High‐resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America
This study performs high‐spatial‐resolution (12 km) Weather Research and Forecasting (WRF) simulations over a very large domain (7200 km × 6180 km, covering much of North America) to explore changes in mean and extreme precipitation in the mid and late 21st century under Representative Concentration...
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description | This study performs high‐spatial‐resolution (12 km) Weather Research and Forecasting (WRF) simulations over a very large domain (7200 km × 6180 km, covering much of North America) to explore changes in mean and extreme precipitation in the mid and late 21st century under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). We evaluate WRF model performance for a historical simulation and future projections, applying the Community Climate System Model version 4 (CCSM4) as initial and boundary conditions with and without a bias correction. WRF simulations using boundary and initial conditions from both versions of CCSM4 show smaller biases versus evaluation data sets than does CCSM4 over western North America. WRF simulations also improve spatial details of precipitation over much of North America. However, driving the WRF with the bias‐corrected CCSM4 does not always reduce the bias. WRF‐projected changes in precipitation include decreasing intensity over the southwestern United States, increasing intensity over the eastern United Sates and most of Canada, and an increase in the number of days with heavy precipitation over much of North America. Projected precipitation changes are more evident in the late 21st century than the mid 21st century, and they are more evident under RCP 8.5 than under RCP 4.5 in the late 21st century. Uncertainties in the projected changes in precipitation due to different warming scenarios are non‐negligible. Differences in summer precipitation changes between WRF and CCSM4 are significant over most of the United States.
Key Points
WRF adds significant value beyond CCSM4
Bias correction of GCMs does not always reduce model bias
Extreme precipitation is projected to increase |
doi_str_mv | 10.1002/2015EF000304 |
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Key Points
WRF adds significant value beyond CCSM4
Bias correction of GCMs does not always reduce model bias
Extreme precipitation is projected to increase</description><identifier>ISSN: 2328-4277</identifier><identifier>EISSN: 2328-4277</identifier><identifier>DOI: 10.1002/2015EF000304</identifier><language>eng</language><publisher>Hoboken, USA: Wiley Periodicals, Inc</publisher><subject>Bias ; Boundary conditions ; Climate change ; Climate models ; Climate system ; Computer simulation ; dynamic downscaling ; ENVIRONMENTAL SCIENCES ; Extreme weather ; Heavy precipitation ; high‐resolution ; Initial conditions ; North America ; Precipitation ; projection ; R&D ; Research & development ; Simulation ; Statistical analysis ; Studies ; Summer ; Summer precipitation ; Weather forecasting ; Winter</subject><ispartof>Earth's future, 2015-07, Vol.3 (7), p.268-288</ispartof><rights>2015 The Authors. Earth's Future published by Wiley on behalf of the American Geophysical Union.</rights><rights>2015 American Geophysical Union</rights><rights>2015. This work is published under http://creativecommons.org/licenses/by-nc-nd/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-c5436-e9dc6bb04c0863b7110fcc68969d2b34ded752c3ee1a3031b52b810bf1a0dc1c3</citedby><cites>FETCH-LOGICAL-c5436-e9dc6bb04c0863b7110fcc68969d2b34ded752c3ee1a3031b52b810bf1a0dc1c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2F2015EF000304$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2F2015EF000304$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,864,885,1417,11562,27924,27925,45574,45575,46052,46476</link.rule.ids><backlink>$$Uhttps://www.osti.gov/servlets/purl/1212863$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Jiali</creatorcontrib><creatorcontrib>Kotamarthi, Veerabhadra R.</creatorcontrib><creatorcontrib>Argonne National Laboratory (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility (ALCF)</creatorcontrib><title>High‐resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America</title><title>Earth's future</title><description>This study performs high‐spatial‐resolution (12 km) Weather Research and Forecasting (WRF) simulations over a very large domain (7200 km × 6180 km, covering much of North America) to explore changes in mean and extreme precipitation in the mid and late 21st century under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). We evaluate WRF model performance for a historical simulation and future projections, applying the Community Climate System Model version 4 (CCSM4) as initial and boundary conditions with and without a bias correction. WRF simulations using boundary and initial conditions from both versions of CCSM4 show smaller biases versus evaluation data sets than does CCSM4 over western North America. WRF simulations also improve spatial details of precipitation over much of North America. However, driving the WRF with the bias‐corrected CCSM4 does not always reduce the bias. WRF‐projected changes in precipitation include decreasing intensity over the southwestern United States, increasing intensity over the eastern United Sates and most of Canada, and an increase in the number of days with heavy precipitation over much of North America. Projected precipitation changes are more evident in the late 21st century than the mid 21st century, and they are more evident under RCP 8.5 than under RCP 4.5 in the late 21st century. Uncertainties in the projected changes in precipitation due to different warming scenarios are non‐negligible. Differences in summer precipitation changes between WRF and CCSM4 are significant over most of the United States.
Key Points
WRF adds significant value beyond CCSM4
Bias correction of GCMs does not always reduce model bias
Extreme precipitation is projected to increase</description><subject>Bias</subject><subject>Boundary conditions</subject><subject>Climate change</subject><subject>Climate models</subject><subject>Climate system</subject><subject>Computer simulation</subject><subject>dynamic downscaling</subject><subject>ENVIRONMENTAL SCIENCES</subject><subject>Extreme weather</subject><subject>Heavy precipitation</subject><subject>high‐resolution</subject><subject>Initial conditions</subject><subject>North America</subject><subject>Precipitation</subject><subject>projection</subject><subject>R&D</subject><subject>Research & development</subject><subject>Simulation</subject><subject>Statistical analysis</subject><subject>Studies</subject><subject>Summer</subject><subject>Summer precipitation</subject><subject>Weather forecasting</subject><subject>Winter</subject><issn>2328-4277</issn><issn>2328-4277</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp90cFu1DAQBuAIgURVeuMBLLhwYGHGTuLkWFW7FKmCSzlbjj1hvUrsxXaocusj8Iw8CS7LoeLQk8fSN7_0a6rqNcIHBOAfOWCz3QGAgPpZdcYF7zY1l_L5o_lldZHSoRjoJYhGnlXrtfu-_33_K1IK05Jd8MyuXs_O6GlamQ13PpWRLDvGcCDzIBILY_mScUeX9d8d51neE5udZdpbNulMjGPKzJDPS1xZ-EmRfQkx79nlTLHEv6pejHpKdPHvPa--7ba3V9ebm6-fPl9d3mxMU4t2Q7017TBAbaBrxSARYTSm7fq2t3wQtSUrG24EEWoBAoeGDx3CMKIGa9CI8-rNKTek7FQyLpPZm-B9KaOQIy-xBb07odLyx0Ipq9klQ9OkPYUlKZSybetOIi_07X_0EJboSwXFeQ8goUZ4SqFsmq6pmx6Len9SJoaUIo3qGN2s46oQ1MNV1eOrFg4nfucmWp-0aru75bIVfwAcWqJY</recordid><startdate>201507</startdate><enddate>201507</enddate><creator>Wang, Jiali</creator><creator>Kotamarthi, Veerabhadra R.</creator><general>Wiley Periodicals, Inc</general><general>John Wiley & Sons, Inc</general><general>American Geophysical Union (AGU)</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>SOI</scope><scope>7U6</scope><scope>OIOZB</scope><scope>OTOTI</scope></search><sort><creationdate>201507</creationdate><title>High‐resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America</title><author>Wang, Jiali ; Kotamarthi, Veerabhadra R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5436-e9dc6bb04c0863b7110fcc68969d2b34ded752c3ee1a3031b52b810bf1a0dc1c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Bias</topic><topic>Boundary conditions</topic><topic>Climate change</topic><topic>Climate models</topic><topic>Climate system</topic><topic>Computer simulation</topic><topic>dynamic downscaling</topic><topic>ENVIRONMENTAL SCIENCES</topic><topic>Extreme weather</topic><topic>Heavy precipitation</topic><topic>high‐resolution</topic><topic>Initial conditions</topic><topic>North America</topic><topic>Precipitation</topic><topic>projection</topic><topic>R&D</topic><topic>Research & development</topic><topic>Simulation</topic><topic>Statistical analysis</topic><topic>Studies</topic><topic>Summer</topic><topic>Summer precipitation</topic><topic>Weather forecasting</topic><topic>Winter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Jiali</creatorcontrib><creatorcontrib>Kotamarthi, Veerabhadra R.</creatorcontrib><creatorcontrib>Argonne National Laboratory (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility (ALCF)</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</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>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content 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>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>OSTI.GOV - Hybrid</collection><collection>OSTI.GOV</collection><jtitle>Earth's future</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Jiali</au><au>Kotamarthi, Veerabhadra R.</au><aucorp>Argonne National Laboratory (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility (ALCF)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>High‐resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America</atitle><jtitle>Earth's future</jtitle><date>2015-07</date><risdate>2015</risdate><volume>3</volume><issue>7</issue><spage>268</spage><epage>288</epage><pages>268-288</pages><issn>2328-4277</issn><eissn>2328-4277</eissn><abstract>This study performs high‐spatial‐resolution (12 km) Weather Research and Forecasting (WRF) simulations over a very large domain (7200 km × 6180 km, covering much of North America) to explore changes in mean and extreme precipitation in the mid and late 21st century under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). We evaluate WRF model performance for a historical simulation and future projections, applying the Community Climate System Model version 4 (CCSM4) as initial and boundary conditions with and without a bias correction. WRF simulations using boundary and initial conditions from both versions of CCSM4 show smaller biases versus evaluation data sets than does CCSM4 over western North America. WRF simulations also improve spatial details of precipitation over much of North America. However, driving the WRF with the bias‐corrected CCSM4 does not always reduce the bias. WRF‐projected changes in precipitation include decreasing intensity over the southwestern United States, increasing intensity over the eastern United Sates and most of Canada, and an increase in the number of days with heavy precipitation over much of North America. Projected precipitation changes are more evident in the late 21st century than the mid 21st century, and they are more evident under RCP 8.5 than under RCP 4.5 in the late 21st century. Uncertainties in the projected changes in precipitation due to different warming scenarios are non‐negligible. Differences in summer precipitation changes between WRF and CCSM4 are significant over most of the United States.
Key Points
WRF adds significant value beyond CCSM4
Bias correction of GCMs does not always reduce model bias
Extreme precipitation is projected to increase</abstract><cop>Hoboken, USA</cop><pub>Wiley Periodicals, Inc</pub><doi>10.1002/2015EF000304</doi><tpages>21</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Bias Boundary conditions Climate change Climate models Climate system Computer simulation dynamic downscaling ENVIRONMENTAL SCIENCES Extreme weather Heavy precipitation high‐resolution Initial conditions North America Precipitation projection R&D Research & development Simulation Statistical analysis Studies Summer Summer precipitation Weather forecasting Winter |
title | High‐resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America |
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