Evaporative Demand Drought Index (EDDI)
Description
Standardization of ETo similar to SPI has shown to be useful for drought monitoring and analysis of atmospheric land surface coupling and feedbacks. One example is the Evaporative Demand Drought Index (EDDI; Hobbins et al., 2016; McEvoy et al., 2016), which is showing promise as a leading indicator of agricultural drought at time-frames pertaining to both flash (i.e., fast-developing) and extended droughts. For time periods of interest, if ETo is higher than normal it is usually indicates dry and hot conditions, whereas lower than normal ETo usually indicates moist and cool conditions. ETo responds positively to both flash droughts and sustained droughts. ETo rises in response to drought via the complementary relationship, where drought typically increases air temperature and lowers humidity levels due to the lack of precipitation and subsequent lack of actual ET. ET based drought metrics complement other in drought metrics.
Climate Engine computes EDDI (and SPEI) using a non-parametric standardized probability based method. Plotting positions are used to obtain probabilities and then converted to EDDI and SPEI values using an inverse-normal distribution.
References