HR: 09:15h
AN: H51F-04    [Abstracts]
TI: Interannual Variability of Summertime Rainfall Over the Southwestern US: How Much of it is Climate-related and how Much is Related to Chance?
AU: * Anderson, B T
EM: brucea@bu.edu
AF: Geography Dep't. Boston University, 675 Commonwealth Ave., Rm. 457, Boston, MA 02214-1401
AU: Wang, J
AF: Geography Dep't. Boston University, 675 Commonwealth Ave., Rm. 457, Boston, MA 02214-1401
AU: Salvucci, G
AF: Geography Dep't. Boston University, 675 Commonwealth Ave., Rm. 457, Boston, MA 02214-1401
AB: Many investigations of the North American monsoon system, particularly as it impacts northwestern Mexico and the southwestern United States, have focused upon summertime precipitation and its interannual variations. Here we study the interannual variance of summertime precipitation at 78 stations in the southwestern US using daily Markov Chain models and empirical intensity distributions. Modeling results suggest that a second-order, daily Markov Chain model with stationary (i.e. non-varying) interannual event frequency and intensity characteristics can capture over 75% of the interannual variance in the seasonal number of wet days in the region and 85% of the interannual variance in the total summertime precipitation. These results indicate that a large fraction of the interannual variance in seasonal precipitation can be explained simply by the random evolution of daily rainfall within the season itself, making it inherently difficult to predict. In addition, only a small fraction (generally smaller than 20%) of the anomalous rainfall years at any given station show "potential predictability" related to significant non-stationary changes in either the event frequency and/or intensity characteristics for the given year. Investigations of the non-stationary variations in the occurrence and intensity characteristics indicate they display similar significance in explaining the remaining 15% of interannual variance in seasonal precipitation over the region, although numerical tests suggest that the non-stationary interannual variations of these two characterizing metrics are not necessarily independent. Further investigation into the use of these models for identifying "potentially predictable" years related to interannual climate variability will also be discussed.
DE: 1620 Climate dynamics (3309)
DE: 1655 Water cycles (1836)
DE: 1854 Precipitation (3354)
DE: 1860 Runoff and streamflow
DE: 6309 Decision making under uncertainty
SC: Hydrology [H]
MN: 2005 Joint Assembly