Tropical cyclone wind speed estimation from satellite altimeter-derived ocean parameters

This study investigates the satellite altimeter-derived ocean parameters from Joint Altimetry Satellite Oceanography Network (Jason)-2 and Jason-3 response to the coincident wind speed at 10 m from sea surface (U10) from Meteorological Operational (MetOp)-A and MetOp-B satellite scatterometers inside the tropical cyclone environment. The high wind speed regime and rainy condition inside the tropical cyclone have reduced the U10 accuracy and thus, would benefit from more ocean related parameters to be considered. The altimeter Ku-band backscatter and significant wave height are commonly used to estimate extreme U10 but still show significant error in rainy tropical cyclone. New U10 models incorporating several Jasons derived ocean parameters (including brightness temperatures and water content) were designed by the multiple linear regression and artificial neural network techniques. Parameter analysis indicated that the C-band backscatter outperforms the Ku-band counterpart in relation to U10 inside the tropical cyclone. The proposed models show U10 estimation up to 35 ms−1 with 1 ms−1 accuracy and major improvement inside the tropical cyclone rain and at the high wind speed regime. This too shows the ability of satellite altimeter in estimating U10 in extreme environment with great accuracy. Plain Language Summary Wind speed is one of the vital variables to describe tropical cyclone intensity and strength. However, the tropical cyclone exhibits complex ocean surface conditions and thus, actual wind speed observed by buoy becomes unreliable. Although satellite altimeter can measure the wind speed to complement the buoy limitation, the existing algorithm was designed for normal and calm sea surface state. Considering only the backscatter and the surface wave height from altimeter as principle parameters in the algorithm is insufficient to emulate the complex interaction between ocean and atmosphere that exists inside the tropical cyclone. Therefore, this study explores the potential of other simultaneously observed parameters – brightness temperatures and water content in the atmosphere – and the importance of incorporating them in the estimation algorithm to produce more accurate tropical cyclone wind speed. Present study investigates available Joint Altimetry Satellite Oceanography Network (Jason)-2 and Jason-3 altimeters moving across 349 tropical cyclones between 2015 and 2018. The novel estimation algorithm provides promising accuracy especially in the tropical cyclone with intense rain and higher wind speed regime. This study proves that the satellite altimeter can measure the wind speed up to 35 ms−1 (≈68 kt) in the tropical cyclone condition at the measurement accuracy around 1 ms−1