# Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones
## 1 Introduction  
The NASA CYGNSS mission is a constellation of small low-Earth-orbit satellites launched on 15 December 2016, with the objective of measuring ocean surface winds over the tropics through the innovative use of ocean surface reflectometry [1, 2, 3, 4, 5]. This is in contrast to traditional satellite missions which instead observe the emission or backscatter from the wind-roughened ocean surface. The CYGNSS satellite constellation was designed with the goal of providing critical and frequent wind measurements in the core of tropical cyclones (TCs). With this objective in mind, here we focus on assessing the capability of CYGNSS observations in TCs from all wind datasets currently available to the public using recently developed satellite TC wind products. Measuring extreme winds in storms has been historically challenging for traditional satellite microwave sensors. Scatterometers suffer from decreased sensitivity to the observed signal and partial saturation at very high winds, making it impossible to distinguish the signal coming from a Category 1 storm (33-42 m/s in the Saffir-Simpson hurricane scale) and the signal from a Category 3 (50-58 m/s) storm. Intense rain in tropical storms affects the observed microwave signals from microwave scatterometers and radiometers. In intense rain, in addition to the desired signal caused by the wind-roughened surface, signals arise due to scattering from rain drops, roughening of the ocean surface caused by a rain \"splash effect\", and precipitation attenuating the surface emission via atmospheric absorption. The impact of rain on microwave signals can be mitigated by using a very low frequency (L-band, about 1.4 GHz), which is mostly unaffected by rain scattering and attenuation. However, sensors operating at these frequencies require large antennas(4-6 m), rendering their missions very expensive. An additional challenge facing traditional sensors is that being in polar, low-Earth orbit, a single instrument can only see each storm at most twice a day, and they often miss storms altogether when TCs fall in the wide satellite coverage gaps. To overcome these challenges, the CYGNSS mission introduced a new approach: a constellation of small satellites with inclined orbits to provide coverage in the tropics, with a frequent revisit time, using L-band reflectometry to measure ocean surface winds via the existing network of Global Navigation Satellite System (GNSS) [3; 4]. The L-band signals are transmitted from the GPS network, and the signals from specular reflection at the ocean surface are received by the CYGNSS sensors, which record the Doppler-delay maps (DDMs) for each specular reflection. DDMs are subsequently converted to normalized radar cross-section (NBRCS) signals. An empirical geophysical model function (GMF) is then used to determine the ocean surface wind speed that corresponds to that NBRCS signal, given the specific observational geometry and several ocean geophysical parameters. Because of these innovative features, CYGNSS is considered a proof-of-concept mission, prone to unplanned difficulties. Nevertheless, future missions based on similar observational principles can benefit from what is learned while addressing the current challenges faced by CYGNSS. Soon after CYGNSS' launch at the end of 2016, unforeseen calibration and methodology issues emerged [6; 7; 8; 9]. Multiple factors contributed to these issues: (a) the assumed nominal calibration of the GPS transmitters has been found to be unreliable, and large signal variability occurs over time [10]; (b) the wind retrieval algorithm depends on many factors, including the sea state and wave height [11; 12; 13]; (c) several calibration issues resulted in wind retrievals of adjacent tracks having inconsistent values, making the wind products unreliable, particularly at high winds and in the small regions affected by storms [8]; (d) the returned signal loses sensitivity at very high winds [14; 15]. Due to these problems, the CYGNSS wind retrievals at high winds proved to be challenging.