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

Project Domain / Website

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

1. Downscaling2. 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

streamflowsoil moisture, snowpack

tailored to application sectorsfire, power, recreation

* ESPextended streamflow prediction(unconditional climate forecastsrun from current hydrologic state)

climate model output(NCEP, NSIPP)

CPC official forecasts (in progress)

Challenge: Climate Model Forecast Use

bias-correcting…

then downscaling…

CRB domain,June precip

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

Overview: VIC Hydrologic Model

Overview: Hydrologic Simulations

Forecast Productsstreamflow soil moisture

runoffsnowpack

derived productse.g., reservoir system

forecasts

model spin-upforecast 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

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

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

Overview: Initial snow state assimilation

SWE state differences due to assimilation of SNOTEL/ASP observations, Feb. 25, 2004

Overview: Initial conditionsSnow Water Equivalent (SWE) and Soil Moisture

Overview: Streamflow Forecast Locations

Overview: Spatial Forecastsmonthly values, anomalies and percentiles of: precip, temp, SWE, soil moisture, runoffgive streamflow forecasts greater context

SWE soil moisture

Overview: Streamflow Forecastshydrographs targeted statistics

raw ensemble data

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 =

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)