HR: 0800h
AN: A21C-0650    [Abstracts]
TI: Improving Hurricane Heat Content Estimates From Satellite Altimeter Data
AU: de Matthaeis, P
EM: pdematth@neptune.gsfc.nasa.gov
AF: UMBC/GEST NASA Goddard Space Flight Center, Hydrospheric and Biospheric Sciences Laboratory, Instrumentation Sciences Branch / Code 614.6, Greenbelt, MD 20771, United States
AU: * Jacob, S
EM: jacob@umbc.edu
AF: UMBC/GEST NASA Goddard Space Flight Center, Hydrospheric and Biospheric Sciences Laboratory, Instrumentation Sciences Branch / Code 614.6, Greenbelt, MD 20771, United States
AU: Roubert, L M
EM: lroubert@neptune.gsfc.nasa.gov
AF: University of Puerto, Department of Mathematical Sciences, Mayagüez, PR 00981, Puerto Rico
AU: Shay, N
EM: nshay@rsmas.miami.edu
AF: University of Miami, RSMAS, 4600 Rickenbacker CSWY, Miami, FL 33149, United States
AU: Black, P
EM: peter.black@noaa.gov
AF: AOML, NOAA, 4301 Rickenbacker CSWY, Miami, FL 33149, United States
AB: Hurricanes are amongst the most destructive natural disasters known to mankind. The primary energy source driving these storms is the latent heat release due to the condensation of water vapor, which ultimately comes from the ocean. While the Sea Surface Temperature (SST) has a direct correlation with wind speeds, the oceanic heat content is dependent on the upper ocean vertical structure. Understanding the impact of these factors in the mutual interaction of hurricane-ocean is critical to more accurately forecasting intensity change in land-falling hurricanes. Use of hurricane heat content derived from the satellite radar altimeter measurements of sea surface height has been shown to improve intensity prediction. The general approach of estimating ocean heat content uses a two-layer model representing the ocean with its anomalies derived from altimeter data. Although these estimates compare reasonably well with in-situ measurements, they are generally about 10% under-biased. Additionally, recent studies show that the comparisons are less than satisfactory in the Western North Pacific. Therefore, our objective is to develop a methodology to more accurately represent the upper ocean structure using in-situ data. As part of a NOAA/ USWRP sponsored research, upper ocean observations were acquired in the Gulf of Mexico during the summers of 1999 and 2000. Overall, 260 expendable profilers (XCTD, XBT and XCP) acquired vertical temperature structure in the high heat content regions corresponding to the Loop Current and Warm Core Eddies. Using the temperature and salinity data from the XCTDs, first the Temperature-Salinity relationships in the Loop Current Water and Gulf Common water are derived based on the depth of the 26° C isotherm. These derived T-S relationships compare well with those inferred from climatology. By means of these relationships, estimated salinity values corresponding to the XBT and XCP temperature measurements are calculated, and used to derive continuous profiles of density. Ocean heat content is then estimated from these profiles, and compared to that derived from altimeter data, showing - as mentioned earlier - a consistent bias. Using a procedure that conserves density in the vertical, these density profiles are discretized into five isopycnic layers representative of the upper ocean in the Gulf of Mexico. Statistical correlations are then derived between the altimetric sea surface height anomalies and the thickness of these layers in the region. Using these correlations, a higher resolution upper ocean structure is derived from the altimeter data. Withholding observations from one snapshot of data in the correlations, and comparing the estimated ocean heat content with in-situ values, will allow us to quantify errors in this approach. This methodology will then be extended to the Western Pacific using Argo data, and results will be presented.
DE: 3339 Ocean/atmosphere interactions (0312, 4504)
DE: 3374 Tropical meteorology
DE: 4275 Remote sensing and electromagnetic processes (0689, 2487, 3285, 4455, 6934)
DE: 4504 Air/sea interactions (0312, 3339)
DE: 4572 Upper ocean and mixed layer processes
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting