Journal article
An Efficient Ensemble Technique for Hydrologic Forecasting Driven by Quantitative Precipitation Forecasts
Journal of hydrometeorology, Vol.24(3), pp.479-495
03/01/2023
DOI: 10.1175/JHM-D-22-0109.1
Abstract
Uncertainty in quantitative precipitation forecasts (QPFs) from numerical weather prediction (NWP) mod- els manifests in errors in the amounts of rainfall, storm structure, storm location, and timing, among other precipitation characteristics. In flash flood forecasting applications, errors in the QPFs can translate into significant uncertainty in fore- casts of surface water flows and their impacts. In particular, the QPF errors in location and structure result in errors on flow paths, which can be highly detrimental in identifying locations susceptible to flash flood impacts. To account for this type of uncertainty, the neighboring pixel ensemble technique (NPET) was devised and implemented as a postprocessing algorithm of deterministic or ensemble outputs from a distributed hydrologic model. The aim of the technique is to address displaced hydrologic responses resulting from location biases in QPFs using a probabilistic approach. NPET identifies a sampling region surrounding each forecast pixel and builds an ensemble of surface water flow values considering the pixel's physiographic similarities. The probabilistic information produced with NPET can be calibrated through a set of tunable parameters that are adjusted to account for NWP-specific QPF error characteristics. The utility of NPET is demonstrated for the Ellicott City flash flood event on 27 May 2018, using products and tools routinely used in the U.S. National Weather Service for warning operations. Results from this case demonstrate that NPET effectively conveys uncertainty information about QPF precipitation location in a hydrologic context.SIGNIFICANCE STATEMENT: This study introduces a new method suitable for operational use called the neigh- boring pixel ensemble technique (NPET). NPET is an algorithm that generates ensemble-based streamflow forecasts accounting for the location uncertainties in quantitative precipitation forecasts (QPFs) without the requirement of multi- ple hydrologic model runs. NPET is capable of this feat through probabilistic assimilation of a priori QPF displacement information and its uncertainty. The application of NPET with the Flooded Locations and Simulated Hydrographs (FLASH) project shows the technique could be beneficial for flash flood warning operations in the U.S. National Weather Service (NWS). It is envisioned that the application of NPET with Warn-on-Forecast System (WoFS)-forced FLASH outputs will further enhance the quality of flash flood forecasts that support NWS warning operations.
Details
- Title: Subtitle
- An Efficient Ensemble Technique for Hydrologic Forecasting Driven by Quantitative Precipitation Forecasts
- Creators
- Humberto Vergara - Cooperative Institute for Mesoscale Meteorological StudiesJonathan J. Gourley - NOAA National Severe Storms LaboratoryMichael Erickson - Cooperative Institute for Research in Environmental Sciences
- Resource Type
- Journal article
- Publication Details
- Journal of hydrometeorology, Vol.24(3), pp.479-495
- DOI
- 10.1175/JHM-D-22-0109.1
- ISSN
- 1525-755X
- eISSN
- 1525-7541
- Publisher
- Amer Meteorological Soc
- Number of pages
- 17
- Grant note
- NA20OAR4590354 / NOAA/OAR-Joint Technology Transfer Initiative U.S. Department of Com-merce, National Oceanic and Atmospheric Administration; National Oceanic Atmospheric Admin (NOAA) - USA
- Language
- English
- Date published
- 03/01/2023
- Academic Unit
- Civil and Environmental Engineering
- Record Identifier
- 9984446064302771
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