Abstract

Northern Hemisphere (NH) snow cover extent (SCE) is one of the most important indicator of climate change due to its unique surface property. However, short temporal coverage, coarse spatial resolution, and different snow discrimination approach among existing continental scale SCE products hampers its detailed studies. Using the latest 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 SCE covering the NH landmass for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite. The development of GLASS SCE contains five steps. First, a decision tree algorithm with multiple threshold tests was applied to distinguish snow cover (NHSCE-D) with other land cover types from daily AVHRR-SR CDR. Second, gridcells with cloud cover and invalid observations were filled by two existing daily SCE products. The gap-filled gridcells were further merged with NHSCE-D to generate combined daily SCE over the NH (NHSCE-Dc). Third, an aggregation process was used to detect the maximum SCE and minimum gaps in each 8-day periods from NHSCE-Dc. Forth, the gaps after aggregation process were further filled by the climatology of snow cover probability to generate the gap-free GLASS SCE. 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 are available at https://doi.org/10.5281/zenodo.5775238 (Chen et al. 2021).

Highlights

  • 30 Season snow cover is the largest component of the cryosphere and has been designated as one of the Essential Climate Variables (ECVs) of the Global Climate Observing System (GCOS) due to its high surface albedo, heat insulation, andData contribution to soil moisture and runoff (GCOS, 2019b; Bojinski et al, 2014)

  • To meet the demands of longterm gap-free snow cover extent (SCE) dataset in climate change monitoring and forecasting, this study developed a 39 year consistent 8-day 0.05 degree gap-free SCE dataset over the Northern Hemisphere (NH) for the period 1981– 2019 based on the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High-Resolution Radiometer (AVHRR)-SR Climate Data Record (CDR) and several contributory datasets

  • Using AVHRR-SR CDR as primary input 395 dataset ensures the temporal consistent of Global LAnd Surface Satellite (GLASS) SCE

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Summary

Introduction

30 Season snow cover is the largest component of the cryosphere and has been designated as one of the Essential Climate Variables (ECVs) of the Global Climate Observing System (GCOS) due to its high surface albedo, heat insulation, andData contribution to soil moisture and runoff (GCOS, 2019b; Bojinski et al, 2014). NH snow cover is highly concerned by the International Panel on Climate Change (IPCC) (Hock et al, 2019) and World 35 Meteorological Organization (WMO) (WMO, 2020), and plays a crucial role in the Earth’s climate system through the surface energy budget (Flanner et al, 2011; Chen et al, 2016; Thackeray and Fletcher, 2016; Chen et al, 2015), atmospheric circulation (Henderson et al, 2018), as well as hydrological cycle (Immerzeel et al, 2019; Barnett et al, 2005; Pulliainen et al, 2020), and influences freshwater resources across a large proportion of the NH, especially in the mountain regions (Barnett et al, 2005).

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