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Estimation of global temperature fields from scattered observations by a spherical‐wavelet‐based spatially adaptive method

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  • Hee‐Seok Oh
  • Ta‐Hsin Li

Abstract

Summary. The paper considers the problem of estimating the entire temperature field for every location on the globe from scattered surface air temperatures observed by a network of weather‐stations. Classical methods such as spherical harmonics and spherical smoothing splines are not efficient in representing data that have inherent multiscale structures. The paper presents an estimation method that can adapt to the multiscale characteristics of the data. The method is based on a spherical wavelet approach that has recently been developed for a multiscale representation and analysis of scattered data. Spatially adaptive estimators are obtained by coupling the spherical wavelets with different thresholding (selective reconstruction) techniques. These estimators are compared for their spatial adaptability and extrapolation performance by using the surface air temperature data.

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  • Hee‐Seok Oh & Ta‐Hsin Li, 2004. "Estimation of global temperature fields from scattered observations by a spherical‐wavelet‐based spatially adaptive method," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 221-238, February.
    • Handle: RePEc:bla:jorssb:v:66:y:2004:i:1:p:221-238
    DOI: 10.1046/j.1369-7412.2003.05220.x
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    Cited by:

    1. Jean-Baptiste Monnier, 2011. "Nonparametric regression on the hyper-sphere with uniform design," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 412-446, August.

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