Abstract's details

Assessing Tropical Cyclone Intensity Forecasts Using the NOAA Next-Generation Enterprise Ocean Heat Content Algorithm

Deirdre Byrne (NOAA/LSA, United States)


Paige Lavin (NOAA/LSA and University of Maryland CISESS/ESSIC, United States); David Trossman (NOAA/LSA and University of Maryland CISESS/ESSIC, United States); Lewis Gramer (NOAA/OAR/AOML/HRD and University of Miami CIMAS, United States)

Event: 2023 Ocean Surface Topography Science Team Meeting

Session: Application development for Operations (ROUND TABLE)

Presentation type: Type Poster

Contribution: PDF file


Tropical cyclones (TCs) can rapidly intensify over the ocean, resulting in much more catastrophic impacts once they make landfall. For example, in 2021 Hurricane Ida intensified rapidly over the Gulf of Mexico from a category 2 to a category 4 storm in less than 24 hours before arriving on land later the same day. Improvements in TC intensity forecasting, particularly for rapid intensification and weakening (RI/RW) events, have historically lagged improvements in TC track forecasting, although recent advances in NOAA forecast capability (e.g., NOAA HAFS) have begun to address this lag. We present here the latest improvements of the NOAA Next Generation Enterprise Ocean Heat Content (NGE OHC) algorithm, a product which may be useful in further improving TC intensity forecasting. The heat content of the upper ocean, traditionally defined as the amount of energy stored in the ocean at sea temperatures of 26°C and above, can have a strong influence on both RI and RW events. However, it is becoming clear that consideration of additional physical characteristics of the upper ocean is important to determine the extent to which TCs are able to rapidly intensify.

The NGE OHC, an empirical parameterization, generates depth-resolved ocean temperature and salinity profiles that will be used operationally to generate daily upper ocean heat content fields and support detailed analysis of coupled numerical hurricane models, particularly with regard to their potential for forecasting TC intensity change. The method leverages the widespread dominance of low mode baroclinic variability in the ocean to directly estimate profiles from altimetry, sea surface temperature, and ancillary parameters such as the Coriolis parameter. Real-time data used for estimating OHC include the NOAA/EUMETSAT Radar Altimeter Database System and the GOES-POES 5km Blended Sea Surface Temperature products, enabling us to produce the NGE OHC product daily at two resolutions: ~10 km along-track and ¼-degree daily gridded. Adding sea surface salinity (SSS) information from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellites can improve both the synthetic temperature and salinity profiles produced by the NGE OHC algorithm – the latter by as much as 25% relative to independent Argo observations.

In comparison with the current operational OHC product, the NGE OHC algorithm shows increased accuracy during extreme conditions, such as when substantial tropical cyclone heat potential is present in the Gulf of Mexico. We retrospectively compare the subsurface ocean conditions generated by the NGE OHC algorithm to output from the ocean-atmosphere coupled Hurricane Analysis and Forecast System (HAFS v1.0) and to in situ Argo float profiles for several case study TCs that underwent rapid intensity change during the 2020–2022 Atlantic hurricane seasons. In particular, we will highlight TCs where our improved OHC product may have enabled more skillful forecasts of the intensity of these storms.

Poster show times:

Room Start Date End Date
Esperanza Beach Room (Lobby) Wed, Nov 08 2023,16:15 Wed, Nov 08 2023,18:00
Esperanza Beach Room (Lobby) Thu, Nov 09 2023,14:00 Thu, Nov 09 2023,15:45
Deirdre Byrne
United States