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Secondary ice production (SIP) plays a key role in the formation of ice particles in tropospheric clouds. Future improvement of the accuracy of weather prediction and climate models relies on a proper description of SIP in numerical simulations. For now, laboratory studies remain a primary tool for developing physically based parameterizations for cloud modeling. Over the past 7 decades, six different SIP-identifying mechanisms have emerged: (1) shattering during droplet freezing, (2) the rime-splintering (Hallett–Mossop) process, (3) fragmentation due to ice–ice collision, (4) ice particle fragmentation due to thermal shock, (5) fragmentation of sublimating ice, and (6) activation of ice-nucleating particles in transient supersaturation around freezing drops. This work presents a critical review of the laboratory studies related to secondary ice production. While some of the six mechanisms have received little research attention, for others contradictory results have been obtained by different research groups. Unfortunately, despite vast investigative efforts, the lack of consistency and the gaps in the accumulated knowledge hinder the development of quantitative descriptions of any of the six SIP mechanisms. The present work aims to identify gaps in our knowledge of SIP as well as to stimulate further laboratory studies focused on obtaining a quantitative description of efficiencies for each SIP mechanism.

Phase transformation and precipitation formation in mixed-phase clouds are usually associated with the Wegener–Bergeron–Findeisen (WBF) process in which ice crystals grow at the expense of liquid droplets. The evolution of mixed-phase clouds, however, is closely related to local thermodynamical conditions, and the WBF process is just one of three possible scenarios. The other two scenarios involve simultaneous growth or evaporation of liquid droplets and ice particles. Particle evolution in the other two scenarios differs significantly from that associated with the WBF process. Thus, during simultaneous growth, liquid droplets compete for the water vapor with the ice particle, which slows down the depositional growth of ice particles instead of promoting their growth at the expense of the liquid as in the WBF process. It is shown that the WBF process is expected to occur under a limited range of conditions and that ice particles and liquid droplets in mixed-phase clouds are not always processed in accordance with the WBF mechanism.

Clouds have a major impact on rapidly decreasing sea ice in the Arctic, yet much is still unknown how cloud microphysics influences cloud development. In situ and remote data were collected by the NASA P-3 and SPEC Inc. Learjet research aircraft in Arctic stratiform boundary-layer clouds over the oceans and sea ice bordering northern Greenland between 25 May and 15 August 2024 during the ARCSIX project. Both aircraft carried a suite of nearly identical state-of-the-art microphysical sensors. Additionally, the P-3 was equipped with aerosol and remote-sensing instrumentation and the Learjet was equipped with a zenith/nadir Ka-band radar. The length of clouds examined remotely and in-situ by the two aircraft totaled 12 417 km, with 6966 km of in-situ measurements. Mixed-phase clouds were sampled during 60.5 % of time in cloud, and all-liquid clouds were measured 39.5 % of the time. Cloud-top temperatures were ≥-9 °C during 90 % of the stratiform boundary-layer cloud investigations. Single-layer mixed-phase clouds sampled with cloud-top temperatures ≥-4 °C often contained concentrations of ice particles more than five orders of magnitude higher than measured concentrations of ice-nucleating particles. Despite the high ice concentrations, microphysical conditions supporting secondary ice production were seldom present. In contrast, in some clouds where environmental conditions met commonly accepted criteria for secondary ice production, ice particle concentrations were closer to what is expected from primary nucleation. The quality of measurements was unprecedented, but results from our preliminary analysis raise more questions about primary and secondary nucleation mechanisms than they answer.

Total ice water content (IWC) derived from an isokinetic evaporator probe and ice crystal particle size distributions (PSDs) measured by a two-dimensional stereo probe and precipitation imaging probe installed on an aircraft during the 2014 European High Altitude Ice Crystals–North American High IWC field campaign (HAIC/HIWC) were used to characterize regions of high IWC consisting mainly of small ice crystals (HIWC_S) with IWC ≥ 1.0 g m −3 and median mass diameter (MMD) < 0.5 mm. A novel fitting routine developed to automatically determine whether a unimodal, bimodal, or trimodal gamma distribution best fits a PSD was used to compare characteristics of HIWC_S and other PSDs (e.g., multimodality, gamma fit parameters) for HIWC_S simulations. The variation of these characteristics and bulk properties (MMD, IWC) was regressed with temperature, IWC, and vertical velocity. HIWC_S regions were most pronounced in updraft cores. The three modes of the PSD reveal different dominant processes contributing to ice growth: nucleation for maximum dimension D < 0.15 mm, diffusion for 0.15 < D < 1.0 mm, and aggregation for D > 1.0 mm. The frequency of trimodal distributions increased with temperature. The volumes of equally plausible parameters derived in the phase space of gamma fit parameters increased with temperature for unimodal distributions and, for temperatures less than −27°C, for multimodal distributions. Bimodal distributions with 0.4 mm in the larger mode were most common in updraft cores and HIWC_S regions; bimodal distributions with 0.4 mm in the smaller mode were least common in convective cores.

High ice water content (HIWC) regions in tropical deep convective clouds, composed of high concentrations of small ice crystals, were not reproduced by Weather Research and Forecasting (WRF) model simulations at 1 km horizontal grid spacing using four different bulk microphysics schemes (i.e., the WRF single‐moment 6‐class microphysics scheme (WSM6), the Morrison scheme and the Predicted Particle Properties (P3) scheme with one- and two-ice options) for conditions encountered during the High Altitude Ice Crystals (HAIC) and HIWC experiment. Instead, overestimates of radar reflectivity and underestimates of ice number concentrations were realized. To explore formation mechanisms for large numbers of small ice crystals in tropical convection, a series of quasi-idealized WRF simulations varying the model resolution, aerosol profile, and representation of secondary ice production (SIP) processes are conducted based on an observed radiosonde released at Cayenne during the HAIC-HIWC field campaign. The P3 two-ice category configuration, which has two “free” ice categories to represent all ice-phase hydrometeors, is used. Regardless of the horizontal grid spacing or aerosol profile used, without including SIP processes the model produces total ice number concentrations about 2 orders of magnitude less than observed at −10 ∘C and about an order of magnitude less than observed at −30 ∘C but slightly overestimates the total ice number concentrations at −45 ∘C. Three simulations including one of three SIP mechanisms separately (i.e., the Hallett–Mossop mechanism, fragmentation during ice–ice collisions, and shattering of freezing droplets) also do not replicate observed HIWCs, with the results of the simulation including shattering of freezing droplets most closely resembling the observations. The simulation including all three SIP processes produces HIWC regions at all temperature levels, remarkably consistent with the observations in terms of ice number concentrations and radar reflectivity, which is not replicated using the original P3 two-ice category configuration. This simulation shows that primary ice production plays a key role in generating HIWC regions at temperatures <-40 ∘C, shattering of freezing droplets dominates ice particle production in HIWC regions at temperatures between −15 and 0 ∘C during the early stage of convection, and fragmentation during ice–ice collisions dominates at temperatures between −15 and 0 ∘C during the later stage of convection and at temperatures between −40 and −20 ∘C over the whole convection period. This study confirms the dominant role of SIP processes in the formation of numerous small crystals in HIWC regions.

This study attempts a new identification of mechanisms of secondary ice production (SIP) based on the observation of small faceted ice crystals (hexagonal plates or columns) with typical sizes smaller than 100µm. Due to their young age, such small ice crystals can be used as tracers for identifying the conditions for SIP. Observations reported here were conducted in oceanic tropical mesoscale convective systems (MCSs) and midlatitude frontal clouds in the temperature range from 0 to −15◦C and heavily seeded by aged ice particles. It was found that in both MCSs and frontal clouds, SIP was observed right above the melting layer and extended to higher altitudes with colder temperatures. The roles of six possible mechanisms to generate the SIP particles are assessed using additional observations. In most observed SIP cases, small secondary ice particles spatially correlated with liquid-phase, vertical updrafts and aged rimed ice particles. However, in many cases, neither graupel nor liquid drops were observed in the SIP regions, and therefore, the conditions for an active Hallett–Mossop process were not met. In many cases, large concentrations of small pristine ice particles were observed right above the melting layer, starting at temperatures as warm as −0.5◦C. It is proposed that the initiation of SIP above the melting layer is stimulated by the recirculation of large liquid drops through the melting layer with convective turbulent updrafts. After re-entering a super cooled environment above the melting layer, they impact with aged ice, freeze, and shatter. The size of the splinters generated during SIP was estimated as 10µm or less. A principal conclusion of this work is that only the freezing drop-shattering mechanism could be clearly supported by the airborne in situ observations.

NRC publication: Yes

We review a cloud feedback mechanism that has so far been considered of secondary importance, despite a body of research suggesting that it represents a powerful climate feedback that can control the sign of the overall cloud feedback simulated in global climate models (GCMs). The feedback mechanism is associated with phase changes in clouds triggered by a warming atmosphere, which in turn yields optically thicker clouds. Output from the latest generation of GCMs suggest that this is the dominant cloud feedback at high latitudes, with obvious implications for climatically sensitive regions such as the Arctic and the Southern Ocean. Here, we present an overview of the relatively few modeling studies that have investigated this particular feedback mechanism to date, along with new results suggesting that the cloud-climate feedback simulated by a GCM can change dramatically depending on its cloud phase partitioning.

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle‐based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next‐generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process‐level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle‐based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods. Plain Language Summary In the atmosphere, microphysics—the small‐scale processes affecting cloud and precipitation particles such as their growth by condensation, evaporation, and melting—is a critical part of Earth's weather and climate. Because it is impossible to simulate every cloud particle individually owing to their sheer number within even a small cloud, atmospheric models have to represent the evolution of particle populations statistically. There are critical gaps in knowledge of the microphysical processes that act on particles, especially for atmospheric ice particles because of their wide variety and intricacy of their shapes. The difficulty of representing cloud and precipitation particle populations and knowledge gaps in cloud processes both introduce important uncertainties into models that translate into uncertainty in weather forecasts and climate simulations, including climate change assessments. We discuss several specific challenges related to these problems. To improve how cloud and precipitation particle populations are represented, we advocate a “particle‐based” approach that addresses several limitations of traditional approaches and has recently gained traction as a tool for cloud modeling. Advances in observations, including laboratory studies, are argued to be essential for addressing gaps in knowledge of microphysical processes. We also advocate using statistical modeling tools to improve how these observations are used to constrain model microphysics. Finally, we discuss a hierarchical approach that combines the various pieces discussed in this article, providing a possible blueprint for accelerating progress in how microphysics is represented in cloud, weather, and climate models. Key Points Microphysics is an important component of weather and climate models, but its representation in current models is highly uncertain Two critical challenges are identified: representing cloud and precipitation particle populations and knowledge gaps in cloud physics A possible blueprint for addressing these challenges is proposed to accelerate progress in improving microphysics schemes

Cloud and aerosol data acquired by the National Research Council of Canada (NRC) Convair-580 aircraft in, above, and below single-layer arctic stratocumulus cloud during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in April 2008 were used to test three aerosol indirect effects hypothesized to act in mixed-phase clouds: the riming indirect effect, the glaciation indirect effect, and the thermodynamic indirect effect. The data showed a correlation of R = 0.78 between liquid drop number concentration, Nliq inside cloud and ambient aerosol number concentration NPCASP below cloud. This, combined with increasing liquid water content LWC with height above cloud base and the nearly constant vertical profile of Nliq, suggested that liquid drops nucleated from aerosol at cloud base. No evidence of a riming indirect effect was observed, but a strong correlation of R = 0.69 between ice crystal number concentration Ni and NPCASP above cloud was noted. Increases in ice nuclei (IN) concentration with NPCASP above cloud for 2 flight dates combined with the subadiabatic LWC profiles suggest possible mixing of IN from cloud top consistent with the glaciation indirect effect. The lower Nice and lower effective radius rel for the more polluted ISDAC cases compared to data collected in cleaner single-layer stratocumulus conditions during the Mixed-Phase Arctic Cloud Experiment is consistent with the operation of the thermodynamic indirect effect. However, more data in a wider variety of meteorological and surface conditions, with greater variations in aerosol forcing, are required to identify the dominant aerosol forcing mechanisms in mixed-phase arctic clouds.