Determining the cause of inconsistent onset-season trends in the Northern Hemisphere snow cover extent record

While seasonal snow cover extent (SCE), an essential climate variable, has broadly declined as a response to global warming, notable inconsistencies remain among long-term satellite-based estimates of SCE change during the Northern Hemisphere snow onset season. SCE datasets from a reanalysis-driven simple snow model serve as benchmarks and allow us to reconcile the trends from one prominent snow cover record with other recent studies. In particular, artificial increasing snow cover trends in the National Oceanic and Atmospheric Administration's Snow Cover Extent Climate Data Record (CDR) during the onset season are related to changes in snow detection sensitivity. This artificial drift primarily affects September, October, and November snow cover but is detectible through February. Revised trends produced by merging the last decade's CDR estimates with the offline model datasets reveal decreasing Northern Hemisphere trends in all months but January. This approach shows that offline snow models produce useful benchmarks that can expose biases in observational snow cover datasets with other cross-validation.

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Publication Details

Journal
Science Advances
Published
2025-10-31
DOI
https://doi.org/10.1126/sciadv.adv7926
Primary Topic
Cryospheric studies and observations
Type
article
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article

Determining the cause of inconsistent onset-season trends in the Northern Hemisphere snow cover extent record

Lawrence Mudryk, Paul J. Kushner, Chris Derksen, Aleksandra Elias Chereque
Science Advances
Cryospheric studies and observations
article

Determining the cause of inconsistent onset-season trends in the Northern Hemisphere snow cover extent record

Lawrence Mudryk, Paul J. Kushner, Chris Derksen, Aleksandra Elias Chereque
article en

Abstract

While seasonal snow cover extent (SCE), an essential climate variable, has broadly declined as a response to global warming, notable inconsistencies remain among long-term satellite-based estimates of SCE change during the Northern Hemisphere snow onset season. SCE datasets from a reanalysis-driven simple snow model serve as benchmarks and allow us to reconcile the trends from one prominent snow cover record with other recent studies. In particular, artificial increasing snow cover trends in the National Oceanic and Atmospheric Administration's Snow Cover Extent Climate Data Record (CDR) during the onset season are related to changes in snow detection sensitivity. This artificial drift primarily affects September, October, and November snow cover but is detectible through February. Revised trends produced by merging the last decade's CDR estimates with the offline model datasets reveal decreasing Northern Hemisphere trends in all months but January. This approach shows that offline snow models produce useful benchmarks that can expose biases in observational snow cover datasets with other cross-validation.

Science AdvancesVol. 11(44)
Environment and Climate Change Canada (CA), University of Toronto (CA)
Openalex Percentile: Top 63%
Cryospheric studies and observations
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Determining the cause of inconsistent onset-season trends in the Northern Hemisphere snow cover extent record — Lawrence Mudryk, Paul J. Kushner, et al. · Science Advances (2025) | TGRS Research Map | TGRS