Characterizing and Modeling Temporal and Spatial Trends in Rainfall Extremes
A hierarchical spatial model for daily rainfall extremes that characterizes their temporal variation due to interannual climatic forcing as well as their spatial pattern is proposed. The model treats the parameters of at-site probability distributions for rainfall extremes as “data” that are likely...
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Veröffentlicht in: | Journal of hydrometeorology 2009-02, Vol.10 (1), p.241-253 |
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creator | Aryal, Santosh K. Bates, Bryson C. Campbell, Edward P. Li, Yun Palmer, Mark J. Viney, Neil R. |
description | A hierarchical spatial model for daily rainfall extremes that characterizes their temporal variation due to interannual climatic forcing as well as their spatial pattern is proposed. The model treats the parameters of at-site probability distributions for rainfall extremes as “data” that are likely to be spatially correlated and driven by atmospheric forcing. The method is applied to daily rainfall extremes for summer and winter half years over the Swan–Avon River basin in Western Australia. Two techniques for the characterization of at-site extremes—peaks-over-threshold (POT) analysis and the generalized extreme value (GEV) distribution—and three climatic drivers—the El Niño–Southern Oscillation as measured by the Southern Oscillation index (SOI), the Southern Hemisphere annular mode as measured by an Antarctic Oscillation index (AOI), and solar irradiance (SI)—were considered. The POT analysis of at-site extremes revealed that at-site thresholds lacked spatial coherence, making it difficult to determine a smooth spatial surface for the threshold parameter. In contrast, the GEV-based analysis indicated smooth spatial patterns in daily rainfall extremes that are consistent with the predominant orientation of storm tracks over the study area and the presence of a coastal escarpment near the western edge of the basin. It also indicated a linkage between temporal trends in daily rainfall extremes and those of the SOI and AOI. By applying the spatial models to winter and summer extreme rainfalls separately, an apparent increasing trend in return levels of summer rainfall to the northwest and decreasing trends in return levels of winter rainfall to the southwest of the region are found. |
doi_str_mv | 10.1175/2008JHM1007.1 |
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The model treats the parameters of at-site probability distributions for rainfall extremes as “data” that are likely to be spatially correlated and driven by atmospheric forcing. The method is applied to daily rainfall extremes for summer and winter half years over the Swan–Avon River basin in Western Australia. Two techniques for the characterization of at-site extremes—peaks-over-threshold (POT) analysis and the generalized extreme value (GEV) distribution—and three climatic drivers—the El Niño–Southern Oscillation as measured by the Southern Oscillation index (SOI), the Southern Hemisphere annular mode as measured by an Antarctic Oscillation index (AOI), and solar irradiance (SI)—were considered. The POT analysis of at-site extremes revealed that at-site thresholds lacked spatial coherence, making it difficult to determine a smooth spatial surface for the threshold parameter. In contrast, the GEV-based analysis indicated smooth spatial patterns in daily rainfall extremes that are consistent with the predominant orientation of storm tracks over the study area and the presence of a coastal escarpment near the western edge of the basin. It also indicated a linkage between temporal trends in daily rainfall extremes and those of the SOI and AOI. By applying the spatial models to winter and summer extreme rainfalls separately, an apparent increasing trend in return levels of summer rainfall to the northwest and decreasing trends in return levels of winter rainfall to the southwest of the region are found.</description><identifier>ISSN: 1525-755X</identifier><identifier>EISSN: 1525-7541</identifier><identifier>DOI: 10.1175/2008JHM1007.1</identifier><language>eng</language><publisher>American Meteorological Society</publisher><subject>Climate change ; Climate models ; Floods ; Modeling ; Rain ; River basins ; Seasons ; Spatial models ; Summer ; Winter</subject><ispartof>Journal of hydrometeorology, 2009-02, Vol.10 (1), p.241-253</ispartof><rights>2009 American Meteorological Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c329t-d24c5d396d590ef7e3231a36ee0425f8102306b97c9fb046d030542f40c336353</citedby><cites>FETCH-LOGICAL-c329t-d24c5d396d590ef7e3231a36ee0425f8102306b97c9fb046d030542f40c336353</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/24911966$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/24911966$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,803,3681,27924,27925,58017,58250</link.rule.ids></links><search><creatorcontrib>Aryal, Santosh K.</creatorcontrib><creatorcontrib>Bates, Bryson C.</creatorcontrib><creatorcontrib>Campbell, Edward P.</creatorcontrib><creatorcontrib>Li, Yun</creatorcontrib><creatorcontrib>Palmer, Mark J.</creatorcontrib><creatorcontrib>Viney, Neil R.</creatorcontrib><title>Characterizing and Modeling Temporal and Spatial Trends in Rainfall Extremes</title><title>Journal of hydrometeorology</title><description>A hierarchical spatial model for daily rainfall extremes that characterizes their temporal variation due to interannual climatic forcing as well as their spatial pattern is proposed. The model treats the parameters of at-site probability distributions for rainfall extremes as “data” that are likely to be spatially correlated and driven by atmospheric forcing. The method is applied to daily rainfall extremes for summer and winter half years over the Swan–Avon River basin in Western Australia. Two techniques for the characterization of at-site extremes—peaks-over-threshold (POT) analysis and the generalized extreme value (GEV) distribution—and three climatic drivers—the El Niño–Southern Oscillation as measured by the Southern Oscillation index (SOI), the Southern Hemisphere annular mode as measured by an Antarctic Oscillation index (AOI), and solar irradiance (SI)—were considered. The POT analysis of at-site extremes revealed that at-site thresholds lacked spatial coherence, making it difficult to determine a smooth spatial surface for the threshold parameter. In contrast, the GEV-based analysis indicated smooth spatial patterns in daily rainfall extremes that are consistent with the predominant orientation of storm tracks over the study area and the presence of a coastal escarpment near the western edge of the basin. It also indicated a linkage between temporal trends in daily rainfall extremes and those of the SOI and AOI. By applying the spatial models to winter and summer extreme rainfalls separately, an apparent increasing trend in return levels of summer rainfall to the northwest and decreasing trends in return levels of winter rainfall to the southwest of the region are found.</description><subject>Climate change</subject><subject>Climate models</subject><subject>Floods</subject><subject>Modeling</subject><subject>Rain</subject><subject>River basins</subject><subject>Seasons</subject><subject>Spatial models</subject><subject>Summer</subject><subject>Winter</subject><issn>1525-755X</issn><issn>1525-7541</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><recordid>eNpNkEtLAzEUhYMoWKtLl8Ks3E29ec5kKUWt0iJoBXchTe7olHmZTEH99U6tFFf3nMPHXXyEnFOYUJrJKwaQP8wWFCCb0AMyopLJNJOCHu6zfD0mJzGuAUBomo_IfPpug3U9hvK7bN4S2_hk0XqstmWJddcGW_2uz53tyyEvAzY-JmWTPNmyKWxVJTeffcAa4yk5GnrEs787Ji-3N8vpLJ0_3t1Pr-ep40z3qWfCSc-18lIDFhlyxqnlChEEk0VOgXFQK505XaxAKA8cpGCFAMe54pKPyeXubxfajw3G3tRldFhVtsF2Ew0DlamcqQFMd6ALbYwBC9OFsrbhy1AwW2fmnzNDB_5ix69j34Y9zAZXVCvFfwDgVmcU</recordid><startdate>20090201</startdate><enddate>20090201</enddate><creator>Aryal, Santosh K.</creator><creator>Bates, Bryson C.</creator><creator>Campbell, Edward P.</creator><creator>Li, Yun</creator><creator>Palmer, Mark J.</creator><creator>Viney, Neil R.</creator><general>American Meteorological Society</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope></search><sort><creationdate>20090201</creationdate><title>Characterizing and Modeling Temporal and Spatial Trends in Rainfall Extremes</title><author>Aryal, Santosh K. ; Bates, Bryson C. ; Campbell, Edward P. ; Li, Yun ; Palmer, Mark J. ; Viney, Neil R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c329t-d24c5d396d590ef7e3231a36ee0425f8102306b97c9fb046d030542f40c336353</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Climate change</topic><topic>Climate models</topic><topic>Floods</topic><topic>Modeling</topic><topic>Rain</topic><topic>River basins</topic><topic>Seasons</topic><topic>Spatial models</topic><topic>Summer</topic><topic>Winter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aryal, Santosh K.</creatorcontrib><creatorcontrib>Bates, Bryson C.</creatorcontrib><creatorcontrib>Campbell, Edward P.</creatorcontrib><creatorcontrib>Li, Yun</creatorcontrib><creatorcontrib>Palmer, Mark J.</creatorcontrib><creatorcontrib>Viney, Neil R.</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</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>Journal of hydrometeorology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aryal, Santosh K.</au><au>Bates, Bryson C.</au><au>Campbell, Edward P.</au><au>Li, Yun</au><au>Palmer, Mark J.</au><au>Viney, Neil R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Characterizing and Modeling Temporal and Spatial Trends in Rainfall Extremes</atitle><jtitle>Journal of hydrometeorology</jtitle><date>2009-02-01</date><risdate>2009</risdate><volume>10</volume><issue>1</issue><spage>241</spage><epage>253</epage><pages>241-253</pages><issn>1525-755X</issn><eissn>1525-7541</eissn><abstract>A hierarchical spatial model for daily rainfall extremes that characterizes their temporal variation due to interannual climatic forcing as well as their spatial pattern is proposed. The model treats the parameters of at-site probability distributions for rainfall extremes as “data” that are likely to be spatially correlated and driven by atmospheric forcing. The method is applied to daily rainfall extremes for summer and winter half years over the Swan–Avon River basin in Western Australia. Two techniques for the characterization of at-site extremes—peaks-over-threshold (POT) analysis and the generalized extreme value (GEV) distribution—and three climatic drivers—the El Niño–Southern Oscillation as measured by the Southern Oscillation index (SOI), the Southern Hemisphere annular mode as measured by an Antarctic Oscillation index (AOI), and solar irradiance (SI)—were considered. The POT analysis of at-site extremes revealed that at-site thresholds lacked spatial coherence, making it difficult to determine a smooth spatial surface for the threshold parameter. In contrast, the GEV-based analysis indicated smooth spatial patterns in daily rainfall extremes that are consistent with the predominant orientation of storm tracks over the study area and the presence of a coastal escarpment near the western edge of the basin. It also indicated a linkage between temporal trends in daily rainfall extremes and those of the SOI and AOI. By applying the spatial models to winter and summer extreme rainfalls separately, an apparent increasing trend in return levels of summer rainfall to the northwest and decreasing trends in return levels of winter rainfall to the southwest of the region are found.</abstract><pub>American Meteorological Society</pub><doi>10.1175/2008JHM1007.1</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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source | American Meteorological Society; JSTOR Archive Collection A-Z Listing; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
subjects | Climate change Climate models Floods Modeling Rain River basins Seasons Spatial models Summer Winter |
title | Characterizing and Modeling Temporal and Spatial Trends in Rainfall Extremes |
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