Abstract
Abstract. 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.
Highlights
High-resolution monitoring of vegetation health conditions using remote sensing observations provides valuable information that is widely used for a variety of purposes, such as drought monitoring (AghaKouchak et al, 2015), ecological health assessments (Li et al, 2014), and crop yield forecasting (Huang and Han, 2014; Johnson, 2016)
Note that the sign is reversed for the DPD, TEMP, WSPD, and DSW correlations given the expectation that larger values for each of these variables will typically be associated with higher moisture stress and negative Evaporative Stress Index (ESI) anomalies when assessed over long time periods
The correlations for DPD and WSPD are similar for all averaging periods. These patterns are evident in each region, but are most conspicuous across the south-central US, and remain consistent throughout the entire growing season. These results indicate that ESI anomalies computed over short time periods are most strongly influenced by short-to-intermediate fluctuations in soil moisture that in turn are controlled by precipitation and evaporative demand anomalies occurring over longer time periods
Summary
High-resolution monitoring of vegetation health conditions using remote sensing observations provides valuable information that is widely used for a variety of purposes, such as drought monitoring (AghaKouchak et al, 2015), ecological health assessments (Li et al, 2014), and crop yield forecasting (Huang and Han, 2014; Johnson, 2016). Though the ESI has primarily been used to monitor agricultural and ecological drought conditions (Anderson et al, 2007b, 2011; Otkin et al, 2013), and is well suited for the early detection of rapidonset flash drought events (Anderson et al, 2013; Otkin et al, 2015a, 2016, 2018), it can be used to identify regions with healthy vegetation as inferred by higher-than-average ET rates As such, it provides useful information about vegetation health under both favorable and unfavorable growing conditions and has been shown to have high correlations to agricultural crop yields (Anderson et al, 2016a, b; Otkin et al, 2016). That combines information from the ESI with precipitation and soil moisture anomalies to predict changes in the US Drought Monitor (Svoboda et al, 2002) over sub-seasonal timescales Their method had some forecast skill and was shown to provide useful forecasts, especially during flash drought events characterized by rapid intensification.
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