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A deficit of shortwave cloud forcing over the Southern Ocean is persistent in many global climate models. Cloud regimes have been widely used in model evaluation studies to make a process-oriented diagnosis of cloud parameterization errors, but cloud regimes have some limitations in resolving both observed and simulated cloud behavior. A hybrid methodology is developed for identifying cloud regimes from observed and simulated cloud simultaneously. Through this methodology, 11 hybrid cloud regimes are identified in the ACCESS1.3 model for the high-latitude Southern Ocean. The hybrid cloud regimes resolve the features of observed cloud and characterize cloud errors in the model. The simulated properties of the hybrid cloud regimes, and their occurrence over the Southern Ocean and in the context of extratropical cyclones, are evaluated, and their contributions to the shortwave radiation errors are quantified. Three errors are identified: an overall deficit of cloud fraction, a tendency toward optically thin low and midtopped cloud, and an absence of a shallow frontal-type cloud at high latitudes and in the warm fronts of extratropical cyclones. To demonstrate the utility of the hybrid cloud regimes for the evaluation of changes to the model, the effects of selected changes to the model microphysics are investigated. [ABSTRACT FROM AUTHOR]

Large hail events are typically infrequent, with significant time gaps between occurrences at specific locations. However, when these events do happen, they can cause rapid and substantial economic losses within a matter of minutes. Therefore, it is crucial to have the ability to accurately observe and understand hail phenomena to improve the mitigation of this impact. While in-situ observations are accurate, they are limited in number for an individual storm. Weather radars, on the other hand, provide a larger observation footprint, but current radar-derived hail size estimates exhibit low accuracy due to horizontal advection of hailstones as they fall, the variability of hail size distributions (HSD), complex scattering and attenuation, and mixed hydrometeor types. In this paper, we propose a new radar-derived hail product that is developed using a large dataset of hail damage insurance claims and radar observations. We use these datasets coupled with environmental information to calculate a Hail Damage Estimate (HDE) using a deep neural network approach aiming to quantify hail impact, with a critical success index of 0.88 and a coefficient of determination against observed damage of 0.78. Furthermore, we compared HDE to a popular hail size product (MESH), allowing us to identify meteorological conditions that are associated with biases on MESH. Environments with relatively low specific humidity, high CAPE and CIN, low wind speeds aloft and southerly winds at ground are associated with a negative MESH bias, potentially due to differences in HSD or mixed hydrometeors. In contrast, environments with low CAPE, high CIN, and relatively high specific humidity aloft are associated with a positive MESH bias. [ABSTRACT FROM AUTHOR]

The evaluation and quantification of Southern Ocean cloud-radiation interactions simulated by climate models is essential in understanding the sources and magnitude of the radiative bias that persists in climate models for this region. To date, most evaluation methods focus on specific synoptic or cloud type conditions and are unable to quantitatively define the impact of cloud properties on the radiative bias whilst considering the system as a whole. In this study, we present a new method of model evaluation, using machine learning, that can at once identify complexities within a system and individual contributions. To do this, we use an XGBoost model to predict the radiative bias within a nudged version of the Australian Community Climate and Earth System Simulator -- Atmosphere-only Model, using cloud property biases as predictive features. We find that the XGBoost model can explain up to 55% of the radiative bias from these cloud properties alone. We then apply SHapley Additive exPlanations feature importance analysis to quantify the role each cloud property bias plays in predicting the radiative bias. We find that biases in liquid water path is the largest contributor to the cloud radiative bias over the Southern Ocean, though important regional and cloud-type dependencies exist. We then test the usefulness of this method in evaluating model perturbations and find that it can clearly identify complex responses, including cloud property and cloud-type compensating errors. [ABSTRACT FROM AUTHOR]

We evaluated the performance in Australia of proxies designed to identify atmospheric conditions prone to hail and severe storms. In a convection-resolving but short-duration simulation, proxies that use instability and wind shear thresholds overestimated the probability of hail occurring when compared to the estimated occurrence of surface graupel in the model, particularly in Australia's tropical north. We used reanalysis data and the Australian Bureau of Meteorology severe storm archive to examine atmospheric conditions at times and locations when hailstorms, other storms, and no storms were reported between January 1979 and March 2021. In instability–shear space, the best discriminator between hail and no-storm times was found to vary predictably with melting-level height, allowing a new proxy to better represent latitudinal trends in atmospheric conditions. We found extra conditions that can be applied to the new proxy to efficiently reduce the number of false alarms. The new proxy outperforms the tested existing proxies for detection of hail-prone conditions in Australia. Significance Statement: Hail proxies take a description of the atmosphere, such as its temperature, moisture content, and wind properties at various heights, and determine the likelihood of hail forming and hitting the ground. It is a difficult task prone to uncertainty, but in many locations there are no direct observations of hail, and in these places information from proxies is valuable. Existing proxies have a tendency to overestimate the probability of hail falling in the north of Australia. In this study we developed an updated proxy that uses information about the atmosphere's melting-level height to refine its hail predictions. The new proxy outperforms other tested proxies for hail in Australia. Accurate hail proxies are important for assessment of past and future changes to hail hazard and risk. [ABSTRACT FROM AUTHOR]

The Global Precipitation Measurement mission is a major U.S.–Japan joint mission to understand the physics of the Earth's global precipitation as a key component of its weather, climate, and hydrological systems. The core satellite carries a dual-precipitation radar and an advanced microwave imager which provide measurements to retrieve the drop size distribution (DSD) and rain rates using a Combined Radar-Radiometer Algorithm (CORRA). Our objective is to validate key assumptions and parameterizations in CORRA and enable improved estimation of precipitation products, especially in the middle-to-higher latitudes in both hemispheres. The DSD parameters and statistical relationships between DSD parameters and radar measurements are a central part of the rainfall retrieval algorithm, which is complicated by regimes where DSD measurements are abysmally sparse (over the open ocean). In view of this, we have assembled optical disdrometer datasets gathered by research vessels, ground stations, and aircrafts to simulate radar observables and validate the scattering lookup tables used in CORRA. The joint use of all DSD datasets spans a large range of drop concentrations and characteristic drop diameters. The scaling normalization of DSDs defines an intercept parameter NW, which normalizes the concentrations, and a scaling diameter Dm, which compresses or stretches the diameter coordinate axis. A major finding of this study is that a single relationship between NW and Dm, on average, unifies all datasets included, from stratocumulus to heavier rainfall regimes. A comparison with the NW–Dm relation used as a constraint in versions 6 and 7 of CORRA highlights the scope for improvement of rainfall retrievals for small drops (Dm < 1 mm) and large drops (Dm > 2 mm). The normalized specific attenuation–reflectivity relationships used in the combined algorithm are also found to match well the equivalent relationships derived using DSDs from the three datasets, suggesting that the currently assumed lookup tables are not a major source of uncertainty in the combined algorithm rainfall estimates. [ABSTRACT FROM AUTHOR]

We present highlights of recent Australian-led clouds and aerosol research over the SouthernOcean and coastal East Antarctica as part of the broader SOCRATES field campaigns. Usinga combined Raman-elastic backscatter lidar deployed aboard a ship, we quantify theproperties of aerosols within the remote Southern Ocean marine boundary layer between43∘S and 66∘S. In clean, marine air, we determine a lidar ratio of S = (18 ± 2) sr, aerosoloptical depths within the well-mixed near-surface layer of τ = (0.12 ± 0.08) north of 55∘Sand τ = (0.07 ± 0.04) further south. Dried sea salt is observed in the lower part ofdehumidified decoupled layers across all latitudes. Merging cloud data from this lidar and aW-band cloud radar allows us to quantify various cloud properties across the SouthernOcean; we will also present results of the differences in cloud properties acrossthe oceanic polar front boundary. Lastly, we present the seasonal cycle of cloudproperties at Macquarie Island (54∘S) based on data from our lidar and the cloud radar.Initial highlights from our current Davis (69∘S) deployment will also be presented. [ABSTRACT FROM AUTHOR]

Data from an upward-pointing wind profiler radar pair at Darwin in tropical Australia are used to determine the characteristics of individual convective up- and downdrafts observed at the site. Drafts are identified as vertically contiguous regions of instantaneous upward or downward motion exceeding 0.2 m s−1. Most updrafts and downdrafts found are less than 2 km in vertical extent, and updrafts exceeding 5 km in vertical length carry no more than 33% of the total upward mass flux. Updraft length correlates positively with rain rates, and on very high rain rates (greater than 20 mm h−1), average updraft lengths are ~5 km. Typical peak updraft velocities increase from ~2.5 m s−1 for the smallest to ~4 m s−1 for the largest drafts, while those for downdrafts remain ~2 m s−1 regardless of size. These results are broadly consistent with other numerical modeling studies, but contrast with the common view of deep convection as being dominated by continuous, deep drafts. [ABSTRACT FROM AUTHOR]

Areas of high ice water content (HIWC) within cloud systems may cause power loss events and engine damage in jet aircraft due to ice crystal icing (ICI). The Algorithm for Prediction of HIWC Areas (ALPHA) was developed to identify these regions and enable provision of guidance to airlines. ALPHA combines numerical weather prediction model data, satellite data, and radar data (where available), and applies fuzzy logic to identify the likely presence of HIWC. In a collaboration between the U.S. National Center for Atmospheric Research, Australian Bureau of Meteorology, U.S. Federal Aviation Administration, and Australian airlines, a trial of ALPHA was conducted for an area across Indonesia, Papua New Guinea (PNG), and northern Australia, a region with frequent deep convection and a relatively high incidence of ICI events. ALPHA was adapted to ingest data from the Australian Community Climate and Earth System Simulator model and the Japanese Himawari-8 geostationary meteorological satellite. Radar data was not used. The HIWC product was made available to stakeholder groups for evaluation. Independent validation of the HIWC product was undertaken by comparing it with retrieved profiles of ice water content (IWC) from the cloud profiling radar on the NASA polar-orbiting CloudSat satellite. Conduct of the ALPHA trial and results from validation of the HIWC product provides confidence in the potential utility for flight planning, maintaining situational awareness, and flight monitoring. [ABSTRACT FROM AUTHOR]

A new method that automatically determines the modality of an observed particle size distribution (PSD) and the representation of each mode as a gamma function was used to characterize data obtained during the High Altitude Ice Crystals and High Ice Water Content (HAIC-HIWC) project based out of Cayenne, French Guiana, in 2015. PSDs measured by a 2D stereo probe and a precipitation imaging probe for particles with maximum dimension (Dmax) > 55 μm were used to show how the gamma parameters varied with environmental conditions, including temperature (T) and convective properties such as cloud type, mesoscale convective system (MCS) age, distance away from the nearest convective peak, and underlying surface characteristics. Four kinds of modality PSDs were observed: unimodal PSDs and three types of multimodal PSDs (Bimodal1 with breakpoints 100 ± 20 μm between modes, Bimodal2 with breakpoints 1000 ± 300 μm, and Trimodal PSDs with two breakpoints). The T and ice water content (IWC) are the most important factors influencing the modality of PSDs, with the frequency of multimodal PSDs increasing with increasing T and IWC. An ellipsoid of equally plausible solutions in (No–λ–μ) phase space is defined for each mode of the observed PSDs for different environmental conditions. The percentage overlap between ellipsoids was used to quantify the differences between overlapping ellipsoids for varying conditions. The volumes of the ellipsoid decrease with increasing IWC for most cases, and (No–λ–μ) vary with environmental conditions related to distribution of IWC. HIWC regions are dominated by small irregular ice crystals and columns. The parameters (No–λ–μ) in each mode exhibit mutual dependence. [ABSTRACT FROM AUTHOR]

Research on the interaction between the Madden–Julian oscillation (MJO) and rainfall around Jakarta is limited, although the influence of the MJO on increased rainfall is acknowledged as one of the primary causes of flooding in the region. This paper investigates the local rainfall response around Jakarta to the MJO. We used C-band Doppler radar in October–April during 2009–12 to study rain-rate characteristics at much higher resolution than previous analyses. Results show that the MJO strongly modulates rain rates over the region; however, its effect varies depending on topography. During active phases, MJO induces a high rain rate over the ocean and coast, meanwhile during suppressed phases, it generates a high rain rate mainly over the mountains. In phase 2 of the MJO we find the strongest increase in mean and extreme rain rate, which is earlier in the MJO cycle than most studies reported, based on lower-resolution data. This higher rain rate is likely due to increases in convective and stratiform activities. The MJO promotes more stratiform rain once it resides over Indonesia. In phase 5, over the northwestern coast and western part of the radar domain, the MJO might bring forward the peak of the hourly rain rate that occurs in the early morning. This is likely due to a strong westerly flow arising from MJO superimposed westerly monsoonal flow, blocked by the mountains, inducing a strong wind propagating offshore resulting in convection near the coast in the morning. Our study demonstrates the benefits of using high-resolution radar for capturing local responses to the larger-scale forcing of the MJO in Indonesia. Significance Statement: Rainfall in Jakarta and its surroundings is highly variable and often heavy resulting in devastating floods. In this region, in the wet season, rainfall is influenced by large-scale climate variability including the Madden–Julian oscillation (MJO) characterized by eastward propagation of clouds near the equatorial regions on intraseasonal time scales. The MJO has been known to increase the probability of rainfall occurrence and its magnitude, but we show that the impact differs in varying topography. The frequency and intensity of rainfall increase over land areas including mountains even when MJO has not arrived in Indonesia. Meanwhile, once MJO moves through Indonesia, the frequency and magnitude of the rainfall increases over the northern coast and ocean as well as in the west of the radar domain. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

For mechanically scanning weather radars, precise pointing of the antenna is a key factor in ensuring accurate observation of the atmosphere at far range. Since operational radars typically scan the atmosphere using a series of 360° sweeps at fixed elevation angles, level scanning during azimuthal rotation is also important but often is not actively monitored after installation. One method of gauging pointing accuracy of a radar is to use solar interference that occurs as the antenna sweeps past the sun. By comparing the observed position of the sun with its known position, an estimate of pointing error in both elevation and azimuth can be obtained. A basic model for this error assumes that the radar sweep is perfectly level and that biases in elevation are therefore independent of azimuth. We extend this model to allow for the possibility that the plane of rotation may not be level. Consequently, the direction and severity of tilt may be diagnosed in addition to any constant error in elevation and azimuth pointing. The extended model was applied to a subset of radars from the Australian weather radar network, resulting in the discovery of several out-of-level radars. One radar, Captains Flat near Canberra, showed a severe tilt of 0.81° prompting inspection by a technician. This revealed that mounting studs on the pedestal of the radar tower were badly worn and loose. Correction of this issue resolved the tilt component of the diagnosed elevation error and prevented further mechanical damage to the instrument. [ABSTRACT FROM AUTHOR]

High ice water content (HIWC) regions above tropical mesoscale convective systems are investigated using data from the second collaboration of the High Altitude Ice Crystals and High Ice Water Content projects (HAIC-HIWC) based in Cayenne, French Guiana, in 2015. Observations from in situ cloud probes on the French Falcon 20 determine the microphysical and thermodynamic properties of such regions. Data from a 2D stereo probe and precipitation imaging probe show how statistical distributions of ice crystal mass median diameter (MMD), ice water content (IWC), and total number concentration (Nt) for particles with maximum dimension (Dmax) > 55 μm vary with environmental conditions, temperature (T), and convective properties such as vertical velocity (w), MCS age, distance away from convective peak (L), and surface characteristics. IWC is significantly correlated with w, whereas MMD decreases and Nt increases with decreasing T consistent with aggregation, sedimentation, and vapor deposition processes at lower altitudes. MMD typically increases with IWC when IWC < 0.5 g m−3, but decreases with IWC when IWC > 0.5 g m−3 for −15° ≤ T ≤ −5°C. Trends also depend on environmental conditions, such as the presence of convective updrafts that are the ice crystal source, MMD being larger in older MCSs consistent with aggregation and less injection of small crystals into anvils, and IWCs decrease with increasing L at lower T. The relationship between IWC and MMD depends on environmental conditions, with correlations decreasing with decreasing T. The strength of correlation between IWC and Nt increases as T decreases. [ABSTRACT FROM AUTHOR]

Understanding the key dynamical and microphysical mechanisms driving precipitation in the Snowy Mountains region of southeast Australia, including the role of orography, can help improve precipitation forecasts, which is of great value for efficient water management. An intensive observation campaign was carried out during the 2018 austral winter, providing a comprehensive range of ground-based observations across the Snowy Mountains. We used data from three vertically pointing rain radars, cloud radar, a PARSIVEL disdrometer, and a network of 76 pluviometers. The observations reveal that all of the precipitation events were associated with cold front passages. About half accumulated during the frontal passage associated with deep, fully glaciated cloud tops, while the rest occurred in the postfrontal environment and were associated with clouds with supercooled liquid water (SLW) tops. About three-quarters of the accumulated precipitation was observed under blocked conditions, likely associated with blocked stratiform orographic enhancement. Specifically, more than a third of the precipitation resulted from moist cloudless air being lifted over stagnant air, upwind from the barrier, creating SLW-top clouds. These SLW clouds then produced stratiform precipitation mostly over the upwind slopes and mountain tops, with hydrometeors reaching the mountain tops mostly as rimed snow. Two precipitation events were studied in detail, which showed that during unblocked conditions, orographic convection invigoration and unblocked stratiform enhancement were the two main mechanisms driving the precipitation, with the latter being more prevalent after the frontal passage. During these events, ice particle growth was likely dominated by vapor deposition and aggregation during the frontal periods, while riming dominated during the postfrontal periods. [ABSTRACT FROM AUTHOR]

Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation, and radiative processes, and their interactions. Projects between 2016 and 2018 used in situ probes, radar, lidar, and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN), and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF-NCAR G-V aircraft flying north-south gradients south of Tasmania, at Macquarie Island, and on the R/V Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons. Results show largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multilayered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of dynamics and turbulence that likely drive heterogeneity of cloud phase. Satellite retrievals confirmed low clouds were responsible for radiation biases. The combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets. [ABSTRACT FROM AUTHOR]

Microorganisms are ubiquitous and highly diverse in the atmosphere. Despite the potential impacts of airborne bacteria found in the lower atmosphere over the Southern Ocean (SO) on the ecology of Antarctica and on marine cloud phase, no previous region-wide assessment of bioaerosols over the SO has been reported. We conducted bacterial profiling of boundary layer shipboard aerosol samples obtained during an Austral summer research voyage, spanning 42.8 to 66.5°S. Contrary to findings over global subtropical regions and the Northern Hemisphere, where transport of microorganisms from continents often controls airborne communities, the great majority of the bacteria detected in our samples were marine, based on taxonomy, back trajectories, and source tracking analysis. Further, the beta diversity of airborne bacterial communities varied with latitude and temperature, but not with other meteorological variables. Limited meridional airborne transport restricts southward community dispersal, isolating Antarctica and inhibiting microorganism and nutrient deposition from lower latitudes to these same regions. A consequence and implication for this region's marine boundary layer and the clouds that overtop it is that it is truly pristine, free from continental and anthropogenic influences, with the ocean as the dominant source controlling low-level concentrations of cloud condensation nuclei and ice nucleating particles., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)