This data set is only available for a restricted user group, please contact us if you want to access these data.
RESTRICTED only accessable in ZMAW net or via CliSAP login What does that mean?
Reflectance and radiance observations obtained with the Moderate Resolution Imaging Spectroradiometer (MODIS) at its bands 4 ( 0.55µm) and 6 (1.6µm) can be used to calculate the Normalized Difference Snow Index (NDSI) which is a measure of the snow cover at the surface.
This NDSI can be used together with a regression to obtain the fractional snow cover (FSC). The data offered here belong to MODIS Collection 006. For this newest release of the MODIS snow cover data set the regression is not applied (unlike done in Collection 005) for reasons detailed in the Users Guide. Users are invited to compute the FSC on their own by taking the regression from the ATBD.
Influence of vegetation, sensor viewing angle, solar illumination, and clouds are taken into account. Collection 006 snow cover data benefit from a number of revisions to both input data and algorithm design as described in the Users Guide. More details can be found in the documents listed in the references listed below.
Last data set update at ICDC: November 6, 2020
|NDSI snow cover||% (0 ... 100)||monthly & daily|
|Percentage clear-sky fraction||% (0 ... 100)||daily|
|Percentage cloud fraction||% (0 ... 100)||daily|
|Quality flag||none||monthly & daily|
Period and temporal resolution:
- Monthly: 2000-03 to 2020-09
- Daily: 2000-02-24 to 2020-09-30
(2000/08, 2001/06, 2002/03, 2003/12, and 2016/02 are missing)
(2003-04-08, and 2016-02-18 to 2016-02-28 are missing)
Coverage and spatial resolution:
- Spatial resolution: 0.05° x 0.05°, cartesian grid
- Geographic latitude: -89.975°N to 89.975°N
- Geographic longitude: -179.975°E to 179.975°E
- Dimension: 7200 columns x 3600 rows
- Altitude: following terrain
- NetCDF (at ICDC)
- HDF (at NSIDC)
The quality flags included in the data set give qualitative information about the quality of the NDSI snow cover retrieval (very good, good, ok, ...). In addition these flags inform about the cloud cover; particularly the latter is important for the monthly product because it does not contain separate maps about cloud cover like the daily product does. The quality flags are included in both the daily and monthly product but are more detailed in the daily one.
The daily product contains in addition maps about the percentage clear-sky fraction and about the percentage cloud fraction. This information has to be taken into account when interpreting the snow cover product. A retrieval of the NDSI is only possible in clear-sky areas.
ICDC / CEN / University of Hamburg
email: stefan.kern (at) uni-hamburg.de
NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449
email: nsidc (at) nsidc.org
- Algorithm Theoretical Basis Document (ATBD)
- Riggs, G. A., et al., Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records. Earth Syst. Sci. Data, 9, 765-777, https://doi.org/10.5194/essd-9-765-2017, 2017.
- Riggs, G. A., and D. K. Hall, MODIS Snow Products Collection 6 User Guide, 11 Dec. 2015, 66 pp.
- Masson, T., et al., 2018, An assessment of existing methodologies to retrieve snow cover fraction from MODIS data. Remote Sensing, 10(4), 619, http://doi.org/10.3390/rs10040619.
- Hall, D. K., J. L. Foster, D. L. Verbyla, A. G. Klein, and C. S. Benson, 1998, Assessment of snow cover mapping accuracy in a variety of vegetation cover densities in Central Alaska. Rem. Sens. Environ., 66, 129-137.
- Hall, D. K., and G. A. Riggs, 2011, Normalized-difference snow index (NDSI). Encyclopedia of Earth Sciences Series, Encyclopedia of Snow, Ice and Glaciers, doi:10.1007/978-90-481-2642-2_376.
- Salomonson, V. V., and I. Appel, 2004, Estimating fractional snow cover from MODIS using the normalized difference snow index (NDSI). Rem. Sens. Environ., 89, 351-360.
- Salomonson, V. V., and I. Appel, 2006, Development of the AQUA MODIS NDSI fractional snow cover algorithm and validation results. Trans. Geosci. Rem. Sens., 44(7), 1747-1756.
- Nolin, A. W., 2010, Recent advances in remote sensing of seasonal snow. J. Glaciol., 56(200), 1141-1150.
- Xin, Q., et al., 2012, View angle effects on MODIS snow mapping in forests. Rem. Sens. Environ., 118, 50-59.
Please cite usage of this data as follows:
Hall, D. K. and G. A. Riggs. 2016. MODIS/Terra Snow Cover Daily L3 Global 0.05Deg CMG, Version 6. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/MODIS/MOD10C1.006 [last accessed: November 2, 2020].
If the monthly instead of the daily data are used, then please replace "Daily" by "Monthly" and "MOD10C1" by "MOD10CM".
In the acknowledgement: Converted into netCDF file format at and provided by the Integrated Climate Data Center (ICDC, icdc.cen.uni-hamburg.de), University of Hamburg.