FLDAS: Project Goals

FLDAS is the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System

The FLDAS (McNally et al. 2017) is a custom instance of the NASA Land Information System (LIS; http://lis.gsfc.nasa.gov/) that has been adapted to work with domains, data streams, and monitoring and forecast requirements associated with food security assessment in data-sparse, developing country settings. Adopting LIS allows FEWS NET to leverage existing land surface models and generate ensembles of soil moisture, ET, and other variables based on multiple meteorological inputs or land surface models. The goal of the FLDAS project is to achieve more effective use of limited available hydroclimatic observations and is designed to be adopted for routine use for FEWS NET decision support.

The FLDAS includes a crop water balance model used operationally by FEWS NET (GeoWRSI: Verdin and Klaver, 2002; Senay and Verdin, 2003), Africa specific daily rainfall from NOAA Climate Prediction Center (RFE2; Xie and Arkin, 1997) and the CHIRPS, a quasi-global rainfall dataset designed for seasonal drought monitoring and trend analysis (Funk et al., 2015). Additional features include a temporal disaggregation scheme so that daily rainfall inputs can be used in both energy and water balance calculations, an irrigation module, and global irrigation and crop maps. State-of-the-practice land data assimilation methods are available in LIS, and will be explored in an associated forecasting project.

In addition to Africa, we the LIS team also routinely models model Snow over Central Asia. These data are provided to USGS EROS where specialized snow products are produced for agroclimatology partners in Afghanistan. Data and additional products are available at the USGS FEWS NET Data Portal.