  In many practical applications, evaluating the joint impact of combinations
of environmental variables is important for risk management and structural
design analysis. When such variables are considered simultaneously,
non-stationarity can exist within both the marginal distributions and
dependence structure, resulting in complex data structures. In the context of
extremes, few methods have been proposed for modelling trends in extremal
dependence, even though capturing this feature is important for quantifying
joint impact. Moreover, most proposed techniques are only applicable to data
structures exhibiting asymptotic dependence. Motivated by observed dependence
trends of data from the UK Climate Projections, we propose a novel
semi-parametric modelling framework for bivariate extremal dependence
structures. This framework allows us to capture a wide variety of dependence
trends for data exhibiting asymptotic independence. When applied to the climate
projection dataset, our model detects significant dependence trends in
observations and, in combination with models for marginal non-stationarity, can
be used to produce estimates of bivariate risk measures at future time points.
