Mapping random and systematic errors of satellite-derived snow water equivalent observations in Eurasia

James Foster, Chaojiao Sun, Jeffrey P. Walker, Richard Kelly, Jairui Dong, Alfred Chang

Research output: Contribution to journalConference articleOther

Abstract

Passive microwave sensors onboard satellites can provide global snow water equivalent (SWE) observations day or night, even under cloudy conditions. However, there are both systematic (bias) and random errors associated with the passive microwave measurements. While these errors are well known, they have thus far not been adequately quantified. In this study, unbiased SWE maps, random error maps and systematic error maps of Eurasia for the 1990-1991 snow season (November-April) have been examined. Dense vegetation, especially in the taiga region, and large snow crystals (+~ 0.3 mm in radius), found in areas where the temperature/vapor gradients are greatest, (in the taiga and tundra regions) are the major source of systematic error. Assumptions about how snow crystals evolve with the progression of the season also contribute to the errors. In general, while random errors for North America and Eurasia are comparable, systematic errors are not as great for Eurasia as those observed for North America. Understanding remote sensing retrieval errors is important for correct interpretation of observations, and successful assimilation of observations into numerical models.

Original languageEnglish
Article number26
Pages (from-to)150-158
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5568
DOIs
Publication statusPublished - 1 Dec 2004
Externally publishedYes
EventRemote Sensing for Agriculture, Ecosystems, and Hydrology VI - Maspalomas, Spain
Duration: 14 Sep 200416 Sep 2004

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