RAMMB Contributions to the Hurricane Forecast Improvement Project (HFIP)
HFIP is a 10 year NOAA project to improve tropical cyclone track and intensity forecasts through development of advanced hurricane models, data assimilation systems and through the optimal use of observations, especially in the storm inner core, HFIP is divided into several science teams, and RAMMB/CIRA is contributing to the diagnostics, verification, ensemble and modeling teams. RAMMB/CIRA is also contributing to the business case development for HFIP. RAMMB co-hosted the HFIP diagnostics workshop, and details can be found at.
- (2009, May) First Hurricane Diagnostics and Verification Workshop, Miami, FL
- (2010, April) Ensemble Products Workshop, Boulder, CO
- (2010, November) HFIP Annual Review, Miami, FL
- (2010, November) Stream 1 Regional Hurricane Model Diagnostics Planning Meeting, Miami, FL
- (2012, August) HFIP Diagnostics Workshop Virtual from Camp Springs, MD
As part of the HFIP program, experimental tropical cyclone forecast models are being run in real time with a number of configurations. The demo includes global and regional models, including ensemble forecasting systems. Various data assimilation techniques are also being used. The global demo models include the NOAA/ESRL FIM, the NCEP GFS, and the Navy NOGAPS. The regional demo models include NOAA/HRD HWRFx, special configurations of the NCEP operational HWRF and GFDL, the NCAR ARW, the Navy COAMPS, the Penn State HWRF and Florida State versions of the ARW and MM5. As part of the CIRA HFIP project, experimental probability products that use the output from multiple model simulations are under development. Below is a links page to some of the demo model web page.
Many of the RAMMB/CIRA tasks are coordinated through the Applications Development and Diagnostics (ADD) Team. Summaries of the bi-weekly ADD and Ensemble Design Group conference calls and meetings are available from the CIRA ADD Team Information Page.
Additional information on the HFIP teams is available from: HFIP Science Teams