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Detection and visualisation of climate trends in China

Gemmer, Marco ; Becker, Stefan ; Jiang, Tong ; Ke, Chanqing


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URN: urn:nbn:de:hebis:26-opus-13743
URL: http://geb.uni-giessen.de/geb/volltexte/2004/1374/

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Freie Schlagwörter (Deutsch): China , Wetter , Trend
Universität Justus-Liebig-Universität Gießen
Institut: Zentrum für internationale Entwicklungs- und Umweltforschung
Fachgebiet: Zentrum für internationale Entwicklungs- und Umweltforschung
DDC-Sachgruppe: Geografie, Reisen
Dokumentart: ResearchPaper
Zeitschrift, Serie: Discussion papers / Zentrum für Internationale Entwicklungs- und Umweltforschung ; 15
Sprache: Englisch
Erstellungsjahr: 2003
Publikationsdatum: 08.01.2004
Kurzfassung auf Englisch: Monthly precipitation and temperature trends of 160 stations in China from 1951-2002 have been analysed and interpolated. The Mann-Kendall trend test was applied to examine the monthly precipitation data. Significant positive and negative trends at the 90, 95 and 99% confidence levels were detected for numerous stations. The number, distribution and direction of the trends varied from month to month.
The detected trends were spatially interpolated by applying the Inverse Distance Weighted (IDW) interpolation method. The spatial illustration of the detected precipitation and temperature trends enables a better understanding of climatic changes or variations in China within the last 50 years. This counts especially for the spatial structure of the trends. An agglomeration of precipitation trends can be observed in certain months including distinct trend belts especially in east and north-east China. Nevertheless, positive as well as negative trends can be noted simultaneously in each month. Negative precipitation trends are often followed by positive trends for the same area during the next month.
In the meantime positive temperature trends can be detected in north, north-east and west China. They can be visualised for large regions in every month and explain a warming trend of northern and western China. Negative temperature trends can only be found from October-December with a relatively limited spatial distribution. The spatial interpolation of precipitation and temperature trend analysis results appears to be an adequate measure to give an understanding of the regional character of trends in China.
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