Subseasonal forecast skill of evaporative demand, soil moisture, and flash drought onset from two dynamic models over the contiguous United States

Abstract

Flash droughts are rapid developing subseasonal climate extreme events that are manifested as suddenly decreased soil moisture, driven by increased evaporative demand and/or sustained precipitation deficits. Over each climate region in the contiguous United States (CONUS), we evaluated forecast skill of weekly root-zone soil moisture (RZSM), evaporative demand (ETo), and relevant flash drought (FD) indices derived from two dynamic models (GEOSV2p1 and GEFSv12) in the Subseasonal Experiment (SubX) project between years 2000-2019 against three reference datasets: MERRA-2, NLDAS-2, and GEFSv12 reanalysis. ETo and its forcing variables at lead week 1 have moderate to high anomaly correlation coefficient (ACC) skill (~0.70-0.95) except downwelling shortwave radiation, and by weeks 3-4 predictability was low for all forcing variables (ACC <0.5). RZSM (0-100cm) for model GEFSv12 showed high skill at lead week 1 (~0.7-0.85 ACC) in the High Plains, West, Midwest, and South CONUS regions when evaluated against GEFSv12 reanalysis but lower skill against MERRA-2 and NLDAS-2 and ACC skill are still close to 0.5 for lead weeks 3-4, better than ETo forecasts. GEFSv12 analysis has not been evaluated against in situ observations and has substantial RZSM anomaly differences when compared to NLDAS-2 and our analysis identified GEFSv12 reforecast prediction limit, which can maximally achieve ACC ~0.6 for RZSM forecasts between lead weeks 3-4. Analysis of major FD events reveal that GEFSv12 reforecast inconsistently captured the correct location of atmospheric and RZSM anomalies contributing to FD onset, suggesting the needs for improving the dynamic models’ assimilation and initialization procedures to improve subseasonal FD predictability.