Evaluation of a regional climate model for impact assessment of climate change on crop productivity in the tropics

Regional climate models (RCMs) are considered to be more useful than general circulation models for assessing impacts of climate change scenarios in agriculture. In this communication, the climatic outputs of an RCM–PRECIS (providing regional climates for impact studies) model were analysed by comparing its baseline simulation daily weather data on temperature and precipitation patterns with the observed weather for the corresponding period (1960–1990) in order to find out the bias in the model. Results showed that model could simulate the mean weather parameters on an aggregated scale, but could not satisfactorily represent spatio-temporal variations. There exists a bias towards higher precipitation along with more intense warm and cold events in the baseline simulation. In order to quantify the impacts of the PRECIS model biasness in baseline simulations on crop performance, rice (kharif season) and wheat (rabi season) yields were simulated using the observed weather and the PRECIS baseline weather for several locations representing the Indo-Gangetic Plains. With more extreme weather parameters in the baseline simulated data, the grain yields of rice and wheat were reduced, even causing wheat crop failure in several years as against none observed. The results indicated that using PRECIS baseline daily weather may cause bias in crop performance assessments. Since the bias in baseline will be carried forward in the assessment of future climatic impacts, there is a need to develop more reliable regional climate scenarios for the Indian region.