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Eric A. Hendricks, Melinda S. Peng, Xuyang Ge, and Tim Li

Abstract

A dynamic initialization scheme for tropical cyclone structure and intensity in numerical prediction systems is described and tested. The procedure involves the removal of the analyzed vortex and, then, insertion of a new vortex that is dynamically initialized to the observed surface pressure into the numerical model initial conditions. This new vortex has the potential to be more balanced, and to have a more realistic boundary layer structure than by adding synthetic data in the data assimilation procedure to initialize the tropical cyclone in a model. The dynamic initialization scheme was tested on multiple tropical cyclones during 2008 and 2009 in the North Atlantic and western North Pacific Ocean basins using the Naval Research Laboratory’s tropical cyclone version of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS-TC). The use of this initialization procedure yielded significant improvements in intensity forecasts, with no degradation in track performance. Mean absolute errors in the maximum sustained surface wind were reduced by approximately 5 kt for all lead times up to 72 h.

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Shengjun Zhang, Tim Li, Xuyang Ge, Melinda Peng, and Ning Pan

Abstract

A combined tropical cyclone dynamic initialization–three-dimensional variational data assimilation scheme (TCDI–3DVAR) is proposed. The specific procedure for the new initialization scheme is described as follows. First, a first-guess vortex field derived from a global analysis will be spun up in a full-physics mesoscale regional model in a quiescent environment. During the spinup period, the weak vortex is forced toward the observed central minimum sea level pressure (MSLP). The so-generated balanced TC vortex with realistic MSLP and a warm core is then merged into the environmental field and used in the subsequent 3DVAR data assimilation. The observation system simulation experiments (OSSEs) demonstrate that this new TC initialization scheme leads to much improved initial MSLP, warm core, and asymmetric temperature patterns compared to those from the conventional 3DVAR scheme. Forecasts of TC intensity with the new initialization scheme are made, and the results show that the new scheme is able to predict the “observed” TC intensity change, compared to runs with the conventional 3DVAR scheme or the TCDI-only scheme. Sensitivity experiments further show that the intensity forecasts with knowledge of the initial MSLP and wind fields appear more skillful than do the cases where the initial MSLP, temperature, and humidity fields are known. The numerical experiments above demonstrate the potential usefulness of the proposed new initialization scheme in operational applications. A preliminary test of this scheme with a navy operational model shows encouraging results.

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Ge Peng, Huai-Min Zhang, Helmut P. Frank, Jean-Raymond Bidlot, Masakazu Higaki, Scott Stevens, and William R. Hankins

Abstract

To facilitate evaluation and monitoring of numerical weather prediction model forecasts and satellite-based products against high-quality in situ observations, a data repository for collocated model forecasts, a satellite product, and in situ observations has been created under the support of various World Climate Research Program (WCRP) working groups. Daily measurements from 11 OceanSITES buoys are used as the reference dataset to evaluate five ocean surface wind products (three short-range forecasts, one reanalysis, and one satellite based) over a 1-yr intensive analysis period, using the WCRP community weather prediction model evaluation metrics. All five wind products correlate well with the buoy winds with correlations above 0.76 for all 11 buoy stations except the meridional wind at four stations, where the satellite and model performances are weakest in estimating the meridional wind (or wind direction). The reanalysis has higher cross-correlation coefficients (above 0.83) and smaller root-mean-square (RMS) errors than others. The satellite wind shows larger variability than that observed by buoys; contrarily, the models underestimate the variability. For the zonal and meridional winds, although the magnitude of biases averaged over all the stations are mostly <0.12 m s−1 for each product, the magnitude of biases at individual stations can be >1.2 m s−1, confirming the need for regional/site analysis when characterizing any wind product. On wind direction, systematic negative (positive) biases are found in the central (east central) Pacific Ocean. Wind speed and direction errors could induce erroneous ocean currents and states from ocean models driven by these products. The deficiencies revealed here are useful for product and model improvement.

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