NERC Data Catalogue Service
ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from MODIS (2000 - 2019), version 1.0
This dataset contains Daily Snow Cover Fraction of viewable snow from the MODIS satellite instruments, produced by the Snow project of the ESA Climate Change Initiative programme.
Snow cover fraction viewable (SCFV) indicates the area of snow viewable from space over all land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel.
The global SCFV product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.
The SCFV time series provides daily products for the period 2000 – 2019.
The SCFV product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite.
The retrieval method of the snow_cci SCFV product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO. For the SCFV product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 550 nm and 1.6 µm, and an emissive band centred at about 11 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Improvements to the GlobSnow algorithm implemented for snow_cci version 1 include (i) the utilisation of a background reflectance map derived from statistical analyses of MODIS time series replacing the constant values for snow free ground used in the GlobSnow approach, and (ii) the adaptation of the retrieval method for mapping in forested areas the SCFV.
Permanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFV product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable.
The SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.
ENVEO is responsible for the SCFV product development and generation from MODIS data, SYKE supported the development.
There are a few days without any MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2018. On several days in the years 2000 to 2006, and on a few days in the years 2012, 2015 and 2016, the acquired MODIS data have either only limited coverage, or some of the MODIS data were corrupted during the download process. For these days, the SCFV products are available but have data gaps.
Default
Identification info
- Metadata Language
- English (en)
- Dataset Reference Date ()
- 2021-05-10T15:24:50
- Dataset Reference Date ()
- 2021-05-10T15:24:50
- Identifier
- NERC EDS Centre for Environmental Data Analysis / ef8eb5ff84994f2ca416dbb2df7f72c7
- Identifier
- doi / 10.5285/ef8eb5ff84994f2ca416dbb2df7f72c7
- Maintenance and update frequency
- notPlanned
- Update scope
- dataset
- Keywords
- GEMET - INSPIRE themes, version 1.0 ()
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- orthoimagery
- Limitations on Public Access
- otherRestrictions
- Other constraints
- Public data: access to these data is available to both registered and non-registered users.
- Use constraints
- otherRestrictions
- Spatial representation type
- grid
- Topic category
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- Imagery base maps earth cover
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- Begin date
- 2000-02-24T00:00:00
- End date
- 2019-12-31T23:59:59
- Code
- WGS 84
Distribution Information
- Data format
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Data are netCDF formatted.
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Data are netCDF formatted.
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- Resource Locator
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CEDA Data Catalogue Page
Detail and access information for the resource
- Resource Locator
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DOWNLOAD
Download Data
- Resource Locator
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Metsämäki, S., Pulliainen, J., Salminen, M., Luojus, K., Wiesmann, A., Solberg R. and Ripper, E. 2015. Introduction to GlobSnow Snow Extent products with considerations for accuracy assessment. Remote Sensing of Environment, 156, 96–108
No further details.
- Resource Locator
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ESA Land Cover CCI project team; Defourny, P. (2019): ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Land Cover Maps, Version 2.0.7. Centre for Environmental Data Analysis, 13.04.2021
No further details.
- Resource Locator
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Salminen, M., Pulliainen, J., Metsämäki, S., Ikonen, J., Heinilä, K. (2018). Determination of uncertainty characteristics for the satellite-based estimation of fractional snow cover. Remote Sensing Environ., 212, 103-113. https://doi.org/10.1016/j.rse.2018.04.038
No further details.
- Resource Locator
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MODIS Characterization Support Team, MODIS Adaptive Processing System, 2012. Level 1 and Atmosphere Archive and Distribution System (LAADS): MOD03
No further details.
- Resource Locator
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MODIS Characterization Support Team, MODIS Adaptive Processing System, 2012. Level 1 and Atmosphere Archive and Distribution System (LAADS): MOD021KM
No further details.
- Resource Locator
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ESA Climate Change Initiative Website
No further details.
- Resource Locator
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Product User Guide
No further details.
- Resource Locator
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ESA CCI Snow project website
No further details.
- Resource Locator
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ESA CCI Snow key documents
No further details.
- Resource Locator
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CEDA Data Catalogue Page
Detail and access information for the resource
- Resource Locator
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DOWNLOAD
Download Data
- Resource Locator
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Metsämäki, S., Pulliainen, J., Salminen, M., Luojus, K., Wiesmann, A., Solberg R. and Ripper, E. 2015. Introduction to GlobSnow Snow Extent products with considerations for accuracy assessment. Remote Sensing of Environment, 156, 96–108
No further details.
- Resource Locator
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ESA Land Cover CCI project team; Defourny, P. (2019): ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Land Cover Maps, Version 2.0.7. Centre for Environmental Data Analysis, 13.04.2021
No further details.
- Resource Locator
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Salminen, M., Pulliainen, J., Metsämäki, S., Ikonen, J., Heinilä, K. (2018). Determination of uncertainty characteristics for the satellite-based estimation of fractional snow cover. Remote Sensing Environ., 212, 103-113. https://doi.org/10.1016/j.rse.2018.04.038
No further details.
- Resource Locator
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MODIS Characterization Support Team, MODIS Adaptive Processing System, 2012. Level 1 and Atmosphere Archive and Distribution System (LAADS): MOD03
No further details.
- Resource Locator
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MODIS Characterization Support Team, MODIS Adaptive Processing System, 2012. Level 1 and Atmosphere Archive and Distribution System (LAADS): MOD021KM
No further details.
- Resource Locator
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ESA Climate Change Initiative Website
No further details.
- Resource Locator
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Product User Guide
No further details.
- Resource Locator
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ESA CCI Snow project website
No further details.
- Resource Locator
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ESA CCI Snow key documents
No further details.
- Quality Scope
- dataset
Report
- Dataset Reference Date ()
- 2010-12-08
- Statement
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The snow_cci SCFV products from MODIS are based on the MODIS/Terra Calibrated Radiances 5-Min L1B Swath 1km (MOD021KM) and the MODIS/Terra Geolocation Fields 5-Min L1A Swath 1km (MOD03) Collection 6.1 data sets, provided by NASA.
The snow_cci SCF processing chain for MODIS includes the masking of clouds, the identification of certainly snow free areas, and the classification of snow cover fraction per pixel for all remaining observed pixels. Finally, permanent snow and ice areas as well as water bodies are masked in the SCFV products based on the Land Cover CCI map of the year 2000. All SCFV products are prepared according to the CCI data standards.
An automated and a manual quality check was performed on the full time series.
We acknowledge Norsk Regnesentral (Norwegian Computing Center, NR) for downloading the MODIS data from NASA, and UNINETT Sigma2 AS (Sigma2, The Norwegian e-infrastructure for Research & Education) for providing the processing infrastructure for the CRDP generation from MODIS.
Metadata
- File identifier
- ef8eb5ff84994f2ca416dbb2df7f72c7 XML
- Metadata Language
- English (en)
- Character set
- 8-bit variable size UCS Transfer Format, based on ISO/IEC 10646
- Resource type
- dataset
- Metadata Date
- 2022-12-20T00:51:23
- Metadata standard name
- UK GEMINI
- Metadata standard version
- 2.3
