Abstract
Although regional climate models (RCMs) provide more reliable results for a regional impact study of climate change,however a considerable bias still exists that needs to be corrected before they are used for climate change research. In this study two correction functions using two methods viz. modified difference approach and linear scaling method were applied for local bias correction of Tmax. Tmin and rainfall data at monthly scales and validated to minimize the bias between the modelled (HAD GEM2-ES-GCM) and observed climate data at Ludhiana, Punjab.Correction functions derived using linear scaling method at monthly time scale for Tmax, Tmin and rainfall were found to be better than modified difference approach for bias correction of the weather data to bring it to close to observed data.
Highlights
GEM2-ES-GCM) and observed climate data at Ludhiana, Punjab.Correction functions derived using linear scaling method at monthly time scale for Tmax, Tmin and rainfall were found to be better than modified difference approach for bias correction of the weather data to bring it to close to observed data
The seven year (2010-2016) observed, modelled and corrected by both the correction functions are presented in Table 1, while dailycomparisons are mode with linear scaling methods and presented in Fig. 1 to 3 for temperature and rainfall
Correction functions for Tmax and Tmin based on linear scaling method were developed based on equations 3 and 4 for each of the calendar month
Summary
Two simple methods (1) modified difference approach and (2) linear scaling method have been used for local bias correction of temperature and rainfall. Where T (uncor) is the uncorrected daily temperature for a scenario, T (obs) and T (mod) is the observed and modelled daily temperature obtained from the baseline scenario. In this equation an over bar denotes the average over the considered period. The linear scaling method aims to perfectlymatch the monthly mean of corrected values with that of observed ones (Lenderink et al 2007). It operates with monthly correction values based on the differences between observed and raw data (raw GCM simulated data in this case). Precipitation is typically corrected with a multiplier and temperature with an additive term on a monthly basis.The multipliers and additives are based on the formulas given under linear scaling which are:
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