Puerto Rico/U.S. Virgin Islands Storm Surge & Waves

Project Team

Project Lead: Andre van der Westhuysen, NOAA NCEP

CO-PIs: Joannes Westerink, University of Notre Dame

Collaborators: Juan Gonzalez (CariCOOS/Wood Group PLC), Julio Morell (CariCOOS), Aurelio Mercado (UPRM), Reniel Calzada (UPRM/NOAA CSL), Volker Roeber (University of Hawaii), Dongming Yang (NOAA NCEP), Hugh Cobb (NOAA NCEP NHC), Carlos Anselmi (NOAA NWS San Juan Forecast Office), Ernesto Rodriguez (NOAA NWS San Juan Forecast Office) , Luis Aponte (UPRM)

Federal Partners: Jamie Rhome (NOAA NVEP NHC), Jane Smith (USACE ERDC)

Project Overview and Results

The goal of this COMT project is to extend the present wave/surge operational forecasting capability from mild-sloped coastal areas such as the US East and Gulf of Mexico coasts to steep-sloped areas such as around Caribbean and Pacific islands and transition this capability to NOAA’s National Hurricane Center and local WFOs. Broad project objectives are to: (1) compile a data set of observations collected around Puerto Rico and the USVI by the IOOS Caribbean Regional Association; (2) evaluate multiple, coupled wave/surge/inundation models against this data; (3) recommend the most suitable model for transition to operations and (4) assist with the transition. These outcomes will also be applicable to U.S. island regions in the Pacific and may therefore guide future implementations at NOAA’s Central Pacific Hurricane Center.

U.S. island regions in the Caribbean and Pacific pose many challenges to the accurate modeling and prediction of hazardous wave-dominated storm surge inundation events. The relative importance of physical processes leading to inundation in steep-sloped, reef-edged island environments differs from those in milder-sloped mainland environments. Relatively little research has been done in these environments, constituting a significant knowledge gap. To compound this uncertainty, little observational data are available in many island environments. As a result, the U.S. National Weather Service (NWS) currently lacks operational surge and inundation guidance for these regions. An exception to this general data scarcity is Puerto Rico and the U.S. Virgin Islands (USVI), which frequently experience strong tropical and extra-tropical storms resulting in high waves, storm surge, and river flooding. A large number of observational instruments have been deployed here, many by IOOS Caribbean Regional Association partners, creating a valuable resource for the evaluation and advancement of operational wave/surge/inundation models of these areas.

Three teams – an operational assessment team (federal user group), a numerical modeling team and a data management team – will work together to understand the driving processes of sea level variability in deep ocean island geographies, understand the robustness and accuracy of a variety of wind products, and to discern the ability to forecast tides, storm events and intra-annual variability.

Specifically in the wake of Hurricanes Irma and Maria in September of 2017, detailed hindcasts were performed of these storm events using a high fidelity research grade ADCIRC+SWAN model of the Caribbean and Puerto Rico / U.S. Virgin Islands (PR/USVI), NOAA’s ADCIRC-driven HSOFS operational mesh, and NOAA NHC’s SLOSH using the latest PR/USVI grid. Furthermore, the impact of baroclinic processes on intra-annual and storm driven sea level variability is evaluated. The results from these studies are described in a sequence of two Journal of Geophysical Research papers (REF here; in review).

In addition, two sets of ancillary simulation sets were also developed as a result of the work and developments made in this project. The first are detailed analyses and hindcasts of Hurricanes Georges (1998) and Irene (2011). Unfortunately, the lack of highly reliable hindcast winds and/or water level data for these storms did not make for sufficiently reliable hindcasts to draw conclusions about the storm physics and/or model inter-comparisons. In addition, a statistical response probability set was developed with the SLOSH PR/USVI model.

Model Descriptions

ADCIRC

SLOSH

Sub-Project Descriptions/Data

Published Results