Articles | Volume 5, issue 4
https://doi.org/10.5194/wcd-5-1545-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-5-1545-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Dec 2024
Research article |
| 20 Dec 2024
| 20 Dec 2024
Detection and consequences of atmospheric deserts: insights from a case study
Department of Atmospheric and Cryospheric Sciences, Universität Innsbruck, Innsbruck, Austria
Georg Mayr
Department of Atmospheric and Cryospheric Sciences, Universität Innsbruck, Innsbruck, Austria
Achim Zeileis
Department of Statistics, Universität Innsbruck, Innsbruck, Austria
Isabell Stucke
Department of Atmospheric and Cryospheric Sciences, Universität Innsbruck, Innsbruck, Austria
Reto Stauffer
Department of Statistics & Digital Science Center, Universität Innsbruck, Innsbruck, Austria
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Atmospheric deserts are air masses from the boundary layer of desert regions. This study tracked them from North Africa to Europe during a two-year period (May 2022–April 2024). They can occur up to 60 % of the time, and can span large parts of Europe. They typically last about a day, and can alter the atmosphere throughout the free troposphere. On its way from Africa the air either rises and may become even warmer and drier, or it stays at mid-altitudes and cools, or retains its properties.
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Atmospheric deserts are air masses from the boundary layer of desert regions. This study tracked them from North Africa to Europe during a two-year period (May 2022–April 2024). They can occur up to 60 % of the time, and can span large parts of Europe. They typically last about a day, and can alter the atmosphere throughout the free troposphere. On its way from Africa the air either rises and may become even warmer and drier, or it stays at mid-altitudes and cools, or retains its properties.
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Statistical post-processing is necessary to generate probabilistic forecasts from physical numerical weather prediction models. To allow for more flexibility, there has been a shift in post-processing away from traditional parametric regression models towards modern machine learning methods. By fusing these two approaches, we developed model output statistics random forests, a new post-processing method that is highly flexible but at the same time also very robust and easy to interpret.
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Two thunderstorm environments are described for Europe: mass-field thunderstorms, which occur mostly in summer, over land, and under similar meteorological conditions, and wind-field thunderstorms, which occur mostly in winter, over the sea, and under more diverse meteorological conditions. Our descriptions are independent of static thresholds and help to understand why thunderstorms in unfavorable seasons for lightning pose a particular risk to tall infrastructure such as wind turbines.
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The power generated by offshore wind farms can vary greatly within a couple of hours, and failing to anticipate these ramp events can lead to costly imbalances in the electrical grid. A novel multivariate Gaussian regression model helps us to forecast not just the means and variances of the next day's hourly wind speeds, but also their corresponding correlations. This information is used to generate more realistic scenarios of power production and accurate estimates for ramp probabilities.
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Wintertime lightning in central Europe is rare but has a large damage potential for tall structures such as wind turbines. We use a data-driven approach to explain why it even occurs when the meteorological processes causing thunderstorms in summer are absent. In summer, with strong solar input, thunderclouds have a large vertical extent, whereas in winter, thunderclouds are shallower in the vertical but tilted and elongated in the horizontal by strong winds that increase with altitude.
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Short summary
Atmospheric deserts (ADs) are air masses that are transported away from hot, dry regions. Our study introduces this new concept. ADs can suppress or boost thunderstorms and potentially contribute to the formation of heat waves, which makes them relevant for forecasting extreme events. Using a novel detection method, we follow an AD directly from North Africa to Europe for a case in June 2022, allowing us to analyse the air mass at any time and investigate how it is modified along the way.
Atmospheric deserts (ADs) are air masses that are transported away from hot, dry regions. Our...
