Anomaly based analysis of extreme heat waves in Eastern China during 1981–2013
ABSTRACT This study shows applications of an anomaly based analysis method to describe extreme summer heat waves in Eastern China during 1981–2013 using two reanalysis products. These events are defined in an area of a spatial size larger than 300 × 500 km (0.15 × 106 km2) when its daily maximum sur...
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Veröffentlicht in: | International journal of climatology 2017-01, Vol.37 (1), p.509-523 |
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creator | Chen, Yun Hu, Qi Yang, Yinming Qian, Weihong |
description | ABSTRACT
This study shows applications of an anomaly based analysis method to describe extreme summer heat waves in Eastern China during 1981–2013 using two reanalysis products. These events are defined in an area of a spatial size larger than 300 × 500 km (0.15 × 106 km2) when its daily maximum surface air temperature (DMSAT) exceeds 35 °C, and the DMSAT anomaly is no less than 5 °C for at least five consecutive days. Results show that by extracting the transient anomalies, the anomaly based method can substantially improve descriptions of key synoptic features of heat waves in their central location, spatial coverage, intensity, and duration as well as their spatial structure of geopotential height and temperature anomalies. They also show the capability of the method in helping identify and trace the early disturbances that evolved into extreme heat wave events in Eastern China in 12 summers during 1981–2013. Over that period, the statistics of heat waves indicate an increase in the number of extreme heat wave events in China, especially in the 21st century. The method is further applied to the National Centres for Environmental Prediction (NCEP) and European Centre for Medium‐Range Weather Forecasts (ECMWF) model predictions to illustrate its usefulness in interpreting model predictions for heat waves. |
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This study shows applications of an anomaly based analysis method to describe extreme summer heat waves in Eastern China during 1981–2013 using two reanalysis products. These events are defined in an area of a spatial size larger than 300 × 500 km (0.15 × 106 km2) when its daily maximum surface air temperature (DMSAT) exceeds 35 °C, and the DMSAT anomaly is no less than 5 °C for at least five consecutive days. Results show that by extracting the transient anomalies, the anomaly based method can substantially improve descriptions of key synoptic features of heat waves in their central location, spatial coverage, intensity, and duration as well as their spatial structure of geopotential height and temperature anomalies. They also show the capability of the method in helping identify and trace the early disturbances that evolved into extreme heat wave events in Eastern China in 12 summers during 1981–2013. Over that period, the statistics of heat waves indicate an increase in the number of extreme heat wave events in China, especially in the 21st century. The method is further applied to the National Centres for Environmental Prediction (NCEP) and European Centre for Medium‐Range Weather Forecasts (ECMWF) model predictions to illustrate its usefulness in interpreting model predictions for heat waves.</description><identifier>ISSN: 0899-8418</identifier><identifier>EISSN: 1097-0088</identifier><identifier>DOI: 10.1002/joc.4724</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>early disturbance ; heat wave event ; interpreting model prediction ; tracing</subject><ispartof>International journal of climatology, 2017-01, Vol.37 (1), p.509-523</ispartof><rights>2016 Royal Meteorological Society</rights><rights>2017 Royal Meteorological Society</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2934-eb0fb4a3ee763f254518f734c49cfa9638a1feaf75c7662b5467062d5ffea6303</citedby></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.4724$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjoc.4724$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Chen, Yun</creatorcontrib><creatorcontrib>Hu, Qi</creatorcontrib><creatorcontrib>Yang, Yinming</creatorcontrib><creatorcontrib>Qian, Weihong</creatorcontrib><title>Anomaly based analysis of extreme heat waves in Eastern China during 1981–2013</title><title>International journal of climatology</title><description>ABSTRACT
This study shows applications of an anomaly based analysis method to describe extreme summer heat waves in Eastern China during 1981–2013 using two reanalysis products. These events are defined in an area of a spatial size larger than 300 × 500 km (0.15 × 106 km2) when its daily maximum surface air temperature (DMSAT) exceeds 35 °C, and the DMSAT anomaly is no less than 5 °C for at least five consecutive days. Results show that by extracting the transient anomalies, the anomaly based method can substantially improve descriptions of key synoptic features of heat waves in their central location, spatial coverage, intensity, and duration as well as their spatial structure of geopotential height and temperature anomalies. They also show the capability of the method in helping identify and trace the early disturbances that evolved into extreme heat wave events in Eastern China in 12 summers during 1981–2013. Over that period, the statistics of heat waves indicate an increase in the number of extreme heat wave events in China, especially in the 21st century. The method is further applied to the National Centres for Environmental Prediction (NCEP) and European Centre for Medium‐Range Weather Forecasts (ECMWF) model predictions to illustrate its usefulness in interpreting model predictions for heat waves.</description><subject>early disturbance</subject><subject>heat wave event</subject><subject>interpreting model prediction</subject><subject>tracing</subject><issn>0899-8418</issn><issn>1097-0088</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNpdkMtOwzAURC0EEqUg8QmW2LBJuX7EsZdVVF6qVBawjpz0mrrKo8QJpTv-gT_kS0gpK1Yzujoz0h1CLhlMGAC_WTfFRCZcHpERA5NEAFofkxFoYyItmT4lZyGsAcAYpkbkaVo3lS13NLcBl9TWgw8-0MZR_OharJCu0HZ0a98xUF_TmQ0dtjVNV762dNm3vn6lzGj2_fnFgYlzcuJsGfDiT8fk5Xb2nN5H88XdQzqdRwU3QkaYg8ulFYiJEo7HMmbaJUIW0hTOGiW0ZQ6tS-IiUYrnsVQJKL6M3XBVAsSYXB96N23z1mPossqHAsvS1tj0IWM6NtJIIdSAXv1D103fDp_-UlIpIwwfqOhAbX2Ju2zT-sq2u4xBtt91iBTZftfscZHuVfwADklq_A</recordid><startdate>201701</startdate><enddate>201701</enddate><creator>Chen, Yun</creator><creator>Hu, Qi</creator><creator>Yang, Yinming</creator><creator>Qian, Weihong</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>7TG</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope></search><sort><creationdate>201701</creationdate><title>Anomaly based analysis of extreme heat waves in Eastern China during 1981–2013</title><author>Chen, Yun ; Hu, Qi ; Yang, Yinming ; Qian, Weihong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2934-eb0fb4a3ee763f254518f734c49cfa9638a1feaf75c7662b5467062d5ffea6303</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>early disturbance</topic><topic>heat wave event</topic><topic>interpreting model prediction</topic><topic>tracing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Yun</creatorcontrib><creatorcontrib>Hu, Qi</creatorcontrib><creatorcontrib>Yang, Yinming</creatorcontrib><creatorcontrib>Qian, Weihong</creatorcontrib><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>Chen, Yun</au><au>Hu, Qi</au><au>Yang, Yinming</au><au>Qian, Weihong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Anomaly based analysis of extreme heat waves in Eastern China during 1981–2013</atitle><jtitle>International journal of climatology</jtitle><date>2017-01</date><risdate>2017</risdate><volume>37</volume><issue>1</issue><spage>509</spage><epage>523</epage><pages>509-523</pages><issn>0899-8418</issn><eissn>1097-0088</eissn><abstract>ABSTRACT
This study shows applications of an anomaly based analysis method to describe extreme summer heat waves in Eastern China during 1981–2013 using two reanalysis products. These events are defined in an area of a spatial size larger than 300 × 500 km (0.15 × 106 km2) when its daily maximum surface air temperature (DMSAT) exceeds 35 °C, and the DMSAT anomaly is no less than 5 °C for at least five consecutive days. Results show that by extracting the transient anomalies, the anomaly based method can substantially improve descriptions of key synoptic features of heat waves in their central location, spatial coverage, intensity, and duration as well as their spatial structure of geopotential height and temperature anomalies. They also show the capability of the method in helping identify and trace the early disturbances that evolved into extreme heat wave events in Eastern China in 12 summers during 1981–2013. Over that period, the statistics of heat waves indicate an increase in the number of extreme heat wave events in China, especially in the 21st century. The method is further applied to the National Centres for Environmental Prediction (NCEP) and European Centre for Medium‐Range Weather Forecasts (ECMWF) model predictions to illustrate its usefulness in interpreting model predictions for heat waves.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/joc.4724</doi><tpages>15</tpages></addata></record> |
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title | Anomaly based analysis of extreme heat waves in Eastern China during 1981–2013 |
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