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Several functional forms of cloud particle size distributions (PSDs) have been used in numerical modeling and remote sensing retrieval studies of clouds and precipitation, including exponential, gamma, lognormal, and Weibull distributions. However, there is no satisfying theoretical explanation as to why certain distribution forms preferentially occur instead of others. Intuitively, the analytical form of a PSD can be derived by directly solving the general dynamic equation, but no analytical solutions have been found yet. Instead of a process-level approach, the use of the principle of maximum entropy (MaxEnt) for determining the theoretical form of PSDs from the perspective of system is examined here. MaxEnt theory states that the probability density function with the largest information entropy among a group satisfying the given properties of the variable should be chosen. Here, the issue of variability under coordinate transformations that arises using the Gibbs–Shannon definition of entropy is identified, and the use of the concept of relative entropy to avoid these problems is discussed. Focusing on cloud physics, the four-parameter generalized gamma distribution is proposed as the analytical form of a PSD using the principle of maximum (relative) entropy with assumptions on power-law relations among state variables, scale invariance, and a further constraint on the expectation of one state variable (e.g., bulk water mass). The four-parameter generalized gamma distribution is very flexible to accommodate various type of constraints that could be assumed for cloud PSDs.

Many studies have provided microphysical retrievals using radars of different frequencies, platforms, and methodologies. However, little is known about the consistency of retrievals derived from different radar platforms (i.e., airborne or spaceborne vs. groundbased) and their methodologies. This study is the first to directly compare snow mean volume diameter (Dm) retrievals from both nadir-pointing airborne multi-frequency radars and ground-based polarimetric range-height indicator (RHI) radar scans along a coincident airborne flight track. Compared to typical airborne/spaceborne/ground validation studies which at best provide O(1 km) resolution, these two platforms together provide directly collocated, high-resolution O(10m) retrievals. Dm retrieval values were over all both largest and smallest when using two separate dual-wavelength methods from aircraft measurements. A Triple-frequency analysis suggests the possibility that snow aggregates were generally composed of needles. The results shown here can be used as a benchmark for comparing retrieval methodologies.

On 7 February 2020, precipitation within the comma-head region of an extratropical cyclone was sampled remotely and in situ by two research aircraft, providing a vertical cross section of microphysical observations and fine-scale radar measurements. The sampled region was stratified vertically by distinct temperature layers and horizontally into a stratiform region on the west side, and a region of elevated convection on the east side. In the stratiform region, precipitation formed near cloud top as side-plane, polycrystalline, and platelike particles. These habits occurred through cloud depth, implying that the cloud-top region was the primary source of particles. Almost no supercooled water was present. The ice water content within the stratiform region showed an overall increase with depth between the aircraft flight levels, while the total number concentration slightly decreased, consistent with growth by vapor deposition and aggregation. In the convective region, new particle habits were observed within each temperature-defined layer along with detectable amounts of supercooled water, implying that ice particle formation occurred in several layers. Total number concentration decreased from cloud top to the −8°C level, consistent with particle aggregation. At temperatures > −8°C, ice particle concentrations in some regions increased to >100 L −1 , suggesting secondary ice production occurred at lower altitudes. WSR-88D reflectivity composites during the sampling period showed a weak, loosely organized banded feature. The band, evident on earlier flight legs, was consistent with enhanced vertical motion associated with frontogenesis, and at least partial melting of ice particles near the surface. A conceptual model of precipitation growth processes within the comma head is presented.

Satellite‐based post‐tornado assessments have been widely used for the detection of tornado tracks, which heavily relies on the identification of vegetation changes through observations at visible and near‐infrared channels. During the deadly 10–11 December 2021 tornado outbreak, a series of violent tornadoes first touched down over northeastern Arkansas, an area dominated by cropland with rare vegetation coverage in winter. Through the examination of Moderate Resolution Imaging Spectroradiometer multi‐spectral observations, this study reveals significant scars on shortwave infrared channels over this region, but none are captured by visible and near‐infrared channels. The dominant soil type is aquert (one of vertisols), whose high clay content well preserves the severe changes in soil structure during the tornado passage, when the topmost soil layer was removed and underlying soil with higher moisture content was exposed to the air. This study suggests a quick post‐tornado assessment method over less vegetated area by using shortwave infrared channels. Plain Language Summary This study showcases an application of using Moderate Resolution Imaging Spectroradiometer (MODIS) data to detect tornado damage tracks over northeastern Arkansas after the deadly 10–11 December 2021 tornado outbreak. The special soil type with rich clay content well retains the tornado scars, whose moisture content is higher than the surrounding area, causing significant signals on MODIS shortwave infrared channels. Although coarse in spatial resolution, MODIS’s rapid revisit cycle and minimal latency in data availability make it an ideal platform for the post‐tornado assessment over the winter farmland, when the vegetation coverage is low, thus the conventional vegetation‐based tornado track detection does not work well. Key Points The 2021 winter tornado outbreak left significant linear scars on Arkansas aquert farmland observed from Moderate Resolution Imaging Spectroradiometer (MODIS) shortwave infrared (SWIR) channels The scars are unrecognizable on MODIS visible and near‐infrared channels due to the coarse resolution and rare vegetation cover in winter SWIR provides a fast assessment of tornado track as topmost layer is removed by suction vortices and wetter underlying soil is exposed

The vertical motion and physical structure of elevated convection and generating cells within the comma heads of three continental winter cyclones are investigated using the Wyoming W-band cloud radar mounted on the National Science Foundation/National Center for Atmospheric Research (NSF/NCAR) C-130, supplemented by analyses from the Rapid Update Cycle model and Weather Surveillance Radar-1988 Doppler (WSR-88D) data. The cyclones followed three distinct archetypical tracks and were typical of those producing winter weather in the midwestern United States. In two of the cyclones, dry air in the middle and upper troposphere behind the Pacific cold front intruded over moist Gulf of Mexico air at lower altitudes within the comma head, separating the comma head into two zones. Elevated convection in the southern zone extended from the cold-frontal surface to the tropopause. The stronger convective updrafts ranged from 2 to 7 m s−1 and downdrafts ranged from −2 to −6 m s−1. The horizontal scale of the convective cells was approximately 5 km. The poleward zone of the comma head was characterized by deep stratiform clouds topped by cloud-top generating cells that reached the tropopause. Updrafts and downdrafts within the generating cells ranged from 1 to 2 m s−1, with the horizontal scale of the cells from about 1 to 2 km. Precipitation on the poleward side of the comma head conformed to a seeder–feeder process—the generating cells seeding the stratiform cloud—which was forced by synoptic-scale ascent. In one case, shallow clouds behind the cyclone’s cold front were also topped by cloud-top generating cells, with vertical motions ranging from 1 to 2 m s−1.

This paper presents analyses of the microphysical structure of cloud-top convective generating cells at temperatures between −10° and −55°C across the comma head of 11 continental cyclones, using data collected by the W-band Wyoming Cloud Radar and in situ instrumentation aboard the National Science Foundation (NSF)/NCAR C-130. A case study of one cyclone is presented, followed by statistical analyses of the entire dataset. Ice particle number concentrations averaged 1.9 times larger inside generating cells compared to outside, and derived ice water contents and median mass diameters averaged 2.2 and 1.1 times larger in cells, respectively. Supercooled water was directly measured at temperatures between −31.4° and −11.1°C, with the median and 95th-percentile liquid water content increasing from ~0.09 to 0.12 g m−3 and 0.14 to 0.28 g m−3 over this temperature range, respectively. Liquid water was present in 26% of observations within cells and 18% of observations between cells over the same temperature range, and it was nearly ubiquitous at temperatures above −16°C. The larger ice particle concentrations in cells are consistent with greater ice production in convective updrafts. The increased mass and diameter of the ice particles demonstrate that generating cells provide environments favorable for enhanced particle growth. The impact of water saturation and supercooled water in the cells was evident, with rapid particle growth by diffusion and sometimes riming apparent, in addition to aggregation. Turbulent mixing lessened the observed differences between cells and surrounding regions, with supercooled water observed within and between cells, similar habits within and between cells, and rimed particles evident even in ice-phase conditions.

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.

Advancing understanding of deep convection microphysics via mesoscale modeling studies of well-observed case studies requires observation-based aerosol inputs. Here, we derive hygroscopic aerosol size distribution input profiles from ground-based and airborne measurements for six convection case studies observed during the Midlatitude Continental Convective Cloud Experiment (MC3E) over Oklahoma. We demonstrate use of an input profile in simulations of the only well-observed case study that produced extensive stratiform outflow on 20 May 2011. At well-sampled elevations between −11 and −23 C over widespread stratiform rain, ice crystal number concentrations are consistently dominated by a single mode near approx. 400 microm in randomly oriented maximum dimension (Dmax). The ice mass at −23 C is primarily in a closely collocated mode, whereas a mass mode near Dmax approx. 1000 microns becomes dominant with decreasing elevation to the −11 C level, consistent with possible aggregation during sedimentation. However, simulations with and without observation-based aerosol inputs systematically overpredict mass peak Dmax by a factor of 3-5 and underpredict ice number concentration by a factor of 4-10. Previously reported simulations with both two-moment and size-resolved microphysics have shown biases of a similar nature. The observed ice properties are notably similar to those reported from recent tropical measurements. Based on several lines of evidence, we speculate that updraft microphysical pathways determining outflow properties in the 20 May case are similar to a tropical regime, likely associated with warm-temperature ice multiplication that is not well understood or well represented in models.

Compared to other regions, little is known about clouds in Antarctica. This arises in part from the challenging deployment of instrumentation in this remote and harsh environment and from the limitations of traditional satellite passive remote sensing over the polar regions. Yet clouds have a critical influence on the ice sheet's radiation budget and its surface mass balance. The extremely low temperatures, absolute humidity levels, and aerosol concentrations found in Antarctica create unique conditions for cloud formation that greatly differ from those encountered in other regions, including the Arctic. During the first decade of the 21st century, new results from field studies, the advent of cloud observations from spaceborne active sensors, and improvements in cloud parameterizations in numerical models have contributed to significant advances in our understanding of Antarctic clouds. This review covers four main topics: (1) observational methods and instruments, (2) the seasonal and interannual variability of cloud amounts, (3) the microphysical properties of clouds and aerosols, and (4) cloud representation in global and regional numerical models. Aside from a synthesis of the existing literature, novel insights are also presented. A new climatology of clouds over Antarctica and the Southern Ocean is derived from combined measurements of the CloudSat and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites. This climatology is used to assess the forecast cloud amounts in 20th century global climate model simulations. While cloud monitoring over Antarctica from space has proved essential to the recent advances, the review concludes by emphasizing the need for additional in situ measurements. Key Points CloudSat‐CALIPSO data provide new insight into Antarctic cloud climatology This data set is used to assess clouds in IPCC global climate models Direct observations of Antarctic clouds are still limited and urgently needed

This study employs four years of spatiotemporally collocated A-Train satellite observations to investigate cloud and precipitation characteristics in relation to the underlying properties of the Southern Ocean (SO). Results show that liquid-phase cloud properties strongly correlate with the sea surface temperature (SST). In summer, ubiquitous supercooled liquid water (SLW) is observed over SSTs less than about 4°C. Cloud-top temperature (CTT) and effective radius of liquid-phase clouds generally decrease for colder SSTs, whereas the opposite trend is observed for cloud-top height, cloud optical thickness, and liquid water path. The deduced cloud depth is larger over the colder oceans. Notable differences are observed between “precipitating” and “nonprecipitating” clouds and between different ocean sectors. Using a novel joint SST–CTT histogram, two distinct liquid-phase cloud types are identified, where the retrieved particle size appears to increase with decreasing CTT over warmer water (SSTs. > ∼7°C), while the opposite is true over colder water. A comparison with the Northern Hemisphere (NH) storm-track regions suggests that the ubiquitous SLW with markedly smaller droplet size is a unique feature for the cold SO (occurring where SSTs < ∼4°C), while the presence of this cloud type is much less frequent over the NH counterparts, where the SSTs are rarely colder than about 4°C at any time of the year. This study also suggests that precipitation, which has a profound influence on cloud properties, remains poorly observed over the SO with the current spaceborne sensors. Large uncertainties in precipitation properties are associated with the ubiquitous boundary layer clouds within the lowest kilometer of the atmosphere.