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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Publications at this Location » Publication #305922
Title: Climate change scenarios of surface solar radiation in data sparse regions: a case study in Malaprabha River Basin, India

Author
item AAVUDAI, ANANDHI - Kansas State University
item V.V., SRINIVAS - Indian Institute Of Science
item KUMAR, D. NAGESH - Indian Institute Of Science
item NANJUNDIAH, R.S. - Indian Institute Of Science
item Gowda, Prasanna

Submitted to: Climate Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/12/2014
Publication Date: 5/7/2014
Citation: Aavudai, A., V.V., S., Kumar, D., Nanjundiah, R., Gowda, P. 2014. Climate change scenarios of surface solar radiation in data sparse regions: a case study in Malaprabha River Basin, India. Climate Research. 59:259-270.

Interpretive Summary: Solar radiation plays an important role in hydrological processes. The lack of observed solar radiation in developing countries limited our ability to estimate future solar radiation scenarios for climate change impact studies. Also, there are no clear guidelines to derive future solar radiation scenarios for regions where data is either measured but sparse or not measured. In this study, we developed a guidance on how different methods of estimating future solar radiation scenarios under different circumstances and discussed in detail.

Technical Abstract: A variety of methods are available to estimate future solar radiation (SR) scenarios at spatial scales that are appropriate for local climate change impact assessment. However, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. Three methodologies to guide the estimation of SR are discussed in this study, namely: Case 1: SR is measured, Case 2: SR is measured but sparse and Case 3: SR is not measured. In Case 1, future SR scenarios are derived using several downscaling methodologies that transfer the simulated large-scale information of global climate models to a local scale (measurements). In Case 2, the SR was first estimated at the local scale for a longer time period using sparse measured records, and then future scenarios were derived using several downscaling methodologies. In Case 3: the SR was first estimated at a regional scale for a longer time period using complete or sparse measured records of SR from which SR at the local scale was estimated. Finally, the future scenarios were derived using several downscaling methodologies. The lack of observed SR data, especially in developing countries, has hindered various climate change impact studies. Hence, this was further elaborated by applying the Case 3 methodology to a semi-arid Malaprabha reservoir catchment in southern India. A support vector machine was used in downscaling SR. Future monthly scenarios of SR were estimated from simulations of third-generation Canadian General Circulation Model (CGCM3) for various SRES emission scenarios (A1B, A2, B1, and COMMIT). Results indicated a projected decrease of 0.4 to 12.2 W m-2 yr-1 in SR during the period 2001-2100 across the 4 scenarios. SR was calculated using the modified Hargreaves method. The decreasing trends for the future were in agreement with the simulations of SR from the CGCM3 model directly obtained for the 4 scenarios.