Preprints
https://doi.org/10.5194/egusphere-2024-670
https://doi.org/10.5194/egusphere-2024-670
25 Mar 2024
 | 25 Mar 2024
Status: this preprint has been withdrawn by the authors.

Analysing CMIP5 EURO-CORDEX models in their ability to produce south foehn and the resulting climate change impact on frequency and spatial extent over western Austria

Philipp Maier, Fabian Lehner, Tatiana Klisho, and Herbert Formayer

Abstract. Foehn has an impact on various climatological variables like temperature and humidity in the highly populated valleys of western Austria. With increasing global warming, the question arises as to how well climate projections are able to produce conditions for foehn and how their occurrence changes with climate change. This study uses six XGBoost models to classify south foehn in EURO-CORDEX climate models of CMIP5 generation for two spatial extents (localised and widespread) and three regions Vorarlberg, Tiroler Oberland and Tiroler Unterland in western Austria, located in the Eastern Alps. For each region, a model for distinguishing foehn from no foehn and one to distinguish the foehn event's spatial extent is trained. Several meteorological inputs on  pressure levels from ERA5 reanalysis in combination with training data derived from semi-automated weather station data with Objective Foehn Classification are used in the training process. Weights for individual models are derived by analysing the performance of EURO-CORDEX models in their ability to produce south foehn and considering their independence from each other. The performance of individual EURO-CORDEX models is hereby evaluated by analysing their biases for annual occurrence, seasonal accuracy and inter-annual variability in comparison to the training data.The training data confirm other studies by showing that the three selected regions behave differently in their south foehn occurrence and in the portion of widespread events. Bias analysis shows a pronounced negative bias in annual foehn occurrence for models driven by the general circulation model ICHEC-EC-EARTH or MOHC-HadGEM2-ES. EURO-CORDEX models perform similar in capturing south foehn's seasonality, but highly vary in reproducing the inter-annual variability in the historical period. A weighted trend analysis for future behaviour of south foehn in the 21st century shows a slight decrease in south foehn frequency under increasing warming conditions in the Tirol regions but an increase in widespread events in all regions, most pronounced in Vorarlberg at the strongest warming. Further, a shift in foehn seasonality can be observed in all regions with a higher frequency in the spring months and a lower frequency from July to October, also depending on the climate change signal.

This preprint has been withdrawn.

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Philipp Maier, Fabian Lehner, Tatiana Klisho, and Herbert Formayer

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-670', Anonymous Referee #1, 24 Apr 2024
  • RC2: 'Comment on egusphere-2024-670', Anonymous Referee #2, 15 May 2024
  • AC1: 'Final Author Response', Philipp Maier, 06 Jun 2024

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-670', Anonymous Referee #1, 24 Apr 2024
  • RC2: 'Comment on egusphere-2024-670', Anonymous Referee #2, 15 May 2024
  • AC1: 'Final Author Response', Philipp Maier, 06 Jun 2024
Philipp Maier, Fabian Lehner, Tatiana Klisho, and Herbert Formayer

Data sets

Eleven years of training data for south foehn for three regions of Western Austria Philipp Maier, Fabian Lehner, Tatiana Klisho, and Herbert Formayer https://doi.org/10.5281/zenodo.10478610

Philipp Maier, Fabian Lehner, Tatiana Klisho, and Herbert Formayer

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This preprint has been withdrawn.

Short summary
In this article, we analyse the ability of climate models to produce south foehn in the valleys of western Austria using a machine learning technique and assess, how well they capture different aspects of annual foehn occurrence. The performance of these models is largely influenced by the underlying global climate model. After weighting the models based on their performance, we found that foehn occurrence slightly decreases with global warming, but events tend to become more widespread.