Potential Index Insurance Changes under Climate Change in St. Kitts and Nevis: A Case Study Using Monte Carlo methods, observational and GCM data

Climate change poses significant challenges to Small Island Developing States (SIDS) through heat extremes, hydrometeorological extremes and sea level rise. The societal impacts of these climate hazards are closely connected to both quantifiable and non-monetary loss and damage across multiple sectors and to presently or potentially insurable risks. One type of insurance that has been explored in many developing country contexts but is particularly sensitive to the recurrence frequency of extreme events is climate index insurance (analogous to parametric insurance), in which the contract is based on a geophysical index, rather than verified material losses.

This study explores the historical risk of heat and precipitation extreme events in the small Caribbean Island nation of St. Kitts and Nevis over the period of available record (1981-2024) and the projected frequency and severity of such events over the next 50 years (2025-2075), using historical analysis, model data and Monte Carlo statistical simulation methods. Observational data will include merged station/satellite data from the products of the Climate Hazards Group at University of Santa Barbara (CHIRPS, CHIRP and CHIRTS) and may include local station data. Climate model data will include output from CMIP6 runs of the NMME and Copernicus model suites. The Monte Carlo methods used for estimating extreme event frequencies are based on earlier research (Siebert and Ward 2011, Siebert 2016). As climate risks increase, theoretical index/parametric insurance premiums are expected to increase.

            Since the frequency of threshold crossing extreme events is the primary basis for pricing index (parametric) insurance contracts, this study will explore the evolving price of relevant parametric insurance contracts for specified return liabilities (defined through recurrence interval). This project is being conducted by the company Climate Analytics and is funded by the UN Office for Project Services (UNOPS). This methodology may inform the quantification of a national loss and damage policy and plan, in coordination with multiple stakeholders in St. Kitts and Nevis and the Caribbean Climate Risk Insurance Facility (CCRIF).