Parametric solutions emerged in the 1990s as an alternative to the traditional insurance solutions. Parametric solutions offer a faster and more efficient risk transfer approach, not relying on lengthy claims process, but on pre-agreed payouts triggered by specific parameters. This paper explores a regression-based methodology to support the design of cat-in-a-grid tropical cyclone parametric solutions, considering different tropical cyclone characteristics, typically publicly available in the aftermath of the event. The paper specifically investigates different single-metric parametric solutions for Jamaica based on maximum wind speed, minimum central pressure, and radius of maximum wind speed, respectively. However, the methodology is general and can be applied to different regions and hazards. Results show that parametric solutions based on maximum wind speed and minimum central pressure provide good accuracy metrics and a satisfactory agreement with loss estimates for historical events, whereas parametric solutions based on the radius of maximum wind speed have limited predictive power, suggesting a better use of such parameter as a complement of maximum wind speed and/or minimum central pressure in multi-metric parametric solutions.