Climate change in the alps: Comparing different climate models based on estimates of monthly data.

The new generation of global climate models (GCM) CMIP6 show significantly higher climate sensitivity then their predecessors (Zelinka 2020), introducing faster temperature rise than expected. Especially mountainous regions are sensitive to climate change resulting in higher frequency of extreme weather events (Gobiet 2014). Unfortunately, global climate models are too coarse to deliver reliable data in complex terrain, making it difficult to estimate regional effects of climate change. Climate indicators like maximum precipitation in one day or heat days are a profound way to investigate climate change, not only in its means, but also in its extremes. These indicators are often peak-over-threshold indicators which need daily and bias adjusted data to be calculated from. But there are valuable data sets like HISTALP which reach back until the year 1750 consisting solely of monthly frequency. We compare two generations of GCMs (CMIP6 vs CMP5) to understand their systematic differences and how these differences affect the climate indices in the models global warming levels (GWL). Furthermore, we try to analyse the differences in precipitation trends and if these interact with the trends in extreme temperatures. To be able to compare the data with mentioned HISTALP dataset, we calculate the indices from monthly data using the method presented in Hasel et. al. 2023. The method consists of a linear regression model connecting monthly meteorological parameters with their respective climate index. Trained by ERA5 Land data, which is supplemented by a CMIP6 global climate model, it also allows to capture the effects of climate change. Additionally, it contains a simple bias adjustment and regrids the data to ERA5 Lands 0.1 grid. References Zelinka, M. D., Myers, T. A., McCoy, D. T., PoChedley, S., Caldwell, P. M., Ceppi, P., ... Taylor, K. E. (2020). Causes of higher climate sensitivity in CMIP6 models.Geophysical Research Letters,47(1), e2019GL085782. Hasel, K., Bgelmayer-Blaschek, M., Formayer, H. (2023). A statistical approach on estimations of climate change indices by monthly instead of daily data.Atmosphere,14(11), 1634. Gobiet, A., Kotlarski, S., Beniston, M., Heinrich, G., Rajczak, J., Stoffel, M. (2014). 21st century climate change in the European AlpsA review.Science of the total environment,493, 1138-1151.