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Urban areas are prone to climate change impacts. Simultaneously the world’s population increasingly resides in cities. In this light, there is a growing need to equip urban decision makers with evidence-based climate information tailored to their specific context, to adequately adapt to and prepare for future climate change.
To construct climate information high-resolution regional climate models and their projections are pivotal, to provide a better understanding of the unique urban climate and its evolution under climate change. There is a need to move beyond commonly investigated variables, such as temperature and precipitation, to cover a wider breath of possible climate impacts. In this light, the research presented in this thesis is centered around enhancing the understanding about regional-to-local climate change in Berlin and its surroundings, with a focus on humidity. More specifically, following a regional climate modelling and data analysis approach, this research aims to understand the potential of regional climate models, and the possible added value of convection-permitting simulations, to support the development of high-quality climate information for urban regions, to support knowledge-based decision-making.
The first part of the thesis investigates what can already be understood with available regional climate model simulations about future climate change in Berlin and its surroundings, particularly with respect to humidity and related variables. Ten EURO-CORDEX model combinations are analyzed, for the RCP8.5 emission scenario during the time period 1970 ̶ 2100, for the Berlin region. The results are the first to show an urban-rural humidity contrast under a changing climate, simulated by the EURO-CORDEX ensemble, of around 6 % relative humidity, and a robust enlarging urban drying effect, of approximately 2 ̶ 4 % relative humidity, in Berlin compared to its surroundings throughout the 21st century.
The second part explores how crossing spatial scales from 12.5 km to 3 km model grid size affects unprecedented humidity extremes and related variables under future climate conditions for Berlin and its surroundings. Based on the unique HAPPI regional climate model dataset, two unprecedented humidity extremes are identified happening under 1.5 °C and 2 °C global mean warming, respectively SH>0.02 kg/kg and RH<30 %. Employing a double-nesting approach, specifically designed for this study, the two humidity extremes are downscaled to the 12.5 km grid resolution with the regional climate model REMO, and thereafter to the 3 km with the convection-permitting model version of REMO (REMO NH). The findings indicate that the convection-permitting scale mitigates the SH>0.02 kg/kg moist extreme and intensifies the RH<30 % dry extreme. The multi-variate process analysis shows that the more profound urban drying effect on the convection-permitting resolution is mainly due to better resolving the physical processes related to the land surface scheme and land-atmosphere interactions on the 3 km compared to the 12.5 km grid resolution. The results demonstrate the added value of the convection-permitting resolution to simulate future humidity extremes in the urban-rural context.
The third part of the research investigates the added value of convection-permitting models to simulate humidity related meteorological conditions driving specific climate change impacts, for the Berlin region. Three novel humidity related impact cases are defined for this research: influenza spread and survival; ragweed pollen dispersion; and in-door mold growth. Simulations by the regional climate model REMO are analyzed for the near future (2041 ̶ 2050) under emission scenario RCP8.5, on the 12.5 km and 3 km grid resolution. The findings show that the change signal reverses on the convection-permitting resolution for the impact cases pollen, and mold (positive and negative). For influenza, the convection-permitting resolution intensifies the decrease of influenza days under climate change. Longer periods of consecutive influenza and mold days are projected under near-term climate change. The results show the potential of convection-permitting simulations to generate improved information about climate change impacts in urban regions to support decision makers.
Generally, all results show an urban drying effect in Berlin compared to its surroundings for relative and specific humidity under climate change, respectively for the urban-rural contrast throughout the 21st century, for the downscaled future extreme conditions, and for the three humidity related impact cases. Added value for the convection-permitting resolution is found to simulate humidity extremes and the meteorological conditions driving the three impacts cases.
The research makes novel contributions that advance science, through demonstrating the potential of regional climate models, and especially the added value of convection-permitting models, to understand urban rural humidity contrasts under climate change, supporting the development of knowledge-based climate information for urban regions.
