2023, https://doi.org/10.5194/tc-17-33-2023, 2023
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The geographically and temporally weighted neural network (GTWNN) model is constructed for estimating large-scale daily snow density by integrating satellite, ground, and reanalysis data, which addresses the importance of spatiotemporal heterogeneity and a nonlinear relationship between snow density and impact variables, as well as allows us to understand the spatiotemporal pattern and heterogeneity of snow density in different snow periods and snow cover regions in China from 2013 to 2020.
Hui Guo, Xiaoyan Wang, Zecheng Guo, Gaofeng Zhu, Tao Che, Jian Wang, Xiaodong Huang, Chao Han, and Zhiqi Ouyang
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-229, https://doi.org/10.5194/tc-2022-229, 2022
Revised manuscript not accepted
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Snow phenology is a seasonal pattern in snow cover and snowfall. In this review, we found that during the past 50 years in the Northern Hemisphere, the snow cover end date has shown a significantly advanced change trend. Eurasia contributes more to the snow phenology in the Northern Hemisphere than does North America. Snow phenology is related to climate and atmospheric circulation, and the response to vegetation phenology depends on geographical regions, temperature and precipitation gradients.
Yanzhi Cao, Zhuang Jiang, Becky Alexander, Jihong Cole-Dai, Joel Savarino, Joseph Erbland, and Lei Geng
Atmos. Chem. Phys., 22, 13407–13422, https://doi.org/10.5194/acp-22-13407-2022, https://doi.org/10.5194/acp-22-13407-2022, 2022
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We investigate the potential of ice-core preserved nitrate isotopes as proxies of stratospheric ozone variability by measuring nitrate isotopes in a shallow ice core from the South Pole. The large variability in the snow accumulation rate and its slight increase after the 1970s masked any signals caused by the ozone hole. Moreover, the nitrate oxygen isotope decrease may reflect changes in the atmospheric oxidation environment in the Southern Ocean.
Xueyin Ruan, Chun Zhao, Rahul A. Zaveri, Pengzhen He, Xinming Wang, Jingyuan Shao, and Lei Geng
Geosci. Model Dev., 15, 6143–6164, https://doi.org/10.5194/gmd-15-6143-2022, https://doi.org/10.5194/gmd-15-6143-2022, 2022
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Accurate prediction of aerosol pH in chemical transport models is essential to aerosol modeling. This study examines the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) on aerosol pH predictions and the sensitivities to emissions of nonvolatile cations and NH3, aerosol-phase state assumption, and heterogeneous sulfate production. Temporal evolution of aerosol pH during haze cycles in Beijing and the driving factors are also presented and discussed.
Liyun Dai, Tao Che, Yang Zhang, Zhiguo Ren, Junlei Tan, Meerzhan Akynbekkyzy, Lin Xiao, Shengnan Zhou, Yuna Yan, Yan Liu, Hongyi Li, and Lifu Wang
Earth Syst. Sci. Data, 14, 3509–3530, https://doi.org/10.5194/essd-14-3509-2022, https://doi.org/10.5194/essd-14-3509-2022, 2022
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An Integrated Microwave Radiometry Campaign for Snow (IMCS) was conducted to collect ground-based passive microwave and optical remote-sensing data, snow pit and underlying soil data, and meteorological parameters. The dataset is unique in continuously providing electromagnetic and physical features of snowpack and environment. The dataset is expected to serve the evaluation and development of microwave radiative transfer models and snow process models, along with land surface process models.
Zhuang Jiang, Joel Savarino, Becky Alexander, Joseph Erbland, Jean-Luc Jaffrezo, and Lei Geng
The Cryosphere, 16, 2709–2724, https://doi.org/10.5194/tc-16-2709-2022, https://doi.org/10.5194/tc-16-2709-2022, 2022
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A record of year-round atmospheric nitrate isotopic composition along with snow nitrate isotopic data from Summit, Greenland, revealed apparent enrichments in nitrogen isotopes in snow nitrate compared to atmospheric nitrate, in addition to a relatively smaller degree of changes in oxygen isotopes. The results suggest that at this site post-depositional processing takes effect, which should be taken into account when interpreting ice-core nitrate isotope records.
Yanxing Hu, Tao Che, Liyun Dai, Yu Zhu, Lin Xiao, Jie Deng, and Xin Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-63, https://doi.org/10.5194/essd-2022-63, 2022
Preprint withdrawn
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We propose a data fusion framework based on the random forest regression algorithm to derive a comprehensive snow depth product for the Northern Hemisphere from 1980 to 2019. This new fused snow depth dataset not only provides information about snow depth and its variation over the Northern Hemisphere but also presents potential value for hydrological and water cycle studies related to seasonal snowpacks.
Donghang Shao, Hongyi Li, Jian Wang, Xiaohua Hao, Tao Che, and Wenzheng Ji
Earth Syst. Sci. Data, 14, 795–809, https://doi.org/10.5194/essd-14-795-2022, https://doi.org/10.5194/essd-14-795-2022, 2022
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The temporal series and spatial distribution discontinuity of the existing snow water equivalent (SWE) products in the pan-Arctic region severely restricts the use of SWE data in cryosphere change and climate change studies. Using a ridge regression machine learning algorithm, this study developed a set of spatiotemporally seamless and high-precision SWE products. This product could contribute to the study of cryosphere change and climate change at large spatial scales.
Xiaodong Wang, Chun Zhao, Mingyue Xu, Qiuyan Du, Jianqiu Zheng, Yun Bi, Shengfu Lin, and Yali Luo
Geosci. Model Dev., 15, 199–218, https://doi.org/10.5194/gmd-15-199-2022, https://doi.org/10.5194/gmd-15-199-2022, 2022
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Regional models are widely used to investigate aerosol climatic impacts. However, there are few studies examining the sensitivities of modeling results to regional domain size. In this study, the regional model is used to study the aerosol impacts on the East Asian summer monsoon system and focus on the modeling sensitivities to domain size. This study highlights the important impacts of domain size on regional modeling results of aerosol climatic impacts, which may not be limited to East Asia.
Xiaohua Hao, Guanghui Huang, Tao Che, Wenzheng Ji, Xingliang Sun, Qin Zhao, Hongyu Zhao, Jian Wang, Hongyi Li, and Qian Yang
Earth Syst. Sci. Data, 13, 4711–4726, https://doi.org/10.5194/essd-13-4711-2021, https://doi.org/10.5194/essd-13-4711-2021, 2021
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Long-term snow cover data are not only of importance for climate research. Currently China still lacks a high-quality snow cover extent (SCE) product for climate research. This study develops a multi-level decision tree algorithm for cloud and snow discrimination and gap-filled technique based on AVHRR surface reflectance data. We generate a daily 5 km SCE product across China from 1981 to 2019. It has high accuracy and will serve as baseline data for climate and other applications.
Mingshuai Zhang, Chun Zhao, Yuhan Yang, Qiuyan Du, Yonglin Shen, Shengfu Lin, Dasa Gu, Wenjing Su, and Cheng Liu
Geosci. Model Dev., 14, 6155–6175, https://doi.org/10.5194/gmd-14-6155-2021, https://doi.org/10.5194/gmd-14-6155-2021, 2021
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Biogenic volatile organic compounds (BVOCs) can influence atmospheric chemistry and secondary pollutant formation. This study examines the performance of different versions of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) in modeling BVOCs and ozone and their sensitivities to vegetation distributions over eastern China. The results suggest more accurate vegetation distribution and measurements of BVOC emission fluxes are needed to reduce the uncertainties.
Zhuang Jiang, Becky Alexander, Joel Savarino, Joseph Erbland, and Lei Geng
The Cryosphere, 15, 4207–4220, https://doi.org/10.5194/tc-15-4207-2021, https://doi.org/10.5194/tc-15-4207-2021, 2021
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We used a snow photochemistry model (TRANSITS) to simulate the seasonal nitrate snow profile at Summit, Greenland. Comparisons between model outputs and observations suggest that at Summit post-depositional processing is active and probably dominates the snowpack δ15N seasonality. We also used the model to assess the degree of snow nitrate loss and the consequences in its isotopes at present and in the past, which helps for quantitative interpretations of ice-core nitrate records.
Jiahua Zhang, Lin Liu, Lei Su, and Tao Che
The Cryosphere, 15, 3021–3033, https://doi.org/10.5194/tc-15-3021-2021, https://doi.org/10.5194/tc-15-3021-2021, 2021
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We improve the commonly used GPS-IR algorithm for estimating surface soil moisture in permafrost areas, which does not consider the bias introduced by seasonal surface vertical movement. We propose a three-in-one framework to integrate the GPS-IR observations of surface elevation changes, soil moisture, and snow depth at one site and illustrate it by using a GPS site in the Qinghai–Tibet Plateau. This study is the first to use GPS-IR to measure environmental variables in the Tibetan Plateau.
Zhuang Wang, Cheng Liu, Zhouqing Xie, Qihou Hu, Meinrat O. Andreae, Yunsheng Dong, Chun Zhao, Ting Liu, Yizhi Zhu, Haoran Liu, Chengzhi Xing, Wei Tan, Xiangguang Ji, Jinan Lin, and Jianguo Liu
Atmos. Chem. Phys., 20, 14917–14932, https://doi.org/10.5194/acp-20-14917-2020, https://doi.org/10.5194/acp-20-14917-2020, 2020
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Significant stratification of aerosols was observed in North China. Polluted dust dominated above the PBL, and anthropogenic aerosols prevailed within the PBL, which is mainly driven by meteorological conditions. The key role of the elevated dust is to alter atmospheric thermodynamics and stability, causing the suppression of turbulence exchange and a decrease in PBL height, especially during the dissipation stage, thereby inhibiting dissipation of persistent heavy surface haze pollution.
Stefan Rahimi, Xiaohong Liu, Chun Zhao, Zheng Lu, and Zachary J. Lebo
Atmos. Chem. Phys., 20, 10911–10935, https://doi.org/10.5194/acp-20-10911-2020, https://doi.org/10.5194/acp-20-10911-2020, 2020
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Dark particles emitted to the atmosphere can absorb sunlight and heat the air. As these particles settle, they may darken the surface, especially over snow-covered regions like the Rocky Mountains. This darkening of the surface may lead to changes in snowpack, affecting the local meteorology and hydrology. We seek to evaluate whether these light-absorbing particles more prominently affect this region through their atmospheric presence or their on-snow presence.
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Short summary
We employed the WRF-Chem model to parameterize atmospheric nitrate deposition in snow and evaluate its performance in simulating snow cover, snow depth, and concentrations of dust and nitrate using new observations from northern China. The results generally exhibit reasonable agreement with field observations in northern China, demonstrating the model's capability to simulate snow properties, including concentrations of reservoir species.
We employed the WRF-Chem model to parameterize atmospheric nitrate deposition in snow and...