Interannual variability of winter precipitation in Southeast China

Zhang, Ling; Fraedrich, Klaus F.; Zhu, Xiuhua; Sielmann, Frank; Zhi, Xiefei

doi:10.1007/s00704-014-1111-5

アイテム詳細

登録内容を編集ファイル形式で保存

一時保存へ追加

タグ情報を表示リリース履歴を表示詳細要約

公開

学術論文

Interannual variability of winter precipitation in Southeast China

MPS-Authors

Zhang, Ling
Max Planck Fellows, MPI for Meteorology, Max Planck Society;

/persons/resource/persons37148

Fraedrich, Klaus F.
Max Planck Fellows, MPI for Meteorology, Max Planck Society;

External Resource

There are no locators available

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

フルテキスト (公開)

公開されているフルテキストはありません

付随資料 (公開)

There is no public supplementary material available

引用

Zhang, L., Fraedrich, K. F., Zhu, X., Sielmann, F., & Zhi, X. (2015). Interannual variability of winter precipitation in Southeast China. Theoretical and Applied Climatology, 119, 229-238. doi:10.1007/s00704-014-1111-5.

引用: https://hdl.handle.net/11858/00-001M-0000-0024-B6D4-4

要旨

The observed winter (DJF) precipitation in Southeast China (1961-2010) is characterized by a monopole pattern of the 3-monthly Standardized Precipitation Index (SPI-3) whose interannual variability is related to the anomalies of East Asian Winter Monsoon (EAWM) systems. Dynamic composites and linear regression analysis indicate that the intensity of EAWM and Siberia High (SH), the position of East Asian Trough (EAT), and El Nio events and sea surface temperature (SST) anomalies over South China Sea (SCS) influence different regions of anomalous Southeast China winter precipitation on interannual scales. The circulation indices (EAWM index, SH index, and EAT index) mainly affect the winter precipitation in the eastern part of Southeast China. El Nio events affect the South China winter precipitation due to the anticyclone anomalies over Philippines. The effect of SCS SST anomalies on the winter precipitation is mainly in the southern part of Yangtze River. Thus, a set of circulation regimes, represented by a handful indices, provide the basis for modeling precipitation anomalies or extremes in future climate projections.