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Space–time calibration of radar rainfall data
Author(s) -
Brown Patrick E.,
Diggle Peter J.,
Lord Martin E.,
Young Peter C.
Publication year - 2001
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/1467-9876.00230
Subject(s) - radar , context (archaeology) , computer science , weather radar , calibration , series (stratigraphy) , remote sensing , covariance , data set , multivariate statistics , computation , meteorology , data mining , geography , algorithm , mathematics , statistics , artificial intelligence , machine learning , geology , telecommunications , paleontology , archaeology
Motivated by a specific problem concerning the relationship between radar reflectance and rainfall intensity, the paper develops a space–time model for use in environmental monitoring applications. The model is cast as a high dimensional multivariate state space time series model, in which the cross‐covariance structure is derived from the spatial context of the component series, in such a way that its interpretation is essentially independent of the particular set of spatial locations at which the data are recorded. We develop algorithms for estimating the parameters of the model by maximum likelihood, and for making spatial predictions of the radar calibration parameters by using realtime computations. We apply the model to data from a weather radar station in Lancashire, England, and demonstrate through empirical validation the predictive performance of the model.