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Journal of the Meteorological Society of Japan
Article . 2007 . Peer-reviewed
Data sources: Crossref
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Modeling Annual Extreme Precipitation in China Using the Generalized Extreme Value Distribution

Authors: Feng, Song; Nadarajah, Saralees; Hu, Qi;

Modeling Annual Extreme Precipitation in China Using the Generalized Extreme Value Distribution

Abstract

Extreme precipitation events are the major causes of severe floods in China. In this study, four time series of daily, 2-day, 5-day, and 10-day annual maximum precipitation from 1951 to 2000 at 651 weather stations in China were analyzed. The generalized extreme value (GEV) distribution was used, to model the annual extreme precipitation events at each station. The GEV distribution was also modified to explore the linear temporal trends in the extreme events. The results showed that more than 12% of the stations have significant ( p-value < 0:10) linear trends. Decreasing trends are mainly observed in northern China, and increasing trends are observed in the Yangtze River basin and northwestern China. The return periods of extreme precipitation have changed for stations with significant temporal trends. The 50-year event observed in parts of the Yangtze River basin, and northwestern China during 1951‐ 60, has become a more frequent 25-year event in the 1990s. The spatial distribution of the return levels of the 651 stations are closely related to the climatic mean precipitation, and are influenced by the East Asian summer monsoon system (return levels are measures of extremity—for example, a 10 year return level is the value that can be expected to be exceeded on average once in every 10 years). The return period of extreme precipitation, that caused the 1998 severe floods in the Yangtze River basin, was also evaluated from a probabilistic perspective.

Country
United States
Keywords

550, Earth Sciences

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    91
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
91
Top 10%
Top 10%
Average
gold