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  • 1
    Publication Date: 2014-02-01
    Description: This paper introduces a next-generation operational Hurricane Weather Research and Forecasting (HWRF) system that was developed at the U.S. National Centers for Environmental Prediction. The new system, HWRF–Hybrid Coordinate Ocean Model (HYCOM), retains the same atmospheric component of operational HWRF, but it replaces the feature-model-based Princeton Ocean Model (POM) with the eddy-resolving HYCOM. The primary motivation is to improve enthalpy fluxes in the air–sea interface, by providing the best possible estimates of the balanced oceanic states using data assimilated Real-Time Ocean Forecast System products as oceanic initial conditions (IC) and boundary conditions. A proof-of-concept exercise of HWRF–HYCOM is conducted by validating ocean simulations, followed by the verification of hurricane forecasts. The ocean validation employs airborne expendable bathythermograph sampled during Hurricane Gustav (2008). Storm-driven sea surface temperature changes agree within 0.1° and 0.5°C of the mean and root-mean-square difference, respectively. In-storm deepening mixed layer and shoaling 26°C isotherm depth are similar to observations, but they are overpredicted at similar magnitudes of their ICs. The forecast verification for 10 Atlantic hurricanes in 2008 and 2009 shows that HWRF–HYCOM improves intensity by 13.8% and reduces positive bias by 43.9% over HWRF–POM. The HWRF–HYCOM track forecast is indifferent, except for days 4 and 5, when it shows better skill (8%) than HWRF–POM. While this study proves the concept and results in a better skillful hurricane forecast, one well-defined conclusion is to improve the estimates of IC, particularly the oceanic upper layer.
    Print ISSN: 0739-0572
    Electronic ISSN: 1520-0426
    Topics: Geography , Geosciences , Physics
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  • 2
    Publication Date: 2015-09-01
    Description: A 2-yr-long daily gridded field of sea surface temperature (SST) in the Atlantic centered for the year 2013 is projected onto orthogonal components: its mean, six harmonics of the year cycle, the slow-varying contribution, and the fast-varying contribution. The periodic function defined by the year harmonics, referred to here as the seasonal harmonic, contains most of the year variability in 2013. The seasonal harmonic is examined in its spatial and temporal distribution by describing the amplitude and phase of its maxima and minima, and other associated parameters. In the seasonal harmonic, the ratio of the duration of warming period to cooling period ranges from 0.2 to 2.0. There are also differences in the spatial patterns and dominance of the year harmonics—in general associated with regions with different insolation, oceanic, and atmospheric regimes. Empirical orthogonal functions (EOFs) of the seasonal harmonic allow for a succinct description of the seasonal evolution for the Atlantic and its subdomains. The decomposition can be applied to model output, allowing for a more incisive model validation and data assimilation. The decorrelation time scale of the rapidly varying signal is found to be nearly independent of the time of the year once four or more harmonics are used. The decomposition algorithm, here implemented for a single year cycle, can be applied to obtain a multiyear average of the seasonal harmonic.
    Print ISSN: 0739-0572
    Electronic ISSN: 1520-0426
    Topics: Geography , Geosciences , Physics
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