Spatial Heterogeneity of Compound Heat and Ozone Extremes: A Multivariate Extreme Value Perspective in Southern Germany

Extreme heat and surface ozone pollution frequently co-occur during summer and pose a growing risk to human health under climate warming. This co-occurrence is expected to intensify in the future, as global climate change is projected to increase the frequency, intensity, and duration of heatwaves. At the same time, ozone remains a major air quality concern in Europe despite substantial reductions in precursor emissions, and its health impacts are well documented even at concentrations below current regulatory standards.

Previous studies have shown that temperature is a key meteorological driver of high ozone episodes, particularly in summer when photochemical activity is strongest. However, recent work on compound climate extremes has demonstrated that univariate or linear approaches can substantially underestimate risk when extremes occur simultaneously, highlighting the need for multivariate extreme-value methods.

Moreover, spatial heterogeneity related to urbanization, land use, topography, and local meteorological conditions is often acknowledged but rarely examined in terms of how it modifies the occurrence and strength of heat–ozone extremes at the local scale. Ozone formation is governed by complex, nonlinear interactions between temperature, emissions, boundary-layer processes, and deposition, making its response highly variable in space and time. As a result, simple correlation-based analyses may underestimate the true influence of temperature on ozone, particularly under extreme conditions and in heterogeneous environments.

Previous studies in Germany and Bavaria have linked ozone and temperature observations using either nearest station matching or reanalysis products such as ERA5, often assuming limited influence of urban heat island effects on daily maximum temperature. While this approach reflects established practice in regional air-quality studies, it may introduce uncertainty in spatially heterogeneous environments, particularly for local-scale compound extremes. Matching based solely on proximity or large-scale fields may not fully capture the influence of land use and station setting. To address this methodological challenge, the present study adopts a land-use–informed, multi-scale matching perspective to evaluate the sensitivity of compound heat–ozone dependence to spatial scale.

This study aims to quantify compound heat–ozone extremes in Bavaria using multivariate analysis, with a focus on (i) how urban–rural setting and local spatial context shape compound risk, and (ii) how dependence strengthens during heatwave extremes and multi-day heatwave conditions.

By bridging statistical extreme-value analysis with atmospheric chemistry interpretation, this work provides a physically consistent and regionally relevant assessment of heat–ozone risks in southern Germany.