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Modeling regional precipitation over the Indus River basin of Pakistan using statistical downscaling

Journal Article · · Theoretical and Applied Climatology
 [1];  [2];  [3];  [4]
  1. Univ. of Augsburg (Germany); Pakistan Agricultural Research Council (PARC) (Pakistan)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  3. Pakistan Agricultural Research Council (PARC) (Pakistan)
  4. Univ. of Augsburg (Germany)
Complex processes govern spatiotemporal distribution of precipitation within the high-mountainous headwater regions (commonly known as the upper Indus basin (UIB)), of the Indus River basin of Pakistan. Reliable precipitation simulations particularly over the UIB present a major scientific challenge due to regional complexity and inadequate observational coverage. Here, we present a statistical downscaling approach to model observed precipitation of the entire Indus basin, with a focus on UIB within available data constraints. Taking advantage of recent high altitude (HA) observatories, we perform precipitation regionalization using K-means cluster analysis to demonstrate effectiveness of low-altitude stations to provide useful precipitation inferences over more uncertain and hydrologically important HA of the UIB. We further employ generalized linear models (GLM) with gamma and Tweedie distributions to identify major dynamic and thermodynamic drivers from a reanalysis dataset within a robust cross-validation framework that explain observed spatiotemporal precipitation patterns across the Indus basin. Final statistical models demonstrate higher predictability to resolve precipitation variability over wetter southern Himalayans and different lower Indus regions, by mainly using different dynamic predictors. The modeling framework also shows an adequate performance over more complex and uncertain trans-Himalayans and the northwestern regions of the UIB, particularly during the seasons dominated by the westerly circulations. However, the cryosphere-dominated trans-Himalayan regions, which largely govern the basin hydrology, require relatively complex models that contain dynamic and thermodynamic circulations. Furthermore, we also analyzed relevant atmospheric circulations during precipitation anomalies over the UIB, to evaluate physical consistency of the statistical models, as an additional measure of reliability. Overall, our results suggest that such circulation-based statistical downscaling has the potential to improve our understanding towards distinct features of the regional-scale precipitation across the upper and lower Indus basin. Additionally, such understanding should help to assess the response of this complex, data-scarce, and climate-sensitive river basin amid future climatic changes, to serve communal and scientific interests.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
German Research Foundation (DFG); National Oceanic and Atmospheric Administration (NOAA); USDOE Office of Science (SC)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1649480
Journal Information:
Theoretical and Applied Climatology, Journal Name: Theoretical and Applied Climatology Vol. 142; ISSN 0177-798X
Publisher:
Springer NatureCopyright Statement
Country of Publication:
United States
Language:
English

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