Improvement in Dust Storm Simulation by Considering Stone Coverage Effects for Stony Deserts in East Asia
Approximately 50% of the Earth's deserts are covered with stony surfaces, not dunes. The stony surfaces often block or diminish mineral dust aerosol emissions through area fraction and roughness element effects. Incorporating these stone coverage effects is crucial for climate and environmental...
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creator | Sekiyama, T. T. Kurosaki, Y. Kajino, M. Ishizuka, M. Buyantogtokh, B. Wu, J. Maki, T. |
description | Approximately 50% of the Earth's deserts are covered with stony surfaces, not dunes. The stony surfaces often block or diminish mineral dust aerosol emissions through area fraction and roughness element effects. Incorporating these stone coverage effects is crucial for climate and environmental modeling research. Based on our field observations, this study combined the stone coverage effects into a dust simulation model for East Asia using two regression formulas and some constants. The double regression scheme assumed that the stone roughness density could be derived from the coarse fragment fraction of the SoilGrids 2.0 data set. According to the data set, the stone coverage is higher in Western Mongolia and Dzungaria and lower in the Chinese Gobi Desert and the Loess Plateau. Consequently, the model reproduced fewer dust aerosols in the higher coverage areas and more in the lower coverage areas. This simulation result was consistent with the World Meteorological Organization's current weather reports and satellite aerosol observations. The improved model reproduced the diversity of soil erodibility and was well balanced in performance statistics. This study is the first successful investigation of stone coverage effects on dust storm simulation using a realistic stone coverage map to the authors' best knowledge.
Plain Language Summary
More than 50% of the Earth's deserts are covered with stones, not dunes. The stony surfaces suppress sand and dust storms in the deserts. Because the mineral dust particles globally influence climate change, investigating the stony surfaces is crucial to climate prediction research. Therefore, we developed a new simulation scheme for sand and dust storms to incorporate the stony surface effects. Formulating the stony surface effects was based on our field observations in East Asia. The global stone map we used was obtained from the SoilGrids 2.0 data set. Our simulation model reproduced fewer dust storms in higher stone coverage areas and more in lower areas. This simulation result was consistent with weather observatory observations in Mongolia and China. Satellite measurements for air pollution also backed up the simulation result. This study is the first successful investigation of the stony surface effects on dust storm simulations using a realistic stone coverage map to the authors' best knowledge.
Key Points
Stony surfaces of drylands significantly affect dust aerosol emissions through area fraction and roughness ele |
doi_str_mv | 10.1029/2022JD037295 |
format | Article |
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Plain Language Summary
More than 50% of the Earth's deserts are covered with stones, not dunes. The stony surfaces suppress sand and dust storms in the deserts. Because the mineral dust particles globally influence climate change, investigating the stony surfaces is crucial to climate prediction research. Therefore, we developed a new simulation scheme for sand and dust storms to incorporate the stony surface effects. Formulating the stony surface effects was based on our field observations in East Asia. The global stone map we used was obtained from the SoilGrids 2.0 data set. Our simulation model reproduced fewer dust storms in higher stone coverage areas and more in lower areas. This simulation result was consistent with weather observatory observations in Mongolia and China. Satellite measurements for air pollution also backed up the simulation result. This study is the first successful investigation of the stony surface effects on dust storm simulations using a realistic stone coverage map to the authors' best knowledge.
Key Points
Stony surfaces of drylands significantly affect dust aerosol emissions through area fraction and roughness element effects
A dust simulation model incorporated the stone coverage effects with an actual soil/stone map
The conversion function from the stone coverage to the stone roughness density was derived from field observations in the Gobi Desert</description><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1029/2022JD037295</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>aerosol modeling ; Aerosol observations ; Aerosols ; Air pollution ; Air pollution measurements ; Atmospheric particulates ; Climate change ; Climate change influences ; Climate models ; Climate prediction ; Constants ; Datasets ; Deserts ; drylands ; Dunes ; Dust ; Dust effects ; dust emission ; Dust particles ; Dust storms ; Earth ; Emissions ; Environment models ; Environmental modeling ; Geophysics ; Modelling ; Roughness ; roughness element ; Sand ; sand saltation ; Satellite observation ; Satellites ; Simulation ; Simulation models ; Soil erodibility ; Soil erosion ; Statistical methods ; Stone ; Storms ; Weather</subject><ispartof>Journal of geophysical research. Atmospheres, 2023-01, Vol.128 (2), p.n/a</ispartof><rights>2023 The Authors.</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a4340-c2acb40f3c71bcfc9ebd2c327c90a133438fbb44e5e97fa22b099f3f4845d4203</citedby><cites>FETCH-LOGICAL-a4340-c2acb40f3c71bcfc9ebd2c327c90a133438fbb44e5e97fa22b099f3f4845d4203</cites><orcidid>0000-0002-3988-0565 ; 0000-0001-9296-4103 ; 0000-0002-9595-0484 ; 0000-0002-7427-1482 ; 0000-0002-1843-4291</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2022JD037295$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2022JD037295$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,1412,27905,27906,45555,45556</link.rule.ids></links><search><creatorcontrib>Sekiyama, T. T.</creatorcontrib><creatorcontrib>Kurosaki, Y.</creatorcontrib><creatorcontrib>Kajino, M.</creatorcontrib><creatorcontrib>Ishizuka, M.</creatorcontrib><creatorcontrib>Buyantogtokh, B.</creatorcontrib><creatorcontrib>Wu, J.</creatorcontrib><creatorcontrib>Maki, T.</creatorcontrib><title>Improvement in Dust Storm Simulation by Considering Stone Coverage Effects for Stony Deserts in East Asia</title><title>Journal of geophysical research. Atmospheres</title><description>Approximately 50% of the Earth's deserts are covered with stony surfaces, not dunes. The stony surfaces often block or diminish mineral dust aerosol emissions through area fraction and roughness element effects. Incorporating these stone coverage effects is crucial for climate and environmental modeling research. Based on our field observations, this study combined the stone coverage effects into a dust simulation model for East Asia using two regression formulas and some constants. The double regression scheme assumed that the stone roughness density could be derived from the coarse fragment fraction of the SoilGrids 2.0 data set. According to the data set, the stone coverage is higher in Western Mongolia and Dzungaria and lower in the Chinese Gobi Desert and the Loess Plateau. Consequently, the model reproduced fewer dust aerosols in the higher coverage areas and more in the lower coverage areas. This simulation result was consistent with the World Meteorological Organization's current weather reports and satellite aerosol observations. The improved model reproduced the diversity of soil erodibility and was well balanced in performance statistics. This study is the first successful investigation of stone coverage effects on dust storm simulation using a realistic stone coverage map to the authors' best knowledge.
Plain Language Summary
More than 50% of the Earth's deserts are covered with stones, not dunes. The stony surfaces suppress sand and dust storms in the deserts. Because the mineral dust particles globally influence climate change, investigating the stony surfaces is crucial to climate prediction research. Therefore, we developed a new simulation scheme for sand and dust storms to incorporate the stony surface effects. Formulating the stony surface effects was based on our field observations in East Asia. The global stone map we used was obtained from the SoilGrids 2.0 data set. Our simulation model reproduced fewer dust storms in higher stone coverage areas and more in lower areas. This simulation result was consistent with weather observatory observations in Mongolia and China. Satellite measurements for air pollution also backed up the simulation result. This study is the first successful investigation of the stony surface effects on dust storm simulations using a realistic stone coverage map to the authors' best knowledge.
Key Points
Stony surfaces of drylands significantly affect dust aerosol emissions through area fraction and roughness element effects
A dust simulation model incorporated the stone coverage effects with an actual soil/stone map
The conversion function from the stone coverage to the stone roughness density was derived from field observations in the Gobi Desert</description><subject>aerosol modeling</subject><subject>Aerosol observations</subject><subject>Aerosols</subject><subject>Air pollution</subject><subject>Air pollution measurements</subject><subject>Atmospheric particulates</subject><subject>Climate change</subject><subject>Climate change influences</subject><subject>Climate models</subject><subject>Climate prediction</subject><subject>Constants</subject><subject>Datasets</subject><subject>Deserts</subject><subject>drylands</subject><subject>Dunes</subject><subject>Dust</subject><subject>Dust effects</subject><subject>dust emission</subject><subject>Dust particles</subject><subject>Dust storms</subject><subject>Earth</subject><subject>Emissions</subject><subject>Environment models</subject><subject>Environmental modeling</subject><subject>Geophysics</subject><subject>Modelling</subject><subject>Roughness</subject><subject>roughness element</subject><subject>Sand</subject><subject>sand saltation</subject><subject>Satellite observation</subject><subject>Satellites</subject><subject>Simulation</subject><subject>Simulation models</subject><subject>Soil erodibility</subject><subject>Soil erosion</subject><subject>Statistical methods</subject><subject>Stone</subject><subject>Storms</subject><subject>Weather</subject><issn>2169-897X</issn><issn>2169-8996</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp9kE1LAzEQhoMoWGpv_oCAV1fztR85lm6tLQXBKnhbsumkpHR3a7Lbsv_e1Ip4ci4zvO_DO8wgdEvJAyVMPjLC2CInPGUyvkADRhMZZVIml79z-nGNRt5vSaiMcBGLAbLzau-aA1RQt9jWOO98i1dt4yq8slW3U61talz2eNLU3q7B2Xpz8msIygGc2gCeGgO69dg07tvqcQ4eXFBC4FSFwLG36gZdGbXzMPrpQ_T-NH2bPEfLl9l8Ml5GSnBBIs2ULgUxXKe01EZLKNdMc5ZqSRTlXPDMlKUQEINMjWKsJFIabkQm4rVghA_R3Tk33PXZgW-LbdO5OqwsWJpIGcuExoG6P1PaNd47MMXe2Uq5vqCkOP2z-PvPgPMzfrQ76P9li8XsNY8zwQn_ArSIdsU</recordid><startdate>20230127</startdate><enddate>20230127</enddate><creator>Sekiyama, T. T.</creator><creator>Kurosaki, Y.</creator><creator>Kajino, M.</creator><creator>Ishizuka, M.</creator><creator>Buyantogtokh, B.</creator><creator>Wu, J.</creator><creator>Maki, T.</creator><general>Blackwell Publishing Ltd</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-3988-0565</orcidid><orcidid>https://orcid.org/0000-0001-9296-4103</orcidid><orcidid>https://orcid.org/0000-0002-9595-0484</orcidid><orcidid>https://orcid.org/0000-0002-7427-1482</orcidid><orcidid>https://orcid.org/0000-0002-1843-4291</orcidid></search><sort><creationdate>20230127</creationdate><title>Improvement in Dust Storm Simulation by Considering Stone Coverage Effects for Stony Deserts in East Asia</title><author>Sekiyama, T. T. ; Kurosaki, Y. ; Kajino, M. ; Ishizuka, M. ; Buyantogtokh, B. ; Wu, J. ; Maki, T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a4340-c2acb40f3c71bcfc9ebd2c327c90a133438fbb44e5e97fa22b099f3f4845d4203</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>aerosol modeling</topic><topic>Aerosol observations</topic><topic>Aerosols</topic><topic>Air pollution</topic><topic>Air pollution measurements</topic><topic>Atmospheric particulates</topic><topic>Climate change</topic><topic>Climate change influences</topic><topic>Climate models</topic><topic>Climate prediction</topic><topic>Constants</topic><topic>Datasets</topic><topic>Deserts</topic><topic>drylands</topic><topic>Dunes</topic><topic>Dust</topic><topic>Dust effects</topic><topic>dust emission</topic><topic>Dust particles</topic><topic>Dust storms</topic><topic>Earth</topic><topic>Emissions</topic><topic>Environment models</topic><topic>Environmental modeling</topic><topic>Geophysics</topic><topic>Modelling</topic><topic>Roughness</topic><topic>roughness element</topic><topic>Sand</topic><topic>sand saltation</topic><topic>Satellite observation</topic><topic>Satellites</topic><topic>Simulation</topic><topic>Simulation models</topic><topic>Soil erodibility</topic><topic>Soil erosion</topic><topic>Statistical methods</topic><topic>Stone</topic><topic>Storms</topic><topic>Weather</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sekiyama, T. T.</creatorcontrib><creatorcontrib>Kurosaki, Y.</creatorcontrib><creatorcontrib>Kajino, M.</creatorcontrib><creatorcontrib>Ishizuka, M.</creatorcontrib><creatorcontrib>Buyantogtokh, B.</creatorcontrib><creatorcontrib>Wu, J.</creatorcontrib><creatorcontrib>Maki, T.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Free Content</collection><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Journal of geophysical research. Atmospheres</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sekiyama, T. T.</au><au>Kurosaki, Y.</au><au>Kajino, M.</au><au>Ishizuka, M.</au><au>Buyantogtokh, B.</au><au>Wu, J.</au><au>Maki, T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Improvement in Dust Storm Simulation by Considering Stone Coverage Effects for Stony Deserts in East Asia</atitle><jtitle>Journal of geophysical research. Atmospheres</jtitle><date>2023-01-27</date><risdate>2023</risdate><volume>128</volume><issue>2</issue><epage>n/a</epage><issn>2169-897X</issn><eissn>2169-8996</eissn><abstract>Approximately 50% of the Earth's deserts are covered with stony surfaces, not dunes. The stony surfaces often block or diminish mineral dust aerosol emissions through area fraction and roughness element effects. Incorporating these stone coverage effects is crucial for climate and environmental modeling research. Based on our field observations, this study combined the stone coverage effects into a dust simulation model for East Asia using two regression formulas and some constants. The double regression scheme assumed that the stone roughness density could be derived from the coarse fragment fraction of the SoilGrids 2.0 data set. According to the data set, the stone coverage is higher in Western Mongolia and Dzungaria and lower in the Chinese Gobi Desert and the Loess Plateau. Consequently, the model reproduced fewer dust aerosols in the higher coverage areas and more in the lower coverage areas. This simulation result was consistent with the World Meteorological Organization's current weather reports and satellite aerosol observations. The improved model reproduced the diversity of soil erodibility and was well balanced in performance statistics. This study is the first successful investigation of stone coverage effects on dust storm simulation using a realistic stone coverage map to the authors' best knowledge.
Plain Language Summary
More than 50% of the Earth's deserts are covered with stones, not dunes. The stony surfaces suppress sand and dust storms in the deserts. Because the mineral dust particles globally influence climate change, investigating the stony surfaces is crucial to climate prediction research. Therefore, we developed a new simulation scheme for sand and dust storms to incorporate the stony surface effects. Formulating the stony surface effects was based on our field observations in East Asia. The global stone map we used was obtained from the SoilGrids 2.0 data set. Our simulation model reproduced fewer dust storms in higher stone coverage areas and more in lower areas. This simulation result was consistent with weather observatory observations in Mongolia and China. Satellite measurements for air pollution also backed up the simulation result. This study is the first successful investigation of the stony surface effects on dust storm simulations using a realistic stone coverage map to the authors' best knowledge.
Key Points
Stony surfaces of drylands significantly affect dust aerosol emissions through area fraction and roughness element effects
A dust simulation model incorporated the stone coverage effects with an actual soil/stone map
The conversion function from the stone coverage to the stone roughness density was derived from field observations in the Gobi Desert</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2022JD037295</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0002-3988-0565</orcidid><orcidid>https://orcid.org/0000-0001-9296-4103</orcidid><orcidid>https://orcid.org/0000-0002-9595-0484</orcidid><orcidid>https://orcid.org/0000-0002-7427-1482</orcidid><orcidid>https://orcid.org/0000-0002-1843-4291</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | aerosol modeling Aerosol observations Aerosols Air pollution Air pollution measurements Atmospheric particulates Climate change Climate change influences Climate models Climate prediction Constants Datasets Deserts drylands Dunes Dust Dust effects dust emission Dust particles Dust storms Earth Emissions Environment models Environmental modeling Geophysics Modelling Roughness roughness element Sand sand saltation Satellite observation Satellites Simulation Simulation models Soil erodibility Soil erosion Statistical methods Stone Storms Weather |
title | Improvement in Dust Storm Simulation by Considering Stone Coverage Effects for Stony Deserts in East Asia |
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