科技报告详细信息
Exploring Seasonal and Regional Relationships Between the Evaporative Stress Index and Surface Weather and Soil Moisture Anomalies Across the United States
Otkin, Jason A [Point of Contact] ; Zhong, Yafang ; Lorenz, David ; Anderson, Martha ; Hain, Christopher R
关键词: ANNUAL VARIATIONS;    REGIONS;    EVAPOTRANSPIRATION;    SOIL MOISTURE;    CORRELATION;    VAPOR PRESSURE;    ANOMALIES;    UNITED STATES;    VEGETATION;    ATMOSPHERIC EFFECTS;   
RP-ID  :  MSFC-E-DAA-TN63258
美国|英语
来源: NASA Technical Reports Server
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【 摘 要 】

This study uses correlation analyses to explore relationships between the satellite-derived Evaporative Stress Index (ESI) – which depicts standardized anomalies in an actual to reference evapotranspiration (ET) fraction – and various land and atmospheric variables that impact ET. Correlations between the ESI and forcing variable anomalies calculated over sub-seasonal timescales were computed at weekly and monthly intervals during the growing season. Overall, the results revealed that the ESI is most strongly correlated to anomalies in soil moisture and 2 m dew point depression. Correlations between the ESI and precipitation were also large across most of the US; however, they were typically smaller than those associated with soil moisture and vapor pressure deficit. In contrast, correlations were much weaker for air temperature, wind speed, and radiation across most of the US, with the exception of the south-central US where correlations were large for all variables at some point during the growing season. Together, these results indicate that changes in soil moisture and near-surface atmospheric vapor pressure deficit are better predictors of the ESI than precipitation and air temperature anomalies are by themselves. Large regional and seasonal dependencies were also observed for each forcing variable. Each of the regional and seasonal correlation patterns were similar for ESI anomalies computed over 2-, 4-, and 8-week time periods; however, the maximum correlations increased as the ESI anomalies were computed over longer time periods and also shifted toward longer averaging periods for the forcing variables.

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