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Preprints
https://doi.org/10.5194/egusphere-2023-1519
https://doi.org/10.5194/egusphere-2023-1519
11 Jul 2023
 | 11 Jul 2023

Sensitivity of the nocturnal and polar boundary layer to transient phenomena

Amandine Kaiser, Nikki Vercauteren, and Sebastian Krumscheid

Abstract. Numerical weather prediction and climate models encounter challenges in accurately representing flow regimes in the stably stratified atmospheric boundary layer and the transitions between them, leading to an inadequate depiction of regime occupation statistics. As a consequence, existing models exhibit significant biases in near-surface temperatures at high latitudes. To explore inherent uncertainties in modeling regime transitions, the response of the near-surface temperature inversion to transient small-scale phenomena is analyzed based on a stochastic modeling approach. A sensitivity analysis is conducted by augmenting a conceptual model for near-surface temperature inversions with randomizations that account for different types of model uncertainty. The stochastic conceptual model serves as a tool to systematically investigate what types of unsteady flow features, and in what contexts, may trigger abrupt transitions in the mean boundary layer state. The findings show that the incorporation of enhanced mixing, a common practice in numerical weather prediction models, blurs the two regime characteristic of the stably stratified atmospheric boundary layer. Simulating intermittent turbulence is shown to provide a potential workaround for this issue. Including key uncertainty in models could lead to a better statistical representation of the regimes in long-term climate simulation. This would help to improve our understanding and the forecasting of climate change especially in high-latitude regions.

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Journal article(s) based on this preprint

19 Jan 2024
Sensitivity of the polar boundary layer to transient phenomena
Amandine Kaiser, Nikki Vercauteren, and Sebastian Krumscheid
Nonlin. Processes Geophys., 31, 45–60, https://doi.org/10.5194/npg-31-45-2024,https://doi.org/10.5194/npg-31-45-2024, 2024
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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Current numerical weather prediction models encounter challenges in accurately representing...
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