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The secondary ice process (SIP) is a major microphysical process, which can result in rapid enhancement of ice particle concentration in the presence of preexisting ice. SPICULE was conducted to further investigate the effect of collision–coalescence on the rate of the fragmentation of freezing drop (FFD) SIP mechanism in cumulus congestus clouds. Measurements were conducted over the Great Plains and central United States from two coordinated aircraft, the NSF Gulfstream V (GV) and SPEC Learjet 35A, both equipped with state-of-the-art microphysical instrumentation and vertically pointing W- and Ka-band radars, respectively. The GV primarily targeted measurements of subcloud aerosols with subsequent sampling in warm cloud. Simultaneously, the Learjet performed multiple penetrations of the ascending cumulus congestus (CuCg) cloud top. First primary ice was typically detected at temperatures colder than −10°C, consistent with measured ice nucleating particles. Subsequent production of ice via FFD SIP was strongly related to the concentration of supercooled large drops (SLDs), with diameters from about 0.2 to a few millimeters. The concentration of SLDs is directly linked to the rate of collision–coalescence, which depends primarily on the subcloud aerosol size distribution and cloud-base temperature. SPICULE supports previous observational results showing that FFD SIP efficiency could be deduced from the product of cloud-base temperature and maximum diameter of drops measured ∼300 m above cloud base. However, new measurements with higher concentrations of aerosol and total cloud-base drop concentrations show an attenuating effect on the rate of coalescence. The SPICULE dataset provides rich material for validation of numerical schemes of collision–coalescence and SIP to improve weather prediction simulations

The retrieval of hail kinetic energy with weather radars or its simulation in numerical models is challenging because of the shape complexity and variable density of hailstones. We combine 3D scans of individual hailstones with measurements of the particle size distributions (PSD) and T-matrix calculations to understand how hail reflectivity Z changes when approximating hailstones as spheroids, as compared to the realistic shapes obtained by 3D scanning technology. Additionally, recent terminal velocity relations are used to compare Z to the hail kinetic energy flux . We parameterize the hail backscattering cross sections at L, S, C, and X bands as a function of size between 0.5 and 5.0 cm, matching the range of the observed PSDs. The scattering calculations use the T-matrix method for size parameters below 1.0 and the discrete dipole approximation (DDA) method otherwise. The DDA calculations are done for 48 digital models of realistic hailstones of sizes between 1 and 5 cm. The DDA cross sections are calculated for multiple orientations and averaged assuming a fully random orientation distribution to provide a single value per hailstone. The T-matrix reflectivity assuming solid ice spheres presents negligible differences to DDA results for size parameters below 1.0. Therefore, T matrix was used to fill in the gaps left by the DDA calculations. The results are mapped to the same size bins of the observed PSDs, allowing the calculation of the radar reflectivity. This is then correlated to , allowing a potential improvement of past retrieval methods of from Z in multiple wavelengths.

The stability of ice crystal orientation is studied by modeling the air flow around ice crystals at moderate Reynolds number, where an ice crystal is approximated by a cylinder with three parameters: diameter D, length L, and zenith angle of the axis θ. In this paper the torque acting on ice crystals is simulated at different θ first and then a special θ with zero horizontal torque, denoted as θe, is sought as an equilibrium of ice crystal orientation. The equilibrium is classified into two kinds: stable and unstable. Ice crystals rotate to θe of stable equilibriums while deviating from θe of unstable ones once they are released into quiet air. Multiple equilibriums of ice crystal orientation are found via numerical simulations. A cylinder with D/L close to one has three equilibriums, two of which are stable (i.e., θe = 0 and 90°). A cylinder with D/L away from one has only two equilibriums, one of which is stable (i.e., either θe = 0 or 90°). In addition, an asymmetric cylinder has two, three or five equilibriums, and their θ e is sensitive to the distance between its geometrical center and its center of gravity. The sensitivity of θe to crystal asymmetry suggests large symmetric ice crystals tend to become asymmetric (or irregular) and subsequently oriented randomly.

The Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) is a NASA-sponsored field campaign to study wintertime snowstorms focusing on East Coast cyclones. This large cooperative effort takes place during the winters of 2020–23 to study precipitation variability in winter cyclones to improve remote sensing and numerical forecasts of snowfall. Snowfall within these storms is frequently organized in banded structures on multiple scales. The causes for the occurrence and evolution of a wide spectrum of snowbands remain poorly understood. The goals of IMPACTS are to characterize the spatial and temporal scales and structures of snowbands, understand their dynamical, thermodynamical, and microphysical processes, and apply this understanding to improve remote sensing and modeling of snowfall. The first deployment took place in January–February 2020 with two aircraft that flew coordinated flight patterns and sampled a range of storms from the Midwest to the East Coast. The satellite-simulating ER-2 aircraft flew above the clouds and carried a suite of remote sensing instruments including cloud and precipitation radars, lidar, and passive microwave radiometers. The in situ P-3 aircraft flew within the clouds and sampled environmental and microphysical quantities. Ground-based radar measurements from the National Weather Service network and a suite of radars located on Long Island, New York, along with supplemental soundings and the New York State Mesonet ground network provided environmental context for the airborne observations. Future deployments will occur during the 2022 and 2023 winters. The coordination between remote sensing and in situ platforms makes this a unique publicly available dataset applicable to a wide variety of interests.

Polarimetric microphysical retrievals reveal a great potential for the evaluation of numerical models and data assimilation. However, the accuracy of ice microphysical retrievals is still poorly explored. To evaluate these retrievals and assess their accuracy, polarimetric radar measurements are spatially and temporally collocated with in situ aircraft measurements obtained during the OLYMPEX campaign (Olympic Mountain Experiment). Retrievals for ice water content (IWC), total number concentration Nt, and mean volume diameter Dm of ice particles are assessed by comparing an in situ dataset obtained by the University of North Dakota (UND) Citation II aircraft with X-band Doppler on Wheels (DOW) measurements. Sector-averaged range height indicator (RHI) scans are used to derive vertical profiles of microphysical retrievals. The comparison of these estimates with in situ data provides insights into strengths, weaknesses, and the accuracy of the different retrievals and quantifies the improvements in polarimetry-informed retrievals compared to conventional, non-polarimetric ones. In particular, the recently introduced hybrid ice water content retrieval exploiting reflectivity ZH, differential reflectivity ZDR, and specific differential phase KDP outperforms other retrievals based on either (ZH, ZDR) or (ZH, KDP) or non-polarimetric retrievals in terms of correlations with in situ measurements and the root mean square error.

Our goal is to provide an overview of the microphysical measurements made during the C-FOG (Toward Improving Coastal Fog Prediction) field project. In addition, we evaluate microphysical parametrizations using the C-FOG dataset. The C-FOG project is designed to advance understanding of liquid fog formation, particularly its development and dissipation in coastal environments, so as to improve fog predictability and monitoring. The project took place along eastern Canada’s (Nova Scotia and Newfoundland) coastlines and open water environments from August−October 2018, where environmental conditions play an important role for late-season fog formation. Visibility, wind speed, and atmospheric turbulence along coastlines are the most critical weather-related factors affecting marine transportation and aviation. In the analysis, microphysical observations are summarized first and then, together with three-dimensional wind components, used for fog intensity (visibility) evaluation. Results suggest that detailed microphysical observations collected at the supersites and aboard the Research Vessel Hugh R. Sharp are useful for developing microphysical parametrizations. The fog life cycle and turbulence-kinetic-energy dissipation rate are strongly related to each other. The magnitudes of three-dimensional wind fluctuations are higher during the formation and dissipation stages. An array of cutting-edge instruments used for data collection provides new insight into the variability and intensity of fog (visibility) and microphysics. It is concluded that further modifications in microphysical observations and parametrizations are needed to improve fog predictability of numerical-weather-prediction models.

As the near-surface atmosphere over the Antarctic Plateau is cold and pristine, its physico-chemical conditions resemble to a certain extent those of the high troposphere where cirrus clouds form. In this paper, we carry out an observational analysis of two shallow fog clouds forming in situ at cirrus temperatures – that is, temperatures lower than 235 K – at Dome C, inner Antarctic Plateau. The combination of lidar profiles with temperature and humidity measurements from advanced thermo-hygrometers along a 45 m mast makes it possible to characterise the formation and development of the fog. High supersaturations with respect to ice are observed before the initiation of fog, and the values attained suggest that the nucleation process at play is the homogeneous freezing of solution aerosol droplets. This is the first time that in situ observations show that this nucleation pathway can be at the origin of an ice fog. Once nucleation occurs, the relative humidity gradually decreases down to subsaturated values with respect to ice in a few hours, owing to vapour deposition onto ice crystals and turbulent mixing. The development of fog is tightly coupled with the dynamics of the boundary layer which, in the first study case, experiences a weak diurnal cycle, while in the second case, it transits from a very stable to a weakly stable dynamical regime. Overall, this paper highlights the potential of the site of Dome C for carrying out observational studies of very cold cloud microphysical processes in natural conditions and using in situ ground-based instruments.

The objective of this work is to evaluate GOES-R (Geostationary Operational Environmental Satellites-R series) data-based fog conditions which occurred during the C-FOG (Toward Improving Coastal Fog Prediction) field campaign. The C-FOG campaign was designed to advance understanding of fog formation, development, and dissipation over coastal environments to improve predictability. The project took place along coastlines and open water environments of eastern Canada (Nova Scotia, and the Island of Newfoundland) during August−October of 2018 where environmental conditions play an important role for late season fog formation. During the C-FOG field campaign, coastal instruments were mainly located at the Ferryland supersite, Newfoundland, with two main sites, and five satellite sites, as well as on the Research Vessel Hugh R. Sharp. Key in-situ measurement instruments included microphysical, meteorological, radiation, and aerosol sensors. A fog spectral probe was used for measuring droplet spectra from 1–50 µm at the Ferryland supersite. A laser precipitation monitor with 100 µm to 10 mm size range and an optical particle counter with 0.3–17 µm at 16 spectral channels provided information for fog and drizzle discrimination. Remote sensing platforms, e.g. profiling microwave radiometer, ceilometer, microwave rain radar, lidar, meteorological towers, tethered balloons, and GOES-R products for fog coverage, and droplet size and liquid water path) were used to evaluate fog over horizontal and vertical dimensions. Results suggest that effective radius, phase, liquid water path, and liquid water content values obtained from GOES-R and the profiling microwave radiometer are comparable to ground-based in-situ observations. It is concluded that integration of observations and nowcasting products may help improve short-term local fog predictions.

The research outputs provided foundational knowledge on hailstone properties, microphysics, and severe storm dynamics [ ]a recent resurgence, little attention was paid to hail within the research communities, relative to more threatening perils (e g , tornadoes, hurricanes), despite the mounting costs of hail damage across the globe Figure 1 provides a time history of AMS journal publications that have “hail” or “hailstorm/s” in the title or as a keyword relative to other topics (i e , hurricanes/tropical cyclones, tornadoes, and climate change) The T-28 continued flying hail missions for 33 years, with its last flight in 2003 Since the 1980s, field programs have focused on severe storm dynamics and thermodynamics (VORTEX, STEPS, VORTEX-2, PECAN, TORUS, etc ) Since 2000, the population of Colorado has grown by 1 3 million people (2015 U S Census)

This study is the first to reach a global view of the precipitation process partitioning, using a combination of satellite and global climate modeling data. The pathways investigated are 1) precipitating ice (ice/snow/graupel) that forms above the freezing level and melts to produce rain (S) followed by additional condensation and collection as the melted precipitating ice falls to the surface (R); 2) growth completely through condensation and collection (coalescence), warm rain (W); and 3) precipitating ice (primarily snow) that falls to the surface (SS). To quantify the amounts, data from satellite-based radar measurements—CloudSat, GPM, and TRMM—are used, as well as climate model simulations from the Community Atmosphere Model (CAM) and the Met Office Unified Model (UM). Total precipitation amounts and the fraction of the total precipitation amount for each of the pathways is examined latitudinally, regionally, and globally. Carefully examining the contributions from the satellite-based products leads to the conclusion that about 57% of Earth’s precipitation follows pathway S, 15% R, 23% W, and 5% SS, each with an uncertainty of ±5%. The percentages differ significantly from the global climate model results, with the UM indicating smaller fractional S, more R, and more SS; and CAM showing appreciably greater S, negative R (indicating net evaporation below the melting layer), a much larger percentage of W and much less SS. Possible reasons for the wide differences between the satellite- and model-based results are discussed.

The global near-surface temperature increased by ~0.155 K per decade during 1979–2012, which resulted in decreasing snow and increasing rain events, retreating mountain glaciers and more frequent and intense rainfall extremes. Although surface temperature increases are well studied, less attention is given to the associated changes in the tropospheric thermal structure, such as melting level height, which affects cloud microphysics and surface precipitation. Here we use observations and reanalyses to show that the melting level height increased by 32 ± 14 m per decade over global land areas during 1979–2010, consistent with a warming atmosphere. This causes a transition from snow to rain, the enhanced melting of hail and an increased depth of warm cloud layers (cloud base to melting level distance). Warm cloud layers with a depth beyond ~3.5 km result in an intensification of extreme precipitation at twice the rate of the atmospheric moisture increases. Days with such environments increased by 25% per decade in populated regions, such as the eastern United States. Climate change has altered the vertical structure of atmospheric temperature. Global land observations show melting level height (the altitude where falling precipitation begins to melt) has increased, deepening the warm cloud layer and intensifying rainfall extremes at the expense of snow and hail.

This article illustrates how multifrequency radar observations can refine the mass–size parameterization of frozen hydrometeors in scattering models and improve the correlation between the radar observations and in situ measurements of microphysical properties of ice and snow. The data presented in this article were collected during the GPM Cold Season Precipitation Experiment (GCPEx) (2012) and Olympic Mountain Experiment (OLYMPEx) (2015) field campaigns, where the true mass–size relationship was not measured. Starting from size and shape distributions of ice particles measured in situ, scattering models are used to simulate an ensemble of reflectivity factors for various assumed mass–size parameterizations (MSP) of the power-law type. This ensemble is then collocated to airborne and ground-based radar observations, and the MSPs are refined by retaining only those that reproduce the radar observations to a prescribed level of accuracy. A versatile “retrieval dashboard” is built to jointly analyze the optimal MSPs and associated retrievals. The analysis shows that the optimality of an MSP depends on the physical assumptions made in the scattering simulators. This work confirms also the existence of a relationship between parameters of the optimal MSPs. Through the MSP optimization, the retrievals of ice water contentMand mean diameterDmseem robust to the change in meteorological regime (between GCPEx and OLYMPEx); whereas the retrieval of the diameter spreadSmseems more campaign dependent.

Cloud representation is one of the largest uncertainties in the current weather and climate models. In this article, the observations and modeling of the radiative effect on (cloud) microphysics (REM) from the Arctic to the Tropics are overviewed, providing a new direction to meet the challenge of cloud representation. REM deals with the radiation-induced temperature difference between cloud particles and air. It leads to two common phenomena observed at the surface—dew and frost—and impacts clouds aloft significantly, which is noticed via the wide occurrence of horizontally oriented ice crystals (HOICs). However, REM has been overlooked by all of the operational weather and climate models. Based on the bin model of REM and the global distribution of radiative cooling/warming, the observations of REM from several platforms (e.g., aircrafts, field campaigns, and satellites) are coordinated in this article, yielding a global picture on REM. As a result, the picture is compatible with the global distribution of HOICs and other ice crystal characteristics obtained from various clouds on the globe, such as diamond dust (or clear-sky precipitation) in the Arctic, sub-visual cirrus clouds in the tropical tropopause layer, and other cirrus clouds from the low to high latitudes. In addition, ice crystals possess relatively strong REM compared to liquid drops because their aspect ratio is usually not one. The global picture on REM can be used by the weather and climate modelers to diagnose their cloud representation biases. It can also be used to improve the atmospheric ice retrieval algorithm from satellite observations.

The tethered balloon-borne measurement system BELUGA (Balloon-bornE moduLar Utility for profilinG the lower Atmosphere) was deployed over the Arctic sea ice for 4 weeks in summer 2020 as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition. Using BELUGA, vertical profiles of dynamic, thermodynamic, aerosol particle, cloud, radiation, and turbulence properties were measured from the ground up to a height of 1,500 m. BELUGA was operated during an anomalously warm period with frequent liquid water clouds and variable sea ice conditions. Three case studies of liquid water phase, single-layer clouds observed on 3 days (July 13, 23, and 24, 2020) are discussed to show the potential of the collected data set to comprehensively investigate cloud properties determining cloud evolution in the inner Arctic over sea ice. Simulated back-trajectories show that the observed clouds have evolved within 3 different air masses (“aged Arctic,” “advected over sea ice,” and “advected over open ocean”), which left distinct fingerprints in the cloud properties. Strong cloud top radiative cooling rates agree with simulated results of previous studies. The weak warming at cloud base is mostly driven by the vertical temperature profile between the surface and cloud base. In-cloud turbulence induced by the cloud top cooling was similar in strength compared to former studies. From the extent of the mixing layer, it is speculated that the overall cloud cooling is stronger and thus faster in the warm oceanic air mass. Larger aerosol particle number concentrations and larger sizes were observed in the air mass advected over the sea ice and in the air mass advected over the open ocean.

An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming parameterised by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment For Future Precipitation Mission. During this campaign, in situ microphysical probes were mounted on the same aeroplane as the radars. This nearly perfectly co-located dataset of the remote and in situ measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content (IWC) and mean mass-weighted diameters obtaining root-mean-square errors of 0.13 and 0.15, respectively, for log 10IWC and log 10Dm . The retrieval of the degree of riming is more challenging, and only the algorithm that uses Doppler information obtains results that are highly correlated with the in situ data.

The terminal velocity (Vt) of ice hydrometeors is of high importance to atmospheric modeling. Vt is governed by the physical characteristics of a hydrometeor, including mass and projected area, as well as environmental conditions. When liquid hydrometeors coalesce to form larger hydrometeors, the resulting hydrometeor can readily be characterized by its spherical or near-spherical shape. For ice hydrometeors, it is more complicated because of the variability of ice shapes possible in the atmosphere as well as the inherent randomness in the aggregation process, which leads to highly variable characteristics. The abundance of atmospheric processes affecting ice particle dimensional characteristics creates potential for highly variable Vt for ice particles that are predicted or measured to be of the “same size.” In this article we explore the variability of ice hydrometeor Vt both theoretically and through the use of experimental observations. Theoretically, the variability in Vt is investigated by analyzing the microphysical characteristics of randomly aggregated hexagonal shapes. The modeled dimensional characteristics are then compared to aircraft probe measurements to constrain the variability in atmospheric ice hydrometeor Vt. Results show that the spread in Vt can be represented with Gaussian distributions relative to a mean. Variability expressed as the full width at half maximum of the normalized Gaussian probability distribution function is around 20%, with somewhat higher values associated with larger particle sizes and warmer temperatures. Field campaigns where mostly convective clouds were sampled displayed low variability, while Arctic and midlatitude winter campaigns showed broader Vt spectra.

Hail and graupel are linked to lightning production and are important components of cloud evolution. Hail can also cause significant damage when it precipitates to the surface. The accurate prediction of the amount and location of hail and graupel and the effects on the other hydrometeor species depends upon the size distribution assumed. Here, we use ~310 km of in situ observations from flights of the South Dakota School of Mines and Technology T-28 storm-penetrating aircraft to constrain the representation of the particle size distribution (PSD) of hail. The maximum ~1-km hail water content encountered was 9 g m−3. Optical probe PSD measurements are normalized using two-moment normalization relations to obtain an underlying exponential shape. By linking the two normalizing moments through a power law, a parameterization of the hail PSD is provided based on the hail water content only. Preliminary numerical weather simulations indicate that the new parameterization produces increased radar reflectivity relative to commonly used PSD representations.

Severe (>2.5 cm) hail causes >$5 billion in damage annually in the United States. However, radar sizing of hail remains challenging. Typically, spheroids are used to represent hailstones in radar forward operators and to inform radar hail-sizing algorithms. However, natural hailstones can have irregular shapes and lobes; these details significantly influence the hailstone’s scattering properties. The high-resolution 3D structure of real hailstones was obtained using a laser scanner for hail collected during the 2016–17 Insurance Institute for Business and Home Safety (IBHS) Hail Field Study. Plaster casts of several record hailstones (e.g., Vivian, South Dakota, 2010) were also scanned. The S-band scattering properties of these hailstones were calculated with the discrete dipole approximation (DDA). For comparison, scattering properties of spheroidal approximations of each hailstone (with identical maximum and minimum dimensions and mass) were calculated with the T matrix. The polarimetric radar variables have errors when using spheroids, even for small hail. Spheroids generally have smaller variations in the polarimetric variables than the real hailstones. This increased variability is one reason why the correlation coefficienttends to be lower in observations than in forward-simulated cases using spheroids. Backscatter differential phaseδalso is found to have large variance, particularly for large hailstones. Irregular hailstones with a thin liquid layer produce enhanced and more variable values for reflectivity factor at horizontal polarizationZHH, differential reflectivityZDR, specific differential phaseKDP, linear depolarization ratio (LDR), andδcompared with dry hailstones;is also significantly reduced.

This study quantifies how far snow can fall into the melting layer (ML) before all snow has melted by examining a combination of in-situ observations from aircraft measurements in Lagrangian spiral descents from above through the ML and descents and ascents into the ML, as well as an extensive database of NOAA surface observer reports during the past 50 years. The airborne data contain information on the particle phase (solid, mixed, or liquid), population size distributions and shapes, along with temperature, relative humidity, and vertical velocity. A wide range of temperatures and ambient relative humidities are used for both the airborne and ground-based data. It is shown that an ice bulb temperature of 0°C, together with the air temperature and pressure (altitude), are good first order predictors of the highest temperature snowflakes can survive in the melting layer before completely melting. Particle size is also important, as is whether the particles are graupel or hail. If the relative humidity is too low, the particles will sublimate completely as they fall into the melting layer. Snow as warm as +7°C is observed from aircraft measurements and surface observations. Snow pellets survive to even warmer temperatures. Relationships are developed to represent the primary findings.

Observations and prediction of extreme weather (Wx) conditions are important for land, air and sea or water transportation applications. These conditions adversely affect the economic and social life of people. Extreme Wx conditions for aviation operations for example, include, gust (Ug), wind (Uh), and turbulence (U’), low visibility (Vis), fog and frost, and icing as well as heavy precipitation. These conditions can be studied either in the natural atmosphere or in the laboratory. There have been several aircraft and balloon based in-situ studies related to extreme Wx conditions affecting aviation operations. However, studying extreme Wx conditions from aircraft observations is limited due to safety and sampling issues, instrument uncertainties, and even the possibility of the aircraft producing its own physical and dynamical effects. Remote sensing-based techniques (e.g., retrieval techniques) for studying extreme Wx conditions usually represent a volume that cannot characterize the important scales, and also represents indirect observations. Therefore, climatic wind tunnel simulations of atmospheric processes together with field observations can help us to better evaluate the interactions among microphysical and dynamical processes affecting extreme Wx conditions e.g., cold air temperatures (Ta) and low/high relative humidity with respect to water (RHw). The Climatic Wind Tunnel (CWT) in the Automotive Centre of Excellence (ACE) at the Ontario Tech University has a large semi-open jet test chamber with a flow area of 7-13 m2 that can precisely control Ta down to -40ºC, and Uh up to 250 km hr-1. Ice and liquid phases of particle size distributions n the CWT are measured with optical probes such as GCIP, CDP, BCP, FMD, and LPM probes (Gultepe et al 2019, PAAG). The ACE CWT employs several modes of generating sprays, including a spray nozzle array suspended in its settling chamber and fed by heated pressurized de-ionized water to create supercooled droplets, a snow gun also located in the settling chamber, and a spray rig at the nozzle exit, to create a wide range of particle sizes from a few µm up to mm size range to create extreme Wx conditions. These set-ups, together with a range of cold Ta and RHw, plus a wide range of Uh, enabled simulation of severe Wx conditions, including icing, Vis, strong Uh and U’, ice fog and frost, freezing fog, heavy snow, and blizzard conditions. Overall, the results from the CWT simulations supported by the Ontario Tech University AViation MEteorological Supersite (AVMES) observations will be summarized for the aviation operations representing cold environments.

Orographic wave clouds offer a natural laboratory to investigate cloud microphysical processes and their representation in atmospheric models. Wave clouds impact the larger-scale flow by the vertical redistribution of moisture and aerosol. Here we use detailed cloud microphysical observations from the Ice in Clouds Experiment – Layer Clouds (ICE-L) campaign to evaluate the recently developed Cloud Aerosol Interacting Microphysics (CASIM) module in the Met Office Unified Model (UM) with a particular focus on different parameterizations for heterogeneous freezing. Modelled and observed thermodynamic and microphysical properties agree very well (deviation of air temperature  K; specific humidity  g kg−1; vertical velocity  m s−1; cloud droplet number concentration  cm−3), with the exception of an overestimated total condensate content and too long a sedimentation tail. The accurate reproduction of the environmental thermodynamic and dynamical wave structure enables the model to reproduce the right cloud in the right place and at the right time. All heterogeneous freezing parameterizations except Atkinson et al. (2013) perform reasonably well, with the best agreement in terms of the temperature dependency of ice crystal number concentrations for the parameterizations of DeMott et al. (2010) and Tobo et al. (2013). The novel capabilities of CASIM allowed testing of the impact of assuming different soluble fractions of dust particles on immersion freezing, but this is found to only have a minor impact on hydrometeor mass and number concentrations. The simulations were further used to quantify the modification of moisture and aerosol profiles by the wave cloud. The changes in both variables are on order of 15 % of their upstream values, but the modifications have very different vertical structures for the two variables. Using a large number of idealized simulations we investigate how the induced changes depend on the wave period (100–1800 s), cloud top temperature (−15 to −50 ∘C), and cloud thickness (1–5 km) and propose a conceptual model to describe these dependencies.

Tropical anvil clouds have a profound impact on Earth's weather and climate. Their role in Earth's energy balance and hydrologic cycle is heavily modulated by the vertical structure of the microphysical properties for various hydrometeors in these clouds and their dependence on the ambient environmental conditions. Accurate representations of the variability and covariability of such vertical structures are key to both the satellite remote sensing of cloud and precipitation and numerical modeling of weather and climate, which remain a challenge. This study presents a new method to combine vertically resolved observations from CloudSat radar reflectivity and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud masks with probability distributions of cloud microphysical properties and the ambient atmospheric conditions from detailed in situ measurements on tropical anvils sampled during the National Aeronautics and Space Administration TC4 (Tropical Composition, Cloud and Climate Coupling) mission. We focus on the microphysical properties of the vertical distribution of ice water content, particle size distributions, and effective sizes for different hydrometeors, including ice particles and supercooled liquid droplets. Results from this method are compared with those from in situ data alone and various CloudSat/Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud retrievals. The sampling limitation of the field experiment and algorithm limitations in the current retrievals is highlighted, especially for the liquid cloud particles, while a generally good agreement with ice cloud microphysical properties is seen from different methods. While the method presented in this study is applied to tropical anvil clouds observed during TC4, it can be readily employed to study a broad range of ice clouds sampled by various field campaigns., Key Points The vertical structure of ice cloud microphysics is studied by combining field campaign in situ measurements with satellite observationsA generally good agreement with ice cloud microphysical properties below 12 km is seen from in situ observations and satellite retrievalsResults indicate the sampling limitation of the field experiment and algorithm limitations in the satellite retrievals

Ice fog consists of suspended small ice crystals with maximum sizes less than about 200 μm, having similar fall velocities as fog droplets, and that often reduces visibility to less than 1 km. Its formation is strongly dependent on high number concentrations of available heterogeneous ice nuclei (IN) at temperatures (T) > −40 oC, homogeneous nucleation below −40 oC, and available moisture in the air. Radiative cooling, advective cooling, and cold air subsidence, particularly over the Polar region or high elevation mountainous geographical regions, play an important role in its formation and development. Ice fog crystals form at cold T when the relative humidity with respect to ice (RHi) is ≥100%. Favorable ice nucleation conditions typically occur at T < −15 oC and its microphysical characteristics and their evolution needs to be better understood for a physically based representation in numerical forecast models. This is likely to be of growing societal importance due to the known sensitivity of the Arctic environment to climate change. Accidents related to low visibility over the northern latitudes may increase tenfold over the Arctic regions because of increasing population and traffic. This suggests that ice fog conditions can have major impacts on aviation and ground/water-based transportation, as well as on climate change and ecosystem. These open issues, as well as challenges related to ice fog measurements and predictions, are discussed in detail, and its importance for evaluating weather and climate conditions over cold environments are emphasized.

In this study, a nonparametric method to estimate precipitating ice from multiple-frequency radar observations is investigated. The method does not require any assumptions regarding the distribution of ice particle sizes and relies on an efficient search procedure to incorporate information from observed particle size distributions (PSDs) in the estimation process. Similar to other approaches rooted in optimal-estimation theory, the nonparametric method is robust in the presence of noise in observations and uncertainties in the forward models. Over 200 000 PSDs derived from in situ observations collected during the Olympic Mountains Experiment (OLYMPEX) and Integrated Precipitation and Hydrology Experiment (IPHEX) field campaigns are used in the development and evaluation of the nonparametric estimation method. These PSDs are used to create a database of ice-related variables and associated computed radar reflectivity factors at the Ku, Ka, and W bands. The computed reflectivity factors are used to derive precipitating ice estimates and investigate the associated errors and uncertainties. The method is applied to triple-frequency radar observations collected during OLYMPEX and IPHEX. Direct comparisons of estimated ice variables with estimates from in situ instruments show results consistent with the error analysis. Global application of the method requires an extension of the supporting PSD database, which can be achieved through the processing of information from additional past and future field campaigns.

This study uses novel approaches to estimate the fall characteristics of hail, covering a size range from about 0.5 to 7 cm, and the drag coefficients of lump and conical graupel. Three-dimensional (3D) volume scans of 60 hailstones of sizes from 2.5 to 6.7 cm were printed in three dimensions using acrylonitrile butadiene styrene (ABS) plastic, and their terminal velocities were measured in the Mainz, Germany, vertical wind tunnel. To simulate lump graupel, 40 of the hailstones were printed with maximum dimensions of about 0.2, 0.3, and 0.5 cm, and their terminal velocities were measured. Conical graupel, whose three dimensions (maximum dimension 0.1–1 cm) were estimated from an analytical representation and printed, and the terminal velocities of seven groups of particles were measured in the tunnel. From these experiments, with printed particle densities from 0.2 to 0.9 g cm−3, together with earlier observations, relationships between the drag coefficient and the Reynolds number and between the Reynolds number and the Best number were derived for a wide range of particle sizes and heights (pressures) in the atmosphere. This information, together with the combined total of more than 2800 hailstones for which the mass and the cross-sectional area were measured, has been used to develop size-dependent relationships for the terminal velocity, the mass flux, and the kinetic energy of realistic hailstones.

Ice generation and evolution in tropical maritime convective clouds are still poorly understood and challenging to model. Aircraft measurements during the Ice in Clouds-Tropical (ICE-T) project suggest that the observed ice particles in intense convective clouds are primarily small at relatively warm temperature (between −7 °C and −10 °C), and large frozen drops are detected at a temperature colder than −10 °C. However, the ice particle size distributions (PSDs) between −7 °C and −10 °C modelled using a parcel model with spectral bin microphysics scheme are much broader than the observation. To interpret the difference in the temperature-dependent ice PSD evolution between the model simulations and the observations, the freezing times and temperatures of supercooled drops are modelled and analyzed. The results indicate that the freezing time (from the initial nucleation to fully frozen) must be considered; it is not instantaneous, and is longer for large drops than for small drops. In strong updrafts, such as that sampled by the Learjet during ICE-T, large freezing drops may be carried upwards to a temperature lower than their nucleation temperature before they are fully frozen. This offers a feasible explanation for the temperature-dependent ice particle size evolution in strong updrafts observed during ICE-T. In models, drop freezing is normally assumed to be instantaneous, which is not realistic; the models yields broader ice PSDs between −7 °C and −10 °C than is observed. The results highlight the importance to consider the freezing time of supercooled drops in interpreting the observed and modelled ice PSDs in growing turrets and in modelling ice generation in cloud resolving models. To better understand the time-dependent drop freezing and its impact on the microphysics and dynamics of convective clouds, more field measurements and laboratory experiments, as well as modelling studies are needed.

We use the Atmospheric Infrared Sounder (AIRS) version 6 ice cloud property and thermodynamic phase retrievals to quantify variability and 14-year trends in ice cloud frequency, ice cloud top temperature (Tci), ice optical thickness (τi) and ice effective radius (rei). The trends in ice cloud properties are shown to be independent of trends in information content and χ2. Statistically significant decreases in ice frequency, τi, and ice water path (IWP) are found in the SH and NH extratropics, but trends are of much smaller magnitude and statistically insignificant in the tropics. However, statistically significant increases in rei are found in all three latitude bands. Perturbation experiments consistent with estimates of AIRS radiometric stability fall significantly short of explaining the observed trends in ice properties, averaging kernels, and χ2 trends. Values of rei are larger at the tops of opaque clouds and exhibit dependence on surface wind speed, column water vapour (CWV) and surface temperature (Tsfc) with changes up to 4–5 µm but are only 1.9 % of all ice clouds. Non-opaque clouds exhibit a much smaller change in rei with respect to CWV and Tsfc. Comparisons between DARDAR and AIRS suggest that rei is smallest for single-layer cirrus, larger for cirrus above weak convection, and largest for cirrus above strong convection at the same cloud top temperature. This behaviour is consistent with enhanced particle growth from radiative cooling above convection or large particle lofting from strong convection.

Two methods for deriving relationships between the equivalent radar reflectivity factor Ze and the snowfall rate S at three radar wavelengths are described. The first method uses collocations of in situ aircraft (microphysical observations) and overflying aircraft (radar observations) from two field programs to develop Ze–S relationships. In the second method, measurements of Ze at the top of the melting layer (ML), from radars on the Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Measurement (GPM), and CloudSat satellites, are related to the retrieved rainfall rate R at the base of the ML, assuming that the mass flux through the ML is constant. Retrievals of R are likely to be more reliable than S because far fewer assumptions are involved in the retrieval and because supporting ground-based validation data are available. The Ze–S relationships developed here for the collocations and the mass-flux technique are compared with those derived from level 2 retrievals from the standard satellite products and with a number of relationships developed and reported by others. It is shown that there are substantial differences among them. The relationships developed here promise improvements in snowfall-rate retrievals from satellite-based radar measurements.

The squall-line event on 20 May 2011, during the Midlatitude Continental Convective Clouds (MC3E) field campaign has been simulated by three bin (spectral) microphysics schemes coupled into the Weather Research and Forecasting (WRF) Model. Semi-idealized three-dimensional simulations driven by temperature and moisture profiles acquired by a radiosonde released in the preconvection environment at 1200 UTC in Morris, Oklahoma, show that each scheme produced a squall line with features broadly consistent with the observed storm characteristics. However, substantial differences in the details of the simulated dynamic and thermodynamic structure are evident. These differences are attributed to different algorithms and numerical representations of microphysical processes, assumptions of the hydrometeor processes and properties, especially ice particle mass, density, and terminal velocity relationships with size, and the resulting interactions between the microphysics, cold pool, and dynamics. This study shows that different bin microphysics schemes, designed to be conceptually more realistic and thus arguably more accurate than bulk microphysics schemes, still simulate a wide spread of microphysical, thermodynamic, and dynamic characteristics of a squall line, qualitatively similar to the spread of squall-line characteristics using various bulk schemes. Future work may focus on improving the representation of ice particle properties in bin schemes to reduce this uncertainty and using the similar assumptions for all schemes to isolate the impact of physics from numerics.

In this study, two parameterizations of ice nucleation rate on dust particles are used in a parcel model to simulate aircraft measurements of ice crystal number concentration Ni in the Arctic. The parcel model has detailed microphysics for droplet and ice nucleation, growth, and evaporation with prescribed vertical air velocities. Three dynamic regimes are considered, including large-scale ascent, cloud-top generating cells, and their combination. With observed meteorological conditions and aerosol concentrations, the parcel model predicts the number concentrations of size-resolved ice crystals, which may be compared to aircraft measurements. Model results show rapid changes with height/time in relative humidity, Ni, and thermodynamic phase partitioning, which is not resolved in current climate and weather forecasting models. Parameterizations for ice number and nucleation rate in mixed-phase stratus clouds are thus developed based on the parcel model results to represent the time-integrated effect of some microphysical processes in large-scale models.

Empirical power-law relations between the equivalent radar reflectivity factor Ze and the slope parameter of the gamma function Λ (i.e., Λ = c; used to describe ice hydrometeor size distributions) are derived. The Λ parameter can also be considered as a size parameter since it is proportional to the inverse of the hydrometeor characteristic size, which is an important geophysical parameter describing the entire distribution. Two datasets from two-dimensional microphysical probes, collected during aircraft flights in subtropical and midlatitude regions, were used to obtain Λ by fitting measured size distributions. Reflectivity for different radar frequencies was calculated from microphysical probe data by using nonspherical-particle models. The derived relations have exponent d values that are approximately from −0.35 to −0.40, and the prefactors c are approximately between 30 and 55 (Λ: cm−1; Ze: mm6 m−3). There is a tendency for d and c to decrease when radar frequency increases from Ku band (~14 GHz) to W band (~94 GHz). Correlation coefficients between Ze and Λ can be very high (~0.8), especially for lower frequencies. Such correlations are similar to those for empirical relations between reflectivity and ice water content (IWC), which are used in many modeling and remote sensing applications. Close correspondences of reflectivity to both Λ and IWC are due to a relatively high correlation between these two microphysical parameters. Expected uncertainties in estimating Λ from reflectivity could be as high as a factor of 2, although estimates at lower radar frequencies are more robust. Stratifying retrievals by temperature could result in relatively modest improvement of Λ estimates.

International audience; Mean properties of individual contrails are characterized for a wide range of jet aircraft as a function of age during their life cycle from seconds to 11.5 h (7.4-18.7 km altitude, -88 to -31 °C ambient temperature), based on a compilation of about 230 previous in situ and remote sensing measurements. The airborne, satellite, and ground-based observations encompass exhaust contrails from jet aircraft from 1972 onwards, as well as a few older data for propeller aircraft. The contrails are characterized by mean ice particle sizes and concentrations, extinction, ice water content, optical depth, geometrical depth, and contrail width. Integral contrail properties include the cross-section area and total number of ice particles, total ice water content, and total extinction (area integral of extinction) per contrail length. When known, the contrail-causing aircraft and ambient conditions are characterized. The individual datasets are briefly described, including a few new analyses performed for this study, and compiled together to form a contrail library (COLI). The data are compared with results of the Contrail Cirrus Prediction (CoCiP) model. The observations confirm that the number of ice particles in contrails is controlled by the engine exhaust and the formation process in the jet phase, with some particle losses in the wake vortex phase, followed later by weak decreases with time. Contrail cross sections grow more quickly than expected from exhaust dilution. The cross-section-integrated extinction follows an algebraic approximation. The ratio of volume to effective mean radius decreases with time. The ice water content increases with increasing temperature, similar to non-contrail cirrus, while the equivalent relative humidity over ice saturation of the contrail ice mass increases at lower temperatures in the data. Several contrails were observed in warm air above the Schmidt-Appleman threshold temperature. The emission index of ice particles, i.e., the number of ice particles formed in the young contrail per burnt fuel mass, is estimated from the measured concentrations for estimated dilution; maximum values exceed 1015 kg-1. The dependence of the data on the observation methods is discussed. We find no obvious indication for significant contributions from spurious particles resulting from shattering of ice crystals on the microphysical probes.