The Hurricane Forecast Improvement Project
Top Cited Papers
- 1 March 2013
- journal article
- Published by American Meteorological Society in Bulletin of the American Meteorological Society
- Vol. 94 (3), 329-343
- https://doi.org/10.1175/bams-d-12-00071.1
Abstract
Over the decade prior to 2007, the increasing vulnerability of the United States to damage and economic disruption from tropical storms and hurricanes was dramatically demonstrated by the impacts of a number of land-falling storms. In 2008, the National Oceanic and Atmospheric Administration (NOAA) established the Hurricane Forecast Improvement Project (HFIP) to significantly increase the agency's capability to address this vulnerability and begin to mitigate the impacts. In fiscal year 2009, The White House amended the president's budget and Congress appropriated funding to achieve a 20% reduction in forecast error (track and intensity) in 5 years with 50% reduction in 10 years. Over the past 3 years, HFIP has built computational infrastructure and implemented a focused set of cross-organizational research and development (R&D) activities to develop, demonstrate, and implement enhanced operational modeling capabilities to improve the numerical forecast guidance made available to the National Hurricane Center (NHC). HFIP collaborators, including federal laboratories and academic partners, have demonstrated potential for dramatic improvements in both hurricane track and intensity (up to 40%) prediction through the application of new techniques, including improved data assimilation, higher-resolution models (global and regional), enhanced model physics, better use of existing data sources to initialize regional hurricane models, and new postprocessing techniques. During each hurricane season, HFIP will run an experimental forecast system on NOAA's R&D high-performance computing to provide experimental improved guidance to NHC forecasters. Prior to each season, NHC will review and select a set of enhanced guidance products to evaluate operationally during the season (mid-July–October).Keywords
This publication has 28 references indexed in Scilit:
- The HWRF Hurricane Ensemble Data Assimilation System (HEDAS) for High-Resolution Data: The Impact of Airborne Doppler Radar Observations in an OSSEMonthly Weather Review, 2012
- A Simplified Dynamical System for Tropical Cyclone Intensity PredictionMonthly Weather Review, 2009
- A Comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction SystemsMonthly Weather Review, 2005
- Mesoscale Weather Prediction with the RUC Hybrid Isentropic–Terrain-Following Coordinate ModelMonthly Weather Review, 2004
- NAVDAS: Formulation and DiagnosticsMonthly Weather Review, 2001
- Potential Forecast Skill of Ensemble Prediction and Spread and Skill Distributions of the ECMWF Ensemble Prediction SystemMonthly Weather Review, 1997
- A Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic BasinWeather and Forecasting, 1994
- Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statisticsJournal of Geophysical Research: Oceans, 1994
- Downstream Development of Baroclinic Waves As Inferred from Regression AnalysisJournal of the Atmospheric Sciences, 1993
- The Behavior of Forecast Error Covariances for a Kalman Filter in Two DimensionsMonthly Weather Review, 1991