Bias correction demonstration in two of the Indian Himalayan river basins

Abstract

Abstract There is imperative need of robust basin-scale data for climate impact studies over the topographically varying and landuse heterogenous river basins in the Indian Himalayan Region (IHR). Even finer resolution regional climate models’ (RCMs) information is elusive for these purposes. Based on available model fields and corresponding in-situ observed fields, bias correction for precipitation over Upper Ganga River Basin (UGRB) and temperature over Satluj River Basin (SRB) is demonstrated. These chosen river basins are in central and western Himalayas, respectively. Model precipitation (temperature) field from RegCM4.7 (REMO) and corresponding observed precipitation (temperature) field from nine (eight) stations of UGRB (SRB) are considered. Empirical quantile mapping (inverse function method) method is used. It is seen that each model has a distinct systematic bias relating to both precipitation and temperature means with respect to their corresponding observed means. Applying bias correction methods to the model fields resulted in reducing these mean biases and other errors. These findings illustrate handling and improving the model fields for hydrology, glaciology studies, etc.