Articles | Volume 19, issue 2
https://doi.org/10.5194/amt-19-617-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-617-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Lightning Differential Space framework: multiscale analysis of stroke and flash behavior
Yuval Ben Ami
Department of Earth and Planetary Sciences, The Weizmann Institute of Science, Rehovot, 7610001, Israel
Orit Altaratz
Department of Earth and Planetary Sciences, The Weizmann Institute of Science, Rehovot, 7610001, Israel
Yoav Yair
School of Sustainability, Reichman University, Herzliya, 4610101, Israel
Department of Earth and Planetary Sciences, The Weizmann Institute of Science, Rehovot, 7610001, Israel
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Huan Liu, Ilan Koren, Orit Altaratz, and Shutian Mu
EGUsphere, https://doi.org/10.5194/egusphere-2025-2574, https://doi.org/10.5194/egusphere-2025-2574, 2025
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Clouds play a crucial role in Earth's climate by reflecting sunlight and trapping heat. Understanding how clouds respond to global warming (cloud feedback) is essential for climate change. However, the natural climate variability, like ENSO, can distort these estimates. Relying on long-term reanalysis data and simulations, this study finds that ENSO with a typical periodicity of 2–7 years can introduce a significant bias on cloud feedback estimates on even decadal to century time scales.
Manuel Santos Gutiérrez, Mickaël David Chekroun, and Ilan Koren
EGUsphere, https://doi.org/10.48550/arXiv.2405.11545, https://doi.org/10.48550/arXiv.2405.11545, 2024
Preprint withdrawn
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This letter explores a novel approach for the formation of cloud droplets in rising adiabatic air parcels. Our approach combines microphysical equations accounting for moisture, updrafts and concentration of aerosols. Our analysis reveals three regimes: A) Low moisture and high concentration can hinder activation; B) Droplets can activate and stabilize above critical sizes, and C) sparse clouds can have droplets exhibiting activation and deactivation cycles.
Huan Liu, Ilan Koren, Orit Altaratz, and Mickaël D. Chekroun
Atmos. Chem. Phys., 23, 6559–6569, https://doi.org/10.5194/acp-23-6559-2023, https://doi.org/10.5194/acp-23-6559-2023, 2023
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Clouds' responses to global warming contribute the largest uncertainty in climate prediction. Here, we analyze 42 years of global cloud cover in reanalysis data and show a decreasing trend over most continents and an increasing trend over the tropical and subtropical oceans. A reduction in near-surface relative humidity can explain the decreasing trend in cloud cover over land. Our results suggest potential stress on the terrestrial water cycle, associated with global warming.
Elisa T. Sena, Ilan Koren, Orit Altaratz, and Alexander B. Kostinski
Atmos. Chem. Phys., 22, 16111–16122, https://doi.org/10.5194/acp-22-16111-2022, https://doi.org/10.5194/acp-22-16111-2022, 2022
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We used record-breaking statistics together with spatial information to create record-breaking SST maps. The maps reveal warming patterns in the overwhelming majority of the ocean and coherent islands of cooling, where low records occur more frequently than high ones. Some of these cooling spots are well known; however, a surprising elliptical area in the Southern Ocean is observed as well. Similar analyses can be performed on other key climatological variables to explore their trend patterns.
Eshkol Eytan, Ilan Koren, Orit Altaratz, Mark Pinsky, and Alexander Khain
Atmos. Chem. Phys., 21, 16203–16217, https://doi.org/10.5194/acp-21-16203-2021, https://doi.org/10.5194/acp-21-16203-2021, 2021
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Describing cloud mixing processes is among the most challenging fronts in cloud physics. Therefore, the adiabatic fraction (AF) that serves as a mixing measure is a valuable metric. We use high-resolution (10 m) simulations of single clouds with a passive tracer to test the skill of different methods used to derive AF. We highlight a method that is insensitive to the available cloud samples and allows considering microphysical effects on AF estimations in different environmental conditions.
Mengyu Sun, Dongxia Liu, Xiushu Qie, Edward R. Mansell, Yoav Yair, Alexandre O. Fierro, Shanfeng Yuan, Zhixiong Chen, and Dongfang Wang
Atmos. Chem. Phys., 21, 14141–14158, https://doi.org/10.5194/acp-21-14141-2021, https://doi.org/10.5194/acp-21-14141-2021, 2021
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By acting as cloud condensation nuclei (CCN), increasing aerosol loading tends to enhance lightning activity through microphysical processes. We investigated the aerosol effects on the development of a thunderstorm. A two-moment bulk microphysics scheme and bulk lightning model were coupled in the WRF Model to simulate a multicell thunderstorm. Sensitivity experiments show that the enhancement of lightning activity under polluted conditions results from an increasing ice crystal number.
Tom Dror, Mickaël D. Chekroun, Orit Altaratz, and Ilan Koren
Atmos. Chem. Phys., 21, 12261–12272, https://doi.org/10.5194/acp-21-12261-2021, https://doi.org/10.5194/acp-21-12261-2021, 2021
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A part of continental shallow convective cumulus (Cu) was shown to share properties such as organization and formation over vegetated areas, thus named green Cu. Mechanisms behind the formed patterns are not understood. We use different metrics and an empirical orthogonal function (EOF) to decompose the dataset and quantify organization factors (cloud streets and gravity waves). We show that clouds form a highly organized grid structure over hundreds of kilometers at the field lifetime.
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Short summary
We advanced the Lightning Differential Space (LDS) method, which maps time and distance between lightning strokes, and demonstrated its use across three distinct meteorological regions. By comparing stroke strength and timing, our new Current Ratio approach reveals flash initiation patterns in different storm types. The method is straightforward and data-driven, enabling physical insight without model-based analysis or prior assumptions, and supports regional lightning analysis and forecasting.
We advanced the Lightning Differential Space (LDS) method, which maps time and distance between...