spatial statistics, covariance function, weather forecasting, random field
Abstract:
We introduce a flexible parametric family of matrix-valued covariance functions for multivariate spatial random fields, where each constituent component is a Matern process. The model parameters are interpretable in terms of process variance, smoothness, correlation length, and co-located correlation coefficients, which can be positive or negative. Both the marginal and the cross covariance functions are of the Matern type. In a data example on error fields for numerical predictions of temperature and pressure over the Pacific Northwest, we compare the Matern model to the traditional linear model of coregionalization.
Dieser Datensatz wurde nicht während einer Tätigkeit an der Universität Mannheim veröffentlicht, dies ist eine Externe Publikation.
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