Articles | Volume 19, issue 11
https://doi.org/10.5194/gmd-19-5041-2026
© 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/gmd-19-5041-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
15 Jun 2026
Methods for assessment of models |
| 15 Jun 2026
| 15 Jun 2026
Composite sharpening by vortex symmetrization and normalization of tropical cyclones
Andrina Caratsch
CORRESPONDING AUTHOR
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Sylvaine Ferrachat
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Ulrike Lohmann
CORRESPONDING AUTHOR
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Related authors
No articles found.
Hailing Jia, David Neubauer, Yusuf Bhatti, Duncan Watson-Parris, Philip Stier, Johannes Quaas, Daniel Partridge, Ardit Arifi, Anne Kubin, Athanasios Nenes, Muhammed Irfan, Ulas Im, Carl Svenhag, Nick Schutgens, Bastiaan van Diedenhoven, Sylvaine Ferrachat, Ulrike Lohmann, Ina Tegen, Alice Henkes, Guangliang Fu, and Otto Hasekamp
EGUsphere, https://doi.org/10.5194/egusphere-2026-3275, https://doi.org/10.5194/egusphere-2026-3275, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Tiny aerosol particles affect Earth’s climate by interacting with clouds and sunlight, but their impact remains uncertain. Combining climate model simulations and emulators, we explored millions of model variants across different aerosol and cloud settings to identify the causes of the uncertainty. We found that aerosol emissions and cloud convection are key contributors. Our work suggests that better integration of existing observations could help reduce these uncertainties in the future.
Nikolaos Papaevangelou, Diego Villanueva, and Ulrike Lohmann
Atmos. Chem. Phys., 26, 9393–9412, https://doi.org/10.5194/acp-26-9393-2026, https://doi.org/10.5194/acp-26-9393-2026, 2026
Short summary
Short summary
In this study, we investigate the impact of silver iodide (AgI) perturbations on eight hailstorms over Switzerland and southern Germany using the Consortium for Small-scale Modeling (COSMO) model. Generally, the impact of AgI seeding on hail is highly case-dependent and sensitive to the choice of tracking thresholds. However, in most cases, the mean hail size increases after seeding, while the hail-affected area decreases.
Huiying Zhang, Chia Rui Ong, Anurag Dipankar, Ulrike Lohmann, and Jan Henneberger
Atmos. Chem. Phys., 26, 8677–8693, https://doi.org/10.5194/acp-26-8677-2026, https://doi.org/10.5194/acp-26-8677-2026, 2026
Short summary
Short summary
We used computer simulations to study cloud seeding. We discovered a 'self-lofting' mechanism whereby, as the seeded ice crystals grow, they release heat, generating an upward air current. This enables the ice plume to rise and spread vertically, even when the surrounding air is sinking. This is why seeded ice survives in unfavourable wind conditions. Our results demonstrate that this internal heating is essential for the effectiveness and validation of weather modification technologies.
Ryan Vella and Ulrike Lohmann
EGUsphere, https://doi.org/10.5194/egusphere-2026-2961, https://doi.org/10.5194/egusphere-2026-2961, 2026
Short summary
Short summary
The Atlantic Ocean's overturning circulation transports heat northward and may weaken under climate change. We show that this weakening redistributes natural dust and other particles across the atmosphere, altering cloud properties worldwide. Clouds become thinner in cold regions, reducing their ability to cool the planet. This produces a warming effect of about 0.84 watts per square metre that partially counteracts the cooling from a weaker circulation.
Nadja Omanovic, Debora Bötticher, Christopher Fuchs, and Ulrike Lohmann
Atmos. Chem. Phys., 26, 5345–5353, https://doi.org/10.5194/acp-26-5345-2026, https://doi.org/10.5194/acp-26-5345-2026, 2026
Short summary
Short summary
The interplay of liquid and ice particles in clouds is a crucial driver for forming rain over land. We use numerical simulations to evaluate how fast clouds can be glaciated through ice particles and how this depends on different initial states of the cloud. We find that the more water a cloud contains, the longer the glaciation takes while any additional turbulent mixing does not have a major impact.
Yichen Jia, Hendrik Andersen, David Neubauer, Ulrike Lohmann, Corinna Hoose, and Jan Cermak
EGUsphere, https://doi.org/10.5194/egusphere-2026-569, https://doi.org/10.5194/egusphere-2026-569, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Understanding how ocean clouds respond to air pollution is important for climate projections. Using artificial intelligence and a climate model, we show that some model settings produce very high cloud cover, leaving little room for further cloud growth as pollution increases. This “headroom effect” can make cloud responses appear weak. Our results highlight the need to consider existing cloud conditions when interpreting how cloud cover responds to the environment.
Huiying Zhang, Fabiola Ramelli, Christopher Fuchs, Nadja Omanovic, Anna J. Miller, Robert Spirig, Zhaolong Wu, Yunpei Chu, Xia Li, Ulrike Lohmann, and Jan Henneberger
Atmos. Chem. Phys., 26, 1459–1481, https://doi.org/10.5194/acp-26-1459-2026, https://doi.org/10.5194/acp-26-1459-2026, 2026
Short summary
Short summary
Ice crystals in clouds aggregate, shaping snow and rain, yet rates are hard to measure. Using cloud seeding, we sampled crystals downwind after known times. A deep-learning algorithm quantified aggregation by counting crystal components. Initial ice concentration was the main driver, confirmed by causal analysis, physics, and machine learning, though weaker than theory predicts. Temperature, size, and shape also mattered, while turbulence was negligible.
Christopher Fuchs, Fabiola Ramelli, Anna J. Miller, Nadja Omanovic, Robert Spirig, Huiying Zhang, Patric Seifert, Kevin Ohneiser, Ulrike Lohmann, and Jan Henneberger
Atmos. Chem. Phys., 25, 12177–12196, https://doi.org/10.5194/acp-25-12177-2025, https://doi.org/10.5194/acp-25-12177-2025, 2025
Short summary
Short summary
We quantify diffusional ice crystal growth in natural clouds using cloud seeding experiments. We report growth rates for 14 experiments between −5.1 °C and −8.3 °C and observe strong variations depending on the cloud characteristics. Comparing our growth rates to laboratory data, we found similar temperature-dependent trends, but the laboratory rates are higher. These data fill the gap in quantitative in situ observation of ice crystal growth, helping to validate models and laboratory experiments.
Kai Jeggle, David Neubauer, Hanin Binder, and Ulrike Lohmann
Atmos. Chem. Phys., 25, 7227–7243, https://doi.org/10.5194/acp-25-7227-2025, https://doi.org/10.5194/acp-25-7227-2025, 2025
Short summary
Short summary
This work uncovers the formation regimes of cirrus clouds and how dust particles influence their properties. By applying machine learning to a combination of satellite and reanalysis data, cirrus clouds are classified into different formation regimes. Depending on the regime, increasing dust aerosol concentrations can either decrease or increase the number of ice crystals. This challenges the idea of using cloud seeding to cool the planet, as it may unintentionally lead to warming instead.
Christopher Fuchs, Fabiola Ramelli, David Schweizer, Ulrike Lohmann, and Jan Henneberger
Atmos. Meas. Tech., 18, 2969–2986, https://doi.org/10.5194/amt-18-2969-2025, https://doi.org/10.5194/amt-18-2969-2025, 2025
Short summary
Short summary
We present a new instrument based on digital in-line holography (SmHOLIMO) for in situ cloud measurements. SmHOLIMO is designed to specifically measure small cloud droplets with diameters > 3.7 μm. This way we retrieve accurate cloud droplet size distributions, which are crucial to understand the evolution and governing microphysical processes of a cloud. Results of a field study are compared to co-located measurements of a second holographic imager, microwave radiometer, and cloud radar.
Guangyu Li, André Welti, Iris Thurnherr, Ulrike Lohmann, and Zamin A. Kanji
EGUsphere, https://doi.org/10.5194/egusphere-2025-2798, https://doi.org/10.5194/egusphere-2025-2798, 2025
Short summary
Short summary
This study presents ship-based measurements of summertime ice-nucleating particles (INPs) over the data-scarce Eurasian-Arctic Seas. We found that INPs are driven by both local and regional sources, with the highest levels observed near land and over ice-free waters. This study is highlighted for improving the understanding of INP abundance, sources, and their role in cloud processes in the rapidly warming Arctic.
Anna J. Miller, Christopher Fuchs, Fabiola Ramelli, Huiying Zhang, Nadja Omanovic, Robert Spirig, Claudia Marcolli, Zamin A. Kanji, Ulrike Lohmann, and Jan Henneberger
Atmos. Chem. Phys., 25, 5387–5407, https://doi.org/10.5194/acp-25-5387-2025, https://doi.org/10.5194/acp-25-5387-2025, 2025
Short summary
Short summary
We analyzed the ability of silver iodide particles (a commonly used cloud-seeding agent) to form ice crystals in naturally occurring liquid clouds at −5 to −8 °C and found that only ≈ 0.1 %−1 % of particles nucleate ice, with a negative dependence on temperature. By contextualizing our results with previous laboratory studies, we help to bridge the gap between laboratory and field experiments, which also helps to inform future cloud-seeding projects.
Judith Kleinheins, Nadia Shardt, Ulrike Lohmann, and Claudia Marcolli
Atmos. Chem. Phys., 25, 881–903, https://doi.org/10.5194/acp-25-881-2025, https://doi.org/10.5194/acp-25-881-2025, 2025
Short summary
Short summary
We model the cloud condensation nuclei (CCN) activation of sea spray aerosol particles with classical Köhler theory and with a new model approach that takes surface tension lowering into account. We categorize organic compounds into weak, intermediate, and strong surfactants, and we outline for which composition surface tension lowering is important. The results suggest that surface tension lowering allows sea spray aerosol particles in the Aitken mode to be a source of CCN in marine updraughts.
Nadja Omanovic, Brigitta Goger, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 14145–14175, https://doi.org/10.5194/acp-24-14145-2024, https://doi.org/10.5194/acp-24-14145-2024, 2024
Short summary
Short summary
We evaluated the numerical weather model ICON in two horizontal resolutions with two bulk microphysics schemes over hilly and complex terrain in Switzerland and Austria, respectively. We focused on the model's ability to simulate mid-level clouds in summer and winter. By combining observational data from two different field campaigns, we show that an increase in the horizontal resolution and a more advanced cloud microphysics scheme is strongly beneficial for cloud representation.
Emilie Fons, Ann Kristin Naumann, David Neubauer, Theresa Lang, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 8653–8675, https://doi.org/10.5194/acp-24-8653-2024, https://doi.org/10.5194/acp-24-8653-2024, 2024
Short summary
Short summary
Aerosols can modify the liquid water path (LWP) of stratocumulus and, thus, their radiative effect. We compare storm-resolving model and satellite data that disagree on the sign of LWP adjustments and diagnose this discrepancy with causal inference. We find that strong precipitation, the absence of wet scavenging, and cloud deepening under a weak inversion contribute to positive LWP adjustments to aerosols in the model, despite weak negative effects from cloud-top entrainment enhancement.
Nadja Omanovic, Sylvaine Ferrachat, Christopher Fuchs, Jan Henneberger, Anna J. Miller, Kevin Ohneiser, Fabiola Ramelli, Patric Seifert, Robert Spirig, Huiying Zhang, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 6825–6844, https://doi.org/10.5194/acp-24-6825-2024, https://doi.org/10.5194/acp-24-6825-2024, 2024
Short summary
Short summary
We present simulations with a high-resolution numerical weather prediction model to study the growth of ice crystals in low clouds following glaciogenic seeding. We show that the simulated ice crystals grow slower than observed and do not consume as many cloud droplets as measured in the field. This may have implications for forecasting precipitation, as the ice phase is crucial for precipitation at middle and high latitudes.
Ulrike Proske, Sylvaine Ferrachat, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 5907–5933, https://doi.org/10.5194/acp-24-5907-2024, https://doi.org/10.5194/acp-24-5907-2024, 2024
Short summary
Short summary
Climate models include treatment of aerosol particles because these influence clouds and radiation. Over time their representation has grown increasingly detailed. This complexity may hinder our understanding of model behaviour. Thus here we simplify the aerosol representation of our climate model by prescribing mean concentrations, which saves run time and helps to discover unexpected model behaviour. We conclude that simplifications provide a new perspective for model study and development.
Zane Dedekind, Ulrike Proske, Sylvaine Ferrachat, Ulrike Lohmann, and David Neubauer
Atmos. Chem. Phys., 24, 5389–5404, https://doi.org/10.5194/acp-24-5389-2024, https://doi.org/10.5194/acp-24-5389-2024, 2024
Short summary
Short summary
Ice particles precipitating into lower clouds from an upper cloud, the seeder–feeder process, can enhance precipitation. A numerical modeling study conducted in the Swiss Alps found that 48 % of observed clouds were overlapping, with the seeder–feeder process occurring in 10 % of these clouds. Inhibiting the seeder–feeder process reduced the surface precipitation and ice particle growth rates, which were further reduced when additional ice multiplication processes were included in the model.
Anna J. Miller, Fabiola Ramelli, Christopher Fuchs, Nadja Omanovic, Robert Spirig, Huiying Zhang, Ulrike Lohmann, Zamin A. Kanji, and Jan Henneberger
Atmos. Meas. Tech., 17, 601–625, https://doi.org/10.5194/amt-17-601-2024, https://doi.org/10.5194/amt-17-601-2024, 2024
Short summary
Short summary
We present a method for aerosol and cloud research using two uncrewed aerial vehicles (UAVs). The UAVs have a propeller heating mechanism that allows flights in icing conditions, which has so far been a limitation for cloud research with UAVs. One UAV burns seeding flares, producing a plume of particles that causes ice formation in supercooled clouds. The second UAV measures aerosol size distributions and is used for measuring the seeding plume or for characterizing the boundary layer.
Guangyu Li, Elise K. Wilbourn, Zezhen Cheng, Jörg Wieder, Allison Fagerson, Jan Henneberger, Ghislain Motos, Rita Traversi, Sarah D. Brooks, Mauro Mazzola, Swarup China, Athanasios Nenes, Ulrike Lohmann, Naruki Hiranuma, and Zamin A. Kanji
Atmos. Chem. Phys., 23, 10489–10516, https://doi.org/10.5194/acp-23-10489-2023, https://doi.org/10.5194/acp-23-10489-2023, 2023
Short summary
Short summary
In this work, we present results from an Arctic field campaign (NASCENT) in Ny-Ålesund, Svalbard, on the abundance, variability, physicochemical properties, and potential sources of ice-nucleating particles (INPs) relevant for mixed-phase cloud formation. This work improves the data coverage of Arctic INPs and aerosol properties, allowing for the validation of models predicting cloud microphysical and radiative properties of mixed-phase clouds in the rapidly warming Arctic.
Bernhard M. Enz, Jan P. Engelmann, and Ulrike Lohmann
Geosci. Model Dev., 16, 5093–5112, https://doi.org/10.5194/gmd-16-5093-2023, https://doi.org/10.5194/gmd-16-5093-2023, 2023
Short summary
Short summary
An algorithm to track tropical cyclones in model simulation data has been developed. The algorithm uses many combinations of varying parameter thresholds to detect weaker phases of tropical cyclones while still being resilient to false positives. It is shown that the algorithm performs well and adequately represents the tropical cyclone activity of the underlying simulation data. The impact of false positives on overall tropical cyclone activity is shown to be insignificant.
Colin Tully, David Neubauer, Diego Villanueva, and Ulrike Lohmann
Atmos. Chem. Phys., 23, 7673–7698, https://doi.org/10.5194/acp-23-7673-2023, https://doi.org/10.5194/acp-23-7673-2023, 2023
Short summary
Short summary
This study details the first attempt with a GCM to simulate a fully prognostic aerosol species specifically for cirrus climate intervention. The new approach is in line with the real-world delivery mechanism via aircraft. However, to achieve an appreciable signal from seeding, smaller particles were needed, and their mass emissions needed to be scaled by at least a factor of 100. These biases contributed to either overseeding or small and insignificant effects in response to seeding cirrus.
Colin Tully, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 16, 2957–2973, https://doi.org/10.5194/gmd-16-2957-2023, https://doi.org/10.5194/gmd-16-2957-2023, 2023
Short summary
Short summary
A new method to simulate deterministic ice nucleation processes based on the differential activated fraction was evaluated against a cumulative approach. Box model simulations of heterogeneous-only ice nucleation within cirrus suggest that the latter approach likely underpredicts the ice crystal number concentration. Longer simulations with a GCM show that choosing between these two approaches impacts ice nucleation competition within cirrus but leads to small and insignificant climate effects.
Zane Dedekind, Jacopo Grazioli, Philip H. Austin, and Ulrike Lohmann
Atmos. Chem. Phys., 23, 2345–2364, https://doi.org/10.5194/acp-23-2345-2023, https://doi.org/10.5194/acp-23-2345-2023, 2023
Short summary
Short summary
Simulations allowing ice particles to collide with one another producing more ice particles represented surface observations of ice particles accurately. An increase in ice particles formed through collisions was related to sharp changes in the wind direction and speed with height. Changes in wind speed and direction can therefore cause more enhanced collisions between ice particles and alter how fast and how much precipitation forms. Simulations were conducted with the atmospheric model COSMO.
Julie Thérèse Pasquier, Jan Henneberger, Fabiola Ramelli, Annika Lauber, Robert Oscar David, Jörg Wieder, Tim Carlsen, Rosa Gierens, Marion Maturilli, and Ulrike Lohmann
Atmos. Chem. Phys., 22, 15579–15601, https://doi.org/10.5194/acp-22-15579-2022, https://doi.org/10.5194/acp-22-15579-2022, 2022
Short summary
Short summary
It is important to understand how ice crystals and cloud droplets form in clouds, as their concentrations and sizes determine the exact radiative properties of the clouds. Normally, ice crystals form from aerosols, but we found evidence for the formation of additional ice crystals from the original ones over a large temperature range within Arctic clouds. In particular, additional ice crystals were formed during collisions of several ice crystals or during the freezing of large cloud droplets.
Florin N. Isenrich, Nadia Shardt, Michael Rösch, Julia Nette, Stavros Stavrakis, Claudia Marcolli, Zamin A. Kanji, Andrew J. deMello, and Ulrike Lohmann
Atmos. Meas. Tech., 15, 5367–5381, https://doi.org/10.5194/amt-15-5367-2022, https://doi.org/10.5194/amt-15-5367-2022, 2022
Short summary
Short summary
Ice nucleation in the atmosphere influences cloud properties and lifetimes. Microfluidic instruments have recently been used to investigate ice nucleation, but these instruments are typically made out of a polymer that contributes to droplet instability over extended timescales and relatively high temperature uncertainty. To address these drawbacks, we develop and validate a new microfluidic instrument that uses fluoropolymer tubing to extend droplet stability and improve temperature accuracy.
Colin Tully, David Neubauer, Nadja Omanovic, and Ulrike Lohmann
Atmos. Chem. Phys., 22, 11455–11484, https://doi.org/10.5194/acp-22-11455-2022, https://doi.org/10.5194/acp-22-11455-2022, 2022
Short summary
Short summary
The proposed geoengineering method, cirrus cloud thinning, was evaluated using a more physically based microphysics scheme coupled to a more realistic approach for calculating ice cloud fractions in the ECHAM-HAM GCM. Sensitivity tests reveal that using the new ice cloud fraction approach and increasing the critical ice saturation ratio for ice nucleation on seeding particles reduces warming from overseeding. However, this geoengineering method is unlikely to be feasible on a global scale.
Jörg Wieder, Nikola Ihn, Claudia Mignani, Moritz Haarig, Johannes Bühl, Patric Seifert, Ronny Engelmann, Fabiola Ramelli, Zamin A. Kanji, Ulrike Lohmann, and Jan Henneberger
Atmos. Chem. Phys., 22, 9767–9797, https://doi.org/10.5194/acp-22-9767-2022, https://doi.org/10.5194/acp-22-9767-2022, 2022
Short summary
Short summary
Ice formation and its evolution in mixed-phase clouds are still uncertain. We evaluate the lidar retrieval of ice-nucleating particle concentration in dust-dominated and continental air masses over the Swiss Alps with in situ observations. A calibration factor to improve the retrieval from continental air masses is proposed. Ice multiplication factors are obtained with a new method utilizing remote sensing. Our results indicate that secondary ice production occurs at temperatures down to −30 °C.
Ulrike Proske, Sylvaine Ferrachat, David Neubauer, Martin Staab, and Ulrike Lohmann
Atmos. Chem. Phys., 22, 4737–4762, https://doi.org/10.5194/acp-22-4737-2022, https://doi.org/10.5194/acp-22-4737-2022, 2022
Short summary
Short summary
Cloud microphysical processes shape cloud properties and are therefore important to represent in climate models. Their parameterization has grown more complex, making the model results more difficult to interpret. Using sensitivity analysis we test how the global aerosol–climate model ECHAM-HAM reacts to changes to these parameterizations. The model is sensitive to the parameterization of ice crystal autoconversion but not to, e.g., self-collection, suggesting that it may be simplified.
Jörg Wieder, Claudia Mignani, Mario Schär, Lucie Roth, Michael Sprenger, Jan Henneberger, Ulrike Lohmann, Cyril Brunner, and Zamin A. Kanji
Atmos. Chem. Phys., 22, 3111–3130, https://doi.org/10.5194/acp-22-3111-2022, https://doi.org/10.5194/acp-22-3111-2022, 2022
Short summary
Short summary
We investigate the variation in ice-nucleating particles (INPs) relevant for primary ice formation in mixed-phased clouds over the Alps based on simultaneous in situ observations at a mountaintop and a nearby high valley (1060 m height difference). In most cases, advection from the surrounding lower regions was responsible for changes in INP concentration, causing a diurnal cycle at the mountaintop. Our study underlines the importance of the planetary boundary layer as an INP reserve.
Zane Dedekind, Annika Lauber, Sylvaine Ferrachat, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 15115–15134, https://doi.org/10.5194/acp-21-15115-2021, https://doi.org/10.5194/acp-21-15115-2021, 2021
Short summary
Short summary
The RACLETS campaign combined cloud and snow research to improve the understanding of precipitation formation in clouds. A numerical weather prediction model, COSMO, was used to assess the importance of ice crystal enhancement by ice–ice collisions for cloud properties. We found that the number of ice crystals increased by 1 to 3 orders of magnitude when ice–ice collisions were permitted to occur, reducing localized regions of high precipitation and, thereby, improving the model performance.
Paolo Pelucchi, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 14, 5413–5434, https://doi.org/10.5194/gmd-14-5413-2021, https://doi.org/10.5194/gmd-14-5413-2021, 2021
Short summary
Short summary
Stratocumulus are thin clouds whose cloud cover is underestimated in climate models partly due to overly low vertical resolution. We develop a scheme that locally refines the vertical grid based on a physical constraint for the cloud top. Global simulations show that the scheme, implemented only in the radiation routine, can increase stratocumulus cloud cover. However, this effect is poorly propagated to the simulated cloud cover. The scheme's limitations and possible ways forward are discussed.
Paraskevi Georgakaki, Aikaterini Bougiatioti, Jörg Wieder, Claudia Mignani, Fabiola Ramelli, Zamin A. Kanji, Jan Henneberger, Maxime Hervo, Alexis Berne, Ulrike Lohmann, and Athanasios Nenes
Atmos. Chem. Phys., 21, 10993–11012, https://doi.org/10.5194/acp-21-10993-2021, https://doi.org/10.5194/acp-21-10993-2021, 2021
Short summary
Short summary
Aerosol and cloud observations coupled with a droplet activation parameterization was used to investigate the aerosol–cloud droplet link in alpine mixed-phase clouds. Predicted droplet number, Nd, agrees with observations and never exceeds a characteristic “limiting droplet number”, Ndlim, which depends solely on σw. Nd becomes velocity limited when it is within 50 % of Ndlim. Identifying when dynamical changes control Nd variability is central for understanding aerosol–cloud interactions.
Cited articles
Baker, A. J., Vannière, B., and Vidale, P. L.: On the Realism of Tropical Cyclone Intensification in Global Storm-Resolving Climate Models, Geophys. Res. Lett., 51, https://doi.org/10.1029/2024GL109841, 2024. a, b, c
Bao, J.-W., Gopalakrishnan, S. G., Michelson, S. A., Marks, F. D., and Montgomery, M. T.: Impact of Physics Representations in the HWRFX on Simulated Hurricane Structure and Pressure–Wind Relationships, Mon. Weather Rev., 140, 3278–3299, https://doi.org/10.1175/MWR-D-11-00332.1, 2012. a, b, c
Bengtsson, L., Hodges, K. I., Esch, M., Keenlyside, N., Kornblueh, L., Luo, J.-J., and Yamagata, T.: How may tropical cyclones change in a warmer climate?, Tellus A, 59, 539–561, https://doi.org/10.1111/j.1600-0870.2007.00251.x, 2007. a, b, c
Bengtsson, L., Hodges, K. I., and Keenlyside, N.: Will Extratropical Storms Intensify in a Warmer Climate?, J. Climate, 22, 2276–2301, https://doi.org/10.1175/2008JCLI2678.1, 2009. a
Benjamini, Y. and Hochberg, Y.: Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing, J. Roy. Stat. Soc. B Met., 57, 289–300, https://doi.org/10.1111/j.2517-6161.1995.tb02031.x, 1995. a
Binder, H., Boettcher, M., Joos, H., and Wernli, H.: The Role of Warm Conveyor Belts for the Intensification of Extratropical Cyclones in Northern Hemisphere Winter, J. Atmos. Sci., 73, 3997–4020, https://doi.org/10.1175/JAS-D-15-0302.1, 2016. a
Caratsch, A., Ferrachat, S., and Lohmann, U.: Data for publication “Composite Sharpening by Vortex Symmetrization and Normalization of Tropical Cyclones”, version v2, Zenodo [data set], https://doi.org/10.5281/zenodo.20027435, 2026a. a
Caratsch, A., Ferrachat, S., and Lohmann, U.: Scripts for publication “Composite Sharpening by Vortex Symmetrization and Normalization of Tropical Cyclones”, version v2, Zenodo [code], https://doi.org/10.5281/zenodo.20027390, 2026b. a
Carstens, J. D., Didlake, A. C., and Zarzycki, C. M.: Tropical Cyclone Wind Shear-Relative Asymmetry in Reanalyses, J. Climate, 37, 5793–5816, https://doi.org/10.1175/JCLI-D-23-0628.1, 2024. a, b, c
Chan, K. T. F. and Chan, J. C. L.: Size and Strength of Tropical Cyclones as Inferred from QuikSCAT Data, Mon. Weather Rev., 140, 811–824, https://doi.org/10.1175/MWR-D-10-05062.1, 2012. a, b, c
Chan, K. T. F., Zhang, K., and Xu, L.: Tropical cyclone size asymmetry index and climatology, Clim. Dynam., 61, 5049–5064, https://doi.org/10.1007/s00382-023-06840-5, 2023. a, b, c
Chen, S. S., Price, J. F., Zhao, W., Donelan, M. A., and Walsh, E. J.: The CBLAST-Hurricane Program and the Next-Generation Fully Coupled Atmosphere–Wave–Ocean Models for Hurricane Research and Prediction, B. Am. Meteorol. Soc., 88, 311–318, https://doi.org/10.1175/BAMS-88-3-311, 2007. a, b, c
Choudhury, G. and Tesche, M.: A first global height-resolved cloud condensation nuclei data set derived from spaceborne lidar measurements, Earth Syst. Sci. Data, 15, 3747–3760, https://doi.org/10.5194/essd-15-3747-2023, 2023. a
Dacre, H. F., Hawcroft, M. K., Stringer, M. A., and Hodges, K. I.: An Extratropical Cyclone Atlas: A Tool for Illustrating Cyclone Structure and Evolution Characteristics, B. Am. Meteorol. Soc., 93, 1497–1502, https://doi.org/10.1175/BAMS-D-11-00164.1, 2012. a
Davis, C. A.: Resolving Tropical Cyclone Intensity in Models, Geophys. Res. Lett., 45, 2082–2087, https://doi.org/10.1002/2017GL076966, 2018. a
Emanuel, K. A.: The power of a hurricane: An example of reckless driving on the information superhighway, Weather, 54, 107–108, https://doi.org/10.1002/j.1477-8696.1999.tb06435.x, 1999. a
Enz, B., Engelmann, J., and Ferrachat, S.: Tropical cyclone tracking method from numerical weather prediction and climate model ICON, Zenodo [data set], https://doi.org/10.5281/zenodo.19821081, 2026. a
Fischer, E. M., Beyerle, U., Bloin-Wibe, L., Gessner, C., Humphrey, V., Lehner, F., Pendergrass, A. G., Sippel, S., Zeder, J., and Knutti, R.: Storylines for unprecedented heatwaves based on ensemble boosting, Nat. Commun., 14, 4643, https://doi.org/10.1038/s41467-023-40112-4, 2023. a
Hanley, D., Molinari, J., and Keyser, D.: A Composite Study of the Interactions between Tropical Cyclones and Upper-Tropospheric Troughs, Mon. Weather Rev., 129, 2570–2584, https://doi.org/10.1175/1520-0493(2001)129<2570:ACSOTI>2.0.CO;2, 2001. a, b
Hogan, R. J. and Bozzo, A.: A Flexible and Efficient Radiation Scheme for the ECMWF Model, J. Adv. Model. Earth Sy., 10, 1990–2008, https://doi.org/10.1029/2018MS001364, 2018. a
Hohenegger, C., Kornblueh, L., Klocke, D., Becker, T., Cioni, G., Engels, J. F., Schulzweida, U., and Stevens, B.: Climate Statistics in Global Simulations of the Atmosphere, from 80 to 2.5 km Grid Spacing, J. Meteorol. Soc. Jpn. Ser. II, 98, 73–91, https://doi.org/10.2151/jmsj.2020-005, 2020. a
Hohenegger, C., Korn, P., Linardakis, L., Redler, R., Schnur, R., Adamidis, P., Bao, J., Bastin, S., Behravesh, M., Bergemann, M., Biercamp, J., Bockelmann, H., Brokopf, R., Brüggemann, N., Casaroli, L., Chegini, F., Datseris, G., Esch, M., George, G., Giorgetta, M., Gutjahr, O., Haak, H., Hanke, M., Ilyina, T., Jahns, T., Jungclaus, J., Kern, M., Klocke, D., Kluft, L., Kölling, T., Kornblueh, L., Kosukhin, S., Kroll, C., Lee, J., Mauritsen, T., Mehlmann, C., Mieslinger, T., Naumann, A. K., Paccini, L., Peinado, A., Praturi, D. S., Putrasahan, D., Rast, S., Riddick, T., Roeber, N., Schmidt, H., Schulzweida, U., Schütte, F., Segura, H., Shevchenko, R., Singh, V., Specht, M., Stephan, C. C., von Storch, J.-S., Vogel, R., Wengel, C., Winkler, M., Ziemen, F., Marotzke, J., and Stevens, B.: ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales, Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, 2023. a
Judt, F., Klocke, D., Rios-Berrios, R., Vanniere, B., Ziemen, F., Auger, L., Biercamp, J., Bretherton, C., Chen, X., Düben, P., Hohenegger, C., Khairoutdinov, M., Kodama, C., Kornblueh, L., Lin, S.-J., Nakano, M., Neumann, P., Putman, W., Röber, N., Roberts, M., Satoh, M., Shibuya, R., Stevens, B., Vidale, P. L., Wedi, N., and Zhou, L.: Tropical Cyclones in Global Storm-Resolving Models, J. Meteorol. Soc. Jpn. Ser. II, 99, 579–602, https://doi.org/10.2151/jmsj.2021-029, 2021. a, b, c, d, e, f, g, h, i
Klotz, B. W. and Jiang, H.: Examination of Surface Wind Asymmetries in Tropical Cyclones. Part I: General Structure and Wind Shear Impacts, Mon. Weather Rev., 145, 3989–4009, https://doi.org/10.1175/MWR-D-17-0019.1, 2017. a, b, c, d
Klotzbach, P. J., Bell, M. M., Bowen, S. G., Gibney, E. J., Knapp, K. R., and Schreck, C. J.: Surface Pressure a More Skillful Predictor of Normalized Hurricane Damage than Maximum Sustained Wind, B. Am. Meteorol. Soc., 101, E830–E846, https://doi.org/10.1175/BAMS-D-19-0062.1, 2020. a, b
Knutson, T. R., Sirutis, J. J., Zhao, M., Tuleya, R. E., Bender, M., Vecchi, G. A., Villarini, G., and Chavas, D.: Global Projections of Intense Tropical Cyclone Activity for the Late Twenty-First Century from Dynamical Downscaling of CMIP5/RCP4.5 Scenarios, J. Climate, 28, 7203–7224, https://doi.org/10.1175/JCLI-D-15-0129.1, 2015. a, b, c
Krzywinski, M. and Altman, N.: Analysis of variance and blocking, Nat. Meth., 11, 699–700, https://doi.org/10.1038/nmeth.3005, 2014. a
Landsea, C. W. and Franklin, J. L.: Atlantic Hurricane Database Uncertainty and Presentation of a New Database Format, Monthly Weather Review, 141, 3576–3592, https://doi.org/10.1175/MWR-D-12-00254.1, 2013. a, b, c
Li, H. and Tang, X.: Outer-core size asymmetry and intensification of North Atlantic tropical cyclones, Atmos. Res., 322, 108131, https://doi.org/10.1016/j.atmosres.2025.108131, 2025. a, b, c, d
Lin, Y., Wang, Y., Hsieh, J.-S., Jiang, J. H., Su, Q., Zhao, L., Lavallee, M., and Zhang, R.: Assessing the destructiveness of tropical cyclones induced by anthropogenic aerosols in an atmosphere–ocean coupled framework, Atmos. Chem. Phys., 23, 13835–13852, https://doi.org/10.5194/acp-23-13835-2023, 2023. a
Manganello, J. V., Hodges, K. I., Kinter, J. L., Cash, B. A., Marx, L., Jung, T., Achuthavarier, D., Adams, J. M., Altshuler, E. L., Huang, B., Jin, E. K., Stan, C., Towers, P., and Wedi, N.: Tropical Cyclone Climatology in a 10-km Global Atmospheric GCM: Toward Weather-Resolving Climate Modeling, J. Climate, 25, 3867–3893, https://doi.org/10.1175/JCLI-D-11-00346.1, 2012. a, b, c, d, e, f
Martinez, J., Davis, C. A., and Bell, M. M.: Eyewall Asymmetries and Their Contributions to the Intensification of an Idealized Tropical Cyclone Translating in Uniform Flow, J. Atmos. Sci., 79, 2471–2491, https://doi.org/10.1175/JAS-D-21-0302.1, 2022. a, b, c
Ming, J., Zhang, J., and Rogers, R.: Typhoon kinematic and thermodynamic boundary layer structure from dropsonde composites: Typhoon BL structure from dropsonde, J. Geophys. Res.-Atmos., 120, https://doi.org/10.1002/2014JD022640, 2015. a, b
Ohno, T. and Satoh, M.: On the Warm Core of a Tropical Cyclone Formed near the Tropopause, J. Atmos. Sci., 72, 551–571, https://doi.org/10.1175/JAS-D-14-0078.1, 2015. a
Ohno, T., Satoh, M., and Yamada, Y.: Warm Cores, Eyewall Slopes, and Intensities of Tropical Cyclones Simulated by a 7-km-Mesh Global Nonhydrostatic Model, J. Atmos. Sci., 73, 4289–4309, https://doi.org/10.1175/JAS-D-15-0318.1, 2016. a, b
Persing, J., Montgomery, M. T., McWilliams, J. C., and Smith, R. K.: Asymmetric and axisymmetric dynamics of tropical cyclones, Atmos. Chem. Phys., 13, 12299–12341, https://doi.org/10.5194/acp-13-12299-2013, 2013. a, b, c
Raschendorfer, M.: The new turbulence parameterization of LM, COSMO Newsletter, No. 1, http://www.cosmo-model.org/content/model/documentation/newsLetters/newsLetter01/newsLetter_01.pdf (last access: 24 May 2026), 2001. a
Reed, K. A., Bacmeister, J. T., Rosenbloom, N. A., Wehner, M. F., Bates, S. C., Lauritzen, P. H., Truesdale, J. E., and Hannay, C.: Impact of the dynamical core on the direct simulation of tropical cyclones in a high-resolution global model, Geophys. Res. Lett., 42, 3603–3608, https://doi.org/10.1002/2015GL063974, 2015. a, b, c
Rios-Berrios, R. and Torn, R. D.: Climatological Analysis of Tropical Cyclone Intensity Changes under Moderate Vertical Wind Shear, Mon. Weather Rev., 145, 1717–1738, https://doi.org/10.1175/MWR-D-16-0350.1, 2017. a
Rios-Berrios, R., Finocchio, P. M., Alland, J. J., Chen, X., Fischer, M. S., Stevenson, S. N., and Tao, D.: A Review of the Interactions between Tropical Cyclones and Environmental Vertical Wind Shear, J. Atmos. Sci., 81, 713–741, https://doi.org/10.1175/JAS-D-23-0022.1, 2024. a
Rosenfeld, D., Woodley, W. L., Khain, A., Cotton, W. R., Carrió, G., Ginis, I., and Golden, J. H.: Aerosol Effects on Microstructure and Intensity of Tropical Cyclones, B. Am. Meteorol. Soc., 93, 987–1001, https://doi.org/10.1175/BAMS-D-11-00147.1, 2012. a
Ryglicki, D. R. and Hart, R. E.: An Investigation of Center-Finding Techniques for Tropical Cyclones in Mesoscale Models, J. Appl. Meteorol. Clim., 54, 825–846, https://doi.org/10.1175/JAMC-D-14-0106.1, 2015. a
Sanabia, E. R., Barrett, B. S., and Fine, C. M.: Relationships between Tropical Cyclone Intensity and Eyewall Structure as Determined by Radial Profiles of Inner-Core Infrared Brightness Temperature, Mon. Weather Rev., 142, 4581–4599, https://doi.org/10.1175/MWR-D-13-00336.1, 2014. a, b
Schemm, S., Sprenger, M., and Wernli, H.: When during Their Life Cycle Are Extratropical Cyclones Attended by Fronts?, B. Am. Meteorol. Soc., 99, 149–165, https://doi.org/10.1175/BAMS-D-16-0261.1, 2018. a
Schulz, J.-P., Vogel, G., Becker, C., Kothe, S., Rummel, U., and Ahrens, B.: Evaluation of the ground heat flux simulated by a multi-layer land surface scheme using high-quality observations at grass land and bare soil, Meteorol. Z., 607–620, https://doi.org/10.1127/metz/2016/0537, 2016. a
Segal, Y. and Khain, A.: Dependence of droplet concentration on aerosol conditions in different cloud types: Application to droplet concentration parameterization of aerosol conditions, J. Geophys. Res.-Atmos., 111, https://doi.org/10.1029/2005JD006561, 2006. a
Segura, H., Pedruzo-Bagazgoitia, X., Weiss, P., Müller, S. K., Rackow, T., Lee, J., Dolores-Tesillos, E., Benedict, I., Aengenheyster, M., Aguridan, R., Arduini, G., Baker, A. J., Bao, J., Bastin, S., Baulenas, E., Becker, T., Beyer, S., Bockelmann, H., Brüggemann, N., Brunner, L., Cheedela, S. K., Das, S., Denissen, J., Dragaud, I., Dziekan, P., Ekblom, M., Engels, J. F., Esch, M., Forbes, R., Frauen, C., Freischem, L., García-Maroto, D., Geier, P., Gierz, P., González-Cervera, Á., Grayson, K., Griffith, M., Gutjahr, O., Haak, H., Hadade, I., Haslehner, K., ul Hasson, S., Hegewald, J., Kluft, L., Koldunov, A., Koldunov, N., Kölling, T., Koseki, S., Kosukhin, S., Kousal, J., Kuma, P., Kumar, A. U., Li, R., Maury, N., Meindl, M., Milinski, S., Mogensen, K., Niraula, B., Nowak, J., Praturi, D. S., Proske, U., Putrasahan, D., Redler, R., Santuy, D., Sármány, D., Schnur, R., Scholz, P., Sidorenko, D., Spät, D., Sützl, B., Takasuka, D., Tompkins, A., Uribe, A., Valentini, M., Veerman, M., Voigt, A., Warnau, S., Wachsmann, F., Wacławczyk, M., Wedi, N., Wieners, K.-H., Wille, J., Winkler, M., Wu, Y., Ziemen, F., Zimmermann, J., Bender, F. A.-M., Bojovic, D., Bony, S., Bordoni, S., Brehmer, P., Dengler, M., Dutra, E., Faye, S., Fischer, E., van Heerwaarden, C., Hohenegger, C., Järvinen, H., Jochum, M., Jung, T., Jungclaus, J. H., Keenlyside, N. S., Klocke, D., Konow, H., Klose, M., Malinowski, S., Martius, O., Mauritsen, T., Mellado, J. P., Mieslinger, T., Mohino, E., Pawłowska, H., Peters-von Gehlen, K., Sarré, A., Sobhani, P., Stier, P., Tuppi, L., Vidale, P. L., Sandu, I., and Stevens, B.: nextGEMS: entering the era of kilometer-scale Earth system modeling, Geosci. Model Dev., 18, 7735–7761, https://doi.org/10.5194/gmd-18-7735-2025, 2025. a
Seifert, A. and Beheng, K. D.: A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 1: Model description, Meteorol. Atmos. Phys., 92, 45–66, https://doi.org/10.1007/s00703-005-0112-4, 2006. a
Sena, A. C. T., Patricola, C. M., Camargo, S. J., and Sobel, A. H.: The atmospheric effect of aerosols on future tropical cyclone frequency and precipitation in the Energy Exascale Earth System Model, Clim. Dynam., https://doi.org/10.1007/s00382-024-07359-z, 2024. a, b
Shea, D. J. and Gray, W. M.: The Hurricane's Inner Core Region. I. Symmetric and Asymmetric Structure, J. Atmos. Sci., 30, 1544–1564, https://doi.org/10.1175/1520-0469(1973)030<1544:THICRI>2.0.CO;2, 1973. a, b
Smith, R. K. and Montgomery, M. T.: Chapter 6 – Frictional effects, in: Tropical Cyclones, edited by: Smith, R. K. and Montgomery, M. T., Vol. 4 of Developments in Weather and Climate Science, 137–162, Elsevier, ISBN 978-0-443-13449-4, https://doi.org/10.1016/B978-0-44-313449-4.00014-X, 2023. a
Stern, D. P., Vigh, J. L., Nolan, D. S., and Zhang, F.: Revisiting the Relationship between Eyewall Contraction and Intensification, J. Atmos. Sci., 72, 1283–1306, https://doi.org/10.1175/JAS-D-14-0261.1, 2015. a, b, c
Sun, Z., Zhang, B., Zhang, J. A., and Perrie, W.: Examination of Surface Wind Asymmetry in Tropical Cyclones over the Northwest Pacific Ocean Using SMAP Observations, Remote Sensing, 11, 2604, https://doi.org/10.3390/rs11222604, 2019. a, b
Trier, S. B., Ahijevych, D. A., Carroll-Smith, D., Bryan, G. H., and Edwards, R.: Composite Mesoscale Environmental Conditions Influencing Tornado Frequencies in Landfalling Tropical Cyclones, Weather Forecast., 38, 2481–2508, https://doi.org/10.1175/WAF-D-22-0227.1, 2023. a, b
Uhlhorn, E. W., Klotz, B. W., Vukicevic, T., Reasor, P. D., and Rogers, R. F.: Observed Hurricane Wind Speed Asymmetries and Relationships to Motion and Environmental Shear, Mon. Weather Rev., 142, 1290–1311, https://doi.org/10.1175/MWR-D-13-00249.1, 2014. a, b
Ventura, V., Paciorek, C. J., and Risbey, J. S.: Controlling the Proportion of Falsely Rejected Hypotheses when Conducting Multiple Tests with Climatological Data, J. Climate, 17, 4343–4356, https://doi.org/10.1175/3199.1, 2004. a
Vessey, A. F., Hodges, K. I., Shaffrey, L. C., and Day, J. J.: The composite development and structure of intense synoptic-scale Arctic cyclones, Weather Climate Dynam., 3, 1097–1112, https://doi.org/10.5194/wcd-3-1097-2022, 2022. a, b
Wang, Y., Lee, K.-H., Lin, Y., Levy, M., and Zhang, R.: Distinct effects of anthropogenic aerosols on tropical cyclones, Nat. Clim. Change, 4, 368–373, https://doi.org/10.1038/nclimate2144, 2014. a
Wei, C., Zhao, X., Liu, Y., Yang, P., Zhou, Z., and Chen, Y.: Bias Analysis and Correction of ERA5 Reanalysis in the Context of Tropical Cyclones, J. Geophys. Res.-Atmos., 130, e2024JD042737, https://doi.org/10.1029/2024JD042737, 2025. a, b
Weiss, P., Herbert, R., and Stier, P.: ICON-HAM-lite 1.0: simulating the Earth system with interactive aerosols at kilometer scales, Geosci. Model Dev., 18, 3877–3894, https://doi.org/10.5194/gmd-18-3877-2025, 2025. a
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, Academic Press, ISBN 978-0-12-385023-2, 2011. a
Yu, C.-K., Lin, C.-Y., and Pun, C.-H.: Origin of outer tropical cyclone rainbands, Nat. Commun., 14, 7061, https://doi.org/10.1038/s41467-023-42896-x, 2023. a
Zhang, F. and Tao, D.: Effects of Vertical Wind Shear on the Predictability of Tropical Cyclones, J. Atmos. Sci., 70, 975–983, https://doi.org/10.1175/JAS-D-12-0133.1, 2013. a
Zhang, J. A., Rogers, R. F., Reasor, P. D., Uhlhorn, E. W., and Marks, F. D.: Asymmetric Hurricane Boundary Layer Structure from Dropsonde Composites in Relation to the Environmental Vertical Wind Shear, Mon. Weather Rev., 141, 3968–3984, https://doi.org/10.1175/MWR-D-12-00335.1, 2013. a, b
Zhang, W., Villarini, G., Scoccimarro, E., Roberts, M., Vidale, P. L., Vanniere, B., Caron, L.-P., Putrasahan, D., Roberts, C., Senan, R., and Moine, M.-P.: Tropical cyclone precipitation in the HighResMIP atmosphere-only experiments of the PRIMAVERA Project, Clim. Dynam., 57, 253–273, https://doi.org/10.1007/s00382-021-05707-x, 2021. a, b
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core, Q. J. Roy. Meteorol. Soc., 141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a
Short summary
Tropical cyclones come in various size and shape, which smoothes out key storm features in composite analyses. To address this, we developed a compositing method that symmetrizes storms and better aligns their eyewalls and horizontal extents prior to compositing. This approach preserves mesoscale features in the composites, reduces within-group variance, and enhances the power of statistical testing. The method facilitates the investigation and understanding of tropical cyclone development.
Tropical cyclones come in various size and shape, which smoothes out key storm features in...
