Kostas Andreadis, Dennis Lettenmaier

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Presentation transcript:

Kostas Andreadis, Dennis Lettenmaier A System for Real-time Prediction of Hydrological Drought Over the Continental U.S. Andy Wood Kostas Andreadis, Dennis Lettenmaier Dept. of Civil and Environmental Engineering Land Surface Hydrology Research Group 2007 NOAA CPAS Workshop Seattle, WA March 2007

drought definition practices are evolving

talk outline experimental Surface Water Monitor background nowcast and retrospective products forecasting drought final comments

SW Monitor in a nutshell Background: merges UW west-wide streamflow forecast system methods with NLDAS modeling advances “index station” method + VIC implementation (Maurer et al., 2002) benefits from recent NCDC extension of digital data archives back to 1915 created to illustrate concept from unfunded NCTP05 proposal Future: water cycle analysis – current and retrospective “proving ground” for forecasting / assimilation methods will be useful for staging real-time products based on other UW drought reconstruction work: Severity-Area-Duration analysis (Andreadis et al. 2005) CONUS drought trends (Andreadis and Lettenmaier, 2006)

VIC Retrospective Simulation Index Station Method Gridded Forcing Creation SW Monitor Schematic NOAA ACIS Prcp Tmax Tmin Coop Stations 1930s 1955+ VIC Retrospective Simulation Daily, 1915 to Near Current Hydrologic State VIC Real-time Spinup Simulation Hydrologic State (-1 Day) Hydrologic values, anom’s, %-iles w.r.t. retrospective PDF climatology (PDF) of hydrologic values w.r.t. defined period vals, anoms %-iles w.r.t. PDF

www.hydro.washington.edu / forecast / monitor /

Surface Water Monitor products 1 month change in soil moisture 2 week change in SWE

Surface Water Monitor archive (1915-current) June 1934 Aug 1993

Drought delineation / S.A.D. index In each of these figures, the upper panel shows percent severity based on soil moisture. Red is most severe (100%), yellow is less severe (80%). The lower panel shows the classification of distinct drought events, with each color denoting a separate event. The question remains: How can we define a distinct drought event if droughts are continuous in one month, but discontinuous in the next month? Our algorithm identifies droughts at each time step, checks for common pixels between time steps, and groups the cluster with overlapping pixels at the current timestep with that in the last time step. If a drought seperates, as shown here, or merges, each subdrought (distinct) cluster is grouped as a continuation of the single larger drought event. However, in the subsequent steps, each subdrought is treated separately to ensure that only contiguous areas are compared. Work of Kostas Andreadis and Liz Clark

Washington State ‘Monitor’

Monitoring and Prediction Methods WA State soil moisture SWE

WA State testbed for experimental indices Can we develop alternative, model-based descriptors of drought and stage them reliably for use in state & local actions? NOAA PDSI smoothed SM %-ile

extension of monitoring to Mexico

Forecast Products Ensemble Streamflow Prediction (ESP) technique: combine: (1) estimate of current hydrologic state (2) forecast of historical climate produce: streamflow forecast with uncertainty information CPC Outlook ICs Spin-up Forecast obs recently observed meteorological data ensemble of met. data to generate forecast ESP-type forecast method hydrologic state

drought onset / recovery prediction

median forecasts Initial soil moisture percentiles 2/2006 1 month lead, forecast for 3/2006 3 month lead, forecast for 5/2006 6 month lead, forecast for 8/2006) median forecasts

Initial Condition

One month lead -- observed

Three month lead -- observed

Six month lead -- observed

California-Arizona drought recovery forecast SAD Index feb mar apr may jun jul aug

Texas drought recovery forecast SAD Index feb mar apr may jun jul aug

Verification possibilities? What are the obs for drought? In football, everything is complicated by the presence of the other team. Jean-Paul Sartre modeling observations. paraphrasing

Final Comment How will models (land surface / climate / coupled) become integrated into drought management? “nowcasting”, forecasting? retrospective diagnosis? attribution / detection?

Acknowledgments NOAA CDEP, CPPA, SARP, (TRACS?) Feedback from: CPC’s Doug Lecomte DRI’s Kelly Redmond SRCC’s Victor Murphy SRCC/ACIS’s David Sathiaraj In house: Ali Akanda, George Thomas Kostas Andreadis