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Estimating fine scale ground solar radiation from GIS-modelled and historical meteorological records

Kumar, Lalit and Singh, Anirudh (2008) Estimating fine scale ground solar radiation from GIS-modelled and historical meteorological records. UNSPECIFIED.

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      Abstract

      Solar radiation is a critical driver of many processes on the earth’s surface. In fields such as micrometeorology, environmental science and climatology the estimation of the thermic action of the relief and the calculation of the radiative budget of the surfaces constitute an important prerequisite for any modelling work. Unlike rainfall it is difficult or almost impossible to measure solar radiation at a few sights and interpolate this to estimate the values at other locations due to the high dependence of solar radiation on topography. GIS-based solar radiation models allow us to take into account, on a fine scale, the complexity of the interactions between the incident solar radiation (direct as well as diffuse) and the local topography. Such models provide a rapid, cost-efficient and accurate estimation of radiation over large areas, while considering slope and aspect gradients, and shadowing effects. While GIS-based models predict the potential direct (and in some cases diffuse) radiation and are able to predict quite accurately the relative spatial variation, for a number of applications the actual and not the potential solar radiation is needed. This is especially so for micrometeorological and evapotranspiration related studies. This paper discusses the correlation between the GIS modelled radiation and the actual recorded data and presents regression equations that can be used to convert modelled radiation for use in other environmental models that utilize field recorded solar radiation data. The impacts of different climatic conditions as well as seasons on the regression equations are discussed. Analysis of daily meteorological records spanning eight years for a number of stations around Australia show that the correlations are quite high (r2 = 0.95) when the data is pooled and higher still (r2 = 0.98) when seasonal effects are taken into consideration.

      Item Type: Other
      Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
      Q Science > Q Science (General)
      Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
      Depositing User: Anirudh Singh
      Date Deposited: 11 Feb 2013 14:55
      Last Modified: 11 Feb 2013 14:55
      URI: http://repository.usp.ac.fj/id/eprint/5545
      UNSPECIFIED

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