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TitleValidation of VEGETATION, MODIS, and GOES+SSM/I Snow Cover Products over Canada Based on Surface Snow Depth Observations
DownloadDownloads (Preprint)
LicencePlease note the adoption of the Open Government Licence - Canada supersedes any previous licences.
AuthorSimic, A; Fernandes, RORCID logo; Brown, R; Romanov, P; Park, W M
SourceHydrological Processes; 18, 6, 2003 p. 1089-1104, Open Access logo Open Access
Alt SeriesEarth Sciences Sector, Contribution Series 20043231
Mediapaper; on-line; digital
File formatpdf
Released2003 01 01
AbstractThe ability to accurately map the areal depletion of snow is important for operational decision making (e.g. reservoir management), for correct specification of boundary conditions in Numerical Weather Prediction models, and for modeling atmospheric, hydrological and ecological processes. A number of satellite-derived snow cover products are available in real-time; however, these can differ considerably due to variations in sensor and platform characteristics, data pre-processing methods and the particular snow cover classification algorithms employed. This article evaluated the performance of three daily snow cover products over Canada (1) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover maps provided at 500m spatial resolution for 2001, (2) National Oceanic Atmospheric Administration (NOAA) GOES+SSM/I snow maps provided at 4km resolution for 2001 (~30km resolution SSM/I data were used for cloud covered areas), and (3) SPOT-4 Vegetation (VGT) snow maps derived at 1km resolution for 2000. An evaluation of the snow cover products with daily surface snow depth observations collected from almost two thousand meteorological stations across Canada revealed that the VGT snow product used in this study may not be suitable for snow mapping in Canada due to a significant bias towards mapping snow-free conditions. The MODIS and NOAA products showed similar reasonable levels of agreement ranging from approximately 80% to 100% on a monthly basis. Somewhat lower agreement was found in January suggesting that better correction for tree and surface shadow effects is needed in current snow cover mapping algorithms. The lowest agreement was seen during snow melt mainly in forest areas. Comparison of MODIS agreement statistics between sparse and dense conifer regions indicated that the effect of non-representativenes of surface snow depth observations was on the order of 10% disagreement. The NOAA product was found to be most consistent among land cover types and had the highest percentage of cloud-free pixels.

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