SAR and ASCAT Tropical Cyclone Wind Speed Reconciliation

Weicheng Ni ,Ad Stoffelen, Kaijun Ren, Xiaofeng Yang, Jur Vogelzang

Wind speed reconciliation across different wind sources is critically needed for extending available satellite wind records in Tropical Cyclones. The deviations between wind references of extremes, such as the moored buoy data and dropsonde wind estimates for guidance on geophysical model function development, are one of the main causes of wind speed differences for wind products, for instance, the overestimation of Synthetic Aperture Radars (SARs) relative to ASCAT winds. The study proposes a new wind speed adjustment to achieve mutual adjustment between ASCAT CMOD7 winds and simultaneous SAR wind speeds. The so-called CMOD7D-v2 adjustment is constructed based on the statistical analysis of SAR and ASCAT Tropical Cyclone acquisitions between 2016 and 2021, showing a satisfactory performance in wind speed reconciliation for winds with speeds higher than 14 m/s. Furthermore, the error characteristics of the CMOD7D-v2 adjustment for Tropical Cyclone winds are analyzed using the Triple Collocation analysis technique. The analysis results show that the proposed wind adjustment can reduce ASCAT wind errors by around 16.0% when adjusting ASCAT winds to SAR wind speeds. In particular, when downscaling SAR winds, the improvement in ASCAT wind errors can be up to 42.3%, effectively alleviating wind speed differences across wind sources. Furthermore, to avoid the impacts of large footprints by ASCAT sensors, wind speeds retrieved from SAR VV signals (acting as a substitute for ASCAT winds) are adjusted accordingly and compared against SAR dual-polarized winds and collocated Stepped Frequency Microwave Radiometer (SFMR) observations. We find that the bias values of adjusted winds are lower than products from other adjustment schemes by around 5 m/s at the most extreme values. These promising results verify the plausibility of the CMOD7D-v2 adjustment, which is conducive to SAR and ASCAT wind speed comparisons and extreme wind analysis in Tropical Cyclone cases.

Bibliographic data

Weicheng Ni , Ad Stoffelen, Kaijun Ren, Xiaofeng Yang, Jur Vogelzang . SAR and ASCAT Tropical Cyclone Wind Speed Reconciliation
Journal: Remote Sensing, Volume: 14, Year: 2022, doi: