Thursday, 2 September 2010: 10:45 AM
Alpine Ballroom A (Resort at Squaw Creek)
The lake level elevation of the Great Salt Lake (GSL), a large closed basin lake in the arid western United States, is characterized by a pronounced quasi-decadal oscillation (QDO). Tree-ring reconstructed precipitation records confirm that the quasi-decadal signal in precipitation is a prominent feature in this region. The variation of the GSL elevation is very coherent with the QDO of sea surface temperature anomalies in the tropical central Pacific (also known as the Pacific QDO). However, such coherence denies any direct association between the precipitation in the GSL watershed and the Pacific QDO because, in a given frequency, the precipitation variation always leads the GSL elevation variation. Therefore, the precipitation variation is phase shifted from the Pacific QDO. This study investigates the physical mechanism forming the coherence between the GSL elevation and the Pacific QDO. Pronounced and coherent quasi-decadal signals in precipitation, streamflow, water vapor flux, and drought conditions are found throughout the Great Basin. Recurrent atmospheric circulation patterns develop over the Gulf of Alaska during the warm-to-cool and cool-to-warm transition phases of the Pacific QDO. These circulation patterns modulate the water vapor flux associated with synoptic transient activities over the western United States and, in turn, lead to the QDO in the hydrological cycle of the Great Basin. As the GSL integrates the hydrological responses in the Great Basin, the hydrological QDO is then transferred to the GSL elevation. Because the GSL elevation consistently lags the precipitation by a quarter-phase (about 3 years in the quasi-decadal time scale), these processes take an average of 6 years for the GSL elevation to eventually respond to the Pacific QDO. This creates a half-phase delay of the GSL elevation from the Pacific QDO, thereby forming the inverse, yet coherent, relationship between them. Using the Pacific QDO index and precipitation as input, a principal component-lagged regression model was built to forecast the GSL elevation for the next decade.
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