Abstract
In this paper, we present new methods and estimates of the spatial (horizontal) covariance of the ground-based Global Positioning System Zenith Delay observation errors. An algorithm is developed which enables estimation of the observation error covariance as a linear combination of innovation covariances of Zenith Total Delay (ZTD) at ground-based receiver stations, surface pressure at synoptic stations and integrated water vapour at radiosonde stations, respectively. Innovation (observation minus model background) sequences computed with the High-Resolution Limited Area Model (HIRLAM) are used as statistical material for the estimation.We present a four-parameter exponential observation error covariance model for the ZTD horizontal observation error covariance. Seasonal and yearly mean models are provided for implementation into meteorological data assimilation systems.
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