Abstract

Relationships between snow cover and atmospheric dynamics are difþcult to isolate because of the complex nature of their interaction. While regional snow cover patterns can be altered radically by a single cyclonic event, the presence or absence of terrestrial snow cover can also greatly influence passing weather systems. A consistent time series of snow cover data, covering an extensive spatial area, at a synoptically sensitive temporal resolution is therefore required to examine potential relationships between surface snow conditions and atmospheric variables. Snow water equivalent (SWE) derived from Special Sensor Microwave/Imager (SSM/I) passive microwave data þts these requirements because of all weather imaging capabilities, broad spatial resolution, wide swath width, and frequent revisit time. The applicability of these data to examining relationships between snow cover and atmospheric dynamics is evaluated in this paper through a comparative study of two winter seasons currently available in the appropriate grid format: December, January and February (DJF) 1988/89 and 1989/90. Five‐day average (pentad) SWE imagery derived from SSM/I brightness temperatures using the Atmospheric Environment Service's (AES) dual channel algorithm is analyzed along with gridded National Meteorological Center (NMC, now National Center for Environmental Prediction, NCEP) atmospheric data. Principal components analysis is used to isolate within variable relationships, while time lagged cross correlation analysis is used to identify between variable relationships. Results indicate that both these data and the methodology show great potential for developing an SWE/atmospheric climatology, although integration of a wet snow indicator, also developed by AES, would strengthen the snow cover product. Further discussion regarding the future use of SSM/I derived SWE data for studying snow cover/atmospheric interaction is also presented.

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