820296dc-11c9-4214-84bf-4871a01fc926 Dataseries German Aerospace Center (DLR) geoservice@dlr.de 2024-06-20T13:06:58 ISO 19115-1:2014/19139 2003/Cor.1:2006 2 86400 460 43200 460 false EPSG:4326 Global SnowPack - MODIS - Yearly 2022-03-01T00:00:00 2 https://geoservice.dlr.de/catalogue/srv/metadata/820296dc-11c9-4214-84bf-4871a01fc926 This product shows the snow cover duration for a hydrological year. Its beginning differs from the calendar year, since some of the precipitation that falls in late autumn and winter falls as snow and only drains away when the snow melts in the following spring or summer. The meteorological seasons are used for subdivision and the hydrological year begins in autumn and ends in summer. The snow cover duration is made available for three time periods: the snow cover duration for the entire hydrological year (SCD), the early snow cover duration (SCDE), which extends from autumn to midwinter (), and the late snow cover duration (SCDL), which in turn extends over the period from mid-winter to the end of summer. For the northern hemisphere SCD lasts from September 1st to August 31st, for the southern hemisphere it lasts from March 1st to February 28th/29th. The SCDE lasts from September 1st to January 14th in the northern hemisphere and from March 1st to July 14th in the southern hemisphere. The SCDL lasts from January 15th to August 31st in the northern hemisphere and from July 15th to February 28th/29th in the southern hemisphere. The “Global SnowPack” is derived from daily, operational MODIS snow cover product for each day since February 2000. Data gaps due to polar night and cloud cover are filled in several processing steps, which provides a unique global data set characterized by its high accuracy, spatial resolution of 500 meters and continuous future expansion. It consists of the two main elements daily snow cover extent (SCE) and seasonal snow cover duration (SCD; full and for early and late season). Both parameters have been designated by the WMO as essential climate variables, the accurate determination of which is important in order to be able to record the effects of climate change. Changes in the largest part of the cryosphere in terms of area have drastic effects on people and the environment. For more information please also refer to: Dietz, A.J., Kuenzer, C., Conrad, C., 2013. Snow-cover variability in central Asia between 2000 and 2011 derived from improved MODIS daily snow-cover products. International Journal of Remote Sensing 34, 3879–3902. https://doi.org/10.1080/01431161.2013.767480 Dietz, A.J., Kuenzer, C., Dech, S., 2015. Global SnowPack: a new set of snow cover parameters for studying status and dynamics of the planetary snow cover extent. Remote Sensing Letters 6, 844–853. https://doi.org/10.1080/2150704X.2015.1084551 Dietz, A.J., Wohner, C., Kuenzer, C., 2012. European Snow Cover Characteristics between 2000 and 2011 Derived from Improved MODIS Daily Snow Cover Products. Remote Sensing 4. https://doi.org/10.3390/rs4082432 Dietz, J.A., Conrad, C., Kuenzer, C., Gesell, G., Dech, S., 2014. Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data. Remote Sensing 6. https://doi.org/10.3390/rs61212752 Rößler, S., Witt, M.S., Ikonen, J., Brown, I.A., Dietz, A.J., 2021. Remote Sensing of Snow Cover Variability and Its Influence on the Runoff of Sápmi’s Rivers. Geosciences 11, 130. https://doi.org/10.3390/geosciences11030130 DFD-LAX Global-SnowPack@dlr.de German Aerospace Center (DLR) geoservice@dlr.de https://geoservice.dlr.de/catalogue/srv/api/records/820296dc-11c9-4214-84bf-4871a01fc926/attachments/gsp_ql.png large_thumbnail https://geoservice.dlr.de/catalogue/srv/api/records/820296dc-11c9-4214-84bf-4871a01fc926/attachments/gsp_ql_s.png thumbnail Land cover GEMET - INSPIRE themes, version 1.0 2008-06-01 geonetwork.thesaurus.external.theme.inspire-theme global Spatial scope 2019-05-22 MODIS Global SnowPack snow cover duration snow cover duration late season snow cover duration early season snow SCD SCDE SCDL opendata inspireidentifiziert Nutzungseinschränkungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Use Limitations: DLR not liable for damage resulting from use. Es gelten keine Zugriffsbeschränkungen Nutzungsbedingungen: Lizenz, https://creativecommons.org/licenses/by/4.0 / Terms of use: License, https://creativecommons.org/licenses/by/4.0 {"id": "cc-by/4.0", "name": "Creative Commons - Attribution 4.0 International (CC BY 4.0)", "url": "http://dcat-ap.de/def/licenses/cc-by/4.0", "quelle": "Copyright DLR (2022)"} 920000 climatologyMeteorologyAtmosphere -180.00 180.00 -90.00 90.00 2000-01-01T00:00:00 2022-02-28T00:00:00 GeoTIFF https://geoservice.dlr.de/eoc/land/wms? OGC:WMS GSP_SCD_P1Y Global SnowPack - Snow Cover Duration (SCD) https://geoservice.dlr.de/eoc/land/wms? OGC:WMS GSP_SCDE_P1Y Global SnowPack - Snow Cover Duration Early Season (SCDE) https://geoservice.dlr.de/eoc/land/wms? OGC:WMS GSP_SCDL_P1Y Global SnowPack - Snow Cover Duration Late Season (SCDL) https://geoservice.dlr.de/eoc/land/wms?SERVICE=WMS%26REQUEST=GetCapabilities OGC:WMS-http-get-capabilities https://geoservice.dlr.de/web/maps/eoc:gsp:yearly WWW:LINK-1.0-http--link EOC Geoservice map context EOC Geoservice map context https://download.geoservice.dlr.de/GSP/files/yearly WWW:LINK-1.0-http--link EOC Download Service EOC Download Service https://www.dlr.de/eoc/desktopdefault.aspx/tabid-18220/29005_read-77046 WWW:LINK-1.0-http--link Global SnowPack - EOC News Global SnowPack - EOC News Conformity_001 INSPIRE Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 See the referenced specification. true Created from MODIS daily snow cover products MOD10A1, MYD10A1 provided by the National Snow and Ice Datacenter NSIDC (https://nsidc.org/) Processing steps include combination of observations recorded by Aqua and Terra, temporal interpolation of 3 successive days, snow line identification, and a seasonal filter. More details are available in the publication "Dietz A.J., Kuenzer, C., and Dech, S. (2015): Global SnowPack: a new set of snow cover parameters for studying status and dynamics of the planetary snow cover extent; Remote Sensing Letters 6, No. 11. pp. 844-853 Single day snow cover datasets MOD10A1 and MYD10A1 were first cleared of any clouds/data gaps/polar darkness areas using 4 different interpolation techniques, then merged to produce the seasonal products. Accuracy of the seasonal product ranges between 77% and 85%, depending on the location and the duration of data gaps caused by clouds or darkness.