Climate Change Effects on Spatiotemporal Distribution of Precipitation over West Central India: A Statistical Downscaling Approach

Abstract

The long-term shifts in temperatures and weather patterns are referred to as climate change. Climate change not only leads to long-term shifts in average temperatures but also changes in the spatial and temporal distribution of rainfall over continents. This study aims to predict likely changes in the rainfall pattern induced by climate change over the West Central (WC) region of India. The approach uses a statistical downscaling technique that converts coarse-scale outputs of the global climate model (GCM) to high-resolution future precipitation projections giving refined distribution. The decision support tool that uses a robust statistical downscaling technique viz. statistical downscaling model (SDSM) is used for assessing local climate change impacts.

The research includes the study of likely regional climate variability, by integrating historical observational data and empirical relationships between large-scale climate variables and local weather patterns. Historical data and the SDSM, version 4.2, are employed to forecast future rainfall trends. Rainfall data from the India Meteorological Department and the National Centre for Environmental Prediction (NCEP) from 1961 to 2001 are used along with outputs from general circulation models (GCMs), viz. Hadley Centre coupled model, version 3 (HadCM3), and coupled global climate model, version 3 (CGCM3), for the period 1961–2099. Rainfall scenarios are presented for three future time periods (2011–2040, 2041–2070, and 2071–2099). The study indicates a significant increase in the mean annual precipitation across the West Central India region, particularly in the 2050s and 2080s.

Mean annual rainfall is projected to rise by 10–19.4% under HadCM3 A2 and B2 scenarios. The HadCM3 indicates the month of September as the month of the highest precipitation in later time periods, whereas it is the month of August, according to CGCM3 simulations. When comparing the results of the two models, HadCM3 gives better results, as indicated by better R² value in validation. Thus, the analysis gives climate change-induced likely changes in the spatiotemporal distribution of precipitation over the West Central India region. The insight given by the work will be useful for decision making in many sectors like agriculture, water management, disaster risk reduction, and infrastructure planning.