Extreme Precipitation Spatial Analog: In Search of an Alternative Approach for Future Extreme Precipitation in Urban Hydrological Studies
In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future p...
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description | In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. Results show that future 3-h and 30-day rainfall in Chicago will be similar to historical rainfall from Memphis, TN and Springfield, IL, respectively. This indicates that the spatial analog is potentially useful, but highlights the fact that the analogs may depend on the duration of the rainfall of interest. |
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The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. Results show that future 3-h and 30-day rainfall in Chicago will be similar to historical rainfall from Memphis, TN and Springfield, IL, respectively. This indicates that the spatial analog is potentially useful, but highlights the fact that the analogs may depend on the duration of the rainfall of interest.</description><identifier>ISSN: 2073-4441</identifier><identifier>EISSN: 2073-4441</identifier><identifier>DOI: 10.3390/w11051032</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Analogs ; Analysis ; Bias ; Climate change ; Climate models ; Climatic changes ; Design ; Environmental assessment ; Estimates ; Flood damage ; General circulation models ; Hydraulics ; Hydrology ; Infrastructure ; Precipitation ; Rain and rainfall ; Rainfall ; Regional analysis ; Simulation ; Simulation methods ; Storms ; Stormwater management ; Urban areas</subject><ispartof>Water (Basel), 2019-05, Vol.11 (5), p.1032</ispartof><rights>COPYRIGHT 2019 MDPI AG</rights><rights>2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 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-c331t-4982aa420bcef6976c5fc5f62e7a159cce816dae471ac8c28444049e2cb93b0c3</citedby><cites>FETCH-LOGICAL-c331t-4982aa420bcef6976c5fc5f62e7a159cce816dae471ac8c28444049e2cb93b0c3</cites><orcidid>0000-0003-2674-3382 ; 0000-0002-4200-8233 ; 0000-0002-7579-0030</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><creatorcontrib>Wang, Ariel</creatorcontrib><creatorcontrib>Dominguez, Francina</creatorcontrib><creatorcontrib>Schmidt, Arthur</creatorcontrib><title>Extreme Precipitation Spatial Analog: In Search of an Alternative Approach for Future Extreme Precipitation in Urban Hydrological Studies</title><title>Water (Basel)</title><description>In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. 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Dominguez, Francina ; Schmidt, Arthur</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-4982aa420bcef6976c5fc5f62e7a159cce816dae471ac8c28444049e2cb93b0c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Analogs</topic><topic>Analysis</topic><topic>Bias</topic><topic>Climate change</topic><topic>Climate models</topic><topic>Climatic changes</topic><topic>Design</topic><topic>Environmental assessment</topic><topic>Estimates</topic><topic>Flood damage</topic><topic>General circulation models</topic><topic>Hydraulics</topic><topic>Hydrology</topic><topic>Infrastructure</topic><topic>Precipitation</topic><topic>Rain and rainfall</topic><topic>Rainfall</topic><topic>Regional analysis</topic><topic>Simulation</topic><topic>Simulation methods</topic><topic>Storms</topic><topic>Stormwater management</topic><topic>Urban areas</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Ariel</creatorcontrib><creatorcontrib>Dominguez, Francina</creatorcontrib><creatorcontrib>Schmidt, Arthur</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</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><jtitle>Water (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Ariel</au><au>Dominguez, Francina</au><au>Schmidt, Arthur</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Extreme Precipitation Spatial Analog: In Search of an Alternative Approach for Future Extreme Precipitation in Urban Hydrological Studies</atitle><jtitle>Water (Basel)</jtitle><date>2019-05-01</date><risdate>2019</risdate><volume>11</volume><issue>5</issue><spage>1032</spage><pages>1032-</pages><issn>2073-4441</issn><eissn>2073-4441</eissn><abstract>In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. Results show that future 3-h and 30-day rainfall in Chicago will be similar to historical rainfall from Memphis, TN and Springfield, IL, respectively. This indicates that the spatial analog is potentially useful, but highlights the fact that the analogs may depend on the duration of the rainfall of interest.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/w11051032</doi><orcidid>https://orcid.org/0000-0003-2674-3382</orcidid><orcidid>https://orcid.org/0000-0002-4200-8233</orcidid><orcidid>https://orcid.org/0000-0002-7579-0030</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analogs Analysis Bias Climate change Climate models Climatic changes Design Environmental assessment Estimates Flood damage General circulation models Hydraulics Hydrology Infrastructure Precipitation Rain and rainfall Rainfall Regional analysis Simulation Simulation methods Storms Stormwater management Urban areas |
title | Extreme Precipitation Spatial Analog: In Search of an Alternative Approach for Future Extreme Precipitation in Urban Hydrological Studies |
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