Arctic Mixed-phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity to Microphysics Parameterizations

Single-layer mixed-phase stratiform (MPS) Arctic clouds, which formed under conditions of large surface heat flux combined with general subsidence during a subperiod of the Atmospheric Radiation Measurement (ARM) Program Mixed-Phase Arctic Cloud Experiment (M-PACE), are simulated with a cloud resolving model (CRM). The CRM is implemented with either an advanced two-moment (M05) or a commonly used one-moment (L83) bulk microphysics scheme and a state-of-the-art radiative transfer scheme. The CONTROL simulation, that uses the M05 scheme and observed aerosol size distribution and ice nulei (IN) number concentration, reproduces the magnitudes and vertical structures of cloud liquid water content (LWC), total ice water content (IWC), number concentration and effective radius of cloud droplets as suggested by the M-PACE observations. It underestimates ice crystal number concentrations by an order of magnitude and overestimates effective radius of ice crystals by a factor of 2-3. The OneM experiment, that uses the L83 scheme, produces values of liquid water path (LWP) and ice plus snow water path (ISWP) that were about 30% and 4 times, respectively, of those produced by the CONTROL. Its vertical profile of IWC exhibits a bimodal distribution in contrast to the constant distribution of IWC produced in the CONTROL and observations

Measurement report: Understanding the seasonal cycle of Southern Ocean aerosols

Published: 29 March 2023The remoteness and extreme conditions of the Southern Ocean and Antarctic region have meant that observations in this region are rare, and typically restricted to summertime during research or resupply voyages. Observations of aerosols outside of the summer season are typically limited to long-term stations, such as Kennaook / Cape Grim (KCG; 40.7∘ S, 144.7∘ E), which is situated in the northern latitudes of the Southern Ocean, and Antarctic research stations, such as the Japanese operated Syowa (SYO; 69.0∘ S, 39.6∘ E). Measurements in the midlatitudes of the Southern Ocean are important, particularly in light of recent observations that highlighted the latitudinal gradient that exists across the region in summertime. Here we present 2 years (March 2016–March 2018) of observations from Macquarie Island (MQI; 54.5∘ S, 159.0∘ E) of aerosol (condensation nuclei larger than 10 nm, CN10) and cloud condensation nuclei (CCN at various supersaturations) concentrations. This important multi-year data set is characterised, and its features are compared with the long-term data sets from KCG and SYO together with those from recent, regionally relevant voyages. CN10 concentrations were the highest at KCG by a factor of ∼50 % across all non-winter seasons compared to the other two stations, which were similar (summer medians of 530, 426 and 468 cm−3 at KCG, MQI and SYO, respectively). In wintertime, seasonal minima at KCG and MQI were similar (142 and 152 cm−3, respectively), with SYO being distinctly lower (87 cm−3), likely the result of the reduction in sea spray aerosol generation due to the sea ice ocean cover around the site. CN10 seasonal maxima were observed at the stations at different times of year, with KCG and MQI exhibiting January maxima and SYO having a distinct February high. Comparison of CCN0.5 data between KCG and MQI showed similar overall trends with summertime maxima and wintertime minima; however, KCG exhibited slightly (∼10 %) higher concentrations in summer (medians of 158 and 145 cm−3, respectively), whereas KCG showed ∼40 % lower concentrations than MQI in winter (medians of 57 and 92 cm−3, respectively). Spatial and temporal trends in the data were analysed further by contrasting data to coincident observations that occurred aboard several voyages of the RSV Aurora Australis and the RV Investigator. Results from this study are important for validating and improving our models and highlight the heterogeneity of this pristine region and the need for further long-term observations that capture the seasonal cycles.Ruhi S. Humphries, Melita D. Keywood, Jason P. Ward, James Harnwell, Simon P. Alexander, Andrew R. Klekociuk, Keiichiro Hara, Ian M. McRobert, Alain Protat, Joel Alroe, Luke T. Cravigan, Branka Miljevic, Zoran D. Ristovski, Robyn Schofield, Stephen R. Wilson, Connor J. Flynn, Gourihar R. Kulkarni, Gerald G. Mace, Greg M. McFarquhar, Scott D. Chambers, Alastair G. Williams, and Alan D. Griffith

Millimeter wave scattering from ice crystals and their aggregates: Comparing cloud model simulations with X- and Ka-band radar measurements

Arctic clouds are often mixed-phase, such that the radiative properties of the clouds are a strong function of the relative amounts of cloud liquid and ice. Modeling studies have shown that the poorly understood ice phase processes are the regulators of the liquid water fraction. However, evaluating the fidelity of the model ice parameterizations has proven to be a difficult task. This study evaluates results of different ice microphysics representations in a cloud resolving model (CRM) using cloud radar measurements. An algorithm is presented to generate realistic ice crystals and their aggregates from which radar backscattering cross sections may be calculated using a generalized solution for a cluster of spheres. The aggregate is composed of a collection of ice crystals, each of which is constructed from a cluster of tiny ice spheres. Each aggregate satisfies the constraints set by the component crystal type and the mass-dimensional relationship used in the cloud resolving model, but is free to adjust its aspect ratio. This model for calculating radar backscattering is compared to two spherical and two spheroidal (bulk model) representations for ice hydrometeors. It was found that a refined model for representing the ice hydrometeors, both pristine crystals and their aggregates, is required in order to obtain good comparisons between the CRM calculations and the radar measurements. The addition of the radar-CRM comparisons to CRM-in situ measurements comparisons allowed conclusions about the appropriateness of different CRM ice microphysics parameterizations. Copyright 2011 by the American Geophysical Union.Peer reviewed: YesNRC publication: Ye

Toward ice formation closure in Arctic mixed-phase boundary layer clouds during ISDAC

A modeling study of a low-lying mixed-phase cloud layer observed on 8 April 2008 during the Indirect and Semi-Direct Aerosol Campaign is presented. Large-eddy simulations with size-resolved microphysics were used to test the hypothesis that heterogeneous ice nucleus (IN) concentrations measured above cloud top can account for observed ice concentrations, while also matching ice size distributions, radar reflectivities, and mean Doppler velocities. The conditions for the case are favorable for the hypothesis: springtime IN concentrations are high in the Arctic, the predominant ice habit falls slowly, and overlying IN concentrations were greater than ice particle number concentrations. Based on particle imagery, we considered two dendrite types, broad armed (high density) and stellar (low density), in addition to high and low density aggregates. Two simulations with low-density aggregates reproduced observations best overall: one in which IN concentrations aloft were increased fourfold (as could have been present above water saturation) and another in which initial IN concentrations were vertically uniform. A key aspect of the latter was an IN reservoir under the well-mixed cloud layer: as the simulations progressed, the reservoir IN slowly mixed upward, helping to maintain ice concentrations close to those observed. Given the uncertainties of the measurements and parameterizations of the microphysical processes embedded in the model, we found agreement between simulated and measured ice number concentrations in most of the simulations, in contrast with previous modeling studies of Arctic mixed-phase clouds, which typically show a large discrepancy when IN are treated prognostically and constrained by measurements. Copyright 2011 by the American Geophysical Union.Peer reviewed: YesNRC publication: Ye

Towards more realistic hypotheses for the information content analysis of cloudy/precipitating situations – Application to a hyperspectral instrument in the microwave

Information Content (IC) analysis can be used before an instrument is built to estimate its retrieval uncertainties and analyse their sensitivity to several factors. It is a very useful method to define/optimize satellite instruments. IC has shown its potential to compare instrument concepts in the infrared or the microwave. IC is based on some hypotheses such as the the Gaussian character of the radiative transfer (RT) and instrument errors, the first-guess errors (Gaussian character, std and correlation structure), or the linearization of the RT around a first guess. These hypotheses are easier to define for simple atmospheric situations. However, even in the clear-sky case, their complexity has never ceased to increase towards more realism, to optimize the assimilation of satellite measurements in numerical weather prediction (NWP) systems. In the cloudy/precipitating case, these hypotheses are even more difficult to define in a realistic way as many factors are still very difficult to quantify. In this study, several tools are introduced to specify more realistic IC hypotheses than the current practice. We focus on microwave observations as they are more pertinent for clouds and precipitation. Although not perfect, the proposed solutions are a new step towards more realistic IC assumptions of cloudy/precipitating scenes. A state-dependence of the RT errors is introduced, the first-guess errors have a more complex vertical structure, the IC is performed simultaneously on all the hydrometeors to take into account the contamination effect of the RT input uncertainties, and the IC is performed on a diversified set of cloudy/precipitating scenes with well-defined hydrometeor assumptions. The method presented in this study is illustrated using the HYperspectral Microwave Sensor (HYMS) instrument concept with channels between 6.9 and 874 GHz (millimetre and sub-millimetre regions). HYMS is considered as a potential next generation microwave sounder

Observations of clouds, aerosols, precipitation, and surface radiation over the Southern Ocean: an overview of CAPRICORN, MARCUS, MICRE, and SOCRATES

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.Greg M. McFarquhar … Andrew R. Klekociuk … et al