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The physics of star formation and the deposition of mass, momentum and energy into the interstellar medium by massive stars (‘feedback’) are the main uncertainties in modern cosmological simulations of galaxy formation and evolution 1 , 2 . These processes determine the properties of galaxies 3 , 4 but are poorly understood on the scale of individual giant molecular clouds (less than 100 parsecs) 5 , 6 , which are resolved in modern galaxy formation simulations 7 , 8 . The key question is why the timescale for depleting molecular gas through star formation in galaxies (about 2 billion years) 9 , 10 exceeds the cloud dynamical timescale by two orders of magnitude 11 . Either most of a cloud’s mass is converted into stars over many dynamical times 12 or only a small fraction turns into stars before the cloud is dispersed on a dynamical timescale 13 , 14 . Here we report high-angular-resolution observations of the nearby flocculent spiral galaxy NGC 300. We find that the molecular gas and high-mass star formation on the scale of giant molecular clouds are spatially decorrelated, in contrast to their tight correlation on galactic scales 5 . We demonstrate that this decorrelation implies rapid evolutionary cycling between clouds, star formation and feedback. We apply a statistical method 15 , 16 to quantify the evolutionary timeline and find that star formation is regulated by efficient stellar feedback, which drives cloud dispersal on short timescales (around 1.5 million years). The rapid feedback arises from radiation and stellar winds, before supernova explosions can occur. This feedback limits cloud lifetimes to about one dynamical timescale (about 10 million years), with integrated star formation efficiencies of only 2 to 3 per cent. Our findings reveal that galaxies consist of building blocks undergoing vigorous, feedback-driven life cycles that vary with the galactic environment and collectively define how galaxies form stars. Observations that molecular gas in NGC 300 is spatially uncorrelated with high-mass stars are attributed to rapid evolution, with molecular clouds quickly destroyed by stellar feedback, and low star-formation efficiency.

Despite the integral role of ice nucleators (IN) in atmospheric processes leading to precipitation, their sources and distributions have not been well established. We examined IN in snowfall from mid- and high-latitude locations and found that the most active were biological in origin. Of the IN larger than 0.2 micrometer that were active at temperatures warmer than -7 C, 69 to 100% were biological, and a substantial fraction were bacteria. Our results indicate that the biosphere is a source of highly active IN and suggest that these biological particles may affect the precipitation cycle and/or their own precipitation during atmospheric transport.

This study aims to understand cloud growth behavior and enhance cloud safety and reliability by investigating the design of cloud dispersal devices. Based on the experimental results and simulation results, this study analyzes the dispersion characteristics of cloud materials within a frustoconical device with a semi-cone angle ranging from 0° to 10° across multiple scales. The collision aggregation model for cloud particles and the multi-scale coupling mechanism for cloud growth are established. The research shows that the semi-cone angle of the device extends the effective cloud growth duration and enlarges the cloud macroscopic size. At the mesoscopic scale, vortex phenomena are observed, causing particles to converge within the cloud, resulting in collisions and aggregation. The vortices enhance the continuity of the cloud concentration. The magnitude of these vortices demonstrates a positive correlation with the magnitude of the semi-cone angle of the dispersal device. For a macroscopically stable cloud, the high-concentration area within the cloud moves outward radially with an increase in the semi-cone angle. This study provides a theoretical foundation for cloud morphology control technology, contributing to enhancing the safety and reliability of cloud systems.

Eruption source parameters (ESP) characterizing volcanic eruption plumes are crucial inputs for atmospheric tephra dispersal models, used for hazard assessment and risk mitigation. We present FPLUME-1.0, a steady-state 1-D (one-dimensional) cross-section-averaged eruption column model based on the buoyant plume theory (BPT). The model accounts for plume bending by wind, entrainment of ambient moisture, effects of water phase changes, particle fallout and re-entrainment, a new parameterization for the air entrainment coefficients and a model for wet aggregation of ash particles in the presence of liquid water or ice. In the occurrence of wet aggregation, the model predicts an effective grain size distribution depleted in fines with respect to that erupted at the vent. Given a wind profile, the model can be used to determine the column height from the eruption mass flow rate or vice versa. The ultimate goal is to improve ash cloud dispersal forecasts by better constraining the ESP (column height, eruption rate and vertical distribution of mass) and the effective particle grain size distribution resulting from eventual wet aggregation within the plume. As test cases we apply the model to the eruptive phase-B of the 4 April 1982 El Chichón volcano eruption (México) and the 6 May 2010 Eyjafjallajökull eruption phase (Iceland). The modular structure of the code facilitates the implementation in the future code versions of more quantitative ash aggregation parameterization as further observations and experiment data will be available for better constraining ash aggregation processes.

Weather conditions fundamentally affect the activity of short-lived insects. Annual variation in weather is therefore likely to be an important determinant of their between-year variation in dispersal, but conclusive empirical studies are lacking. We studied whether the annual variation of dispersal can be explained by the flight season's weather conditions in a Clouded Apollo (Parnassius mnemosyne) metapopulation. This metapopulation was monitored using the mark–release–recapture method for 12 years. Dispersal was quantified for each monitoring year using three complementary measures: emigration rate (fraction of individuals moving between habitat patches), average residence time in the natal patch, and average distance moved. There was much variation both in dispersal and average weather conditions among the years. Weather variables significantly affected the three measures of dispersal and together with adjusting variables explained 79–91% of the variation observed in dispersal. Different weather variables became selected in the models explaining variation in three dispersal measures apparently because of the notable intercorrelations. In general, dispersal rate increased with increasing temperature, solar radiation, proportion of especially warm days, and butterfly density, and decreased with increasing cloudiness, rainfall, and wind speed. These results help to understand and model annually varying dispersal dynamics of species affected by global warming.

Traditionally, tephra transport and dispersal models have evolved decoupled (offline) from numerical weather prediction models. There is a concern that inconsistencies and shortcomings associated with this coupling strategy might lead to errors in the ash cloud forecast. Despite this concern and the significant progress in improving the accuracy of tephra dispersal models in the aftermath of the 2010 Eyjafjallajökull and 2011 Cordón Caulle eruptions, to date, no operational online dispersal model is available to forecast volcanic ash. Here, we describe and evaluate NMMB-MONARCH-ASH, a new online multi-scale meteorological and transport model that attempts to pioneer the forecast of volcanic aerosols at operational level. The model forecasts volcanic ash cloud trajectories, concentration of ash at relevant flight levels, and the expected deposit thickness for both regional and global configurations. Its online coupling approach improves the current state-of-the-art tephra dispersal models, especially in situations where meteorological conditions are changing rapidly in time, two-way feedbacks are significant, or distal ash cloud dispersal simulations are required. This work presents the model application for the first phases of the 2011 Cordón Caulle and 2001 Mount Etna eruptions. The computational efficiency of NMMB-MONARCH-ASH and its application results compare favorably with other long-range tephra dispersal models, supporting its operational implementation.

A numerical modeling study has been conducted to explore the ability of the Weather Research and Forecasting (WRF) model-based large-eddy simulation (LES) with 100-m grid spacing to reproduce silver iodide (AgI) particle dispersion by comparing the model results with measurements made on 16 February 2011 over the Medicine Bow Mountains in Wyoming. Xue et al.’s recently developed AgI cloud-seeding parameterization was applied in this study to simulate AgI release from ground-based generators. Qualitative and quantitative comparisons between the LES results and observed AgI concentrations were conducted. Analyses of turbulent kinetic energy (TKE) features within the planetary boundary layer (PBL) and comparisons between the 100-m LES and simulations with 500-m grid spacing were performed as well. The results showed the following: 1) Despite the moist bias close to the ground and above 4 km AGL, the LES with 100-m grid spacing captured the essential environmental conditions except for a slightly more stable PBL relative to the observed soundings. 2) Wind shear is the dominant TKE production mechanism in wintertime PBL over complex terrain and generates a PBL of about 1000-m depth. The terrain-induced turbulent eddies are primarily responsible for the vertical dispersion of AgI particles. 3) The LES-simulated AgI plumes were shallow and narrow, in agreement with observations. The LES overestimated AgI concentrations close to the ground, which is consistent with the higher static stability in the model than is observed. 4) Non-LES simulations using PBL schemes had difficulty in capturing the shear-dominant turbulent PBL structure over complex terrain in wintertime. Therefore, LES of wintertime orographic clouds with grid spacing close to 500 m or finer are recommended.

Major disruptions of the aviation system from recent volcanic eruptions have intensified discussions about and increased the international consensus toward improving volcanic ash warnings. Central to making progress is to better discern low volcanic ash loadings and to describe the ash cloud structure more accurately in three-dimensional space and time. Here, dispersed volcanic ash observed by theCloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)space-based lidar near 20 000–40 000 ft [∼(6–13) km] over Australia and New Zealand during June 2011 is studied. This ash event took place 3 weeks after the Puyehue-Cordon Caulle eruption, which disrupted air traffic in much of the Southern Hemisphere. The volcanic ash layers are shown to exhibit color ratios (1064/532 nm) near 0.5, significantly lower than unity, as is observed with ice. Those optical properties are used to develop an ash detection algorithm. A “trajectory mapping” technique is then demonstrated wherein ash cloud observations are ingested into a Lagrangian model and used to construct ash dispersion maps and cross sections. Comparisons of the model results with independent observations suggest that the model successfully reproduces the 3D structure of volcanic ash clouds. This technique has a potential operational application in providing important additional information to worldwide volcanic ash advisory centers.

Gemini surfactant is the family of surfactant molecules possessing more than one hydrophobic tail and hydrophilic head group. These surfactants usually have better surface-active properties than corresponding conventional surfactants of equal chain length. Geminis are used as promising surfactants in industrial detergency and have shown efficiency in skin care, antibacterial property, metal-encapped porphyrazine and vesicle formation, construction of highporosity materials, etc. This review deals with synthesis, structure, critical micellar concentration, surface active properties and uses of geminis.

Cloud forming by solid explosive dispersal plays a decisive factor for twice-detonating FAE. The study of the flow field of internal cloud field can be more intuitive to understand the whole process of the formation of cloud diffusion, and it also has an important role to the delay time setting of secondary detonating fuze. Internal parameters of spreading cloud are difficult to obtain even through by the experiment method, but numerical analysis and simulations method can get the parameter. In this paper, we use experimental and simulation methods to study fuel dispersal process, aims to establish an effective and reliable mathematical models of cloud dispersal, and get the model data coinciding with the real situation.