Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes
For attributing hydrological changes to anthropogenic climate change, catchment models are driven by climate model output. A widespread approach to bridge the spatial gap between global climate and hydrological catchment models is to use a weather generator conditioned on weather patterns (WPs). Thi...
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Veröffentlicht in: | Journal of geophysical research. Atmospheres 2018-02, Vol.123 (3), p.1562-1584 |
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description | For attributing hydrological changes to anthropogenic climate change, catchment models are driven by climate model output. A widespread approach to bridge the spatial gap between global climate and hydrological catchment models is to use a weather generator conditioned on weather patterns (WPs). This approach assumes that changes in local climate are characterized by between‐type changes of patterns. In this study we test this assumption by analyzing a previously developed WP classification for the Rhine basin, which is based on dynamic and thermodynamic variables. We quantify changes in pattern characteristics and associated climatic properties. The amount of between‐ and within‐type changes is investigated by comparing observed trends to trends resulting solely from WP occurrence. To overcome uncertainties in trend detection resulting from the selected time period, all possible periods in 1901–2010 with a minimum length of 31 years are analyzed. Increasing frequency is found for some patterns associated with high precipitation, although the trend sign highly depends on the considered period. Trends and interannual variations of WP frequencies are related to the long‐term variability of large‐scale circulation modes. Long‐term WP internal warming is evident for summer patterns and enhanced warming for spring/autumn patterns since the 1970s. Observed trends in temperature and partly in precipitation are mainly associated with frequency changes of specific WPs, but some amount of within‐type changes remains. The classification can be used for downscaling of past changes considering this limitation, but the inclusion of thermodynamic variables into the classification impedes the downscaling of future climate projections.
Key Points
Analysed large (490 stations) and long(111 years) data set for Rhine catchment
Stationarity of weather pattern characteristics using multiple periods has been tested for the purpose of downscaling
Changes in temperature and precipitation are mainly related to changes in the occurrence of patterns |
doi_str_mv | 10.1002/2017JD026654 |
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Key Points
Analysed large (490 stations) and long(111 years) data set for Rhine catchment
Stationarity of weather pattern characteristics using multiple periods has been tested for the purpose of downscaling
Changes in temperature and precipitation are mainly related to changes in the occurrence of patterns</description><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1002/2017JD026654</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Annual variations ; Anthropogenic climate changes ; Anthropogenic factors ; attribution ; Catchment area ; Catchment models ; Classification ; Climate change ; Climate models ; Climate trends ; Conditioning ; Detection ; downscaling ; Future climates ; Geophysics ; Global climate ; Hydrologic models ; Hydrology ; hypothetical trend ; Interannual variations ; Local climates ; Precipitation ; trend analysis ; Trends ; Weather ; weather pattern ; Weather patterns ; Weather types</subject><ispartof>Journal of geophysical research. Atmospheres, 2018-02, Vol.123 (3), p.1562-1584</ispartof><rights>2018. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3452-297ac3376394537f7f333ca46027f11e37194e0deda5b93c86cecbd99d1178713</citedby><cites>FETCH-LOGICAL-c3452-297ac3376394537f7f333ca46027f11e37194e0deda5b93c86cecbd99d1178713</cites><orcidid>0000-0003-4639-7982 ; 0000-0003-2661-9314 ; 0000-0003-3539-2975 ; 0000-0002-5992-1440</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%2F2017JD026654$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2F2017JD026654$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>315,781,785,1418,1434,27928,27929,45578,45579,46413,46837</link.rule.ids></links><search><creatorcontrib>Murawski, Aline</creatorcontrib><creatorcontrib>Vorogushyn, Sergiy</creatorcontrib><creatorcontrib>Bürger, Gerd</creatorcontrib><creatorcontrib>Gerlitz, Lars</creatorcontrib><creatorcontrib>Merz, Bruno</creatorcontrib><title>Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes</title><title>Journal of geophysical research. Atmospheres</title><description>For attributing hydrological changes to anthropogenic climate change, catchment models are driven by climate model output. A widespread approach to bridge the spatial gap between global climate and hydrological catchment models is to use a weather generator conditioned on weather patterns (WPs). This approach assumes that changes in local climate are characterized by between‐type changes of patterns. In this study we test this assumption by analyzing a previously developed WP classification for the Rhine basin, which is based on dynamic and thermodynamic variables. We quantify changes in pattern characteristics and associated climatic properties. The amount of between‐ and within‐type changes is investigated by comparing observed trends to trends resulting solely from WP occurrence. To overcome uncertainties in trend detection resulting from the selected time period, all possible periods in 1901–2010 with a minimum length of 31 years are analyzed. Increasing frequency is found for some patterns associated with high precipitation, although the trend sign highly depends on the considered period. Trends and interannual variations of WP frequencies are related to the long‐term variability of large‐scale circulation modes. Long‐term WP internal warming is evident for summer patterns and enhanced warming for spring/autumn patterns since the 1970s. Observed trends in temperature and partly in precipitation are mainly associated with frequency changes of specific WPs, but some amount of within‐type changes remains. The classification can be used for downscaling of past changes considering this limitation, but the inclusion of thermodynamic variables into the classification impedes the downscaling of future climate projections.
Key Points
Analysed large (490 stations) and long(111 years) data set for Rhine catchment
Stationarity of weather pattern characteristics using multiple periods has been tested for the purpose of downscaling
Changes in temperature and precipitation are mainly related to changes in the occurrence of patterns</description><subject>Annual variations</subject><subject>Anthropogenic climate changes</subject><subject>Anthropogenic factors</subject><subject>attribution</subject><subject>Catchment area</subject><subject>Catchment models</subject><subject>Classification</subject><subject>Climate change</subject><subject>Climate models</subject><subject>Climate trends</subject><subject>Conditioning</subject><subject>Detection</subject><subject>downscaling</subject><subject>Future climates</subject><subject>Geophysics</subject><subject>Global climate</subject><subject>Hydrologic models</subject><subject>Hydrology</subject><subject>hypothetical trend</subject><subject>Interannual variations</subject><subject>Local climates</subject><subject>Precipitation</subject><subject>trend analysis</subject><subject>Trends</subject><subject>Weather</subject><subject>weather pattern</subject><subject>Weather patterns</subject><subject>Weather types</subject><issn>2169-897X</issn><issn>2169-8996</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kM1Kw0AQx4MoWLQ3H2DBq9H9SjZ7kn5ZLYVCqdRb2CaTdktM4m5qzU18Ap_RJ3FLRDw5DMwM82P-M-N5FwRfE4zpDcVETIaYhmHAj7wOJaH0IynD499cPJ16XWu32FmEGQ94x_sYlmiwUcVaF2u0BFVvwKBFU4FFo7cqV7pAs5UF8wopGuT6WdU6QQsDRWqR6zkczTe6ANRXVhe3qFc4V3ljtUVlhpa6dt2v90-kihT1od4DHMqDQqsL9tw7yVRuofsTz7zHu9FicO9PZ-OHQW_qJ25V6lMpVMKYCJnkAROZyBhjieIhpiIjBJggkgNOIVXBSrIkChNIVqmUKSEiEoSdeZft3MqULzuwdbwtd8Yta2OKsWAs4pQ76qqlElNaayCLK-PONk1McHx4dPz30Q5nLb7XOTT_svFkPB8GnGPKvgFB3X9p</recordid><startdate>20180216</startdate><enddate>20180216</enddate><creator>Murawski, Aline</creator><creator>Vorogushyn, Sergiy</creator><creator>Bürger, Gerd</creator><creator>Gerlitz, Lars</creator><creator>Merz, Bruno</creator><general>Blackwell Publishing Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-4639-7982</orcidid><orcidid>https://orcid.org/0000-0003-2661-9314</orcidid><orcidid>https://orcid.org/0000-0003-3539-2975</orcidid><orcidid>https://orcid.org/0000-0002-5992-1440</orcidid></search><sort><creationdate>20180216</creationdate><title>Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes</title><author>Murawski, Aline ; Vorogushyn, Sergiy ; Bürger, Gerd ; Gerlitz, Lars ; Merz, Bruno</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3452-297ac3376394537f7f333ca46027f11e37194e0deda5b93c86cecbd99d1178713</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Annual variations</topic><topic>Anthropogenic climate changes</topic><topic>Anthropogenic factors</topic><topic>attribution</topic><topic>Catchment area</topic><topic>Catchment models</topic><topic>Classification</topic><topic>Climate change</topic><topic>Climate models</topic><topic>Climate trends</topic><topic>Conditioning</topic><topic>Detection</topic><topic>downscaling</topic><topic>Future climates</topic><topic>Geophysics</topic><topic>Global climate</topic><topic>Hydrologic models</topic><topic>Hydrology</topic><topic>hypothetical trend</topic><topic>Interannual variations</topic><topic>Local climates</topic><topic>Precipitation</topic><topic>trend analysis</topic><topic>Trends</topic><topic>Weather</topic><topic>weather pattern</topic><topic>Weather patterns</topic><topic>Weather types</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Murawski, Aline</creatorcontrib><creatorcontrib>Vorogushyn, Sergiy</creatorcontrib><creatorcontrib>Bürger, Gerd</creatorcontrib><creatorcontrib>Gerlitz, Lars</creatorcontrib><creatorcontrib>Merz, Bruno</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Journal of geophysical research. Atmospheres</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Murawski, Aline</au><au>Vorogushyn, Sergiy</au><au>Bürger, Gerd</au><au>Gerlitz, Lars</au><au>Merz, Bruno</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes</atitle><jtitle>Journal of geophysical research. Atmospheres</jtitle><date>2018-02-16</date><risdate>2018</risdate><volume>123</volume><issue>3</issue><spage>1562</spage><epage>1584</epage><pages>1562-1584</pages><issn>2169-897X</issn><eissn>2169-8996</eissn><abstract>For attributing hydrological changes to anthropogenic climate change, catchment models are driven by climate model output. A widespread approach to bridge the spatial gap between global climate and hydrological catchment models is to use a weather generator conditioned on weather patterns (WPs). This approach assumes that changes in local climate are characterized by between‐type changes of patterns. In this study we test this assumption by analyzing a previously developed WP classification for the Rhine basin, which is based on dynamic and thermodynamic variables. We quantify changes in pattern characteristics and associated climatic properties. The amount of between‐ and within‐type changes is investigated by comparing observed trends to trends resulting solely from WP occurrence. To overcome uncertainties in trend detection resulting from the selected time period, all possible periods in 1901–2010 with a minimum length of 31 years are analyzed. Increasing frequency is found for some patterns associated with high precipitation, although the trend sign highly depends on the considered period. Trends and interannual variations of WP frequencies are related to the long‐term variability of large‐scale circulation modes. Long‐term WP internal warming is evident for summer patterns and enhanced warming for spring/autumn patterns since the 1970s. Observed trends in temperature and partly in precipitation are mainly associated with frequency changes of specific WPs, but some amount of within‐type changes remains. The classification can be used for downscaling of past changes considering this limitation, but the inclusion of thermodynamic variables into the classification impedes the downscaling of future climate projections.
Key Points
Analysed large (490 stations) and long(111 years) data set for Rhine catchment
Stationarity of weather pattern characteristics using multiple periods has been tested for the purpose of downscaling
Changes in temperature and precipitation are mainly related to changes in the occurrence of patterns</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/2017JD026654</doi><tpages>23</tpages><orcidid>https://orcid.org/0000-0003-4639-7982</orcidid><orcidid>https://orcid.org/0000-0003-2661-9314</orcidid><orcidid>https://orcid.org/0000-0003-3539-2975</orcidid><orcidid>https://orcid.org/0000-0002-5992-1440</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Annual variations Anthropogenic climate changes Anthropogenic factors attribution Catchment area Catchment models Classification Climate change Climate models Climate trends Conditioning Detection downscaling Future climates Geophysics Global climate Hydrologic models Hydrology hypothetical trend Interannual variations Local climates Precipitation trend analysis Trends Weather weather pattern Weather patterns Weather types |
title | Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes |
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