Uncertainties in estimating spatial and interannual variations in precipitation climatology in the India–Tibet region from multiple gridded precipitation datasets

• DOI: 10.1002/joc.4306
• Publication Date: 2015-03-14T14:26:48Z
• Authors: J. Kim; J. Sanjay; C. Mattmann; M. Boustani; M. V. S. Ramarao; R. Krishnan; D. Waliser
• Keywords: 13. Climate action; 0207 environmental engineering; 02 engineering and technology; 15. Life on land; 01 natural sciences; 6. Clean water; 0105 earth and related environmental sciences

ABSTRACT Uncertainty in calculating the spatial‐ and interannual variability of precipitation over India Tibet from widely used gridded datasets is examined for 29‐year period 1979 to 2007. defined terms spread among calculated multiple datasets, a useful method when similar or unknown accuracy are available analyses. The resulting uncertainty varies regions seasons. Geographical variations clearly seen signal‐to‐noise ratio ( SNR ), with largest Jammu Kashmir (J&K), western India‐eastern Pakistan, Tibet, Hindu‐Kush mountains, Western Ghats which characterized by either dry climate complex terrain, both. Seasonally, larger December–February DJF ) than June–September JJAS most region except J&K two wet seasons: winter summer. also according especially where nearly factor datasets. range determined largely gauge‐based data finest resolution, Asian Precipitation – Highly‐Resolved Observational Data Integration Towards Evaluation water resources (smallest) Meteorological Department (largest) all regions. regional seasonal do not appear depend on spatial resolution length records. This implies that analysis methodology such as quality control input data, spatial/temporal interpolation, retrieval algorithms producing these plays crucial role determining characteristics climatology represented individual Our results show must be accompanied careful examinations seasons arid/mountainous