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|
|Temporal coverage||1 Jun 2014 - 30 Jun 2014|
|Date of data production||8 Aug 2018|