Global Flash Drought Monitoring Using Surface Soil Moisture

Abrupt onset and swift intensification characterize flash droughts. Global surface soil moisture (theta(RS)) from NASA's Soil Moisture Active Passive (SMAP) satellite can facilitate a near-real-time assessment of emerging flash droughts at a 36-km footprint. However, a robust flash drought monitoring using theta(RS) must account for the (a) short observation record of SMAP, (b) nonlinear geophysical controls over theta(RS) dynamics, and (c) emergent meteorological drivers of flash droughts. We propose a new method for near-real-time characterization of droughts using Soil Moisture Stress (SMS, drought stress) and Relative Rate of Drydown (RRD, drought stress intensification rate)-developed using SMAP theta(RS) (March 2015-May 2021), footprint-scale seasonal soil water retention parameters and land-atmospheric coupling strength. SMS and RRD are nonlinearly combined to develop Flash Drought Stress Index (FDSI) to characterize emerging flash droughts (FDSI >= 0.71 for moderate to high RRD and SMS). Globally, FDSI shows a high correlation with concurrent meteorological anomalies. A mechanistic evaluation of flash droughts is presented for the Northern Great Plains, Central South Africa, and Eastern Australia using FDSI, SMS, and RRD. About 5.6% of the earth's landmass experienced flash droughts of varying intensity and duration during 2015-2021 (FDSI >= 0.71 for >30 consecutive days), majorly in global drylands. FDSI shows high skill in forecasting vegetation health with a lead of 0-2 weeks, with exceptions in irrigated croplands and mixed forests. With readily available parameters, low data latency, and no dependence on model simulations, we provide a robust tool for global near-real-time flash drought monitoring using SMAP.

Automated summary

Flash droughts are characterized by sudden onset and rapid intensification, and can be assessed in near-real-time using global surface soil moisture data from the SMAP satellite. A new method involving the development of the Flash Drought Stress Index (FDSI) using SMS and RRD parameters shows high skill in forecasting vegetation health.