# Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones
## 1 Introduction
As a result, over the course of a few years, multiple Level 1 (DDM and NBRCS) and L2 wind datasets were released by the CYGNSS science team, either to provide incremental improvements to the CYGNSS wind retrievals or to introduce novel empirical approaches to correct for the observed calibration and algorithm deficiencies. The original CYGNSS science team developed L2 and L3 wind datasets which include two different wind products, processed at the Science Operation Center (SOC) at the University of Michigan, Ann Arbor: one for low-to-moderate wind speeds, qualified for \"fully developed sea\" (FDS); and another for \"young sea, limited fetch\" (YSLF), more suitable for high winds (above \(\sim\)20 m/s). These products are characterized as science data products (SDR) and are released to the public with a moderate latency below 6 days [16], recently approaching less than 24 h. The most recent SDRs (V2.1 and V3.0) are available to the public on NASA's Physical Oceanography Distributed Archive Center (PO.DAAC) website ([[https://podaac.jpl.nasa.gov/CYGNSS?sections=data](https://podaac.jpl.nasa.gov/CYGNSS?sections=data)]([https://podaac.jpl.nasa.gov/CYGNSS?sections=data](https://podaac.jpl.nasa.gov/CYGNSS?sections=data)), (accessed on 17 September 2021). To correct for GPS and intersatellite calibration biases, the NOAA team developed, and is currently processing, a single wind product that is suitable at all wind regimes [13]. This product uses significant wave height (SWH) as an additional input parameter in the geophysical model. The NOAA CYGNSS wind speeds include improved L1 calibration and a track-wise bias removal algorithm based on surface winds from the European Center for Medium-range Weather Forecast (ECMWF), and have a moderate latency of about 6 days. This L2 wind data product was first shared only to science team members as V1.0 and, in September 2020, was released to the public on the PO.DAAC website as V1.1 after improvements to the quality control. Motivated by the good preliminary results of the NOAA winds, a similar track-wise correction method was then adopted by the CYGNSS science team to develop a better-quality climate data record (CDR) wind product. The CDR uses the MERRA reanalysis winds for the bias correction, which limits the latency of the CDR product to about 1-2 months. Our work focuses on validating all CYGNSS wind products that are currently available to the public in order to document the differences among them, illustrate advantages and shortcomings of each data product, and guide users in the optimal choice for their application/investigation. Most of these datasets have been independently validated by the team of investigators who developed them [13; 16; 17; 18; 19], with analyses at the global scale, in collective statistics, at regional scales, and for sample tracks in storms. The main objective of this paper is to focus on wind observations within tropical cyclones. We believe that it is the most innovative and sought-after aspect of the planned mission, due to the potential high impact on society, and the one most in need of improvements. Before the CYGNSS wind fields can be used with confidence by investigators interested in tropical storm processes, it is important to provide them with a quantitative and comparative estimate of the quality of the different wind products. Our assessment is based on a suite of radiometer wind datasets specifically developed with remote sensing systems (RSS) to retrieve winds in TCs and processed in near real-time (NRT): the TC-winds from SMAP, AMSR2, and WindSat. These data products have been extensively validated in all storm wind regimes (10-60 m/s), and in rainy environments [20; 21; 22; 23]. The CYGNSS mission was designed around its \"ability to monitor and predict the rapid changes in hurricane intensity\". The constellation of eight satellites orbiting the tropical belt offers an average revisit time of nine hours, critical for monitoring tropical cyclone evolution [16].