Session assets
How to cite: Schimmel, W., Senf, F., Stoll, J., Ohneiser, K., Seifert, P., Henneberger, J., Lohmann, U., Spirig, R., Ramelli, F., Fuchs, C., Miller, A., Zhang, H., and Omanovic, N.: Combined Remote-Sensing, In-Situ and Modelling of Cloud Microphysical Perturbations in Supercooled Stratus Clouds, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12739, https://doi.org/10.5194/egusphere-egu25-12739, 2025.
The ice phase is a major contributor to precipitation formation over continents, as ice hydrometeors efficiently grow to large enough sizes for them to sediment. Several mechanisms underlie the growth of ice crystals, with one being the growth through vapor deposition onto the ice crystal. The speed of this growth depends next to temperature also on the availability of water vapor, one source being cloud droplets in mixed-phase clouds that locally may experience water-subsaturated conditions. This is referred to as the Wegener-Bergeron-Findeisen (WBF) process and describes the ability of ice crystals to grow at the expense of cloud droplets. While the presence of the WBF process is established, the actual growth rates of ice crystals in such conditions remain ambiguous. We conducted field experiments within the CLOUDLAB project with the goal to infer ice crystal growth rates in naturally occurring supercooled clouds through local perturbations from cloud seeding. A unique dataset was collected describing the characteristics of cloud droplets and ice crystals in the probed clouds, including their sizes, number concentrations, and ice and water contents.
Here, we combine large-eddy simulations (LES) in 65 m horizontal resolution with online Lagrangian trajectories to achieve a more straightforward comparison to our observations. We show that the model simulations can reproduce the field experiments in terms of ice crystal number concentrations. However, both the simulated changes in the liquid phase as a consequence of the WBF process and the ice crystal growth rates are underestimated compared to the observations. We perform a series of sensitivity studies on the vapor depositional growth equation of ice crystals given the uncertainty and simplification of two parameters of that equation. We find that an increase of the vapor deposition efficiency up to a factor of three achieves comparable growth rates. However, matching growth rates in the model and observations does not lead to coinciding changes in the liquid phase, i.e., the WBF process remains too slow. We identify two limitations of our approach: (i) the simulated and actual water vapor fields may differ and (ii) our LES are still too coarse to fully capture the small-scale interactions between the liquid and ice phases. This study highlights the synergy of high-resolution model simulations and field observations for investigating a fundamental cloud process. Our results provide insights for future mixed-phase cloud modeling studies.
How to cite: Omanovic, N., Ferrachat, S., Fuchs, C., Ramelli, F., Henneberger, J., Miller, A. J., Spirig, R., Zhang, H., and Lohmann, U.: Chasing ice crystals: Lagrangian trajectories in ICON-LES for investigating liquid and ice phase interactions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6543, https://doi.org/10.5194/egusphere-egu25-6543, 2025.
Clouds remain a major source of uncertainty in climate projections, particularly due to complexities in aerosol-cloud interactions. To improve the representation of mixed-phase clouds in EC-Earth3, the model's heterogeneous ice nucleation scheme has been updated. The previous temperature-based parameterization has been replaced with aerosol- and temperature-sensitive immersion freezing schemes for mixed-phase clouds that consider ice-active desert dust minerals (K-feldspar and quartz) and marine organic aerosols, both explicitly tracked in EC-Earth3. Additionally, a secondary ice production scheme based on a random forest regressor further enhances the ice crystal concentrations.
The updated model is evaluated against an extensive observational dataset of ice-nucleating particle (INP) concentrations, satellite observations of cloud properties (MODIS and CALIPSO), and both Top of the Atmosphere (TOA) and surface radiative Cloud Radiative Effect (CRE) flux components from CERES-EBAF. The impact of the updates is analysed relative to the previous temperature dependent parameterization.
Results from 12-year (2009-2020) nudged simulations show improved agreement with INP observations using the updated aerosol-aware scheme compared to the earlier approach. The ice nucleation parameterization clearly links simulated ice crystal number concentrations with aerosol emission sources and transported pathways. Despite remaining biases largely attributed to other processes, this update improves consistency with MODIS and CALIPSO retrieved data, including total cloud cover, low/mid/high cloud area percentages, liquid and ice cloud fractions, and water paths. Sensitivity analyses reveal that the new scheme impacts global cloud cover, liquid and ice water content, temperature, and radiative balances. Evaluation with CERES-EBAF indicates that the new parameterization reduces surface net CRE bias at mid-to-high latitudes while slightly increasing bias at low latitudes, despite no specific model tuning for this configuration.
Our approach offers potential enhancements in future climate projections using EC-Earth3-AerChem and future generations of the model.
How to cite: Costa-Surós, M., Gonçalves, M., Chatziparaschos, M., Georgakaki, P., Myriokefalitakis, S., Van Noije, T., Le Sager, P., Kanakidou, M., Nenes, A., and Pérez García-Pando, C.: Aerosol-Driven Parameterization of Ice Nucleation and Secondary Ice Processes in EC-Earth3: Evaluation and Climate Impacts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16830, https://doi.org/10.5194/egusphere-egu25-16830, 2025.
Secondary ice production (SIP) refers to a series of physical mechanisms that significantly increase ice number concentrations above those from primary ice production (PIP) via ice nucleating particles (INP). In-cloud observations have provided increasing evidence of SIP in mixed-phase stratiform and convective clouds at different latitudes. The presence of fragmented frozen drops and small columnar particles in measurements from holographic particle imaging systems is consistent with findings of laboratory experiments focused on rime splintering (RS), droplet shattering (DS), and ice-ice collisional breakup (IIBR) mechanisms. Since SIP rates are driven by the relative size of interacting hydrometeors, there is a need to understand which microphysical conditions trigger which mechanism in realistic atmospheric conditions where cloud micro physics are constrained by aerosols. Without describing aerosol-hydrometeor interactions, the majority of cloud modelling tools are limited to prescribed size distributions and process rates that may fail giving proper description of ice formation via primary and secondary pathways missing important links to others such as secondary activation and aerosol invigoration.
In this study we offer insights on aerosol-induced effects on SIP rates by coupling results from aerosol-aware large-eddy- simulations and in-cloud observations of a deep convective cloud case studied in the SPICULE campaign in the Southern Great Plains (USA) on June 05 2021. We employed UCLALES-SALSA, an LES model with sectional representation of aerosol microphysics to resolve rates for PIP via immersion freezing with time evolving contact angle distribution and SIP via droplet shattering (DS), and ice-ice collisional breakup (IIBR). After model initialization with observed atmospheric soundings and aerosol concentrations, we were able to reproduce observed trends in cloud properties including boundaries and vertical profiles of droplet and ice particle size distributions. The model was able to emulate the observed ice multiplication in the rising cloud tower indicating a positive feedback between SIP-DS and SIP-IIBR processes which in turn increased convection intensity through mixed-phase invigoration at the upper level and finally lead to glaciation and precipitation via seeder-feeder mechanism. Both, the convective available energy (CAPE) and the level of neutral buoyancy (LNB), were adjusted to reach model closure in the cloud tower. We also compared simulations differing in the aerosol number concentration in the accumulation mode used for model initialization and found that increasing fine particle concentrations increase ice formation and updraft strength above freezing level suggesting that mixed-phase invigoration has an role in cloud phase structure and glaciation of convective clouds.
How to cite: Romakkaniemi, S., Raatikainen, T., Kokkola, H., Lawson, P., and Calderón, S.: Aerosol effects on Secondary Ice Production in Deep ConvectiveClouds: exploiting the synergistic benefit of observations andaerosol-aware cloud simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9155, https://doi.org/10.5194/egusphere-egu25-9155, 2025.
Warm conveyor belts (WBCs) are large-scale ascending airstreams found in extratopical cyclones. They constitute a major source of upper tropospheric/lower stratospheric (UTLS) water vapor—a potent greenhouse gas—and hydrometeors, which can form cirrus clouds. Therefore, WCBs play an important role for Earth’s radiative budget. Additionally, WCBs transport large amounts of heat across latitudes and can influence large scale upper tropospheric circulation after their dissipation, underscoring their significance for Earth’s weather and climate.
Recent studies using high-resolution, convection-permitting simulations have shown that convection is a prominent feature of WCBs, with convective air parcels transporting significantly more hydrometeors into the UTLS than their slower-ascending counterparts. Furthermore, the cloud and precipitation development in convective air parcels is dominated by different processes than in slower ascending air. However, the global numerical weather prediction and climate models commonly used to assess the climatological and future impacts of WCBs operate at coarse grid resolutions (15–50 km) that are not convection-permitting, relying instead on convection parametrization schemes. The widely used Tiedtke-Bechtold convection parameterization scheme is designed to simulate heat, moisture, and momentum transport in convective systems but includes only basic representations of cloud microphysics. This raises the question of whether low-resolution simulations fail to accurately represent the transport of hydrometeors into the UTLS by WCBs when compared to high-resolution, convection-permitting simulations.
To address this, we analyze two simulations of the same WCB—one convection-permitting and one using convection parameterization—with a specific focus on vapor and hydrometeor transport. Our results show that the WCB in the high-resolution simulation transports substantially larger amounts of hydrometeors into the UTLS, while UTLS vapor conditions remain comparable between the two simulations. Microphysics processes also shift from liquid-dominated to frozen-dominated depending on the grid-scale.
How to cite: Schwenk, C. and Miltenberger, A.: How does Model Grid Resolution Influence Mixed-Phase Processes and UTLS Moisture Transport by a WCB?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4261, https://doi.org/10.5194/egusphere-egu25-4261, 2025.
Representing the glaciation of mixed-phase clouds in terms of the Wegener-Bergeron-Findeisen process is a challenge for many weather and climate models, which tend to overestimate this process because cloud dynamics and microphysics are not accurately represented. As turbulence is essential for the transport of water vapour from evaporating liquid droplets to ice crystals, we developed a statistical model using established closures to assess the role of small-scale turbulence. The model successfully captures results of direct numerical simulations, and we use it to assess the role of small-scale turbulence. We find that small-scale turbulence broadens the droplet-size distribution somewhat, but it does not significantly affect the glaciation time on submetre scales. However, our analysis indicates that turbulence on larger spatial scales is likely to affect ice growth. While the model must be amended to describe larger scales, the present work facilitates a path forward to understanding the role of turbulence in the Wegener-Bergeron-Findeisen process. This talk is based on arXiv:2410.06724 which is joint work with G. Sarnitsky, G. Sardina, G. Svensson, A. Pumir, and F. Hoffmann.
How to cite: Mehlig, B., Sarnitsky, G., Sardina, G., Svensson, G., Pumir, A., and Hoffmann, F.: Does small-scale turbulence matter for ice growth in mixed-phase clouds?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15500, https://doi.org/10.5194/egusphere-egu25-15500, 2025.
One of the sources of uncertainties in climate models and numerical weather prediction (NWP) models is cirrus clouds. They are highly sensitive to subgrid-scale dynamics, such as gravity waves (GWs) and turbulence, making them challenging to model in detail within coarse-resolution settings. Additionally, their net radiative effect remains poorly understood, highlighting the importance of accurately representing their microphysical properties as one of the main areas of focus for research and model refinement.
The current work focuses on a coupled approach to GW–ice microphysics interactions and its application in the global NWP model ICON. The ice scheme, developed by Dolaptchiev et al. (J. Atmos. Sci., 2023), describes GW-induced homogeneous nucleation of ice crystals and proposes a prototype parameterization used in this study. The representation of a local GW field is diagnosed using the Multi-Scale Gravity Wave Model (MS-GWaM) parameterization. MS-GWaM parameterization supports multiple GW source types, and allows for 3D GW propagation, enhancing its physical realism. The full coupling of GW forcing, along with feedback from the new scheme into the overall microphysics and radiation schemes, has been implemented in a test regime in ICON model.
To validate the approach and assess the impact of GWs, several global ICON simulations were conducted. The results show a significant influence of GWs on ice number density, indicating higher concentrations of ice crystals in tropical regions. These findings highlight the potential of the coupled approach to improve predictions of cloud microphysics and their radiative impacts. Further investigations will explore the role of different GW sources and account for the superposition of GWs, offering deeper insights into the broader effects of GW representation on global atmospheric processes.
How to cite: Kosareva, A., Dolaptchiev, S., Seifert, A., Spichtinger, P., and Achatz, U.: Detailed coupled approach to ice particles nucleation induced by gravity waves in a global NWP model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11347, https://doi.org/10.5194/egusphere-egu25-11347, 2025.
Ice crystals in mixed-phase clouds (MPCs) can grow rapidly to large sizes by vapor deposition via the Wegener-Bergeron-Findeisen (WBF) process, i.e., growth of ice crystals at the expense of cloud droplets. This rapid growth can trigger subsequent processes such as riming and aggregation, which often initiate precipitation, making MPCs the major source of precipitation over continents. The growth of ice crystals has been thoroughly studied in the laboratory for many decades and several theoretical models were developed on their basis. However, in situ measurements of growth rates to confirm laboratory studies are still sparse due to the lack of controllability of experiments in natural clouds.
In the CLOUDLAB project, we conducted confined, controlled, and repeatable glaciogenic cloud seeding experiments to study ice crystal growth in natural clouds. A drone released seeding particles in supercooled low stratus clouds to initiate the formation of ice crystals. The freshly formed ice crystals were observed 5-10 minutes downwind of the seeding location using cloud radars and holographic imager for in situ observations. The holographic imager obtains phase-resolved information on cloud droplets > 6 µm and ice crystals > 25 µm with a high spatio-temporal resolution, which allows us to quantify accurate ice crystal growth rates.
In this study, we present ice crystal growth rates obtained from in-situ observations from 14 seeding experiments in the temperature range between -5.1°C and -8.3°C. During the seeding experiments, ice crystal number concentrations (ICNC) increased by several orders of magnitude, accompanied by a strong reduction in cloud droplet number concentration, a clear indicator of the WBF process. We also observed that high ICNCs limit or inhibit ice growth due to the competition of the ice crystals for the available water vapor. The obtained ice crystal growth rates are compared with laboratory studies and show on average slightly lower values. We also observed the expected variation in growth rates across our temperature range agreeing with laboratory findings. These findings can connect laboratory studies and in situ observations and provide valuable insights into vapor depositional growth of ice crystals in natural clouds.
How to cite: Fuchs, C., Ramelli, F., Lohmann, U., Miller, A. J., Omanovic, N., Spirig, R., Zhang, H., and Henneberger, J.: Quantifying ice crystal growth rates in natural clouds from glaciogenic cloud seeding experiments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8032, https://doi.org/10.5194/egusphere-egu25-8032, 2025.
The formation of the first ice particles in developing convective clouds is a critical event in cloud evolution. The timing, location and amount of the initial ice has potentially significant implications for the eventual micro and macro scale properties as the cloud evolves. Here we present in-situ measurements of the first ice particles observed in growing convective clouds during the DCMEX project over the Magdalena mountains in New Mexico, USA. The Facility for Airborne Atmospheric (FAAM) Bae-146 research aircraft was used to make penetrations of the convective clouds below the freezing level, following the cloud top upwards. We used an Optical Array probe with a large sample volume suitable for detecting the earliest ice particles as they developed. We often observed no ice particles initially at only slightly supercooled temperatures before the eventual appearance of small irregular ice particles in low concentrations around the -8°C level. We will present the characteristics of the particles observed and compare their concentrations with Ice Nucleating Particle (INP) data analysed during the same project.
How to cite: Lloyd, G., Blyth, A., Gallagher, M., Choularton, T., Bower, K., Hu, K., Murray, B., and Daily, M.: Early Ice Particles in Growing Convective Clouds over a New Mexico Mountain Range during DCMEX, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18152, https://doi.org/10.5194/egusphere-egu25-18152, 2025.
In-situ based information on the distribution of RHice inside cirrus clouds is still retrieved mainly from focused research aircraft campaigns for dedicated regions and seasons, but a long-term and seasonal perspective is missing. We report on the distribution of RHice in clear sky as well as inside 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.
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. 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 in-situ RHice observations.
The analysed data set covers the period from June 2014 to December 2021. Four regions were identified for in-depth statistical analyses, with three of them located in the Northern midlatitudes (30–60°N), namely Eastern North America (105–65°W), the North Atlantic flight corridor (65–5°W), and Western Europe (5°W–30°E), and one in the Southeast Asian subtropics (0–30°N, 45–120°E).
We will present the novel cloud index and discuss the features of the resulting RHice probability distribution functions of the analysed regions, including seasonal variations, and potential implications for the underlying cirrus cloud formation processes.
How to cite: Petzold, A., Khan, N. F., Li, Y., Rohs, S., Crewell, S., and Krämer, M.: Distribution of RHice inside thin and thick cirrus clouds over the Northern Mid-latitudes and in a Subtropical Region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12954, https://doi.org/10.5194/egusphere-egu25-12954, 2025.
The climate impact of aviation can be separated into CO2 and non-CO2 effects, with the latter being potentially larger than the former. In this context we are more specifically interested in condensation trails (hereafter contrails) and induced cirrus. Monitoring contrail formation and evolution is necessary to understand their radiative effects and help the aviation industry to transition towards a more sustainable activity.
Current research aimed at detecting contrails is mostly based on geostationary satellite images because they allow to follow the contrail over a long period of time. However a major shortcoming of this approach, due to the current spatial resolution of geostationary imagers, is that the contrail formation phase cannot be detected and larger, but older, contrails cannot always be attributed to the flights that produced them. To circumvent this problem and observe the contrail formation phase, we use a ground-based hemispheric camera with a two-minute sampling rate as a complementary source of information.
As a first step, we have developed a traditional morphological algorithm that will help preparing a sufficiently large labelled database as required to train a deep-learning algorithm. This algorithm aims to detect whether each aircraft that passes in the field of view of the camera (as monitored from an ADSB radar) produces a contrail or not and, whenever possible, track the contrail across successive images.
We are thus able to relate contrail formation and evolution with aircraft type, flight altitude and weather conditions. We consider all weather conditions except completely cloudy conditions that prevent contrails from being observed. The performance of this algorithm is evaluated against a database that was manually annotated consisting of 400 images with 407 contrails. We find a specificity of 97\%, i.e. there are few false detections, but a sensitivity of about 55\%, i.e. it is missing a significant fraction of contrail that were annotated manually. An analysis of several years of contrail detection will be presented to determine precisely the fraction of contrail-producing flights and the weather conditions associated with short-lived (less than 2 min) and longer-lived(more than 2 min) contrails.
Additionally to this approach, which misses part of the young contrails and does not detect contrails formed outside the field of view of the camera, we have trained deep neural networks such as Unet and DeeplabV3, on a database of 1600 images in order to overcome those limits. Our preliminary results show a good performance on young contrails, with an improved detection capability, in particular for contrails formed outside of the camera field of view. The deep neural networks also work better for old contrails but may confuse very old contrails with background cloud features.
How to cite: Gourgue, N., Boucher, O., and Barthes, L.: Detection of Linear Contrails with a Morphological Algorithm and with Deep Neural Networks, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6792, https://doi.org/10.5194/egusphere-egu25-6792, 2025.
Tropical tropopause layer (TTL) cirrus clouds play a key role in the Earth climate system, yet the relative role of the various processes shaping them remains poorly known. Characterizing the temporal evolution of cloudy structures from observations is essential to address this issue, but represents a challenge. Indeed, space- and air-borne platform are not well-suited for this task: moving much faster than the air, they only provide instantaneous snapshots. In boreal winter 2021-2022, two balloon-borne lidars flew over the Equatorial Pacific Ocean, slowly drifting above the clouds. We use those unique observations of truncated (nighttime only) lifetime distribution to quantify the underlying continuous distribution of cloud lifetime above this homogeneous region. While most clouds are short-lived (mean lifetime estimated at about 6 h, a median value of 1 h), the temporal cloud cover is still dominated by the few long-lived ones (24 h or more). These results are compared to cirrus lifetimes in ERA5 reanalysis, showing a fair agreement between the reanalysis and the observations, and demonstrating the value of our approach to evaluate cirrus representation in global models.
How to cite: Lesigne, T., Podglajen, A., and Ravetta, F.: First estimates of Tropical Tropopause Cirrus lifetimes using balloon-borne lidar observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17170, https://doi.org/10.5194/egusphere-egu25-17170, 2025.
The coexistence of liquid water and ice crystals in mixed phase clouds allows for collisions and subsequent freezing of droplets on ice crystals and aggregates, which is called riming. Because riming fills air cavities in aggregates and makes particles more round, rimed snow has a higher fall speed compared to unrimed crystals and aggregates. Therefore, a reliable method to detect riming are fall speed measurements based on the Doppler shift of cloud radar echos. For this, the cloud radar has to be oriented vertically, otherwise the Doppler shift is dominated by the horizontal wind advection of the hydrometeors. Limited to vertical observations, one of the key strengths of atmospheric radar is missing: To probe the atmosphere in 3D. In this contribution, we present the results from a winter measurement campaign, where we performed elevation scans through strong riming events. Assuming a model for the horizontal wind speed, we can remove the horizontal wind contribution from the Doppler signal. This reveals the underlying riming signatures from the measurements, allowing us to create snapshots in time of the actual spatial organization of strongly rimed particles in mixed phase clouds. By choosing the scanning plane into the main wind direction, we are able to track spatial features over multiple snapshots. A better characterization of the spatial picture can enhance our conceptual understanding of the structure and organization of strong riming in mixed phase clouds. Since supercooled liquid water is a precondition for riming and aircraft icing alike, our results could also proof helpful to design aircraft icing hazard warning products.
How to cite: Ockenfuss, P., Köcher, G., and Kneifel, S.: Visualizing the Spatial Structure of Strong Riming Events using Scanning Cloud Radars, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18125, https://doi.org/10.5194/egusphere-egu25-18125, 2025.
In the spring of 2024, the US National Science Foundation sponsored the Cold-Air outbrEaks in the Sub-Arctic Region (CAESAR) aircraft campaign, with the simple goal of characterizing cold-air outbreak (CAO) clouds coming off of the Arctic sea ice as comprehensively as possible. A strength of the CAESAR strategy is a comprehensive aerosol, cloud and remote sensing instrumentation suite and early development of a close connection to modeling spanning a range of scales, in part by building on prior DOE-sponsored activity through the Cold-Air Outbreaks in the Marine Boundary Layer (COMBLE) campaign. The higher-level motivation for CAESAR is to better understand how clouds participate and feedback upon the changing Arctic. New technologies, improved data integration and modeling frameworks that are increasingly comparable to the observations hold promise that both the numerical weather prediction and global modeling of the super-cooled liquid, mixed-phase and ice clouds can be improved through the focus provided by the field campaign. In this presentation we provide an overview of the NCAR C-130 aircraft campaign, and its approach to the problem of improving understanding of the cold-air outbreak cloud evolution, microphysical processes including their relationship to aerosol, and cloud mesoscale organization including the development of CAO clouds into polar lows. Initial highlights will be included.
How to cite: Zuidema, P., Geerts, B., and McFarquhar, G.: An Overview of the Cold-Air outbrEaks over the Sub-Arctic Region (CAESAR) campaign, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20471, https://doi.org/10.5194/egusphere-egu25-20471, 2025.
Cirrus clouds permit much of the incoming solar shortwave radiation to pass through while trapping and reemitting the Earth's outgoing longwave thermal radiation. This results in a net warming effect globally at the top of the atmosphere. They are found almost over every region, but their impact can differ depending on latitude. The arctic is a unique and fascinating area. Over the last few decades, scientists have shown that its average temperature is increasing at an accelerated rate compared to global warming. This phenomenon has been labeled Arctic Amplification and cirrus clouds are considered a potential contributor. Another arctic-specific phenomenon linked to arctic amplification are Warm Air Intrusions (WAI). During such events, warm, water-vapor- and aerosol-rich airmasses are meridionally transported into the arctic from the midlatitudes. Apart from the transport of sensible heat and water vapor, a strong greenhouse gas, these events can potentially alter properties and effects of the cirrus clouds that form in the arctic. The positive trend found in the frequency and longevity of these events further highlights the importance to understand how they affect the macrophysical and optical properties of cirrus clouds in the arctic.
In March and April of 2022, the HALO-(AC)3 field campaign was conducted. The main goal of this campaign was to investigate WAI events and airmass transformations in the arctic. One of the platforms employed during this campaign was the German research aircraft HALO. It was used to perform remote sensing measurements at high altitudes over cirrus clouds. Among the instruments aboard HALO, were the combined water vapor differential absorption and high spectral resolution lidar system WALES and the HAMP package including a cloud radar and radiometers. Measurements from these two instruments form the basic dataset analyzed in this study. The cirrus clouds detected during this campaign are classified as either WAI cirrus or AC cirrus depending on if they were measured during an active WAI or during undisturbed arctic conditions. In order to better classify the clouds and provide a more in-depth analysis their backwards trajectories were calculated using the Lagrangian analysis tool LAGRANTO and the CLaMS-Ice model, which combines the Chemical Lagrangian Model of the Stratosphere (CLaMS) with two-moment ice microphysics.
In this presentation we are comparing the geometrical and optical depths of WAI and AC cirrus as measured by WALES. From the same instrument we also calculate the supersaturations with respect to ice and get a first insight into the probable nucleation processes. The backwards trajectories reveal more details regarding the origin, formation process, nucleation pathway and microphysical properties of the two cloud types. The analysis of the microphysical properties is further strengthened by analyzing the combined radar-lidar products.
How to cite: Dekoutsidis, G., Groß, S., Wirth, M., Rolf, C., Krämer, M., Schäfler, A., and Ewald, F.: Observations and Analysis of Cirrus Clouds in the Arctic during Warm Air Intrusions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6928, https://doi.org/10.5194/egusphere-egu25-6928, 2025.
The 50˚–65˚ latitude band exhibits the largest hemispheric asymmetry of cloud albedo over the oceans as well as the largest negative Southern Ocean (SO) cloud albedo biases in CMIP models. In this study, we show that cloud albedo regressed against sea-surface temperatures (SSTs) highlights essential differences between the observed Northern and Southern hemisphere climatologies, and between the SO’s simulated and observed albedos. The threshold 4˚–5˚C stands out as a regime separator in both comparisons.
By linking our empirical findings with the extensive evidence that model errors are related to the unique microphysical characteristics of the SO environment, we hypothesize that cloud albedo as a function of SST may act as a predictor of the presence/absence of supercooled liquid water cloud content.
Using satellite-retrieved cloud optical thickness (COT) and cloud top temperature (CTT), we verify that a regime separation of COT as a function of CTT exists between the Northern and Southern hemispheres (for CTT< -12˚C), which becomes more noticeable under midlevel subsidence conditions (i.e., low, boundary layer clouds).
Our simple and straightforward method using macrophysical variables can be easily applied in model evaluation with an insight in microphysics performance, especially given the scarcity of archived cloud-specific variables by the participating CMIP models. For example, it is well known that models tend to produce glaciated rather than supercooled liquid water clouds, and we show that in many cases models are simulating Northern Hemisphere clouds for the SO. We also detect that some of the CMIP models produce the right climatological cloud albedo over the SO but for the wrong reasons.
How to cite: Blanco, J., Caballero, R., Sherwood, S., and Alexander, L.: Using SST as a proxy for cloud phase biases over the Southern Ocean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2195, https://doi.org/10.5194/egusphere-egu25-2195, 2025.
As part of the NWCSAF project (Nowcasting Satellite Application Facility), the CNRM participates in the retrieval of cloud properties from geostationary satellite observations. These retrievals include the Cloud Mask and Cloud Types classification, thermodynamics properties at the macroscopic scales (Cloud Top Temperature and Height) as well as microphysical cloud properties (effective radius, optical thickness, liquid and ice water path). Radiative transfer simulations are mandatory to retrieve these properties. In this study, I performed simulations of observations from the Meteosat Second Generation satellite based on in-situ measurements taken on board an airborne campaign and mesoscale models using the radiative transfer model RTTOV.In order to compare the differences between simulation and observations for the case of ice clouds formed by deep convective systems, in the infrared and visible. Then discuss the sensitivity of the simulations to the physical and optical properties of the clouds, for example, how a misrepresentation of the ice water content at the top of clouds can be highlighted using simulations.
How to cite: Joseph, R., Fontaine, E., Schwarzenboeck, A., Delanoe, J., Kerdraon, G., Le Bastard, T., Gonthier, H., Tulet, P., Barthe, C., and Vidot, J.: Simulation of satellite observations with RTTOV for ice clouds from deep convection using in-situ observations and a mesoscale model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4385, https://doi.org/10.5194/egusphere-egu25-4385, 2025.
Clouds and their radiative effects remain one of the most pernicious unknowns in our predictions of the climate. Climate models are particularly affected by uncertainties around mixed-phase clouds (MPCs) consisting of both super-cooled liquid droplets and ice crystals. Inaccurate measurements of the liquid water content can lead to an under or overestimation of the warming properties of these clouds. Moreover, we lack adequate constraints and parameterisations of the spatial heterogeneity of water/ice mixtures, and the distribution of ice crystal sizes within MPCs.
Traditional cloud-monitoring satellites are able to retrieve physical cloud properties pertinent to these unknowns via, for example, LIDAR and radar sensors, but must necessarily treat MPCs as homogeneously mixed at scales below their resolution, which is on the order of 100s of metres to kilometres per pixel. Meanwhile, cloudy imagery from multispectral satellites with high spatial resolution, such as Sentinel-2, is treated as a waste product, with the ~60% of cloudy pixels left to gather dust in the archive. Multiple barriers exist that make these multispectral satellites difficult to use for ice cloud property retrievals, including their lack of thermal information, their tendency to mostly observe over land and not the ocean, their infrequent revisit times, and their sun-synchronous orbits which mean they only observe at 10 am local time. Nevertheless, these sensors offer a unique angle from which to study clouds, which can complement existing and future cloud-specialised sensors.
Here, we present early results of the Clouds Decoded project, funded by the Advanced Research + Invention Agency (ARIA), which seeks to help the community to tackle some of the key unknowns related to MPCs and ice clouds. Clouds Decoded aims to retrieve several physical cloud properties including cloud top height, optical depth (for optically thin clouds), ice/water ratio and ice particle effective radius, all at very fine resolution. This is being done at a massive scale, with the goal of processing several hundred terabytes of Sentinel-2 data from across the globe during the project. In this presentation, we will focus on a handful of case-studies which demonstrate how our data can be of use to the community. In particular, statistical relationships between cloud top temperature (inferred from height) and ice properties, alongside spatial frequency analyses, will be leveraged to describe the complex processes occurring in MPCs.
How to cite: Francis, A., Campbell, J., and Czerkawski, M.: Clouds Decoded: Understanding Mixed-Phase Clouds with High Resolution Multispectral Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17522, https://doi.org/10.5194/egusphere-egu25-17522, 2025.
This study aims to enhance the precipitation simulations of regional climate models (RCMs) over the Yucatan Peninsula by implementing a cloud microphysics parameterization based on observational data of ice-nucleating particles (INPs) collected in the region.
Cloud microphysics parameterizations derived from observational INP data enable RCMs to more accurately represent heterogeneous nucleation, a critical process in the formation of ice crystals in clouds, which plays a key role in modulating both the duration and amount of precipitation.
Preliminary analyses with the RegCM model suggest that simulated precipitation is highly sensitive to modifications in cumulus and microphysics parameterizations. These findings provide valuable insights for advancing the understanding of INPs’ role in simulations over tropical regions. Nonetheless, further detailed analyses are required to comprehensively assess their influence and scope in these settings.
How to cite: Castillo-Liñan, S., Cerezo-Mota, R., Ladino-Moreno, L. A., Torres-Alavez, J. A., and Allende-Arandía, M. E.: Improving Precipitation Simulations in Regional Climate Models over the Yucatan Peninsula: The Role of Ice-Nucleating Particles in Cloud Microphysics Parameterizations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-583, https://doi.org/10.5194/egusphere-egu25-583, 2025.
Accurate measurements of snowfall in mid- and high-latitudes are particularly important, because snow provides a vital freshwater source, and impacts glacier mass balances as well as surface albedo. However, ice water content (IWC) and snowfall rates (SR) are hard to measure due to their high spatial variability and the remoteness of polar regions.
Here, we present novel ice water content - equivalent radar reflectivity (IWC-Ze) and snowfall rate - equivalent radar reflectivity (SR-Ze) relations for 40° slanted and vertically pointing W-band cloud radar. The relations are derived from joint in situ snowfall and remote sensing (radar and radiometer) data from the SAIL site (Colorado, USA) and validated for sites in Hyytiälä (Finland), Ny-Ålesund (Svalbard, Norway), and Eriswil (Switzerland). In addition, gauge measurements from SAIL and Hyytiälä are used as an independent reference for validation. We show the dependence of IWC-Ze and SR-Ze on riming, which we utilize to reduce the spread in the IWC-Ze and SR-Ze spaces. Normalized root mean square errors (NRMSE) are below 25% for IWC>0.1 gm⁻³. For SR, the NRMSE is below 70% over the whole SR range. We also present relations using liquid water path (LWP) as a proxy for the occurrence of riming, which can be applied to both ground-based and space-borne radar-radiometer instruments. The latter is demonstrated using the example of the proposed ESA Earth Explorer 11 candidate mission WIVERN, which consists of a conical scanning 94 GHz radar and a passive 94 GHz radiometer. With this approach, NRMSE are below 75% for IWC>0.1 gm⁻³ and below 80% for SR>0.2 mmhr⁻¹.
The proposed IWC and SR relations provide a novel way to reduce uncertainties of IWC and SR estimates for W-band radar by accounting for particle riming. Advantages to current literature relations are the flexibility in terms of viewing angle and the inclusion of LWP, allowing the application to ground-based and space-borne radar-radiometer combinations like EarthCARE or the proposed WIVERN mission.
How to cite: Maherndl, N., Battaglia, A., Kötsche, A., and Maahn, M.: Riming-dependent Snowfall Rate and Ice Water Content Retrievals for W-band cloud radar, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5713, https://doi.org/10.5194/egusphere-egu25-5713, 2025.
Graupel continues to be the least well constrained and understood hydrometeor in numerical models. Playing an important role in cloud electrification and precipitation in cumulonimbus, graupel is critical to model correctly. New observations from the Deep Convective Microphysics Experiment1 (DCMEX) have been used to evaluate a recently developed machine-learning algorithm, which categorises hydrometeor images. An overview of the overarching ice habit distribution from DCMEX cumulonimbus will be presented, alongside preliminary analysis of the observed graupel formation and its corresponding environmental conditions.
DCMEX presents a unique opportunity of complementary in-situ and radar observations. The project was conducted in the Magdalena Mountains of New Mexico during the summer of 2022. The airborne sampling strategy involved repeated sampling of cloud turrets as convection strengthened through the day, allowing for evolving in-situ observations as the cloud deepened. The campaign was able to successfully sample convective cloud on 17 out of 19 flight days.
To understand the microphysical processes within a developing cloud, ice images from the 2D Stereo Probe and High Volume Precipitation Spectrometer have been analysed. These images have been categorised into habit, using the supervised machine learning algorithms from Jaffeux et al.2,3. Independent evaluation of the algorithms has been conducted, to test the generalisation capabilities under different cloud conditions.
This work aims to strengthen our understanding of graupel in deep convective cloud, whilst evaluating a novel machine learning approach to process data. Ultimately, this will contribute to the assessment of ice microphysics in regional forecasts.
References:
(1) Finney, D.L. et al. (2024). Earth Syst. Sci. Data, 16(5), 2141-2163.
(2) Jaffeux, L. et al. (2022). Atmos. Meas. Tech., 15(17), 5141-5157.
(3) Jaffeux, L. et al. (2024). EGUsphere (Preprint).
How to cite: Alkilani-Brown, E., Blyth, A., Finney, D., Deva, C., Field, P., and Crosier, J.: In-situ characterisation of graupel in deep convective cloud, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7218, https://doi.org/10.5194/egusphere-egu25-7218, 2025.
We developed an ice phase extension for the PySDM Python package. PySDM is used for simulating the microphysics of population of particles, e.g. for modeling liquid droplets and their interactions with aerosol in clouds. PySDM uses the particle-based approach (‘super droplet method’) and features Monte-Carlo type solvers for processes such as collisions, coagulation, breakup, and freezing.
Our aim is to adapt that framework for the simulation of (pure) ice clouds in the cirrus temperature regime. Ice super particles are affected by homogeneous freezing of solution droplets, deposition nucleation, growth by vapor deposition and sedimentation. The main research question is the investigation of in-situ ice formation and sedimentation rates of in-situ formed ice into lower cloud layers. We present some early results for prescribed flow.
How to cite: Lüttmer, T., Arabas, S., and Spichtinger, P.: Cirrus formation in particle-based aerosol-cloud microphysics, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7011, https://doi.org/10.5194/egusphere-egu25-7011, 2025.
We present lattice Boltzmann method (LBM) for simulating light scattering by hydrometeors, addressing the limitations of existing techniques. The accurate modelling of light scattering by hydrometeors, which include raindrops, hailstones, graupel, snowflakes, and ice crystals, is essential for remote sensing, climate modelling, and atmospheric studies. Current methods, such as the Finite-Difference Time-Domain (FDTD) method, are limited by computational cost and accuracy issues, particularly for larger particle sizes; for example, FDTD is generally restricted to size parameters smaller than about 20. This restriction arises from the method's need for fine grid resolution, where the number of numerical operations increases rapidly with particle size, scaling approximately with the fourth power of the size parameter. These limitations make FDTD impractical for many hydrometeor simulations, which often require larger size parameters. The T-matrix method and the Discrete Dipole Approximation (DDA) are alternative approaches, but they, too, have limitations. Therefore, a more efficient and accurate numerical method is needed to overcome these challenges. The LBM aims to overcome these limitations by exploring an alternative numerical approach; the goal is to provide a more computationally efficient and accurate approach. By addressing the computational challenges associated with existing numerical methods, this work enables more realistic and detailed simulations of light scattering by hydrometeors across a wider range of sizes and shapes. This has significant implications for improving remote sensing retrievals of cloud and precipitation properties, as well as advancing our understanding of the role of hydrometeors in the Earth's climate system.
How to cite: Khan, M. M., Thampi, S. P., and Roy, A.: A lattice Boltzmann method to study light scattering by hydrometeors, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17818, https://doi.org/10.5194/egusphere-egu25-17818, 2025.
The detailed information on the particle size distributions (PSDs) of ice clouds is essential for various topics of radiative transport in a cloudy atmosphere. The new composite of in-situ PSD measurements, including 9 airborne campaigns with in total 137 flight hours in cirrus cloud conditions, is currently the most comprehensive data set for studying PSD parameters. The PSDs cover for all campaigns particle diameters down to 3 microns and are not affected by the so-called shattering effect. The database covers the complete cirrus cloud temperature range (185 - 235 K) and IWC from 10−6 to 1 g/m3 and and is thus especially well-suited to investigate optically thinnest clouds hitherto not included in PSD data bases.
Here, the database is used for detailed analysis of PSDs of cirrus clouds for two size modes, as Bartolomé García et al. (2023) have shown that ice cloud PSDs are better represented by bimodal PSDs. To this end, two log-normal functions are derived for the measured PSDs, one for small and one for large ice particles. An iterative approach for fitting the bimodal log-normal functions to the measured PSD by minimizing a cost function have been applied to the data with overall good fitting results.
Next, microphysical and optical properties such as ice water content (IWC), mean mass diameter (D), effective radius (Reff) and extinction are determined for the total cirrus particle size range and also for each of the two size modes. For each parameter, median values are then computed at predefined IWC - temperature intervals.
Characteristics of the total size range as well as of the small and large size modes in the IWC-temperature space in terms of microphysical and optical properties will be presented for mid-latitudes and the tropics. The potential imprint of the results on currently applied cloud modules and cloud parameterization in global climate models will be investigated.
References: Bartolomé García, I., Sourdeval, O., Spang, R., and Krämer, M.: Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions, Atmos. Chem. Phys., 24, 1699–1716, https://doi.org/10.5194/acp-24-1699-2024, 2024.
How to cite: Spang, R., Krämer, M., Bartolome Garcia, I., and Spelten, N.: Cirrus cloud median microphysical and optical properties in the IWC-temperature space from a comprehensive airborne size distribution database , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8666, https://doi.org/10.5194/egusphere-egu25-8666, 2025.
Understanding the formation mechanisms of ice clouds is challenging due to their complex composition and diverse growth processes. Observational constraints have historically been limited, resulting in significant gaps in our understanding and representation of ice clouds. Satellite measurements are particularly limited by the absence of critical environmental context information needed to identify cloud formation mechanisms and evolution. These observations provide only a snapshot of cloud states and their microphysical properties at a single moment. This study seeks to overcome these limitations by incorporating additional metrics on ice cloud history and origin alongside operational satellite products.
We introduce a novel framework that combines satellite observations with Lagrangian transport and ice microphysical modelling to provide insights into the history and origin of air parcels contributing to ice cloud formation. The Chemical LAgrangian Model of the Stratosphere (CLaMS) is employed to trace air parcel trajectories along the DARDAR-Nice track. Additionally, the CLaMS-Ice model is used to simulate cirrus clouds along these trajectories, offering metrics on cirrus age, origin (in situ vs. liquid-origin), and ice formation pathways (heterogeneous vs. homogeneous nucleation) that can be associated with satellite observations.
To illustrate this approach, we present three case studies representative of distinct mid-latitude synoptic conditions: fast updraft, slow updraft, and orographically driven ice clouds. These cases demonstrate an in-depth analysis of air parcel evolution since cirrus formation, followed by a statistical examination of the relationship between microphysical properties and the origin-based metrics. Furthermore, the method is evaluated by comparing modeled microphysics with satellite retrievals. A sensitivity analysis is conducted to assess the impact of input parameters in CLaMS-Ice, including small-scale temperature fluctuations, environmental ice-nucleating particle (INP) concentrations, and sedimentation parameterizations. Overall, this comprehensive approach enhances our understanding of ice cloud processes, provides valuable context for interpreting satellite observations, and contributes to refining the representation of cirrus clouds in atmospheric models.
How to cite: Saiprakash, A., Krämer, M., Rolf, C., Konjari, P., Riedi, J., and Sourdeval, O.: Investigating ice formation pathways in satellite-observed cirrus clouds using Lagrangian microphysical modelling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18983, https://doi.org/10.5194/egusphere-egu25-18983, 2025.
In addition to their formation mechanisms, the origin of cirrus clouds (liquid-origin or in situ) can significantly influence their microphysical and radiative properties. Liquid-origin cirrus, which form through the freezing of water droplets from the mixed-phase region upon reaching cirrus temperatures (below -38°C), are typically characterized by high ice crystal concentrations and are associated with a strong cooling effect. In contrast, in situ-origin cirrus consist of ice crystals that form directly within the cirrus regime via homogeneous or heterogeneous freezing. Large cloud systems often comprise a mixture of both types. However, the global occurrence, distribution, and environmental conditions associated with these cirrus types remain poorly understood.
This study investigates cirrus clouds by integrating satellite observations with reanalysis data. Observations from lidar-radar satellite instruments (DARDAR-Nice) provide detailed retrievals of cirrus microphysical properties, including ice water content and ice crystal number concentration. To trace the origins of cirrus clouds, we employ Lagrangian air mass trajectories based on ERA5 reanalyses, using the FLEXPART Lagrangian model. This analysis is conducted for every satellite retrieval pixel, with a horizontal resolution of 1.7 km and a vertical resolution of 60 m. Environmental conditions at and preceding cirrus formation, as well as those in the mixed-phase regime for liquid-origin cirrus, are examined along the trajectories. Aerosol data from CAMS reanalyses are also included to assess their influence.
A combined cloud-aerosol dataset, derived from satellite observations and reanalysis tools, is compiled for one year of global data. The global occurrence of liquid-origin cirrus is analyzed in relation to ice crystal formation drivers and the resulting microphysical and radiative properties of these clouds, as retrieved by the DARDAR-Nice product. The relative occurence of insitu- and liquid-origin ice in cirrus is also assessed. The role of aerosols in cirrus formation processes will briefly be explored.
How to cite: Sourdeval, O., Bucci, S., and Saiprakash, A.: Global analysis of cirrus origins using satellite observations and Lagrangian trajectories, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16983, https://doi.org/10.5194/egusphere-egu25-16983, 2025.
In this study, we evaluated the simulation performance of Arctic mixed-phase clouds using the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) scheme and its improved version (WDM6_ICE). WDM6_ICE prognoses the cloud ice number concentrations and incorporates the enhanced cloud ice shape parameters and cloud ice formation processes. Sensitivity experiments were conducted during the Mixed-Phase Arctic Cloud Experiment (M-PACE) period of October 9–10, 2004.
WDM6_ICE significantly improved cloud simulation, showing the enhanced low-level cloud fraction and more realistic radiation effects compared to WDM6. The vertical structure analysis revealed that WDM6_ICE more effectively maintained supercooled cloud liquid by reducing ice deposition and enhancing condensation processes and reduced efficiency of Wegener-Bergeron-Findeisen (WBF) process. Through the sensitivity experiments involving changes in cloud ice shape (SP) and ice nucleation processes (IN) (WDM6_SP and WDM6_SP_IN), we demonstrated how these changes contributed to the improved phase partitioning in mixed-phase clouds. However, our analysis also revealed limitations in the representation of total water content and boundary layer structure, suggesting the need for further improvements in surface-atmosphere interactions under stable Arctic conditions. Our findings provide insights for improving the representation of cloud microphysics and their interaction with boundary layer processes in Arctic mixed-phase clouds.
How to cite: Sung, H.-J., Lim, K.-S. S., Hong, S.-Y., Shin, J., Kim, B.-M., and Choi, J.-H.: Improved Simulation of Arctic Mixed-Phase Clouds with Modified Ice Microphysics in the WDM6 Scheme, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14507, https://doi.org/10.5194/egusphere-egu25-14507, 2025.
Mixed-phase clouds consist of both liquid water and ice crystals, which affect their radiative properties. The amount of ice in the clouds is also important for the formation of precipitation and the lifetime of the clouds. Mixed-phase clouds are abundant in the Arctic, which through Arctic amplification is experiencing the largest and fastest changes in climate. Clouds, including Mixed-phase clouds, remain one of the biggest causes of uncertainty in climate models. The clouds' radiative effects depend on the composition, location, amount, and longevity of the clouds, which are complex properties both to measure and to model.
So how will the Arctic mixed-phase clouds change in a warming world? We expect warmer temperatures to lead to more liquid clouds, with smaller and more abundant cloud particles and thereby more reflective clouds. Ultimately resulting in surface cooling (temperature effect). However, increased warming also leads to a decrease in sea ice. Less sea ice will lead to changes in the available aerosols, making more locally emitted aerosols available to act as ice-nucleating particles (INPs), possibly resulting in ice forming at higher temperatures. Less sea ice can then lead to more ice in the clouds, resulting in less reflective clouds and surface warming (aerosol effect).
The focus of this study is to investigate the changes in microphysical properties of the mixed-phase clouds over different surface conditions: How do the microphysical properties change as the sea ice disappears?
Aircraft measurements from the spring 2022 field campaign of the Isotopic Links to Atmospheric water's Sources (ISLAS) project are used to investigate the microphysical properties of Arctic mixed-phase clouds during Cold Air Outbreaks. These Cold air outbreaks act like a natural laboratory, which makes them ideal for studying the effect of the clouds from the same airmass over different surfaces such as sea ice and open ocean.
The ISLAS flights from April 3rd, 2022 passed over both sea ice and open ocean and are used as a case study. We focus on cloud microphysical properties such as cloud droplet number concentration, size distribution, and the supercooled liquid fraction (SLF: liquid water content/ total water content), measured by in-situ cloud probes. We compare the results for the clouds encountered over sea ice vs. over open ocean, and at different heights within the clouds. Whether or not we see any differences for the clouds above sea ice vs. open ocean indicates which of the two processes, the temperature effect or the aerosol effect, dominates as the sea ice disappears in a warming climate.
How to cite: Larsgård, N. E., David, R. O., Carlsen, T., Schwarzenboeck, A., Sodemann, H., and Storelvmo, T.: How does the change from sea ice to open ocean alter Arctic mixed-phase clouds?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18946, https://doi.org/10.5194/egusphere-egu25-18946, 2025.
Clouds present one of the major challenges for climate modeling and cause large uncertainties in climate projections. This results from the complexity involved in representing small-scale cloud microphysics in coarse-gridded climate models. Over the Greenland Ice Sheet, clouds modulate melt, but with sharply contrasting impacts for snow and ice surfaces. Therefore, accurate representation of cloud processes and cloud occurrence is essential for reliable melt projections over the ice sheet.
The recently launched Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) will provide cloud, precipitation and radiation profiles in unprecedented detail. We use these novel observations to evaluate cloud representation over Greenland in the latest version of the Regional Atmospheric Climate Model (RACMO2.4). Along-track atmospheric profiles of RACMO2.4 model output are compared with EarthCARE Level 2 cloud retrievals, as well as with Level 1 lidar and radar data, using derived backscatter and reflectivity profiles from the RACMO2.4 model output. The latter will help to explain which of the differences between observed and modeled cloud properties are due to model inaccuracies, and which are due to sensor limitations and data processing choices.
Using a selected number of case studies, our first comparison indicates that RACMO2.4 represents ice clouds reasonably well. However, we find large discrepancies regarding the representation of liquid clouds. Our analysis of cloud microphysical properties and aerosol representation will provide insights into the processes underlying these differences and will guide model development.
How to cite: Feenstra, T., van de Berg, W. J., and van Zadelhoff, G.-J.: First evaluation of Greenland clouds in RACMO2.4 using EarthCARE observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3449, https://doi.org/10.5194/egusphere-egu25-3449, 2025.
This paper introduces the early results obtained from the active sensor-based EarthCARE JAXA Level 2 cloud and precipitation microphysics products (Sato et al., 2024, Sato and Okamoto, 2023). In the microphysics retrievals, a maximum of two size modes in each vertical grid are considered to treat coexistence of cloud liquid particles and ice/snow in the mixed phase, transition from cloud ice to snow and cloud liquid to precipitation in the ice phase and liquid phase, respectively. Ice and snow are classified into five different habit categories, and their vertical resolved geographical distributions are investigated together with their microphysical properties, Doppler velocity-related products such as hydrometeor fall speeds and air vertical velocities, and environmental conditions.
How to cite: Sato, K. and Okamoto, H.: Early results from EarthCARE cloud microphysics and Doppler Velocity products, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19056, https://doi.org/10.5194/egusphere-egu25-19056, 2025.
Shallow mixed-phase clouds, in which ice and liquid particles co-exist, occur frequently in the middle and high latitudes of Earth. Yet despite their frequency and importance for local precipitation and radiative balance, our understanding of these clouds is limited. Especially the interaction of small-scale turbulence and mixed-phase microphysics has received little attention so far. To address this knowledge gap, we conducted large-eddy simulations with a highly detailed Lagrangian cloud microphysics parameterization. We simulate a shallow mixed-phase cloud observed during the Indirect and Semi-Direct Aerosol Campaign (ISDAC). We focus on the processes occurring in regions of mixing and entrainment near the cloud edges, with particular focus on the Wegener-Bergeron-Findeisen (WBF) process. We also investigate the effect on cloud properties, lifetime, and radiative balance from using a kinetically-limited ice crystal growth parameterization as opposed to a traditional capacitance-based growth parameterization.
How to cite: Ascher, B. and Hoffmann, F.: Impacts of Entrainment and Mixing on Ice Growth in Mixed-Phase Clouds, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10410, https://doi.org/10.5194/egusphere-egu25-10410, 2025.
Global climate models poorly represent mixed-phase clouds in a realistic way, which leads to uncertainties in cloud radiative forcing and precipitation. In the FORCeS ice experiment (FOR-ICE) we compare three global climate models (ECHAM-HAM, NorESM, EC-Earth) and show which processes are crucial for a realistic representation of cloud ice and supercooled water in each global climate model framework using the factorial method as a statistical approach. A specific focus of the experiments is on secondary ice production (SIP) - which apart from one mechanism (rime splintering) is not represented in models, even if observations of ice crystal concentrations of ice crystal number in warm mixed-phase clouds often exceed available ice nuclei by orders of magnitude. We evaluate the importance of three SIP mechanisms combined (rime splintering, ice-ice collisions, and droplet shattering) compared to all other processes that can modulate ice mass and number in mixed-phase clouds: ice nucleation, sedimentation, and transport of ice crystals. Satellite observations are used to evaluate the representation of mixed-phase clouds. We found large discrepancies in dominant microphysical processes for mixed-phase clouds across the investigated climate models.
How to cite: Ickes, L., Frostenberg, H., Costa Surós, M., Georgakaki, P., Proske, U., Sotiropoulou, G., May, E., Gonçalves Ageitos, M., Eriksson, P., Lewinschall, A., Nenes, A., Neubauer, D., Pérez García-Pando, C., and Sedland, Ø.: Dominant microphysical processes for mixed-phase clouds across climate models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20620, https://doi.org/10.5194/egusphere-egu25-20620, 2025.
Climate models struggle to accurately represent polar regions, particularly during polar night, when cloud cover is especially prevalent. The uncertainty budget is dominated by cloud and cloud-aerosol interactions, but the difficulty in maintaining robust field observations means a lack of long-term validation datasets for key cloud parameters. Long-term measurements of the downwelling thermal infrared (400 - 3000 cm-1) have been recorded since 2008 with an Atmosphere Emitted Radiance Interferometer (AERI) at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80°N, 86°W) and operated by the Canadian Network for the Detection of Atmospheric Change (CANDAC), while a similar instrument was deployed at McMurdo Station for 2016 as part of the ARM [Atmosphere Radiation Measurement] West Antarctic Radiation Experiment (AWARE) program. We analyse the downwelling infrared emission of the polar atmosphere recorded by these AERI instruments, with supplementary data from observations and models, to derive a climatology of microphysical and optical properties of clouds at Eureka (since 2008) and McMurdo (2016), including optical depth, thermodynamic phase, and liquid droplet and ice crystal effective scattering radii. A comparison of these Arctic and Antarctic cloud properties reveals an abundance of cloud morphological states at these two polar locations. This presentation will also describe the temperature dependence of cloud microphysics, seasonality in the timeseries, and the effect of inversions on cloud boundaries, as well as challenges in performing these retrievals.
How to cite: Hung, J., Rowe, P., McCullough, E., Kroll, L., Ottenheimer, R., Chang, R., and Strong, K.: Cloud microphysics in Arctic and Antarctic environments derived from infrared emission spectroscopy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7821, https://doi.org/10.5194/egusphere-egu25-7821, 2025.
We investigate the orientation dynamics of an ice crystal in homogeneous isotropic turbulence and in the presence of an external electric field in a cloud. At the scale of the ice crystal, we assume that viscous effects dominate the flow, and thus, the dynamics can be studied in the Stokesian regime. Further, when the size of the ice crystal is smaller than the Kolmogorov scale, the flow field around the particle can be modeled locally as a stochastic linear flow. This approximation becomes particularly useful when studying the orientation dynamics of an ice crystal in homogeneous isotropic turbulence and when the orientation dynamics of the ice crystal is governed by the Jeffery equation, which involves the local fluctuating velocity gradient. The turbulent velocity gradient is obtained from the stochastic model given by Girimaji and Pope. The model uses the log-normal distribution of the pseudo-dissipation rate. In the presence of an external electric field, experiments performed in a laboratory cold chamber have revealed that the ice crystal aligns in the direction of the electric field. We study the competition due to the torque induced by the turbulent velocity gradient and the electric field. The orientation dynamics is analyzed by varying a non-dimensional parameter Σ, which is defined as a ratio of the Kolmogorov time scale and the electric relaxation time scale. For lower values of Σ, we show that the ice crystal exhibits an isotropic orientational distribution, whereas it fluctuates along the direction of the electric field at higher values of Σ. We calculate moments of the orientation distribution at large electric field limits using asymptotic methods and compare them with numerical calculations. A second-order moment in the orientation, which quantifies the fluctuations in the orientation, depends on Σ and the shape of an ice crystal. The fourth-order moment of the orientation, a measure of the non-Gaussian statistics of the orientation distribution, increases from its Gaussian value with the increase in Taylor-scale Reynolds number.
How to cite: Mishra, H., Patra, P., and Roy, A.: Orientation dynamics of the ice crystal in a cloud: Effects of Turbulence and Electric Field, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14979, https://doi.org/10.5194/egusphere-egu25-14979, 2025.
