The Physical Basis of the Evaporative Demand Drought Index

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Thursday, 8 January 2015
Michael Hobbins, National Integrated Drought Information System, Boulder, CO; and D. McEvoy, A. W. Wood, J. Verdin, and J. Huntington

Poor representation of evaporative dynamics has long plagued operational drought monitoring, with some popular drought indices relying on only precipitation and temperature (T) to represent hydroclimatic anomalies. Such measures—an instructive example being the Palmer Drought Severity Index that informs much of the US Drought Monitor (USDM)—estimate evaporative demand (Eo) from a poorly performing T-based parameterization that is then used to derive actual evapotranspiration (ET).

Our goal is to create a drought index that both improves the representation of evaporative dynamics in drought and offers a useful leading indicator of both flash and sustained droughts. This presentation will outline the physical basis for such an index: the Evaporative Demand Drought Index (EDDI). EDDI measures the physical response of Eo to surface drying anomalies that occur due to two distinct land surface/atmosphere interactions. In sustained drought, land surface moisture availability is limited, forcing Eo and ET into in a complementary relationship: as ET declines, Eo increases due to the energy balance tipping to favor sensible heating. In flash droughts (which often precede sustained drought), increasing advection, radiation, and/or temperature or decreasing humidity force both ET and Eo upwards. Thus, in contrast to ET-based drought measures, Eo rises in response to both drought types, suggesting strong potential for use as a leading indicator of both drought types.

To examine the physical basis of EDDI, we use for Eo a daily, CONUS-wide reference ET (ETo) from the ASCE Standardized Reference ET equation forced by North American Land Data Assimilation System (NLDAS) drivers (T, specific humidity, downwards SW radiation, and wind speed). For ET, we use data from Atmosphere-Land Exchange Inverse (ALEXI), a two-source model driven by remotely sensed and surface observations that provides daily ET estimates independent of the Eo estimates. EDDI is derived from departures from a 30-year climatological mean ETo accumulated across a given time-window and double-standardized: first by standardizing the anomaly against climatologic ETo; then generating a Z–score. Positive EDDI indicates drier than normal conditions (and so, drought).

This presentation will summarize the different responses of Eo and ET to the various drought types, explain how Eo responses result in a useful drought indicator such as EDDI, examine the long-term performance of EDDI against the USDM in basins across CONUS's hydroclimatic spectrum, and demonstrate the promise of EDDI as a leading indicator of drought.