![Page 1: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/1.jpg)
Experimental seasonal hydrologic forecasting for the Western U.S.
Dennis P. LettenmaierAndrew W. Wood,
Alan F. Hamlet
Climate Impacts GroupUniversity of Washington
Climate Prediction Applications WorkshopTallahassee, FL
March 10, 2004
![Page 2: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/2.jpg)
Project Domain / Website
![Page 3: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/3.jpg)
Forecasting System Evolution
(Funding from: NASA NSIPP; OGP/ARCS; OGP GAPP), NASA Applications)
1998-9
2000
2001
2003
2004
Ohio R. basin w/ COE: First tried climate model-based seasonal forecasts on experimental (retrospective) basis
Eastern US: First attempted real-time seasonal forecasts during drought condition in southeastern states -- results published in: Wood et al. (2001), JGR
Columbia R. basin: Implemented approach during the PNW drought, again using climate model based approach
2002 Western US: Retrospective analysis of forecasts over larger domain (for one climate model and for ESP)
Columbia R. basin: New funding for “pseudo-operational” implementation for western US; began with pilot project in CRB
Western US: expanded to western U.S domain for real-time forecasts; working to improve and evaluate methods each forecast cycle
![Page 4: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/4.jpg)
1. Downscaling
2. VIC hydrologic simulations
UW Experimental West-wide hydrologic prediction system
ESP as baseline fcst
Real-timeEnsemble Forecasts
Ensemble Hindcasts(for bias-correction
and preliminaryskill assessment) West-wide forecast products
streamflow
soil moisture, snowpack
tailored to application sectors
fire, power, recreation
* ESPextended streamflow prediction(unconditional climate forecastsrun from current hydrologic state)
climate model output(NCEP, NSIPP)
CPC official forecasts (in progress)
![Page 5: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/5.jpg)
Challenge: Climate Model Forecast Use
bias-correcting…
then downscaling…
CRB domain,June precip
![Page 6: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/6.jpg)
Overview: Bias Correction
specific to calendar monthand climate model grid cell
numerous methods of downscaling and bias correction exist
the relatively simple one we’ve settled on requires a sufficient retrospective climate model climatology, e.g., NCEP: hindcast ensemble climatology, 21 years X 10 member NSIPP-1: AMIP run climatology, > 50 years, 9 member
![Page 7: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/7.jpg)
Overview: VIC Hydrologic Model
![Page 8: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/8.jpg)
Overview: Hydrologic Simulations
Forecast Productsstreamflow soil moisture
runoffsnowpack
derived productse.g., reservoir system
forecasts
model spin-up
forecast ensemble(s)
climate forecast
information
climatology ensemble
1-2 years back start of month 0 end of mon 6-12
NCDC met. station obs. up to 2-4
months from current
2000-3000 stations in western US
LDAS/other real-time met. forcings for remaining
spin-up~300-400
stations in western US
data sources
obs snow state information
initi
al
cond
ition
s
![Page 9: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/9.jpg)
Problem: met. data availability in 3 months prior to forecast has only a tenth of long term stations used to calibrate model
Solution: use interpolated monthly index station precip percentiles and temperature anomalies to extract values from higher quality retrospective forcing data, then disaggregate using daily index station signal.
Challenge: Hydrologic State Initialization
dense station network for model calibration sparse station network in real-time
![Page 10: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/10.jpg)
Overview: Initial snow state assimilation
Problem sparse station spinup incurs some systematic errors, but snow state estimation is critical
Solution use SWE anomaly observations (from the 600+ station USDA/NRCS SNOTEL network and a dozen ASP stations in BC, Canada) to adjust snow state at the forecast start date
![Page 11: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/11.jpg)
Overview: Initial snow state assimilation
SWE state differences due to assimilation of SNOTEL/ASP observations, Feb. 25, 2004
![Page 12: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/12.jpg)
Overview: Initial conditionsSnow Water Equivalent (SWE) and Soil Moisture
![Page 13: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/13.jpg)
Overview: Streamflow Forecast Locations
![Page 14: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/14.jpg)
Overview: Spatial Forecasts
monthly values, anomalies and percentiles of: precip, temp, SWE, soil moisture, runoffgive streamflow forecasts greater context
SWE soil moisture
![Page 15: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/15.jpg)
Overview: Streamflow Forecasts
hydrographs targeted statistics
raw ensemble data
![Page 16: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/16.jpg)
![Page 17: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/17.jpg)
Challenge: Balancing IC effort with forecast effort
Columbia R. Basin (CRB)
Rio Grande R. Basin (RGB)
RMSE (perfect IC, uncertain fcst)
RMSE (perfect fcst, uncertain IC)RE =
![Page 18: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/18.jpg)
![Page 19: Experimental seasonal hydrologic forecasting for the Western U.S. Dennis P. Lettenmaier Andrew W. Wood, Alan F. Hamlet Climate Impacts Group University](https://reader034.vdocuments.site/reader034/viewer/2022051621/56649ea05503460f94ba2b43/html5/thumbnails/19.jpg)
www.hydro.washington.edu/Lettenmaier/Projects/fcst/
Some obstacles and opportunities in hydrological application of
climate information• The “one model” problem
• Calibration and basin scale (post-processing as an alternative to calibration)
• The value of visualization
• Opportunities to utilize non-traditional data (e.g. remote sensing)