Snow Dataset Inventory

Here is an inventory of satellite-derived, in situ, and analysis/reanalysis snow datasets, compiled by the Snow Watch Team. This inventory is provided in three categories: (1) Satellite-derived snow products and datasets, (2) Analyses, reanalyses, and reanalysis-driven snow products and datasets, and (3) In-situ snow products and datasets. To update or add datasets, please email Ross Brown (ross.brown at canada.ca).

You may select more than one dataset type.

Showing 58 of 58 results
Product(s) Type Organization Description Period Areal Coverage Resolution Variables Frequency Data Sources Comments References Dataset Location Contact
CryoClim Multi-Sensor Snow Cover Product satellite ESA, Norwegian Computing Centre, Norwegian Met. Inst. Combined optical and microwave fusion with SCE estimation based on Hidden Markov Model approach 1982- Northern Hemisphere 5 km snow / no snow Daily, monthly, annual SMMR, SSM/I, AVHRR GAC An update of the dataset will take place in 2015/16 together with a more comprehensive validation http://www.cryoclim.net http://www.cryoclim.net/cryoclim/subsites/data_portal/ Rune Solberg (rune.solberg@nr.no)
Cryoland PanEuropean Fractional Snow Extent Product satellite ESA, ENVEO Snow cover fraction estimated from NDSI thresholding Nov 2000- Pan-European Domain; 35-72 deg. N 11-50 deg. E ~500 m Fractional Snow Cover and uncertainty Daily (latency < 1 day) MODIS (VIIRS; Sentinel-3) Some misclassification of patchy snow in spring/summer related to MODIS Cloud Product; larger uncertainties in rugged terrain as only one band is used in the snow cover calculations not specified http://cryoland.eu Thomas Nagler (Thomas.nagler@enveo.at)
EURACSnowAlps satellite Institute for Applied Remote Sensing, EURAC, Bolzano, Italy Higher resolution snow cover estimates from MODIS using topographic correction for MODIS bands 2002- European Alpine Arch (43-48 deg. N, 5-15 deg. E) 250 m Fractional snow cover Daily MODIS, band 1 (RED) and band 2 (NIR) (for snow) Improved mapping of snow in mountain regions compared to standard MODIS products especially patchy snow; Topographic correction cannot eliminate completely shadow effect in very steep slope especially during the morning acquisition (TERRA);Some limitations in detecting snow in forested areas; Some misclassification of snow-cloud Notarnicola et al. (2013) webgis.eurac.edu/snowalps/ Claudia Notarnicola (claudia.notarnicola@eurac.edu)
European Alps AVHRR SE dataset satellite Remote Sensing Research Group, University of Bern, Switzerland 1 km snow extent climatology for the Alpine region derived from AVHRR data over the period 1985-2011 1985-2014 European Alps + Europe 1 km snow / no snow AVHRR Hüsler et al (2014), Hüsler, et al (2012) http://www.geography.unibe.ch/content/forschungsgruppen/fernerkundung/forschung/globsnow/index_eng.html Stefan Wunderle (Stefan.wunderle@giub.unibe.ch)
Global 4KM Multisensor Automated Snow/Ice Map Product (GMASI) satellite NOAA NESDIS Combined optical and microwave retrievals with recurrent gap filling to maintain data continuity 2006- Global 4 km snow / no snow Daily MetOp AVHRR, MSG SEVIRI, GOES Imager and DMSP SSMIS http://www.star.nesdis.noaa.gov/smcd/emb/snow/documents/Global_Auto_Snow-Ice_4km_ATBD_February_2014.pdf Maps: http://satepsanone.nesdis.noaa.gov/; Data: contact PI Peter Romanov (peter.romanov@noaa.gov)
GlobSnow Snow Extent satellite ESA, Finnish Meteorological Institute (FMI) Estimation of fractional snow covered area from SCAmod algorithm 1995- Northern Hemisphere 0.01 deg Fractional Snow Cover Daily; weekly; monthly ERS-2/ATSR-2 and EnviSat/AATSR Global daily coverage not possible due to narrow swath width of AATSR; snow cover fraction may be overestimated over very dense forest due to low reflectance dynamics Metsämäki et al. 2015 http://www.globsnow.info Sari Metsämäki (sari.metsamaki@ymparisto.fi)
GlobSnow SWE satellite ESA, Finnish Meteorological Institute (FMI) Combination of climate station snow depth observations and forward microwave emission model simulations with SMMR and SSM/I satellite passive microwave data. Version 3.0 includes several enhancements: (1) inclusion of lake ice; (2) revised modelling of forest canopy Tb; (3) enhanced surface obs and QC. A V3 bias-corrected version includes corrections based on snow s 1979- Northern Hemisphere 25 km SWE Daily; weekly; monthly SMMR; SSM/I; AMSR-E; SSM/I-S Evaluation with surface obs over Eurasia gave an RMSE of 30 to 40mm for SWE values below 150 mm; systematically underestimates SWE for snowpacks > 150 mm; SWE masked out over areas with complex topography, glaciers and ice sheets. The above issues are corrected in the V3 bias-corrected version of the dataset. Takala et al., 2011; Pulliainen et al. 2020 http://www.globsnow.info Kari Luojus (kari.luojus@fmi.fi)
GRACE satellite NASA JPL, German Space Agency, ESA, University of Texas at Austin Area-averaged estimates of terrestrial water storage anomalies (snow + ice + soil + ground water) March 2002- Global 1x1 deg. and 4X4 deg. grids Water storage anomalies (depth) monthly Requires expert knowledge to use these data correctly. See Frappart et al (2011) and Forman et al (2012) for examples of GRACE applications related to snow water storage. Landerer and Swenson, (2012) Grace Products: http://podaac.jpl.nasa.gov/grace Felix.W.Landerer@jpl.nasa.gov
Japanese Global Snow Cover Extent for Climate Dataset (GHRM5C) satellite JAXA (Japan Aerospace Exploration Agency) Estimate of global SCE from 5 channels of AVHRR and MODIS to create climate record from 1979 1979-2013 Global 0.05 deg snow / no snow / wet snow Daily, weekly, monthly AVHRR (1979-2000), MODIS (2000-2013) Higher resolution coverage than NOAA CDR product; Discriminates between dry and wet snow; Some missing months in 1980, 1981, 1994, 1995, 2001; Values over Antarctic are not valid; degraded performance in dense forest, cold desert and high mountains not specified http://kuroshio.eorc.jaxa.jp/JASMES/index.html Masahiro Hori (EORC/JAXA) (hori.masahiro@jaxa.jp)
JAXA AMSR2 Snow Products satellite JAXA Rosenkrantz (1998) (11 yr RAOB + RT) 2012- Near-global (daily) 10 & 25 km, swath Snow Cover, SWE, SD Daily AMSR2 (18, 36, 10 23 GHz) http://gcom-w1.jaxa.jp (V1 product) Richard Kelly (rejkelly@uwaterloo.ca)
MEaSUREs Northern Hemisphere Terrestrial Snow Cover Extent Daily 25km EASE-Grid 2.0 satellite NSIDC Snow cover presence/absence from three satellite sources plus a merged source estimate 1999-2012; MODIS in 2000-2012 period Northern Hemisphere 25 km snow cover presence/absence daily IMS, MODIS Collection 5 Cloud Gap Filled Snow Cover, PMW brightness temperature, merged estimate Robinson et al (2014). NSIDC. DOI: 10.5067/MEASURES/CRYOSPHERE/nsidc-0530.001 ; http://nsidc.org/data/docs/measures/nsidc-0530/index.html#data_description ftp://sidads.colorado.edu/pub/DATASETS/nsidc0530_MEASURES_nhsnow_daily25/ Hall, Robinson and Mote nsidc@nsidc.org
MEaSUREs Northern Hemisphere Terrestrial Snow Cover Extent Weekly 100km EASE-Grid 2.0 satellite NSIDC Snow cover presence/absence from two satellite sources plus a merged source estimate 1966-2012; PMW in 1979-2012 period Northern Hemisphere 100 km Snow cover presence/absence weekly NOAA-CDR, PMW brightness temperature, merged estimate Robinson et al (2014). NSIDC. DOI: 10.5067/MEASURES/CRYOSPHERE/nsidc-0531.001; http://nsidc.org/data/docs/measures/nsidc-0531/index.html#data_description ftp://sidads.colorado.edu/pub/DATASETS/nsidc0531_MEASURES_nhsnow_weekly100/ Robinson and Mote; nsidc@nsidc.org
MODIS MODSCAG Products satellite NASA JPL Snow cover fraction estimated from spectral mixture analysis MODSCAG method March 2000- Global Snow cover fraction (%) Research Dataset TERRA, AQUA Painter et al. (2009) http://snow.jpl.nasa.gov/portal/browse/dataset/urn:snow:MODSCAG Tom Painter (Tom.Painter@jpl.nasa.gov)
MODIS Snow Products Collection 6 satellite NASA Goddard Snow cover fraction estimated from the spectral characteristics of reflected solar energy. Daily data are cloud gap filled. Terra: 24 Feb 2000; Aqua: 4 July 2007- Global 500 m swath; 0.05 by 0.05 deg. Snow cover fraction (%), cloud persistence count, QA assessment day, 8-day, month MODIS bands 1,2,4,6 More accurate mapping of spring and summer snow cover in mountainous areas achieved by removing the surface temperature screen Hall, D. K., V. V. Salomonson, and G. A. Riggs, 2006. NSIDC Dorothy Hall (Dorothy.K.Hall@nasa.gov)
NASA Airborne Snow Observatory (ASO) satellite NASA Gridded snow depth data at 3-meter and 50-meter resolutions derived from airborne light detection and ranging (lidar) measurements of surface elevations; derived gridded SWE from 50-meter resolution snow depths Various flight times from 3 April 2013 to 16 July 2019 River basins in the western United States 3-meter and 50-meter Snow depth, estimated SWE, snow albedo Various times NSIDC Painter et al. (2016) https://nsidc.org/data/aso/data-summaries NSIDC user services
NASA Prototype AMSR-E satellite NASA Combination of numerical techniques, snow emission modeling and climatology 2002-2011 Northern Hemisphere 25 km SWE Daily; monthly AMSR-E Marco Tedesco (cryocity@gmail.com)
NASA Standard AMSR-E satellite NASA 19 and 37 GHz Tb difference; enhancements for vegetation and grain size evolution; distinction between shallow and deep snow 2002-2011 Northern Hemisphere 25 km SWE Daily; pentad; monthly AMSR-E, AMSR2 Kelly, 2009 http://nsidc.org/data/docs/daac/ae_swe_ease-grids.gd.html Marco Tedesco (cryocity@gmail.com)
NOAA AMSR2 Snow Products satellite NOAA Variation of NASA AMSR-E methodology 2014- Global 25 km Snow Cover, Depth, SWE Daily AMSR2 This is a new set of products that is generated routinely at CIMSS/University of Wisconsin, but will not be operational in NOAA until later in 2015 Yong-Keun Lee (yklee@ssec.wisc.edu) or Jeff Key (jeff.key@noaa.gov)
NOAA-CDR satellite Rutgers University, NOAA, NCDC 89 x 89 Polar Stereographic grid (190.5 km spacing) 1966; Some missing months in 1966-1971 period Northern Hemisphere 190.5 km snow presence/absence based on 50% snow cover threshold (weekly); snow cover duration fraction % (monthly) weekly, monthly Mainly visible imagery (VHRR, AVHRR, VISSR, VAS); Based on IMS 24 km from June 1999- Data extensively used for climate monitoring (e.g. IPCC, BAMS State of Climate), model evaluation and snow cover-climate studies. Mainly recommended for continental-hemispheric scale studies. Changes in charting procedures and satellite resolution and frequency have occurred over time that impact data homogeneity e.g. anomalous trends in autumn and summer SCE (Brown and Derksen 2013; Mudryk et al. 2014). Note that the monthly snow cover fraction is a duration fraction not an areal fraction. Robinson et al. (2012) NOAA National Climatic Data Center. doi: 10.7289/V5N014G9; Robinson et al. (1993); Estilow et al. (2013) http://climate.rutgers.edu/snowcover/ David Robinson (david.robinsonrobins@rci.rutgers.edu); Thomas Estilow (thomas.estilowesti@rci.rutgers.edu)
Theia Snow Product satellite CNES, CESBIO Snow cover presence or absence Nov-15 Western Alps, Pyrenees, Atlas (to be extended to European mountains) 20 m snow and cloud presence or absence 5 to 10 days Sentinel-2 Real-time data production scheduled to start in December 2017 Gascoin, Simon, & Grizonnet, Manuel. (2017). Algorithm theoretical basis documentation for an operational snow cover extent product from Sentinel-2 and Landsat-8 data. Retrieved from http://tully.ups-tlse.fr/grizonne theia.cnes.fr Simon Gascoin (simon.gascoin@cesbio.cnes.fr)
US National Ice Center Operational Global Snow Products (IMS) satellite NIC Trained analyst interpretation of satellite imagery and derived mapped products IMS 24 km 1997-, IMS 4 km 2004-, IMS 1 km 2015- Northern Hemisphere, Global 1 km, 4 km, 24 km snow /no snow Daily AVHRR, MODIS, GOES, SSMI, as well as derived mapped products (USAF Snow/Ice Analysis, AMSU, AMSR-E, NCEP models, etc.) and surface observations Ramsay 1998; Helfrich et al. 2007 http://www.natice.noaa.gov/ims/ Sean Helfrich (sean.helfrich@noaa.gov)
20CR (V2) reanalysis NCEP Derived snow cover information from 4-layer Noah LSP model based on assimilating only surface pressure reports with observed; monthly sea-surface temperature and sea-ice distributions as boundary conditions. 1871-2012 Gobal 2 deg. SD, snow cover fraction 3-hourly, daily, monthly; Note: 20CR includes the mean and spread from 56 ensemble members Updated annually Peings et al. (2013) found 20CR provided realistic simulations of snow cover onset variability over Eurasia. Compo et al (2011) http://www.esrl.noaa.gov/psd/data/gridded/data.20thC_ReanV2.html Gil Compo, Research Scientist, CIRES University of Colorado compo@colorado.edu
Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis reanalysis Env. and Climate Change Canada Optimal interpolation of real-time snow depth obs with first guess field generated by a snow model forced with analyzed air temp and forecast precip (Brasnett, 1999). Mean monthly SWE estimated from mean mly snow depth using mly mean snow density look-up table by snow-climate region (Brown and Mote, 2009) Aug 01 1998 - July 31 2014 NH land area subset of global output corresponding to the 1024x1024 grid used by the IMS-24km product The native resolution of the global analysis is ~35 km. The NH subset archived at NSIDC is interpolated to a 24 km Polar Stereographic grid Daily SD, monthly average estimated SWE daily, monthly average Research subset over NH updated annually. Will be replaced in 2015 with a high resolution land data assimilation scheme using in situ and satellite obs. Contains discontinuity in 2007 due to change in precip forecast. Quality assessment and error notes included in the online documentation at NSIDC. Brown, Ross D. and Bruce Brasnett. 2010, updated annually. Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data. Environment Canada, 2010. Boulder, Colorado USA: National Snow and Ice Data Center. http://nsidc.org/data/nsidc-0447 Ross Brown (rdbrown@videotron.ca)
CanSISE reanalysis Env. and Climate Change Canada Gridded terrestrial SWE (average and spread) from 5 SWE products: GlobSnow V2, ERA-Interim/Land, MERRA, Crocus snowpack model driven by ERA-Interim, and GLDAS SWE product. See Mudryk et al. (2015) for a description of datasets and intercomparison results. 1981-2010 NH 1 deg. SWE (avg, spread) daily Static Provides an indication of the uncertainty in SWE from the spread in the 5 datasets. The multi-dataset average is typically more strongly correlated with surface observations than any single dataset. The gridding process created an artificial gradient around coastlines that can be removed by setting a minimum SWE threshold ~5-10 mm. Mudryk, L. R. and C. Derksen. 2017. CanSISE Observation-Based Ensemble of Northern Hemisphere Terrestrial Snow Water Equivalent, Version 2. [Indicate subset used]. Boulder, Colorado USA. NSIDC: National Snow and Ice http://nsidc.org/data/NSIDC-0668 Lawrence Mudryk, Env. and Climate Change Canada, lawrence.mudryk@canada.ca
CFSR - Climate Forecast System Reanalysis reanalysis NCEP 3DVAR assimilation using snow simulated by Noah 4-layer land surface process model, SWE obs from US Air Force daily snow depth analysis and snow cover analysis from IMS. 1979-2010; Version 2 updates from 2011 Global 0.5 deg. Snow cover, SD, SWE Hourly, 6-hourly, monthly Ongoing. 1-2 month delay. Klehmet et al. (2013) found CFSR to underestimate SWE over most of Siberia compared to GlobSnow and surface observations. Saha et al. (2010) http://rda.ucar.edu/pub/cfsr.html; http://rda.ucar.edu/datasets/ds093.1/ http://cfs.ncep.noaa.gov/cfsr/
ERA-40 reanalysis ECMWF Assimilation of surface snow depth observations where available. Background field generated by LSP model driven by forecast fields (Douville et al. 1995). 1957-2002 Global 2.5 deg. SWE, snow melt, snow sublimation, snowfall 6-hourly, daily, monthly Replaced by ERA-interim Snow depth observations between 1992 and 1994 inadvertently omitted from analysis. Khan et al. (2008) found reasonable agreement with surface obs over Russia. Uppala et al. (2005) http://apps.ecmwf.int/datasets/data/era40_daily/ http://www.ecmwf.int/
ERA5 reanalysis ECMWF Assimilation of surface snow depth observations. NOAA IMS-4km SCE assimilated from 2004. Background field generated by H-TESSEL land surface scheme (de Rosnay et al. 2014). 1981- Global 30 km SCF, SWE, depth, density, evaporation, snowmelt, albedo, snowfall, snow layer temperature hourly, monthly Ongoing with back extension to 1950 Discontinuity in 2004 with assimilation of IMS-4km snow cover extent (Orsolini et al. 2019; Mortimer et al. 2020) Hersbach et al. (2020) Copernicus Climate Data Store, https://cds.climate.copernicus.eu http://www.ecmwf.int
ERA5-Land reanalysis ECMWF Statistical downscaling of ERA5 fields to H-TESSEL land surface scheme (Dutra et al. 2020). 1981- Global 9 km SCF, SWE, depth, density, evaporation, snowmelt, albedo, snowfall, snow layer temperature hourly, monthly Ongoing with back extension to 1950 No known issues. Corrects the discontinuity in ERA5 snow. Muñoz Sabater (2019) Copernicus Climate Data Store, https://cds.climate.copernicus.eu http://www.ecmwf.int
ERA-Interim reanalysis ECMWF Assimilation of surface snow depth observations where available. NOAA IMS-24km SCE assimilated from 2003. Background field generated by LSP model driven by forecast fields (Douville et al. 1995). 1979-2019 Global 0.75 deg. SWE, snow density, snow melt, snow sublimation, snow albedo, snow temperature, snowfall 6-hourly, daily, monthly Ended August 2019 Documented problems with the in situ snow depth assimilation from 2003-2010. The Cressman analysis method creates unrealistic spatial patterns in mountainous and data sparse regions. Dee et al. (2011) http://apps.ecmwf.int/datasets/data/interim_full_daily/ http://www.ecmwf.int/
ERA-interim/Land reanalysis ECMWF HTESSEL land surface model driven by ERA-Interim + GPCP v2.1 adjustments 1979-2010 Global 80 km Snow water equivalent, albedo, density 6-hourly Superseded by ERA5/Land Balsamo et al., 2013 http://apps.ecmwf.int/datasets/data/interim_land/ Gianpaolo Balsamo gianpaolo.balsamo@ecmwf.int
GLDAS-1 (Noah, Vic, Mosaic and CLM LSMs) reanalysis Suite of land surface models driven offline by GLDAS-1 output 1979-2020 Global 1 x 1 deg. SWE, snow melt, snowfall rate (additional snow variables for the Vic simulation) 3-hourly, monthly Decommissioned June 2020 "GLDAS-1 forcing data sources were switched several times, over the record from 1979 to present, which introduced unnatural trends and resulted in highly uncertain forcing fields in 1995-1997". (Rui and Beaudoing 2014) NASA, Rodell et al., 2004; Online Documentation (Rui 2011): ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/GLDAS_V1/README.GLDAS.pdf http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings http://ldas.gsfc.nasa.gov/gldas/
GLDAS-2.0 Reanalysis (Noah LSM) reanalysis Noah land surface model driven offline by GLDAS-2 forced with the global meteorological data set from Princeton University (Sheffield et al., 2006). 1948-2014 Global 0.25 x 0.25 deg. SWE, SD, snow melt, snowfall rate, snow sfc temp 3-hourly, monthly Infrequent updates Abnormally high SWE values over Greenland and other points with conditions conducive to land ice formation. These need to be masked out. NASA, Rodell et al., 2004 ; Online documentation (Rui and Beaudoing 2014): http://hydro1.sci.gsfc.nasa.gov/data/s4pa/GLDAS/README.GLDAS2.pdf http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings http://ldas.gsfc.nasa.gov/gldas/
JRA-25 reanalysis JMA 3D-Var data assimilation. Incorporates snow depth from SYNOP reports plus additional historical data from China. Snow cover extent from NOAA weekly product used prior to 1987; SSM/I-derived snow depth and snow cover used from 1987. 1979-2004 Global ~120 km SWE, SD, snowfall 6-hourly, monthly Replaced by JRA-55 Snow mass is not represented explicitly in the analysis. A constant snow density of 200 kg/m3 is assumed. Analyzed snow depths over Siberia prior to winter 1982/83 are too low due to omission of snow depth obs. See Onogi et al (2007) Section 4.1.2 for documentation of other snow-related issues in the analysis. Khan et al. (2008) found JRA-25 underestimated SD over most of the main Russian river basins. Onogi et al. (2007) Data support no longer provide by JMA; Data archived at UCAR; http://rda.ucar.edu/datasets/ds625.0/ Dave Stepaniak (303-497-1343). davestep@ucar.edu
JRA-55 reanalysis JMA 4D-Var data assimilation. Includes the same snow data sources as JRA-25 plus additional snow depth data over USA, Russia and Mongolia 1958-2012 Global ~60 km SWE, SD 3-hr, 6-hr, daily, monthly Static Ebita et al (2011) http://jra.kishou.go.jp/JRA-55/index_en.html 3-hr, 6-hr and daily: http://rda.ucar.edu/datasets/ds628.1/; Monthly means and variances: http://rda.ucar.edu/datasets/ds628.1/ Dave Stepaniak (303-497-1343). davestep@ucar.edu
Liston and Hiemstra (2011) reanalysis UCAR/NCAR SnowModel driven by 10 km downscaled MERRA output. Incorporates SnowTran blowing snow model. 1979-2009 NH land area north of ~55N 10 km SWE Daily One-off research dataset No land/sea mask provided. SWE set to zero over water points. Liston and Hiemstra, 2011 http://data.eol.ucar.edu/codiac/dss/id=106.309 Glen Liston, (Glen.Liston@colostate.edu)
MERRA Reanalysis (Catchment LSM) reanalysis NASA Catchment land surface model driven by MERRA's AGCM (3DVAR assimilation of mainly satellite-derived atmospheric variables and surface pressure obs) 1979-2016 Global 0.5 x 0.67 deg. Snowfall, SWE, SD, Snow sfce and layer temps, Snowmelt, Fractional snow covered area Variables available at hourly, synoptic, daily, and monthly averaging periods Replaced by MERRA-2 No evidence of major discontinuities in SWE over the period NASA, Rienecker et al., 2011 http://disc.sci.gsfc.nasa.gov/daac-bin/DataHoldings.pl merra-questions@lists.nasa.gov
MERRA-Land Reanalysis (Catchment LSM with enhanced precip forcing) reanalysis NASA Catchment land surface model driven by MERRA's AGCM (3DVAR assimilation of mainly satellite-derived atmospheric variables, surface pressure obs and precipitation) 1979-2016 Global 0.5 x 0.67 deg. Snowfall, SWE, SD, Snow sfce and layer temps, Snowmelt, Fractional snow covered area Variables available at hourly, synoptic, daily, and monthly averaging periods Replaced by MERRA-2 This version of MERRA-land contains a discontinuity in SWE related to changes to precip forcing (RDB). Does not perform as well as MERRA or MERRA-2 (Reichle et al. 2017). NASA, Reichle et al. 2011 Data: http://disc.sci.gsfc.nasa.gov/daac-bin/DataHoldings.pl Variable definitions: http://gmao.gsfc.nasa.gov/products/documents/MERRA_File_Specification.pdf Rolf Reichle, (rolf.h.reichle@nasa.gov; merra-questions@lists.nasa.gov)
MERRA-2 Reanalysis reanalysis NASA SWE diagnosed from MERRA, 2 fields with multilayer, physical snow pack model 1980- Global 0.5 x 0.625 deg. Snowfall, SWE, SD, Snow sfce and layer temps, Snowmelt, Fractional snow covered area Variables available at hourly, synoptic, daily, and monthly averaging periods Typically updated 2-3 weeks after the end of the month Performance comparable to MERRA and ERA-Interim Land. Brown et al. (2018) found MERRA-2 ability to capture interannual variability in maximum annual SWE over southern Quebec was degraded compared to MERRA. NASA, Gelaro et al. 2017; Reichle et al. (2017) https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/data_access/ https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/diag_feedback.php
NARR reanalysis NCEP Based on the Noah land surface process model and assimilated snow depths from US Air Force daily snow depth analysis 1979-2014 North America 32 km SD, SWE, snow cover fraction, snow melt, albedo 3hr, daily, monthly Static Found to greatly underestimate maximum SWE compared to Brown et al. (2003) historical analysis. Mesinger et al. (2006) 3-hourly data: ftp://ftp.cdc.noaa.gov/Datasets/NARR/ http://www.emc.ncep.noaa.gov/mmb/rreanl/
NCEP/DOE (NCEP Reanalysis 2 reanalysis NCEP Similar to Reanalysis-1 but allows snow accumulation from dynamic snow model. 1979- Global 1.875 deg. SWE 6 hours Updated annually Found to overestimate winter SWE cf GlobSnow over Siberia in period prior to 2001 and to underestimate from 2001 (Klehmet et al. 2013). Khan et al. (2008) report poor results over Russia for 1979-2004 period. Kanamitsu et al (2002) http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis2.gaussian.html http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis2.html
NCEP/NCAR (NCEP Reanalysis 1) reanalysis NCEP 3D-Var assimilation using snow cover from NESDIS weekly charts. Snow cover capped at 100 mm. 1948- Global 1.875 deg. SWE 6 hours Updated daily Snow fields not recommended for various reasons. See Khan et al. (2008) and Klehmet et al. (2013). Kalnay et al. (1996) http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.surfaceflux.html http://www.esrl.noaa.gov/psd/data/reanalysis/reanalysis.shtml
NLDAS LSM reanalysis NASA Mosaic, Vic, Noah and SAC LSMs forced with output from NLDAS-2 1979- North America 0.125 deg. SD, SWE, snow cover fraction, snow melt, sublimation Hourly, monthly Sheffield et al. (2003), Pan et al. (2003), Livneh et al. (2010), Rui and Mocko (2014) http://ldas.gsfc.nasa.gov/nldas/NLDAS2model_download.php David Mocko David.Mocko@nasa.gov
SNODAS (SNOw Data Assimilation System); NSIDC G02158 reanalysis NWS/NOHRSC Output from snow modelling and data assimilation system run at NOHRSC. Incorporates satellite data, surface observations, and output from physical snowpack model. 30 Sept 2003- Contiguous US and southern Canada up to 58.23 deg N 30 arc seconds SWE, SD, Snowmelt Runoff, Snowpack temperature, Sublimation, Solid/Liquid Precipitation NSIDC archives fields representing the model state for 06:00 Universal Time (UTC). Operational product SNODAS has varying spatial coverage over southern Canada. For eastern Canada, coverage is non-existent up to 2010, extends up to 50 deg N in 2011 and 2012, then extends to 58.23 deg N from 2013. National Operational Hydrologic Remote Sensing Center. 2004. Snow Data Assimilation System (SNODAS) Data Products at NSIDC, Boulder, Colorado USA: National Snow and Ice Data Center. http://dx.doi.org/10.7265/N5TB14TC http://nsidc.org/data/docs/noaa/g02158_snodas_snow_cover_model/ Andy Rost (andy.rost@noaa.gov)
Canadian Historical Snow Depth Data insitu Env. and Climate Change Canada Mainly manual ruler observations (average of several measurements in open area free of drifting snow), but with more frequent SR50-equipped autostation observations in the period since ~2000. 1883-2017; Pan-Canadian coverage after ~1955 Canada Variable spatial coverage; peak of ~2000 stations in 1980s; most data located south of ~55N SD from manual ruler or SR50 sensor-equipped autostations daily Variable number of stations over time; peak of ~2000 stations in 1980s; rapid decline in station numbers after 1995. Dataset not updated regularly Observations are made at open, grassed sites, often at airports, that may not be representative of snow conditions in the prevailing land cover. Manual ruler observations report systematically more snow than SR50 sensors. Brown and Braaten (1998), Brown et al. (2021). Dataset will be published on the Government of Canada Open Data site. Daily snow depth observations can also be downloaded from https://climate-change.canada.ca/climate-data/#/daily-cl Ross Brown (rdbrown@videotron.ca)
Canadian Historical Snow Survey Data insitu Env. and Climate Change Canada Mainly manual snow measurements of SWE from gravimetric method (MSC snow sampler) with snow pillow observations from mountainous region of western Canada 1928-2017 Canada Variable density; network peaks at ~2000 surveys in period 1965-1985; most data located south of ~55N Average SD and SWE from 5-10 point snow course bi-weekly; observations tend to be concentrated in the 2nd half of the snow season to capture annual maximum SWE Relatively few snow courses with 30+ years of continuous measurements. Dataset not regularly updated. Due to proprietary data restrictions post-1985 observations from Quebec are not included in the dataset. These data were included in a 0.1 degree lat/long box average version of the data for the period 1950-2016. Braaten (1998), Brown et al. (2019) https://open.canada.ca/data/en/dataset/f57afb37-90c7-4ff0-a757-ba792a4f40a1 Ross Brown (rdbrown@videotron.ca)
Chinese historical daily snow depth data insitu China Meteorological Administration, National Meteorological Information Manual observations of daily snow depth from ruler 1951-2014 updated annually China 212 stations (GTS stations) SD daily The length of station record varies across the 212 stations but the majority of stations have more than 50 years of data in the period since 1950. SD is reported to nearest cm. SD is set to 32700 for trace values (SD < 0.5 cm) and 32766 for missing values. Data format is described in a Readme file included in the dataset. Some stations from the tropical regions of China have entirely zero snow depths. ftp://ccrp.tor.ec.gc.ca/pub/RBrown/China_Snow_Data Zhifu Zhang (zzfrain@126.com); Yu Yu (yuyu@cma.gov.cn)
French Alpine snow data, insitu Meteo-France Snow depth, snow properties and climate observations from mountain stations run by Meteo-France partners for avalanche risk monitoring 1971- French Alps 156 stations snowfall, SD, liquid water content of snowpack, snowpack density, information on snow grain size 12 hours Operational program https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=94&id_rubrique=32 http://www.meteofrance.com/contact
Global Historical Climate Network - Daily (GHCN-D) insitu NOAA NCDC Daily snow depth observation from various sources subject to a common set of QC protocols. 1763- Mainly countries reporting real-time snow depth observations to the WMO GTS/WIS Spatial coverage highly variable in space and time; most dense coverage over NH mid-latitudes SD, snowfall, SWE; other climate variables such as temperature, precipitation and pressure are also included in the dataset daily Station numbers vary in time. Data updated in near real-time Menne et al (2012) ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/ http://www1.ncdc.noaa.gov/pub/data/ghcn/daily/ http://www.ncdc.noaa.gov/oa/climate/ghcn-daily/
Integrated Surface Database (ISD) insitu NCDC The Integrated Surface Database (ISD) consists of global hourly and synoptic observations compiled from numerous sources into a single common ASCII format and common data model. ISD integrates data from over 100 original data sources, including numerous data formats that were key-entered from paper forms during the 1950s–1970s time frame. http://www.ncdc.noaa.gov/isd 1902- Global ~20,000 station; NH coverage most dense over mid-latitudes SD, snowfall sub-daily, daily Smith et al (2011) http://www.ncdc.noaa.gov/isd/data-access http://www.ncdc.noaa.gov/contact
Morphometric Characteristics of Ice and Snow in the Arctic Basin: Aircraft Landing Observations from the Former Soviet Union, 1928-1989, NSIDC G02140 insitu NSIDC 1928-1989 200 stations max. SD, snow cover, density http://nsidc.org/data/g02140
Russian Historical Snow Depth Data insitu RIHMI-WDC Manual obs of daily snow depth (avg of readings from 3 fixed stakes) 1881- Russia and Former Soviet Union 600 stations - higher density of coverage over European sector SD; snow cover fraction daily Continuous measurements at most stations. Updated annually. Bulygina et al (2011) http://meteo.ru/english/climate/snow.php Natalia Korshunova (nnk@meteo.ru)
Russian Historical Snow Survey Data insitu RIHMI-WDC Manual snow surveys 1966- Russia and Former Soviet Union 517 stations - higher density of coverage over European Sector snow cover fraction, SD, SWE, ice crust presence and thickness; observations at both open and vegetated survey lines at some sites 1-3 times per month (typically every 10 days) Continuous measurements at most stations. Updated annually. Bulygina et al (2011) http://meteo.ru/english/climate/snow1.php Natalia Korshunova (nnk@meteo.ru)
SCAN Network insitu Natural Resources Conservation Service (NRCS) of US Dept. of Agriculture Automated soil moisture/temperature stations with other climatic parameters including precipitation and air temperature. Snow depth and SWE at some sites 1991- Across the USA and Puerto Rico and US Virgin Islands 221 SWE, SD at some sites. Mostly soil moisture/temperature and climatic parameters Hourly, daily, 7-day, Monthly Online data updated in near real-time National soil moisture and soil temperature network http://www.wcc.nrcs.usda.gov/scan/ http://www.wcc.nrcs.usda.gov/webmap/index.html Mike Strobel (michael.strobel@por.usda.gov)
SNOlite insitu Natural Resources Conservation Service (NRCS) of US Dept. of Agriculture Automated snow depth and snow water equivalent network across the western USA and Alaska in support of water resource and flood management. Basic sites have a snow depth and temperature sensor. 2012- Concentrated in mountains of western USA and Alaska 22 sites Snow depth and other climatic observations Hourly,daily, 7-day, Monthly Online data updated in near real-time These data compliment SNOTEL observations and replace manual/aerial observation points http://www.wcc.nrcs.usda.gov/snow/ http://www.wcc.nrcs.usda.gov/webmap/index.html Mike Strobel (michael.strobel@por.usda.gov)
SNOTEL (Snow Telemetry) insitu Natural Resources Conservation Service (NRCS) of US Dept. of Agriculture Automated snow depth and snow water equivalent network across the western USA and Alaska in support of water resource and flood management. Basic sites have a snow pillow, precipitation gauge and temperature sensor. 1979- Concentrated in mountains of western USA and Alaska 853 Snow depth, SWE; additional climate observations, soil moisture and temperate at most sites Hourly,daily, 7-day, Monthly Online data updated in near real-time NRCS data interface provides mainly single site access. Serreze et al (1999) developed a QCd compilation of SNOTEL data covering 1980-1998 period but it is not known if this dataset has been updated. http://www.wcc.nrcs.usda.gov/snow/ http://www.wcc.nrcs.usda.gov/snow/snotel-wedata.html Mike Strobel (michael.strobel@por.usda.gov)
Snow Survey of Great Britain insitu British Glaciological Society (1945-1953), Met Office (1953-2007) Manual observation of the elevation of the local snowline (> 50% snow cover) 1945-2007 The data for Scotland are digitised; Great Britain data still paper records 145 stations in digitized dataset for Scotland Snowline elevation Daily (Oct-May) Not all stations reported each year or for whole record Example of data use: https://scottishsnow.wordpress.com/2014/11/09/derrylodge/ Spencer et al (2014) http://badc.nerc.ac.uk/ Mike Spencer (m.spencer@ed.ac.uk)
USDA snow courses insitu Natural Resources Conservation Service (NRCS) of US Dept. of Agriculture Manually measured snow courses in the Western US, Canada, and Alaska 1935-- Concentrated in mountains of western USA, Canada and Alaska 1,111 courses SWE, SD Monthly from January to June Online data updated monthly Data used for monthly water supply forecasts http://www.wcc.nrcs.usda.gov/snow/ http://www.wcc.nrcs.usda.gov/webmap/index.html Mike Strobel (michael.strobel@por.usda.gov)
Western Italian Alps Monthly Snowfall and Snow Cover Duration, NSIDC G01186 insitu NSIDC Monthly snowfall amounts and monthly snow cover duration in days 1877-1996 18 stations. Available stations range from 565 meters to 2720 meters in elevation. Snow cover duration monthly The period of record varies with each station, with the longest station record including data from 1877 to 1996. The average station record duration is approximately 61 years. Mercalli and Castellano ( 1999) http://nsidc.org/data/g01186

Last updated 11 December 2020

AATSR Advanced Along Track Scanning Radiometer (ESA)
AMSR-2 Advanced Microwave Scanning Radiometer on JAXA GCOM-W1 spacecraft, launched May 18, 2012. This instrument is currently operating.
AMSR-E Advanced Microwave Scanning Radiometer on NASA's EOS Aqua spacecraft, launched May 4, 2002. The instrument stopped rotating Oct 4, 2011.
AMSU Advanced Microwave Sounding Unit
ATSR-1/2 Along-Track Scanning Radiometer on ERS-1/2 (ESA)
Aqua One of the two NASA MODIS satellites. The local equatorial crossing time is approximately 1:30 p.m. in an ascending node.
AVHRR Advanced Very High Resolution Radiometer (NOAA, NESDIS)
AVHRR GAC Global Area Coverage (reduced resolution image data processed onboard the satellite)
CDR Climate Data Record
CMC Canadian Meteorological Centre (Environment Canada)
ECMWF European Centre for Medium-Range Weather Forecasts
EnviSat Environmental Satellite (ESA)
EOS Earth Observing System (NASA)
ERS-1/2 European Remote Sensing satellite (ESA)
ESA European Space Agency
FMI Finnish Meteorological Institute
GCOM-W1 Global Change Observation Mission – Water (JAXA)
GOES Geostationary Operational Environmental Satellite system (NOAA, NESDIS)
GRACE Gravity Recovery and Climate Experiment (NASA, German Aerospace Center)
IMS Interactive Multisensor Snow and Ice Mapping System (NOAA, NESDIS)
INTAS-SCCONE International Association for the promotion of co-operation with scientists from the New Independent States of the former Soviet Union — Snow Cover Changes Over Northern Eurasia
JAXA Japan Aerospace Exploration Agency
JMA Japan Meteorological Agency
MetOp Series of three polar orbiting meteorological satellites operated by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT).
MODIS Moderate Resolution Imaging Spectroradiometer (NASA)
MODSCAG MODIS Snow Covered Area and Grain Size method for snow cover fraction retrieval
MSG SEVIRI Spinning Enhanced Visible and Infrared Imager on the Meteosat Second Generation satellite (ESA)
NASA National Aeronautics and Space Administration (US)
NASA Goddard NASA Goddard Space Flight Center, Greenbelt, MD (US)
NASA JPL NASA Jet Propulsion Laboratory, Pasadena, CA (US)
NCAR National Center for Atmospheric Research (US)
NCDC National Climatic Data Center (NOAA, US)
NCEP National Centers for Environmental Prediction (NOAA, US)
NESDIS National Environmental Satellite, Data, and Information Service (NOAA, US)
NIC National Ice Center (US)
NIR Near infrared
NMIC National Meteorological Information Center (China)
NOAA National Oceanic and Atmospheric Administration (US)
NOHRSC National Operational Hydrologic Remote Sensing Center (NWS, US)
NSIDC National Snow and Ice Data Center (US)
NWS National Weather Service (US)
RIHMI-WDC All-Russia Research Institute of Hydrometeorological Information - World Data Centre
Sentinel-3 Satellite in the ESA Copernicus mission
SMMR Scanning Multichannel Microwave Radiometer (NASA)
SSM/I Special Sensor Microwave/Imager (NASA)
SSMIS Special Sensor Microwave Imager Sounder (NASA)
SWE Snow Water Equivalent
Terra One of the two NASA MODIS satellites. The local equatorial crossing time is approximately 10:30 a.m. in a descending node.
UCAR University Corporation for Atmospheric Research (US)
USDA United States Department of Agriculture
VIIRS Visible Infrared Imaging Radiometer Suite (NASA)

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