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The macro- and microphysical properties of clouds can reflect their vertical physical structure and evolution and are important indications of the formation and development of precipitation. We used four-year merged CloudSat-CALIPSO-MODIS products to distinguish the macro- and microphysical properties of precipitating and non-precipitating clouds over central-eastern China during the warm season (May–September). Our results showed that the clouds were dominated by single- and double-layer forms with occurrence frequencies > 85%. Clouds with a low probability of precipitation (POP) were usually geometrically thin. The POP showed an increasing trend with increases in the cloud optical depth, liquid water path, and ice water path, reaching maxima of 50%, 60%, and 75%, respectively. However, as cloud effective radius (CER) increased, the POP changed from an increasing to a decreasing trend for a CER > 22 μm, in contrast with our perception that large particles fall more easily against updrafts, but this shift can be attributed to the transition of the cloud phase from mixed clouds to ice clouds. A high POP > 60% usually occurred in mixed clouds with vigorous ice-phase processes. There were clear differences in the microphysical properties of non-precipitating and precipitating clouds. In contrast with the vertical evolution of non-precipitating clouds with weaker reflectivity, precipitating clouds were present above 0 dBZ with a significant downward increase in reflectivity, suggesting inherent differences in cloud dynamical and microphysical processes. Our findings highlight the differences in the POP of warm and mixed clouds, suggesting that the low frequency of precipitation from water clouds should be the focus of future studies.

As a component of Earth’s hydrologic cycle, and especially at higher latitudes, falling snow creates snowpack accumulation that in turn provides a large proportion of the freshwater resources required by many communities throughout the world. To assess the relationships between remotely sensed snow measurements with in situ measurements, a winter field project, termed the Global Precipitation Measurement (GPM) Cold Season Precipitation Experiment (GCPEx), was carried out in the winter of 2011/12 in Ontario, Canada. Its goal was to provide information on the precipitation microphysics and processes associated with cold season precipitation to support GPM snowfall retrieval algorithms that make use of a dual-frequency precipitation radar and a passive microwave imager on board the GPM core satellite and radiometers on constellation member satellites. Multiparameter methods are required to be able to relate changes in the microphysical character of the snow to measureable parameters from which precipitation detection and estimation can be based. The data collection strategy was coordinated, stacked, high-altitude, and in situ cloud aircraft missions with three research aircraft sampling within a broader surface network of five ground sites that in turn were taking in situ and volumetric observations. During the field campaign 25 events were identified and classified according to their varied precipitation type, synoptic context, and precipitation amount. Herein, the GCPEx field campaign is described and three illustrative cases detailed.

Improved snowfall predictions require accurate knowledge of the properties of ice crystals and snow particles, such as their size, cross-sectional area, shape, and fall speed. The fall speed of ice particles is a critical parameter for the representation of ice clouds and snow in atmospheric numerical models, as it determines the rate of removal of ice from the modelled clouds. Fall speed is also required for snowfall predictions alongside other properties such as ice particle size, cross-sectional area, and shape. For example, shape is important as it strongly influences the scattering properties of these ice particles and thus their response to remote sensing techniques. This work analyzes fall speed as a function of particle size (maximum dimension), cross-sectional area, and shape using ground-based in situ measurements. The measurements for this study were done in Kiruna, Sweden, during the snowfall seasons of 2014 to 2019, using the ground-based in situ instrument Dual Ice Crystal Imager (D-ICI). The resulting data consist of high-resolution images of falling hydrometeors from two viewing geometries that are used to determine particle size (maximum dimension), cross-sectional area, area ratio, orientation, and the fall speed of individual particles. The selected dataset covers sizes from about 0.06 to 3.2 mm and fall speeds from 0.06 to 1.6 m s−1. Relationships between particle size, cross-sectional area, and fall speed are studied for different shapes. The data show in general low correlations to fitted fall speed relationships due to large spread observed in fall speed. After binning the data according to size or cross-sectional area, correlations improve, and we can report reliable parameterizations of fall speed vs. particle size or cross-sectional area for part of the shapes. For most of these shapes, the fall speed is better correlated with cross-sectional area than with particle size. The effects of orientation and area ratio on the fall speed are also studied, and measurements show that vertically oriented particles fall faster on average. However, most particles for which orientation can be defined fall horizontally.

Since the first Global Energy and Water Exchanges cloud assessment a decade ago, existing cloud property retrievals have been revised and new retrievals have been developed. The new global long-term cloud datasets show, in general, similar results to those of the previous assessment. A notable exception is the reduced cloud amount provided by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Science Team, resulting from an improved aerosol–cloud distinction. Height, opacity and thermodynamic phase determine the radiative effect of clouds. Their distributions as well as relative occurrences of cloud types distinguished by height and optical depth are discussed. The similar results of the two assessments indicate that further improvement, in particular on vertical cloud layering, can only be achieved by combining complementary information. We suggest such combination methods to estimate the amount of all clouds within the atmospheric column, including those hidden by clouds aloft. The results compare well with those from CloudSat-CALIPSO radar–lidar geometrical profiles as well as with results from the International Satellite Cloud Climatology Project (ISCCP) corrected by the cloud vertical layer model, which is used for the computation of the ISCCP-derived radiative fluxes. Furthermore, we highlight studies on cloud monitoring using the information from the histograms of the database and give guidelines for: (1) the use of satellite-retrieved cloud properties in climate studies and climate model evaluation and (2) improved retrieval strategies.

The microphysical attributes of black carbon (BC) can determine its absorption and hygroscopic properties. However, long-term information is difficult to obtain from the field. In this study, the BC properties including mass concentration, the coating volume ratio (VR) relative to the refractory BC (rBC), the rBC diameter and the fraction of cloud condensation nuclei (CCN), are derived from a number of field experiments using a random forest model. This model effectively derives the long-term BC microphysical properties in the Beijing region from 2013 to 2020 using continuous measurements of particulate matter, gas, BC mass concentration and meteorological parameters. The results reveal notably higher BC coatings (mean VR = 7.2) and a greater fraction of CCN-like BC (51%) in the winter compared to other seasons. Following the implementation of national air pollution control measures in 2017, BC mass exhibited a substantial reduction of 60% (29%) in the winter (summer), and VR decreased by 45% (24%). Apart from the influence of meteorological variations, these can be attributed to the declined primary emissions and the gas precursors which are associated with secondary formation of BC coatings. The reduction of both BC mass loading and coatings leads to its solar absorption decreasing by 50%, and the fraction of CCN-like BC (likely in clouds) decreasing by 23%. Environmental regulation will therefore continue to reduce both direct and indirect radiative impacts of BC in this region.

The understanding of the macro- and micro-structure, particle spectrum parameters, and their evolutions in different parts of stratocumulus clouds based on aircraft observation data, is important basic data for the development of cloud microphysical parameterization schemes and the quantitative retrieval of cloud-precipitation by radar and satellite detections. In this study, a total of ten vertical measurements during three aircraft observations were selected to analyze the vertical distribution of cloud microphysical properties in different parts of stratocumulus clouds in Hebei, North China. It was found that the downdraft in the cumulus cloud area was stronger than that in the stratiform cloud area, with the temperature at the same height higher than that in the stratiform cloud area, and the height of the 0 °C layers was correspondingly higher. In terms of particle spectrum parameters, the intercept and slope parameters of particle spectrum below melting levels in the cumulus part were higher than those in stratiform clouds area in the same weather process. In different vertical detection, it was found that the ice particles have begun to melt in the negative temperature layer near 0 °C level, and there might be sublimation, fragmentation, and aggregation in the melting process of ice phase particles. In addition, the melting process changed the spectral parameters greatly and also changed the correlation between the intercept and slope of the particle spectrum. The slope below the 0 °C level increased with the increase of intercept, which was greater than that above the 0 °C level. The relationship obtained between the intercept parameter of the particle’s spectrum and temperature, and the correlation between the maximum diameter and slope parameter of the particle spectrum, have certain reference significance for cloud physical parameterization and the quantitative retrieval of cloud precipitation by radar and satellite in North China and similar climate background areas.

Aerosols play an important role in global meteorology and climate, as well as in air transport and human health, but there are still many unknowns on their effects and importance, in particular for the coarser (giant and ultragiant) aerosol particles. In this study, we aim to exploit the synergy between Raman lidar and Ka-band cloud radar to enlarge the size range in which aerosols can be observed and characterized. To this end, we developed an inversion technique that retrieves the aerosol microphysical properties based on cloud radar reflectivity and linear depolarization ratio. We applied this technique to a 6-year-long dataset, which was created using a recently developed methodology for the identification of giant aerosols in cloud radar measurements, with measurements from Potenza in Italy. Similarly, using collocated and concurrent lidar profiles, a dataset of aerosol microphysical properties using a widely used inversion technique complements the radar-retrieved dataset. Hence, we demonstrate that the combined use of lidar- and radar-derived aerosol properties enables the inclusion of particles with radii up to 12 µm, which is twice the size typically observed using atmospheric lidar alone.

Progress in numerical models and improved computational capabilities have significantly advanced our comprehension of how aerosol particles impact thunderstorm clouds. Yet, much of this research has focused on employing bulk microphysics models to explain the impacts of aerosol particles acting as cloud condensation nuclei (CCN) on electrical activities in thunderstorm clouds. The bulk thunderstorm models use mean sizes of particles and terminal-fall velocities. This causes calculation deviation in the electrification simulation, which in turn leads to deviations in the simulation of lightning processes. Developing this further, we established a three-dimensional high-resolution cloud–aerosol bin thunderstorm model with electrification and lightning to provide more accurate microphysics and dynamic fields for studying electrical activities. For evaluating the impacts of aerosol particles, specifically CCN, on the properties of continental thunderclouds, aerosols from both clean and polluted continental environments were selected. Cloud simulations indicate that droplets develop a narrower spectrum in polluted continental conditions, and weakened ice crystal growth increases the number of small ice crystals compared to clean conditions. Smaller droplets and ice crystals result in less effective riming and decreased graupel concentration and mass. Consequently, a significant decrease in large ice particles leads to a weakened process of charge separation under conditions of pollution. As a direct result, there is about a 43% reduction in lightning frequency and a delay of approximately 5 min in the lightning process under polluted conditions.

A fresh biomass‐burning pollution plume was monitored and characterized in terms of optical and microphysical properties for the first time with a combination of Raman lidar and star‐ and sun‐photometers. Such an instrument combination is highly useful for 24‐h monitoring of pollution events. The observations were made at Granada (37.16°N, 3.6°W), Spain. The fresh smoke particles show a rather pronounced accumulation mode and features markedly different from those reported for aged particles. We find lidar ratios around 60–65 sr at 355 nm and 532 nm, and particle effective radii below 0.20 μm. We find low values of the single‐scattering albedo of 0.76–0.9 depending on measurement wavelength. The numbers are lower than what have been found for aged, long‐range‐transported smoke that originated from boreal fires in Canada and Siberia.

The impact of aerosol spatio-temporal variability on the Arctic radiative budget is not fully constrained. This case study focuses on the intra-Arctic modification of long-range transported aerosol and its direct aerosol radiative effect (ARE). Different types of air-borne and ground-based remote sensing observations (from Lidar and sun-photometer) revealed a high tropospheric aerosol transport episode over two parts of the European Arctic in April 2018. By incorporating the derived aerosol optical and microphysical properties into a radiative transfer model, we assessed the ARE over the two locations. Our study displayed that even in neighboring Arctic upper tropospheric levels, aged aerosol was transformed due to the interplay of removal processes (nucleation scavenging and dry deposition) and alteration of the aerosol source regions (northeast Asia and north Europe). Along the intra-Arctic transport, the coarse aerosol mode was depleted and the visible wavelength Lidar ratio (LR) increased significantly (from 15 to 64–82 sr). However, the aerosol modifications were not reflected on the ARE. More specifically, the short-wave (SW) atmospheric column ARE amounted to +4.4 - +4.9 W m−2 over the ice-covered Fram Strait and +4.5 W m−2 over the snow-covered Ny-Ålesund. Over both locations, top-of-atmosphere (TOA) warming was accompanied by surface cooling. These similarities can be attributed to the predominant accumulation mode, which drives the SW radiative budget, as well as to the similar layer altitude, solar geometry, and surface albedo conditions over both locations. However, in the context of retreating sea ice, the ARE may change even along individual transport episodes due to the ice albedo feedback.