Optimizing the Uses of the Hydrologic Ensemble Forecast System at a National Weather Service River Forecast Center

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Monday, 5 January 2015: 2:15 PM
127ABC (Phoenix Convention Center - West and North Buildings)
Eric T. Jones, NOAA/NWS, Tulsa, OK; and R. Harjo and T. Anderson

The Arkansas-Red Basin River Forecast Center (ABRFC) will be creating new probabilistic streamflow products in the future. These products will convey the uncertainty in the forecast through ensembles, with the forecast confidence being visible in the spread between the ensemble members. Forecast users can incorporate the additional information regarding the forecast's confidence and uncertainty into their decision making processes.

The ABRFC embarked on the implementation of the National Weather Service Hydrologic Ensemble Forecast System (HEFS) in October 2012 using the Community Hydrologic Prediction System (CHPS). HEFS currently uses statistical processing to create localized probabilities of precipitation and temperature based on local deterministic forecasts along with the ensemble mean of global-scale models. These probabilities are used as forcings in hydrologic models to produce uncertainties in streamflow forecasts. The ABRFC plans to provide users with both short and long term probabilistic hydrologic forecasts. Emergency managers, reservoir managers, recreational users, and the informed public are targeted users of the short term forecasts. The targeted users of long term forecasts are primarily water managers and agricultural entities.

Numerous verification metrics were studied at various river locations and basins across the ABRFC area to subjectively optimize future time horizons of these probabilistic forecasts. Also subjective analyses were performed on many individual events to discover the strengths and weaknesses of the HEFS system. Results of these analyses will aid in formulating policy on the creation and issuance of new forecast products that can provide users the most reliable and skillful forecast available while still minimizing false alarms.