Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013
This study investigated the spatial–temporal patterns and trends of potential evapotranspiration (ET 0 ) and aridity index (AI) over Southwest China during 1960–2013 based on daily temperature, precipitation, wind speed, sunshine duration, total solar radiation, and relative humidity data from 108 m...
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| Veröffentlicht in: | Theoretical and applied climatology 2018-08, Vol.133 (3-4), p.711-726 |
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| creator | Zhao, Yifei Zou, Xinqing Cao, Liguo Yao, Yulong Fu, Guanghe |
| description | This study investigated the spatial–temporal patterns and trends of potential evapotranspiration (ET
0
) and aridity index (AI) over Southwest China during 1960–2013 based on daily temperature, precipitation, wind speed, sunshine duration, total solar radiation, and relative humidity data from 108 meteorological stations. The Penman–Monteith model, Mann–Kendall (M–K) test, moving
t
test, and Morlet wavelet method were used. The results indicated that ET
0
and AI across the region displayed decreasing trends, but the former was significant. After 2000, regionally average trends in ET
0
and AI increased rapidly, indicating that droughts increased over Southwest China in recent years. Spatially, the changes of ET
0
and AI were dissimilar and not clustered, either. Temporally, both ET
0
and AI displayed obvious abrupt change points over different timescales and that of AI was during the winter monsoon period. Significant periodic variations with periods of 27, 13, and 5 years were found in ET
0
, but only of 13 and 5 years existed in AI. Correlation analysis revealed that the sunshine duration and wind speed were the dominant factors affecting ET
0
and that AI showed strong negative correlation with precipitation. The findings of this study enhance the understanding of the relationship between climate change and drought in Southwest China, while the mechanism controlling the variation in drought requires further study. |
| doi_str_mv | 10.1007/s00704-017-2216-4 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2068235176</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A546322391</galeid><sourcerecordid>A546322391</sourcerecordid><originalsourceid>FETCH-LOGICAL-c389t-f206509a9b35baab4f36120ceff50ca915b14326d8d64a03b3db5f30bd37806c3</originalsourceid><addsrcrecordid>eNp1kd1qFTEQx4MoeKw-gHcBr7zYmq_N7l6Wg9pCQfBU8C5kN8lpyp5kTbKn7Z3vUPABfRJnXUF6UQITZub3n0xmEHpLySklpPmQwRBREdpUjFFZiWdoQwUXlRAtf442kGiqpmu_v0Svcr4hhDApmw36tZt08bHYwxSTHvFRJ78EQsbR4QkSoXiI26MGJ-mQJ5_-AlgHg4E2vtxjH4y9A4uTHddsieC6cbZh8GGPnR5KTFD0aBPexblc39pc8PbaB43NnBaGdpL8_vnACOWv0Qunx2zf_LtP0LdPH6-259Xll88X27PLauBtVyrHiKxJp7ue173WvXBcUkYG61xNBt3RuochMGlaI4UmvOemrx0nveFNS-TAT9C7te6U4o8ZOlI3cU4BnlRQumW8po0E6nSl9nq0Cr61TGKAY-zBDzFY5yF-VgvJGeMdBcH7RwJgir0rez3nrC52Xx-zdGWHFHNO1qkp-YNO94oStexWrbtVsEK17FYJ0LBVk6dlcjb9b_tp0R94d6ku</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2068235176</pqid></control><display><type>article</type><title>Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013</title><source>SpringerLink Journals - AutoHoldings</source><creator>Zhao, Yifei ; Zou, Xinqing ; Cao, Liguo ; Yao, Yulong ; Fu, Guanghe</creator><creatorcontrib>Zhao, Yifei ; Zou, Xinqing ; Cao, Liguo ; Yao, Yulong ; Fu, Guanghe</creatorcontrib><description>This study investigated the spatial–temporal patterns and trends of potential evapotranspiration (ET
0
) and aridity index (AI) over Southwest China during 1960–2013 based on daily temperature, precipitation, wind speed, sunshine duration, total solar radiation, and relative humidity data from 108 meteorological stations. The Penman–Monteith model, Mann–Kendall (M–K) test, moving
t
test, and Morlet wavelet method were used. The results indicated that ET
0
and AI across the region displayed decreasing trends, but the former was significant. After 2000, regionally average trends in ET
0
and AI increased rapidly, indicating that droughts increased over Southwest China in recent years. Spatially, the changes of ET
0
and AI were dissimilar and not clustered, either. Temporally, both ET
0
and AI displayed obvious abrupt change points over different timescales and that of AI was during the winter monsoon period. Significant periodic variations with periods of 27, 13, and 5 years were found in ET
0
, but only of 13 and 5 years existed in AI. Correlation analysis revealed that the sunshine duration and wind speed were the dominant factors affecting ET
0
and that AI showed strong negative correlation with precipitation. The findings of this study enhance the understanding of the relationship between climate change and drought in Southwest China, while the mechanism controlling the variation in drought requires further study.</description><identifier>ISSN: 0177-798X</identifier><identifier>EISSN: 1434-4483</identifier><identifier>DOI: 10.1007/s00704-017-2216-4</identifier><language>eng</language><publisher>Vienna: Springer Vienna</publisher><subject>Analysis ; Aquatic Pollution ; Aridity ; Aridity index ; Atmospheric Protection/Air Quality Control/Air Pollution ; Atmospheric Sciences ; Chinese history ; Climate change ; Climate science ; Climatology ; Correlation analysis ; Daily temperatures ; Drought ; Duration ; Earth and Environmental Science ; Earth Sciences ; Evapotranspiration ; Global temperature changes ; Humidity ; Humidity data ; Morlet wavelet ; Original Paper ; Periodic variations ; Potential evapotranspiration ; Precipitation ; Precipitation (Meteorology) ; Relative humidity ; Solar radiation ; Sunlight ; Sunshine duration ; Test procedures ; Trends ; Variation ; Waste Water Technology ; Water Management ; Water Pollution Control ; Wavelet analysis ; Weather ; Weather stations ; Wind speed ; Winter monsoon</subject><ispartof>Theoretical and applied climatology, 2018-08, Vol.133 (3-4), p.711-726</ispartof><rights>Springer-Verlag GmbH Austria 2017</rights><rights>COPYRIGHT 2018 Springer</rights><rights>Theoretical and Applied Climatology is a copyright of Springer, (2017). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c389t-f206509a9b35baab4f36120ceff50ca915b14326d8d64a03b3db5f30bd37806c3</citedby><cites>FETCH-LOGICAL-c389t-f206509a9b35baab4f36120ceff50ca915b14326d8d64a03b3db5f30bd37806c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00704-017-2216-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00704-017-2216-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Zhao, Yifei</creatorcontrib><creatorcontrib>Zou, Xinqing</creatorcontrib><creatorcontrib>Cao, Liguo</creatorcontrib><creatorcontrib>Yao, Yulong</creatorcontrib><creatorcontrib>Fu, Guanghe</creatorcontrib><title>Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013</title><title>Theoretical and applied climatology</title><addtitle>Theor Appl Climatol</addtitle><description>This study investigated the spatial–temporal patterns and trends of potential evapotranspiration (ET
0
) and aridity index (AI) over Southwest China during 1960–2013 based on daily temperature, precipitation, wind speed, sunshine duration, total solar radiation, and relative humidity data from 108 meteorological stations. The Penman–Monteith model, Mann–Kendall (M–K) test, moving
t
test, and Morlet wavelet method were used. The results indicated that ET
0
and AI across the region displayed decreasing trends, but the former was significant. After 2000, regionally average trends in ET
0
and AI increased rapidly, indicating that droughts increased over Southwest China in recent years. Spatially, the changes of ET
0
and AI were dissimilar and not clustered, either. Temporally, both ET
0
and AI displayed obvious abrupt change points over different timescales and that of AI was during the winter monsoon period. Significant periodic variations with periods of 27, 13, and 5 years were found in ET
0
, but only of 13 and 5 years existed in AI. Correlation analysis revealed that the sunshine duration and wind speed were the dominant factors affecting ET
0
and that AI showed strong negative correlation with precipitation. The findings of this study enhance the understanding of the relationship between climate change and drought in Southwest China, while the mechanism controlling the variation in drought requires further study.</description><subject>Analysis</subject><subject>Aquatic Pollution</subject><subject>Aridity</subject><subject>Aridity index</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Atmospheric Sciences</subject><subject>Chinese history</subject><subject>Climate change</subject><subject>Climate science</subject><subject>Climatology</subject><subject>Correlation analysis</subject><subject>Daily temperatures</subject><subject>Drought</subject><subject>Duration</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Evapotranspiration</subject><subject>Global temperature changes</subject><subject>Humidity</subject><subject>Humidity data</subject><subject>Morlet wavelet</subject><subject>Original Paper</subject><subject>Periodic variations</subject><subject>Potential evapotranspiration</subject><subject>Precipitation</subject><subject>Precipitation (Meteorology)</subject><subject>Relative humidity</subject><subject>Solar radiation</subject><subject>Sunlight</subject><subject>Sunshine duration</subject><subject>Test procedures</subject><subject>Trends</subject><subject>Variation</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><subject>Wavelet analysis</subject><subject>Weather</subject><subject>Weather stations</subject><subject>Wind speed</subject><subject>Winter monsoon</subject><issn>0177-798X</issn><issn>1434-4483</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kd1qFTEQx4MoeKw-gHcBr7zYmq_N7l6Wg9pCQfBU8C5kN8lpyp5kTbKn7Z3vUPABfRJnXUF6UQITZub3n0xmEHpLySklpPmQwRBREdpUjFFZiWdoQwUXlRAtf442kGiqpmu_v0Svcr4hhDApmw36tZt08bHYwxSTHvFRJ78EQsbR4QkSoXiI26MGJ-mQJ5_-AlgHg4E2vtxjH4y9A4uTHddsieC6cbZh8GGPnR5KTFD0aBPexblc39pc8PbaB43NnBaGdpL8_vnACOWv0Qunx2zf_LtP0LdPH6-259Xll88X27PLauBtVyrHiKxJp7ue173WvXBcUkYG61xNBt3RuochMGlaI4UmvOemrx0nveFNS-TAT9C7te6U4o8ZOlI3cU4BnlRQumW8po0E6nSl9nq0Cr61TGKAY-zBDzFY5yF-VgvJGeMdBcH7RwJgir0rez3nrC52Xx-zdGWHFHNO1qkp-YNO94oStexWrbtVsEK17FYJ0LBVk6dlcjb9b_tp0R94d6ku</recordid><startdate>20180801</startdate><enddate>20180801</enddate><creator>Zhao, 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factors over Southwest China during 1960–2013</title><author>Zhao, Yifei ; Zou, Xinqing ; Cao, Liguo ; Yao, Yulong ; Fu, Guanghe</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c389t-f206509a9b35baab4f36120ceff50ca915b14326d8d64a03b3db5f30bd37806c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Analysis</topic><topic>Aquatic Pollution</topic><topic>Aridity</topic><topic>Aridity index</topic><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>Atmospheric Sciences</topic><topic>Chinese history</topic><topic>Climate change</topic><topic>Climate science</topic><topic>Climatology</topic><topic>Correlation analysis</topic><topic>Daily temperatures</topic><topic>Drought</topic><topic>Duration</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Evapotranspiration</topic><topic>Global temperature changes</topic><topic>Humidity</topic><topic>Humidity data</topic><topic>Morlet wavelet</topic><topic>Original Paper</topic><topic>Periodic variations</topic><topic>Potential evapotranspiration</topic><topic>Precipitation</topic><topic>Precipitation (Meteorology)</topic><topic>Relative humidity</topic><topic>Solar radiation</topic><topic>Sunlight</topic><topic>Sunshine duration</topic><topic>Test procedures</topic><topic>Trends</topic><topic>Variation</topic><topic>Waste Water Technology</topic><topic>Water Management</topic><topic>Water Pollution Control</topic><topic>Wavelet analysis</topic><topic>Weather</topic><topic>Weather stations</topic><topic>Wind speed</topic><topic>Winter monsoon</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhao, Yifei</creatorcontrib><creatorcontrib>Zou, Xinqing</creatorcontrib><creatorcontrib>Cao, Liguo</creatorcontrib><creatorcontrib>Yao, Yulong</creatorcontrib><creatorcontrib>Fu, 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1960–2013</atitle><jtitle>Theoretical and applied climatology</jtitle><stitle>Theor Appl Climatol</stitle><date>2018-08-01</date><risdate>2018</risdate><volume>133</volume><issue>3-4</issue><spage>711</spage><epage>726</epage><pages>711-726</pages><issn>0177-798X</issn><eissn>1434-4483</eissn><abstract>This study investigated the spatial–temporal patterns and trends of potential evapotranspiration (ET
0
) and aridity index (AI) over Southwest China during 1960–2013 based on daily temperature, precipitation, wind speed, sunshine duration, total solar radiation, and relative humidity data from 108 meteorological stations. The Penman–Monteith model, Mann–Kendall (M–K) test, moving
t
test, and Morlet wavelet method were used. The results indicated that ET
0
and AI across the region displayed decreasing trends, but the former was significant. After 2000, regionally average trends in ET
0
and AI increased rapidly, indicating that droughts increased over Southwest China in recent years. Spatially, the changes of ET
0
and AI were dissimilar and not clustered, either. Temporally, both ET
0
and AI displayed obvious abrupt change points over different timescales and that of AI was during the winter monsoon period. Significant periodic variations with periods of 27, 13, and 5 years were found in ET
0
, but only of 13 and 5 years existed in AI. Correlation analysis revealed that the sunshine duration and wind speed were the dominant factors affecting ET
0
and that AI showed strong negative correlation with precipitation. The findings of this study enhance the understanding of the relationship between climate change and drought in Southwest China, while the mechanism controlling the variation in drought requires further study.</abstract><cop>Vienna</cop><pub>Springer Vienna</pub><doi>10.1007/s00704-017-2216-4</doi><tpages>16</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0177-798X |
| ispartof | Theoretical and applied climatology, 2018-08, Vol.133 (3-4), p.711-726 |
| issn | 0177-798X 1434-4483 |
| language | eng |
| recordid | cdi_proquest_journals_2068235176 |
| source | SpringerLink Journals - AutoHoldings |
| subjects | Analysis Aquatic Pollution Aridity Aridity index Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Chinese history Climate change Climate science Climatology Correlation analysis Daily temperatures Drought Duration Earth and Environmental Science Earth Sciences Evapotranspiration Global temperature changes Humidity Humidity data Morlet wavelet Original Paper Periodic variations Potential evapotranspiration Precipitation Precipitation (Meteorology) Relative humidity Solar radiation Sunlight Sunshine duration Test procedures Trends Variation Waste Water Technology Water Management Water Pollution Control Wavelet analysis Weather Weather stations Wind speed Winter monsoon |
| title | Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013 |
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