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A new analytical model for temperature predictions

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  • Njau, Ernest C.

Abstract

A new analytical model for predicting surface air temperature as well as (solar-derived) heat energy variations is described. This model, which can be used for global or regional heat/temperature predictions, is much simpler than general circulation models (GCMs) and requires relatively less computer power to the extent that it can be implemented on a simple personal computer. The usefulness and accuracy of the new model are ascertained through sample predictions made for equatorial regions from 1982 to 2009. The new model offers a cheaper alternative for implementing global and regional predictions which have been almost exclusively done through GCMs. Fortunately, this cheaper alternative is easily affordable even by individual departments/universities in developing countries which have been unable to implement locally any of the current GCMs due to the latter's high computer power demand and intricacy.

Suggested Citation

  • Njau, Ernest C., 1997. "A new analytical model for temperature predictions," Renewable Energy, Elsevier, vol. 11(1), pages 61-68.
    • Handle: RePEc:eee:renene:v:11:y:1997:i:1:p:61-68
    DOI: 10.1016/S0960-1481(96)00121-8
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    References listed on IDEAS

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    1. Tasadduq, Imran & Rehman, Shafiqur & Bubshait, Khaled, 2002. "Application of neural networks for the prediction of hourly mean surface temperatures in Saudi Arabia," Renewable Energy, Elsevier, vol. 25(4), pages 545-554.
    2. Njau, Ernest C., 2000. "A new patterning of atmospherically absorbed solar energy," Renewable Energy, Elsevier, vol. 20(2), pages 135-143.

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