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Evaluation of summer precipitation over Far East Asia and South Korea simulated by multiple regional climate models
The evaluation of climate model performance is necessary to enhance the reliability of available models. Recently, the interest in the added value has been increasing due to the continued enhancement of the horizontal model resolution for dynamical downscaling. We have examined the simulation perfor...
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| Published in: | International journal of climatology 2020-03, Vol.40 (4), p.2270-2284 |
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| Main Authors: | , , , , , , , , |
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| container_title | International journal of climatology |
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| creator | Park, Changyong Cha, Dong‐Hyun Kim, Gayoung Lee, Gil Lee, Dong‐Kyou Suh, Myoung‐Seok Hong, Song‐You Ahn, Joong‐Bae Min, Seung‐Ki |
| description | The evaluation of climate model performance is necessary to enhance the reliability of available models. Recently, the interest in the added value has been increasing due to the continued enhancement of the horizontal model resolution for dynamical downscaling. We have examined the simulation performance of regional climate models (RCMs) forced by two global climate models (GCMs) for summer precipitation over Far East Asia and South Korea on the basis of spatial resolution improvement. In terms of model resolution, coarse‐resolution RCMs present limitations, whilst high‐resolution RCMs offer the added value as revealed by several performance evaluations. RCMs forced by HadGEM2‐AO estimated smaller summer precipitation over South Korea than those observed, whereas RCMs forced by MPI‐ESM‐LR presented a wet bias. Here, moderate‐heavy rain in RCMs forced by HadGEM2‐AO and light‐moderate rain in RCMs forced by MPI‐ESM‐LR were found to lead to dry and wet biases, respectively.
Spatial distributions of summer precipitation climatology: (a, b) APHRODITE, (c–f) biases of GCMs, and (g–i) biases of MMEs of RCMs, and inter‐model agreements for simulated data sets over Far East Asia. The area‐averaged biases of Far East Asia and South Korea are expressed at the bottom of each panel. Stippling represents areas where all RCMs have the same bias sign. |
| doi_str_mv | 10.1002/joc.6331 |
| format | article |
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Spatial distributions of summer precipitation climatology: (a, b) APHRODITE, (c–f) biases of GCMs, and (g–i) biases of MMEs of RCMs, and inter‐model agreements for simulated data sets over Far East Asia. The area‐averaged biases of Far East Asia and South Korea are expressed at the bottom of each panel. Stippling represents areas where all RCMs have the same bias sign.</description><identifier>ISSN: 0899-8418</identifier><identifier>EISSN: 1097-0088</identifier><identifier>DOI: 10.1002/joc.6331</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>added value ; Atmospheric precipitations ; Climate ; Climate models ; Computer simulation ; Far East Asia ; Global climate ; Global climate models ; Heavy rainfall ; model evaluation ; Performance evaluation ; Precipitation ; Rain ; Regional analysis ; regional climate model ; Regional climate models ; Regional climates ; Reliability analysis ; Resolution ; South Korea ; Spatial discrimination ; Spatial resolution ; Summer ; Summer climates ; Summer precipitation</subject><ispartof>International journal of climatology, 2020-03, Vol.40 (4), p.2270-2284</ispartof><rights>2019 Royal Meteorological Society</rights><rights>2020 Royal Meteorological Society</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2931-264bca54bd31f2d2b9ef96a9b899efe8c626e0723dde065289ed69f3834a80e33</citedby><cites>FETCH-LOGICAL-c2931-264bca54bd31f2d2b9ef96a9b899efe8c626e0723dde065289ed69f3834a80e33</cites><orcidid>0000-0002-6749-010X ; 0000-0001-6958-2801 ; 0000-0001-5053-6741</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjoc.6331$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjoc.6331$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>315,786,790,27957,27958,50923,51032</link.rule.ids></links><search><creatorcontrib>Park, Changyong</creatorcontrib><creatorcontrib>Cha, Dong‐Hyun</creatorcontrib><creatorcontrib>Kim, Gayoung</creatorcontrib><creatorcontrib>Lee, Gil</creatorcontrib><creatorcontrib>Lee, Dong‐Kyou</creatorcontrib><creatorcontrib>Suh, Myoung‐Seok</creatorcontrib><creatorcontrib>Hong, Song‐You</creatorcontrib><creatorcontrib>Ahn, Joong‐Bae</creatorcontrib><creatorcontrib>Min, Seung‐Ki</creatorcontrib><title>Evaluation of summer precipitation over Far East Asia and South Korea simulated by multiple regional climate models</title><title>International journal of climatology</title><description>The evaluation of climate model performance is necessary to enhance the reliability of available models. Recently, the interest in the added value has been increasing due to the continued enhancement of the horizontal model resolution for dynamical downscaling. We have examined the simulation performance of regional climate models (RCMs) forced by two global climate models (GCMs) for summer precipitation over Far East Asia and South Korea on the basis of spatial resolution improvement. In terms of model resolution, coarse‐resolution RCMs present limitations, whilst high‐resolution RCMs offer the added value as revealed by several performance evaluations. RCMs forced by HadGEM2‐AO estimated smaller summer precipitation over South Korea than those observed, whereas RCMs forced by MPI‐ESM‐LR presented a wet bias. Here, moderate‐heavy rain in RCMs forced by HadGEM2‐AO and light‐moderate rain in RCMs forced by MPI‐ESM‐LR were found to lead to dry and wet biases, respectively.
Spatial distributions of summer precipitation climatology: (a, b) APHRODITE, (c–f) biases of GCMs, and (g–i) biases of MMEs of RCMs, and inter‐model agreements for simulated data sets over Far East Asia. The area‐averaged biases of Far East Asia and South Korea are expressed at the bottom of each panel. Stippling represents areas where all RCMs have the same bias sign.</description><subject>added value</subject><subject>Atmospheric precipitations</subject><subject>Climate</subject><subject>Climate models</subject><subject>Computer simulation</subject><subject>Far East Asia</subject><subject>Global climate</subject><subject>Global climate models</subject><subject>Heavy rainfall</subject><subject>model evaluation</subject><subject>Performance evaluation</subject><subject>Precipitation</subject><subject>Rain</subject><subject>Regional analysis</subject><subject>regional climate model</subject><subject>Regional climate models</subject><subject>Regional climates</subject><subject>Reliability analysis</subject><subject>Resolution</subject><subject>South Korea</subject><subject>Spatial discrimination</subject><subject>Spatial resolution</subject><subject>Summer</subject><subject>Summer climates</subject><subject>Summer precipitation</subject><issn>0899-8418</issn><issn>1097-0088</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp1kE1PAjEQhhujiYgm_oQmXrws9gNKeyQE_CLhoJ433XZWS7p0bXcx_HuLcPU0k5nnnbzzInRLyYgSwh42wYwE5_QMDShR04IQKc_RgEilCjmm8hJdpbQhhChFxQClxU77XncubHGoceqbBiJuIxjXuu403-XRUke80KnDs-Q01luL30LffeHXEEHj5Jre6w4srvY4t51rPeAIn1mvPTbeNXmLm2DBp2t0UWuf4OZUh-hjuXifPxWr9ePzfLYqDFOcFkyMK6Mn48pyWjPLKgW1ElpV-RWoQRrBBJAp49YCERMmFVihai75WEsCnA_R3fFuG8N3D6krN6GP2U8qGc86rnIembo_UiaGlCLUZRuz27gvKSkPkWaVKQ-RZrQ4oj_Ow_5frnxZz__4X1oqeM0</recordid><startdate>20200330</startdate><enddate>20200330</enddate><creator>Park, Changyong</creator><creator>Cha, Dong‐Hyun</creator><creator>Kim, Gayoung</creator><creator>Lee, Gil</creator><creator>Lee, Dong‐Kyou</creator><creator>Suh, Myoung‐Seok</creator><creator>Hong, Song‐You</creator><creator>Ahn, Joong‐Bae</creator><creator>Min, Seung‐Ki</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0002-6749-010X</orcidid><orcidid>https://orcid.org/0000-0001-6958-2801</orcidid><orcidid>https://orcid.org/0000-0001-5053-6741</orcidid></search><sort><creationdate>20200330</creationdate><title>Evaluation of summer precipitation over Far East Asia and South Korea simulated by multiple regional climate models</title><author>Park, Changyong ; Cha, Dong‐Hyun ; Kim, Gayoung ; Lee, Gil ; Lee, Dong‐Kyou ; Suh, Myoung‐Seok ; Hong, Song‐You ; Ahn, Joong‐Bae ; Min, Seung‐Ki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2931-264bca54bd31f2d2b9ef96a9b899efe8c626e0723dde065289ed69f3834a80e33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>added value</topic><topic>Atmospheric precipitations</topic><topic>Climate</topic><topic>Climate models</topic><topic>Computer simulation</topic><topic>Far East Asia</topic><topic>Global climate</topic><topic>Global climate models</topic><topic>Heavy rainfall</topic><topic>model evaluation</topic><topic>Performance evaluation</topic><topic>Precipitation</topic><topic>Rain</topic><topic>Regional analysis</topic><topic>regional climate model</topic><topic>Regional climate models</topic><topic>Regional climates</topic><topic>Reliability analysis</topic><topic>Resolution</topic><topic>South Korea</topic><topic>Spatial discrimination</topic><topic>Spatial resolution</topic><topic>Summer</topic><topic>Summer climates</topic><topic>Summer precipitation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Park, Changyong</creatorcontrib><creatorcontrib>Cha, Dong‐Hyun</creatorcontrib><creatorcontrib>Kim, Gayoung</creatorcontrib><creatorcontrib>Lee, Gil</creatorcontrib><creatorcontrib>Lee, Dong‐Kyou</creatorcontrib><creatorcontrib>Suh, Myoung‐Seok</creatorcontrib><creatorcontrib>Hong, Song‐You</creatorcontrib><creatorcontrib>Ahn, Joong‐Bae</creatorcontrib><creatorcontrib>Min, Seung‐Ki</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>International journal of climatology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Park, Changyong</au><au>Cha, Dong‐Hyun</au><au>Kim, Gayoung</au><au>Lee, Gil</au><au>Lee, Dong‐Kyou</au><au>Suh, Myoung‐Seok</au><au>Hong, Song‐You</au><au>Ahn, Joong‐Bae</au><au>Min, Seung‐Ki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of summer precipitation over Far East Asia and South Korea simulated by multiple regional climate models</atitle><jtitle>International journal of climatology</jtitle><date>2020-03-30</date><risdate>2020</risdate><volume>40</volume><issue>4</issue><spage>2270</spage><epage>2284</epage><pages>2270-2284</pages><issn>0899-8418</issn><eissn>1097-0088</eissn><notes>Funding information</notes><notes>Korea Meteorological Administration Research and Development, Grant/Award Number: KMI 2018‐03310</notes><abstract>The evaluation of climate model performance is necessary to enhance the reliability of available models. Recently, the interest in the added value has been increasing due to the continued enhancement of the horizontal model resolution for dynamical downscaling. We have examined the simulation performance of regional climate models (RCMs) forced by two global climate models (GCMs) for summer precipitation over Far East Asia and South Korea on the basis of spatial resolution improvement. In terms of model resolution, coarse‐resolution RCMs present limitations, whilst high‐resolution RCMs offer the added value as revealed by several performance evaluations. RCMs forced by HadGEM2‐AO estimated smaller summer precipitation over South Korea than those observed, whereas RCMs forced by MPI‐ESM‐LR presented a wet bias. Here, moderate‐heavy rain in RCMs forced by HadGEM2‐AO and light‐moderate rain in RCMs forced by MPI‐ESM‐LR were found to lead to dry and wet biases, respectively.
Spatial distributions of summer precipitation climatology: (a, b) APHRODITE, (c–f) biases of GCMs, and (g–i) biases of MMEs of RCMs, and inter‐model agreements for simulated data sets over Far East Asia. The area‐averaged biases of Far East Asia and South Korea are expressed at the bottom of each panel. Stippling represents areas where all RCMs have the same bias sign.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/joc.6331</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-6749-010X</orcidid><orcidid>https://orcid.org/0000-0001-6958-2801</orcidid><orcidid>https://orcid.org/0000-0001-5053-6741</orcidid></addata></record> |
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| subjects | added value Atmospheric precipitations Climate Climate models Computer simulation Far East Asia Global climate Global climate models Heavy rainfall model evaluation Performance evaluation Precipitation Rain Regional analysis regional climate model Regional climate models Regional climates Reliability analysis Resolution South Korea Spatial discrimination Spatial resolution Summer Summer climates Summer precipitation |
| title | Evaluation of summer precipitation over Far East Asia and South Korea simulated by multiple regional climate models |
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