WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China
<p>Snow is a key component of the cryosphere and has significant impacts on surface energy balance, hydrology, atmospheric circulation, etc. In addition, numerous studies have indicated that snow impurities, especially nitrate, are sensitive to sunlight and can be photolyzed to emit reactive s...
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Copernicus Publications
2025-02-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/18/651/2025/gmd-18-651-2025.pdf |
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| author | X. Wang X. Wang T. Che T. Che X. Ruan S. Yue S. Yue J. Wang J. Wang C. Zhao C. Zhao C. Zhao L. Geng L. Geng L. Geng |
| author_facet | X. Wang X. Wang T. Che T. Che X. Ruan S. Yue S. Yue J. Wang J. Wang C. Zhao C. Zhao C. Zhao L. Geng L. Geng L. Geng |
| author_sort | X. Wang |
| collection | DOAJ |
| description | <p>Snow is a key component of the cryosphere and has significant impacts on surface energy balance, hydrology, atmospheric circulation, etc. In addition, numerous studies have indicated that snow impurities, especially nitrate, are sensitive to sunlight and can be photolyzed to emit reactive species including NO<span class="inline-formula"><sub>2</sub></span> and HONO, which serve as precursors of O<span class="inline-formula"><sub>3</sub></span> and radicals and disturb the overlying atmospheric chemistry. This makes snow a reservoir of reactive species, and this reservoir is particularly important in remote and pristine regions with limited anthropogenic emissions. The magnitude of snow chemical emissions is also influenced by snow physical properties, including snow depth, density, and concentrations of light-absorbing impurities (e.g., black carbon (BC) and dust). Exploring and elucidating the emissions and atmospheric consequences of the snow-sourced reactive species require a global or regional model with a snow module. Here, we parameterized atmospheric nitrate deposition and its distributions in snow using a regional chemical transport model, i.e., WRF-Chem (Weather Research and Forecasting Model coupled with Chemistry), and evaluated the performance of WRF-Chem in simulating snow cover; snow depth; and BC, dust, and nitrate concentrations with field observations in northern China, which is one of the regions with a dense and prolonged snow cover. In general, the model-simulated spatial variability in nitrate mass concentrations in the top snow layer (hereafter NITS) is consistent with observations. Simulated NITS values in northeast China from December 2017 to March 2018 had a maximum range of 7.11–16.58 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>, minimum range of 0.06–0.21 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>, and 4-month average of 2.72 <span class="inline-formula">±</span> 1.34 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>. In comparison, observed values showed a maximum range of 9.35–33.43 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>, minimum range of 0.09–0.51 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>, and average of 3.74 <span class="inline-formula">±</span> 5.42 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>. The model results show an underestimation especially in regions closes to large cities in northeastern China, most likely due to the underestimation of NO<span class="inline-formula"><sub><i>x</i></sub></span> emissions in these regions. Additionally, nitrate deposition, snowpack accumulation processes, and challenges in capturing fine-scale emission variability may also contribute to the bias. These results illustrate the ability of WRF-Chem to simulate snow properties including concentrations of reservoir species in northern China, and in the future, we will incorporate snow nitrate photolysis in the model, exploring the emissions of snow NO<span class="inline-formula"><sub><i>x</i></sub></span> from nitrate photolysis and the impacts on local and regional atmospheric chemistry and air pollutant transformations.</p> |
| format | Article |
| id | doaj-art-70a09c67dfa84616a4e86ddb40ce6690 |
| institution | Kabale University |
| issn | 1991-959X 1991-9603 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Copernicus Publications |
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| series | Geoscientific Model Development |
| spelling | doaj-art-70a09c67dfa84616a4e86ddb40ce66902025-02-07T06:45:11ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032025-02-011865167010.5194/gmd-18-651-2025WRF-Chem simulations of snow nitrate and other physicochemical properties in northern ChinaX. Wang0X. Wang1T. Che2T. Che3X. Ruan4S. Yue5S. Yue6J. Wang7J. Wang8C. Zhao9C. Zhao10C. Zhao11L. Geng12L. Geng13L. Geng14School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, Anhui, ChinaNational Key Laboratory of Deep Space Exploration, Deep Space Exploration Laboratory, Hefei 230088, Anhui, ChinaKey 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, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, ChinaSchool of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, Anhui, ChinaKey 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, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, ChinaKey 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, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, ChinaSchool of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, Anhui, ChinaNational Key Laboratory of Deep Space Exploration, Deep Space Exploration Laboratory, Hefei 230088, Anhui, ChinaCAS Center for Excellence in Comparative Planetology, University of Science and Technology of China, Hefei 230026, Anhui, ChinaSchool of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, Anhui, ChinaNational Key Laboratory of Deep Space Exploration, Deep Space Exploration Laboratory, Hefei 230088, Anhui, ChinaCAS Center for Excellence in Comparative Planetology, University of Science and Technology of China, Hefei 230026, Anhui, China<p>Snow is a key component of the cryosphere and has significant impacts on surface energy balance, hydrology, atmospheric circulation, etc. In addition, numerous studies have indicated that snow impurities, especially nitrate, are sensitive to sunlight and can be photolyzed to emit reactive species including NO<span class="inline-formula"><sub>2</sub></span> and HONO, which serve as precursors of O<span class="inline-formula"><sub>3</sub></span> and radicals and disturb the overlying atmospheric chemistry. This makes snow a reservoir of reactive species, and this reservoir is particularly important in remote and pristine regions with limited anthropogenic emissions. The magnitude of snow chemical emissions is also influenced by snow physical properties, including snow depth, density, and concentrations of light-absorbing impurities (e.g., black carbon (BC) and dust). Exploring and elucidating the emissions and atmospheric consequences of the snow-sourced reactive species require a global or regional model with a snow module. Here, we parameterized atmospheric nitrate deposition and its distributions in snow using a regional chemical transport model, i.e., WRF-Chem (Weather Research and Forecasting Model coupled with Chemistry), and evaluated the performance of WRF-Chem in simulating snow cover; snow depth; and BC, dust, and nitrate concentrations with field observations in northern China, which is one of the regions with a dense and prolonged snow cover. In general, the model-simulated spatial variability in nitrate mass concentrations in the top snow layer (hereafter NITS) is consistent with observations. Simulated NITS values in northeast China from December 2017 to March 2018 had a maximum range of 7.11–16.58 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>, minimum range of 0.06–0.21 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>, and 4-month average of 2.72 <span class="inline-formula">±</span> 1.34 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>. In comparison, observed values showed a maximum range of 9.35–33.43 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>, minimum range of 0.09–0.51 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>, and average of 3.74 <span class="inline-formula">±</span> 5.42 <span class="inline-formula">µ</span>g g<span class="inline-formula"><sup>−1</sup></span>. The model results show an underestimation especially in regions closes to large cities in northeastern China, most likely due to the underestimation of NO<span class="inline-formula"><sub><i>x</i></sub></span> emissions in these regions. Additionally, nitrate deposition, snowpack accumulation processes, and challenges in capturing fine-scale emission variability may also contribute to the bias. These results illustrate the ability of WRF-Chem to simulate snow properties including concentrations of reservoir species in northern China, and in the future, we will incorporate snow nitrate photolysis in the model, exploring the emissions of snow NO<span class="inline-formula"><sub><i>x</i></sub></span> from nitrate photolysis and the impacts on local and regional atmospheric chemistry and air pollutant transformations.</p>https://gmd.copernicus.org/articles/18/651/2025/gmd-18-651-2025.pdf |
| spellingShingle | X. Wang X. Wang T. Che T. Che X. Ruan S. Yue S. Yue J. Wang J. Wang C. Zhao C. Zhao C. Zhao L. Geng L. Geng L. Geng WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China Geoscientific Model Development |
| title | WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China |
| title_full | WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China |
| title_fullStr | WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China |
| title_full_unstemmed | WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China |
| title_short | WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China |
| title_sort | wrf chem simulations of snow nitrate and other physicochemical properties in northern china |
| url | https://gmd.copernicus.org/articles/18/651/2025/gmd-18-651-2025.pdf |
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