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  Predictors of precipitation for improved water resources management in the Tarim River basin: Creating a seasonal forecast model

Hartmann, H., Snow, J., Stein, S., Su, B., Zhai, J., Jiang, T., Krysanova, V., Kundzewicz, Z. W. (2016): Predictors of precipitation for improved water resources management in the Tarim River basin: Creating a seasonal forecast model. - Journal of Arid Environments, 125, 31-42.
https://doi.org/10.1016/j.jaridenv.2015.09.010

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 Creators:
Hartmann, H.1, Author
Snow, J.1, Author
Stein, S.1, Author
Su, B.1, Author
Zhai, J.1, Author
Jiang, T.1, Author
Krysanova, Valentina2, Author              
Kundzewicz, Zbigniew W.2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: In recent years, an expansion of irrigated agriculture and rapid population growth have threatened the Tarim River basin's natural ecosystems and caused water shortages. Improving the water resources management in the basin requires accurate seasonal precipitation forecasts. Based on previous research, possible predictors of precipitation were selected and either downloaded directly or calculated using NCEP/NCAR Reanalysis 1 or NOAA Extended Reconstructed Sea Surface Temperature (SST) V3b data. Predictors were correlated with precipitation data, provided by the National Climate Centre of the China Meteorological Administration for the period 1961 to 2010 and averaged over the subbasins of the Tarim River. The Spearman rank correlation analyses with lead times of up to six months (or two seasons) revealed significant (at the 1% level) and strong (ρ ≤ −0.6 or ρ ≥ 0.6) correlations of precipitation in all subbasins with the SST and monsoon indices as well as with the Siberian High Intensity (SHI) and the Westerly Circulation Index (WCI). Lastly, we demonstrate the setup of a forecast model based on a multiple linear regression on the example of the Hotan River subbasin. This model predicts precipitation 5 months in advance with reasonable accuracy in two out of three configurations.

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 Dates: 2016
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.jaridenv.2015.09.010
PIKDOMAIN: Climate Impacts & Vulnerabilities - Research Domain II
eDoc: 7445
Research topic keyword: Weather
Model / method: Nonlinear Data Analysis
Regional keyword: Asia
Organisational keyword: RD2 - Climate Resilience
Working Group: Hydroclimatic Risks
 Degree: -

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Title: Journal of Arid Environments
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 125 Sequence Number: - Start / End Page: 31 - 42 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals246