1. Towards a global drought prediction capability
Dennis P. Lettenmaier
Department of Civil and Environmental Engineering
University of Washington
Workshop on Adapting to the impacts of global changes on river basins and aquifer systems
UNESCO/IHP, Paris
September 8, 2008

2. Outline Some characteristics of droughts
A model-based approach to real-time drought estimation
Drought forecasting and predictability
U.S. multimodel implementation
Challenges in global adaptation
Summary

3. Characteristics of droughts
Standard definition lacking, but meteorological drought mostly associated with precipitation deficits, agricultural drought with soil moisture, and hydrological drought with runoff
Spatial as well as temporal dimension is critical
Droughts don’t necessarily conform to river basin boundaries
Slowly evolving, and mostly slowly ending
Hydrologic predictability mostly due to ICs (snow and soil moisture storage)

4. Drought nowcasting– the U.S. experience
U.S. DM is widely used, but link to direct observations (e.g., of soil moisture) is weak – hence reliance on indirect methods, such as PDSI.
Need for reproducible basis for identifying drought-affected regions.
Land surface model representations of soil moisture (and runoff) offer an alternative means for estimating severity, frequency, duration, and variability of current droughts, and linking them to the climatology of observed droughts.

5. Rational for model-based approaches
Gridded observation-based precipitation products provide a basis for estimation of products like SPI
No such equivalent soil moisture data exist over large areas
While streamflow gauge networks exist (especially in developed countries), use of gauge data introduces spatial scale dependence, and management effects – difficult to extract information about spatial dimension of runoff from gauge observations

9. Extent of drought over continental U. S
Extent of drought over continental U.S. based on reconstructed total column soil moisture, June 1988

10. Severity Area Duration analysis Andreadis et al, JHM, 2005)
Similar to Depth Area Duration analysis (design storms)
Encompasses drought characteristics (severity, spatial extent and duration)
Each event has its own set of SAD curves

11. Soil Moisture SAD envelope curves
1930s and 1950s droughts most severe for short and long durations respectively
2000s W US drought among the most severe

12. Near-real time CONUS soil moisture based on VIC

13. Data
Daily precipitation and temperature max-min, other land surface variables (downward solar and longwave radiation, near-surface humidity, and wind) derived via index methods. Methods as described in Maurer et al. (2002). Data duration is from , and period of analysis is Spatial resolution 0.5  (3322 land grid cells), domain conterminous United States.
Soil and vegetation parameters are from different sources for different models (generally NLDAS), as provided by model developers. Other parameters are model standard setup.

14. Multi-model approach (for details see Wang et al, J Clim in review)
VIC: Variable Infiltration Capacity Model
(Liang et al. 1994)
CLM3.5: Community Land Model version 3.5
(Oleson et al. 2007)
NOAH LSM: NCEP, OSU, Air Force, Hydrol. research lab
(Mitchell et al. 1994, Chen and Mitchell 1996)
Sacramento (grid-based version of NWS operational
hydrologic prediction system; uses NOAH PET)
(Burnash et al, 1973)

15. The challenge: Different land schemes have different soil moisture dynamics
Model simulated
soil moisture at cell
(40.25N, W)

16. Solution: Normalize total column soil moisture as percentiles relative to each model’s climatology
For each model, total column soil moisture was expressed as percentiles (hence by construct, uniformly distributed from zero to one).
Percentiles were estimated for each model by month, using simulated total column soil moisture for the period
Percentiles were computed using the Weibull plotting position formula.

17. Areas for spatially averaged soil moisture percentilesNW NE SW SE
Box sizes are 5 x 5 degrees

18. NW

19. NE

20. SW

21. SE

22. Multimodel results from UW real-time surface water monitor, 11/07 – 1/08

23. UW SWM for 9/7/08 (updated 9/5/08)

24. Drought forecasting – ensemble forecast approaches

25. DEMETER forecast predictability evaluation
VIC model long-term ( ) simulations at ½ degree spatial resolution assumed to be truth
DEMETER reforecasts with ECMWF seasonal forecast model for 6 month lead, forecasts made on Feb 1, May 1, Aug 1, Nov
9 forecast ensembles on each date
Forecast forcings (precipitation and temperature) downscaled and bias corrected using Wood et al approach (also incorporated in UW West-wide system)
On each forecast date, 9 ensemble members also resampled at random from to form ESP ensemble
Forecast skill evaluated using Cp for unrouted runoff

26. Test sites

27. Missouri River at Fort Benton

28. Snake River at Milne

29. Owyhee River

30. Riley

31. Rosco

32. Challenges in global implementation
Availability of accurate real-time precipitation (satellite products are only viable alternative over much of the globe)
Reliable historical climatology for evaluation of drought statistics (transformation to percentiles
Validation data

33. TRMM multi-satellite precipitation “research product”, evaluation over La Plata basin

34. Bias in TRMM TMPA research and real-time precipitation products in La Plata basin, 2003-2005

35. Implementation in African Drought Monitor (Sheffield et al, GEWEX NEWS, Aug. 2008)

36. Summary and Conclusions
Current drought products suffer from the absence of reproducible, objective methods for identifying drought extent and severity.
Land surface parameterizations, such as the family of NLDAS models, avoid these shortcomings. However, soil moisture, a key drought-related variable, is model-dependent
Multi-model estimates of soil moisture, appropriately normalized, address all of the above shortcomings. When forced with common observations, major drought events appear to be plausibly reproduced by the individual models, and two methods of combining results into a multi-model ensemble.
The challenges in global implementation of these methods have to do mostly with data availability and quality. Particularly for data-sparse areas (where improved drought nowcasting and forecasting is arguably most needed) improvements in consistency between retrospective and real-time precipitation products (effectively reanalysis of satellite products) are needed.