# Validating CYGNSS Wind Speeds with Surface-Based Observations and Triple Collocation Analysis
## 2 Materials and Methods  
### Study Domains and Datasets  
Three CYGNSS wind speed products are validated: level 2 Fully Developed Seas (FDS) v3.2 [18], level 3 Merged product v3.2 [30], and the level 2 product produced by NOAA v1.2 [20]. FDS is optimised for wind speeds < 15 m/s, where winds interact with the ocean over long distances [31]. The Merged product is designed for TC applications only. It uses FDS for all ocean measurements except for the vicinity of a registered TC, where it transitions to a different storm-centred grid product [30]. The NOAA product requires additional ancillary datasets and stricter quality controlling thresholds, which result in a more accurate product at the cost of less spatial coverage and longer latency (7 days, instead of 3 for FDS). Merged currently has a latency of several months as it depends upon best-track records produced by the National Hurricane Centre and Joint Typhoon Warning Centre. While there is a recently released near-real time product that uses preliminary best-track data, this has only been produced for TCs in 2024. The climate data record product of CYGNSS is not considered in this paper, as it has similar quality control processes as in NOAA and is generally found to perform in between FDS and NOAA products [19; 32]. Due to the sparsity between surface-based observations and the rarity of TC events, there are two levels to this analysis. Firstly, there is a coastal anemometer surface-based analysis for all wind conditions, and secondly, a gridded TCA focussed on TC events. The surface-based analysis validates CYGNSS against anemometer data from Australia and the Pacific region. Hourly anemometer data from 1 January 2020 to 31 December 2023 was provided by the Australian Bureau of Meteorology, with different datasets for the Australia and Pacific domains [33]. The Australian hourly dataset contains average speeds from the 10 min before the hour, whereas the Pacific dataset contains a maximum of 1 min sustained gust for the hour. As a result of this difference, the results for the two datasets are presented separately. There are 5 stations in the Pacific, and 17 around Australia, for a total of 22 stations. Many of the Australian sensors are strategically located away from landmasses to provide ocean-data capture, with three of them located on small coral reefs. Conversely, the gauges in the Pacific dataset are located near docks that provide complimentary data to tide gauges [33]. TCA validated CYGNSS against JPL Soil Moisture Active Passive (SMAP) [34] and NOAA STAR Synthetic Aperture Radar (SAR) [35], two leading publicly available satellite-based estimates for TC winds. Satellite-products alone were used to increase similarity between the datasets. FDS is not included in the TCA as it is not designed for TC conditions. SMAP is selected as it also operates at L-band frequency (1.41 GHz), which is the similar to CYGNSS (1.58 GHz) and has shown similar performance to AMSR-2 and WindSat [19]. SMAP has been used in previous CYGNSS validation studies, as it is one of few L-band radiometers that can provides surface wind estimates [19; 30]. Surface wind estimates are included within JPL's surface salinity product [34]. The SMAP wind speed product produced by Remote Sensing Systems was attempted and found to have a fraction of the spatial coverage compared to JPL's. It is a level 2 dataset with grid-cells at a 30 km resolution. SAR is recommended for determining the TC radius of maximum winds [36], as polarisation and higher resolution enables measurements of higher wind speeds [35]. SAR is also included, as there has not been a study comparing CYGNSS and SAR TC wind estimates, to the authors' knowledge. In order to estimate surface winds, normalised radar cross-section backscatter from Sentinel-1 and the Radarsat Constellation Missionwere mapped to coincident SMAP wind speeds to create a geophysical model function (in effect, a lookup table) [36].