Diurnal differences in tropical maritime anvil cloud evolution

Satellite observations of tropical maritime convection indicate an afternoon maximum in anvil cloud fraction that cannot be explained by the diurnal cycle of deep convection peaking at night. We use idealized cloud-resolving model simulations of single anvil cloud evolution pathways, initialized at different times of the day, to show that tropical anvil clouds formed during the day are more widespread and longer lasting than those formed at night. This diurnal difference is caused by shortwave radiative heating, which lofts and spreads anvil clouds via a mesoscale circulation that is largely absent at night, when a different, longwave-driven circulation dominates. The nighttime circulation entrains dry environmental air that erodes cloud top and shortens anvil lifetime. Increased ice nucleation in more turbulent nighttime conditions supported by the longwave cloud top cooling and cloud base heating dipole cannot overcompensate for the effect of diurnal shortwave radiative heating. Radiative-convective equilibrium simulations with a realistic diurnal cycle of insolation confirm the crucial role of shortwave heating in lofting and sustaining anvil clouds. The shortwave-driven mesoscale ascent leads to daytime anvils with larger ice crystal size, number concentration, and water content at cloud top than their nighttime counterparts.

Model emulation to understand the joint effects of ice-nucleating particles and secondary ice production on deep convective anvil cirrus

Ice crystal formation in the mixed-phase region of deep convective clouds can affect the properties of climatically important convectively generated anvil clouds. Small ice crystals in the mixed-phase cloud region can be formed by heterogeneous ice nucleation by ice-nucleating particles (INPs) and secondary ice production (SIP) by, for example, the Hallett–Mossop process. We quantify the effects of INP number concentration, the temperature dependence of the INP number concentration at mixed-phase temperatures, and the Hallett–Mossop splinter production efficiency on the anvil of an idealised deep convective cloud using a Latin hypercube sampling method, which allows optimal coverage of a multidimensional parameter space, and statistical emulation, which allows us to identify interdependencies between the three uncertain inputs. Our results show that anvil ice crystal number concentration (ICNC) is determined predominately by INP number concentration, with the temperature dependence of ice-nucleating aerosol activity having a secondary role. Conversely, anvil ice crystal size is determined predominately by the temperature dependence of ice-nucleating aerosol activity, with INP number concentration having a secondary role. This is because in our simulations ICNC is predominately controlled by the number concentration of cloud droplets reaching the homogeneous freezing level which is in turn determined by INP number concentrations at low temperatures. Ice crystal size, however, is more strongly affected by the amount of liquid available for riming and the time available for deposition growth which is determined by INP number concentrations at higher temperatures. This work indicates that the amount of ice particle production by the Hallett–Mossop process is determined jointly by the prescribed Hallett–Mossop splinter production efficiency and the temperature dependence of ice-nucleating aerosol activity. In particular, our sampling of the joint parameter space shows that high rates of SIP do not occur unless the INP parameterisation slope (the temperature dependence of the number concentration of particles which nucleate ice) is shallow, regardless of the prescribed Hallett–Mossop splinter production efficiency. A shallow INP parameterisation slope and consequently high ice particle production by the Hallett–Mossop process in our simulations leads to a sharp transition to a cloud with extensive glaciation at warm temperatures, higher cloud updraughts, enhanced vertical mass flux, and condensate divergence at the outflow level, all of which leads to a larger convectively generated anvil comprised of larger ice crystals. This work highlights the importance of quantifying the full spectrum of INP number concentrations across all mixed-phase altitudes and the ways in which INP and SIP interact to control anvil properties.

Cleaner burning aviation fuels can reduce contrail cloudiness

Contrail cirrus account for the major share of aviation’s climate impact. Yet, the links between jet fuel composition, contrail microphysics and climate impact remain unresolved. Here we present unique observations from two DLR-NASA aircraft campaigns that measured exhaust and contrail characteristics of an Airbus A320 burning either standard jet fuels or low aromatic sustainable aviation fuel blends. Our results show that soot particles can regulate the number of contrail cirrus ice crystals for current emission levels. We provide experimental evidence that burning low aromatic sustainable aviation fuel can result in a 50 to 70% reduction in soot and ice number concentrations and an increase in ice crystal size. Reduced contrail ice numbers cause less energy deposition in the atmosphere and less warming. Meaningful reductions in aviation’s climate impact could therefore be obtained from the widespread adoptation of low aromatic fuels, and from regulations to lower the maximum aromatic fuel content.

Exploring the Effect of Dehydration on Water Migrating Property and Protein Changes of Large Yellow Croaker (Pseudosciaena crocea) during Frozen Storage

This study aimed to explore the effect of dehydration on the water migrating property and protein changes of large yellow croaker during frozen storage. A freeze-dryer was used to accelerate experiments, which was isolated from oxygen and excluded the effects of protein oxidation. After dehydration time (3, 9, 18, and 30 h) for both fast- and slow-freezing samples, the results showed that the ice sublimation of samples containing small ice crystals was faster than that of samples containing large ice crystals in the early stages of dehydration, but in the latest stage, there was an opposite trend. The results indicated that dehydration reduced the water freedom degrees and water–protein interaction. At the same time, dehydration had a significant effect on protein secondary and tertiary structures. The significant increase in surface hydrophobicity and particle size indicated that dehydration exacerbated myofibrillar protein aggregation. The ΔH1 values (from 1.275 to 0.834 J/g for slow-freezing group and from 1.129 to 0.855 J/g for fast-freezing group) decreased gradually as the dehydration time extended, indicating the decrease in protein thermal stability. Additionally, significant protein degradation occurred when the water content of the sample decreased to a certain level. This study showed that ice crystal size had an important effect on the rate of ice sublimation, and the occurrence of dehydration during frozen storage accelerated the water loss and the decrease in protein stability.

The Microstructure of Yellow River Ice in the Freezing Period

Accurately determining true ice microstructure and material parameters is a basis for ice disaster theoretical research on the Yellow River. In this work, natural Yellow River ice was collected, and ice crystals parallel and perpendicular to the ice surface were photographed using an orthogonal polarizing mirror. Morphologies of ice microstructure were extracted, and equivalent ice grain sizes were calculated. The results show that Yellow River ice mainly consists of granular ice and columnar ice and vary greatly in different time and space ranges. The ice crystal shape is irregular, and the ice crystal size is larger span, and mainly between 1 mm and 10 mm. Ice crystal initial defects come from bubbles, sediment particles, impurities, and microcracks; among them, bubbles are the most common and have a relatively large impact. In addition, a calculation model of the Yellow River ice microstructure was constructed according to the ice crystal test results. Based on the experimental data and numerical model, the obtained Yellow River ice parameters provide help for analyzing ice disaster mechanisms along the Yellow River.