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- Title
Predicting Rapid Changes in Evaporative Stress Index (ESI) and Soil Moisture Anomalies over the Continental United States.
- Authors
Lorenz, David J.; Otkin, Jason A.; Zaitchik, Benjamin; Hain, Christopher; Anderson, Martha C.
- Abstract
Probabilistic forecasts of changes in soil moisture and an evaporative stress index (ESI) on subseasonal time scales over the contiguous United States are developed. The forecasts use the current land surface conditions and numerical weather prediction forecasts from the Subseasonal to Seasonal (S2S) Prediction project. Changes in soil moisture are quite predictable 8–14 days in advance with 50% or more of the variance explained over the majority of the contiguous United States; however, changes in ESI are significantly less predictable. A simple red noise model of predictability shows that the spatial variations in forecast skill are primarily a result of variations in the autocorrelation, or persistence, of the predicted variable, especially for the ESI. The difference in overall skill between soil moisture and ESI, on the other hand, is due to the greater soil moisture predictability by the numerical model forecasts. As the forecast lead time increases from 8–14 to 15–28 days, however, the autocorrelation dominates the soil moisture and ESI differences as well. An analysis of modeled transpiration, and bare soil and canopy water evaporation contributions to total evaporation, suggests improvements to the ESI forecasts can be achieved by estimating the relative contributions of these components to the initial ESI state. The importance of probabilistic forecasts for reproducing the correct probability of anomaly intensification is also shown.
- Subjects
UNITED States; SOIL moisture; NUMERICAL weather forecasting; SEASONS; LEAD time (Supply chain management); SPATIAL variation
- Publication
Journal of Hydrometeorology, 2021, Vol 22, Issue 11, p3017
- ISSN
1525-755X
- Publication type
Article
- DOI
10.1175/JHM-D-20-0289.1