ESSIC Scientists Abheera Hazra and Kimberly Slinski are co-authors on a new paper in Journal of Hydrology that describes the improvements in seasonal hydrologic forecasts produced with the updated FEWS NET Land Data Assimilation System.
Socioeconomic concerns, political issues, and environmental factors can make in situ hydrologic monitoring over regions most susceptible to food insecurity challenging. To sidestep these barriers, remotely sensed and analyzed data can contribute significantly to early warning in these regions. Recently, NASA’s Hydrologic Forecasting and Analysis System (NHyFAS) has added routine hydrologic forecasts to early warning systems. The Famine Early Warning Systems Network (FEWS NET), a leading provider of early warning and analysis on food insecurity, is using a custom instance of NHyFAS, termed FLDAS-Forecast, in their Land Data Assimilation System (FLDAS). The FLDAS-Forecast’s dynamic forecasting component was originally set up with Goddard Earth Observing System (GEOS) forecast inputs and has been recently expanded with precipitation forecast forcing from the North American Multi-Model Ensemble (NMME).
The researchers evaluated soil moisture across southern Africa’s growing season, evaluating moisture forecasts relative to climatology-based forecasts and historic runs. These forecasts are then verified with remotely sensed observations of soil moisture and vegetation.
The team found that using the larger ensemble of NMME precipitation inputs in the forecast system results in higher quality hydrologic forecasts than are allowed by climatology- or GEOS-only-based forecasts. Further, the near-real-time NMME-based rootzone soil moisture forecasts were able to correctly predict developing drought conditions over southern Africa through late 2019 and into early 2020.
Hazra is an Assistant Research Scientist at the Earth System Science Interdisciplinary Center (ESSIC) at the University of Maryland and in the Hydrological Sciences Laboratory at the NASA Goddard Space Flight Center. Her research interest includes hydrologic predictions of extreme conditions, designing experiments for better understanding of land and atmospheric processes through simulations using dynamical models such as NoahMP, CLSM, CESM and CAM. Her previous research experiences were at University of California Santa Barbara’s Earth Research Institute (California) and George Mason University’s Department of Civil, Environmental and Infrastructural Engineering (Virginia). She currently leads the task of routine hydrologic forecasting (FLDAS-Forecast) over continental Africa and the Middle East and has authored and been part of several peer reviewed articles, as well as research presentations.
Slinski currently holds a position as an Assistant Research Scientist both at the Earth System Science Interdisciplinary Center (ESSIC) at the University of Maryland and in the Hydrological Sciences Laboratory at the NASA Goddard Space Flight Center. She graduated with an undergraduate degree in Civil Engineering from Johns Hopkins University before continuing her education at Cornell University (M.S. in Agricultural and Biological Engineering) and the Colorado School of Mines (CSM) where she earned her Ph.D in Hydrology. Kim has a vast array of research experience including serving in various roles in institutions across the world including the Institut des Géosciences de l’Environnement (France), NASA Goddard, CSM, and UMD ESSIC. She has many contributions to environmental studies through her authorship of hydrological data sets and research presentations at many conferences and workshops around the United States.
To access the paper, click here: “NASA’s NMME-based S2S hydrologic forecast system for food insecurity early warning in southern Africa”.
