Inter-Research > CR > v59 > n3 > p259-270  
CR
Climate Research


via Mailchimp

CR 59:259-270 (2014)  -  DOI: https://doi.org/10.3354/cr01180

Climate change scenarios of surface solar radiation in data sparse regions: a case study in Malaprabha River Basin, India

Aavudai Anandhi1,6, V. V. Srinivas1, D. Nagesh Kumar1,2,*, Ravi S. Nanjundiah3,4, Prasanna H. Gowda5

1Department of Civil Engineering, Indian Institute of Science, Bangalore 560 012, India
2Center for Earth Sciences, Indian Institute of Science, Bangalore 560 012, India
3Centre for Atmospheric & Oceanic Sciences, Indian Institute of Science, Bangalore 560012, India
4Divecha Centre for Climate Change, Indian Institute of Science, Bangalore 560012, India
5USDA-ARS Conservation & Production Research Laboratory, Bushland, Texas 79012, USA
6Present address: Department of Agronomy, Kansas State University, Manhattan, Kansas 66506, USA
*Corresponding author. Email:

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.


KEY WORDS: Downscaling · Modified Hargreaves and Donatelli-Bellocchi methods · Support vector machine · SVM · IPCC SRES scenarios · Cloud cover downscaling


Full text in pdf format
Supplementary material
Cite this article as: Anandhi A, Srinivas VV, Nagesh Kumar D, Nanjundiah RS, Gowda PH (2014) Climate change scenarios of surface solar radiation in data sparse regions: a case study in Malaprabha River Basin, India. Clim Res 59:259-270. https://doi.org/10.3354/cr01180

Export citation
Share:    Facebook - - linkedIn

 Previous article