Solar Potential in the Himalayan Landscape
Ramachandra T V 1,2,3,*                Gautham Krishnadas 1                Rishabh Jain 1
1 Energy & Wetlands Research Group, Center for Ecological Sciences [CES], 2 Centre for Sustainable Technologies (astra), 3 Centre for infrastructure, Sustainable Transportation and Urban Planning [CiSTUP], Indian Institute of Science, Bangalore, Karnataka, 560 012, India
*Corresponding author:

Data, models and methodology


Data: Surface Meteorology and Solar Energy (SSE) datasets provided by the National Aeronautics and Space Administration (NASA) Langley Research Center derives solar radiation and meteorological data from a variety of earth-observing satellites. The SSE Release 6.0 (accessible at provides 1°x1° (~100 X 100 km) spatial resolution data on a global grid with temporal coverage of solar radiation parameters for 22 years from July 1st, 1983 to June 30th, 2005 obtained from daily 3 hourly satellite measurements for UTC (Coordinated Universal Time) 0, 3, 6, 9, 12, 15, 18, 21 hrs. The GHI data are available as daily, monthly and annual averages [5].

Model: The NASA SSE solar dataset was derived from a physical model based on the radiative transfer theory which states that the solar radiation incident on the earth’s surface is a result of absorption, scattering and reflection of the sun’s incoming radiation. The model demands precise knowledge of solar geometry, satellite calibration and atmospheric composition. It employs a modeled atmosphere along with parameterization of its absorption and scattering properties. Primary inputs to the model include visible and infrared radiation, inferred cloud and surface properties, temperature, precipitable water, column ozone amounts and atmospheric state variables such as temperature and pressure [28]. The parameters were measured using instruments like CERES (Clouds and the Earth’s Radiant Energy System), MODIS (Moderate-resolution Imaging Spectro Radiometer), TOMS (Total Ozone Mapping Spectrometer) etc mounted on GMS, NIMBUS, METEOR, GOES, METEOSAT, NOAA and multifarious satellites. Insolation at a given location on the earth’s surface was inferred based on the shortwave (0.2 to 4um) and longwave (4 to 100um) solar radiation reflected to the satellite sensors from the Top of Atmosphere (TOA). A calculative TOA solar radiation was iteratively compared to the values measured by the satellite sensors. Iterations were carried on parameters like aerosol distribution until the error was within a marginal value. GHI on the surface for each such iteration was computed for different durations [5].

Validation: Shortwave and longwave solar radiation datasets were derived based on primary algorithms by Pinker and Lazlo (1992) and Fu et al (1997) respectively. The quality check algorithms called the Langley Parameterized Shortwave Algorithm (LPSA) and Downward Longwave Algorithm by Gupta et al [29, 30] validates the primary algorithms. All the released datasets in SSE have undergone validation based on these four algorithms [31]. The derived solar radiation parameters were validated with Baseline Surface Radiation Network (BSRN) and RMSE of 10.25 % were observed for GHI. The meteorological parameters were validated with information from National Climate Data Center (NCDC).


Data: The National Renewable Energy Laboratory (NREL) and the Atmospheric Sciences Research Center (ASRC) at the State University of New York (SUNY)/Albany developed satellite based solar radiation data for India in collaboration with its Ministry of New and Renewable Energy (MNRE). They furnished 0.1° X 0.1° (~ 10 X 10 km) higher spatial resolution data from half hourly satellite measurements of January 2002 to December 2008 made available in their web-portal (

Model: The solar radiation data was derived from the SUNY satellite-to-irradiance model developed by Perez et al [32]. This semi-empirical model has characteristics of physical models (like that employed by NASA SSE) in addition to regression analyses on quality surface measurements.  The model is based on the observation that shortwave atmospheric transmissivity is linearly related to the earth’s planetary albedo captured as satellite image-pixel counts. These image-pixels are normalized by the cosine of solar zenith angle and location specific cloud indices are generated. For each location, the GHI is derived from the cloud index based on extraterrestrial normal incident values, solar zenith angle, elevation, elevation-corrected air mass and certain additional parameters. The model output is fit to high quality surface measurements at distinct geographic locations for correction and validation.

Apart from solar geometry and cloud cover, aerosol composition significantly influences the GHI. Aerosol Optical Depth (AOD) a unit-less measure of the aerosol induced solar attenuation, is considered as an indispensable input to the SUNY model. Reports of higher aerosol concentrations across India and studies on their temporal variability demanded monthly AOD values to be input. These detailed AOD values were developed based on available satellite and ground data [33].  

Validation: The SUNY model enhanced with analytical and numerical methods were employed for North and Central America. Later on, the methodology was adapted for Central Asia based on European Meteosat 5 and 7 geostationary satellites. The model run for Northwest India was validated with measurements provided by IMD, NASA SSE as well as NREL’s ~40 km resolution Climatological Solar Radiation (CSR) data. The SSE and CSR data were used for quality check of the 10 km NREL-SUNY data [34]. The model enhanced with monthly AOD values and adopted for the entire geography of the country needs further validation with quality controlled ground measurements.

Citation : Ramachandra. T.V., Gautham Krishnadas and Rishab Jain, 2012. Solar Potential in the Himalayan Landscape., International Scholarly Research Network, ISRN Renwable Energy, Volume 2012, 13 pages.
* Corresponding Author :
  Dr. T.V. Ramachandra
Energy & Wetlands Research Group, Centre for Ecological Sciences, Indian Institute of Science, Bangalore – 560 012, India.
Tel : 91-80-23600985 / 22932506 / 22933099,      Fax : 91-80-23601428 / 23600085 / 23600683 [CES-TVR]
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