Global Drought Information System: Influence of Differences in Land Surface Model Dynamics on Drought Monitoring

Monday, 15 December 2014
Bart Nijssen, University of Washington, Seattle, WA, United States, Shraddhanand Shukla, University of California Santa Barbara, Santa Barbara, CA, United States, Kingtse C Mo, NOAA Science Center, College Park, MD, United States and Dennis P Lettenmaier, University of California, Los Angeles (effective Nov., 2014), Dept. of Geography, Los Angeles, CA, United States
Real-time drought monitoring enables a proactive drought management approach that can lead to timely actions to mitigate the losses due to a drought event. In recent years, the availability of long-term, high quality, satellite and reanalysis based datasets of atmospheric forcings, combined with the development of state-of-the-art hydrologic models have made real-time global drought monitoring feasible. Hydrologic models are invaluable tools for global drought monitoring given the scarcity of long-term moisture observations (e.g. soil moisture, streamflow). However, as valuable as they are for drought monitoring, characteristics of a drought event (i.e. onset, severity and persistence) as estimated by a hydrologic model depend on the model’s parameters (e.g. soil and vegetation parameters) and its inherent dynamics that guide the partition of precipitation into evapotranspiration and runoff. One approach to account for the differences in drought estimates due to differences in model dynamics is to use multiple hydrologic models. Each hydrologic model is forced with the same atmospheric forcings to simulate moisture conditions which are converted into objective drought indicators (e.g. soil moisture percentile) with respect to the model’s own climatology and then those estimates are combined to provide a multimodel based drought estimates. The University of Washington’s Global Drought Information System (GDIS) developed in 2013, is one such prototype drought monitoring system. This system uses the VIC, NOAH and Catchment models. In this presentation we investigate how the differences in the dynamics of the models used in UW’s GDIS, influence the drought monitoring estimates. Specifically we answer following questions: 1.What is the level of uncertainties in drought onset, severity and persistence as estimated by different hydrologic models? 2. How do the uncertainties vary spatially and seasonally? 3. What are the sources of the uncertainties?