Northern Hemisphere Blended Snow Extent and Snow Mass Time Series : Séries chronologiques mixtes de l'hémisphère nord de la masse de la neige et l'étendue de la couverture neigeuse

This paper presents an analysis of observed and simulated historical snow cover extent and snow mass, along with future snow cover projections from models participating in the 6th phase of the World Climate Research Programme Coupled Model Inter-comparison Project (CMIP6). Where appropriate, the CMI...

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Bibliographic Details
Main Author: Climate Research Division
Format: Dataset
Language:English
Published: Environment and Climate Change Canada 2020
Subjects:
Ice
Online Access:https://dx.doi.org/10.18164/cc133287-1a07-4588-b3b8-40d714edd90e
https://data-donnees.ec.gc.ca/data/climate/scientificknowledge/climate-research-publication-based-data/northern-hemisphere-blended-snow-extent-and-snow-mass-time-series/
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Summary:This paper presents an analysis of observed and simulated historical snow cover extent and snow mass, along with future snow cover projections from models participating in the 6th phase of the World Climate Research Programme Coupled Model Inter-comparison Project (CMIP6). Where appropriate, the CMIP6 output is compared to CMIP5 results in order to assess progress (or absence thereof) between successive model generations. An ensemble of six observation-based products is used to produce a new time series of historical Northern Hemisphere snow extent anomalies and trends; a subset of four of these products is used for snow mass. Trends in snow extent over 1981-2018 are negative in all months, and exceed -50 x 103 km2 during November, December, March, and May. Snow mass trends are approximately -5 Gt/year or more for all months from December to May. Overall, the CMIP6 multi-model ensemble better represents the snow extent climatology over the 1981-2014 period for all months, correcting a low bias in CMIP5. Simulated snow extent and snow mass trends over the 1981-2014 period are stronger in CMIP6 than in CMIP5, although large inter-model spread remains in the simulated trends for both variables. There is a single linear relationship between projected spring snow extent and global surface air temperature (GSAT) changes, which is valid across all scenarios. This finding suggests that Northern Hemisphere spring snow extent will decrease by about 8% relative to the 1995-2014 level per °C of GSAT increase. The sensitivity of snow to temperature forcing largely explains the absence of any climate change pathway dependency, similar to other fast response components of the cryosphere such as sea ice and near surface permafrost.