Tides of Change: How Climate Will Reshape Coastal Tourism in Europe. Destination Shifts, Economic Impacts, and Adaptation Options

European coastal regions represent a substantial share of the European tourism economy, but they are also among the places where climate change is most likely to be felt by visitors and businesses alike. Rising temperatures, changing precipitation regimes, and altered wind and cloudiness patterns can directly affect thermal comfort and perceived “beach quality,” with implications for visitation, seasonality, and local economies. This study quantifies how climate shapes coastal-beach tourism demand across Europe and translates these relationships into forward-looking, risk-based scenario insights.

Climate suitability is characterized using the Holiday Climate Index for beach tourism (HCI:Beach; Scott et al., 2016), a bioclimatic indicator integrating temperature, precipitation, humidity, wind, and cloudiness to reflect tourists’ stated preferences and destination comfort. This indicator is employed in a monthly panel tourism-demand model estimated on historical regional observations of tourism activity, alongside sector-specific controls and fixed effects. The resulting estimates indicate a statistically significant link between HCI:Beach and tourism demand, and a clear north-south pattern in demand changes in observed , with northern regions benefiting and southern regions experiencing significant reductions, particularly in higher warming scenarios.

To evaluate future impacts, monthly HCI:Beach projections through 2100 are generated using an ensemble of ten regional climate models, and corresponding changes in tourism demand are simulated. Uncertainty is represented from two sources: (i) climate model spread, by sampling across the ensemble projections of the underlying climate variables, and (ii) statistical uncertainty, by repeatedly drawing from the estimated parameter distribution of the demand model. These components are combined in a Monte Carlo framework, producing distributions of future demand outcomes.

Results are reported under two emissions pathways (RCP4.5 and RCP8.5) and, to support policy-relevant interpretation, are also summarized for four global warming levels (1.5°C, 2°C, 3°C, and 4°C). Across European coasts, projections reveal strong spatial and seasonal heterogeneity: climate change can improve suitability in some destinations and months (often in shoulder seasons) while degrading peak-season conditions elsewhere, implying shifts in the timing and geography of demand.

The risk assessment translates probabilistic projections into decision-ready metrics, such as the probability of peak-season demand losses exceeding specified thresholds, the likelihood of shoulder-season demand gains, and the emergence of “high-risk months” in which unfavorable beach conditions become consistently more common. Robust signals are further identified (high agreement across climate models and stable econometric effects) versus deep-uncertainty cases where adaptive strategies should remain flexible.

Finally, building on these findings, adaptation options tailored to regional and seasonal risk profiles are discussed, including spreading demand though season extension and product diversification, or managing heat and comfort through services and information. By integrating a preference-based climate index, econometric demand estimation, multi-model climate projections, and probabilistic risk metrics, this study provides a transparent framework to anticipate where, when, and how European coastal tourism may change.

Keywords: climate change impacts, coastal tourism demand, panel data analysis, HCI:Beach (Holiday Climate Index)