Prediction methods for tropical cyclone induced wind field by using mesoscale model and JMA best track of tropical cyclones are proposed. A tropical cyclone database is produced by using JMA best track and NCEP/NCAR Reanalysis Project (NNRP) data. It is found that the identification success ratio of tropical cyclone parameters in present database, which is produced by JMA best track and NNRP data, is higher than previous one, which was produced by surface pressures measurement at weather stations. Predicted wind speeds obtained from present database and previous one show good agreement with measurement. A combined wind field model is proposed to predict tropical cyclone induced wind fields, in which mesoscale model and typhoon model are used. Underestimations of wind speeds caused by mesoscale model at the tropical cyclone center, and those by typhoon model at the outside region are improved by proposed model.
This paper investigates the validity of the method used in the Japanese offshore wind map (NeoWins) to seamlessly connecting satellite-derived wind speed for open oceans to mesoscale model-simulated wind speed for coastal waters. In the Neo-Wins, the former was obtained from the satellite-borne Advanced Scatterometer (ASCAT), and the latter was obtained from numerical simulations using the Weather Research and Forecasting (WRF) model. In this study, the consistency of the ASCAT and WRF 10-m height wind speeds is examined in their overwrapping areas. The comparison between ASCAT and WRF model reveals that their differences in annual mean wind speed are mostly within ±5% and that the ASCAT annual mean wind speed is, as a whole, slightly higher than the WRF annual mean wind speed. The results indicate that there are no large wind speed gaps between WRF and ASCAT in most parts of the Japanese offshore areas. It is moreover found that the discrepancies between the two wind speeds are due to two factors: one is the existence of winter sea ice in the ASCAT observation in the Sea of Okhotsk in ASCAT observation and the other is that the accuracy of the WRF wind speed depends on atmospheric stability. K E Y W O R D SASCAT, NeoWins, offshore wind, WRF | INTRODUCTIONOffshore wind resource maps have been developed worldwide using various methods, including satellite observations, numerical simulations, and the interpolation/extrapolation of in situ observations. A recent offshore wind resource map for Japan developed by the New Energy and Industrial Technology Development Organization (NEDO), called "offshore wind information system" (NeoWins), 1 employed both a satellite-borne microwave scatterometer and a mesoscale model-simulated wind speeds with spatial resolutions of approximately 10 km and 500 m, respectively; the two types of wind field were connected horizontally at around 30 km from the coastline.Data from satellite-borne microwave scatterometers can be used to construct reliable offshore wind resource maps, especially for open oceans. For example, wind fields obtained from the Advanced Scatterometer (ASCAT) 2 -a microwave scatterometer carried onboard to European Space Agency's MetOp satellites-have been used to develop an offshore wind atlas project. 3 A microwave scatterometer measures backscattering strengths from the earth's surface. An empirical relationship has been derived between the backscattering strength and the wind speed and
Typhoon Jebi (T1821) derived significant damages around Kansai area in Japan and recorded the highest fire insurance payment. Therefore, the accurate estimation of wind field for Jebi is quite important for the future ratemaking. In this study, several models, which are an engineering typhoon model, a meteorological model and combined/maximum of those models were used for the estimation and validated by using measurements at weather stations and compared with fire insurance payment database. Wind speeds obtained from the engineering typhoon model show better agreement with measurements at weather stations than the meteorological model. On the other hand, the wind speed distribution from the meteorological model shows best agreement with damage occurrences in the insurance payment database, and the wind speeds are higher than the engineering model in those area. It is also found that the relation between estimated wind speeds and damage occurrences are slightly improved by considering seismic intensity of the 2018 Osaka earthquake as regression parameters.
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