This dissertation focuses on examining the relationship between antecedent soil
moisture and summer precipitation in the U.S. Great Plains (GP). The influence of Nino
sea surface temperatures (SSTs) on summer precipitation has also been investigated to
compare their relative contributions to those from local moisture recycling. Both
observational data and model simulations have been used to investigate how and why
soil moisture can affect subsequent summer precipitation in the GP.
Observational analysis indicates that spring (May 1st) soil moisture is
significantly correlated with summer precipitation only during periods when Nino SSTs
are not strongly correlated with summer precipitation (e.g. 1925-1936). During periods
when Nino SSTs are strongly correlated with summer precipitation (e.g. 1940-1970),
spring soil moisture is not a good predictor of summer precipitation in the GP. The
periods of strong correlation between Nino SSTs and summer precipitation are
associated with strong SST persistence. This study suggests that both local soil moisture and remote SST anomalies (deviation from SST climatology) influence summer
precipitation in the GP. The soil moisture anomalies are of greatest importance during
years when Nino SST persistence is low.
Model results have demonstrated that there are significant differences in
precipitation response to soil moisture anomalies depending on their sign (+/-), timing
and persistence. The influence of dry soil moisture anomalies on subsequent
precipitation tends to last longer than wet soil moisture anomalies when initialized on
May 1st. Dry soils can influence summer precipitation in the subsequent 2-3 months.
However, the precipitation response to wet soil moisture anomalies is faster and greater
in magnitude than the response to dry soil moisture anomalies. Persistent soil moisture
anomalies that are sustained for an entire month produced larger precipitation changes
than soil moisture anomalies only applied on the first day of the month. It appears that
the length of soil moisture memory also depends on the sign of soil moisture anomaly.
The results of this study may be model-dependent due to the significant inter-model
variations in land surface parameterizations. This may restrict the potential for drawing
general conclusions.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2009-08-2949 |
| Date | 14 January 2010 |
| Creators | Meng, Lei |
| Contributors | Quiring, Steven M. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation |
| Format | application/pdf |
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