HR: 1340h
AN: H13G-1390    [Abstracts]
TI: Assessing the Importance of Hydrologic Initial Conditions Versus Climate Forecast Errors for Seasonal Hydrologic Prediction
AU: * Wood, A W
EM: aww@u.washington.edu
AF: University of Washington, Department of Civil and Environmental Engineering Box 352700, Seattle, WA 98195 United States
AU: Lettenmaier, D P
EM: lettenma@u.washington.edu
AF: University of Washington, Department of Civil and Environmental Engineering Box 352700, Seattle, WA 98195 United States
AB: Seasonal streamflow forecast uncertainty arises mainly from errors in specifying forecast initial conditions and in predicting atmospheric forcings (primarily precipitation, but also temperature and other surface variables) during the forecast period. By contrasting the influence of perturbations in initial conditions versus forcings, the relative contribution of uncertainty in each to forecasts errors can be estimated. In the context of hydrologic forecasting, the most important initial conditions are the moisture states (snowpack and soil moisture), while the forcings are time series of climate variables such as precipitation and temperature. Via a retrospective analysis of six month hydrologic forecasts (of snowpack, runoff and soil moisture) in the western U.S., we estimated the relative contributions of uncertainty in these two sources to forecast uncertainty at different lead times, and for different forecast initiation months. The analysis is based on comparison of the results of Ensemble Streamflow Prediction (ESP) forecasts with those of a "reverse-ESP" approach. In the former, forecasts are produced by coupling perfect initial conditions with an ensemble of climate forecasts derived from observed climate sequences; whereas for the latter, a perfect climate forecast is coupled with an ensemble of initial conditions. The climate sequences are taken from a retrospective observation-based dataset, and the initial conditions are simulated using this forcing dataset and semi-distributed macroscale hydrologic model. Based on the relative variance of the forecast error in the two experiments: a) uncertainty in initial snowpack and soil moisture dominate forecast uncertainty in winter and spring, and in summer, respectively, for lead times of 3-5 months; while in autumn, initial soil moisture uncertainty influence was limited to 1-2 months; and b) boundary forcing uncertainty dominated forecast uncertainty at longer lead times. The results, which show considerable variation for streamflow locations across the domain, indicate when and where improvements in initial state estimation versus in climate forecasts will most benefit hydrologic forecasts, and ultimately, the forecast end users.
DE: 1816 Estimation and forecasting
DE: 1833 Hydroclimatology
DE: 1836 Hydrological cycles and budgets (1218, 1655)
DE: 1840 Hydrometeorology
DE: 1873 Uncertainty assessment (3275)
SC: Hydrology [H]
MN: Fall Meeting 2005