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Ice formation and growth processes play a crucial role in the evolution of cloud systems and the formation of precipitation. However, the initial formation and growth of ice crystals are challenging to study in the real atmosphere resulting in uncertainties in weather forecasts and climate projections. The CLOUDLAB project tackles this problem by using supercooled stratus clouds as a natural laboratory for targeted glaciogenic cloud seeding to advance the understanding of ice processes: Ice nucleating particles are injected from an uncrewed aerial vehicle (UAV) into supercooled stratus clouds to induce ice crystal formation and subsequent growth processes. Microphysical changes induced by seeding are measured 3–15 min downstream of the seeding location using in situ and ground-based remote sensing instrumentation. The novel application of seeding with a multirotor UAV combined with the persistent nature of stratus clouds enables repeated seeding experiments under similar and well-constrained initial conditions. This article describes the scientific goals, experimental design, and first results of CLOUDLAB. First, the seeding plume is characterized by using measurements of a UAV equipped with an optical particle counter. Second, the seeding-induced microphysical changes observed by cloud radars and a tethered balloon system are presented. The seeding signatures were detected by regions of increased radar reflectivity (>−20 dBZ), which were 10–20 dBZ higher than the natural background. Simultaneously, high concentrations of seeding particles and ice crystals (up to 2,000 L−1) were observed. A cloud seeding case was simulated with the numerical weather model ICON to contextualize the findings.

Clouds play a critical role in modulating the Earth’s radiation balance and climate. Anthropogenic aerosol particles that undergo aging processes, such as soot, aid cloud droplet and ice crystal formation and thus influence the microphysical structure of clouds. However, the associated changes in cloud radiative properties and climate effects remain uncertain and are largely omitted in climate models. Here we present global climate simulations of past and future effects of both ozone-aged soot particles acting as cloud condensation nuclei and sulfuric acid-aged soot particles acting as ice-nucleating particles on the structure and radiative effects of clouds. Under pre-industrial conditions, soot aging led to an increase in thick, low-level clouds that reduced negative shortwave effective radiative forcing by 0.2 to 0.3 W m−2. In the simulations of a future, warmer climate under double pre-industrial atmospheric carbon dioxide concentrations, soot aging and compensating cloud adjustments led to a reduction in low-level clouds and enhanced high-altitude cirrus cloud thickness, which influenced the longwave radiative balance and exacerbated the global mean surface warming by 0.4 to 0.5 K. Our findings suggest that reducing emissions of soot particles is beneficial for future climate, in addition to air quality and human health.Aged soot particles in the atmosphere enhance future warming through their influence on cloud formation and thus Earth’s radiation balance, according to global climate simulations.

In this review, recent findings related to various factors influencing quality properties of fish meat and its products during frozen storage are introduced. Many studies have indicated that protein denaturation is the factor determining the quality of frozen fish meat. Ice crystal size does not necessarily determine the quality of frozen fish meat because the tissue of meat reabsorbs water during the thawing process, unless it has been previously damaged by protein denaturation. However, the effects of ice crystals on the quality of thawed fish meat differ based on the fish species, post-mortem stages, protein denaturation, and processing conditions of the fish meat. In the case of frozen-thawed lightly salted fish meat, salting conditions greatly affect the water holding capacity of muscle and the ice crystal size. Also, in the case of frozen kamaboko, which is denatured protein gel, as the thawed water is not absorbed enough by the protein gel, ice crystal size could be a determining factor of quality. The appropriate freezing and storage conditions required for maintaining quality must be based upon the characteristics of each seafood product.

Observations show that the ice water content (IWC) in mixed-phase clouds (MPCs) tends to occur in clusters. However, it is not sufficiently understood which ice crystal formation and growth processes play a dominant role in IWC clustering in clouds. One important ice growth process is riming, which occurs when liquid water droplets freeze onto ice crystals upon contact. Here we use airborne measurements of MPCs at mid- and high-latitudes to investigate the spatial variability of ice clusters in clouds and how this variability is linked to riming. We use data from the IMPACTS (mid-latitudes) and the HALO-(AC)3 (high-latitudes) aircraft campaigns, where spatially and temporally colocated cloud radar and in situ measurements were collected. We derive riming and IWC by combining cloud radar and in situ measurements. Ice cluster scales in clouds are quantified using pair correlation functions. During all analyzed flight segments, riming is responsible for 66 % and 63 % of the total IWC during IMPACTS and HALO-(AC)3, respectively. In mid-latitude MPCs, riming does not significantly change IWC cluster scales but increases the probability of cluster occurrence. In cold-air-outbreak MPCs observed during HALO-(AC)3, riming leads to additional in-cloud IWC clustering at spatial scales of 3–5 km due to the presence of mesoscale updraft features. An increased liquid water path might increase the effect, but it is not a necessary criterion. These results can be used to evaluate and constrain models' representations of MPCs.

The Arctic is very susceptible to climate change and thus is warming much faster than the rest of the world. Clouds influence terrestrial and solar radiative fluxes and thereby impact the amplified Arctic warming. The partitioning of thermodynamic phases (i.e., ice crystals and water droplets) within mixed-phase clouds (MPCs) especially influences their radiative properties. However, the processes responsible for ice crystal formation remain only partially characterized. In particular, so-called secondary ice production (SIP) processes, which create supplementary ice crystals from primary ice crystals and the environmental conditions that they occur in, are poorly understood. The microphysical properties of Arctic MPCs were measured during the Ny-Ålesund AeroSol Cloud ExperimENT (NASCENT) campaign to obtain a better understanding of the atmospheric conditions favorable for the occurrence of SIP processes. To this aim, the in situ cloud microphysical properties retrieved by a holographic cloud imager mounted on a tethered balloon system were complemented by ground-based remote sensing and ice-nucleating particle measurements. During the 6 d investigated in this study, SIP occurred during about 40 % of the in-cloud measurements, and high SIP events with number concentrations larger than 10 L−1 of small pristine ice crystals occurred in 4 % of the in-cloud measurements. This demonstrates the role of SIP for Arctic MPCs. The highest concentrations of small pristine ice crystals were produced at temperatures between −5 and −3 ∘C and were related to the occurrence of supercooled large droplets freezing upon collision with ice crystals. This suggests that a large fraction of ice crystals in Arctic MPCs are produced via the droplet-shattering mechanism. From evaluating the ice crystal images, we could identify ice–ice collision as a second SIP mechanism that dominated when fragile ice crystals were observed. Moreover, SIP occurred over a large temperature range and was observed in up to 80 % of the measurements down to −24 ∘C due to the occurrence of ice–ice collisions. This emphasizes the importance of SIP at temperatures below −8 ∘C, which are currently not accounted for in most numerical weather models. Although ice-nucleating particles may be necessary for the initial freezing of water droplets, the ice crystal number concentration is frequently determined by secondary production mechanisms.

Hole-punch clouds are a visual representation of ice crystal formation and growth as well as their interactions with the liquid phase via the Wegener–Bergeron–Findeisen process. Their appearance is usually associated with an aircraft passing through a liquid cloud layer. However, they can also appear upon glaciogenic seeding of a supercooled low-level stratus cloud, as we showcase in this study. The observations of a hole-punch cloud prompted an investigation into the sensitivity of these clouds to the clouds' background state. We employ high-resolution large-eddy simulations with the weather model ICON and simulate one seeding experiment with different initial liquid water paths. The ensemble of 9 simulations helps us to quantify how the properties of a hole-punch cloud, i.e., strong reductions in the liquid water contents, depends on the cloud liquid water paths. Moreover, we perturb the turbulent mixing length, i.e., the Smagorinsky constant, to evaluate the impact of the intensity of mixing on hole-punch clouds. Generally, larger liquid water paths lead to a delay in the strongest reductions of liquid water content through the Wegener–Bergeron–Findeisen process. Interestingly, the turbulent mixing length does not appear to have a significant impact on the hole-punch cloud properties. These findings improve our understanding of the Wegener–Bergeron–Findeisen process and of the effectiveness of glaciogenic cloud seeding.

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol–ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on collocated measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, which are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol–ice formation closure. The closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

Ice crystal formation in cirrus clouds is poorly understood, and its representation remains a challenge in global climate models. To enhance the understanding, a novel ice nucleation parameterization based on the Kärcher (2022) (K22) scheme is introduced into the NCAR Community Atmosphere Model version 6 (CAM6). To investigate ice formation in cirrus clouds, sensitivity tests are conducted to analyze three ice sources from orographic gravity wave (OGWs), convective detrainment, and turbulence. These tests employ both the K22 scheme and the default Liu and Penner (2005) (LP05) scheme. Model evaluation includes 6-year climatology and nudged simulations representing the Small Particles in Cirrus (SPARTICUS) and O2 / N2 Ratio and CO2 Airborne Southern Ocean Study (ORCAS) campaigns. Both schemes simulate that convection detrained and turbulence-induced ice crystals are concentrated in low- to mid-latitudes, whereas OGW-induced ice crystals are concentrated in mid- to high latitudes. Compared to the LP05 scheme, the K22 scheme generates a higher number of ice crystals. The simulated cloud microphysical properties using the K22 scheme align well with observations for orographic cirrus during the SPARTICUS campaign. In orographic cirrus over high terrains at mid- to high latitudes, both schemes identify OGW-induced ice crystals as the dominant ice source. Due to its distinct competition parameterizations, the K22 scheme exhibits less contribution from minor ice sources (convection detrained and turbulence-induced). This underscores the significance of competition mechanisms within ice nucleation schemes and helps clarify regional and dynamical controls on ice sources in cirrus clouds. The application of two distinct nucleation schemes provides valuable insights into the dominant ice sources in cirrus clouds.

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations of two cases during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) near Houston, Texas, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, leading to more lightning. Polluted thermals initiate at slightly higher altitudes, and are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, but fewer isolated cells, since convection is more aggregated and intense, especially near the end of the 24 h simulation. Non-linear mesoscale feedback likely triggered by temperature and moisture responses to aerosol-thermal interactions causes the aggregation. Time-lagged aerosol-reinitialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

The number of ice crystals formed during the contrail's jet phase has a long-lasting impact on the life cycle and radiative forcing of contrail cirrus clouds. For conventional kerosene combustion, suitable parameterizations for early ice crystal number have been developed and employed in general circulation models that are used to estimate the climate impact of contrail cirrus. However, a parameterization for the number of ice crystals formed is lacking for hydrogen combustion. To develop such a parameterization, we present a comprehensive set of contrail formation simulations using the particle-based Lagrangian Cloud Module in a box model approach. Unlike kerosene combustion, no soot particles are emitted. Thus, ice crystals are assumed to form on ambient aerosols entrained into the exhaust plume. The total number of entrained particles primarily governs the nonlinear depletion of water vapor. Consequently, the impact of coarse-mode particles is negligible due to their low abundance. Additionally, ice crystal formation from multiple aerosol populations can be reconstructed from single-population simulations using population-specific properties (size and hygroscopicity) and the total number concentration. We also identify atmospheric conditions where homogeneous droplet nucleation can be safely neglected as potential ice formation pathway. Based on more than 20 000 simulations covering a broad range of atmospheric conditions and aerosol properties, we identify a regime where ice crystal formation becomes nearly independent of ambient relative humidity, aerosol size, and hygroscopicity. Our results provide a basis for a data-driven parameterization of ice crystal number in contrails from hydrogen combustion, to be presented in a companion paper.