The center location and the intensity of a Tropical cyclone (TC) are of common concern to both physical oceanographers and weather forecasters, since they are of great significance for improving the accuracy of TC forecast, and in turn reducing the destructiveness of TC events. Satellite scatterometers are able to obtain accurate stream line features in the presence of TCs, as widely used in TC monitoring, notably for TC center location estimation. However, the scatterometer-derived extreme winds are usually underestimated with respect to in-situ GPS dropsonde winds, due to rain contamination, signal saturation, and lack of proper extreme-wind base calibration, therefore limiting the application of its data in determining the TC intensity.
In this paper, the characteristics of scatterometer wind vectors, as well as their divergence and curl, are analyzed. Following the unique pattern of wind stress divergence and curl near the TC core, a new method is developed to determine the TC center location. That is, two positive local maxima and two negative local minima appear symmetrically near the TC core, due to surface convergence around a cyclone, which in turn, creating an area of high pressure aloft and causing air to diverge at upper levels. As such one can take the intersection of the two lines constructed separately by the local maxima and the local minima as the TC center. This technique is applied to the 32 HSCAT and 9 ASCAT acquisitions of TCs over the Western Pacific in 2019. The mean difference between the identified HSCAT/ASCAT TC center and the interpolated best-track positions is about one wind vector cell (~25 km). Moreover, closely collocated (in time) NOAA P-3 Stepped Frequency Microwave Radiometer (SFMR) wind data show a good correspondence between the SFMR minimum wind speed pattern inside the eyewall and the TC centre location as depicted by the new method.
Then the radial extent of 17-m/s winds (i.e., R17) is calculated from the scatterometer wind data. The feasibility of scatterometer wind radii in determining TC intensity is evaluated using the maximum sustained wind speed (MSW) in the China Meteorological Administration best-track database, with the objective of predicting the TC intensity using the scatterometer wind radii information. It proves that the estimated R17 value is better than the maximum wind speed of Ku-band scatterometer in terms of characterizing the TC intensity. However, the correlation between R17 and MSW is still relatively low (r = 0.54) to develop a universal TC intensity prediction model. Through case-by-case analysis, we find that the R17 value is highly correlated with the best-track MSW for each single TC event, implying that the scatterometer wind radii are useful in estimating TC intensity by limiting the concerned spatial region and temporal duration.
In summary, in terms of nowcasting or short-range forecasting purpose, the scatterometer R17 value is quite useful in assessing the evolution of TC intensity. With the joint observations from the current virtual scatterometer constellation, e.g., the HSCATs onboard HY-2 satellites, the ASCATs onboard Metop satellites, and the China-France Oceanography Satellite scatterometer, it may be feasible to monitor the TC evolution in near-real time.