Editorial Type:
Article
Article Type:
Research Article

Daily Precipitation over Southern Africa: A New Resource for Climate Studies

R. Layberry University of Sussex, Brighton, United Kingdom

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D. R. Kniveton University of Sussex, Brighton, United Kingdom

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M. C. Todd University College London, London, United Kingdom

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C. Kidd University of Birmingham, Birmingham, United Kingdom

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T. J. Bellerby University of Hull, Hull, United Kingdom

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Print Publication:
01 Feb 2006
DOI:
https://doi.org/10.1175/JHM477.1
Page(s):
149–159
Restricted access

Abstract

This paper describes a new high-resolution multiplatform multisensor satellite rainfall product for southern Africa covering the period 1993–2002. The microwave infrared rainfall algorithm (MIRA) employed to generate the rainfall estimates combines high spatial and temporal resolution Meteosat infrared data with infrequent Special Sensor Microwave Imager (SSM/I) overpasses. A transfer function relating Meteosat thermal infrared cloud brightness temperatures to SSM/I rainfall estimates is derived using collocated data from the two instruments and then applied to the full coverage of the Meteosat data. An extensive continental-scale validation against synoptic station data of both the daily MIRA precipitation product and a normalized geostationary IR-only Geostationary Operational Environmental Satellite (GOES) precipitation index (GPI) demonstrates a consistent advantage using the former over the latter for rain delineation. Potential uses for the resulting high-resolution daily rainfall dataset are discussed.

Corresponding author address: D. R. Kniveton, Department of Geography, University of Sussex, Falmer, East Sussex, BN1 9RH, United Kingdom. Email: kafw3@susx.ac.uk

Abstract

This paper describes a new high-resolution multiplatform multisensor satellite rainfall product for southern Africa covering the period 1993–2002. The microwave infrared rainfall algorithm (MIRA) employed to generate the rainfall estimates combines high spatial and temporal resolution Meteosat infrared data with infrequent Special Sensor Microwave Imager (SSM/I) overpasses. A transfer function relating Meteosat thermal infrared cloud brightness temperatures to SSM/I rainfall estimates is derived using collocated data from the two instruments and then applied to the full coverage of the Meteosat data. An extensive continental-scale validation against synoptic station data of both the daily MIRA precipitation product and a normalized geostationary IR-only Geostationary Operational Environmental Satellite (GOES) precipitation index (GPI) demonstrates a consistent advantage using the former over the latter for rain delineation. Potential uses for the resulting high-resolution daily rainfall dataset are discussed.

Corresponding author address: D. R. Kniveton, Department of Geography, University of Sussex, Falmer, East Sussex, BN1 9RH, United Kingdom. Email: kafw3@susx.ac.uk

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