Published April 3, 2019
| Version v1
Dataset
Open
Global Seasonal Mountain Snow Mask from MODIS MOD10A2
- 1. University of North Carolina at Chapel Hill
- 2. Ohio State University
- 3. University of Washington
- 4. University of California Santa Barbara
Description
Seasonal Mountain Snow (SMS) mask derived from MODIS MOD10A2 snow cover extent and GTOPO30 digital elevation model produced at 30 arcsecond spatial resolution.
Three datasets are provided: the Seasonal Mountain Snow mask (MODIS_mtnsnow_classes), a seasonal snow cover classification (MODIS_snow_classes), and cool-season cloud percentages (MODIS_clouds). The classification systems are as follows:
MODIS_snow_classes:
- 0: Little-to-no snow
- 1: Indeterminate due to clouds
- 2: Ephemeral snow
- 3: Seasonal snow
MODIS_mtnsnow_classes:
- 0: Mountains with little-to-no snow
- 1: Indeterminate due to clouds
- 2: Mountains with ephemeral snow
- 3: Mountains with seasonal snow
MODIS_clouds
- 0: < 5% of clouds during the cool season (defined Oct.-Mar. for Northern Hemisphere and Apr.-Sep. for Southern Hemisphere)
- 1: 5% cool-season days with cloud cover
- 2: 10% cool-season days with cloud cover
- 3: 20% cool-season days with cloud cover
- 4: 30% cool-season days with cloud cover
- 5: 40% cool-season days with cloud cover
- 6: 50% cool-season days with cloud cover
For manuscript "Characterizing biases in mountain snow accumulation from global datasets" submitted to WRR
Notes
See manuscript for additional details.
Wrzesien, M. L., Pavelsky, T. M., Durand, M. T., Dozier, J., & Lundquist, J. D. ( 2019). Characterizing biases in mountain snow accumulation from global datasets. Water Resources Research, 55. https://doi.org/10.1029/2019WR025350