Monday, 12 January 2009
Influence of Niņo sea-surface temperatures and soil moisture on summer precipitation in the U.S. Great Plains
Hall 5 (Phoenix Convention Center)
Various modeling studies have been performed to investigate the influence of remote sea-surface temperatures (SST) and local soil moisture on summer precipitation in the U.S. Great Plains. Due to the lack of observational soil moisture data, few studies have examined how interactions between teleconnections and local variables (such as snow cover and soil moisture) influence summer precipitation. In this study, we used Variable Infiltration Capacity (VIC) (1920-2007) to provide simulated soil moisture data to examine the relationship between antecedent soil moisture conditions and summer precipitation. VIC soil moisture simulations have been extensively evaluated against measured soil moisture in the United States and results suggest that VIC does well in replicating observed soil moisture patterns. For example, our own analysis using soil moisture observations from the Soil Climate Network Analysis Network (SCAN) demonstrated that the correlations with the VIC soil moisture model exceed 0.8. The Standardized Precipitation Index (SPI) was calculated using the Precipitation-elevation Regressions on Independent Slopes Model (PRISM) data and the 1-month SPI values for June-July-August (JJA) were averaged to represent summer precipitation. The extended reconstructed sea surface temperature (ERSST) v.3 was used to calculate monthly SST anomalies over the Niņo regions (e.g. Niņo 3 and Niņo 4).
Preliminary results indicate that spring (May 1st) soil moisture is significantly correlated with summer SPI only during periods of where Niņo SSTs are not strongly correlation with summer SPI (e.g. 1925-1936). During periods where Niņo SSTs are strongly correlated with summer SPI (e.g. 1940-1970), spring soil moisture is not a good indicator of summer precipitation in the U.S. Great Plains. These periods of strong correlation between Niņo SSTs and summer precipitation are often associated with strong SST persistence. In our study SST persistence was measured by calculating the lagged spatial SST correlations over the Niņo regions. This study suggests that both local soil moisture and remote SST anomalies influence summer precipitation in the U.S. Great Plains. The soil moisture anomalies are of greatest important during years when SST persistence is low.