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 cloudsnucleating 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 RV 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 a 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, multi-layered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of 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.
In situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in situ data collected during different field projects processed by different groups must be used. However, because of the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single-particle light-scattering spectrometers and cloud-imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats, and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in situ data include the following: establishment of a common reference library of individual processing algorithms, better documentation of assumptions used in these algorithms, development and maintenance of sustainable community software for processing in situ observations, and more studies that compare different algorithms with the same benchmark datasets.
The information regarding the effect of hepatitis B virus (HBV) infection on gut microbiota and the relationship between gut microbiota dysbiosis and hepatitis B virus-induced chronic liver disease (HBVCLD) is limited. In this study, we aimed at characterizing the gut microbiota composition in the three different stages of hepatitis B virus-induced chronic liver disease patients and healthy individuals. Faecal samples and clinical data were collected from HBVCLD patients and healthy individuals.The 16S rDNA gene amplification products were sequenced. Bioinformatic analysis including alpha diversity and PICRUSt was performed. A total of 19 phyla, 43 classes, 72 orders, 126 families and 225 genera were detected. The beta-diversity showed a separate clustering of healthy controls and HBVCLD patients covering chronic hepatitis (CHB), liver cirrhosis (LC) and hepatocellular carcinoma (HCC); and gut microbiota of healthy controls was more consistent, whereas those of CHB, LC and HCC varied substantially. The abundance of Firmicutes was lower, and Bacteroidetes was higher in patients with CHB, LC and HCC than in healthy controls. Predicted metagenomics of microbial communities showed an increase in glycan biosynthesis and metabolism-related genes and lipid metabolism-related genes in HBVCLD than in healthy individuals. Our study suggested that HBVCLD is associated with gut dysbiosis, with characteristics including, a gain in potential bacteria and a loss in potential beneficial bacteria or genes. Further study of CHB, LC and HCC based on microbiota may provide a novel insight into the pathogenesis of HBVCLD as well as a novel treatment strategy. K E Y W O R D S16S rDNA, dysbiosis, Gut Microbiota, hepatitis B virus, progression
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.
Southern Ocean (S. Ocean) clouds are important for climate prediction. Yet previous global climate models failed to accurately represent cloud phase distributions in this observation-sparse region. In this study, data from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES) experiment is compared to constrained simulations from a global climate model (the Community Atmosphere Model, CAM). Nudged versions of CAM are found to reproduce many of the features of detailed in situ observations, such as cloud location, cloud phase, and boundary layer structure. The simulation in CAM6 has improved its representation of S. Ocean clouds with adjustments to the ice nucleation and cloud microphysics schemes that permit more supercooled liquid. Comparisons between modeled and observed hydrometeor size distributions suggest that the modeled hydrometeor size distributions represent the dual peaked shape and form of observed distributions, which is remarkable given the scale difference between model and observations. Comparison to satellite observations of cloud physics is difficult due to model assumptions that do not match retrieval assumptions. Some biases in the model's representation of S. Ocean clouds and aerosols remain, but the detailed cloud physical parameterization provides a basis for process level improvement and direct comparisons to observations. This is crucial because cloud feedbacks and climate sensitivity are sensitive to the representation of S. Ocean clouds. Plain Language Summary Clouds over the Southern Ocean are important for climate prediction and may influence the evolution of global temperatures. Thus, these clouds are important to represent properly in models; however, recent studies have revealed models inadequately represent Southern Ocean cloud occurrence and phase, which drive large biases in radiation and subsequent climate sensitivity. Observations from research aircraft over the Southern Ocean south of Australia are compared to simulations with a global climate model which is "nudged" to reproduce the day-today cloud systems which are sampled. Despite being a coarse horizontal and vertical resolution, the model is able to reproduce many details of cloud phase and water content during the flights. However, the model has some biases, and these observations have been used to improve the model to better represent cloud phase. These results point to specific observational constraints for improving model simulations.
Three flights from the Ice in Clouds Experiment–Tropical (ICE-T) field campaign examined the onset of ice near the ascending cloud tops of tropical maritime cumuli as they cooled from 0° to −14°C. Careful quantitative analysis of ice number concentrations included manual scrutiny of particle images and corrections for possible particle-shattering artifacts. The novel use of the Wyoming Cloud Radar documented the stage of cloud development and tops relative to the aircraft sampling, complemented the manual estimates of graupel concentrations, and provided new clear evidence of graupel movement through the rime-splintering zone. Measurements of ice-nucleating particles (INPs) provided an estimate of primary initiated ice. The data portray a dynamically complex picture of hydrometeor transport contributing to, and likely resulting from, the rime-splintering process. Hundreds per liter of supercooled raindrops ascended within the updrafts as the cloud tops reached 0°C and contributed in part to the 0.1 L−1 graupel detected soon after the cloud tops cooled to −5°C. Rime splintering could thus be initiated upon first ascent of the cloud top through that zone and arguably contributed to the 1 L−1 or more graupel observed above it. Graupel ascending/descending into, or balanced within, the rime-splintering zone were found. In wider, less isolated clouds with dying updrafts and tops near −14°C, ice particle concentrations sometimes reached 100 L−1. Future 3D numerical modeling will be required to evaluate if rime splintering alone can explain the difference of three to four orders of magnitude in the observed INPs and the graupel observed at −5°C and colder.
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