Search

Marine boundary-layer clouds play a critical role in the Earth's energy balance. Their microphysical and radiative properties are highly impacted by ambient aerosols and dynamical forcings. In this study, we evaluate the representation of these clouds and related aerosol-cloud interactions processes in the single-column version of E3SM climate model (SCM), against field measurements collected during the NASA ACTIVATE campaign over the western North Atlantic, as well as intercompare with high-resolution process-level models. Results show that E3SM-SCM, driven by the ERA5 reanalysis, reproduces the cloud properties as good as the high-resolution WRF simulations. For stronger surface forcings combined with a weaker subsidence taken from a WRF cloud-resolving simulation, both E3SM-SCM and WRF large-eddy simulation produce thicker clouds. This indicates that a proper combination of large-scale dynamics, sub-grid scale parameterizations, and model configurations is needed to obtain optimal performance of cloud simulations. In the E3SM-SCM sensitivity tests with fixed dynamics but perturbed aerosol properties, higher aerosol number concentration leads to more numerous but smaller cloud droplets, resulting in a stronger shortwave cloud forcing (i.e., stronger radiative cooling). This apparent Twomey effect is consistent with prior climate model studies. Cloud liquid water path shows a weakly positive relation with cloud droplet number concentration associated with precipitation suppression, which is different from the nonlinear relation approximated from prior observations and E3SM studies, warranting future investigation. Our findings indicate that the SCM framework is a key tool to bridge the gap between climate models, high-resolution models, and field observations to facilitate process-level understanding. [ABSTRACT FROM AUTHOR]

It was previously shown that the superdroplet algorithm for modeling the collision–coalescence process can faithfully represent mean droplet growth in turbulent clouds. An open question is how accurately the superdroplet algorithm accounts for fluctuations in the collisional aggregation process. Such fluctuations are particularly important in dilute suspensions. Even in the absence of turbulence, Poisson fluctuations of collision times in dilute suspensions may result in substantial variations in the growth process, resulting in a broad distribution of growth times to reach a certain droplet size. We quantify the accuracy of the superdroplet algorithm in describing the fluctuating growth history of a larger droplet that settles under the effect of gravity in a quiescent fluid and collides with a dilute suspension of smaller droplets that were initially randomly distributed in space (“lucky droplet model”). We assess the effect of fluctuations upon the growth history of the lucky droplet and compute the distribution of cumulative collision times. The latter is shown to be sensitive enough to detect the subtle increase of fluctuations associated with collisions between multiple lucky droplets. The superdroplet algorithm incorporates fluctuations in two distinct ways: through the random spatial distribution of superdroplets and through the Monte Carlo collision algorithm involved. Using specifically designed numerical experiments, we show that both on their own give an accurate representation of fluctuations. We conclude that the superdroplet algorithm can faithfully represent fluctuations in the coagulation of droplets driven by gravity. [ABSTRACT FROM AUTHOR]

Condensational growth of cloud droplets due to supersaturation fluctuations is investigated by solving the hydrodynamic and thermodynamic equations using direct numerical simulations with droplets being modeled as Lagrangian particles. We find that the width of droplet size distributions increases with time, which is contrary to the classical theory without supersaturation fluctuations, where condensational growth leads to progressively narrower size distributions. Nevertheless, in agreement with earlier Lagrangian stochastic models of the condensational growth, the standard deviation of the surface area of droplets increases as t1/2. Also, we numerically confirm that the time evolution of the size distribution depends strongly on the Reynolds number and only weakly on the mean energy dissipation rate. This is shown to be due to the fact that temperature fluctuations and water vapor mixing ratio fluctuations increases with increasing Reynolds number, therefore the resulting supersaturation fluctuations are enhanced with increasing Reynolds number. Our simulations may explain the broadening of the size distribution in stratiform clouds qualitatively, where the updraft velocity is almost zero. [ABSTRACT FROM AUTHOR]

Background: Anopheles sinensis (Diptera: Culicidae) is a primary vector of Plasmodium vivax and Brugia malayi in most regions of China. In addition, its phylogenetic relationship with the cryptic species of the Hyrcanus Group is complex and remains unresolved. Mitochondrial genome sequences are widely used as molecular markers for phylogenetic studies of mosquito species complexes, of which mitochondrial genome data of An. sinensis is not available. Methods: An. sinensis samples was collected from Shandong, China, and identified by molecular marker. Genomic DNA was extracted, followed by the Illumina sequencing. Two complete mitochondrial genomes were assembled and annotated using the mitochondrial genome of An. gambiae as reference. The mitochondrial genomes sequences of the 28 known Anopheles species were aligned and reconstructed phylogenetic tree by Maximum Likelihood (ML) method. Findings: The length of complete mitochondrial genomes of An. sinensis was 15,076 bp and 15,138 bp, consisting of 13 protein-coding genes, 22 transfer RNA (tRNA) genes, 2 ribosomal RNA (rRNA) genes, and an AT-rich control region. As in other insects, most mitochondrial genes are encoded on the J strand, except for ND5, ND4, ND4L, ND1, two rRNA and eight tRNA genes, which are encoded on the N strand. The bootstrap value was set as 1000 in ML analyses. The topologies restored phylogenetic affinity within subfamily Anophelinae. The ML tree showed four major clades, corresponding to the subgenera Cellia, Anopheles, Nyssorhynchus and Kerteszia of the genus Anopheles. Conclusions: The complete mitochondrial genomes of An. sinensis were obtained. The number, order and transcription direction of An. sinensis mitochondrial genes were the same as in other species of family Culicidae. [ABSTRACT FROM AUTHOR]

Nine new pregnane alkaloids (1–9), together with eight known alkaloids (10–17),were isolated from the whole herb of Pachysandra terminalis. Their structures were elucidated on the basis of spectroscopic analyses. In addition, the isolates were examined for their ability to inhibit the migration of MDA-MB-231 cells induced by the chemokine epidermal growth factor (EGF). Alkaloids 1, 5, 7, 9, 12, and 17 presented significant anti-metastasis activities compared with the positive reagent, LY294002. [ABSTRACT FROM AUTHOR]

Nine new pregnane alkaloids (1-9), together with eight known alkaloids (10-17), were isolated from the whole herb of Pachysandra terminalis. Their structures were elucidated on the basis of spectroscopic analyses. In addition, the isolates were examined for their ability to inhibit the migration of MDA-MB-231 cells induced by the chemokine epidermal growth factor (EGF). Alkaloids 1, 5, 7, 9, 12, and 17 presented significant anti-metastasis activities compared with the positive reagent, LY294002. [ABSTRACT FROM AUTHOR]

Nine new pregnane alkaloids (1–9), together with eight known alkaloids (10–17),were isolated from the whole herb of Pachysandra terminalis. Their structures were elucidated on the basis of spectroscopic analyses. In addition, the isolates were examined for their ability to inhibit the migration of MDA-MB-231 cells induced by the chemokine epidermal growth factor (EGF). Alkaloids 1, 5, 7, 9, 12, and 17 presented significant anti-metastasis activities compared with the positive reagent, LY294002. [ABSTRACT FROM AUTHOR]