Dataset
ESA Snow Climate Change Initiative (Snow_cci): Snow Water Equivalent (SWE) level 3C daily global climate research data package (CRDP) (1979 – 2020), version 2.0
Abstract
This dataset contains v2.0 of the Daily Snow Water Equivalent (SWE) product from the ESA Climate Change Initiative (CCI) Snow project, at 0.1 degree resolution.
Snow water equivalent (SWE) indicates the amount of accumulated snow on land surfaces, in other words the amount of water contained within the snowpack. The SWE product time series covers the period from 1979/01 to 2020/05. Northern Hemisphere SWE products are available at daily temporal resolution with alpine areas masked.
The product is based on data from the Scanning Multichannel Microwave Radiometer (SMMR) operated on National Aeronautics and Space Administration’s (NASA) Nimbus-7 satellite, the Special Sensor Microwave / Imager (SSM/I) and the Special Sensor Microwave Imager / Sounder (SSMI/S) carried onboard the Defense Meteorological Satellite Program (DMSP) 5D- and F-series satellites. The satellite bands provide spatial resolutions between 15 and 69 km. The retrieval methodology combines satellite passive microwave radiometer (PMR) measurements with ground-based synoptic weather station observations by Bayesian non-linear iterative assimilation. A background snow-depth field from re-gridded surface snow-depth observations and a passive microwave emission model are required components of the retrieval scheme.
The dataset is aimed to serve the needs of users working on climate research and monitoring activities, including the detection of variability and trends, climate modelling, and aspects of hydrology and meteorology.
The Finnish Meteorological Institute is responsible for the SWE product development and generation.
For the period from 1979 to May 1987, the products are available every second day. From October 1987 till May 2020, the products are available daily. Products are only generated for the Northern Hemisphere winter seasons, usually from beginning of October till the middle of May. A limited number of SWE products are available for days in June and September; products are not available for the months July and August as there is usually no snow information reported on synoptic weather stations, which is required as input for the SWE retrieval. Because of known limitations in alpine terrain, a complex-terrain mask is applied based on the sub-grid variability in elevation determined from a high-resolution digital elevation model. All land ice and large lakes are also masked; retrievals are not produced for coastal regions of Greenland.
This version 2 dataset has some notable differences compared to the v1 data. In v2, passive microwave radiometer data are obtained from the recalibrated enhanced resolution CETB ESDR dataset (MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) https://nsidc.org/pmesdr/data-sets/), the grid spacing is reduced from 25 km to 12.5 km, and spatially and temporally varying snow density fields are used to adjust SWE retrievals in post processing. The output grid spacing is reduced from 0.25-degree to 0.10-degree WGS84 latitude / longitude to be compatible with other Snow_cci products. The time series has been extended by two years with data from 2018 to 2020 added.
The ESA CCI phased product development framework allowed for a systematic analysis of these changes to the input data and snow density parameterization that occurred between v1 and v2 using a series of step-wise developmental datasets. In comparison with in-situ snow courses, the correlation and RMSE of v2 improved 18% (0.1) and 12% (5mm), respectively, relative to v1. The timing of peak snow mass is shifted two weeks later and a temporal discontinuity in the monthly northern hemisphere snow mass time series associated with the shift from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS) in 2009 is removed in v2.
Details
Previous Info: |
No news update for this record
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Previously used record identifiers: |
No related previous identifiers.
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Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s): https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_snow_terms_and_conditions.pdf When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
Data lineage: |
Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA). |
Data Quality: |
For information on data quality see the Snow_cci documentation
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File Format: |
This data product follows CCI Data Standards v2.3, 2021 and are distributed as NetCDF files conforming to Climate and Forecast (CF) convention version 1.9.
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Related Documents
Citations: 1
The following citations have been automatically harvested from external sources associated with this resource where DOI tracking is possible. As such some citations may be missing from this list whilst others may not be accurate. Please contact the helpdesk to raise any issues to help refine these citation trackings.
Moon, T.A., Thoman, R., Druckenmiller, M.L., et al. (2023) The Arctic. Bulletin of the American Meteorological Society 104, S271–S321. https://doi.org/10.1175/bams-d-23-0079.1 https://doi.org/10.1175/bams-d-23-0079.1 |
Process overview
Instrument/Platform pairings
Computation Element: 1
Title | ESA Snow Climate Change Initiative (snow_cci): SWE, v2 |
Abstract | The snow_cci SWE product has been based on the ESA GlobSnow SWE retrieval approach (Takala et al. 2011). The retrieval is based on passive microwave radiometer (PMR) data considering the change of brightness temperature due to different snow depth, snow density, grain size and more. The retrieval algorithm handles data from the sensors SMMR, SSM/I, SSMIS, AMSR-E and AMSR-2. The retrieval methodology combines the satellite passive microwave radiometer (PMR) measurements with ground-based synoptic weather station observations by Bayesian non-linear iterative assimilation. A background snow-depth field from re-gridded surface snow-depth observations and a passive microwave emission model are required components of the retrieval scheme. Improvements to the GlobSnow algorithm implemented for snow_cci version 1 include the utilisation of an advanced emission model with an improved forest transmissivity module and treatment of sub-grid lake ice. Because of the importance of the weather station snow-depth observations on the SWE retrieval, there is improved screening for consistency through the time series. The version 2 dataset has some notable differences compared to the v1 data. In v2, passive microwave radiometer data are obtained from the recalibrated enhanced resolution CETB ESDR dataset (MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) https://nsidc.org/pmesdr/data-sets/), the grid spacing is reduced from 25 km to 12.5 km, and spatially and temporally varying snow density fields are used to adjust SWE retrievals in post processing. The output grid spacing is reduced from 0.25-degree to 0.10-degree WGS84 latitude / longitude to be compatible with other Snow_cci products. The time series has been extended by two years with data from 2018 to 2020 added. SWE products are based on SMMR, SSM/I and SSMIS passive microwave radiometer data for non-alpine regions of the Northern Hemisphere. |
Input Description | None |
Output Description | None |
Software Reference | None |
Output Description | None |
- long_name: Coordinate reference system definition
- var_id: spatial_ref
- names: Coordinate reference system definition
- units: mm
- long_name: Snow Water Equivalent
- var_id: swe
- names: Snow Water Equivalent
- var_id: lat_bnds
- var_id: lon_bnds
- units: mm
- long_name: statistical standard deviation of estimate
- var_id: swe_std
- names: statistical standard deviation of estimate
Co-ordinate Variables
- units: degree_north
- standard_name: latitude
- var_id: lat
- long_name: WGS84 latitude coordinates, center of pixel
- names: latitude, WGS84 latitude coordinates, center of pixel
- units: degree_east
- standard_name: longitude
- var_id: lon
- long_name: WGS84 longitude coordinates, center of pixel
- names: longitude, WGS84 longitude coordinates, center of pixel
- long_name: time
- standard_name: time
- var_id: time
- names: time
Temporal Range
1979-01-02T00:00:00
2020-05-24T23:59:59
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |