Northern Hemisphere (NH) snow cover extent (SCE) is one of the most important indicator of climate change for its unique surface property. However, short temporal coverage, coarse spatial resolution, and different snow discrimination approach among published SCE products hampers its detailed studies. Using the Advanced Very High Resolution Radiometer Surface Reflectance (AVHRR-SR) Climate Data Record (CDR) and several ancillary datasets, this study generated a temporally consistent 8-day 0.05° gap-free NH terrestrial SCE product for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite. This process consistent of five steps. First, a decision tree algorithm with multiple threshold tests was applied to detect SCE from daily AVHRR-SR CDR. Second, we merge two existing daily SCE products to take advantage of their spatial coverage. Third, an aggregation process was used to detect the maximum SCE in each 8-day periods. Forth, the GLASS SCE was generated with the help of snow cover probability climatology. Fifth, the validation process was carried out to evaluate the quality of GLASS SCE. Validation results by using 562 Global Historical Climatology Network stations during 1981–2017 (r=0.61, p<0.05) and MOD10C2 during 2001–2019 (r=0.97, p<0.01) proved that the GLASS SCE product is credible in snow cover frequency monitoring. Moreover, cross-comparison between GLASS SCE and surface albedo during 1982–2018 further confirmed its values in climate changes studies. The GLASS SCE contains 39 files. The files are organized by year and can be opened by using ENVI software. Spatial Coverage: N: 90, S: 0, E: 180, W: -180
Spatial Resolution: 0.05 deg x 0.05 deg
Samples = 7200
Lines = 1800
Temporal Coverage: September 1981 to December 2019
Temporal Resolution: 8-day

Northern Hemisphere (NH) snow cover extent (SCE) is one of the most important indicator of climate change for its unique surface property. However, short temporal coverage, coarse spatial resolution, and different snow discrimination approach among published SCE products hampers its detailed studies. Using the Advanced Very High Resolution Radiometer Surface Reflectance (AVHRR-SR) Climate Data Record (CDR) and several ancillary datasets, this study generated a temporally consistent 8-day 0.05° gap-free NH terrestrial SCE product for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite. This process consistent of five steps. First, a decision tree algorithm with multiple threshold tests was applied to detect SCE from daily AVHRR-SR CDR. Second, we merge two existing daily SCE products to take advantage of their spatial coverage. Third, an aggregation process was used to detect the maximum SCE in each 8-day periods. Forth, the GLASS SCE was generated with the help of snow cover probability climatology. Fifth, the validation process was carried out to evaluate the quality of GLASS SCE. Validation results by using 562 Global Historical Climatology Network stations during 1981–2017 (r=0.61, p<0.05) and MOD10C2 during 2001–2019 (r=0.97, p<0.01) proved that the GLASS SCE product is credible in snow cover frequency monitoring. Moreover, cross-comparison between GLASS SCE and surface albedo during 1982–2018 further confirmed its values in climate changes studies. The GLASS SCE data set provides binary maps of snow cover for the Northern Hemisphere from September 1981 to the December 2019. The data are organized by year and provided in GeoTIFF formats. The gridcells were flagged as “0” if classified as "Non-snow", "1" if retrieved from AVHRR satellite observations, and "2" if filled by IMS snow climatology. Spatial Coverage: N: 90, S: 0, E: 180, W: -180
Spatial Resolution: 0.05 deg x 0.05 deg
Samples = 7200
Lines = 1800
Temporal Coverage: September 1981 to December 2019
Temporal Resolution: 8-day

Northern Hemisphere (NH) snow cover extent (SCE) is one of the most important indicator of climate change for its unique surface property. However, short temporal coverage, coarse spatial resolution, and different snow discrimination approach among published SCE products hampers its detailed studies. Using the Advanced Very High Resolution Radiometer Surface Reflectance (AVHRR-SR) Climate Data Record (CDR) and several ancillary datasets, this study generated a temporally consistent 8-day 0.05° gap-free NH terrestrial SCE product for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite. This process consistent of five steps. First, a decision tree algorithm with multiple threshold tests was applied to detect SCE from daily AVHRR-SR CDR. Second, we merge two existing daily SCE products to take advantage of their spatial coverage. Third, an aggregation process was used to detect the maximum SCE in each 8-day periods. Forth, the GLASS SCE was generated with the help of snow cover probability climatology. Fifth, the validation process was carried out to evaluate the quality of GLASS SCE. Validation results by using 562 Global Historical Climatology Network stations during 1981–2017 (r=0.61, p<0.05) and MOD10C2 during 2001–2019 (r=0.97, p<0.01) proved that the GLASS SCE product is credible in snow cover frequency monitoring. Moreover, cross-comparison between GLASS SCE and surface albedo during 1982–2018 further confirmed its values in climate changes studies. The GLASS SCE data set provides binary maps of snow cover for the Northern Hemisphere from September 1981 to the December 2019. The data are organized by year and provided in GeoTIFF formats. The gridcells were flagged as “1” if covered by snow and 0 if no snow. Spatial Coverage: N: 90, S: 0, E: 180, W: -180
Spatial Resolution: 0.05 deg x 0.05 deg
Samples = 7200
Lines = 1800
Temporal Coverage: September 1981 to December 2019
Temporal Resolution: 8-day

Northern Hemisphere (NH) snow cover extent (SCE) is one of the most important indicator of climate change for its unique surface property. However, short temporal coverage, coarse spatial resolution, and different snow discrimination approach among published SCE products hampers its detailed studies. Using the Advanced Very High Resolution Radiometer Surface Reflectance (AVHRR-SR) Climate Data Record (CDR) and several ancillary datasets, this study generated a temporally consistent 8-day 0.05° gap-free NH terrestrial SCE product for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite. This process consistent of five steps. First, a decision tree algorithm with multiple threshold tests was applied to detect SCE from daily AVHRR-SR CDR. Second, we merge two existing daily SCE products to take advantage of their spatial coverage. Third, an aggregation process was used to detect the maximum SCE in each 8-day periods. Forth, the GLASS SCE was generated with the help of snow cover probability climatology. Fifth, the validation process was carried out to evaluate the quality of GLASS SCE. Validation results by using 562 Global Historical Climatology Network stations during 1981–2017 (r=0.61, p<0.05) and MOD10C2 during 2001–2019 (r=0.97, p<0.01) proved that the GLASS SCE product is credible in snow cover frequency monitoring. Moreover, cross-comparison between GLASS SCE and surface albedo during 1982–2018 further confirmed its values in climate changes studies. The GLASS SCE data set provides binary maps of snow cover for the Northern Hemisphere from September 1981 to the December 2019. The data are organized by year and provided in GeoTIFF formats. The gridcells were flagged as “1” if covered by snow and 0 if no snow. Spatial Coverage: N: 90, S: 0, E: 180, W: -180
Spatial Resolution: 0.05 deg x 0.05 deg
Samples = 7200
Lines = 1800
Temporal Coverage: September 1981 to December 2019
Temporal Resolution: 8-day

Northern Hemisphere (NH) snow cover extent (SCE) is one of the most important indicator of climate change for its unique surface property. However, short temporal coverage, coarse spatial resolution, and different snow discrimination approach among published SCE products hampers its detailed studies. Using the Advanced Very High Resolution Radiometer Surface Reflectance (AVHRR-SR) Climate Data Record (CDR) and several ancillary datasets, this study generated a temporally consistent 8-day 0.05° gap-free NH terrestrial SCE product for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite. This process consistent of five steps. First, a decision tree algorithm with multiple threshold tests was applied to detect SCE from daily AVHRR-SR CDR. Second, we merge two existing daily SCE products to take advantage of their spatial coverage. Third, an aggregation process was used to detect the maximum SCE in each 8-day periods. Forth, the GLASS SCE was generated with the help of snow cover probability climatology. Fifth, the validation process was carried out to evaluate the quality of GLASS SCE. Validation results by using 562 Global Historical Climatology Network stations during 1981–2017 (r=0.61, p<0.05) and MOD10C2 during 2001–2019 (r=0.97, p<0.01) proved that the GLASS SCE product is credible in snow cover frequency monitoring. Moreover, cross-comparison between GLASS SCE and surface albedo during 1982–2018 further confirmed its values in climate changes studies. The GLASS SCE data set provides binary maps of snow cover for the Northern Hemisphere from September 1981 to the December 2019. The data are organized by year and provided in GeoTIFF formats. The gridcells were flagged as “0” if classified as "Non-snow", "1" if retrieved from AVHRR satellite observations, and "2" if filled by IMS snow climatology. Spatial Coverage: N: 90, S: 0, E: 180, W: -180
Spatial Resolution: 0.05 deg x 0.05 deg
Samples = 7200
Lines = 1800
Temporal Coverage: September 1981 to December 2019
Temporal Resolution: 8-day