VERSION UPDATE NOTE: -------------------------------------------------------------------------------------------------------------------------------------------------Data DescriptionAVHRR10C1.V4 dataset provides gobla daily snow cover fraction (SCF) data at a 0.05° grid cell, spanning four decades (Jan. 1979 to Dec. 2023). SCF represents the proportion of snow-covered area observed from space. This dataset consolidates multiple AVHRR SCF observations derived from three generations of Advanced Very High-Resolution Radiometer (AVHRR) sensors, as part of the ESA Snow CCI+ Phase-2 project (AVHRR/1: TIROS-N, NOAA-6, 8, and 10; AVHRR/2: NOAA-7, 9, 11, 12, and 14; AVHRR/3: 16, 17, 18, 19, and METOP-A/B/C). The algorithm description will be updated lately [The latest update date --- August 6th, 2025].Date typesThe dataset includes two types of SCF:Snow Cover Fraction Viewable (SCFV): Represents the area of snow visible over land surface from space, while snow area in forested area refers to snow visible on top of forest canopies.Snow Cover Fraction on Ground (SCFG): Represents snow on the ground, with corrections applied in forested areas to account for the obstruction caused by forest canopy.Both SCFV and SCFG are provided in percentage (%) per grid, at a spatial resolution of 0.05° (approximately 5 km). The data covers all land areas globally, excluding Antarctica and Greenland ice sheets.Important Notes:The dataset contains gaps for 110 days due to limited availability of AVHRR sensor observations. The missing dates are listed in the accompanying file Dates List of Missing Data.xlsx."The dataset is organized by year, with each day's data stored in a separate GeoTIFF (*.tif) file.Code values of AVHRR10C1.V4 SCF data:CodesDescription0 - 100 Snow cover fraction (SCF) [%]; 0: snow freee; 100: fully snow covered205Cloud206Polar night210Water215Glacier, Icecaps, Icesheets254ERROR: No satellite acuqisition

VERSION UPDATE NOTE: -------------------------------------------------------------------------------------------------------------------------------------------------Data DescriptionAVHRR10C1.V4 dataset provides gobla daily snow cover fraction (SCF) data at a 0.05° grid cell, spanning four decades (Jan. 1979 to Dec. 2023). SCF represents the proportion of snow-covered area observed from space. This dataset consolidates multiple AVHRR SCF observations derived from three generations of Advanced Very High-Resolution Radiometer (AVHRR) sensors, as part of the ESA Snow CCI+ Phase-2 project (AVHRR/1: TIROS-N, NOAA-6, 8, and 10; AVHRR/2: NOAA-7, 9, 11, 12, and 14; AVHRR/3: 16, 17, 18, 19, and METOP-A/B/C). The algorithm description will be updated lately [The latest update date --- August 6th, 2025].Date typesThe dataset includes two types of SCF:Snow Cover Fraction Viewable (SCFV): Represents the area of snow visible over land surface from space, while snow area in forested area refers to snow visible on top of forest canopies.Snow Cover Fraction on Ground (SCFG): Represents snow on the ground, with corrections applied in forested areas to account for the obstruction caused by forest canopy.Both SCFV and SCFG are provided in percentage (%) per grid, at a spatial resolution of 0.05° (approximately 5 km). The data covers all land areas globally, excluding Antarctica and Greenland ice sheets.Important Notes:The dataset contains gaps for 110 days due to limited availability of AVHRR sensor observations. The missing dates are listed in the accompanying file Dates List of Missing Data.xlsx."The dataset is organized by year, with each day's data stored in a separate GeoTIFF (*.tif) file.Code values of AVHRR10C1.V4 SCF data:CodesDescription0 - 100 Snow cover fraction (SCF) [%]; 0: snow freee; 100: fully snow covered205Cloud206Polar night210Water215Glacier, Icecaps, Icesheets254ERROR: No satellite acuqisition

VERSION UPDATE NOTE: This version 3.0 composited dataset will not be publicly availble since January 2025. This composited dataset is generated with ESA CCI AVHRR SCF V3.0 products for single sensor, which are available at the website https://catalogue.ceda.ac.uk/uuid/7491427f8c3442ce825ba5472c224322/ and https://catalogue.ceda.ac.uk/uuid/56ff07acabab42888afe2d20b488ec49/.  Anyone interested in AVHRR SCF V3.0 product can test the composite processing according to your needs.Moreover, our new version dataset (Version 4.0), including the daily compoisted AVHRR SCF product, will be avaiable soon. Given some obvious underestimation errors and missing errors of snow cover pixels in AVHRR 3.0 SCF products, we have done significant improvements for our updaed version AVHRR SCF products (V4.0).  [--12/23/2024]--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Data DescriptionThis dataset provides daily composited snow cover fraction (SCF) data, spanning four decades from 1979 to 2022. SCF represents the proportion of snow-covered area observed from space. This dataset is combining the multiple SCF observations derived from three generations of Advanced Very High-Resolution Radiometer (AVHRR) sensors, as part of the ESA CCI+ Snow project (AVHRR/1: TIROS-N, NOAA-6, 8, and 10; AVHRR/2: NOAA-7, 9, 11, 12, and 14; AVHRR/3: NOAA-15, 16, 17, 18, 19, and METOP-A/B/C).Date typesThe dataset includes two types of SCF:Snow Cover Fraction Viewable (SCFV): Represents the area of snow visible over land surface from space, while snow area in forested area refers to snow visible on top of forest canopies.Snow Cover Fraction on Ground (SCFG): Represents snow on the ground, with corrections applied in forested areas to account for the obstruction caused by forest canopy.Both SCFV and SCFG are provided in percentage (%) per grid, at a spatial resolution of 0.05° (approximately 5 km). The data covers all land areas globally, excluding Antarctica and Greenland ice sheets.Important Notes:Due to limitations in satellite observations, 110 days of data are missing from the dataset. A list of these dates is provided in the accompanying file "Dates List of Missing Data.xlsx".The dataset is organized by year, with each day's data stored in a separate GeoTIFF (*.tif) file.Code for the AVHRR SCF products:CodesDescription0 - 100 Snow cover fraction (SCF) [%]; 0: snow freee; 100: fully snow covered205Cloud206Polar night210Water215Glacier, Icecaps, Icesheets254ERROR: No satellite acuqisition

This data collection contains 40 years of monthly mean daytime AVHRR  Global Area Coverage (GAC)  land surface temperature (LST) data. This dataset covers the 1981-2020 perdiod and covers the whole globe above 50° latitude. The spatial extent of the dataset is the following : (-180°, 50°N) ; (180°, 90°N)Dataset description:The LST monthly mean composites are computed from daily daytime LST files, that were generated from the EUMETSAT AVHRR PyGAC FDR (https://navigator.eumetsat.int/product/EO:EUM:DAT:0862) as described in Dupuis et al. (2024). These daily LST files contain only cloud-free pixels and pixels with sufficient quality regarding satellite zenith angle and error margin from the radiative transfer modelling. The probabilistic cloud mask from the CLARA-A3 (https://navigator.eumetsat.int/product/EO:EUM:DAT:0874) dataset has been used. The LST monthly means do not contain any water masks, as potential users might have different requirements regarding water masks. The dataset has been validated against in situ data from the SURFRAD (https://gml.noaa.gov/grad/surfrad/overview.html), ARM (https://arm.gov/capabilities/observatories/nsa) and KIT (https://www.imk-asf.kit.edu/english/skl_stations.php) networks.Data & File Overview:Short description: AVHRR GAC LST daytime monthly mean composites: daily land surface temperature data are averaged to monthly composites for every afternoon and mid-day satellite (10 different satellites).File List: This dataset contains monthly daytime land surface temperature (LST) data for the AVHRRs onboard NOAA and MetOp satellites. Filename: Pan_Arctic_LST_avhrr_XXXXX_YYYYMM_DAY__***.nc, where XXXXX represents the satellite identifier, YYYYMM the monthly timestamp (YYYY=year, MM=month) and *** the timestamp of the file generation.Relationship between files: Each file covers a one-month period and is recorded by a different satellite.Satellite identifiers:AVN07 : NOAA 7AVN09 : NOAA 9AVN11 : NOAA 11AVN14 : NOAA 14AVN16 : NOAA 16AVN18 : NOAA 18AVN19 : NOAA 19AVMEA : MetOp-AAVMEB : MetOp-BAVMEC : MetOp-CData specific information:The LST files are available as a gridded product in the WGS84 coordinate reference system and are distributed as NetCDF files. The dataset covers the pan-Arctic region (-180°, 90°, 180°, 50°) at a spatial resolution of 0.05°x0.05° pixel size.Each *.nc file contains one variable (LST) with three dimensions (time, lat, lon) and five coordinates (time, lat, lon, band and spatial_ref).- spatial_ref (): stores the spatial information, such as the coordinate reference system (CRS) and WKT string.- time (time): stores the timestamp, here the month and the year of the monthly mean. The timestamp is the same for all pixels belonging to the same composite.- lat (lat): stores the latitude of each pixel- lon (lon): stores the longitude of each pixel- band (): empty inherited layer  Credit:To use this data please cite this dataset and the respective journal publication:Dupuis, S., Göttsche, F.-M., & Wunderle, S. (2024). Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region. The Cryosphere, 18(12), 6027-6059. https://doi.org/10.5194/tc-18-6027-2024 @Article{tc-18-6027-2024,AUTHOR = {Dupuis, S. and G"ottsche, F.-M. and Wunderle, S.},TITLE = {Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region},JOURNAL = {The Cryosphere},VOLUME = {18},YEAR = {2024},NUMBER = {12},PAGES = {6027--6059},URL = {https://tc.copernicus.org/articles/18/6027/2024/},DOI = {10.5194/tc-18-6027-2024}} Information about funding sources that supported the collection of the data:Dr. Alfred Bretscher Fund (University of Bern)

This data collection contains 40 years of monthly mean daytime AVHRR  Global Area Coverage (GAC)  land surface temperature (LST) data. This dataset covers the 1981-2020 perdiod and covers the whole globe above 50° latitude. The spatial extent of the dataset is the following : (-180°, 50°N) ; (180°, 90°N)Dataset description:The LST monthly mean composites are computed from daily daytime LST files, that were generated from the EUMETSAT AVHRR PyGAC FDR (https://navigator.eumetsat.int/product/EO:EUM:DAT:0862) as described in Dupuis et al. (2024). These daily LST files contain only cloud-free pixels and pixels with sufficient quality regarding satellite zenith angle and error margin from the radiative transfer modelling. The probabilistic cloud mask from the CLARA-A3 (https://navigator.eumetsat.int/product/EO:EUM:DAT:0874) dataset has been used. The LST monthly means do not contain any water masks, as potential users might have different requirements regarding water masks. The dataset has been validated against in situ data from the SURFRAD (https://gml.noaa.gov/grad/surfrad/overview.html), ARM (https://arm.gov/capabilities/observatories/nsa) and KIT (https://www.imk-asf.kit.edu/english/skl_stations.php) networks.Data & File Overview:Short description: AVHRR GAC LST daytime monthly mean composites: daily land surface temperature data are averaged to monthly composites for every afternoon and mid-day satellite (10 different satellites).File List: This dataset contains monthly daytime land surface temperature (LST) data for the AVHRRs onboard NOAA and MetOp satellites. Filename: Pan_Arctic_LST_avhrr_XXXXX_YYYYMM_DAY__***.nc, where XXXXX represents the satellite identifier, YYYYMM the monthly timestamp (YYYY=year, MM=month) and *** the timestamp of the file generation.Relationship between files: Each file covers a one-month period and is recorded by a different satellite.Satellite identifiers:AVN07 : NOAA 7AVN09 : NOAA 9AVN11 : NOAA 11AVN14 : NOAA 14AVN16 : NOAA 16AVN18 : NOAA 18AVN19 : NOAA 19AVMEA : MetOp-AAVMEB : MetOp-BAVMEC : MetOp-CData specific information:The LST files are available as a gridded product in the WGS84 coordinate reference system and are distributed as NetCDF files. The dataset covers the pan-Arctic region (-180°, 90°, 180°, 50°) at a spatial resolution of 0.05°x0.05° pixel size.Each *.nc file contains one variable (LST) with three dimensions (time, lat, lon) and five coordinates (time, lat, lon, band and spatial_ref).- spatial_ref (): stores the spatial information, such as the coordinate reference system (CRS) and WKT string.- time (time): stores the timestamp, here the month and the year of the monthly mean. The timestamp is the same for all pixels belonging to the same composite.- lat (lat): stores the latitude of each pixel- lon (lon): stores the longitude of each pixel- band (): empty inherited layer  Credit:To use this data please cite this dataset and the respective journal publication:Dupuis, S., Göttsche, F.-M., & Wunderle, S. (2024). Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region. The Cryosphere, 18(12), 6027-6059. https://doi.org/10.5194/tc-18-6027-2024 @Article{tc-18-6027-2024,AUTHOR = {Dupuis, S. and G"ottsche, F.-M. and Wunderle, S.},TITLE = {Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region},JOURNAL = {The Cryosphere},VOLUME = {18},YEAR = {2024},NUMBER = {12},PAGES = {6027--6059},URL = {https://tc.copernicus.org/articles/18/6027/2024/},DOI = {10.5194/tc-18-6027-2024}} Information about funding sources that supported the collection of the data:Dr. Alfred Bretscher Fund (University of Bern)

The efforts of the European Space Agency (ESA) Data User Element (DUE) funded GlobSnow project has resulted in two new hemispherical records of snow parameters intended for climate research purposes. The dataset contains satellite-retrieved information on snow water equivalent (SWE) extending 34 years. The record on snow water equivalent is produced using a combination of passive microwave radiometer and ground-based weather station data, spanning years 1979 to 2013. The GlobSnow SWE record, based on methodology by Pulliainen (Pulliainen 2006, Takala et al. 2011) utilizes a data-assimilation based approach combining space-borne passive radiometer data (SMMR, SSM/I and SSMIS) with data from ground-based synoptic weather stations. The satellite sensors utilized provide data at K- and Ka-bands (19 GigaHertz and 37 GigaHertz respectively) at a spatial resolution of approximately 25 kilometers (km). The SWE record is produced on a daily, weekly and monthly basis. SWE information is provided for terrestrial non-mountainous regions of Northern Hemisphere, excluding glaciers and Greenland.

The efforts of the European Space Agency (ESA) Data User Element (DUE) funded GlobSnow project has resulted in two new hemispherical records of snow parameters intended for climate research purposes. The dataset contains satellite-retrieved information on snow water equivalent (SWE) extending 34 years. The record on snow water equivalent is produced using a combination of passive microwave radiometer and ground-based weather station data, spanning years 1979 to 2013. The GlobSnow SWE record, based on methodology by Pulliainen (Pulliainen 2006, Takala et al. 2011) utilizes a data-assimilation based approach combining space-borne passive radiometer data (SMMR, SSM/I and SSMIS) with data from ground-based synoptic weather stations. The satellite sensors utilized provide data at K- and Ka-bands (19 GigaHertz and 37 GigaHertz respectively) at a spatial resolution of approximately 25 kilometers (km). The SWE record is produced on a daily, weekly and monthly basis. SWE information is provided for terrestrial non-mountainous regions of Northern Hemisphere, excluding glaciers and Greenland.