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Roadmap for Hydrologic Ensemble Forecast Services

The Hydrologic Ensemble Forecast Services (HEFS) initiative aims to revolutionize water forecasting by addressing core challenges and integrating advanced hydrologic science into National Weather Service operations. Current short-range forecasts are overly simplistic, leaving gaps in understanding and predicting hydrologic events. HEFS will provide an end-to-end ensemble forecast framework that incorporates multiple time scales and diverse hydroclimatic regimes, enabling improved forecast accuracy and decision support. Field testing and collaborative efforts with key institutions will drive implementation, ensuring a seamless transition to more sophisticated forecasting capabilities.

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Roadmap for Hydrologic Ensemble Forecast Services

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  1. Roadmap for Hydrologic Ensemble Forecast Services

  2. Outline • Challenges • Solution – Seamless suite of Hydrologic Ensemble Forecast Services (HEFS) • Current vs. HEFS • Key HEFS Components • Status and Schedule • Field Testing • Budget • Issues and Risks

  3. Background: Water Forecasting Challenges • Implement mature hydrologic science into NWS operations within the constraints of existing infrastructure (data, IT, and people) • Calibrate and enhance hydrologic modeling systems for multiple time scales and over diverse hydroclimatic regimes

  4. Problem • Current short-range river forecasts are single-valued • RFC forecasters examine selected set of “what-if” scenarios • Other ensemble products include bias • No integration of short, medium, long range NWP forecasts

  5. Objective: Ensemble Based Probabilistic Forecast Products Run ensembles of inputs through river models to generate hydrologic forecasts Analyze ensemble information to quantify forecast uncertainty and produce a full range of possible hydrologic scenarios

  6. Hydrologic Ensemble Forecast Services (HEFS) • End-to-end hydrologic ensemble forecast service currently under development • Comprehensive plan developed in 2007 (the first of its kind in the world) • Based and built on leading-edge science and technology • OHD collaborating with NCEP, OAR and universities through: • The Observing-System Research and Predictability Experiment (THORPEX) • Climate Prediction Program for the Americas (CPPA) Core Project • The Hydrologic Ensemble Prediction Experiment (HEPEX) • Research grants • Field deployment via the Community Hydrologic Prediction System (CHPS) • Experimental (prototype) components under evaluation at some RFCs • Additional prototype deployments during the next 2 years

  7. Current (Seasonal ESP) vs. HEFS

  8. Hydrologic Ensemble Prediction System:Key Components Weather & Climate Forecasts Verification System Correct NCEP Model Bias QPE, QTE, Soil Moisture Assess Hydrologic Model Error Create Hydrologic Ensembles AssimilateData Correct Hydrologic Ensemble Bias Streamflow Generate Product

  9. XEFS linkage: EXperimental Ensemble Forecast System (XEFS) EPP User Interface Ens. User Interface XEFS Graphical User Interface OFS Flow Data MODs Web Inter-face IFP Ens. Streamflow Prediction System EPP3 ESP2 EnsPost EPG Hydro-meteorol. ensembles Raw flow ens. Ens. Post-Proc. Pp’ed flow ens. Product Generation Subsystem Ensemble/prob. products Ens. Pre-Processor HMOS Ensemble Processor Atmospheric forcing data Hydrologic Ensemble Hindcaster EVS Ensemble verification products Ensemble Verification System 9

  10. Proposed HEFS Components Merging, Joining & Blending Short-Range Medium-Range Other Ensembles Long-Range 10

  11. HEFS – Field Testing Ensemble Pre-Processor Hydrologic Model Output Statistics (HMOS) Ensemble Processor Ensemble Verification Hydrologic Ensemble Hindcaster

  12. CHPS and HEFS Deployment Plans Develop software-engineered AWIPS II baseline software Prototype components development Today CHPS HEFS 4 RFCs 9 RFCs HEFS capabilities first available to RFCs 2008 2009 2010 20112012 FY Funds two NCEP staff and two collaborativeresearch grants 12

  13. HEFS Challenges • Science • HEFS is a tool; research continues on how best to use that tool • How to produce hydrologic ensemble forecasts based on meteorological ensembles • Extreme events (e.g. record flooding) are harder to monitor and forecast: • Record conditions are outside model limits without historical analogs • Products must be understandable / actionable • Forecast cone must be small enough for effective decision support • Better accuracy required from both met and hydro models • Implementation • Prototype software is not baseline software • OHD staff to implement HEFS is focused on CHPS into 2011 • Delivery with CHPS will be prototype code integrated into FEWS • RFCs will need to calibrate HEFS • We need to train forecasters • Web farms will need to handle more complex data requests • RFCs will require additional computer resources to operate in an ensemble mode

  14. Issues and Risks

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