Use of snow cover derived from satellite passive microwave data as an indicator of climate change

To assess future global change, monitoring of the climate system through observation and analysis of seasonal and interannual fluctuations of climate variables is necessary. Cryospheric elements such as snow cover are often seen as sensitive indicators and integrators of basic climate conditions and...

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Bibliographic Details
Published inAnnals of glaciology Vol. 17; pp. 137 - 142
Main Authors Goodison, B.E., Walker, A.E.
Format Journal Article
LanguageEnglish
Published Cambridge, UK Cambridge University Press 1993
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Summary:To assess future global change, monitoring of the climate system through observation and analysis of seasonal and interannual fluctuations of climate variables is necessary. Cryospheric elements such as snow cover are often seen as sensitive indicators and integrators of basic climate conditions and hence an indicator of regional and global change. Snow-cover elements which may serve as signals of variability and change are discussed with respect to the effective use of conventional and remotely sensed information. Conventional data are shown to be effective for assessing questions of temporal variability, but are limited for spatial variability. Passive microwave satellite data make an important contribution by providing spatial and temporal information on snow water equivalent (SWE) and the regional distribution of snowpack extent and state. Use of NIMBUS-7 SMMR (Scanning Multichannel Microwave Radiometer) data to develop a time series of SWE is assessed as a complement to conventional data. Limitations of SMMR coverage compared to DMSP SSM/I (Special Sensor Microwave/Imager) coverage for production of SWE maps for climate change analysis are discussed. Although there are limitations during early season snow cover, information derived from passive microwave data is shown to be able to map and compute the areal coverage of SWE allowing interannual comparison of the amount of water available, the date of peak accumulation and the associated spatial distribution. However, the satellite data record is still too short to establish any definitive trend in snow-cover variability.
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ISSN:0260-3055
1727-5644
DOI:10.3189/S0260305500012738