Bias correction techniques for meteorological data of A2 scenario climate model output in Chao Phraya River Basin of Thailand

Abstract

Statistical and dynamic methods were used in the downscaling process from Global Climate Model (GCM) to Regional Climate Model (RCM). We selected the European Centre for Medium-Range Weather Forecasts model, Hamburg version 4 (ECHAM4) with 300 × 300 km resolution for A2 scenario. We focused on SE Asia domain located between 20°S to 30°N and 80°E to 135°E for 1960-2099 with wind components, temperature, geo-potential height, and specific humidity as data input in Providing Regional Climates for Impacts Studies (PRECIS) RCM analysis. The downscaling process output was 50 km resolution for 1971-2010 and precipitation, temperature, wind, relative humidity, radiation from 8 meteorological stations in Chao Phaya River Basin; Lampang, Suphanburi, Nan, Sisamrong, Takfa, Chainat, Uthong and Bangna selected and used for bias correction. Three methods, namely 1) adjusting the mean based on RCM, 2) adjusting the mean based on observation, and 3) quantile-based mapping were used. Methods were compared using observed climatic data, RCM outputs of calibration period, and RCM outputs from the validation period. RSME was found to be lower for method 2 compared to other methods implying a relatively superior technique for improving the model. As such method 2 was used to correct the PRECIS products during 2001-2009. These products are useful in the studies of impact of climate change and for early warning systems in Thailand.