Canadian Prairie Snow Cover Variability

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Canadian Prairie Snow Cover Variability Chris Derksen, Ross Brown, Murray MacKay, Anne Walker Climate Research Division Environment Canada Ongoing Activities: Snow Cover Variability and Links to Atmospheric Circulation/Regional Climate Modeling Near Real Time SWE Monitoring: Passive Microwave Data/Algorithm Enhancements Environment Canada Environnement Canada

Snow Cover and Drought Insulating layer between soil/surface vegetation and the boundary layer. Melt release for surface, soil, and groundwater recharge. Potential impact as a drought amplifier/contribution as a drought breaker. Synoptic scale influences on overlying air masses. Low-frequency interactions with atmospheric circulation (i.e. ENSO; PNA). Current MSC Snow Depth/SWE Network Kim Turchenek U. Regina

Observed change (days/yr) in snow cover duration from the NOAA weekly satellite product, 966 to Fall data suggest a slight advance in the start date of snow cover. Spring data show a shortened snow cover duration across the Canadian prairies. SPRING FALL

Merging and Conventional Data Records Brown (J. Climate, ) produced a gridded snow extent and water equivalent dataset for North America from historical conventional observations (9599). Strong agreement with the passive microwave time series was exhibited for the 97899 overlap period, allowing the satellite record to be viewed within the context of a longer dataset. Standardized SWE Anomaly, December 5-yr Moving Average 95 995 9959 959595596965 979759898599995 Standardized SCA Anomaly, December 5-yr Moving Average Passive Microwave 5-yr Moving Average 95995 99599595955969659797598985 99995 Derksen et al., J. Hydromet.,.

Merging and Conventional Data Records Standardized SWE Anomaly, January Standardized SWE Anomaly, February Standardized SWE Anomaly, March 5-yr Moving Average 95 95 95 95 955 965 975 985 995 5-yr Moving Average 95 95 95 95 955 965 975 985 995 5-yr Moving Average 95 95 95 95 955 965 975 985 995 Anomalies during the passive microwave era are not more extreme than those in the historical record. Linear trend analysis provided no evidence of any significant long term trends in either SCA or SWE over the December-March period, but there is a significant periodicity in the SWE record. Standardized SCA Anomaly, January Standardized SCA Anomaly, February Standardized SCA Anomaly, March 5-yr Moving Average 95 95 95 95 955 965 975 985 995 5-yr Moving Average 95 95 95 95 955 965 975 985 995 5-yr Moving Average 95 95 95 95 955 965 975 985 995

Regional Climate Model Simulations (a) (b) (a) Accumulated SWE (d) Sublimation..5. -.5..5..5. mm October November (c) (d) (b) Accumulated Snowfall (e) Accumulated Vapor Flux December January (c) Accumulated Snowmelt 5 6 7 8 9 5 SWE SWE (mm) 5 5 5 5 5 5 mm Water Budget Computations

Regional SSM/I SWE Products C Canadian Prairies -weekly maps produced and sent to users (federal, provincial agencies, private industry) who have a requirement for regular monitoring of snow cover in western Canada - available to public on www.socc.ca (State of Canadian Cryosphere) Manitoba Red River watershed - specialized maps sent to provincial water resource agencies focussed on priority river basins for forecasting spring runoff and flood risk Snare River Basin NWT - maps for hydro companies (e.g. NWT Power; Manitoba Hydro) in support of planning hydroelectric power operations

Information During Wet Snow Periods March, March, During melt episodes, SWE cannot be retrieved, but areas of wet snow cover can be identified. Other additional layers of information (such as retrieval uncertainty) will be distributed to users.

Downside: Algorithm Validation and Enhancements The open prairie environment is not a present region of focus (as opposed to the northern boreal forest and open tundra). Upside:.. Enhancements It is a region where will result uncertainty from field in passive studies microwave and increased SWE used retrievals of AMSR-E is well brightness understood and temperatures: well documented: Environment Canada led activities Potential collaborations with NASA Terrestrial Hydrology Program (Soil Moisture Working Group; Cold Land Process Working Group) Brandon Weyburn Nipawin Comparison over 8 seasons (Derksen et al., Remote Sens. Environ., ).

Summary Snow cover is a significant climatological and hydrological variable to consider in the context of prairie droughts. Various sources of information on historical snow cover variability and present conditions: NOAA snow charts (extent/duration) Passive microwave (SWE) Conventional (Depth/SWE) Conventional + Microwave (SWE) Near real time monitoring of SWE with passive microwave data continues, and will be enhanced: Prairie Boreal Forest Tundra (under development)

Acknowledgments