This paper introduces two copula-based interpolation methods to produce air temperature maps in a data-scarce area: a spatial copula interpolator including covariates, and a mixed copula interpolator. Daily mean air temperature was used from weather stations and ERA_Interim reanalysis weather data at 174 locations in the Qazvin Plain, Iran. The results showed an improved performance of the new methods to describe both spatial variability and co-variability between variables. The methods are potentially useful for other sparsely and irregularly distributed weather data.
copula, interpolation, covariate, data scarce, air temperature
Date made available | 1 Nov 2018 |
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Publisher | DANS |
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Temporal coverage | 1 Jun 2014 - 30 Jun 2014 |
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Date of data production | 8 Aug 2018 |
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