Assessment of Land Surface Models in a High-Resolution Atmospheric Model during Indian Summer Monsoon
Assessment of the land surface models (LSMs) on monsoon studies over the Indian summer monsoon (ISM) region is essential. In this study, we evaluate the skill of LSMs at 10 km spatial resolution in simulating the 2010 monsoon season. The thermal diffusion scheme (TDS), rapid update cycle (RUC), and...
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description | Assessment of the land surface models (LSMs) on monsoon studies over the Indian summer monsoon (ISM) region is essential. In this study, we evaluate the skill of LSMs at 10 km spatial resolution in simulating the 2010 monsoon season. The thermal diffusion scheme (TDS), rapid update cycle (RUC), and Noah and Noah with multi-parameterization (Noah-MP) LSMs are chosen based on nature of complexity, that is, from simple slab model to multi-parameterization options coupled with the Weather Research and Forecasting (WRF) model. Model results are compared with the available in situ observations and reanalysis fields. The sensitivity of monsoon elements, surface characteristics, and vertical structures to different LSMs is discussed. Our results reveal that the monsoon features are reproduced by WRF model with all LSMs, but with some regional discrepancies. The model simulations with selected LSMs are able to reproduce the broad rainfall patterns, orography-induced rainfall over the Himalayan region, and dry zone over the southern tip of India. The unrealistic precipitation pattern over the equatorial western Indian Ocean is simulated by WRF–LSM-based experiments. The spatial and temporal distributions of top 2-m soil characteristics (soil temperature and soil moisture) are well represented in RUC and Noah-MP LSM-based experiments during the ISM. Results show that the WRF simulations with RUC, Noah, and Noah-MP LSM-based experiments significantly improved the skill of 2-m temperature and moisture compared to TDS (chosen as a base) LSM-based experiments. Furthermore, the simulations with Noah, RUC, and Noah-MP LSMs exhibit minimum error in thermodynamics fields. In case of surface wind speed, TDS LSM performed better compared to other LSM experiments. A significant improvement is noticeable in simulating rainfall by WRF model with Noah, RUC, and Noah-MP LSMs over TDS LSM. Thus, this study emphasis the importance of choosing/improving LSMs for simulating the ISM phenomena in a regional model. |
doi_str_mv | 10.1007/s00024-018-1868-z |
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In this study, we evaluate the skill of LSMs at 10 km spatial resolution in simulating the 2010 monsoon season. The thermal diffusion scheme (TDS), rapid update cycle (RUC), and Noah and Noah with multi-parameterization (Noah-MP) LSMs are chosen based on nature of complexity, that is, from simple slab model to multi-parameterization options coupled with the Weather Research and Forecasting (WRF) model. Model results are compared with the available in situ observations and reanalysis fields. The sensitivity of monsoon elements, surface characteristics, and vertical structures to different LSMs is discussed. Our results reveal that the monsoon features are reproduced by WRF model with all LSMs, but with some regional discrepancies. The model simulations with selected LSMs are able to reproduce the broad rainfall patterns, orography-induced rainfall over the Himalayan region, and dry zone over the southern tip of India. The unrealistic precipitation pattern over the equatorial western Indian Ocean is simulated by WRF–LSM-based experiments. The spatial and temporal distributions of top 2-m soil characteristics (soil temperature and soil moisture) are well represented in RUC and Noah-MP LSM-based experiments during the ISM. Results show that the WRF simulations with RUC, Noah, and Noah-MP LSM-based experiments significantly improved the skill of 2-m temperature and moisture compared to TDS (chosen as a base) LSM-based experiments. Furthermore, the simulations with Noah, RUC, and Noah-MP LSMs exhibit minimum error in thermodynamics fields. In case of surface wind speed, TDS LSM performed better compared to other LSM experiments. A significant improvement is noticeable in simulating rainfall by WRF model with Noah, RUC, and Noah-MP LSMs over TDS LSM. Thus, this study emphasis the importance of choosing/improving LSMs for simulating the ISM phenomena in a regional model.</description><identifier>ISSN: 0033-4553</identifier><identifier>EISSN: 1420-9136</identifier><identifier>DOI: 10.1007/s00024-018-1868-z</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Atmospheric models ; Computer simulation ; Dye dispersion ; Earth and Environmental Science ; Earth Sciences ; Experiments ; Fields ; Geophysics/Geodesy ; Land surface models ; Monsoons ; Orography ; Parameterization ; Precipitation ; Rain ; Rainfall ; Rainfall patterns ; Rainfall simulators ; Resolution ; Simulation ; Soil ; Soil characteristics ; Soil moisture ; Soil temperature ; Spatial discrimination ; Spatial resolution ; Summer ; Summer monsoon ; Surface properties ; Surface wind ; Temperature ; Thermal diffusion ; Weather forecasting ; Wind speed</subject><ispartof>Pure and applied geophysics, 2018-10, Vol.175 (10), p.3671-3696</ispartof><rights>Springer International Publishing AG, part of Springer Nature 2018</rights><rights>Pure and Applied Geophysics is a copyright of Springer, (2018). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a448t-83f11c9a9d98ff2ef09a71b90daaa9bf4ee8401953453f503e4738e940d3cda3</citedby><cites>FETCH-LOGICAL-a448t-83f11c9a9d98ff2ef09a71b90daaa9bf4ee8401953453f503e4738e940d3cda3</cites><orcidid>0000-0002-6194-4561</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00024-018-1868-z$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00024-018-1868-z$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids></links><search><creatorcontrib>Attada, Raju</creatorcontrib><creatorcontrib>Kumar, Prashant</creatorcontrib><creatorcontrib>Dasari, Hari Prasad</creatorcontrib><title>Assessment of Land Surface Models in a High-Resolution Atmospheric Model during Indian Summer Monsoon</title><title>Pure and applied geophysics</title><addtitle>Pure Appl. Geophys</addtitle><description>Assessment of the land surface models (LSMs) on monsoon studies over the Indian summer monsoon (ISM) region is essential. In this study, we evaluate the skill of LSMs at 10 km spatial resolution in simulating the 2010 monsoon season. The thermal diffusion scheme (TDS), rapid update cycle (RUC), and Noah and Noah with multi-parameterization (Noah-MP) LSMs are chosen based on nature of complexity, that is, from simple slab model to multi-parameterization options coupled with the Weather Research and Forecasting (WRF) model. Model results are compared with the available in situ observations and reanalysis fields. The sensitivity of monsoon elements, surface characteristics, and vertical structures to different LSMs is discussed. Our results reveal that the monsoon features are reproduced by WRF model with all LSMs, but with some regional discrepancies. The model simulations with selected LSMs are able to reproduce the broad rainfall patterns, orography-induced rainfall over the Himalayan region, and dry zone over the southern tip of India. The unrealistic precipitation pattern over the equatorial western Indian Ocean is simulated by WRF–LSM-based experiments. The spatial and temporal distributions of top 2-m soil characteristics (soil temperature and soil moisture) are well represented in RUC and Noah-MP LSM-based experiments during the ISM. Results show that the WRF simulations with RUC, Noah, and Noah-MP LSM-based experiments significantly improved the skill of 2-m temperature and moisture compared to TDS (chosen as a base) LSM-based experiments. Furthermore, the simulations with Noah, RUC, and Noah-MP LSMs exhibit minimum error in thermodynamics fields. In case of surface wind speed, TDS LSM performed better compared to other LSM experiments. A significant improvement is noticeable in simulating rainfall by WRF model with Noah, RUC, and Noah-MP LSMs over TDS LSM. Thus, this study emphasis the importance of choosing/improving LSMs for simulating the ISM phenomena in a regional model.</description><subject>Atmospheric models</subject><subject>Computer simulation</subject><subject>Dye dispersion</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Experiments</subject><subject>Fields</subject><subject>Geophysics/Geodesy</subject><subject>Land surface models</subject><subject>Monsoons</subject><subject>Orography</subject><subject>Parameterization</subject><subject>Precipitation</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Rainfall patterns</subject><subject>Rainfall simulators</subject><subject>Resolution</subject><subject>Simulation</subject><subject>Soil</subject><subject>Soil characteristics</subject><subject>Soil moisture</subject><subject>Soil temperature</subject><subject>Spatial discrimination</subject><subject>Spatial resolution</subject><subject>Summer</subject><subject>Summer monsoon</subject><subject>Surface properties</subject><subject>Surface wind</subject><subject>Temperature</subject><subject>Thermal diffusion</subject><subject>Weather forecasting</subject><subject>Wind speed</subject><issn>0033-4553</issn><issn>1420-9136</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kLFOwzAQhi0EEqXwAGyWmA3n2GnssaqAVipCgu6Wm5zbVI0d7GSgT0-qIDEx3XD_95_uI-SewyMHKJ4SAGSSAVeMq5lipwsy4TIDprmYXZIJgBBM5rm4JjcpHQB4UeR6QnCeEqbUoO9ocHRtfUU_--hsifQtVHhMtPbU0mW927MPTOHYd3XwdN41IbV7jHU55mjVx9rv6MpXtfVDR9NgHFY-heBvyZWzx4R3v3NKNi_Pm8WSrd9fV4v5mlkpVceUcJyX2upKK-cydKBtwbcaKmut3jqJqCRwnQuZC5eDQFkIhVpCJcrKiil5GGvbGL56TJ05hD764aLJIJtxlQuuhhQfU2UMKUV0po11Y-O34WDOMs0o0wwyzVmmOQ1MNjKpPX-J8a_5f-gHmi94Rw</recordid><startdate>20181001</startdate><enddate>20181001</enddate><creator>Attada, Raju</creator><creator>Kumar, Prashant</creator><creator>Dasari, Hari Prasad</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TG</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>L7M</scope><scope>M2P</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0002-6194-4561</orcidid></search><sort><creationdate>20181001</creationdate><title>Assessment of Land Surface Models in a High-Resolution Atmospheric Model during Indian Summer Monsoon</title><author>Attada, Raju ; Kumar, Prashant ; Dasari, Hari Prasad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a448t-83f11c9a9d98ff2ef09a71b90daaa9bf4ee8401953453f503e4738e940d3cda3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Atmospheric models</topic><topic>Computer simulation</topic><topic>Dye dispersion</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Experiments</topic><topic>Fields</topic><topic>Geophysics/Geodesy</topic><topic>Land surface models</topic><topic>Monsoons</topic><topic>Orography</topic><topic>Parameterization</topic><topic>Precipitation</topic><topic>Rain</topic><topic>Rainfall</topic><topic>Rainfall patterns</topic><topic>Rainfall simulators</topic><topic>Resolution</topic><topic>Simulation</topic><topic>Soil</topic><topic>Soil characteristics</topic><topic>Soil moisture</topic><topic>Soil temperature</topic><topic>Spatial discrimination</topic><topic>Spatial resolution</topic><topic>Summer</topic><topic>Summer monsoon</topic><topic>Surface properties</topic><topic>Surface wind</topic><topic>Temperature</topic><topic>Thermal diffusion</topic><topic>Weather forecasting</topic><topic>Wind speed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Attada, Raju</creatorcontrib><creatorcontrib>Kumar, Prashant</creatorcontrib><creatorcontrib>Dasari, Hari Prasad</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Pure and applied geophysics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Attada, Raju</au><au>Kumar, Prashant</au><au>Dasari, Hari Prasad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessment of Land Surface Models in a High-Resolution Atmospheric Model during Indian Summer Monsoon</atitle><jtitle>Pure and applied geophysics</jtitle><stitle>Pure Appl. Geophys</stitle><date>2018-10-01</date><risdate>2018</risdate><volume>175</volume><issue>10</issue><spage>3671</spage><epage>3696</epage><pages>3671-3696</pages><issn>0033-4553</issn><eissn>1420-9136</eissn><abstract>Assessment of the land surface models (LSMs) on monsoon studies over the Indian summer monsoon (ISM) region is essential. In this study, we evaluate the skill of LSMs at 10 km spatial resolution in simulating the 2010 monsoon season. The thermal diffusion scheme (TDS), rapid update cycle (RUC), and Noah and Noah with multi-parameterization (Noah-MP) LSMs are chosen based on nature of complexity, that is, from simple slab model to multi-parameterization options coupled with the Weather Research and Forecasting (WRF) model. Model results are compared with the available in situ observations and reanalysis fields. The sensitivity of monsoon elements, surface characteristics, and vertical structures to different LSMs is discussed. Our results reveal that the monsoon features are reproduced by WRF model with all LSMs, but with some regional discrepancies. The model simulations with selected LSMs are able to reproduce the broad rainfall patterns, orography-induced rainfall over the Himalayan region, and dry zone over the southern tip of India. The unrealistic precipitation pattern over the equatorial western Indian Ocean is simulated by WRF–LSM-based experiments. The spatial and temporal distributions of top 2-m soil characteristics (soil temperature and soil moisture) are well represented in RUC and Noah-MP LSM-based experiments during the ISM. Results show that the WRF simulations with RUC, Noah, and Noah-MP LSM-based experiments significantly improved the skill of 2-m temperature and moisture compared to TDS (chosen as a base) LSM-based experiments. Furthermore, the simulations with Noah, RUC, and Noah-MP LSMs exhibit minimum error in thermodynamics fields. In case of surface wind speed, TDS LSM performed better compared to other LSM experiments. A significant improvement is noticeable in simulating rainfall by WRF model with Noah, RUC, and Noah-MP LSMs over TDS LSM. Thus, this study emphasis the importance of choosing/improving LSMs for simulating the ISM phenomena in a regional model.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s00024-018-1868-z</doi><tpages>26</tpages><orcidid>https://orcid.org/0000-0002-6194-4561</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Atmospheric models Computer simulation Dye dispersion Earth and Environmental Science Earth Sciences Experiments Fields Geophysics/Geodesy Land surface models Monsoons Orography Parameterization Precipitation Rain Rainfall Rainfall patterns Rainfall simulators Resolution Simulation Soil Soil characteristics Soil moisture Soil temperature Spatial discrimination Spatial resolution Summer Summer monsoon Surface properties Surface wind Temperature Thermal diffusion Weather forecasting Wind speed |
title | Assessment of Land Surface Models in a High-Resolution Atmospheric Model during Indian Summer Monsoon |
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