HR: 11:45h
AN: A12A-06    [Abstracts]
TI: Exploring the Relationships Between Snowpack and Modes of Atmospheric Circulation Over North America
AU: * Sobolowski, S
EM: ssobolow@hunter.cuny.edu
AF: NOAA-CREST Center, City College -CUNY 140th Street at Convent Avenue, New York, NY 10031 United States
AU: * Sobolowski, S
EM: ssobolow@hunter.cuny.edu
AF: Hunter College, Geography Department 695 Park Avenue, New York, NY 10021 United States
AU: Frei, A
EM: afrei@hunter.cuny.edu
AF: Hunter College, Geography Department 695 Park Avenue, New York, NY 10021 United States
AU: Mahani, S
EM: mahani@ce.engr.ccny.cuny
AF: NOAA-CREST Center, City College -CUNY 140th Street at Convent Avenue, New York, NY 10031 United States
AB: The relationships between snowpack, the Pacific North American pattern (PNA), North Atlantic Oscillation (NAO) and El-Nino Southern Oscillation (ENSO) are examined over the course of North American winters from 1980-1997, utilizing a gridded SWE dataset developed by Brown and Brasnet, of the Canadian Cryospheric Network. The present research examines the statistical significance of the relationships between these three patterns of atmospheric variability and SWE (snow water equivalent) from 35§ N to 55§ N over entire extent of the North American continent. Seasonal (JFM) SWE values are correlated to seasonal mean teleconnection indices. Regions of significant negative correlations between the indices and SWE are found over the Pacific Northwest, Southern Plains of Canada and Great Lakes region. The NAO shows some locally significant positive correlations over the Northern Plains and Rocky Mountains. ENSO is significantly correlated to SWE over the Southwestern U.S. PNA shows significant negative correlations over Western New England. Other areas of significance exist but must be treated cautiously due to small numbers of observation stations in these regions. All correlations were performed using Spearman's Ranked method. Composite analysis is employed to better understand the relationships between indices and the winter (JFM) snowpack. PNA positive(negative), NAO positive(negative) and ENSO positive(negative) years were tested for significance, using the t-test, against all other years to determine a relationship between highly positive(negative) events and SWE. Multiple cutoffs were used in determining positive(negative) years. Resulting areas of significance generally agreed well with regions from the correlation analysis. Composite analysis results also suggest that there may be some potential for predictive skill over certain regions for years above(below) a certain index threshold. SWE has a significant impact on spring snow-melt runoff, water resource availability and may be an indicator for summer temperature variability. Understanding the relationships explored herein will aid in water resources planning and research, improve our understanding of climate variability and the treatment of teleconnections in climate and hydrological models, and may contribute to climate prediction efforts.
DE: 1620 Climate dynamics (3309)
DE: 3309 Climatology (1620)
DE: 3319 General circulation
SC: Atmospheric Sciences [A]
MN: 2005 Joint Assembly