Application of a medium range global hydrologic probabilistic forecast scheme to the Ohio River Basin

Abstract A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003–07. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis temperatures and winds, and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF Ensemble Prediction System (EPS) 10-day ensemble forecast. A parallel setup was used where ECMWF EPS forecasts were interpolated to the spatial scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effects of the initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The hydrologic prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. The initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.

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Calibration and Downscaling Methods for Quantitative Ensemble Precipitation Forecasts

Weather and Forecasting ◽

10.1175/2010waf2222367.1 ◽

2010 ◽

Vol 25 (6) ◽

pp. 1603-1627 ◽

Cited By ~ 47

Author(s):

Nathalie Voisin ◽

John C. Schaake ◽

Dennis P. Lettenmaier

Keyword(s):

River Basin ◽

Ensemble Prediction ◽

Forecast Errors ◽

Ohio River ◽

Ensemble Prediction System ◽

Weather Forecasts ◽

Precipitation Patterns ◽

Ohio River Basin ◽

Medium Range ◽

Analog Approach

Abstract Two approaches for downscaling and calibrating error estimates from ensemble precipitation forecasts are evaluated; the two methods are intended to be used to produce flood forecasts based on global weather forecasts in ungauged river basins. The focus of this study is on the ability of the approaches to reproduce observed forecast errors when applied to daily precipitation forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) for a 10-day forecast period. The two approaches are bias correction with spatial disaggregation (BCSD) and an analog technique. Mean forecast errors and skills are evaluated with respect to Tropical Rainfall Monitoring Mission (TRMM) observations over the Ohio River basin for the period 2002–06 for daily and 5-day accumulations and for 0.25° and 1° spatial resolutions. The Ohio River basin was chosen so that a relatively dense gauge-based observed precipitation dataset could also be used in the evaluation of the two approaches. Neither the BCSD nor the analog approach is able to improve on the forecast prediction skill resulting from a simple spatial interpolation benchmark. However, both approaches improve the forecast reliability, although more so for the analog approach. The BCSD method improves the bias for all forecast amounts (but less so for large amounts), but the downscaled precipitation patterns are unrealistic. The analog approach reduces biases over a wider range of forecast amounts, and the precipitation patterns are more realistic.

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