A joint analysis of CFOSAT SWIM/SCAT and Sentinel-1 SAR data together with results of recently developed parametric model for rapid estimation of waves in tropical cyclones (TC) is presented. The satellite measurements were obtained over the Philippine Sea on October 29th, 2020, in TC Goni. The model for wave evolution inside TC is based on energy and momentum conservation laws. The coupled equations are written in their characteristic form to provide practical means to rapidly assess how the energy, frequency and direction of dominant surface waves are developing under varying wind forcing conditions and how the waves leave the storm area as swell systems. Being tested on a number of cyclones with different parameters (maximum wind speed um, TC radius Rm and heading velocity V), the model results have been reduced to analytical self-similar solution (TC-wave geophysical model function (GMF)) for the immediate first-guess estimate of significant wave height, wavelength and wave direction fields generated by an arbitrary cyclone characterized by a set of um, Rm and V. Results of wave modeling with the wind field input either from Sentinel-1 SAR or CFOSAT SCAT data are compared to CFOSAT SWIM measurements, including altimeter ones. The wave fields inside moving cyclones usually exhibit a strong azimuthal asymmetry, resulting from a resonance between wave group velocity and TC heading velocity. For TC Goni, this effect is well captured, leading to extreme waves with heights up to 8 m, further outrunning as swell with wavelength about 250 m in the TC heading direction. A quantitative agreement between the satellite measurements and model results (both the direct model and its simplified solutions) is observed. In the far zone (~10 Rm) local wind is found to be the leading factor of wave formation. The case study demonstrates that combined radar, altimeter, scatterometer data, numerical modeling and analytical self-similar solutions open new perspectives to study the waves generated by TCs for different scientific and practical purposes including hazard prediction.