Today, advanced operational wave models, e.g. WAM, SWAN or WAVEWATCH-III, provide very accurate solutions. Nevertheless, under extreme weather conditions, surface wave predictions can remain challenging. Indeed, for relatively small-scale tropical cyclones (TCs), rapidly evolving in time and space, and possibly not always well sampled with observing systems, extreme winds may not be properly described, and generated wave systems correctly predicted. In that context, Kudryavtsev et al. (2021b) recently proposed a simplified framework to rapidly assess evolving wave fields under typical TC conditions. Using self-similar functions, termed Tropical Cyclone-Wave Geophysical Model Function (TCW GMF), the proposed methodology and initial results demonstrate robustness and efficiency : 2D functions, assimilating a small number of parameters (maximum wind speed, cyclone radius and translation velocity), provide first-guess estimates of surface wave heights, wave lengths and directions within the intense TC core region. Following this strategy, an improved TCW GMF version is proposed to also cover the TC far zone, providing both wind wave information and outrunning swell conditions. This new version more particularly accounts for the wave field sensitivity to the shape of the wind profile. The procedure follows three main steps: (1) estimation of the characteristics of pure wind waves using self-similar matrices; (2) determination of the contour limiting the transition between wind waves to swell regime using empirically-derived universal functions; (3) derivation of analytical functions to describe the swell parameters using initial parameters estimated at this transition contour. Wind waves and swell systems are further superposed to describe the wave parameters for mixed-sea conditions. In this study, IBTrACS are used to initialize the TC’s wind profiles, coordinates and translation velocities. The proposed methodology is then tested using a large altimeter database. More than 700 altimeter measurements crossing different TCs during 2020–2022 years are used, demonstrating overall convincing agreements between first-guess estimates and satellite data.