Abstract
The movement of convective rainbands embedded in a tropical cyclone (TC) is usually derived from satellite images via the atmospheric motion vector (AMV) method or through the calculation of a radar’s echo track. In estimating the rotation speed of a TC rainband, however, the land-based radar can only detect approaching tropical cyclones within the vicinity. The AMV method is unable to fully account for the TC eyewall movement, thus making it difficult to estimate the TC intensity. The widely used method in estimating the TC maximum wind speed is the Dvorak technique in which the cloud pattern is extracted from only one image. In this study, the rainband rotation speeds are computed via satellite imagery and further applied in estimating the TC maximum wind speed. In contrast to previous research, this study adopts an innovative method by using two subsequent geostationary satellite images. The TC spin rates observed by weather satellites could often be seen to be positively related to the TC intensity. Analyses of the relationship between the typhoon wind intensity and estimated rotation speed at the 130–260-km ring via infrared channels are conducted for major typhoon cases that occurred during 2000–05 in the northwestern Pacific Ocean. Results show that the correlation between the wind intensity and estimated rotation speeds is strong for most of the cases. The highest R2 value from the individual cases could reach 0.93, and on an annual basis it could attain a value of 0.67. The mean R2 value for the 2000–05 dataset was roughly 0.53. The correlation between the wind intensity and estimated rotation speeds is further improved by factoring in the previous 6-h average rotation speeds. A regression equation is derived from the chosen typhoon cases between 2000 and 2005, which is utilized in verifying the major typhoon occurrences during 2006–08. The mean absolute error (MAE) of the hourly and 6-h average intensity estimates during 2000–08 was 20 and 18.7 kt, respectively (1 kt ≃ 0.5 m s−1). The best verification result occurred during 2008, for which the R2 value and MAE could reach 0.7 and 15.6, respectively. These research results demonstrate the suitability of using geostationary satellite image data in estimating the maximum wind speed. Nevertheless, the drawback of this study is that sometimes the rotation speeds will become slower when tropical cyclones mature because of the strong outflow of the secondary circulation. It is assumed that the relationship between the estimated rotation speeds and wind intensity can be further improved if the outflow speed of the tropical cyclones is also considered.
Multi-Factor Intensity Estimation for Tropical Cyclones in the Western North Pacific Based on the Deviation Angle Variance Technique
