North American snowfall variation from a unique gridded data set

1. North American snowfall variation from a unique gridded data set Daria Kluver Department of Geography University of Delaware

2. Introduction • The factors controlling each snowfall event are numerous, and sometimes last for only a few hours (Leathers et al. (1993)). • In contrast, snow cover studies, concerned with the presence of the snow cover over at least several days, incorporate a low temperature persistence factor (Harrington et al., 1987). • Because of these differences, snowfall may be more representative of the short-term meteorological events that produce it. • There have recently been several snow cover, and snow water equivalent (SWE), studies yet few have assessed the trends, climatological aspects, and climate change indication capabilities of actual snowfall (IPCC, 2001, Leathers et al., 1993).

3. North American Snowfall • Snowfall climatology identifies average peak snowfall for U.S. in February (Harrington et al, 1987). • Half-century snowfall trends show decreases in the Pacific North West and increases in the Ohio River Valley (Scott and Kaiser, 2003,2004) • Great Lakes/Upper Mid-West and High Plains experienced increases in snowfall from 1945-1984 (Leathers et al., 1993). • Number and intensity of Alberta Clippers • Studies on Lake-effect snowfall show increases (Burnett et al, 2003; Ellis and Leathers, 1996; and Leather and Ellis, 1996; Scott and Kaiser, 2003, 2004) • Snowfall’s human impacts and cost(Changnon, 1979; Schmidlin, 1993).

4. Aims of study • Determine the quality of a new gridded data set • Construct a climatology of North American snowfall • Calculate trends in various snowfall characteristics • Identify correlations between snowfall and teleconnection patterns

5. Data • 1 by 1 interpolated snowfall data (T. Mote, 2004) • interpolated from U.S. National Weather Service (NWS) cooperative stations and the Canadian daily surface observations • The period of record is 1900-2000 with a daily resolution

6. Snow season is July 1 to June 30.

7. 1900 1909 1919 1949 1929 1939 The first ~50 years of the record had a large increase in the number of reporting stations contributing to the interpolation 1959

8. This becomes an issue when trends are calculated. Example:

9. Solution: determine a criteria for station to be blacked out.

10. Monthly snow climatology

12. This shows that the 1° by 1° resolution can capture smaller features

13. Snowfall Trends 1949-1999

16. Other trends that are calculated with this data set: • average intensity • date of maximum snowfall • first/last day of snow season • number of events Trends we also calculated monthly.

17. Teleconnection patterns

18. Monthly correlations were calculated for PNA, AO, NAO, PDO, and SOI • The PNA and PDO have the strongest correlations

19. Summary of Analysis • High resolution data, but the period of record used is important. • Trends over the last half century include: • increases in the total seasonal snowfall in the Cascades of up to +100 mm/half century in some locations, • Increases of 2 to 3 snowfall events per half century in Western half of the continent and decreases along the eastern seaboard, • Increases in the length of snow season in Southeast US and Southern Canada of 1 to 6 days, • and decreases in length of snowseason in southwestern and western US of 2 to 5 days. • PDO and PNA have a strong negative correlation with snowfall (-0.6 to -.07) in the Pacific North West in winter. • AO and NAO also have relative large correlations.