Northern Hemisphere Blended Snow Extent and Snow Mass Time Series

Northern Hemisphere Blended Snow Extent and Snow Mass Time Series 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. Supplemental Information The data in these four files are described in Mudryk et al. (2020). 1. monthly NH snow mass over the 1981-2018 time period based on estimates from MERRA2, Crocus, Brown, and GlobSnow. 2. monthly NH snow extent over the 1967-2018 time period based on estimates from NOAA Snow Chart record, JASMES, MERRA2, Crocus, Brown, and GlobSnow. 3. March snow extent based on Brown (2000) recalibrated to match 2. 4. April snow extent based on Brown (2000) recalibrated to match 2. A full description of the analysis is contained in Mudryk et al. 2020 References: Brown, R. D.: Northern Hemisphere snow cover variability and change, 1915–1997, J. Climate, 13, 2339–2355, 2000. Mudryk, L., Santolaria-Otín, M., Krinner, G., Ménégoz, M., Derksen, C., Brutel-Vuilmet, C., Brady, M., and Essery, R.: Historical Northern Hemisphere snow cover trends and projected changes in the CMIP-6 multi-model ensemble, The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-320, in review, 2020. 2021-07-21 Environment and Climate Change Canada open-ouvert@tbs-sct.gc.ca Nature and EnvironmentCMIP6snow extentsnow massClimateClimatologymeteorologyatmosphereWeather and Climate View ECCC Data Mart (English)HTML https://data-donnees.ec.gc.ca/data/climate/scientificknowledge/climate-research-publication-based-data/northern-hemisphere-blended-snow-extent-and-snow-mass-time-series/ View ECCC Data Mart (French)HTML https://donnees-data.ec.gc.ca/data/climate/scientificknowledge/climate-research-publication-based-data/northern-hemisphere-blended-snow-extent-and-snow-mass-time-series/?lang=fr

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.

Supplemental Information

The data in these four files are described in Mudryk et al. (2020).

  1. monthly NH snow mass over the 1981-2018 time period based on estimates from MERRA2, Crocus, Brown, and GlobSnow.

  2. monthly NH snow extent over the 1967-2018 time period based on estimates from NOAA Snow Chart record, JASMES, MERRA2, Crocus, Brown, and GlobSnow.

  3. March snow extent based on Brown (2000) recalibrated to match 2.

  4. April snow extent based on Brown (2000) recalibrated to match 2.

A full description of the analysis is contained in Mudryk et al. 2020

References:

Brown, R. D.: Northern Hemisphere snow cover variability and change, 1915–1997, J. Climate, 13, 2339–2355, 2000.

Mudryk, L., Santolaria-Otín, M., Krinner, G., Ménégoz, M., Derksen, C., Brutel-Vuilmet, C., Brady, M., and Essery, R.: Historical Northern Hemisphere snow cover trends and projected changes in the CMIP-6 multi-model ensemble, The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-320, in review, 2020.

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