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Application of LDAS-era Land Surface Models to Drought Monitoring and Prediction

Application of LDAS-era Land Surface Models to Drought Monitoring and Prediction. Andy Wood collaborators / contributors Shraddhanand Schukla Kostas Andreadis Dennis Lettenmaier Dept. of Civil and Environmental Engineering Land Surface Hydrology Research Group Drought Monitor Forum

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Application of LDAS-era Land Surface Models to Drought Monitoring and Prediction

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  1. Application of LDAS-era Land Surface Models to Drought Monitoring and Prediction Andy Wood collaborators / contributors Shraddhanand Schukla Kostas Andreadis Dennis Lettenmaier Dept. of Civil and Environmental Engineering Land Surface Hydrology Research Group Drought Monitor Forum Portland, OR October 2007

  2. drought definition practices are evolving

  3. talk outline • NOAA LDAS research into land surface models • UW “Surface Water Monitor” • forecasting drought • final comments

  4. NOAA’s Climate Predictions and Projection Program:Parent Program of CPPA (Climate Prediction Program for the Americas) • Objectives: • to provide climate forecasts to enable regional and national managers to better plan for the impacts of climate variability • to provide climate assessments and projections to support policy decisions with objective and accurate climate change information from j. huang, k. mitchell

  5. NCEP/EMC NWS/OHD NESDIS/ORA Dan Tarpley Ken Mitchell Dag Lohmann Andy Bailey NASA/GSFC Princeton Univ. Paul Houser Brian Cosgrove Eric Wood Justin Sheffield Univ. Washington Univ. Oklahoma Rutgers Univ. NOAA/ARL Dennis Lettenmaier Ken Crawford Jeff Basara John Schaake Qingyun Duan Alan Robock Lifeng Luo NCEP/CPC Tilden Meyers John Augustine Univ. Maryland Wayne Higgins Huug Van den Dool Rachel Pinker N-LDAS* Collaborators GCIP *North American Land Data Assimilation System Project http://ldas.gsfc.nasa.gov from ken mitchell presentation, march 2002

  6. LDAS Soil Wetness Comparison LDAS realtime output example from ken mitchell presentation, march 2002

  7. correlations obs obs Noah Noah RR RR ERA40 ERA40 most models are in the ballpark on soil moisture 1993 1988 from yun fan / huug vandendool

  8. models give similar, but different answers correlations VIC/Noah are LSMs; LB is leaky bucket; R*/ERA40 are reanalyses from yun fan / huug vandendool

  9. NLDAS-era models snow 1/8-degree resolution Runoff routing, calibration, validation Vegetation:UMD, EROS IGBP, NESDIS greenness, EOS products Soils: STATSGO, IGBP

  10. LDAS models sample validation of historic streamflow simulations

  11. What does an 1/8 degree grid cell look like in real life?

  12. talk outline • NOAA LDAS research into land surface models • UW “Surface Water Monitor” & other efforts • forecasting drought • final comments

  13. 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 Future Directions: • further development now funded by NOAA TRACS program • test methods for use at NOAA EMC / CPC, with products for NWCC & NDMC • water cycle analysis – current, retrospective, future • “proving ground” for forecasting methods at national scale • staging real-time products based on other UW drought reconstruction work: • Severity-Area-Duration analysis (Andreadis et al. 2005)

  14. Nowcast/Forecast System Consistency Issue new record or “*” ? Retrospective Simulation Daily, 1915 to Near Current “Modern” Simulation (last 5 years) Current Hydrologic State (Nowcast) ASSIMILATION Snow / Soil Moisture / Runoff / ETC

  15. Nowcast/Forecast System Consistency Issue consistent statistics Retrospective Simulation Daily, 1915 to Near Current “Modern” Simulation (last 5 years) Current Hydrologic State (Nowcast) ASSIMILATION Snow / Soil Moisture / Runoff / ETC

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

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

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

  19. Drought delineation / S.A.D. index Work of Kostas Andreadis and Liz Clark

  20. Washington State ‘Monitor’

  21. WA State Monitoring and Prediction Methods soil moisture SWE

  22. WA State Monitoring and Prediction Methods can use model-based systems to estimate traditional drought indices NOAA PDSI Oct 8, 2007 work by Shrad Shukla

  23. NOAA PDSI smoothed SM %-ile 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?

  24. talk outline • NOAA LDAS research into land surface models • UW “Surface Water Monitor” • forecasting drought • final comments

  25. drought onset / recovery prediction

  26. UW weekly national hydrologic predictions

  27. other nowcast / forecast efforts Seasonal predictions and verification of Spring 2007 drought conditions from the Princeton U. VIC/CFS-based uncoupled seasonal forecast system. (Jan ’07 prediction, L. Luo, E. Wood) http://hydrology.princeton.edu/forecast/ Primary Target: CPC’s North American Drought Briefing http://www.cpc.ncep.noaa.gov/products/Drought/

  28. talk outline • NOAA LDAS research into land surface models • UW “Surface Water Monitor” • forecasting drought • final comments

  29. Final Comment LDAS-era models can simulate and will be able to predict land surface variables (e.g., soil moisture) as climate forecasts improve. Many issues need resolving: - will there be a standard or consensus hydrologic product? - a ‘soil moisture deficit’ is not the same as ‘drought’ - what about traditional &/or meteorological indices? How will models (land surface / climate / coupled) become integrated into drought management? • “nowcasting”, forecasting? • retrospective diagnosis? • attribution / detection?

  30. Acknowledgments NOAA CDEP, CPPA, SARP, TRACS Feedback from: Doug Lecomte (CPC) Kelly Redmond (DRI) Victor Murphy (SRCC) Mark Svoboda (NDMC) David Sathiaraj (SRCC/ACIS) Tom Pagano & Phil Pasteris (NWCC) In house: Ali Akanda, George Thomas Kostas Andreadis, Shrad Shukla

  31. Initial Condition

  32. 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

  33. 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

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