Use of Climate Forecasts in Hydrologic Prediction Applications Alan F. Hamlet Dennis P. Lettenmaier JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering University of Washington

1hr - 1 week 1– 24 months years Weather Forecasts Flood Control and Hydropower Management Flood Forecasts Seasonal to Interannual Climate Forecasts Seasonal Streamflow Volumes Water Resources Management Climate Change Scenarios Long-Range Streamflow Forecasts Water Resources Planning Forecast Lead Time

Example of a Seasonal Forecasting System Based on Regression Models Hydrologic Index Regression Equation Streamflow Volume NRCS SNOTEL Network NRCS/NWRFC Water Supply Forecasts

Example of a Seasonal Forecasting System Using a Physically-Based Hydrologic Model Temperature and Precipitation Forecast Estimated Hydrologic State Hydrologic Forecast VIC Hydrologic Model UW West-Wide Seasonal Hydrologic Forecast System

Future Temperature and Precipitation Forecast Hydrologic Model Initial Hydrologic State Soil Moisture Snowpack Hydrologic Forecast: Streamflow Soil Moisture Snowpack Evaporation Schematic Diagram of a Hydrologic Forecasting System

Simulated Water Balance for the Pacific Northwest

In October future precipitation dominates the inputs to the water balance. In April inputs to the water balance from future precipitation and storage are comparable. Relative Roles of Future Precipitation and Initial Hydrologic State at Different Forecast Dates 99% 46% Simulated Long-Term Water Balance for the Pacific Northwest

Seasonal to Interannual Time Scales

Hydroclimate Signals in the Columbia River Basin Associated with ENSO and Pacific Decadal Variability Cool PDO Cool PDO Warm PDO Warm PDO Red = warm ENSO Green = neutral Blue = cool ENSO

Evaluation of Sept 1 ECMWF Nino3.4 Forecast for WY WY 2003 WY 2004WY 2005

Red = Unconditional mean Blue = Ensemble mean Black = 2005 Observed Natural Streamflow (cfs) Retrospective tests in the Columbia River basin have shown that during cool or warm events, ENSO-based streamflow forecasts are superior to assumptions of “normal” conditions about 65 % of the time on Oct 1 In the PNW Climate forecasts based on ENSO predictions can provide useful information about future streamflows with lead times up to 12 months. Natural Streamflow Columbia River at The Dalles, OR

PNW Trend CRB Trend (Regional to PDO Correlation R 2 ) Can we predict decadal precip. variability?

7-14 Day Time Scales

NOAA’s reforecast data set Model: T62L28 NCEP GFS, circa 1998 Initial Conditions: NCEP-NCAR Reanalysis II plus 7 +/- bred modes. Duration: 15 days runs every day at 00Z from to now. ( Data: Selected fields (winds, hgt, temp on 5 press levels, precip, t2m, u10m, v10m, pwat, prmsl, rh700, heating). NCEP/NCAR reanalysis verifying fields included (Web form to download at Real-time probabilistic precipitation forecasts: Hamill, T. M., J. S. Whitaker, and X. Wei, 2004: Ensemble re-forecasting: improving medium-range forecast skill using retrospective forecasts. Mon. Wea. Rev., 132,

Precipitation Skill Hamill, T. M., J. S. Whitaker, and X. Wei, 2004: Ensemble re-forecasting: improving medium-range forecast skill using retrospective forecasts. Mon. Wea. Rev., 132,

Compositing Approaches Using the Pacific North America Pattern Medium Range Forecast Model PNA Ensemble Gridded Temperature Precipitation Data 7-14 Day Temperature Precipitation Forecast compositing

Ensemble PNA Forecast

Implications of Climate Change

Pacific Northwest °C °C °C °C Observed 20th century variability +1.7°C +0.7°C +3.2°C Until mid-century, emissions scenarios play a minor role in the temperature impacts. Towards the end of the century they play a big role. Conclusions: 1) Adaptation will be an essential component of the response to warming over the next 50 years. 2) Mitigation of greenhouse gas emissions will play an important role in determining the scope of late 21 st century impacts.

Simulated Changes in Natural Runoff Timing in the Naches River Basin Associated with 2 C Warming Increased winter flow Earlier and reduced peak flows Reduced summer flow volume Reduced late summer low flow

°C Climate change assessments using scenarios show significant hydrologic changes due to temperature in basins with substantial snow accumulation in winter. Naches River Basin on the East Slopes of the Cascades. 20 th Century Change

Tmin Tmax PNW CA CRB GB Canada USA Observed Temperature Trends in the Western U.S. ( )

Mote P.W.,Hamlet A.F., Clark M.P., Lettenmaier D.P., 2005, Declining mountain snowpack in western North America, BAMS, 86 (1): Trends in April 1 SWE

Regionally Averaged Cool Season Precipitation Anomalies PRECIP

Climate Models vs. Statistical Approaches

Dynamic Approaches Based on Climate Models Potential Advantages: Ideally accounts for extraordinary changes in the climate system in ways that statistical procedures may ignore or discount (e.g. loss of sea ice in the arctic, altered radiative forcing due to current greenhouse forcing, effects due to soil moisture anomalies, etc.) Reforecast approaches suggest useful precipitation skill in some areas at 6-10 days, but linkage to hydrologic models is needed for test purposes. Limitations: Model bias must almost always be removed (so not a purely dynamic system) With some few exceptions, there has been very limited demonstrated precipitation skill in the U.S. at seasonal to interannual time scales in real-time forecast applications. (Role of downscaling procedures?) Relatively expensive to implement.

Statistical Approaches Potential Advantages: Exploits strengths of models (e.g. large scale index forecasts) while avoiding problems (precipitation simulation). Relatively low implementation costs. Relatively high skill. Limitations: Cannot account easily for unique features of individual years (e.g. different “flavors” of ENSO ) Requires a training data set—problems with parameter stationarity.

Conclusions Useful hydrologic forecasts based on weather or climate forecasts are available with lead times ranging from a few hours (flood forecasts) to 50 years or more (climate change scenarios). Many operational hydrologic forecasting systems are currently based on statistical models, however dynamic, physically-based tools are increasingly being used in both academic and operational forecasting systems. Dynamic forecasting systems based on weather or climate models directly linked to physically-based hydrologic models have important advantages in a rapidly evolving climate system. Short-term forecasts based on weather models have already reached a useful state of development, but many challenges remain at seasonal or longer time scales.

Extras

MM5 mesoscale atmospheric model DHSVM distributed hydrologic model Streamflow Forecast River Stage Forecast Example of a Short Time Scale Flood Forecasting System Estimated Hydrologic State

Background: Forecast System Schematic NCDC met. station obs. up to 2-4 months from current local scale (1/8 degree) weather inputs soil moisture snowpack Hydrologic model spin up SNOTEL Update streamflow, soil moisture, snow water equivalent, runoff 25 th Day, Month years back LDAS/other real-time met. forcings for spin-up gap Hydrologic forecast simulation Month INITIAL STATE SNOTEL Update ensemble forecasts ESP traces (40) CPC-based outlook (13) NCEP GSM ensemble (20) NSIPP-1 ensemble (9)