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G. R. Halliwell Jr., L. K. Shay, S. D. Jacob, O. M. Smedstad, and E. W. Uhlhorn

Abstract

To simulate tropical cyclone (TC) intensification, coupled ocean–atmosphere prediction models must realistically reproduce the magnitude and pattern of storm-forced sea surface temperature (SST) cooling. The potential for the ocean to support intensification depends on the thermal energy available to the storm, which in turn depends on both the temperature and thickness of the upper-ocean warm layer. The ocean heat content (OHC) is used as an index of this potential. Large differences in available thermal energy associated with energetic boundary currents and ocean eddies require their accurate initialization in ocean models. Two generations of the experimental U.S. Navy ocean nowcast–forecast system based on the Hybrid Coordinate Ocean Model (HYCOM) are evaluated for this purpose in the NW Caribbean Sea and Gulf of Mexico prior to Hurricanes Isidore and Lili (2002), Ivan (2004), and Katrina (2005). Evaluations are conducted by comparison to in situ measurements, the navy’s three-dimensional Modular Ocean Data Assimilation System (MODAS) temperature and salinity analyses, microwave satellite SST, and fields of OHC and 26°C isotherm depth derived from satellite altimetry. Both nowcast–forecast systems represent the position of important oceanographic features with reasonable accuracy. Initial fields provided by the first-generation product had a large upper-ocean cold bias because the nowcast was initialized from a biased older-model run. SST response in a free-running Isidore simulation is improved by using initial and boundary fields with reduced cold bias generated from a HYCOM nowcast that relaxed model fields to MODAS analyses. A new climatological initialization procedure used for the second-generation nowcast system tended to reduce the cold bias, but the nowcast still could not adequately reproduce anomalously warm conditions present before all storms within the first few months following nowcast initialization. The initial cold biases in both nowcast products tended to decrease with time. A realistic free-running HYCOM simulation of the ocean response to Ivan illustrates the critical importance of correctly initializing both warm-core rings and cold-core eddies to correctly simulate the magnitude and pattern of SST cooling.

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A. F. Hasler, K. Palaniappan, C. Kambhammetu, P. Black, E. Uhlhorn, and D. Chesters

Mesoscale wind fields have been determined for a mature hurricane with high spatial and temporal resolution, continuity, and coherency. These wind fields, near the tropopause in the inner core and at low levels inside the eye, allow the evolution of mesoscale storm features to be observed. Previously, satellite-derived winds near hurricanes have been determined only at some distance from the eye over a typical time period of 1–2 h. Hurricane reconnaissance aircraft take 30 min to 1 h to complete an inner-core pattern. With the long observation periods of these previous methods, steady-state conditions must be assumed to give a complete description of the observed region.

With the advent of 1-min interval imagery, and fourfold improvement of image dynamic range from NOAA's current generation of GOES satellites, there is a new capability to measure inner-core tropical cyclone wind fields near the tropopause and within the eye, enabling mesoscale dynamical processes to be inferred. These measurements give insights into the general magnitude and structure of the hurricane vortex, along with very detailed measurements of the cloud-top wind's variations in response to convective outbursts. This paper describes the new techniques used to take advantage of the GOES satellite improvements that, in turn, allowed the above innovations to occur.

The source of data for this study is a nearly continuous 12-h sequence of 1-min visible images from NOAA GOES-9 on 6 September 1995. These images are centered on Hurricane Luis with maximum winds of 120 kt (CAT4) when it was 250 km northeast of Puerto Rico. A uniform distribution of long-lived cirrus debris with detailed structure is observed in the central dense overcast (CDO), which has been tracked using the 1-min images. The derived wind field near the tropopause at approximately 15 km in the CDO region has a strong closed circulation with speeds up to 25 m s−1, which pulses in response to the convective outbursts in the eye wall. Cloud displacements are computed at every pixel in every image, resulting in a quarter-million uv winds in each of 488 hurricane images observed at 1- to 4-min intervals over 12 h. For analysis and presentation, these ultradense wind fields are reduced to 8- or 16-km grids using a 7-min time base by smoothing displacement vectors in space and time.

Cloud structures were tracked automatically on a massively parallel processing computer, but with manual spot-checking. Manual tracking has been used to follow CDO structure over long time periods, up to 90 min for a small test sample. Cloud tracking for the wind fields presented here is accomplished using a Massively Parallel Semi-Fluid Motion Analysis (MPSMA) automatic technique. This robust deformable surface-matching algorithm has been implemented on the massively parallel Maspar supercomputer. MPSMA automatic tracking typically follows a feature for 7 min. For this time base the error of these winds is estimated to be 1.5 m s−1. However, systematic navigation and height assignment errors in the moderately sheared hurricane environment must still be considered. Spatial and temporal smoothing of the wind field have been performed to reduce systematic navigation errors and small-scale turbulent noise. The synthesis used here to compute the wind fields gives an order of magnitude reduction in the amount of data presented compared to the amount of data processed. Longer tracking could give higher accuracy but would smooth out the smaller-scale spatial and temporal features that appear dynamically significant.

The authors believe that the techniques described in this paper have great potential for further research on tropical cyclones and severe weather as well as in operational use for nowcasting and forecasting. United States and foreign policymakers are urged to augment the GOES, GMS, FY2, and Meteosat geostationary satellite systems with dual imaging systems such that 1-min observations are routinely taken.

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L. Bernardet, V. Tallapragada, S. Bao, S. Trahan, Y. Kwon, Q. Liu, M. Tong, M. Biswas, T. Brown, D. Stark, L. Carson, R. Yablonsky, E. Uhlhorn, S. Gopalakrishnan, X. Zhang, T. Marchok, B. Kuo, and R. Gall

Abstract

The Hurricane Weather Research and Forecasting Model (HWRF) is an operational model used to provide numerical guidance in support of tropical cyclone forecasting at the National Hurricane Center. HWRF is a complex multicomponent system, consisting of the Weather Research and Forecasting (WRF) atmospheric model coupled to the Princeton Ocean Model for Tropical Cyclones (POM-TC), a sophisticated initialization package including a data assimilation system and a set of postprocessing and vortex tracking tools. HWRF’s development is centralized at the Environmental Modeling Center of NOAA’s National Weather Service, but it incorporates contributions from a variety of scientists spread out over several governmental laboratories and academic institutions. This distributed development scenario poses significant challenges: a large number of scientists need to learn how to use the model, operational and research codes need to stay synchronized to avoid divergence, and promising new capabilities need to be tested for operational consideration. This article describes how the Developmental Testbed Center has engaged in the HWRF developmental cycle in the last three years and the services it provides to the community in using and developing HWRF.

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