Future climate change scenario in hot semi-arid climate of Saurashtra, Gujarat by using statistical downscaling by LARS-WG model
Keywords:Climate change, LARS-WG model, Weather data generation, GCMs, Semi-arid climate of Saurashtra.
Climate change is considered to be the greatest challenge faced by mankind in the twenty first century which can lead to severe impacts on different major sectors of the world such as water resources, agriculture, energy and tourism and are likely to alter trends and timing of precipitation and other weather drivers. Analyses and prediction of change in critical climatic variables like rainfall and temperature are, therefore, extremely important. Keeping this in mind, this study aims to verify the skills of LARS-WG (Long Ashton Research - Weather Generator), a statistical downscaling model, in simulating weather data in hot semi-arid climate of Saurashtra and analyze the future changes of temperature (maximum and minimum) and precipitation downscaled by LARS-WG based on IPCC SRA2 scenario generated by seven GCMs' projections for the near (2011-2030), medium (2046-2065) and far (2080-2099) future periods. Rajkot (22.3° N, 70.78° E) observatory of IMD, representing hot semi-arid climate of Saurashtra, Gujarat state was chosen for this purpose. Daily rainfall, maximum and minimum temperature data for the period of 1969-2013 have been utilized.
LARS-WG is found to show reasonably good skill in downscaling daily rainfall and excellent skill in downscaling maximum and minimum temperature. The downscaled rainfall indicated no coherent change trends among various GCMs’ projections of rainfall during near, medium and far future periods. Contrary to rainfall projections, simulations from the seven GCMs have coherent results for both the maximum and minimum temperatures. Based on the ensemble mean of seven GCMs, projected rainfall at Rajkot in monsoon season (JJAS) showed an increase in near future, i.e., 2011-2030, medium future (2046-2065) and far future (2080-2099) periods to the tune of 2, 11 and 14% respectively compared to the baseline value. Model studies indicating tropospheric warming leading to enhancement of atmospheric moisture content could be the reason for this increasing trend. Further, at the study site summer (MAM) maximum temperature is projected to increase by 0.5, 1.7 and 3.3°C during 2011-2030, 2046-2065 and 2080-2099 respectively and winter (DJF) minimum temperature is projected to increase by 0.8, 2.2 and 4.5 °C during 2011-2030, 2046-2065 and 2080-2099 respectively.
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