Novel Approaches to Predict Extreme Events in Atmospheric Flows: From Turbulence to Climate

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: 25 August 2025 | Viewed by 91

Special Issue Editor


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Guest Editor
Natural Resources Institute Finland (Luke), Latokartanonkaari 9, 00790 Helsinki, Finland
Interests: atmospheric boundary layer; turbulence; scaling analysis; complex system science; network science

Special Issue Information

Dear Colleagues,

In the current era, extremes hold a very special place, especially in the context of atmospheric science. To make research more challenging, extremes in meteorological variables have multiscale natures with different physical origins. For instance, at turbulent scales, the extreme events in wind components and scalar concentrations (temperature, greenhouse gases) are related to intermittency, a phenomenon that introduces significant challenges in turbulence parameterizations. This eventually has an impact on predictions of pollution concentrations, wind gusts, and turbulent fluxes over complex landscapes. On the other hand, at climate scales, the occurrences of extreme events (e.g., droughts, wildfires) are linked to different climatic phenomena, such as ENSO, volcanic eruptions, etc. However, with increasing global temperature, these events have risen in frequency at an unprecedented rate, with catastrophic consequences.

Despite their importance, the chaotic dynamics of atmospheric flows impose significant uncertainties regarding how the future intensities and spatial distributions of climatic extremes will vary. At the opposite end of the spectrum, the detection of extremes in turbulent variables continues to be an active area of research. Therefore, to make progress towards these issues, we encourage submissions that propose novel approaches (both theoretical and experimental) to diagnose extremes spanning across scales from turbulence to the climate. In this Special Issue, we invite submissions on topics that include, but are not limited to, the following:

  1. Statistical models to predict extreme events across multiple scales.
  2. Novel theoretical and experimental approaches to detect extreme events.
  3. The impacts of extremes on ecosystem greenhouse gas exchanges.
  4. Assessments of artificial intelligence/machine learning approaches in extreme event predictions.

Dr. Subharthi Chowdhuri
Guest Editor

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Keywords

  • atmospheric flows
  • climate extremes
  • boundary layer meteorology
  • fire–turbulence interactions
  • precipitation
  • extremes in turbulent flows
  • artificial intelligence/machine learning approaches
  • non-linear dynamics

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Published Papers (1 paper)

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Research

17 pages, 2511 KiB  
Article
Can GCMs Simulate ENSO Cycles, Amplitudes, and Its Teleconnection Patterns with Global Precipitation?
by Chongya Ma, Jiaqi Li, Yuanchun Zou, Jiping Liu and Guobin Fu
Atmosphere 2025, 16(5), 507; https://doi.org/10.3390/atmos16050507 - 27 Apr 2025
Viewed by 101
Abstract
The ability of a general circulation model (GCM) to capture the variability of El Niño–Southern Oscillation (ENSO) is not only a scientific issue of climate model performance, but also critical for climate change and variability impact studies. Here, we assess 48 CMIP5 GCMs [...] Read more.
The ability of a general circulation model (GCM) to capture the variability of El Niño–Southern Oscillation (ENSO) is not only a scientific issue of climate model performance, but also critical for climate change and variability impact studies. Here, we assess 48 CMIP5 GCMs for their skill in simulating ENSO interdecadal variability and its teleconnection with precipitation globally. The results show that (1) only 22 out of 48 GCMs display interdecadal variability that is similar to the observations; (2) the ensemble of the 48 GCMs captures the ENSO–precipitation teleconnection at the global scale; (3) no single GCM can capture the observed ENSO–precipitation teleconnection globally; and (4) a GCM that can realistically simulate ENSO variability does not necessarily capture the ENSO-precipitation teleconnection, and vice versa. The results could also be used by climate change impact studies to select suitable GCMs, especially for regions with a statistically significant teleconnection between ENSO and precipitation, as well as for the comparison of CMIP5 and CMIP6. Full article
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