This session aims to advance our comprehension of cold clouds by bringing observation- and modelling-based research together.
A diversity of research topics shall be covered, highlighting recent advances in cloud observation techniques, modelling, and subsequent process studies:
(1) Airborne, space borne, ground- or laboratory-based measurements and their derived products (retrievals), which are useful to constrain cloud properties like extent, emissivity, or crystal size distributions, to clarify formation mechanisms, and to provide climatology.
(2) Process-based, regional, and global model simulations that employ observations for better representation of cloud microphysical properties and radiative forcing under both current and future climate.
The synthesis of these approaches can uniquely answer questions regarding dynamical influence on cloud formation, life cycle, coverage, microphysical and radiative properties, crystal shapes, sizes, and variability of ice particles in mixed-phase as well as ice clouds. Joint observation-modelling contributions are therefore particularly encouraged.
Orals: Tue, 5 May, 16:15–08:30 | Room F2
Contrail-cirrus is considered the most important component of aviation-induced climate impact. However, a reliable assessment requires a better understanding of the environment in which they are formed, and the resulting radiative effects. One study has been recently published on the quantification of the radiative forcing of contrails embedded in cirrus clouds (Seelig et al., 2025) and found a contribution of around 10% of the current estimate of the climate impact of line-shaped contrails.
Our study (Petzold et al., 2025) focuses on the occurrence of long-lived contrail-cirrus with natural cirrus clouds. To this end, we investigated the distribution of relative humidity with respect to ice (RHice) – the key parameter controlling the lifetime of contrails - in clear sky as well as inside optically thin and thick cirrus clouds for the North Atlantic region and over subtropical Southeast Asia, with the focus on the occurrence of ice-supersaturated air masses and the potential of contrail formation.
The underlying data base builds on more than 7 years of continuous in-situ observations by the European research infrastructure IAGOS (www.iagos.org) which measures, among others, temperature, RHice and ice cloud particles, on instrumented passenger aircraft, and covers the period from June 2014 to December 2021. Information on cloud coverage and cloud thickness were taken from ERA5 global reanalysis by means of the cloud ice water content (CIWC). The separation of clear-sky and in-cloud flight sequences was achieved by applying a novel ERA5 CIWC based cloud index validated by IAGOS and research aircraft in-situ RHice observations as well as by process simulations.
The analysis shows that conditions promoting long-lived contrails are fulfilled most often in regions already covered by subvisible or visible cirrus: ~90% over the Northern midlatitudes and almost 100% in the Southeast Asian subtropics, approximately equally distributed among visible and subvisible cirrus clouds. A conceptual analysis shows that subvisible cirrus and clear-sky cover ~10% of the cruise altitude over Northern midlatitudes (< 2% in the subtropics) and contrails within these regions are expected to cause additional warming. However, most contrails in the thicker, visible cirrus, only slightly enhance the cirrus warming effect or possibly reverse it to cooling. Our results suggest that potential flight rerouting concepts for contrail avoidance need to consider cirrus cloud coverage in addition to ice- supersaturation, which is currently the primary criterion for rerouting.
References:
Petzold, A., Khan, N. F., Li, Y., Spichtinger, P., Rohs, S., Crewell, S., Wahner, A., and Krämer, M.: Most long-lived contrails form within cirrus clouds with uncertain climate impact, Nat Commun, 16, 9695, doi: 10.1038/s41467-025-65532-2, 2025.
Seelig, T., Wolf, K., Bellouin, N., and Tesche, M.: Quantification of the radiative forcing of contrails embedded in cirrus clouds, Nat Commun, 16, 10703, doi: 10.1038/s41467-025-66231-8, 2025.
How to cite: Petzold, A., Khan, N. F., Li, Y., Spichtinger, P., Rohs, S., Crewell, S., Wahner, A., and Krämer, M.: Long-lived contrails in cirrus clouds underestimated with uncertain climate impact, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3357, https://doi.org/10.5194/egusphere-egu26-3357, 2026.
Cirrus clouds exhibit varying radiative impacts depending on their origin of formation. For example, in situ origin cirrus clouds tend to have a warming effect, whereas liquid-origin cirrus clouds exhibit a rather cooling effect, though with large uncertainty. Understanding the global distribution of cirrus clouds, particularly with respect to their origin types is therefore essential for accurately assessing their radiative impacts. Consequently, analyzing their vertical and seasonal distributions is of key importance.
In this study, we use the refined cirrus origin index from the large-scale, Lagrangian model for the microphysical properties of cirrus clouds (CLaMS-Ice: Krämer et al., 2026; Gasparini et al., 2025), which extends the existing classification of in-situ and liquid origin cirrus by introducing a third origin type termed dual-origin cirrus. Dual-origin cirrus are initially of liquid origin, in which later in-situ ice nucleation occurs. They therefore bear the signature of both pure cirrus types. So far, this type is assigned to the liquid-origin cirrus. CLaMS-Ice was applied to seven years of passenger aircraft flight data from the European research infrastructure IAGOS. The relative variability of the three types of cirrus cloud is then investigated along the IAGOS flight routes using the new origin index of CLaMS-Ice.
The variability of the cirrus types is examined with respect to 30 hPa layers around and below the tropopause in the northern mid-latitudinal regions of North America, the North Atlantic, and Western Europe, including a seasonal analysis. The total frequency of cirrus clouds is found to be highest over the North Atlantic, with a high fractional density across the upper troposphere, particularly in layers closest to the tropopause. In situ origin cirrus clouds show the highest fractional occurrence near the tropopause across all seasons and represent the dominant category among all cirrus types, with their fraction gradually decreasing at higher pressure levels (lower altitudes). In addition to the two cirrus categories of in-situ and liquid origin, a substantial fraction of the data falls into the dual-origin category. The fraction of dual-origin cirrus clouds is observed to be higher than that of liquid-origin cirrus clouds. Our analysis reveals a significant contribution from this dual-origin cirrus class, highlighting the importance of distinguishing it when assessing cirrus cloud variability and their associated radiative impacts.
Gasparini, B., Atlas, R., Voigt, A., Krämer, M., and Blossey, P. N.: Tropical cirrus evolution in a kilometer-scale model with improved ice microphysics, Atmos. Chem. Phys., 25, 9957–9979, https://doi.org/10.5194/acp-25-9957-2025, 2025.
Krämer, M, J.-U. Grooß, P. Spichtinger, I. Bartolomé Garçia, and C. Rolf: Large-scale Lagrangian 3D cirrus modeling with ClaMS-Ice; in preparation for ACP.
How to cite: Khan, N. F., Petzold, A., Rohs, S., Garcia, I. B., Crewell, S., and Kraemer, M.: Cirrus cloud origin classification for seven years of IAGOS flights including a new origin category, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12544, https://doi.org/10.5194/egusphere-egu26-12544, 2026.
Cirrus clouds exert a strong control on Earth’s radiation budget, yet their shortwave radiative impact remains one of the largest sources of uncertainty in climate projections. A key quantity governing this impact is the asymmetry parameter (g), which describes the angular redistribution of scattered solar radiation and is highly sensitive to ice crystal morphology and surface structure. However, direct observational constraints on g in natural cirrus clouds remain scarce.
Here, we present simultaneous in situ measurements of ice particle morphology and angular light scattering obtained with the Particle Habit Imaging and Polar Scattering (PHIPS) probe during the CIRRUS-HL aircraft campaign in summer 2021. The dataset spans both mid-latitude and Arctic cirrus clouds over a wide range of cloud types and temperatures down to -63°C. Across all conditions, we find consistently low median asymmetry parameters, with a campaign-wide median of g = 0.738. The observed values show little sensitivity to temperature, relative humidity over ice, crystal habit, or aspect ratio, but exhibit a systematic decrease with increasing particle size. These values are substantially lower than those commonly assumed in current radiative transfer schemes, implying that the shortwave warming effect of cirrus clouds may be overestimated in many climate models.
Motivated by this discrepancy, we introduce an observationally constrained optical parameterisation for ice crystals aimed at improving their representation in climate models. The parameterisation is based on a new physical-optics hybrid approach that explicitly accounts for surface roughness using a physically motivated description, avoiding ad hoc treatments employed in earlier schemes. By fitting this model to the measured scattering properties, we derive an updated parameterisation of ice crystal optical properties suitable for climate applications. Together, these results provide both new observational constraints and a pathway toward more physically realistic representations of cirrus cloud optical properties, helping to reduce uncertainties in cloud radiative forcing.
How to cite: Järvinen, E., Schnaiter, F. M., and Ballington, H.: Observational constraints on the ice cloud asymmetry parameter and a new optical parameterisation for cirrus clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20046, https://doi.org/10.5194/egusphere-egu26-20046, 2026.
The concentration of ice nucleation particles (INP) in river waters surpasses the levels found in oceans and in the sea by orders of magnitude. Therefore, despite covering a small surface area, lakes and rivers could be a significant local source of INPs along river systems and also beyond when the INPs contained in river waters flow into the sea. Most aerosolisation mechanisms that occur in the sea (e.g., wave breaking and bubble bursting) also occur in flowing systems such as rivers or lakes. However, how efficiently INPs are aerosolized from rivers remains an open question, limiting the estimation of the impact of rivers as a source of INPs.
In this work, we present INP measurements from the urban section of the Vantaa river in Helsinki, Finland. We characterise the INP concentrations both in the water and in the adjacent air at an artificial weir next to the mouth of the river. Additionally, we study the aerosolisation mechanisms and examine how INP concentrations in the water change at the river mouth, where the river water mixes into the Baltic Sea.
This work was supported by the Research Council of Finland Flagship ACCC (grant 337552) and MEDICEN project (grants no. 336557 and 345125)
How to cite: Piedehierro, A. A., Vasenkari, V., Welti, A., and Laaksonen, A.: Significance of an urban river as a local source of ice nucleating particles, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5467, https://doi.org/10.5194/egusphere-egu26-5467, 2026.
Vertical profiling with ground-based lidars and radars offers excellent opportunities to monitor life cycles of mixed-phase clouds (MPCs) and cirrus fields in a coherent way over hours to days. In this presentation, we will discuss the new potential of modern lidar techniques in combination with cloud radar methods (a) to explore the evolution of MPCs, separately in terms of liquid- and ice-phase properties and (b) to study in detail the contribution of heterogenous ice nucleation to cirrus formation processes. The discussion is based on measurements performed in the framework of the MOSAiC expedition (life cycles of long-lasting Arctic MPCs), and intensive field studies at Dushanbe, Tajikistan (water and mixed-phase cloud evolution in aged dust and dust-haze mixtures in central Asia), at Leipzig, Germany (cirrus evolution in aged Canadian wildfire smoke), and in Cyprus and Punta Arenas, Chile (MPC evolution in the polluted Eastern Mediterranean vs the MPC evolution over the pristine Southern Ocean). Of central importance are closure studies in which retrieved cloud condensation nucleus concentrations (CCNC) and cloud droplet number concentrations (CDNC) as well as ice-nucleating particle concentrations (INPC) and ice crystal number concentrations (ICNC) are compared.
In the case of mixed-phase clouds, the CCNC and INPC information is derived from extinction and backscatter lidar observations in combination with the POLIPHON (Polarization Lidar Photometer Networking) method. Relevant INP types in the free troposphere are wildfire smoke particles and mineral dust. By means of the fluorescence and the polarization lidar techniques a clear identification of fluorescing smoke and non-fluorescing, but polarizing dust particles is possible. The recently introduced dual-field-of-view (dual-FOV) polarization lidar method allows continuous monitoring of CDNC at about 75 to 100 m above the base of liquid-dominated cloud layers, occurring for example at the top of stratiform MPC systems. ICNC information is provided in the ice virga region using the synergy of cloud radar reflectivity and lidar extinction measurements. As will be shown, we observed long lasting Arctic mixed-phase cloud decks with permanently occurring liquid-dominated cloud top layers with CDNC typically ranging from 50-300 cm-3 and the continuous production of ice crystals with ICNC of typically 0.1-1 per liter.
In the case of cirrus field studies, an important step forward was the integration of fluorescence lidar measurements into the combined lidar-radar observations. Now, we were able to clearly identify and quantify fluorescing wildfire smoke particles serving as INPs in the upper troposphere. Strong smoke plumes in the tropopause region fruwently occurred in 2023 and 2025. The smoke INPC can now be determined within the cirrus top layers in which ice nucleation takes place. We are able to answer the question whether a smoke INP reservoir in ice clouds can be depleted quickly during a cirrus life cycle or not and how important the smoke impact on heterogenous ice nucleation for cirrus formation is. The synergy of cloud radar and lidar observations again delivers ICNC information. The INPC-ICNC closure studies provided clear indications for a significant impact of smoke on cirrus formation over Leipzig, Germany.
How to cite: Ansmann, A., Gast, B., Jimenez, C., Hofer, J., Engelmann, R., Baars, H., Seifert, P., Radenz, M., Wandinger, U., and He, Y.: New ways of mixed-phase cloud and cirrus research by means of field studies with combined fluorescence, dual-FOV polarization lidar and cloud radar: CCNC-CDNC and INPC-ICNC closure studies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6196, https://doi.org/10.5194/egusphere-egu26-6196, 2026.
In-situ cloud measurement techniques, particularly those collected by airborne platforms, capture microphysical characteristics of mixed-phase clouds but are unable to directly measure ice formation mechanisms and particle growth histories. Addressing this observational gap, we demonstrate that in-situ measurement of stable water isotopes can be used to quantify ice growth processes more directly. By analyzing the isotopic composition of ice hydrometeors, we can identify their dominant growth pathway: direct vapor deposition, riming, or through Wegener-Bergeron (WBF) conditions.
Stable water isotopologues are water molecules which contain deuterium (D) or oxygen-18 (O18). They are present within water everywhere, and are termed “heavy” due to their larger molecular mass. The concentration of heavy water isotopes found in atmospheric ice particles is dependent on the thermodynamic conditions experienced during growth. Specifically, the in-situ temperature, relative humidity, and thermodynamic phase (liquid or ice) dictate the amount of heavy isotopes that enter the cloud condensate.
Water isotopes within mixed-phase clouds were measured in-situ during the CAESAR 2024 (Cold Air Outbreak Experiment in the Sub-Arctic Region) airborne field campaign. We first provide an overview of stable water isotopes and their dependence on environmental conditions. Then, we present the use of isotopic measurements to identify vapor deposition, riming, and WBF growth conditions inside mixed-phase clouds from CAESAR. A suite of in-situ cloud probes (PHIPS, HOLODEC, and Optical Array Probes) is used to validate the results of the isotopic analysis. This observational technique can be leveraged to study each ice growth mechanism’s influence on cloud properties.
How to cite: Rosky, E., Bailey, A., Sarkar, M., Bansemer, A., Woods, S., Sodemann, H., Seidl, A., Geerts, B., McFarquhar, G., and Zuidema, P.: Tracking ice growth pathways in mixed-phase Arctic clouds using stable water isotopes: Airborne in-situ measurements from CAESAR 2024., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16210, https://doi.org/10.5194/egusphere-egu26-16210, 2026.
Ice clouds play a crucial role in the Earth’s atmosphere system. They interact with both the incoming shortwave and outgoing longwave radiation and thus have a strong influence on the atmospheric radiation budget. Their net radiative effect is still not well-quantified and is highly sensitive to their macrophysical and microphysical characteristics. However, determining these properties remains a challenging task. As a consequence, ice clouds are frequently under- or misrepresented in weather and climate models, contributing substantially to uncertainties in climate research.
The Arctic climate system is undergoing rapid and complex changes, in connection to global warming. While various properties and processes are affected, most notably the Arctic troposphere is warming at an accelerated rate, compared to the global average. The term Arctic Amplification, has been introduced to describe the unique changes occurring in the Arctic. Ice clouds are expected to play an important role in Arctic Amplification, either directly by interacting with radiation or as part of new or altered feedback loops. Despite their potential significance, there is a scarcity of observations of their macro- and microphysical properties in the Arctic and a missing link between hose crucial properties and the ambient dynamical conditions.
The Arctic Study of Cloud, Circulation and Climate (ASCCI) campaign took place in the Arctic during the Spring of 2025. For this campaign the German research aircraft HALO was used. With its high flight ceiling and long range, HALO is perfectly suited for the study of remote ice clouds in the Arctic. On-board HALO was, among others, the WALES (Water Vapour Lidar Experiment in Space) lidar system. WALES is an airborne water vapor differential absorption (DIAL) and high spectral resolution (HSRL) lidar system. It provides 2D vertically resolved measurements along the flight track, of water vapor concentration, aerosol backscatter and linear depolarization ratio, as well as the two-way atmospheric transmission. These capabilities allow for a detailed characterization of ice clouds including their vertical structure.
In this study we use observations from WALES during ASCCI. In the generated dataset, first we identify and extract the ice clouds and then derive properties, including the Relative Humidity over ice (RHi) and optical depth. In addition, we use reanalysis data from ERA5, and more precisely the large-scale vertical velocity and static stability in order to characterize the dynamical environment in which the ice clouds were detected. The ice clouds are then grouped according to these environmental regimes, allowing us to investigate how their macro-, microphysical and optical properties vary with large-scale ascent or subsidence and atmospheric stability. Our aim is to improve our understanding of Arctic ice cloud characteristics and their sensitivity to state of the atmosphere. The results provide observational constraints important for the representation of ice clouds in weather and climate models and for reducing uncertainties regarding the role of ice clouds in the rapidly changing Arctic climate system.
How to cite: Dekoutsidis, G., Groß, S., and Wirth, M.: Linking Arctic ice cloud properties to atmospheric stability and vertical motion using lidar observations , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13333, https://doi.org/10.5194/egusphere-egu26-13333, 2026.
In the current climate, Arctic mixed-phase clouds (MPCs) have a warming effect on average. While the radiative impact of MPCs is driven by their liquid phase, the formation and growth of ice particles can alter their radiative properties. Ice crystal formation and growth processes in MPCs are still poorly understood, leading to large uncertainties in their representation in weather and climate models, and thus in their role in a rapidly warming Arctic. Contributions from secondary ice production (SIP)---ice formation without ice nucleating particles (INP)---are still poorly constrained.
In this study, we investigate the occurrence of SIP, riming, and aggregation in springtime Arctic MPCs. We use airborne data collected during the (AC)³ field campaigns AFLUX and HALO-(AC)³, conducted near Svalbard in 2019 and 2022, respectively. During both campaigns, in situ cloud probes covered a particle size range from 2.8 µm to 6.4 mm. We derive estimates of rime mass based on particle shape observations. A clustering approach is used to distinguish particle populations dominated by pristine crystals, aggregates, and rimed particles based on their particle size, number concentration, and rime mass. We investigate the relative occurrence of each class and its dependence on meteorological conditions. SIP events are identified through multimodal particle size distributions with high concentrations of small ice particles (50 µm < diameter < 100 µm). We analyze the occurrence of SIP in terms of meteorological conditions, cloud properties, and particle class (although direct causal links cannot be made based on airborne data alone). This will lead to a better understanding of ice formation and growth in Arctic MPCs and thus helps to improve future modeling efforts.
How to cite: Maherndl, N., Maahn, M., Moser, M., and Lucke, J.: Investigating Secondary Ice Production in Springtime Arctic Mixed-phase Clouds , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4848, https://doi.org/10.5194/egusphere-egu26-4848, 2026.
Observations from recent field campaigns investigating glaciogenic cloud seeding demonstrate the process of silver iodide (AgI) dispersion through ice nucleation, crystal growth, then enhanced snowfall at the surface. These observations, combined with numerical simulations, were used to quantify seeding’s impact on enhancing precipitation in targeted regions. With the microphysical chain of events established, fundamental knowledge gaps remain on the mechanisms by which seeding modifies the cloud dynamics, structure, and precipitation enhancement. This study presents the first direct observational evidence that glaciogenic seeding generates buoyant forces in wintertime orographic clouds that elevate cloud tops and secondary circulations that alter the cloud structure.
In this study, we analyze dynamic responses induced from seeding in the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) and CLOUDLAB field campaigns. The SNOWIE cases occurred in the Payette mountains in presence of widespread supercooled liquid conditions and low natural ice number concentrations. Ground-based X-band radars tracked the development and evolution of cloud and precipitation from five seeding legs. Distinct cells, directly attributable to airborne seeding, developed from smaller weaker echoes (10 dBZ) at the natural cloud top and rapidly intensified to produce precipitation with echoes >30 dBZ. The key observed processes were dynamic responses induced by the latent heat released from seeding that led to enhancing cloud top by 350 m compared to the natural cloud. An airborne W-band Dual-Doppler cross-section illustrates the detailed dynamic structure for one cell consisting of a central updraft, divergence near cloud top, and toroidal circulations along its periphery in an observed moist-neutral environment. In situ measurements show distinct microphysical regimes in the elevated cloud top, with seeding generated ice number concentrations up to 580 L-1. A WRF-WxMod ensemble shows the evolution of dynamic responses, the microphysical characteristics, and precipitation enhancement up to 200 km downwind of release.
We combine these results with preliminary observations from the 2025-2026 CLOUDLAB field campaign that further investigate the roles each step in a dynamic response has on seeded cloud microphysical properties. We show the evolution of seeded cloud from Ka-band cloud radars, combined with in-situ measurements from a holographic imager, to show dynamic response impact on microphysical structure and cloud properties.
How to cite: Hohman, C., French, J., Xue, L., Tessendorf, S., Friedrich, K., Chen, S., Geerts, B., Xie, Z., Rauber, R., Grasmic, C., and Hennenberger, J.: Observed and Simulated Dynamic Responses to Glaciogenic Seeding in Wintertime Mixed-Phase Clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7428, https://doi.org/10.5194/egusphere-egu26-7428, 2026.
Orals: Wed, 6 May, 08:30–12:30 | Room F2
Constraining frozen cloud particles remains a key challenge for improving global climate models. Current estimates of atmospheric ice mass have significant limitations. The spaceborne radar-lidar missions CloudSat-CALIPSO and EarthCARE offer high-quality data but with sparse sampling and limited mission duration. Passive satellite products provide better spatiotemporal coverage but have traditionally exhibited strong biases compared to CloudSat-based measurements. These observational gaps limit our ability to evaluate and validate simulations of ice clouds.
We present two complementary datasets to address this challenge: the Chalmers Cloud Ice Climatology (CCIC) and the Chalmers Hydrometeor Inversion Product from the Arctic Weather Satellite (CHIP-AWS). Both datasets provide a number of quantities; here we focus on vertically integrated atmospheric ice mass: frozen water path (FWP). They provide estimates with regular global coverage between ±60° latitude and are accompanied by per-retrieval uncertainty. Though both use neural networks, they have contrasting training approaches: CCIC employs empirical training on CloudSat-retrieved data, while CHIP-AWS uses physics-based radiative transfer simulations. For average values, both datasets agree with CloudSat-based retrievals.
CCIC provides quasi-global coverage of FWP estimates at high temporal resolution. The inputs are geostationary infrared images to a neural network model trained on 3.5 years of CloudSat-CALIPSO data. Once trained, the model can be applied to archived and future imagery. Two variants are available: a 0.07°/3-hour product spanning 1980-present and a higher resolution 0.036°/30-minute product spanning 2000-present. These 40+/20+ year climatologies enable analysis of both long-term trends and diurnal variations in ice cloud properties and have been applied to evaluate global storm-resolving models and identify regional trends.
CHIP-AWS uses novel sub-mm passive microwave radiances from the polar-orbiting Arctic Weather Satellite (launched 2024), providing more direct sensitivity to ice mass compared to previous passive instruments. The retrieval model is trained on a database of radiative transfer simulations that use defined particle models and scattering data. This approach allows assessment of the underlying microphysical assumptions. The dataset covers 2025 and onward with an 800 km swath and ~10 km nadir resolution. This provides high spatial coverage compared to a satellite cloud radar but low compared to CCIC. On the other hand, CHIP-AWS offers higher spatial resolution and much higher accuracy at local scales.
Together, the different strengths of these datasets provide observational constraints for evaluating and improving ice cloud processes in climate models across scales from individual cloud systems to multi-decadal trends.
How to cite: McEvoy, P., May, E., Amell Tosas, A., and Eriksson, P.: A 40-year Climatology and New Sub-Millimeter Retrievals: Two Novel Datasets for Observational Constraints on Ice Cloud Mass, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16826, https://doi.org/10.5194/egusphere-egu26-16826, 2026.
Below 0 °C, cloud droplets can freeze, altering a cloud’s optical and radiative properties and thereby affecting Earth’s energy balance. The microphysical mechanisms that govern this process, known as glaciation, are expected to act on minute timescales. Nevertheless, stratiform clouds can persist in the mixed-phase temperature range (0 °C to -38 °C) for hours, thus glaciation events remain poorly characterised.
We analysed satellite observations of individual cloud tops to track their temporal phase evolution and to quantify the extent of glaciation. We find that most glaciation events do not result in complete freezing. Rather, they induce a sustained shift in cloud properties while the clouds remain in the mixed‐phase regime. While the precise glaciation initiation mechanism remains unknown, higher hemispheric and seasonal ice-nucleating particle concentrations are shown to correlate with glaciation occurrence rate.
A cloud that retains supercooled liquid water after glaciation will have higher shortwave reflectance than a fully glaciated cloud. Inaccurate representations of glaciation can therefore bias radiative fluxes and, ultimately, climate projections. We are currently using our dataset to evaluate how accurately ICON represents mixed-phased cloud evolution. Simulations with progressively higher resolution are expected to yield higher phase heterogeneity in the cloud tops, thereby improving the representation of glaciation. This should help provide insights into the physical mechanisms that limit the extent of glaciation.
How to cite: Nikolov, D., Vella, R., Lohmann, U., and Villanueva, D.: What can satellites tell us about cloud glaciation? A time-resolved view., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10437, https://doi.org/10.5194/egusphere-egu26-10437, 2026.
Clouds influence the atmosphere's radiation balance, but cloud formation and lifetime itself is also influenced by radiation. Overlapping cloud layers, a common occurrence globally, are thus indirectly coupled through the individual layer's influence on radiative fluxes. In this work, we study the impacts of overlap between mid level (altocumulus and congestus) and high clouds (cirrus).
First, we identify tropical to subtropical West Africa as a hotspot of mid and high cloud overlap, based on CloudSat-CALIPSO observations. During the wet season, altocumulus and cirrus clouds overlap during at least 20% of all-sky conditions. Second, we design an idealized numerical setup that resolves two radiatively coupled cloud layers, allowing one cloud layer to evolve based on the influence of the other. We run experiments by varying the initial optical thickness of each cloud layer according to observed climatology. These experiment allows us to quantify how cloud overlap affects overall cloud lifetime, atmospheric radiative heating, and local radiative balance.
Since both altocumulus and cirrus in this region find their origin in deep convection, we expect that cloud overlap, via radiative heating, affects subsequent deep convection. Given the difficulty of representing mid level clouds in models, our results have implications for cloud climatology and regional radiation balance in climate simulations as well.
How to cite: Mol, W., Gasparini, B., and Voigt, A.: Impact of cloud overlap on cloud formation and lifetime through radiative coupling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7738, https://doi.org/10.5194/egusphere-egu26-7738, 2026.
Cloud phase is often described as a function of temperature, yet whether a single phase–temperature relationship applies across cloud vertical structure and seasons remains poorly constrained by observations. Using 15 years (2008–2022) of CALIPSO lidar observations, we investigate the partitioning of ice and liquid cloud phase as a function of temperature throughout the cloud column. Cloud phase and temperature are collocated at CALIOP’s native vertical resolution, allowing us to distinguish cloud-top and cloud-bulk phase characteristics.
We show that cloud phase–temperature relationships differ systematically between cloud tops and cloud interiors, and that these differences are strongly modulated by season and latitude. At low temperatures (below −10 °C), cloud interiors generally exhibit lower liquid fractions than cloud tops, whereas vertical phase differences become small at warmer temperatures. For a given temperature, extratropical clouds in the Northern Hemisphere generally contain more ice than those in the Southern Hemisphere. Seasonal modulation is most pronounced at high latitudes, where clouds during local winter exhibit higher liquid fractions than summer clouds at the same temperature. In contrast, seasonal variations in cloud phase partitioning are relatively weak in the tropics.
Vertical phase differences also depend on cloud geometric depth. Shallow clouds tend to be vertically homogeneous in phase, while clouds of intermediate depth exhibit more pronounced vertical phase contrasts, particularly at high latitudes and for colder cloud-top temperatures. These results demonstrate that cloud phase–temperature relationships are not universal, but depend on cloud vertical structure, season, and latitude, with implications for satellite-based cloud phase climatologies and the representation of mixed-phase clouds in climate models.
How to cite: Che, H. and Storelvmo, T.: Seasonal and vertical controls on cloud phase partitioning from long-term CALIPSO observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11104, https://doi.org/10.5194/egusphere-egu26-11104, 2026.
Aviation leads to the emission of CO2 but also exerts non-CO2 effects on climate (Lee et al., 2021). The latter include line-shaped condensation trails (contrails) and contrail cirrus that are known to cause warming. However, contrails can also form in already existing cirrus clouds. So far, such embedded contrails have received little attention and their climate impact is unknown. Here, we combine aircraft position data with height-resolved cloud observations from spaceborne lidar to obtain about 40,000 cases, in which aircraft are confirmed to have passed through cirrus less than 30 min before the observation. The data set is used to contrast the properties of perturbed from unperturbed cloud regions, and to infer the local net radiative forcing (RF) of embedded contrails. We find that cirrus with embedded contrails has an overwhelmingly warming effect (83% of cases) even though the majority (62%) of cases occurs during daytime when the addition of a contrail could potentially lead to cooling. The annual mean local net RF of individual embedded contrails ranges between -320 mW m−2 (2020, COVID lockdown) and 160 mW m−2. Considering the period from 2015 to 2021, we find an annual mean local warming effect of 60 mW m−2. Expanding these findings to the global scale suggests an annual global mean net RF of embedded contrails on the order of 5 mW m−2. This corresponds to around 10% of the current estimate of the climate impact of line-shaped contrails and, together with recent findings that conditions for contrail formation are found most often in already-existing cirrus (Petzold et al, 2025), suggests that embedded contrails are a non-negligible contributor to aviation’s impact on climate.
References:
Lee, D. S. et al. The contribution of global aviation to anthropogenic climate forcing from 2000 to 2018. Atmos. Environ. 244, 117834 (2021), https://doi.org/10.1016/j.atmosenv.2020.117834
Petzold, A. et al. Most long-lived contrails form within cirrus clouds with uncertain climate impact. Nat. Commun. 16, 9695 (2025), https://doi.org/10.1038/s41467-025-65532-2
How to cite: Seelig, T., Wolf, K., Bellouin, N., and Tesche, M.: Quantification of the radiative forcing of contrails embedded in cirrus clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9659, https://doi.org/10.5194/egusphere-egu26-9659, 2026.
Tropical cirrus clouds are commonly divided into those detrained from convection and those formed in situ. However, the relative contribution of these two categories to tropical high-cloud cover—particularly for thin cirrus in the tropical tropopause layer (TTL)—remains poorly constrained. Here, we take advantage of the 17-year CALIOP spaceborne lidar record to revisit the convective origin of tropical cirrus.
We perform systematic diabatic backward Lagrangian calculations starting from CALIOP curtain observations of both cloudy and clear-sky air, using ERA5 reanalysis winds and heating rates. Air parcels are followed for up to three months or until they intersect a convective cloud, defined when parcel temperature drops below the local brightness temperature inferred from geostationary satellite observations. Using a convective-origin criterion based on the evolution of relative humidity along trajectories, we classify cirrus into convective and in situ categories and characterize their climatology across the tropical band. We further investigate their space-time variability, as well as the geographic origin and transport lifetime of convective cirrus.
How to cite: Podglajen, A., Johansson, E., Kottayil, A., and Bernard, L.: On the convective origin of tropical upper-tropospheric cirrus using 17 years of CALIOP observations and Lagrangian trajectories, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12284, https://doi.org/10.5194/egusphere-egu26-12284, 2026.
Tropical ice clouds influence Earth’s radiation budget and hydrological cycle by reflecting incoming solar radiation and trapping outgoing longwave radiation. However, their diurnal variability remains poorly quantified across observational and reanalysis products. This study evaluates the diurnal and seasonal behavior of tropical Ice Water Path (IWP) using three complementary datasets: European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) reanalysis, NOAA Climate Prediction Center Infrared (IR) (CPCIR)–based Ice Water Path, and Cloud Profiling Radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CloudSat–CALIPSO radar-lidar retrievals for 2007-2010).
ERA5 provides hourly global estimates of total column ice (TCIW) and snow water (TCSW), CPCIR offers hourly total ice water path (TIWP) derived from combined infrared and microwave observations, and CloudSat-CALIPSO provides vertically resolved measurements at fixed local times (01:30 AM/PM) that serve as an observational reference for day and night contrasts. Spatially, all datasets exhibit consistent latitudinal IWP distributions within 30° S-30° N, with maxima along the Intertropical Convergence Zone (ITCZ) and minima in the subtropical dry zones. We find IWP peaks between 6-8° N with values of 0.350 kg m⁻² (CALIPSO), 0.269 kg m⁻² (CPCIR), and 0.115 kg m⁻² (ERA5), indicating that ERA5 underestimates IWP magnitude despite capturing the correct spatial structure. Seasonal variability reflects the meridional migration of the ITCZ, with maxima shifting northward during boreal summer (JJA) and southward during boreal winter (DJF). Both longitudinal and latitudinal analyses confirm that the three datasets reproduce similar large-scale IWP patterns across tropical regions.
The diurnal cycle derived from ERA5 and CPCIR reveals comparable phase behavior, with IWP local peaks both occurring at 4 LST, and global peaks on 15 and 16 LST. This alignment shows consistent timing of convective development across datasets, although CPCIR shows a larger diurnal amplitude and a peak that occurs approximately one hour later in the afternoon. Comparison with CALIPSO day-night retrievals supports that tropical IWP peaks in the afternoon. Comparison between land and sea diurnal cycle reveals that land areas dominate the diurnal signal, supporting that the structure of the diurnal cycle is associated with continental convection, whereas oceanic regions display weaker and flatter cycles. Overall, the results demonstrate that while reanalysis and satellite datasets differ in IWP magnitude, they exhibit consistent spatial, seasonal, and diurnal patterns. The strong land-ocean contrast highlights the key role of continental convection. These findings provide a benchmark for ice cloud diurnal cycle analysis in climate models.
How to cite: Wang, Y., Gupta, A., Bai, H., and Bennartz, R.: Constraining the Diurnal Cycle of Tropical Ice Clouds Using Satellite Observations and Reanalysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-669, https://doi.org/10.5194/egusphere-egu26-669, 2026.
Aerosol impacts on ice clouds remain a highly uncertain component of the effective radiative forcing from aerosol-cloud interactions, with models simulating a wide range of responses. Developing observational constraints for these aerosol-cloud effects is challenging. The low aerosol concentrations involved hinder their direct observation and the meteorological conditions that affect cloud properties (such as temperature and updraught speed) also impact ice crystal number, limiting its use for inferring information about aerosol. Variations in meteorological conditions can also impact cloud and aerosol properties together, obscuring the causal impact of aerosol on cloud.
Similar to the use of ship emitted aerosol and the resulting 'shiptrack' cloud perturbation to understand aerosol-cloud interactions in liquid clouds, here we use aircraft to understand the response of ice clouds to aerosol perturbations. Aircraft release water, aerosol and heat into the atmosphere as they fly, creating contrails in clear sky if conditions are suitable and perturbing existing clouds they fly through. The perturbation sizes vary with aircraft type, allowing a more detailed assessment of cloud responses.
Using a range of satellite data and ground-based radar observations, we composite contrails and aircraft impacts on existing clouds under a variety of conditions from a range of different aircraft types. We see that contrails formed from different aircraft types have varying lifetimes, consistent with an aerosol effect that increases cloud lifetime. Impacts on existing clouds vary significantly with time since the perturbation and meteorological conditions, highlighting the importance of the background cloud conditions. We also demonstrate how non-aerosol effects can be isolated and removed, to better constrain the impact of aerosols and aircraft on ice clouds and climate.
How to cite: Gryspeerdt, E., Driver, O. G. A., Marjani, S., Maruhashi, J., Neely III, R. R., Rhodes, L., Stettler, M. E. J., Tippett, A., Walden, C. J., and Walker, D.: Aircraft as a natural experiment on ice clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21074, https://doi.org/10.5194/egusphere-egu26-21074, 2026.
A realistic quantification of aviation’s net global climate impact depends on how well models represent aviation-induced aerosols (e.g., soot and sulfate) and their dual role: contributing to net warming through the formation of persistent ice clouds (contrails) and contributing to cooling by altering the microphysical properties of existing liquid clouds. Here, we focus on the warming pathway. Persistent contrails are estimated to produce warming over a year comparable to the warming from aviation CO₂ accumulated over several decades [1] and may account for ~2% of the total anthropogenic surface temperature increase since pre-industrial times [2]. Given their importance, contrails must be modelled both accurately and efficiently to support operational mitigation and to track aviation’s climate impact.
The Contrail Cirrus Prediction (CoCiP) tool is a widely used Lagrangian model that predicts contrail formation and evolution on a flight-by-flight basis. CoCiP is integrated into the Non-CO₂ Aviation Effects Tracking System (NEATS), which supports compliance with recent European reporting requirements for non-CO₂ aviation effects. Despite its broad adoption, CoCiP has been shown to underestimate lifetime-integrated optical depth relative to higher-fidelity models [3], motivating further evaluation against observations.
We analyze ~500 flights from 2025 that flew through the UK and surrounding region (approximately 48°N-63°N, 20°W-4°E) that have been contrail-matched using detections from the Earth Cloud Aerosol and Radiation Explorer (EarthCARE) mission. For each flight, we run CoCiP and compare its output at the advected waypoint closest to the satellite-detected contrail at the detection time. We find that CoCiP fails to predict a contrail for roughly half of the cases. For ~20% of flights, contrail formation is not expected based on the Schmidt–Appleman criterion, which depends on both atmospheric and aircraft characteristics. In other cases, flights satisfy this criterion but occur in ice-subsaturated regions according to the ERA5 reanalysis dataset, again leading CoCiP to predict no persistent contrail. These false negatives are therefore not solely model-driven, but also reflect uncertainties in the meteorological inputs, highlighting the need to disentangle error sources to robustly diagnose and address failures in a modeling chain.
References
[1] Lee, D.S. et al.: The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018, Atmospheric Environment, Volume 244, 117834, ISSN 1352-2310, 2021, https://doi.org/10.1016/j.atmosenv.2020.117834.
[2] IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 3−32, doi:10.1017/9781009157896.001.
[3] Akhtar Martínez, C. et al.: Zero-dimensional contrail models could underpredict lifetime optical depth, Atmos. Chem. Phys., 25, 12875–12891, 2025, https://doi.org/10.5194/acp-25-12875-2025.
How to cite: Maruhashi, J., Marjani, S., Driver, O., Itcovitz, J., Gryspeerdt, E., and Stettler, M.: Success and failure of contrail models: a flight-by-flight investigation using satellite observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15065, https://doi.org/10.5194/egusphere-egu26-15065, 2026.
We revised and simplified the microphysics of mixed-phase clouds in CESM2, assuming sedimentation and immersion freezing by mineral dust as the only sources of ice crystals. We find that these assumptions produce variability in cloud-top phase that agrees with long-term global satellite observations (Villanueva et al., 2025; Toll et al., 2024, Science). These simulations confirm that the interannual variability of cloud phase is controlled by dust loading.
Furthermore, by probing instantaneous cloud states daily over a 10-year simulation, we propose a simplified theoretical framework that maps the log-normal variability of ice-forming processes onto the observed variability of cloud-top phase. For cold mixed-phase clouds (cloud-top temperatures below −21 °C), we find the cloud climatology is dominated by a reduced set of processes:
1. Aerosol-driven droplet freezing,
2. Ice depositional growth (WBF),
3. Droplet–snow riming in thick clouds, and
4. Cloud-top radiative cooling in thin clouds.
As a result, ice-nucleating particles (INPs) can impose a logarithmic control on cloud mass. At sufficiently high INP concentrations, this control becomes reversible (the WBF process is skipped), leading to a log-parabolic cloud response.
How to cite: Villanueva, D.: A log-parabolic sensitivity of mixed-phase clouds to ice-nucleating aerosols, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12224, https://doi.org/10.5194/egusphere-egu26-12224, 2026.
Ice particles and their properties (shape, size, etc.) have great potential for influencing cloud lifecycles, from their formation through their growth, and precipitation. Coupled with liquid-phase hydrometeors and associated processes in mixed-phase clouds, ice processes can be critical for understanding the extent of aerosol-cloud interactions and their causal links, which require model simulations across scales. Robust estimates of observed ice properties, therefore, can support the evaluation and rectification of model physics, which could ultimately increase model fidelity. However, the entanglement of various parameterized processes that affect modeled cloud characteristics poses challenges for direct comparisons of model state variables with cloud observations. The use of consistent cloud process metrics can help address some of these difficulties and enable direct comparisons between observations and models. In the case of Arctic mixed-phase clouds, the representation of ice precipitation rates at and below cloud base, which serve as a key cloud water sink, could impact simulated cloud lifecycles and alter cloud feedbacks. These metrics can be robustly retrieved from ground-based measurements, which are considerably less susceptible to uncertainties associated with accurately locating cloud base, tropospheric profiling limitations, and spatial footprint size.
Here, we describe the main approaches of ice property retrievals. We then focus on cloud-base ice particle property retrievals using a Markov Chain Monte Carlo (MCMC) algorithm applied to radar and high-spectral-resolution lidar observations from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility site at the North Slope of Alaska (NSA). We describe the analysis results, including a qualitative distinction between ice-number- and size-dominated reflectivity regimes, number-concentration enhancements in certain temperature ranges, and a weak, typical Arctic cloud-base vertical motion. After examining insights derived from those retrievals, they are used in a brief bulk evaluation of mixed-phase cloud ice representation in three different global models: the NASA Goddard Institute for Space Studies ModelE3, the NCAR Community Earth System Model Version 2 (CESM2), and the DOE Energy Exascale Earth System Model Version 1 (E3SMv1). To perform a robust evaluation of Arctic cloud precipitation rates against observations, we process regional model output using the Earth Model Column Collaboratory (EMC²) instrument simulator and subcolumn generator, and compare them with corresponding cloud-base precipitation statistics calculated from the long-term ground-based remote-sensing dataset collected at the ARM NSA site. This brief analysis demonstrates key differences between the models and examines the agreement between model output and observations. Finally, we describe our current effort to generate sub-mixed-phase cloud ice precipitation profiles using a deep neural network emulator of the computationally intensive MCMC algorithm and discuss future plans.
How to cite: Silber, I., Comstock, J. M., Shi, Y., Fridlind, A. M., Ackerman, A. S., Liu, X., Nugent, J. M., and McCoy, D. T.: On Lower-Tropospheric Arctic Ice Particle Properties Retrieved Using Machine Learning Applications to Remote Sensing Data, and their representation in Global Model Simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3188, https://doi.org/10.5194/egusphere-egu26-3188, 2026.
Liquid-containing clouds have an important impact on Arctic winter climate because they suppress radiative cooling of the surface. Pure ice clouds have a much weaker effect on longwave radiation, and often permit substantial surface radiative cooling. Here, we show that climate models typically underestimate the difference in surface radiation under low-level liquid and ice clouds in the Arctic. The analysed models consistently overestimate the longwave radiative effect of thin ice clouds compared to ground-based observations from the MOSAiC expedition. This mismatch occurs despite realistic ice cloud effective radii in models, and thus cannot be due to errors in cloud properties. The model behaviour reflects the relationship between ice water path and cloud optical thickness that is at the core of commonly used ice optics parametrizations, but this relationship is inconsistent with MOSAiC observations. Ice optics parametrizations have been developed for cirrus clouds, and low-level Arctic ice clouds may be more heterogeneous, or have different ice habits, reducing their radiative impact compared to a cirrus cloud of the same ice water path and effective radius. Our results suggest that climate models understimate the surface warming effect of an increasing liquid fraction of cloud condensate in a warming Arctic.
How to cite: Pithan, F., Abraham, C., Athanase, M., Huo, Y., Michalezyk, N., Naakka, T., Roehrig, R., Streffing, J., and Sanchez-Benitez, A.: Climate models overestimate the radiative effect of thin Arctic ice clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20223, https://doi.org/10.5194/egusphere-egu26-20223, 2026.
Clouds over the Southern Ocean are critical to accurately representing Earth’s radiative properties, yet continue to challenge Earth System Models due to complex micro-scale processes that influence regional-scale radiation. Subgrid-scale processes, including turbulence, cloud droplet activation, droplet collision-coalescence, ice nucleation, secondary ice production, and ice growth, are represented in coarse resolution models with parameterizations. It is well-documented that coupled Earth System model simulation results are highly sensitive to changes in these subgrid processes and that both structural and parameter uncertainties remain large.
In this talk, we will discuss a process system approach for interrogating the representation of model microphysical processes in the Community Atmosphere Model version 6 (CAM6). Instrument simulators that translate model output into “observable” quantities were developed based on the sampling and measurement capabilities of the field instruments and “deployed” during several SO field campaigns using a specified dynamics configuration of the CAM6. Assessments revealed a low bias in cloud droplet number concentrations (CDNC), consistent with a low bias in cloud condensation nuclei (CCN) from missing sulfate aerosol. Model predictions of SO ice nucleating particles (INPs) are skillful in the boundary layer, but are much more variable aloft. In a series of simulations aimed at determining the needed INP predictive skill for accurately representing SO clouds, we find little to no sensitivity in CAM6 clouds to changes in ice nucleation. Analysis of these simulations reveal that ice formation in CAM6 SO clouds is unrealistically dominated by heterogeneous freezing of supercooled rain and is linked to the CDNC-CCN bias chain. Efforts to address these biases will also be discussed.
How to cite: McCluskey, C., Niu, Q., Thayer-Calder, K., Patnaude, R., Gohil, K., Nusbaumer, J., Hannay, C., Medeiros, B., and Mace, G.: Ice, Ice, Maybe? A Process System Assessment of Southern Ocean Aerosol-Cloud Interactions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15117, https://doi.org/10.5194/egusphere-egu26-15117, 2026.
Ice clouds, as all clouds, are important components of the Earth-Atmosphere system, influencing Earth’s energy budget and the hydrological cycle. For the representation of ice clouds in models on different scales, we have to design meaningful cloud schemes based on the relevant process (as, e.g., nucleation, growth/evaporation, or sedimentation). Since most of these processes are quite complex, we have to derive simple (or even much simpler) schemes, adapted adequately to the scales as resolved in the respective model. The derivation of bulk schemes from the underlying population balance equation is a typical example for such model reduction; this procedure typically results into a set of ordinary differential equations for averaged quantities. Even for such bulk models, simplification of these complex schemes is often necessary for the use in weather models. However, further reduction of the dynamical systems might alter their qualitative properties, i.e. the quality of solutions.
In this contribution, a consistent hierarchy of models for ice clouds at low temperatures is developed. Using several consistent approximations and simplifications, complex (bulk) schemes can be reduced to simpler models, allowing a better understanding of the represented processes. These models are analyzed in terms of qualitative behavior of solutions. It can be shown, that certain reduction steps, as, e.g., the change to a constant sedimentation velocity of cloud particles suppresses oscillatory solutions, as recently determined. During the reduction process, the ability of the resulting simpler models to represent measurements at least qualitatively is addressed.
How to cite: Spichtinger, P.: A hierarchy of ice cloud models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8252, https://doi.org/10.5194/egusphere-egu26-8252, 2026.
In tropical convection, the microphysical properties of ice in anvils are a major factor in determining cloud-radiative forcing and cloud-climate feedbacks. One large source of uncertainty in predicting the ice number, size, shape, and sedimentation in storm anvils is establishing the efficiency of ice self-aggregation processes. Ice crystal adhesion decreases as temperature decreases, but aggregation process rates are difficult to measure and depend on complex environmental factors. The overarching goal of this study is to identify how uncertainty related to ice aggregation efficiencies affects anvil properties and cloud radiative feedbacks, and how we may constrain this uncertainty in the future.
We exploit a high-resolution database of simulated convective systems being produced for the NASA INvestigation of Convective UpdraftS (INCUS) mission with the Regional Atmospheric Modeling System (RAMS), which features a bin-emulating microphysics scheme. The INCUS LES dataset represents an expanding collection of diverse storm morphologies in a variety of maritime and continental (sub)tropical environments, including scattered congestus, multicell convective clouds, squall lines, and tropical cyclones. To address our science goals, ice aggregation efficiencies for temperatures -20 to -50 ◦C are perturbed in the INCUS simulation ensemble. The perturbed aggregation efficiencies all fall within the spread of uncertainty of those obtained from previous laboratory and modeling studies. The simulations are then run through the Community Radiative Transfer Model (CRTM), and storm anvils are tracked and separated into their optically thick and thin components.
Overall, small changes to ice aggregation efficiencies below -20 °C can significantly reduce or expand anvil extent, lifetime, depth, and their associated cloud radiative effects. Thick anvils are more sensitive to changes in aggregation than thin anvils, with a 25% reduction in thin anvil area and a near complete dissipation of thick anvils. As such, anvil cooling feedbacks are more sensitive to ice aggregation than cloud warming effects, with changes in outgoing longwave radiation on the order of 100 W/m^2. This analysis demonstrates how poorly constrained ice self-aggregation efficiencies are within observations and numerical models, proving a critical need for more observations and physical understanding of ice aggregation processes.
How to cite: Bukowski, J., Saleeby, S., Chase, R., Posselt, D., Dolan, B., Grant, L., Leung, G., Marinescu, P., Rasmussen, K., Singh, I., Storer, R., and van den Heever, S.: Sensitivity of Tropical Anvils to Ice Aggregation , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8328, https://doi.org/10.5194/egusphere-egu26-8328, 2026.
Dusty cirrus clouds are optically thick cirrus that form under the influence of elevated concentrations of ice nucleation active mineral dust. These clouds are associated with dust plume events in which freshly emitted mineral dust particles are lifted to near-tropopause levels by baroclinic storms. At present, dusty cirrus clouds are not well represented in global climate models, primarily because aerosol-cloud interactions are inadequately parameterized and model resolutions are insufficient to resolve the convective motions within these clouds (Seifert et al., 2023, ACP).
We used large-eddy simulatior (LES) UCLALES-SALSA to investigate the formation conditions of dusty cirrus clouds, supported by a sensitivity analysis based on observations from the ML-CIRRUS (2014) campaign. The results indicate that mineral dust concentrations must be approximately 10-100 times higher than climatological values to sustain convective overturning motions. Furthermore, the sensitivity analysis shows that both sub-500 nm and super-500 nm dust particles play a significant role in producing ice crystal number concentrations consistent with in situ observations.
We further find that the choice of deposition ice nucleation parameterization has a strong influence on the simulated properties of dusty cirrus clouds and on the temperature range over which they can form. The sensitivity analysis was conducted using the Ullrich et al. (2017, JAS) scheme, which exhibits strong sensitivity to temperature and relative humidity with respect to ice within the temperature range characteristic of dusty cirrus clouds, and produces a relatively large fraction of ice concentration near the top of the cirrus layer. In contrast, simulations using the Phillips et al. (2013, JAS) scheme yield markedly different cloud structures, with more vertically uniform ice crystal number concentrations, reflecting its weaker temperature dependence compared to the Ullrich et al. (2017) parameterization.
How to cite: Juurikkala, K., Raatikainen, T., Krämer, M., and Laaksonen, A.: Exploring Formation Conditions of Dusty Cirrus Using a Large-Eddy Simulator, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7445, https://doi.org/10.5194/egusphere-egu26-7445, 2026.
Homogeneous freezing of supercooled cloud droplets controls the transition from mixed- to ice-phase regime in the upper troposphere. We discuss a stochastic representation of the process, for use in particle-based aerosol-cloud microphysics models. The embraced Poissonian formulation is governed by droplet volume, model time step, and the homogeneous nucleation rate.
Using an implementation of the model in the PySDM particle-based modelling package, we evaluate two nucleation-rate formulations: a temperature-dependent and a water-activity-based parameterisations, the latter applicable also to aqueous solution droplets.
Using an air-parcel framework, we investigate freezing-temperature distributions and resulting ice number concentrations across ensembles of simulations with varying updraft speeds, CCN concentrations, droplet size distributions, and number of super-particles. The two nucleation-rate parameterisations diverge under super- or subsaturated conditions with respect to water, yielding differences in freezing temperatures and ice number concentrations.
To asses the impact of Wegener-Bergeron-Findeisen process on ice concentrations, we consider simulations with and without vapour deposition on ice. With deposition enabled, early stochastic freezing events dominate the evolution of the frozen droplet fraction and substantially reduce the number of droplets that ultimately freeze.
The developed model allows to validate the common assumption that homogeneous freezing is a threshold phenomenon occurring at ca. 235 K. We find that homogeneous freezing spans a broad temperature range controlled by cooling rate and droplet size, highlight the importance of stochastic freezing formulations and nucleation-rate choice for representing cloud glaciation.
How to cite: Lüttmer, T., Arabas, S., and Spichtinger, P.: Stochastic homogeneous freezing of supercooled droplets in particle-based microphysics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5282, https://doi.org/10.5194/egusphere-egu26-5282, 2026.
Secondary ice production (SIP) is the process through which the number concentration of ice crystals increases to greatly exceed the number concentration of ice nuclei. Though recent field campaigns investigating SIP within deep convection have revealed important insights, the importance of different pathways (rime splintering, droplet fragmentation, ice-ice collisional breakup, sublimation fragmentation, droplet jet freezing) to total SIP is still uncertain. To investigate these unknowns, we simulated a subtropical deep convective cloud using Lagrangian cloud microphysics.
Our results indicate that SIP produces stronger updrafts but reduces overall precipitation, reflecting a shift from condensational to vapor depositional growth. We find that droplet fragmentation dominates SIP early in the cloud’s development, while ice-ice collisional breakup becomes increasingly important later as large graupel forms. SIP also greatly increases ice water content and produces a more optically-thick anvil. Colder-temperature ice nuclei delay the onset of SIP and lead to higher overall precipitation despite lower total condensate. Increasing background cloud condensation nuclei (CCN) concentration reduces total precipitation, with a stronger relative reduction when SIP is present. Increasing CCN concentration increases ice water content, though this increase is non-monotonic with CCN concentration when SIP is present.
Our work supports the feasibility of modeling SIP within a Lagrangian microphysical framework, and highlights the complex interactions between SIP, background CCN concentration, and ice nuclei type.
How to cite: Ascher, B. and Hoffmann, F.: Secondary Ice Production Invigorates Updrafts but Suppresses Precipitation in Simulated Subtropical Convection, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5284, https://doi.org/10.5194/egusphere-egu26-5284, 2026.
Mixed-phase clouds, consisting of both liquid and ice phases, are crucial for precipitation formation over continents. The presence of the ice phase acts as a catalyst for forming precipitable particles through depositional growth, aggregation, and riming. The efficiency of these growth processes is strongly governed by the spatial distribution of the liquid and ice phases and the interfaces between them. A homogeneous mixture of liquid and ice particles maximizes the growth of the ice particles, and with that expedites precipitation formation. In contrast, a strong separation into a liquid and ice clusters may limit the growth by reducing phase interactions. Observations indicate that these heterogeneous clusters exist down to a spatial extent of 100 m [1] potentially creating a limiting factor for the efficiency of a mixed-phase cloud to precipitate.
Here, we show that these cloud phase heterogeneities even exist down to the meter-scale based on in-situ observations. A total of 19 glaciogenic seeding experiments conducted in supercooled low-stratus clouds in Switzerland within the CLOUDLAB project [2], were sampled with an in-house developed holographic imager, capable of distinguishing cloud droplets from ice crystals. Applying thresholds to separate liquid, mixed, and ice clusters, we demonstrate the highly variable nature of mixed-phase cloud phase structures. We furthermore contextualize these findings with high-resolution model simulations with the weather model ICON [3] at 50 m and 250 m. These simulations highlight the importance of resolving cloud phase heterogeneities for efficiently forming precipitation. By combining novel cloud in situ observations with high-resolution modeling, this study emphasizes the need to capture the heterogeneity in mixed-phase clouds and its importance for numerical weather models.
[1] A. Korolev and J. Milbrandt, “How are mixed-phase clouds mixed?,” Geophysical Research Letters, 49, e2022GL099578, DOI: 10.1029/2022GL099578
[2] J. Henneberger, F. Ramelli, R. Spirig, N. Omanovic, A. J. Miller, C. Fuchs, H. Zhang, J. Bühl, M. Hervo, Z. A. Kanji, K. Ohneiser, M. Radenz, M. Rösch, P. Seifert, and U. Lohmann, “Seeding of Supercooled Low Stratus Clouds with a UAV to Study Microphysical Ice Processes: An Introduction to the CLOUDLAB Project,” Bulletin of the American Meteorological Society, vol. 104, no. 11, E1962–E1979, 2023, ISSN: 0003-0007, 1520-0477. DOI: 10.1175/BAMS-D-22-0178.1
[3] G. Zängl, D. Reinert, P. Ripodas, and M. Baldauf, “The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core,” Quarterly Journal of the Royal Meteorological Society, vol. 141, no. 687, pp. 563–579, 2015, ISSN: 1477-870X. DOI: 10.1002/qj.2378
How to cite: Omanovic, N., Fuchs, C., Henneberger, J., Zhang, H., and Lohmann, U.: The implications of unresolved cloud phase heterogeneities on precipitation formation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9021, https://doi.org/10.5194/egusphere-egu26-9021, 2026.
Posters on site: Tue, 5 May, 08:30–10:15 | Hall X5
Homogeneous nucleation is generally not considered a possibility in cloud formation processes in the atmosphere of Mars (Määttänen et al. 2005; Clancy et al., 2017), or Earth (Pruppacher & Klett, 1996), as it requires high levels of supersaturation that are considered unlikely to occur under real atmospheric conditions, in which heterogeneous nucleation on widespread aerosols depletes water in excess of saturation.
The Arsia Mons Elongated Cloud (AMEC) is an eye-catching and mysterious cloud occurring recurrently every morning during the dusty season over the Arsia Mons volcano on Mars (Hernández-Bernal et al., 2021). It shows a peculiar elongated shape that in only 3 hours expands up to 1800 km from its origin point. Hernández-Bernal et al. (2022) investigated this cloud based on the LMD Mars Mesoscale model (Spiga and Forget, 2009). The tail of the cloud was not reproduced in the model, but a cold pocket with temperatures down to 30K below the environment and supersaturation up to 105 appeared next to Arsia Mons, in a position, altitude, and local time and season coincident with the origin point of the AMEC in observations.
In this work we show that these are conditions conductive to homogeneous nucleation, and when we introduce this process as a new cloud formation process in the LMD Mars Mesoscale model, we obtain a good representation of the AMEC, and its long tail. This provides an excellent explanation for this mysterious cloud and shows that homogeneous nucleation is possible and can have significant effects in the atmosphere of Mars. We intend to explore these and other clouds on Mars and Earth possibly involving homogeneous nucleation.
References:
- Clancy, R., Montmessin, F., Benson, J., Daerden, F., Colaprete, A., & Wolff, M. (2017). Mars Clouds. In R. Haberle, R. Clancy, F. Forget, M. Smith, & R. Zurek (Eds.), The Atmosphere and Climate of Mars (Cambridge planetary science (pp. 76–105). Cambridge: Cambridge University Press. https://doi.org/10.1017/9781139060172.005
- Määttänen, A., Vehkamäki, H., Lauri, A., Merikallio, S., Kauhanen, J., Savijärvi, H., & Kulmala, M. (2005). Nucleation studies in the Martian atmosphere. Journal of Geophysical Research: Planets, 110(E2). https://doi.org/10.1029/2004JE002308
- Hernández‐Bernal, J., Sánchez‐Lavega, A., del Río‐Gaztelurrutia, T., Ravanis, E., Cardesín‐Moinelo, A., Connour, K., ... & Hauber, E. (2021). An extremely elongated cloud over Arsia Mons volcano on Mars: I. Life cycle. Journal of Geophysical Research: Planets, 126(3), e2020JE006517. https://doi.org/10.1029/2020JE006517
- Hernández‐Bernal, J., Spiga, A., Sánchez‐Lavega, A., del Río‐Gaztelurrutia, T., Forget, F., & Millour, E. (2022). An extremely elongated cloud over Arsia Mons volcano on Mars: 2. Mesoscale modeling. Journal of Geophysical Research: Planets, 127(10), e2022JE007352. https://doi.org/10.1029/2022JE007352
- Pruppacher, H. R., Klett, J. D., & Wang, P. K. (1996). Microphysics of clouds and precipitation. Springer Science. https://doi.org/10.1007/978-0-306-48100-0
- Spiga, A., & Forget, F. (2009). A new model to simulate the Martian mesoscale and microscale atmospheric circulation: Validation and first results. Journal of Geophysical Research: Planets, 114(E2). https://doi.org/10.1029/2008JE003242
How to cite: Hernandez Bernal, J., Määttänen, A., Spiga, A., and Forget, F.: Homogeneous nucleation on Mars. An unexpected process that deciphers mysterious elongated clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9572, https://doi.org/10.5194/egusphere-egu26-9572, 2026.
Understanding ice microphysics processes within storms is key to developing parameterizations that accurately represent them in models. In this study, we analyze the ice formation pathways of a convective system observed over southern Scandinavia during the airborne TPEx campaign (Konjari et al., 2025). Using the ICOsahedral Nonhydrostatic (ICON) modeling framework (version 2024.7), we performed a high-resolution simulation (400 m horizontal, 150 m vertical) with the ice-mode implementation that differentiates between five formation mechanisms (Lüttmer et al., 2025). We identified and tracked convective cells using tobac (Tracking and Object Based Analysis of Clouds, Heikenfeld et al., 2019), analyzing only those whose complete life cycles were captured. For each stage of the life cycle (developing, mature, and dissipating) we examined the importance of each formation pathway by altitude, further distinguishing between the convective core and the anvil and analyzing overshoots as a sub-case. Our results suggest, for example, that homogeneous drop freezing was the most important source of the ice crystals in the overshooting anvil of the convection. Additionally, we compare our conclusions to the ones made by Konjari et al. (2025) based on observations of the same study case.
Heikenfeld, M., Marinescu, P. J., Christensen, M., Watson-Parris, D., Senf, F., van den Heever, S. C., and Stier, P.: tobac 1.2: towards a flexible framework for tracking and analysis of clouds in diverse datasets, Geoscientific Model Development, 12, 4551–4570, https://doi.org/10.5194/gmd-12-4551-2019, 2019.
ICON partnership (MPI-M; DWD; DKRZ; KIT; C2SM): ICON, https://www.icon-model.org/, accessed: 2026-01-15.
Konjari, P., Rolf, C., Krämer, M., Afchine, A., Spelten, N., Bartolome Garcia, I., Miltenberger, A., Emig, N., Joppe, P., Schneider, J., Li, Y., Petzold, A., Bozem, H., and Hoor, P.: Stratospheric Hydration and Ice Microphysics of a Convective Overshoot Observed during the TPEx Campaign over Sweden, EGUsphere, 2025, 1–27, https://doi.org/10.5194/egusphere-2025-2847, 2025.
Lüttmer, T., Spichtinger, P., and Seifert, A.: Investigating ice formation pathways using a novel two-moment multi-class cloud microphysics scheme, Atmospheric Chemistry and Physics, 25, 4505–4529, https://doi.org/10.5194/acp-25-4505-2025, 2025.
How to cite: Bartolome Garcia, I., Miltenberger, A., Rolf, C., Krämer, M., and Konjari, P.: Convection over Southern Scandinavia: a Modeling Perspective, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17594, https://doi.org/10.5194/egusphere-egu26-17594, 2026.
Mesoscale convective systems (MCSs) are vital to Earth's climate system, fundamentally influencing water and energy cycles and by driving a large fraction of extreme weather events, including intense precipitation, flooding, and severe winds. A defining characteristic of these systems is their extensive ice anvils, whose shortwave and longwave radiative interactions generate cloud-radiative heating that strongly controls anvil lifetime, organization, and storm evolution. Despite their importance, the representation of deep convective systems remains a major source of uncertainty in weather and climate models, largely due to the complex and tightly coupled interactions between aerosols, cloud microphysics, and radiation. In particular, the role of ice crystal number, size, and habit in modulating radiative heating profiles and feedbacks on convective dynamics is still poorly constrained.
The High Altitude Ice Crystals (HAIC) field campaign provides a unique observational framework to investigate these processes. HAIC combined in situ airborne microphysical measurements with satellite observations to document the properties of ice crystals in deep convective structure, with a specific focus on high ice water content conditions relevant for both climate processes and aviation safety. During the campaign, detailed observations of ice crystal concentrations, size distributions, and thermodynamic conditions were collected in tropical deep convective systems, offering an exceptional opportunity to evaluate and constrain model representations of ice microphysics and their radiative impacts.
In this study, we focus on a well-documented deep convective system that formed over the Atlantic Ocean and was advected toward French Guiana on 16 May 2015. We combine HAIC airborne and satellite observations with high-resolution numerical simulations performed with the Meso-NH model. The simulations employ the two-moment LIMA microphysical scheme, explicitly coupled to the ecRad radiative transfer code. The radiative properties of ice crystals are prescribed using habit-dependent optical parameterizations derived from the Yang et al. (2013) ice optics lookup tables. Aerosol sources, transport, activation, and scavenging are explicitly represented, allowing an assessment of how aerosol variability propagates through cloud microphysical processes and radiative feedbacks. This configuration allows a physically consistent representation of aerosol–microphysics–radiation interactions. Sensitivity experiments are performed to investigate both aerosol life-cycle effects and ice crystal habit variability, while keeping the large-scale dynamical forcing unchanged. Dedicated sensitivity simulations are conducted by systematically testing distinct ice crystal habits in order to isolate their respective impacts on cloud-radiative heating profiles, anvil structure, precipitation efficiency, and convective lifecycle. This combined observational–modeling framework provides quantitative insight into how aerosol processes and ice microphysical properties jointly modulate radiative feedbacks in deep convection.
How to cite: El Gdachi, S. and Barthe, C.: Aerosol–Ice Crystal–Radiation Interactions in Deep Convection: Insights from High-Resolution Meso-NH Simulations and HAIC Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4868, https://doi.org/10.5194/egusphere-egu26-4868, 2026.
Secondary ice production (SIP) plays an important role in tropical deep convection. This study implements multiple SIP mechanisms, including droplet fragmentation and ice–ice collisional breakup, into the CASIM microphysics scheme of the UK Met Office Unified Model, and evaluates their impacts through a real-case simulation of a Hector thunderstorm. SIP enhances ice number concentration in upper cloud layers, with values up to 3 orders of magnitude higher than the no-SIP case, particularly above −10 °C. Ice water content (IWC) increases by a factor of 3–5 in the anvil region, contributing to more extensive upper-level cloud coverage. These microphysical changes reduce outgoing longwave radiation (OLR) by ∼ 3.2 W m−2 (1.3 %) and increase outgoing shortwave radiation (OSR) by ∼ 4.5 W m−2 (1.8 %) over a 6 h analysis period and a 110 km × 110 km domain. SIP modifies precipitation spatially, yielding a more localized, compact rainfall pattern near the convective core, while reducing domain-averaged precipitation by ∼ 8 %. Peak rainfall rates remain only slightly affected, consistent with the minor changes (< 1 m s−1) in maximum updraft velocity. Among the tested mechanisms, ice–ice collisional breakup shows negligible impact on simulated ice concentration, consistent with limited graupel-involved collision energetics under warm profiles. Ensemble experiments confirm that these effects are robust and exceed the influence of meteorological variability. These results highlight the importance of representing SIP processes in cloud-resolving models of tropical convection and accounting for their environmental dependence.
How to cite: Sun, M., Connolly, P. J., Field, P. R., Finney, D. L., and Blyth, A. M.: Secondary ice production in tropical deep convection: Insights from high-resolution simulations with the Unified Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2045, https://doi.org/10.5194/egusphere-egu26-2045, 2026.
Secondary ice production explains why clouds often contain ice particle concentrations that are orders of magnitude higher than the number of ice-nucleating particles available to initiate freezing. Accurate prediction of concentrations of ice in atmospheric clouds necessitates an understanding of SIP mechanisms. A fundamental challenge is determining how modeled SIP mechanisms depend on cloud properties and environmental conditions.
In this study, we used the Aerosol–Cloud (AC) model, which incorporates four secondary ice production mechanisms: ice–ice collisional breakup, fragmentation during raindrop freezing, the Hallett–Mossop process, and sublimational breakup. The various numerical simulations for sensitivity studies are conducted with the AC model and evaluated using a control simulation.
Ice multiplication is driven by positive feedback mechanisms formed by interconnected microphysical processes. Investigating the potential for ice enhancement in natural clouds therefore requires consideration of the full range of microphysical interactions that may either suppress or amplify its influence under varying environmental conditions. The objective is to assess and determine the synergy among the secondary ice mechanisms.
In tropical deep convective clouds with very warm cloud bases, lower environmental CCN concentrations led to higher simulated ice concentrations in the lower mixed-phase region. In contrast, plausible variations in environmental IN concentrations had little effect on total simulated ice at any altitude. Overall, ice multiplication acted to dampen the simulated sensitivity to changes in both IN and CCN aerosol loadings.
How to cite: Deshmukh, A., Waman, D., Patade, S., Gupta, A. K., and Phillips, V.: Sensitivity of ice multiplication mechanisms among natural clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18136, https://doi.org/10.5194/egusphere-egu26-18136, 2026.
Aircraft icing associated with supercooled large droplets (SLD) remains a critical hazard to flight safety, yet direct in situ observations over China are scarce. This study presents the cloud microphysical characteristics observed during two flight missions of the Aircraft Icing Research Flight Experiment (AIRFEx) conducted in March 2025 over eastern Sichuan Province, southwestern China. A Cloud, Aerosol and Precipitation Spectrometer (CAPS), a Nevzorov total water content probe, and an icing detector were deployed to obtain particle size distributions from 0.6–1550 μm, liquid and ice water contents. The 17 March case featured a mixed-phase, ice-dominated cloud with enhanced large irregular particles near an elevated inversion, suggesting active secondary ice production. In contrast, the 29 March case exhibited a liquid-dominated cloud with persistent supercooled droplets and episodic SLD, accompanied by pronounced ice accretion on the airframe. Icing periods Among icing environmente extracted to compare microphysical conditions between icing and non-icing periods at subfreezing temperatures and to evaluate consistency with the FAR Part 25 Appendix O freezing-drizzle envelopes. Icing periods were characterized by systematically higher liquid water content and slightly larger droplet sizes than non-icing periods, while most observed conditions fell within the Appendix O envelopes, with one out-of-envelope event indicating locally enhanced severity. These first in situ observations of SLD-related icing over southwestern China provide a process-based reference for validating icing hazard assessments and support future development of region-specific SLD climatologies and icing certification criteria.
How to cite: shi, Y.: Aircraft In Situ Observations of Cloud Microphysics During Icing Events over Southwestern China in Spring 2025, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8528, https://doi.org/10.5194/egusphere-egu26-8528, 2026.
Satellite observations provide instantaneous snapshots of cloud properties, such as ice water content and ice crystal number concentration, which may retain information on the prior history of cloud parcels. However, inferring cloud microphysical processes from satellite data alone remains challenging, as these processes are not directly observable.
Lagrangian models, either purely transport-based or coupled to microphysics, are commonly used to reconstruct the history of cirrus clouds and to infer their origin (in situ vs. liquid-origin) and ice formation pathways (e.g. homogeneous vs. heterogeneous nucleation). These approaches, however, strongly depend on meteorological reanalyses and microphysical assumptions, which remain particularly uncertain for cirrus clouds. While very useful, they would ideally be further constrained by observation-based information.
Here, we explore whether satellite observations can provide additional indications of ice nucleation events. For this purpose, we analyse global lidar-radar observations from the DARDAR-Nice product, focusing on spatial patterns in vertical profiles of ice cloud properties. In particular, we investigate whether strong local absolute or relative increases in ice crystal number concentration can be interpreted as signatures of nucleation events. This methodology is applied globally over one year of observations to estimate the occurrence of homogeneous and heterogeneous ice nucleation, and the statistical occurrence of different ice nucleation pathways is presented. The approach is further evaluated using high-resolution ICON simulations of ice cloud structures to assess its limitations. Finally, global results from this observation-only method are compared with nucleation diagnostics derived from back-trajectory approaches using CLaMS-Ice and FLEXPART.
How to cite: Sourdeval, O., Bartolome Garcia, I., Saiprakash, A., and Bucci, S.: Exploring signatures of ice nucleation events in satellite observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20455, https://doi.org/10.5194/egusphere-egu26-20455, 2026.
The highest concentrations of ice nucleating particles (INPs) in biomass-burning smoke are observed during intense, flaming fires (Schaefer, 1952; Prenni, 2012). While evidence that INPs can be generated by the combustion process itself is sparse, their presence is commonly attributed to lofting of dust and soil from the ground by strong fire induced convection. Potassium containing particles are abundant in smoke plumes and serve as a marker for biomass burning. Inorganic potassium compounds include KCl, KNO3, and K2SO4. Fresh smoke from flaming fires contains crystalline KCl, which is converted to KNO3 and K2SO4 through reactions with HNO3 and H2SO4 during plume aging (Freney, 2009).
We present ice nucleation experiments on monodisperse potassium salt particles conducted using a modified version of the SPectrometer for Ice Nucleation (SPIN) chamber (Welti, 2020), in which the test particles are exposed to temperatures down to 208 K and well-defined humidity. Ice nucleation occurred at temperatures below 235 K, relevant for cirrus cloud formation. While KCl particles deliquesce at approx. 85% relative humidity and their solution droplets freeze homogeneously, the experiments demonstrate that crystalline K2SO4 can serve as INP below its deliquescence point. The absence of ice formation at higher temperatures suggests ice nucleation proceeds via homogeneous freezing within a thin layer of adsorbed water on the salt particle surface.
However, atmospheric observations show that most biomass-burning aerosol occur as mixed particles, with the potassium salt either coated by organics or attached to an organic particle (Freney, 2009). In mixed particles, ice formation could be inhibited by the uptake of water into the organic material, preventing the formation of a surface water layer. Together, these findings indicate that the ice nucleation potential of pyrogenic potassium compounds should be represented in atmospheric models in conjunction with their emission, chemical aging, and mixing state to improve the simulation of biomass-burning INPs.
This work was supported by the Academy of Finland, project MEDICEN (grant no. 345125), and the ACCC Flagship programme (grant no. 337552).
References:
Freney, E. J., et al.: Deliquescence and efflorescence of potassium salts relevant to biomass-burning aerosol particles, Aerosol Sci. Technol., 43, 799–807, 2009.
Prenni, A. J., et al.: Biomass burning as a potential source for atmospheric ice nuclei: Western wildfires and prescribed burns, Geophys. Res. Lett., 39, L11805, 2012.
Schaefer, V. J.: Relation of ice nuclei to forest fire smoke, Occasional Report, Project Cirrus, 35, 7–11, 1952.
Welti, A., et al.: SPIN modification for low-temperature experiments, Atmos. Meas. Tech., 13, 7059–7067, 2020.
How to cite: Welti, A., Alvarez Piedehierro, A., and Laaksonen, A.: Ice nucleation active potassium salt from biomass-burning smoke, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11520, https://doi.org/10.5194/egusphere-egu26-11520, 2026.
Measuring the ice-nucleating particles (INPs) that populate the upper troposphere is critical to understanding the climate impact of cirrus clouds. INPs facilitate in-situ cirrus formation and influence the size and number of ice crystals composing these clouds, as heterogeneous nucleation outcompetes homogeneous nucleation at lower supersaturation with respect to ice. The significant logistical challenges and costs associated with upper troposphere measurements render observational data for this region especially scarce. Analysis of cirrus ice crystal residues by Cziczo et al. (2013) point to heterogeneous nucleation by inorganic INPs as their dominant formation mechanism. Despite their postulated importance, very little is known about the nature and global distribution of INPs in the upper troposphere. Developing capability for routine analysis of upper troposphere INPs is therefore crucial for reducing cirrus-driven uncertainties in climate projections. Here we present our plans and progress towards a new lab-based instrument for offline analysis of INPs in cirrus cloud conditions, aimed at improving understanding of the drivers of heterogeneous ice nucleation in the upper troposphere. This custom-built isothermal diffusion chamber, based on the FRIDGE chamber design (Bundke et al., 2008; Schrod et al., 2016), is adapted to allow cirrus conditions to be accessed. Visual detection of ice growth on a substrate in the chamber will enable quantification of INPs retrieved from the upper troposphere via a balloon-borne collector. The electrostatic precipitator (ESP) for INP collection will be deployed alongside the In-situ Balloon-borne Ice Spectrometer (IBIS) which will measure cirrus ice crystal size distributions during balloon flight. Quantification and subsequent analyses of INPs made possible by the isothermal diffusion chamber development will provide new insights into the formation and evolution of cirrus clouds and their climate impacts.
References
Bundke, U., Nillius, B., Jaenicke, R., Wetter, T., Klein, H., and Bingemer, H.: The fast Ice Nucleus chamber FINCH, Atmospheric Research, 90, 180-186, 10.1016/j.atmosres.2008.02.008, 2008.
Cziczo, D. J., Froyd, K. D., Hoose, C., Jensen, E. J., Diao, M. H., Zondlo, M. A., Smith, J. B., Twohy, C. H., and Murphy, D. M.: Clarifying the Dominant Sources and Mechanisms of Cirrus Cloud Formation, Science, 340, 1320-1324, 10.1126/science.1234145, 2013.
Schrod, J., Danielczok, A., Weber, D., Ebert, M., Thomson, E. S., and Bingemer, H. G.: Re-evaluating the Frankfurt isothermal static diffusion chamber for ice nucleation, Atmospheric Measurement Techniques, 9, 1313-1324, 10.5194/amt-9-1313-2016, 2016.
How to cite: Kinney, N. L. H., Baron, A., Murray, B. J., Schwarz, J. P., and Whale, T. F.: Towards New Measurements of Ice-Nucleating Particles in Cirrus Conditions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12534, https://doi.org/10.5194/egusphere-egu26-12534, 2026.
Cloud phase feedbacks remain a major source of uncertainty in climate projections, with shallow mixed phase clouds at mid- and high-latitudes contributing substantially to this uncertainty. Poor understanding of the microphysical processes governing these clouds, particularly their ice content, and limitations in model representations of ice formation, including the frequent neglect of ice nucleating particles (INPs), are key drivers of this problem.
In this presentation we show an extensive model analysis of many aircraft flight days during the M-Phase and ACAO projects. The two projects addressed key uncertainties related to mixed-phase clouds through extensive observations of present-day shallow mixed-phase cloud environments collected during two aircraft campaigns, one over the Labrador Sea and one over the Norwegian-Barents Sea. These campaigns sampled cold air outbreak (CAO) clouds in environments characterised by differing sea surface temperatures and INP concentrations (Clarke et al., submitted to GDJ).
High resolution (1.5 km) regional simulations are performed for each case using the UK Met Office Unified Model, enabling explicit representation of convection and aerosol cloud interactions over approximately 1000 km domains with 36 hour forecasts. Model output is evaluated against aircraft and satellite observations to assess how well CAO cloud properties are represented. To investigate the role of primary ice production, model INP concentrations are varied, including using an average representation of the INP observed for each flight campaign.
The CAO cloud properties show a clear sensitivity to the prescribed INP concentrations, with consistent responses in liquid and ice water path, albedo and cloud fraction across most cases. The magnitude of this sensitivity is larger in colder Norwegian-Barents Sea CAO cases than in the warmer Labrador Sea cases. INP variability explains a larger proportion of liquid water path bias variability in Norwegian-Barents Sea CAOs than in the Labrador Sea cases, suggesting that other processes dominate liquid water path variability in the latter. The warmer Labrador Sea environment indicates a potentially greater role for secondary ice production mechanisms. Variations in the slope of the INP temperature relationship, particularly at colder temperatures, strongly influence ice production in the colder Norwegian-Barents Sea cases.
INP parameterisations that are more representative of observed conditions generally reduce the model biases compared to satellite data, although INP sensitivity alone does not account for the full range of biases, which also vary substantially from day to day due to environmental and large-scale meteorological factors along with inherent biases in satellite observations.
These results demonstrate that including more-realistic INP concentrations in simulations can improve the representation of cloud properties within CAOs, offering a potential pathway to reducing cloud phase related uncertainty in climate projections.
How to cite: Clarke, S., Huang, X., Raif, E., Tarn, M., Ashmore, D., Carslaw, K., Field, P., and Murray, B.: Sensitivity of Regional Cold-Air Outbreak Simulations to Ice-Nucleating Particle Concentrations , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10924, https://doi.org/10.5194/egusphere-egu26-10924, 2026.
Arctic low-level clouds are highly sensitive to microphysical processes, which can either sustain or break down the cloud-phase state and thereby determine the longevity of the clouds and their radiative impacts. They are influenced by aerosol particles, which can act as ice nuclei or cloud condensation nuclei, and simulating these clouds is additionally influenced by the parameterization schemes used for the aerosol-cloud interactions and the microphysical processes in the cloud.
In the presented study, we simulate a stable mixed-phase stratocumulus cloud case observed during the ship-based ARTofMELT campaign (Atmospheric rivers and the onset of Arctic melt) on 7 June 2023 with the large-eddy simulation model MIMICA-LES. The simulation is initialized by radiosoundings and constrained by ground-based remote sensing (liquid water path (LWP) and ice water path (IWP)) and aerosol measurements (aerosol size distributions, hygroscopicity, and aerosol type). We perturb the total aerosol number concentration, aerosol type, initial liquid water content (LWC), prescribed ice crystal number concentration, and ice habit to estimate the relative importance of these aerosol and microphysical parameters with respect to the modeled LWP/IWP using a factorial analysis as a statistical approach. Through factorial analysis, we can quantify the variance contribution of all parameters to LWP/IWP and quantify the interaction between different parameters. We find that ice crystal number concentration has the greatest impact on LWP and IWP, followed by the ice crystal habit, which can determine whether a cloud glaciates or not, given a fixed ice crystal number concentration. The ice habit is relatively less important, but it can determine whether a cloud glaciates or not, given fixed aerosol type and ice crystal number concentration. The results from our study can help to constrain and improve future closure studies between observations and small-scale modeling.
How to cite: Ickes, L., Frostenberg, H., Creamean, J., Thomson, E. S., Pohorsky, R., Schmale, J., Guy, H., Brooks, I., Mavis, C., Murto, S., Faure, N., Kojoj, J., Haberstock, L., and Zieger, P.: Cloud-phase sensitivity of a stable Arctic mixed-phase cloud during ARTofMELT to microphysical factors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17973, https://doi.org/10.5194/egusphere-egu26-17973, 2026.
The Arctic winter climate is characterised by multimodal radiative regimes. Two major regimes are well-documented in observational datasets across diverse Arctic regions. One is a radiatively clear regime with optically thin clouds with strong surface cooling, and another is a radiatively opaque regime characterized by optically thick, mixed-phase clouds and deep ice clouds that maintain a warm surface. The radiative opaque regime is largely driven by the presence of supercooled liquid water in mixed-phase clouds and optically thick ice in ice clouds.
Accurately capturing these regimes is essential for understanding Arctic climate and its future change; however, current reanalysis datasets, struggle to reproduce the multimodality. Analyses reveal that reanalysis often exhibits unimodal or skewed distributions of surface downward longwave radiation, failing to distinguish between the distinct clear and opaque regimes. These biases are from a systematic underestimation of the cloud liquid water path and warm temperature biases in the boundary layer, which obscure the radiative frequency peaks observed in nature.
Recent long-term analyses of in-situ data from the Atmospheric Radiation Management (ARM) North Slope of Alaska (NSA) have identified a rapid deterioration of the transmissive atmospheric radiative regime in the Western Arctic. This decline is particularly pronounced in autumn, where the frequency of clear regimes has dropped significantly over the past 25 years. It is unclear whether reanalysis dataset can capture such regime shift.
To address these discrepancies, we employ Dutch Atmospheric Large Eddy Simulation (DALES) capable of explicitly resolving small-scale turbulence and parameterising cloud with a 2-moment bulk mixed-phase microphysics. In this study, the LES is forced by large-scale reanalysis datasets and compared against long-term in-situ observations from the ARM NSA site.
How to cite: Chu, Y., de Roode, S. R., and Steinke, I.: Resolving the Arctic winter radiative multimodality: a large eddy simulation study at the north slope of Alaska, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20862, https://doi.org/10.5194/egusphere-egu26-20862, 2026.
Gravity waves (GWs) have significant effect on TTL cirrus clouds by influencing their formation and life-cycle. However, modelling such clouds in coarse resolution atmospheric models still remains a challenge since large part of the GW spectrum is not resolved and has to be parameterized. By utilizing idealized simulations of cirrus cloud formation driven by either resolved or parameterized GW dynamics, we investigate the ability of a two-moment ice scheme coupled with a GW parameterization to simulate cirrus properties. The results show that transient GW parameterizations based on ray-tracing techniques are capable of reproducing cloud structure, provided that additional phase information is incorporated in the parameterization. In coarse resolution models the statistical properties of the individual clouds populating a grid box often are represented by assuming some shape of the probability density function (PDF) for the subgrid-scale fluctuations in saturation ratio or ice water content. We estimate the parameters of the PDFs from the wave-resolving simulations and relate those to parameters from the GW parameterization. Applications of the present approach in the global ICON model are discussed.
How to cite: Dolaptchiev, S., Kosareva, A., Spichtinger, P., and Achatz, U.: Towards consistent coupling of cirrus cloud scheme with gravity wave parameterization in coarse resolution models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11443, https://doi.org/10.5194/egusphere-egu26-11443, 2026.
Cirrus clouds play a key role in the Earth’s radiation budget due to their high-altitude location, ice-only composition, and interactions with both longwave and shortwave radiation. Their radiative impact is highly sensitive to variations in ice crystal number concentration, size, and morphology, which are controlled by ice nucleation pathways and aerosol properties. Aerosol–cloud interactions (ACIs) remain one of the largest sources of uncertainty in the climate forcing, particularly through their contribution to the effective radiative forcing (ERFaci). While progress has been made over the past decades in understanding aerosol impacts on liquid clouds using satellite observations, the impact of aerosols on ice cloud formation and evolution is still poorly understood, leading to large uncertainties in the radiative forcing associated with aerosol–ice cloud interactions.
This study provides insights into aerosol-cirrus interactions by combining cirrus properties such as ice crystal number concentration (Ni) and ice water content (IWC) retrieved from the synergistic lidar-radar (DARDAR) remote sensing technique, notably the DARDAR-Nice product, with aerosol reanalysis products from the Copernicus Atmospheric Monitoring Service (CAMS). We quantified the sensitivity of cirrus parameters to aerosol concentration and subsequently infer the associated global aerosol-ice cloud radiative forcing. A variety of cloud regimes is considered to disentangle meteorological effects from the aerosol–cirrus interaction signal, including cirrus classifications based on their formation mechanisms as well as seasonal and regional bins.
How to cite: Leroux, M. and Sourdeval, O.: Quantifying aerosol-cirrus cloud interactions using reanalyses and satellite lidar-radar observations , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14778, https://doi.org/10.5194/egusphere-egu26-14778, 2026.
Persistent contrails have a significant influence on Earth's energy balance, yet their effects within existing cirrus clouds remain underexplored. This study investigates embedded contrails using observations from the HALO aircraft during the ML-CIRRUS, CIRRUS-HL, and NAWDEX campaigns, alongside lidar-radar retrieval data from the VarCloud framework. We developed an automated detection method leveraging WALES lidar parameters, focusing on particle backscatter coefficients (β(λ) > 4 Mm⁻¹ sr⁻¹) and linear depolarization ratios (δ(λ) < 30% or 43%, based on background pollution) to identify contrail regions accurately. Our results reveal that embedded contrails have a smaller ice effective radius and increased ice water content in affected cirrus clouds by aviation, indicating that they can significantly modify the microphysical properties of cirrus clouds. This understanding is essential for evaluating the climate impact of aviation and for enhancing detection techniques in spaceborne observations, such as those from the EarthCare satellite.
How to cite: Soleimanpour, M., Seelig, T., Groß, S., and Tesche, M.: Observation of In-Cirrus Contrail Properties Using Airborne Lidar-Radar Remote Sensing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1636, https://doi.org/10.5194/egusphere-egu26-1636, 2026.
Cirrus clouds having a high degree of spatially heterogeneous/inhomogeneous cloud properties have been shown to correspond with increased wave activity (e.g., Podglajen et al., 2018) and increased uncertainty in remote sensing retrievals (Fauchez et al., 2015, 2018); and incorporating cirrus cloud spatial heterogeneity/inhomogeneity into climate models has been shown to improve simulated output (e.g., Gu and Liou, 2006). These findings highlight the importance of evaluating spatial heterogeneity/inhomogeneity globally, which may provide information of common evolutionary pathways of cirrus clouds. However, relatively few studies have evaluated the spatial heterogeneity and inhomogeneity (often used interchangeably) of cirrus properties, which have primarily been case studies derived from relatively small datasets. Further, such studies often evaluate macro-scale properties such as optical thickness or cloud fraction rather than leveraging high resolution, airborne in situ measurements.
We evaluate the spatial heterogeneity and inhomogeneity of cirrus bulk microphysical properties using ~65 hours of in situ measurements from eight field campaigns taking place in different regions globally. The spatial heterogeneity of ice concentration (ice water content) increases with decreasing ice concentration (ice water content), revealing more tenuous cirrus are more spatially heterogenous. This is suspected to be due to a greater competition amongst ice crystals for available water vapor within thin, in-situ formed cirrus (i.e., cirrus formed directly at temperatures below ~-38°C) compared with thicker, liquid-origin cirrus (i.e., cirrus formed via freezing of rising liquid or mixed phase clouds) which have an abundant amount of available water vapor. This is also a positive finding, since previous modeling work has shown that retrieval uncertainties associated with cirrus heterogeneity are greatest for optically thick cirrus (Fauchez et al., 2015).
Cirrus clouds often contain sets of ice concentration samples whose distributions are heavily skewed. These “heavily skewed” (i.e., more inhomogeneous) clouds also tend to possess higher spatial heterogeneity than “weakly/non-skewed” (i.e., less inhomogeneous) clouds. This skewness results from the absence of small ice crystals (diameter<~50 µm) within localized regions of the cirrus clouds. Clouds having heavily skewed distributions are observed ~20%–40% of the time in each flight campaign, suggesting the ubiquity of temperature perturbations preferentially removing small ice and/or the kelvin effect within cirrus clouds globally.
Bibliography:
Fauchez, T., Dubuisson, P., Cornet, C., Szczap, F., Garnier, A., Pelon, J., and Meyer, K.: Impacts of cloud heterogeneities on cirrus optical properties retrieved from space-based thermal infrared radiometry, Atmospheric Measurement Techniques, 8, 633–647, https://doi.org/10.5194/amt-8-633-2015, 2015.
Fauchez, T., Platnick, S., Sourdeval, O., Wang, C., Meyer, K., Cornet, C., and Szczap, F.: Cirrus Horizontal Heterogeneity and 3-D Radiative Effects on Cloud Optical Property Retrievals From MODIS Near to Thermal Infrared Channels as a Function of Spatial Resolution, Journal of Geophysical Research: Atmospheres, 123, 11,141-11,153, https://doi.org/10.1029/2018JD028726, 2018.
Gu, Y. and Liou, K. N.: Cirrus cloud horizontal and vertical inhomogeneity effects in a GCM, Meteorol. Atmos. Phys., 91, 223–235, https://doi.org/10.1007/s00703-004-0099-2, 2006.
Podglajen, A., Plougonven, R., Hertzog, A., and Jensen, E.: Impact of gravity waves on the motion and distribution of atmospheric ice particles, Atmospheric Chemistry and Physics, 18, 10799–10823, https://doi.org/10.5194/acp-18-10799-2018, 2018
How to cite: Dalessandro, J., Sourdeval, O., and Krämer, M.: The spatial heterogeneity and inhomogeneity of cirrus microphysical properties evaluated globally using in situ measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12426, https://doi.org/10.5194/egusphere-egu26-12426, 2026.
Cirrus clouds, composed of pure ice crystals and forming in the upper troposphere, are particularly challenging to characterize because of their complex microphysics and diverse growth processes. Satellite observations capture only snapshots of cirrus cloud properties, offering limited insight into cloud history. Here, we present DC-Ice, which combines satellite observations and Lagrangian microphysical modelling to trace the history of air parcels contributing to cirrus cloud formation. The Chemical Lagrangian Model of the Stratosphere (CLaMS) is employed to trace air-parcel trajectories along the DARDAR-Nice track, along which cirrus cloud formation and evolution are simulated using the CLaMS-Ice microphysical model. Satellite observations are complemented with origin-based metrics describing ice formation pathways (homogeneous vs heterogeneous), ice crystal origin (liquid-phase or in-situ), and the time since ice formation.
DC-Ice is applied to three representative midlatitude cirrus cases spanning fast updrafts, slow updrafts, and orographically driven conditions. Air parcel histories and reconstructed vertical profiles along the satellite track are used to identify distinct phases of the cirrus life cycle and the distribution of origin-based metrics across cloud layers. Modelled microphysical properties are statistically evaluated against satellite retrievals. In addition, a series of sensitivity experiments assesses the influence of key CLaMS-Ice input parameters, including small-scale temperature fluctuations, environmental ice-nucleating particle (INP) concentrations, and sedimentation parameterizations. Taken together, this framework adds a process-based context to satellite observations and supports a more comprehensive understanding of cirrus cloud origins and their role in the climate system.
How to cite: Saiprakash, A., Krämer, M., Rolf, C., Riedi, J., and Sourdeval, O.: Tracing cirrus cloud formation history using satellite observations and Lagrangian trajectories, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19583, https://doi.org/10.5194/egusphere-egu26-19583, 2026.
The dominant ice nucleation regime, whether homogeneous or heterogeneous, governs the microphysical structure and radiative properties of cirrus clouds. While ground-based observations demonstrate that the long-range transport of wildfire smoke can effectively trigger heterogeneous nucleation in the upper troposphere and lower stratosphere, these studies remain spatially limited. A systematic, global-scale approach is required to identify the broader impacts of smoke on cirrus occurrence and properties.
In this study, we perform a closure analysis by linking potential ice-nucleating particles (INPs) with in-cloud ice crystal number concentrations (ICNC) using spaceborne remote sensing. We retrieve potential smoke INPs from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) level 2 V4.51 data products and compare them with in-cloud ICNC derived from the DARDAR-Nice (liDAR–raDAR-Number concentration of ICE particles) product. By examining the consistency between these two independent datasets across a decade of observations, we can evaluate the extent to which wildfire smoke triggers heterogeneous ice nucleation across different latitudes and seasons. This research provides a global dataset offering the large-scale observational constraints necessary to bridge the gap between local process studies and the representation of smoke-cirrus interactions in global climate models.
How to cite: Georgakaki, P., Papanikolaou, C.-A., Sourdeval, O., and Quaas, J.: Spaceborne Insights into Wildfire-Induced Cirrus Cloud Formation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14711, https://doi.org/10.5194/egusphere-egu26-14711, 2026.
When aircraft exhaust mixes with cold air, it forms an ice cloud: a contrail. If the ambient conditions are dry the contrail is transient, meaning that the ice crystals sublimate during mixing, in the first minutes after emission. Conversely, in humid air the contrail can persist and contribute a significant warming radiative forcing. Errors that are present in weather data therefore make contrails (and aviation's climate impact) hard to model. More humidity observations are needed to reduce model errors in this part of the atmosphere. The observation of persistent contrails implies the presence of ice-supersaturated regions. In this study, we establish the potential to extend these opportunistic observations using measurements of transient contrails, enabling direct measurement of relative humidity with respect to ice.
A refined contrail jet phase bulk microphysics model is compared to ground camera detection and measurement of contrails immediately behind aircraft. Contrails are detected over an all-sky camera in Palaiseau, France using a cross-track peak detection methodcombining ADS-B aircraft positions and winds derived from aircraft-reported data. Around 5% of daytime overhead aircraft lead to a contrail detection (either transient or persistent). However, many contrails go unobserved. This observability limitation is evident when focusing on those aircraft that fly in air satisfying the Schmidt–Appleman temperature threshold condition, for contrail formation. The condition is satisfied in more than 99% of the observations where a contrail is detected, but fewer than 10% of observations behind aircraft where this condition is satisfied yield a detection. Invariably, this is due to natural cloud or the artefact being too faint or small to be detected using the current instrument and method.
We demonstrate that temperature and relative humidity with respect to ice are the main controls on observed transient contrail lifetime. The model reproduces this dependence, though the introduction of a mixing model hybridising the core and bulk plume is critical to constrain this process. This result provides a foundation to infer the relative humidity directly, without requiring new sensors. Some limitations of the observing system remain to be overcome: higher resolution cameras, detection algorithms robust to advection error and understanding the conditions for observability would improve the method accuracy. On top of this, the clear-sky conditions required to detect transient contrails are relatively infrequent, which is an external limitation that must be understood. Nonetheless, these resultshighlight a new pathway to infer the humidity in a part of the atmosphere where accuracy is valuable, but models are insufficiently constrained.
How to cite: Driver, O., Ponsonby, J., Gourgue, N., Boucher, O., Stettler, M., and Gryspeerdt, E.: Transient contrails as an opportunity for upper tropospheric humidity estimation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20695, https://doi.org/10.5194/egusphere-egu26-20695, 2026.
This work presents a modification of the Smith (1990) cloud scheme used in the ARPEGE (Action de Recherche Petite Echelle Grande Echelle) NWP global model in order to improve the forecast of relative humidity with respect to ice, with particular attention paid to supersaturation, a necessary condition for the persistence of aviation contrails. The modeling extends the Smith cloud scheme used in the operational ARPEGE by reworking the statistical concepts of Sommeria and Deardorff (1977) while including a temperature-based parametrization for the representation of homogenous nucleation. A notable point is that this modification can be implemented without major changes and does not require additional computational effort. Furthermore, it allows for extensions to other atmospheric models using a similar framework. The new forecasts are verified using in situ humidity observations made by IAGOS program aircraft and compared to ARPEGE operational forecasts, resulting in a better description of supersaturated regions. Further impacts on other general parameters (wind, temperature) are also presented in this study.
How to cite: crispel, P., arriolabengoa, S., bouteloup, Y., and plu, M.: A modification of the Smith cloud scheme to allow supersaturation with respect to ice in the ARPEGE NWP global model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12598, https://doi.org/10.5194/egusphere-egu26-12598, 2026.
During the ORCESTRA/MAESTRO field campaign, the recurrent, and somewhat unexpected, presence of mid-level clouds was documented in both in-situ and remote sensing observations. These clouds, most predominantly of the altocumulus type, are still poorly understood in terms of their formation mechanisms, and constitute a major challenge for numerical weather prediction and general circulation models, which often struggle against the representation of their mixed-phase composition. In addition, mid-level clouds can perturb the individual shortwave and longwave components of the radiation budget. However, their role in the mesoscale organization of convection, and more generally in climate, is not established yet.
The data from the campaign, including airborne measurements from the ATR-42 research aircraft and radiosoundings conducted at Sal, Cape Verde, represent an excellent framework to help address the questions related to tropical mid-level clouds. We analyze case studies of altocumulus cloud occurrence in order to characterize the conditions of the environment in which they formed as well as their microphysical properties. Relatively deep conditionally unstable layers are found at and below the cloud level, and the cloud is often capped by a strong inversion likely driven by cloud top radiative cooling. Furthermore, there is evidence that the cloud layer is organized into sub-kilometer-scale cells composed of alternating updrafts and downdrafts. The mixed-phase nature of the cloud is confirmed, with a thin supercooled liquid layer at the top, and solid and liquid hydrometeors falling underneath. Based on preliminary results, possible mechanisms responsible for altocumulus formation and maintenance are discussed.
How to cite: Biagioli, G. and Bony, S.: Tropical altocumulus cloud observations during the ORCESTRA/MAESTRO field campaign, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23098, https://doi.org/10.5194/egusphere-egu26-23098, 2026.
The interaction and settling of ice crystals and other hydrometeors inside turbulent cloud environment plays a crucial role in modelling the Earth’s radiation budget as well as it gives rise to certain distinctive optical phenomena such as sundogs and light pillars. Understanding the orientation distribution of ice crystals inside clouds also plays a crucial role in accurately designing certain remote-sensing equipment. In this study, we investigate the interaction dynamics of two columnar ice crystal settling under the action of gravity in a background turbulent flow resembling the cloud environment. The ice crystals are considered to be like-charged as can be observed in the upper parts of deep convective as well as mixed-phase clouds. The columnar ice crystals are modelled using the slender body theory, to capture the hydrodynamic interaction between them in a turbulent background flow. The effect of background turbulence is incorporated using a stochastic model which can predict the statistical behaviour of the turbulent velocity gradients. Based on this, we have predicted the probability density function of the orientations of the settling ice crystals. Furthermore, we also study how the electrostatic forces modify the settling trajectories and orientation distribution of the ice crystals. Our results indicates that the electrostatic forces and background turbulence significantly affects the orientation distribution of the columnar ice crystals, providing key insights into the microphysical behaviour of ice crystals inside clouds.
How to cite: Choudhury, A. and Roy, A.: Interaction and orientation dynamics of charged columnar ice crystals settling in clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-997, https://doi.org/10.5194/egusphere-egu26-997, 2026.
Mixed-phase clouds consist of both supercooled cloud-liquid and ice particles. They are influential for the Earth’s radiation budget. Snow reaches the ground typically from mixed-phase nimbostratus cloud. For humanity, deep snowfalls are influential as they cause much disruption (e.g. to transportation), with a cost of billions of euros annually .
Both the warm rain (coalescence) and ice crystal (vapour growth of crystals, perhaps followed by aggregation) processes of precipitation can co-exist in mixed-phase clouds. A cloud base that is not too warm, depending on aerosol conditions, is typically needed for the ice crystal process to prevail in precipitation production, because otherwise an abundance of cloud-liquid mass can promote coalescence before parcels become supercooled, as with deep tropical convective clouds.
Our theory published in 2024 explained why any competition between both cold and warm processes of precipitation in mixed-phase clouds tends to be won by the ice crystal process. Since the fall-out of snow is slow, boosting its mass aloft, and its low bulk density creates a wide cross-sectional area for riming, the supercooled cloud-liquid mass is kept weak by the ice crystal process. This then reinforces the ice crystal process by minimizing the liquid water content, favouring snow production.
The question of why snow reaches the ground, whether intact or as a melted drop, is partly related also to the issue of why graupel or hail is not produced instead. Snow may rime to produce graupel or hail. Precipitation particles tend to be defined by the intensity of the ascent. Snow particles are balanced against stratiform ascent (< 1 m/s) as it is comparable to their fall-speeds. This is partly why nimbostratus produces deep snowfalls. Graupel/hail tends to fall much faster. But also wintertime deep convection can produce snow at the ground, as sometimes seen in thunderstorms near the Sea of Japan.
On this topic, Steiner and Smith in 1998 theorized that there is a phase-space of in-cloud vertical velocity and temperature in which a region of predominant riming and supercooled cloud-liquid exists in a ‘wedge’ within the convective ascent. Steiner and Smith argued that predominant aggregation for snow is restricted to weak stratiform ascent since at faster convective ascent there is predominant riming.
In this presentation we analyse with a single-crystal growth model the conditions of ascent and temperature determining whether snow or graupel fall out from the mixed-phase region. The model predicts the evolution of a crystal growing first by diffusional growth in various habits and then by aggregation of crystals and riming, with the chance of becoming either graupel or hail. We reproduce the wedge in the phase-space by Steiner and Smith, and analyse contributions from aggregation, sticking efficiency and riming. It is predicted that repeated recirculation cycles and aggregation of crystals by snow is needed to explain the wedge.
In summary, snow reaches the ground partly because the ice crystal process tends to prevail in mixed-phase clouds, while aggregation of ice crystals and related processes (e.g. habit-dependent sticking efficiency) in weak ascent combine to prevent snow from becoming graupel/hail.
How to cite: Phillips, V.: A Theory for Why Some Clouds Produce Snow , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21090, https://doi.org/10.5194/egusphere-egu26-21090, 2026.
As part of the Climaviation project, which is funded by the French Direction Générale de l’Aviation Civile (DGAC) aiming to quantify the non-CO2 effect of civil aviation in the warming climate, this study aims to characterise the optical, macro and microphysical properties of contrails at the SIRTA observatory in Palaiseau, France. To detect contrail occurrence over the site, a co-localised instrumental synergy comprising the IPRAL Lidar (a multi-longwave lidar), a total sky camera, Sentinel-2 satellite data, and aircraft flight altitudes is used. The particular integration method is applied to the lidar backscatter coefficient to estimate the optical depth of contrails after their geometrical characteristics (base height and thickness) have been defined. The optical depth estimated with this method is validated using a CIMEL sun-photometer. The Trappes radiosoundings are used to characterise the atmospheric conditions in with the contrails form. The colour ratio and the volume and particle depolarisation ratios from the analog and photo counting signals are used to qualitatively estimate the crystal size distributions within the contrails. An analysis of ten identified contrails observed on 5 July 2019, will be presented.
How to cite: Dione, C., Dupont, J.-C., Caillault, K., Haeffelin, M., Lapouge, F., and Delville, P.: Demonstrating the capability of instrumental synergy to characterize contrails at the SIRTA observatory in Paris, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17837, https://doi.org/10.5194/egusphere-egu26-17837, 2026.
Accurate representation of ice crystal shapes is critical for simulating polarized radiance and improving radiative transfer in climate and weather models. In this study, we systematically developed a database of 1071 super-ellipsoidal ice crystals covering a broad range of aspect ratios, roundness, and surface roughness, and used POLDER-3/PARASOL polarized radiance observations from 2009 to identify optimal shapes and roughness parameters and obtain a mixed super-ellipsoidal scheme across latitude bands. Based on these results, we evaluated a mixed super-ellipsoidal scheme against traditional single-habit particles from the TAMUice2016 database (e.g., Plate, 5-Plate, 8-Column) using 2012 observations. Conventional single-habit models exhibit varying performance across latitude bands, often underestimating or overestimating polarized radiance in specific regions. In contrast, the mixed super-ellipsoidal models demonstrate consistently higher correlations and lower RMSE, with robust performance across wavelengths and latitudes. These results indicate that observationally constrained mixed super-ellipsoidal scheme provides a flexible framework for ice cloud representation in radiative transfer simulations, paving the way for improved studies in microphysics and polarization-based retrievals.
How to cite: Meng, Y., Bi, L., and Sun, L.: Optimizing Ice Cloud Representations with a Mixed Super-ellipsoidal Scheme using Polarized Radiance Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19359, https://doi.org/10.5194/egusphere-egu26-19359, 2026.
Retrievals of ice precipitation from remote sensing measurements rely on a priori assumptions about particle mass and size within the sampling volume. Such a priori information typically includes a particle size distribution (PSD) and a mass-dimensional relation, m-D, where m is mass and D is the maximum dimension (or diameter). In situ measurements of ice particles from either airborne or ground-based imaging probes inform these assumptions. Owing to limited information about a particle‘s three-dimensional structure from probes with few independent view angles, estimates of the particle’s mass and size (D) based on these instruments are highly uncertain and systematically biased in D. Quantification of the uncertainty in the derived m-D relations is also challenging due to the lack of direct mass and D measurements, making it difficult to quantify the uncertainty of remote-sensing precipitation retrievals.
Using a database of physically plausible three-dimensional ice particle structures, we develop a framework to estimate particle size, mass, and other physical properties from a variety of different imaging probe configurations. The simulated probe configurations we use include those containing a single projection, two orthogonal projections, three orthogonal projections, and up to 13 projections at the nodes of a Lebedev spherical quadrature scheme. We simulate two-dimensional binary images of the particles at each projection and train machine-learning models to estimate the particle size and mass. To provide direct estimates of the uncertainty for each probe configuration, the machine learning models are trained to predict distributions of the size and mass.
The predictions of mean mass and size from the machine learning models increase in accuracy as the number of view angles increases, with greater improvements between the single-view and two-view configurations then between that and the three-orthogonal-view configuration. The uncertainty in mass decreases between the single and three-view models but remains relatively constant for the configurations using more than three views. Calculations of the spherical effective density based on the model predictions show favorable correspondence with the true spherical effective density of the particles, suggesting that the models largely capture the covariance between mass and size of the true particle shapes.
These probabilistic estimates of mass and size are then used to retrieve samples of m-D relation coefficients for a subset of particles corresponding to a known m-D relation. To estimate the impact of the uncertainty in the retrieved m-D relation has on precipitation retrievals, we compare the ice water content (IWC) for the known m-D relation using a variety of PSDs and the retrieved m-D relation samples from each probe configuration. The errors in IWC decrease with increasing numbers of view angles, with smaller reductions in error for configurations with more than three view angles. Future areas of improvement in the machine-learning models, as well as how the errors in m-D retrievals from imaging probes impact the downstream uncertainty in remote sensing retrievals will also be discussed.
How to cite: Schrom, R. and Kuo, K.-S.: Machine-learning based estimates of mass-dimensional relations from simulated in situ imaging probes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22103, https://doi.org/10.5194/egusphere-egu26-22103, 2026.
Accurate estimates of ice crystal mass are essential for reducing uncertainties in cloud radiative forcing and precipitation forecasts. Ice crystal mass can be derived from imaging cloud probes using power-law mass–diameter (m-D) relationships. However, these often do not account for variability in crystal habit, leading to significant biases in ice water content (IWC) retrievals and complicating the comparison between in-situ observations and numerical models.
To address this, we developed a shape-aware m-D parameterization by explicitly incorporating the aspect ratio (AR) into a power-law framework. The parametrization is fitted using data from the CLOUDLAB campaigns, which use glaciogenic seeding to induce ice formation in supercooled stratus clouds. This experimental setup allows for two total water content (TWC) conservation assumptions: (i) the temporal stability of the stratus clouds allows to use the TWC of the unseeded cloud as a reliable baseline for the seeded section., and (ii) the introduction of ice crystals via seeding does not alter the TWC, even as the Wegener–Bergeron–Findeisen process redistributes mass from the liquid to the ice phase. Using data from 20 seeding experiments, we optimized the m-D parameters by minimizing the difference between seeded and the baseline TWC using a loss function based on the Wasserstein distance to ensure that the probability distribution of the derived TWC match the observed variability of the background cloud.
The resulting parameterization m = 0.0487 D2.045 / AR2 aligns well with existing m-D relationships but predicts lower ice crystal masses for high aspect ratios. When applied to the CLOUDLAB data, the formula successfully removes systematic overestimations in ice mass across various temperatures and growth stages. While riming and aggregation were only weakly present in our dataset, they did not lead to significant deviations. This study provides a shape-aware m-D formulation suitable for bulk microphysics schemes and demonstrates a robust, data-driven framework for constraining cloud parameters using field measurement from cloud seeding experiments.
How to cite: Jan, H., Zhang, H., Fuchs, C., Miller, A. J., Omanovic, N., Spirig, R., and Lohmann, U.: A Shape-Aware Mass–Diameter Parameterization for Ice Crystals Constrained by Glaciogenic Seeding Experiments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8217, https://doi.org/10.5194/egusphere-egu26-8217, 2026.
Posters virtual: Mon, 4 May, 14:00–18:00 | vPoster spot 5
EGU26-6493 | Posters virtual | VPS2
A framework for modeling aerosol-cloud-lightning interactions: Validation of charge structure and aerosol effectsMon, 04 May, 14:21–14:24 (CEST) vPoster spot 5
This study develops a novel framework within the Weather Research and Forecast Model for modeling aerosol-cloud-lightning interactions. The framework explicitly represents aerosol-cloud interactions by prescribing aerosols with two configurations: an idealized setup, where both cloud condensation nuclei (CCN) and ice nucleating particles (IN) are assumed to have a single chemical composition and spatially uniform distributions; and a quasi-realistic configuration, with multi-species aerosols assigned spatially varying distributions, where hygroscopic components act as CCN, dust particles act as IN, and all aerosol species influence radiative transfer. Cloud microphysics is coupled with detailed charge separation and discharge processes to enable the lightning simulation. The framework is evaluated using two thunderstorms in Guangdong, China. For an isolated storm, the model successfully reproduces the observed tripolar charge structure (positive–negative–positive), demonstrating its capability in simulating cloud electrification. For a frontal storm, it captures well the observed precipitation and lightning, and shows that increasing CCN suppresses the rainfall while enhancing the lightning. Higher CCN concentrations produce more numerous but smaller cloud droplets, which suppresses the coalescence into rain droplets, allows a greater number of droplets to loft into the upper troposphere, and forms more but smaller cloud ice particles. This boosts graupel–ice collisions, intensifies non-inductive charging, strengthens the upper positive charge and the vertical electric-field gradient, ultimately increasing the lightning frequency. In contrast, no significant aerosol-induced invigoration of updrafts is observed. These results highlight the dominant role of aerosol microphysical effects over dynamical invigoration in modulating thunderstorm electrification and lightning activity.
How to cite: Wang, W., Chen, G., and Zhang, Y.: A framework for modeling aerosol-cloud-lightning interactions: Validation of charge structure and aerosol effects, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6493, https://doi.org/10.5194/egusphere-egu26-6493, 2026.
