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GIS-based high-resolution spatial interpolation of precipitation in mountain–plain areas of Upper Pakistan for regional climate change impact studies

  • Muhammad Waseem AshiqEmail author
  • Chuanyan Zhao
  • Jian Ni
  • Muhammad Akhtar
Original Paper

Abstract

In this study, the baseline period (1960–1990) precipitation simulation of regional climate model PRECIS is evaluated and downscaled on a monthly basis for northwestern Himalayan mountains and upper Indus plains of Pakistan. Different interpolation models in GIS environment are used to generate fine scale (250 × 250 m2) precipitation surfaces from PRECIS precipitation data. Results show that the multivariate extension model of ordinary kriging that uses elevation as secondary data is the best model especially for monsoon months. Model results are further compared with observations from 25 meteorological stations in the study area. Modeled data show overall good correlation with observations confirming the ability of PRECIS to capture major precipitation features in the region. Results for low and erratic precipitation months, September and October, are however showing poor correlation with observations. During monsoon months (June, July, August) precipitation pattern is different from the rest of the months. It increases from south to north, but during monsoon maximum precipitation is in the southern regions of the Himalayas, and extreme northern areas receive very less precipitation. Modeled precipitation toward the end of the twenty-first century under A2 and B2 scenarios show overall decrease during winter and increase in spring and monsoon in the study area. Spatially, both scenarios show similar pattern but with varying magnitude. In monsoon, the Himalayan southern regions will have more precipitation, whereas northern areas and southern plains will face decrease in precipitation. Western and south western areas will suffer from less precipitation throughout the year except peak monsoon months. T test results also show that changes in monthly precipitation over the study area are significant except for July, August, and December. Result of this study provide reliable basis for further climate change impact studies on various resources.

Keywords

Root Mean Square Error Regional Climate Model Baseline Period Ordinary Kriging Cokriging 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgement

The present study is a part of the research funded by Higher Education Commission of Pakistan (PIN no. 041 221461B-057) and also supported by National Natural Science Foundation of China (nos. 40671067 and 30770387). Authors are thankful to Nasir Ahmed (PU), Sally Aitken (UBC) and Tongli Wang (UBC) to facilitate this research and improve the manuscript. Thanks are also due to Pakistan Meteorological Department and CGIAR-Consortium for Spatial Information for making the data available for this study. We also gratefully acknowledge the anonymous reviewers for critical reviews of the manuscript.

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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Muhammad Waseem Ashiq
    • 1
    • 2
    • 6
    Email author
  • Chuanyan Zhao
    • 3
  • Jian Ni
    • 4
    • 5
  • Muhammad Akhtar
    • 2
  1. 1.Punjab Forest DepartmentLahorePakistan
  2. 2.Institute of GeologyUniversity of the Punjab (PU)LahorePakistan
  3. 3.Key Laboratory of Arid and Grassland Agroecology of Ministry of EducationLanzhou UniversityLanzhouChina
  4. 4.Max Planck Institute for BiogeochemistryJenaGermany
  5. 5.Alfred Wegener Institute for Polar and Marine ResearchPotsdamGermany
  6. 6.Centre for Forest Conservation Genetics, Department of Forest SciencesUniversity of British Columbia (UBC)VancouverCanada

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