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D. T. Price, D. W. M. I. A. N. M. F. Hutchinson, and J. L. Kestesen, “A comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data,” Agricultural and Forest Meteorology, vol. 101, p. 14, 2002.

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Article

The Influence of Air Temperature Controls in Estimation of Air Temperature over Homogeneous Terrain

1Malaysian Meteorological Department, Jalan Sultan 46667 Petaling Jaya, Selangor, Malaysia

2Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor, Malaysia


Applied Ecology and Environmental Sciences. 2014, Vol. 2 No. 6, 141-145
DOI: 10.12691/aees-2-6-3
Copyright © 2014 Science and Education Publishing

Cite this paper:
Fariza Yunus, Jasmee Jaafar, Zamalia Mahmod, Nursalleh K Chang. The Influence of Air Temperature Controls in Estimation of Air Temperature over Homogeneous Terrain. Applied Ecology and Environmental Sciences. 2014; 2(6):141-145. doi: 10.12691/aees-2-6-3.

Correspondence to: Jasmee  Jaafar, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor, Malaysia. Email: jasmee@salam.uitm.edu.my

Abstract

Variation of air temperature from one place to another is caused by air temperature controls. In general, the most important control of air temperature is elevation. Another significant independent variable in estimating air temperature is the location of meteorological stations. Distance to coastline as well as land use type also contributes to significant variations in the air temperature. On the other hand, in homogeneous terrain direct interpolation of discrete points of air temperature work well to estimate air temperature values in un-sampled areas. In this process the estimation is solely based on discrete points of air temperature. However, this study presents that air temperature controls also play significant roles in estimating air temperature over the homogenous terrain of Peninsular Malaysia. An Inverse Distance Weighting (IDW) interpolation technique was adopted to generate continuous data of air temperature. This study compared two different datasets, observed mean monthly data of T, and estimation error of T–T’, where T’ is the estimated value from a multiple regression model. The multiple regression model considered eight independent variables. They are elevation, latitude, longitude, coastline, and four land use types consisting of water bodies, forest, agriculture and build up areas to represent the role of air temperature controls. Cross validation analysis was conducted to review the accuracy of the estimated values. Final results show that the estimated values of T–T’ produced lower errors for mean monthly mean air temperature over homogeneous terrain in Peninsular Malaysia.

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