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In this study, we investigated the temporal variation of organic and inorganic aerosol with its optical properties in Mumbai (India), an urban coastal region. Mean PM2.5 concentrations during the sampling period were 175 μg/m3 (winter) and 90 μg/m3 (summer). During winter, the average concentrations of organic (OC), elemental (EC), and water-soluble organic carbon (WSOC) were three times higher than in summer. Secondary organic carbon (SOC) contribution in OC was higher in summer (78%) than in winter (53%), and strong solar radiation in summer likely caused this outcome. Aerosols were slightly acidic in both seasons, with an average pH of 5.7 (winter) and 6.0 (summer). A correlation was observed between SOC and the acidity of particles in summer (R2 = 0.6), indicating some amount of acid-catalysed SOC formation. In both seasons, the sulphate oxidation ratio (SOR) was higher than the nitrate oxidation ratio (NOR), which may reflect a preference for SO2 oxidation over NO2 or the difference in partitioning ammonium nitrate into ammonium sulphate under high RH. The dominant mechanism of SOC formation (gas vs aqueous phase oxidation) also showed seasonal variation. In winter, a relatively steep reduced major axis (RMA) slope of O3/CO suggests gas phase oxidation was the dominant mechanism of SOC production. Winter has more BrC fraction than summer, indicating higher absorbing aerosols, though the efficiency of absorbing the light was higher in summer. To assess the radiative forcing of PM2.5 on a local scale, an effective carbon ratio (ECR) was computed. The findings pointed to a local radiative heating impact caused by PM2.5. The spectral slope ratio and MAE at 250 to 300 nm ratio (E2/E3) revealed a higher abundance of high molecular weight species in WSOC during summer than in winter. [ABSTRACT FROM AUTHOR]

During the natural icing test flight of an aircraft, capturing icing weather conditions, selecting optimal meteorological conditions, and processing compliance data have been long-standing challenges. This article analyzes the background and limitations of the formation of the icing meteorological standard in Appendix C of CCAR25, and proposes a flight method for ice detection using an icing experimental research aircraft. This method includes the selection and modification of icing experimental research aircraft, detection target area determination, flight operation strategy, flight safety management, data processing, etc. Based on statistical analysis of detection data, the selection criteria for meteorological conditions for natural icing flight test of civil aircraft are determined. A series of data processing methods and compliance criteria for icing meteorology are standardized, including cloud gaps, liquid water content, total water collection rate, icing rate, icing thickness, and degree of ice shedding. Domestic icing meteorological prediction algorithms are calibrated and verified, and safety control strategies and risk degradation measures for natural icing flight test are explored. A large number of flight tests have shown that this method has strong versatility and significant effects. It has been successfully applied to the certification of C919 aircraft, and strongly supports the independent development of domestic icing airworthiness standards.

A ground-based microwave radiometer (MWR) provides continuous atmospheric profiles under various weather conditions. The change in total precipitable water vapor (PWV) and liquid water path (LWP) before rainfall events is particularly important for the improvement in the rainfall forecast. However, the analysis of the PWV and LWP before rainfall event on the plateau is especially worth exploring. In this study, the MWR installed at Xining, a city located over the northeastern Tibetan Plateau, was employed during September 2021 to August 2022. The results reveal that the MWR-retrieved temperature and vapor density demonstrate reliable accuracy, when compared with radiosonde observations; PWV and LWP values during the summer account for over 70% of the annual totals in the Xining area; both PWV and LWP at the initiating time of rainfall events are higher during summer, especially after sunset (during 20-00 local solar time); and notably, PWV and LWP anomalies are enhanced abruptly 8 and 28 min prior to the initiating time, respectively. Furthermore, the mean of LWP anomaly rises after the turning time (the moment rises abruptly) to the initiating time; as the intensity of rainfall events increases, the occurrence of the turning time is delayed, especially for PWV anomalies; while the occurrence of the turning time is similar for both convective cloud and stratiform cloud rainfall events, the PWV and LWP anomalies jump more the initiating time; as the intensity of rainfall events increases, the occurrence of the turning time is delayed, especially for PWV anomalies; while the occurrence of the turning time is similar for both convective cloud and stratiform cloud rainfall events, the PWV and LWP anomalies jump more dramatically after the turning time in convective cloud events. This study aims are to analyze the temporal characteristics of PWV and LWP, and assess their potential in predicting rainfall event. [ABSTRACT FROM AUTHOR]

The matric suction of saline soil is the driving force that causes water migration, and it is of great significance for exploring the mechanism of water and salt migration in saline frozen soil. In order to investigate the effect of phase transition of soil pore solution induced by temperature on the matric suction of saline soil, the matric suction of different types of saline soils was measured by pF meter under different temperature conditions. The natural soil was first washed to obtain the desalinized soil, then different salt mass ratios of sodium chloride and sodium sulfate (0:6, 4:2, 2:4, 6:0) were added into the desalinized soil to model the composite saline soil, the salt content and water content were set to 6% and 20%, respectively. Subsequently, the remolded saline soil was compacted into the test chamber (0.37 m×0.25 m×0.22 m), and its dry density was controlled at 1.6 g/cm³. Hydra Probe II and pF meter were embedded at 11cm of the sample to measure the liquid water content and matric suction versus temperature. Freezing-thawing box (TMS 9 018-R30), produced by Zhejiang Tomos company, was employed to control the experimental temperature by step cooling method. The temperature range was from 30 to -24 °C, and the temperature interval was 3 °C. The data was collected by CR300 at an interval of 6 h. When the experiment was complete, the temperature effect of saline soil matric suction was analyzed and the effect of water/salt phase transition was explored. The experimental results reveal that the matric suction of saline soil increases almost linearly with the decrease of temperature when no phase transition occurs, which is caused by surface tension and wetting coefficient. Different types of saline soils have different effects on the phase transition process of pore solution, resulting in significant differences in the matric suction of different types of saline soils. The mirabilite crystallizes at 19 °C and the second phase transition occurs at -9 °C for the composite saline soil with 2% NaCl+4% Na2SO4, and the phase transition of composite saline soil with 4% NaCl+2% Na2SO4 occurs at 11 and -16 °C.Sodium chloride can inhibit the occurrence of ice formation, then the matric suction caused by ice formation is reduced, and the segregated frost heave caused by water migration is restrained indirectly. Besides, sodium sulfate is prone to crystallization at positive temperatures, and ice is also produced in the secondary phase transition process, both salt crystallization and ice formation increase the matric suction in sodium sulfate soil, and water and salt redistribute in this process, salt expansion and frost heave are induced. For composite saline soil, sodium sulfate mainly affects the salt crystallization of the soil at a positive temperature, while sodium chloride mainly affects the ice formation of the soil at a negative temperature. The different proportions of the two salts cause significant differences in the salt crystallization temperature and the secondary phase transition temperature, resulting in more complex phase transition laws in composite saline soil, and it is more difficult to predict the matric suction of composite saline soil. In addition, this paper further explores the contribution of ice and salt crystallization to the variation of matric suction, providing effective references for a deeper understanding of the relationship between phase transition processes and matric suction in saline soils. [ABSTRACT FROM AUTHOR]

The frenzied demand for the transit of humans and commodities in this modern world requires aircraft to operate in adverse weather conditions of rainfall, ice accretion, and gust. The paper also introduces innate characteristics of rainfall, ultimatum due to precipitation. The work gives a brief overview of adverse effect of rainfall on aerodynamic characteristics for various phases of flight in terms of evaluation of the aircraft performance flight characteristics such as CL, CD, L/D. It also portrays the significant phenomenon of boundary layer transition at lower AOA near leading edge and flow separation taking place nearby trailing edge at higher AOA. The study also showcases presence of uneven water film on wing surface due to droplet impingement, instabilities, interaction of water droplets with air flowing over the airfoil and splitting into rivulets which results in degradation of aerodynamic characteristics. The findings of this review paper could be of immense use to aviation industries in developing an aircraft that has better aerodynamic characteristics for all weather conditions. [ABSTRACT FROM AUTHOR]

This study uses an icing model, combining heat transfer with fluid flow and considering the roughness effect, to investigate the influence of liquid water content (LWC) and droplet median volume diameter (MVD) on the ice distribution and anti-icing heat estimation of a wind turbine blade airfoil through the numerical approach. The findings indicate that the simulated ice distribution can have excellent agreement with experimental data. Owing to variations of droplet collection efficiency and heat flux, the increase in LWC and MVD will amplify the fluctuations in ice accretion distribution, which will be prone to ice horns. Owing to high LWC increasing water film flow range, the jumping point of anti-icing heat flux is closer to the trailing edge. Owing to large MVD increasing droplet collection efficiency, the quantity of ice accumulation through solidification ascends to demand higher anti-icing heat flux. The peak anti-icing heat flux is more evidently influenced by LWC than that by MVD, due to the variations in heat flux, induced by water film evaporation and solidification. The findings offer valuable insights into the flow and heat transfer physics for wind turbine anti/de-icing design.

In cold regions, the coexistence and interconversion of liquid water and ice in frozen soils have important implications for energy partitioning and surface runoff at the Earth's surface. Passive microwave remote sensing is crucial for the global monitoring of soil moisture (SM). However, current research on SM focuses mainly on unfrozen soil conditions. Limited studies have been conducted on variations in soil liquid water content throughout the freezing season. This article investigated the potential use of brightness temperature observations from the Soil Moisture Active Passive (SMAP) satellite for retrieving all-season liquid SM. The single-channel algorithm and the Zhang-Zhao dielectric model, which was specifically developed for freezing and thawing soils, achieved successful retrieval of liquid SM in both frozen and thawed soils, even when snow cover was present. The results indicate improved spatial coverage (during winter) and consistent spatial patterns in SM compared with the SMAP products. Validation at 17 SM networks suggests that the retrieved all-season liquid SM effectively captures the dynamic characteristics of each region with an average bias of 0.011 m3/m3, an average unbiased root mean square error of 0.056 m3/m3, and an average correlation coefficient of 0.76. The additional retrieval of unfrozen water content during the freezing season would enhance the monitoring and understanding of the hydrological cycle and energy balance in cold regions.

An effective approach based on the discontinuous Galerkin method (DGM) of a high-order accuracy for calculating the initial stage of an aircraft wing's icing is presented. The problem is solved in the Euler approximation for small water droplets that do not affect the main flow. Systems of Navier–Stokes (NS) equations and Euler model equations for the liquid water content and some relations of the ice growth thermodynamics equations are written. The initial and boundary conditions are formulated. A supercomputer DGM implementation is proposed to solve these systems of equations. The efficiency of the parallel version for the code is investigated. Comments are given on the peculiarities of organizing the calculation procedure. The accuracy of the calculation using the DGM schemes of different accuracy orders is investigated. Test cases on the finely dispersed flow of supercooled droplets around a cylinder and a NACA0012 profile are presented. The numerical and experimental data are compared. A conclusion is drawn about the possibility of applying the developed methodology in practice. [ABSTRACT FROM AUTHOR]

A well-designed flow channel is crucial for effective water management in proton exchange membrane fuel cell. This study presents novel simulation investigation of the dynamic behavior of liquid water in three-dimensional multi-channels with various shape designs, including straight channel (SC), blocked channel (BC), wave channel (WC), and tapered channel (TC). The first, second, and third single channels are arranged in order from gas inlet in multi-channel. The results indicate that drainage rate of first channel in multi-channel is slower than that of second and third channel. Among the four designs, BC and TC reduced water ejection time by 7 ms and 6.5 ms respectively compared to SC, and reduced the time by 39 ms and 38.5 ms respectively compared to WC. In base case, drag reduction rate of TC compared to BC and WC increased by 4.12% and 20.98% respectively. However, WC has the smallest water coverage and average drag reduction ratio, while SC has a lower average gas flow resistance coefficient. This research offers innovative perspectives and theoretical foundations for current flow field design. • Dynamic behavior of liquid water in multi-channels with varying shapes is studied. • The average inlet velocity gradually increases from the first to the third channel. • The blocked channel and tapered channel exhibit better drainage performance. • Wave multi-channel demonstrates lowest water coverage and drag reduction ratio. • Straight multi-channel presents the lowest average flow resistance coefficient. [ABSTRACT FROM AUTHOR]

A ground-based microwave radiometer (MWR) provides continuous atmospheric profiles under various weather conditions. The change in total precipitable water vapor (PWV) and liquid water path (LWP) before rainfall events is particularly important for the improvement in the rainfall forecast. However, the analysis of the PWV and LWP before rainfall event on the plateau is especially worth exploring. In this study, the MWR installed at Xining, a city located over the northeastern Tibetan Plateau, was employed during September 2021 to August 2022. The results reveal that the MWR-retrieved temperature and vapor density demonstrate reliable accuracy, when compared with radiosonde observations; PWV and LWP values during the summer account for over 70% of the annual totals in the Xining area; both PWV and LWP at the initiating time of rainfall events are higher during summer, especially after sunset (during 20-00 local solar time); and notably, PWV and LWP anomalies are enhanced abruptly 8 and 28 min prior to the initiating time, respectively. Furthermore, the mean of LWP anomaly rises after the turning time (the moment rises abruptly) to the initiating time; as the intensity of rainfall events increases, the occurrence of the turning time is delayed, especially for PWV anomalies; while the occurrence of the turning time is similar for both convective cloud and stratiform cloud rainfall events, the PWV and LWP anomalies jump more the initiating time; as the intensity of rainfall events increases, the occurrence of the turning time is delayed, especially for PWV anomalies; while the occurrence of the turning time is similar for both convective cloud and stratiform cloud rainfall events, the PWV and LWP anomalies jump more dramatically after the turning time in convective cloud events. This study aims are to analyze the temporal characteristics of PWV and LWP, and assess their potential in predicting rainfall event.

The liquid water content directly affects the performance of the proton exchange membrane fuel cell (PEMFC). However, the liquid water content is influenced by the temperature, inlet gas pressure and humidity, so this investigation seeks to explore the relationship among the operating parameters, liquid water content and the current density distribution that used to characterize the cell performance. Firstly, a three-dimensional monomer model of PEMFC was established for numerical simulation based the COMSOL software to study the effect of temperature and inlet gas parameters on cell performance. Then the PEMFC reactor performance test used control variable method was carried out on the 15 kW test bench to verify the research. From the simulation and test results, we can acquire that the liquid water content and current density distribution of fuel cell are the maxima under the condition of 0.2 MPa pressure and 100% humidification. Finally, the experiment confirmed that when the temperature is 353 K, the liquid water content is the highest, and when the temperature remains constant, the higher inlet gas pressure and humidity was given, the higher liquid water content will be generated in the proton membrane which can increase the current density on the membrane to a certain extent, hence to improve the cell performance.

Nitrate has become the primary inorganic compound in urban aerosol particles, but its effects on particle phase state, which is crucial in multiphase chemistry, remains largely unknown. Herein, particle rebound measurements were conducted to explore the relationship between the liquid–phase–transition threshold relative humidity (RHthreshold) and the inorganic compounds mass fraction in dry particles (Finorg). Results revealed negative correlations between RHthreshold and Finorg, with more nitrate leading to lower RHthreshold. Even with RH < 20%, particles with ∼50% nitrate mass fraction remained in non‐solid state. Taking Beijing as an example, decreases were observed in RHthreshold from 64% in 2015 to below 53% nowadays during the moderate‐pollution periods (PM2.5 = 35–75 μg/m3) due to an enhanced nitrate fraction. This allowed urban aerosol particles to exist in liquid state at lower RH, and consequently, kinetic limitation by bulk diffusion in nitrate‐dominated particles might be negligible, making them key seeds for secondary aerosol formation through multiphase reactions. Plain Language Summary: The phase state of aerosol particles plays a crucial role in the mass‐transfer processes between gas and particles, which is essential for determining particle mass concentration. Investigating the characteristics of the aerosol phase state is crucial for comprehending the mechanisms behind secondary particle formation and improving air quality. Currently, the chemical composition of urban aerosol particles has shown notable changes. The mass fraction of inorganic components has increased, with nitrate emerging as the dominant inorganic component. However, the impacts of these changes on the phase state of urban aerosol particles remain largely unknown. This study demonstrates that particles with a higher mass fraction of inorganic compounds, particularly nitrate, tend to exist in a liquid state. Consequently, an increased nitrate fraction allows urban aerosol particles to exist in a liquid state at lower relative humidity levels. These findings suggest that changes in the phase state of particles due to changes in chemical properties in urban aerosol particles should be considered to accurately gauge the mass‐transfer processes and promote the air quality improvements in urban cities. Key Points: Particles with more inorganic compounds, particularly nitrate, can exist in a liquid state at lower relative humidity levelsParticles with normalized aerosol liquid water content larger than 0.3 exist in a liquid stateNitrate‐dominated particles can serve as key seeds where secondary aerosol formation can occur via multiphase reactions [ABSTRACT FROM AUTHOR]

The interaction between atmospheric aerosols and moisture is crucial for aerosol properties and their climate effects. In this study, thanks to the rich measurements of aerosol properties during the 2016 and 2018 ORACLES campaigns, we investigate the aerosol liquid water content (ALWC) over the south-eastern Atlantic Ocean during the biomass burning (BB) season, as well as the seldom-reported ALWC associated with organic aerosols (OA) (ALWCOA) (OA). ALWCOA is determined using the OA hygroscopicity parameter KOA, derived from in-situ hygroscopicity measurements, particle number size distribution, and chemical composition. The ALWC can be determined either with the overall hygroscopic parameter K/RH) or from the sum of ALWCOA and the ALWC simulated from ISORROPIA-II, a thermodynamic equilibrium model for inorganic aerosol. The ALWC from both methods is highly correlated at all RHs with an R² of 0.99. The ALWC increases with aerosol loading and ambient relative humidity (RH). Due to the lower RH and higher aerosol loading in the 2016 campaign, the ALWC for both campaigns are generally consistent. ALWCOA accounts for 38±16 % of the total ALWC during both campaigns. Notably, the contribution of ALWCOA is greater than commonly reported in the literature, highlighting the significance of OA in ALWC and therefore the aerosol direct radiative forcing in this climatically significant region. The strong correlation between kOA and ALWCOA/ALWC, as indicated by an R² value of 0.72, underscores the importance of a good estimation of kOA in the ALWC estimation. Additionally, the significant difference between ALWCOAvalues calculated using real-time kOA and those calculated with the campaign mean kOA, highlights the limitation of using a constant kOA value, a practice commonly adopted in climate models. [ABSTRACT FROM AUTHOR]

Previous studies have primarily focused on the hydrological response of snowpack during rain‐on‐snow (ROS) events, with limited attention given to their subsequent stages, despite the significance of these stages. Therefore, this study selected two snow plots with similar initial parameters in the Qilian Mountains at an altitude of 4151 m. One of the snow plots underwent artificial rainfall simulation, and the changes in snow albedo, liquid water content, and snow depth of two snow plots were observed and analysed during the rainfall experiment and for a period of 7 days thereafter. The results indicate that ROS events significantly accelerate the rate of decrease in snow albedo and snow depth, increase the liquid water content within the snowpack, and these effects persist for several days after the rainfall event. Furthermore, the input of liquid water leads to rapid saturation of the snowpack, altering the transport mechanism of water within the snowpack, and transforming a process that would otherwise take a long time to complete into a short time. The decrease in snow albedo enhances the absorption of more energy by the snow, thereby accelerating snowmelt. Compared to natural snowmelt, ROS events cause the snowpack with high liquid water content to rapidly melt over a short period, resulting in a rapid increase in river flow, which may be one of the causes of ROS‐induced flooding. These research findings provide scientific insights for a better understanding of the disaster mechanisms associated with ROS events. [ABSTRACT FROM AUTHOR]

Continuous measurements of rainfall parameters are required for radio planning and flood management among others. However, due to the dearth of requisite infrastructure and expertise within the region, it is usually necessary to use satellite and reanalysis data. In this study, the performance of ECMWF ERA5 data in providing fall velocity (W) and liquid water content (LWC) estimates at different altitudes was compared with measurements from a ground-based Micro Rain Radar in a tropical location. Results obtained showed correlation values of 0.60–0.94 and 0.16–0.93 for fall velocity and liquid water content, respectively. The performance of ERA5 was found to decrease with altitude. In general, the results show the sufficient reliability of the ERA-5 reanalysis data for the two parameters on vertical scales. Therefore, it can be inferred that the ERA-5 data are reliable in estimating the average LWC and W, especially on a vertical scale for both hydrological and radio wave propagation studies. [ABSTRACT FROM AUTHOR]

Abstract Nitrate has become the primary inorganic compound in urban aerosol particles, but its effects on particle phase state, which is crucial in multiphase chemistry, remains largely unknown. Herein, particle rebound measurements were conducted to explore the relationship between the liquid–phase–transition threshold relative humidity (RHthreshold) and the inorganic compounds mass fraction in dry particles (Finorg). Results revealed negative correlations between RHthreshold and Finorg, with more nitrate leading to lower RHthreshold. Even with RH < 20%, particles with ∼50% nitrate mass fraction remained in non‐solid state. Taking Beijing as an example, decreases were observed in RHthreshold from 64% in 2015 to below 53% nowadays during the moderate‐pollution periods (PM2.5 = 35–75 μg/m3) due to an enhanced nitrate fraction. This allowed urban aerosol particles to exist in liquid state at lower RH, and consequently, kinetic limitation by bulk diffusion in nitrate‐dominated particles might be negligible, making them key seeds for secondary aerosol formation through multiphase reactions.

Adverse meteorological conditions often contribute to the formation of ice on aircraft wing section, engine nacelle and other parts leading to the loss of lift coefficient and increase in drag coefficient affecting aircraft control and stability. This paper addresses the problem of in-flight icing on an asymmetric aerofoil under three different ambient and cloud conditions. The study involves prediction of the leading-edge ice thickness using a numerical model developed from the mass and energy conservation law and Messinger freezing fraction model at the same Reynolds number. Later on, degradation in the aerodynamic performance of the iced aerofoil was also investigated using the computational fluid dynamics (CFD) technique, taking the flow field around a 2D aerofoil geometry into account. The aerodynamic study indicates that cumulus clouds embedded with stratified clouds contribute to the formation of mixed ice on aerofoil leading edge and causes the worst icing scenario reducing the lift coefficient to 90% and increasing the drag coefficient to 800% for the same ambient conditions. [ABSTRACT FROM AUTHOR]

Smoke from human-induced fires such as prescribed fires can occasionally cause significant reduction in visibility on highways in the southern United States. Visibility reduction to less than 3 m has been termed “superfog” and environmental conditions that lead to its formation have been proposed previously. Accurate characterization and prediction of precursor conditions for superfog is needed to prevent dangerous low visibility situations when planning prescribed fires. It is hypothesized that extremely hygroscopic cloud condensation nuclei from the smoldering phase of a fire can produce a large number of droplets smaller in size than in naturally occurring fog. This large number of small droplets can produce superfog conditions with relatively low liquid water content. A thermodynamics-based model for fog formation was developed. Laboratory generated superfog measured by a Phase Doppler Particle Analyzer determined that mean droplet radius was 1.5 μm and the size distribution could be modeled with a lognormal distribution. Experiments in an environmentally-conditioned wind tunnel using longleaf pine (Pinus palustris Mill.) needle fuel beds provided visibility, heat flux, temperature, humidity, and particle data for model validation. Numerical modeling was used to approximate the growth of a superfog boundary-layer with liquid water content values of 2 g m−3 or greater. The model successfully predicted previous superfog events.

Smoke from human-induced fires such as prescribed fires can occasionally cause significant reduction in visibility on highways in the southern United States. Visibility reduction to less than 3 m has been termed “superfog” and environmental conditions that lead to its formation have been proposed previously. Accurate characterization and prediction of precursor conditions for superfog is needed to prevent dangerous low visibility situations when planning prescribed fires. It is hypothesized that extremely hygroscopic cloud condensation nuclei from the smoldering phase of a fire can produce a large number of droplets smaller in size than in naturally occurring fog. This large number of small droplets can produce superfog conditions with relatively low liquid water content. A thermodynamics-based model for fog formation was developed. Laboratory generated superfog measured by a Phase Doppler Particle Analyzer determined that mean droplet radius was 1.5 μm and the size distribution could be modeled with a lognormal distribution. Experiments in an environmentally-conditioned wind tunnel using longleaf pine (Pinus palustris Mill.) needle fuel beds provided visibility, heat flux, temperature, humidity, and particle data for model validation. Numerical modeling was used to approximate the growth of a superfog boundary-layer with liquid water content values of 2 g m−3 or greater. The model successfully predicted previous superfog events.

The sensitivity of cloud microphysics to aerosol loading, quantified by the aerosol-cloud interactions (ACI) index, plays a crucial role in calculating the radiative forcing due to ACI (RF aci). However, the dependence of the ACI index on liquid water content (LWC) and its impact on RF aci are often overlooked. This study aims to investigate this dependence and evaluate its implications for RF aci , based on ground in-situ aerosol-cloud observations on Mt. Lu in eastern China. The results demonstrate that the ACI index exhibits an initial increase, followed by a decline with increasing LWC. In the unconstrained LWC scenario, the ACI index, calculated based on cloud droplet number concentration (ACI n of 0.13), is found to be lower than the lower bound of ACI n (0.17 to 0.35) obtained from the constrained LWC scenario. Neglecting this LWC -dependence leads to a significant underestimation of the mean RF aci by 53%. Furthermore, when calculating RF aci using the ACI index from droplet effective diameter (ACI d), implying the neglect of the dispersion effect by assuming a fixed droplet spectrum width, it results in an overestimation of RF aci by 22% compared to using ACI n. These findings shed new light on the assessment of RF aci and help reconcile differences between observed and simulated RF aci. Aerosol-cloud interactions are the major source of uncertainty in understanding human-induced climate change. This study focused on the relationship between aerosol and clouds, specifically investigating how the sensitivity of cloud properties to aerosol loading associates with the amount of liquid water present in the clouds. Using ground in-situ observations of clouds and aerosols on Mt. Lu in eastern China, this study showed that the sensitivity of cloud properties to aerosol loading initially increases and then decreases as the cloud water content increases. Neglecting this dependence can lead to a significant underestimation of the impact of aerosol-cloud interactions on climate. These findings provide valuable insights for improving our understanding of how aerosols and clouds interact and contribute to climate change. • The sensitivity of cloud microphysics to aerosol is highly associated with cloud liquid water content (LWC). • The RF aci could be significantly underestimated due to neglecting the dependence of cloud sensitivity on LWC. • Disregarding the dispersion effect causes RF aci to be overestimated by 22%. [ABSTRACT FROM AUTHOR]

Atmospheric icing, the accumulation of ice on surfaces, is a severe concern for the aviation industry. Deicing and icing prediction tools are necessary for pilots to ensure flight safety, and while there is established technology for large aircraft icing, more research is needed for smaller uncrewed aerial vehicles (UAVs). Here, we present measurements from 59 flights of a multirotor UAV into wintertime low stratus clouds of temperatures between − 3 and − 10 °C. The UAV is equipped with rotor heating to allow flights up to 10 min in icing conditions. Icing severity was quantified by using the rate of increase in battery current during icing, and was then compared with simultaneous, co-located measurements of liquid water content (LWC). LWC measurements were (a) calculated from cloud droplets measured with an in situ holographic imager on a tethered balloon system and (b) retrieved from remote sensing observations (microwave radiometer, ceilometer, cloud radar). We show that, for these environmental conditions, icing was strongly positively correlated to LWC over an LWC range of 0.02 to 0.5 g m−3, independent of temperature and mean droplet size, though droplets > 50 μm in diameter may contribute to increased icing severity. We also show that the LWC retrieved from remote sensing agrees well with the in situ measurements, indicating that remote sensing measurements can effectively be used to assess icing conditions. These are the first known measurements of multirotor UAV icing with co-located LWC measurements in natural clouds. • Icing severity quantified for a multirotor drone using the change in battery current. • Data presented from 59 flights of the drone into supercooled stratus clouds. • Icing severity was found to correlate strongly with supercooled liquid water content. [ABSTRACT FROM AUTHOR]

The amount of liquid water (LWC) present in the snowpack is critical for predicting wet snow avalanches, forecasting meltwater release, and assessing water availability in river basins. However, measuring this variable using traditional in situ methods is challenging. Space imaging spectroscopy is emerging as a promising approach to map the spatial and temporal variations of snow parameters. While some studies suggest the potential of hyperspectral remote sensing to infer liquid water content, field validation is still lacking. In this context, we propose a new spectral index, namely Snow Surficial Water Index (SSWI), which is designed to be sensitive to the percentage of surficial liquid water content in snow. We developed the index using the BioSNICAR radiative transfer model and then we tested it on both field spectral data and satellite PRISMA imagery. Validation was performed using field data collected with a Snow Sensor during four campaigns in alpine environments, one of which simultaneously with PRISMA. Through a k-fold cross-validation analysis, we achieved a coefficient of determination of 0.7 and a Root Mean Square Error equal to 3%, demonstrating the effectiveness of the proposed index in retrieving LWC from field data and mapping LWC from PRISMA data. A spatial analysis at the catchment level reinforced the results, showing an LWC distribution consistent with orography. The proposed method can be easily applied to other space imaging spectroscopy missions. • A snow water content spectral index is developed from a radiative transfer model. • Mapping and validation of liquid water content from hyperspectral satellite data. • The method is applicable to other space imaging spectroscopy missions. [ABSTRACT FROM AUTHOR]

Qilian Mountains are an important ecological barrier in Northwest China. The precipitation in Qilian Mountains is mainly caused by topographical cloud system. Aircraft detection in Qilian Mountains is of great significance for deepening the understanding of cloud microphysical processes, and for scientifically and effectively carrying out artificial precipitation operations to improve the ecological environment. Using the airborne observations of a topographic cloud precipitation process in Qilian Mountains on 29 August 2020, the microphysical characteristics of the summer cloud precipitation process in Qilian Mountains are studied. The cloud system presents an obvious layered structure. The height of the cloud base is 4000 m, and the water content of the whole layer is relatively rich. The liquid water content (L) is between 0.65 and 1.1 g·m-3, and the cloud water large value area appears at 4500-5300 m altitude, which has a high concentration of cloud droplets. The water content of cloud water is mainly contributed by cloud droplets between 15 and 20 μm. The average concentrations of small cloud particles and large cloud particles are 7.54 cm-3 and 0.86 cm-3. The average effective diameters of small cloud particles and large cloud particles are 11.02 μm and 198.11 μm. The cloud particles in Qilian Mountains have the characteristics of small concentration and large diameter. There are obvious differences in cloud microphysical characteristics between the north and south slopes of Qilian Mountains. Affected by the topography, the concentration and diameter of cloud droplets on the northern slope are larger than those on the southern slope, and L on the northern slope are significantly larger than those on the southern slope too. The spectra of cloud droplets at different heights in Qilian Mountains are respectively unimodal distribution. The spectrum of cloud droplets with a diameter less than 50 μm can be fitted by Gamma distribution, while the spectrum of cloud droplets with a diameter greater than 50 μm shows a power exponent distribution. The ice crystals in the ice layer are mainly grown through the process of sublimation and coalescence. The growth mechanism of the ice crystals in the mixed layer is mainly the Bergeron process, and accompanied by attachment and aggregation growth.

Based on the cloud microphysical detection data of 10-sortie aircraft over southern Sichuan Basin in 2015 and 2017, the liquid water content measured by DMT (Droplet Measurement Technologies) hot-wire liquid water content sensor is examined, and abnormal values in maximum, minimum and negative values are found.There are 4 possible causes for the abnormal maximum, minimum and negative values of liquid water content. First, the errors are caused by multiple parameters such as temperature, air pressure and vacuum velocity, which may lead to the error superposition of calculated values. Second, the on-board operators didn't calibrate the zero before entering the cloud. Third, the on-board operators only calibrate the zero once before entering the cloud during the whole flight. Fourth, the interval between cloud entry and exit is too short, so that the manual zero calibration is inaccurate.Using cloud particle spectrum data from cloud droplet probe (CDP), cloud imaging probe (CIP) and precipitation imaging probe (PIP), three solutions are proposed for calibrating hot-wire liquid water content sensor. Solution 1 is to set the criteria for entering cloud as the concentration of particle above a certain size from CDP probe greater than 0. Solution 2 is to set the criteria for entering cloud as the number concentration of cloud particles greater than 10 cm-3 from CDP probe. Solution 3 is to set the criteria for entering cloud as the number concentration from CDP, CIP and PIP probe greater than 0. The results show that when the number concentration is 0 from CDP, CIP and PIP probe, the original non-zero liquid water content problems are corrected by these solutions.To avoid the influence of ice phase particles on CDP number concentration, the verification is carried out in the positive temperature zone. All the test results show that the negative proportion of liquid water content is also significantly reduced compared with the original data. Solution 1 reduces the negative proportion of liquid water content, and make the minimum and maximum more reasonable than other scales. The liquid water content measured by Solution 1 are more reasonable than Solution 2 and 3.

Water percolation in snow plays a crucial role in the avalanche risk assessment. Liquid water content and wetting front are hard to measure in the field; hence, accurate simulation of the phenomena can be of great help to forecasters. This study was the first to evaluate water percolation simulations with the SNOWPACK model using Richards’ scheme on Mount Fidelity, Glacier National Park, Canada. The study highlights that, at this site, an updated configuration on precipitation phase transition and new snow density can significantly improve simulations of the snow cover, and water percolation in particular, which can be relevant in an era of an increased occurrence of rain-on-snow (ROS) events. More specifically, emphasis was put on the quality of the input data and parameters. The analysis of the precipitation phase temperature threshold showed that a value of 1.4°C was the best suited to track the rain/snow transition on site. A 10-year analysis of 24-h precipitation measured using the rain gauge and 24-h new snow water equivalent showed an excellent correlation. New snow density sub-models were evaluated using the 24-h new snow density values taken by the park technicians. The BELLAIRE model performed best and was used to drive the snow simulations. Two SNOWPACK snow simulations were evaluated using 1) rain gauge precipitation amount (PCPM) and 2) automatic snow height measurement (HS) at the same site. Both runs simulated the main snowpack layers observed during the dry season (i.e., before spring percolation was observed), and both simulated the snow properties with good accuracy. The water equivalent of snow cover, used as a proxy for a first-order characterization of the simulations generated by both simulations, was slightly underestimated compared with four manual measurements taken on-site during the winter. Nevertheless, the comparison of both measured density and modeled bulk density showed great correspondence. The percolation timing and wetting front depth were evaluated using field measurements from field campaigns and continuous observations from on-site instruments. The main percolation events were correctly simulated and were coincident with the observed wet avalanche cycles. The results highlight the need for accurate input data on valid simulation of the wetting front and percolation timing on site. Good percolation information generated using the SNOWPACK model and Richards’ scheme could be used to assess the snowpack stability by forecasters in areas where such data are available.

Fog is challenging to predict, and the accuracy of fog prediction may depend on location and time of day. Furthermore, accurate detection of fog is difficult, since, historically, it is often carried out based on visual observations which can be biased and are often not very frequent. Furthermore, visual observations are more challenging to make during the night. To overcome these limitations, we detected fog using FM-120 instruments, which continuously measured liquid water content in the air in the Monterey, California (USA), area. We used and compared the prediction performance of logistic regression (LR) and random forest (RF) models each evening between 5 pm and 9 pm, which is often the time when advection fog is generated in this coastal region. The relative performances of the models depended on the hours between 5 pm and 9 pm, and the two models often generated different predictions. In such cases, a consensus approach was considered by revisiting the past performance of each model and weighting more heavily the more trustworthy model for a given hour. The LR resulted in a higher sensitivity (hit rate) than the RF model early in the evening, but the overall performance of the RF was usually better than that of the LR. The consensus approach provided more robust prediction performance (closer to a better accuracy level between the two methods). It was difficult to conclude which of the LR and RF models was superior consistently, and the consensus approach provided robustness in 3 and 2 h forecasts. [ABSTRACT FROM AUTHOR]

Seasonal alpine snow contributes significantly to the water resource. It plays a crucial role in regulating the environmental feedback and from the perspective of socio-economic sustainability in the alpine regions. While most nations are pursuing renewable energy sources, hydropower generated from snowmelt runoff is one of the primary sources. Additionally, alpine regions with snow cover are major tourist destinations that are often affected by natural disasters such as avalanches. The snowmelt runoff and early avalanche warning require timely information on the spatio-temporal aspects of the snow geophysical parameters. In this regard, advances in remote sensing of snow have been observed to be significant. Recent developments in remote sensing technology in the visible, infrared, and microwave spectrum have significantly improved our understanding of snow geophysical processes. This paper provides a review concerning the qualitative and quantitative studies of alpine snow. The electromagnetic characteristics of the alpine snow are largely dependent upon its inherent geophysical structure and the properties of the snow. Snow behaves differently with respect to the wavelength of the incident radiation. In this paper, we provide a categorical review of the remote sensing techniques for estimating the snow geophysical properties, inclusive of permittivity, density, and wetness corresponding to the wavelength used in the remotely sensed data: (1) visible-infrared spectrum including multispectral/hyperspectral, (2) active and passive microwave spectrums. We also discuss the recent advancements in the remote sensing techniques for approximating the volumetric snowpack parameters such as the snow depth and the snow water equivalent based on active and passive microwave remote sensing. This review further discusses the limitations of the techniques reviewed and future prospects for the retrieval of snow geophysical parameters (SGP) corresponding to the recent progress in remote sensing technology. In summary, the recent advances have laid down a foundation for rigorous assessment of seasonal snow using spaceborne remote sensing, particularly at a regional scale. Yet, the scope for improvements in the methods and payload design exists.

While the assimilation of dual-polarimetric radar observations in weather forecast models is promising especially for short-term forecasts of precipitation, the direct assimilation of polarimetric variables is still challenging because of the rather rudimentary appreciation of particle size and shape distributions by the models. Thus, current studies recede to assimilating model state variables derived from dual-polarimetric observables, such as hydrometeor mixing ratios. This study evaluates, improves and adapts estimators for liquid water content for their application to observations of the polarimetric C‑band radar network of the German national meteorological service as a first step towards their assimilation in the ICON model. T‑matrix simulations are used to derive polarimetric observables from a large data set of drop size distributions (DSDs) observed over Germany. Existing estimators based on reflectivity (Z), differential reflectivity (ZDR), specific attenuation (A) and specific differential phase (KDP) applied to this data set yield mostly unsatisfactory results and motivated the search for and development of improved estimators. The latter much better approximate the simulated data, and also mostly outperform the existing estimators when applied to real radar observations over Germany, although by a smaller degree. The new KDP-based estimator could only outperform existing algorithms, when KDP for azimuth-range intervals with negative KDPs were replaced by a Z-based KDP estimation. Further potential radar observation deficiencies in determining Z, ZDR, A and KDP motivated the development of a potentially more stable hybrid estimator based on the new LWC(Z,ZDR), LWC(A) and LWC(KDP) estimators. This hybrid estimator outperforms both the adapted and existing LWC estimators in terms of the correlation coefficient.

The infiltration of liquid water in a seasonal snowpack is a complex process that consists of two primary mechanisms: a semi-uniform melting front, or matrix flow, and heterogeneous preferential flow paths. Distinguishing between these two mechanisms is important for monitoring snow melt progression, which is relevant for hydrology and avalanche forecasting. It has been demonstrated that a single co-polarized upward-looking radar can be used to track matrix flow, whereas preferential flow paths have yet to be detected. Here, from within a controlled laboratory environment, a continuous polarimetric upward-looking C-band radar was used to monitor melting snow samples to determine if cross-polarized radar returns are sensitive to the presence and development of preferential flow paths. The experimental dataset consisted of six samples, for which the melting process was interrupted at increasing stages of preferential flow path development. Using a new serial-section hyperspectral imaging method, polarimetric radar returns were compared against the three-dimensional liquid water content distribution and preferential flow path morphology. It was observed that the cross-polarized signal increased by 13.1 dB across these experiments. This comparison showed that the metrics used to characterize the flow path morphology are related to the increase in cross-polarized radar returns spanning the six samples, indicating that the upward-looking polarimetric radar has potential to identify preferential flow paths. [ABSTRACT FROM AUTHOR]

To develop effective mitigation policies, a comprehensive understanding of the evolution of the chemical composition, formation mechanisms, and the contribution of sources at different pollution levels is required. PM2.5 samples were collected for 1 year from August 2016 to August 2017 at an urban site in Zibo, then chemical compositions were analyzed. Secondary inorganic aerosols (SNA), anthropogenic minerals (MIN), and organic matter (OM) were the most abundant components of PM2.5, but only the mass fraction of SNA increased as the pollution evolved, implying that PM2.5 pollution was caused by the formation of secondary aerosols, especially nitrate. A more intense secondary transformation was found in the heating season (from November 15, 2016, to March 14, 2017), and a faster secondary conversion of nitrate than sulfate was discovered as the pollution level increased. The formation of sulfate was dominated by heterogeneous reactions. High relative humidity (RH) in polluted periods accelerated the formation of sulfate, and high temperature in the non-heating season also promoted the formation of sulfate. Zibo city was under ammonium-rich conditions during polluted periods in both seasons; therefore, nitrate was mainly formed through homogeneous reactions. The liquid water content increased significantly as the pollution levels increased when the RH was above 80%, indicating that the hygroscopic growth of aerosol aggravated the PM2.5 pollution. Source apportionment showed that PM2.5 was mainly from secondary aerosol formation, road dust, coal combustion, and vehicle emissions, contributing 36.6%, 16.5%, 14.7%, and 13.1% of PM2.5 mass, respectively. The contribution of secondary aerosol formation increased remarkably with the deterioration of air quality, especially in the heating season. [ABSTRACT FROM AUTHOR]

• Snow removal from photovoltaic modules were classified into four distinct mechanisms. • A sensor was used to monitor/measure the liquid water content (LWC) of snow. • The surface-mountable sensor enabled real-time and non-destructive measurement of the LWC. • The LWC measurements enabled classification of snow removal mechanisms. • Classification of snow removal mechanisms could lead to efficient snow mitigation strategies. Snow accumulation on photovoltaic (PV) modules causes major economic losses by reducing/preventing solar energy production. To develop mitigation strategies for snow accumulation issues on the PV modules, it is crucial to understand various snow removal mechanisms from them. Here, natural snow accumulation and its removal from the PV modules were investigated over two years using a surface-mountable sensor that measures liquid water content (LWC) at the interface of snow and module's surface real-time. It was found that the snow removal from the PV modules occurs under four distinct categories: melting, shedding (fast sliding), prolonged melting, and melting followed by shedding. During snow melting, the average LWC of snow and the module's surface temperature increased gradually (13.45%/hr and 0.81 °C/hr), while during snow shedding the average LWC and surface temperature sharply increased (14.4%/hr and 1.46 °C/hr). During prolonged melting, the average LWC of snow slowly increased during the day (4 average LWC slopes were 5.88, 3.22, 6.18, and 7.92%/hr), and the module's surface temperature reached 0 °C for a very short period of time, then decreased back to freezing temperatures at night. Lastly, the final snow removal mechanism is melting followed by shedding, during which the average LWC of snow increased gradually indication of snow melting (LWC of 11.25%/hr), followed by a very sharp increase in LWC with an average rate of ∼83.02%/hr, after which snow shedding occurred. These understanding provide means to develop a combined passive and active mitigation strategy for efficient snow removal from the photovoltaic modules. [ABSTRACT FROM AUTHOR]

This study was the first to conduct high-resolution consecutive detection of clouds over the hinterland of the Taklimakan Desert (TD) from April to June 2018 based on a ground-based Ka-band millimeter-wave cloud radar (MMCR), with focus on the structure and evolution of the desert clouds. We calculated reflectivity factor (Z), cloud boundary, and liquid water content (LWC) by use of the MMCR power spectrum data, which were verified against the observations from cloud profile radar (CPR) on board CloudSat. The results show that the TD clouds were mostly medium and high clouds, with thickness generally less than 2 km; moreover, the mean LWCs of these clouds were less than 0.01 g m−3, implying that cirrus and stratiform clouds were predominant. For the observed low clouds, however, the average thickness was 3166 m and accompanying drizzles were concentrated within 2.5–4.5 km, indicating that precipitation was more likely to occur in the low clouds. The mean LWC in the TD clouds was 0.0196 g m−3, less than that of clean clouds. Compared to other periods, the average durations and LWCs in the TD clouds increased significantly around noon owing to obvious surface sensible heating. The average time for evolution of high clouds into low clouds was approximately 2 h, and the average maximum LWC increased from 0.008 to 0.139 g m−3. The results obtained herein provide a key reference for further studies of the structure and evolution characteristics of the desert clouds. [ABSTRACT FROM AUTHOR]

We developed the “REAL-Fog” (R‑Estimated spatiAL Fog) tool to calculate the ground-level fog by means of liquid water content (lwc) at a temporal resolution of 1 hour. The tool is based on a distributed and mainly physical model and requires a digital elevation model (DEM) and hourly observations of temperature and humidity. The tool spatially interpolates the air temperature and derived vapour pressure to determine whether the air at ground level is supersaturated. From the supersaturation result, the lwc is then calculated. Due to errors in the measured humidity time series, preprocessing is additionally recommended. Different sources of errors, such as sensor ageing, calibration and sensor uncertainty, are discussed, and a correction method is proposed. The “REAL-Fog” method was applied in a case study of Germany from 1949 to 2017. The daily updated results of this analysis can be found at www.nebelzentrale.de. Two validation strategies are applied. First, modelled lwc values are compared with measured lwc values at Mt. Brocken (1141 m a.s.l.), which is one of the longest time series of lwc in the world and the longest in Germany. The event-based (fog, no fog) Heidke skill score (HSS) reached 0.8. Second, the event-based performance was calculated for 306 visibility sites in Germany. HSS was found to be 0.54.

Dense fog events and their micrometeorological characteristics and structural evolution at Indira Gandhi International Airport (IGIA), New Delhi, during the Winter Fog Experiment (WiFEX) are illustrated in this study. Four dense fog events that occurred in January 2016 for which visibility dropped below 200 m have been selected. Depending on the visibility and micrometeorological structure, the fog processes were classified into (i) an initial formation as a thermally stable optically thin fog and (ii) a subsequent mature, weakly unstable deep fog. Surface radiative cooling supported by a deep saturated layer in the nocturnal surface layer promotes the rapid development and intensification of the initial shallow fog into the extremely dense fog. Optically thin fog appeared to develop when a thin saturated layer of air formed near the ground under low-turbulence kinetic energy (< 0.1 m2/s2). The fog was sustained in the optically thin phase until the air at 20 m remained in a sub-saturated condition in the thermally stable surface layer. Furthermore, when the saturated layer near the surface progressively expanded upward as a result of sustained cooling inside the shallow fog, it rapidly transformed into an extremely dense fog. The threshold for transition from the optically thin phase to extremely dense phase appeared when the air at 20 m neared the saturation point. The dense fog observations for all cases indicate that when the saturated layer was deeper than 20 m, the fog was able to withstand larger turbulence intensity (TKE values between 0.4 m2/s2 and 0.5 m2/s2). [ABSTRACT FROM AUTHOR]

To develop the method of retrieving cloud liquid water content by using both radar and microwave radiometer, the present study analyzes the data from the dual band cloud radar and microwave radiometer in the comprehensive observation test that was carried out in Longmen by the Chinese Academy of Meteorological Sciences from April to September 2019. Firstly, the temperature (T), relative humidity (RH), liquid water content (LWC) and liquid water path (LWP) retrieved by microwave radiometer zenith observation and off-zenith observation during precipitation events is tested, and then the difference between LWC and LWP retrieved by two kinds of detection equipment is analyzed. The results are as follows: (1) The products retrieved by microwave radiometer in off-zenith observation mode are less affected by precipitation, and the retrieval results are obviously better than those of zenith observation mode. (2) The LWP retrieved by the two detection devices has good correlation and is consistent over time. However, the LWP retrieved by cloud radar is significantly correlated with average echo intensity. With the increase of radar echo, the ratio of LWP retrieved by cloud radar to microwave radiometer increases. (3) The correlation of LWC retrieved by the two detection devices is poor and there is a significant deviation. When the melting layer is not considered, the LWC retrieved by single band cloud radar and microwave radiometer has a similar change trend with height, and the retrieval results of dualband cloud radar and microwave radiometer are significantly different in the range of 1km and above. [ABSTRACT FROM AUTHOR]

The presence of embedded convection in stratiform clouds strongly affects ice microphysical properties and precipitation formation. In situ aircraft measurements, including upward and downward spirals and horizontal penetrations, were performed within both embedded convective cells and stratiform regions of a mixed-phase stratiform cloud system on 22 May 2017. Supercooled liquid water measurements, particle size distributions, and particle habits in different cloud regions were discussed with the intent of characterizing the riming process and determining how particle size distributions vary from convective to stratiform regions. Significant amounts of supercooled liquid water, with maxima up to 0.6 g m−3, were observed between −3°C and −6°C in the embedded convective cells while the peak liquid water content was generally less than 0.1 g m−3 in the stratiform regions. There are two distinct differences in particle size distributions between convective and stratiform regions. One difference is the significant shift toward larger particles from upper −15°C to lower −10°C in the convective region, with the maximum particle dimensions increasing from less than 6000 µm to over 1 cm. The particles larger than 1 cm at −10°C are composed of dendrites and their aggregates. The other difference is the large concentrations of small particles (25–205 µm) at temperatures between −3°C and −5°C in the convective region, where rimed ice particles and needles coexist. Needle regions are observed from three of the five spirals, but only the cloud conditions within the convective region fit into the Hallett-Mossop criteria. [ABSTRACT FROM AUTHOR]

Different salt types have different effects on the liquid water content of saline soil, resulting in differences in the physico-mechanical properties and water/salt migration process of saline soil. In order to investigate the phase transition process and the change of the liquid water content in composite saline soil, saline soils with the same total salt content and different ratios of sodium chloride and sodium sulfate were taken as the objects. The results indicated that two phase transitions occur in the saline soil with single salt type, while three phase transitions can be found in the composite saline soil with two salt types. Mirabilite crystallization contributes to the 1st phase transition, mirabilite and ice precipitate together in the 2nd phase transition process, and mirabilite, ice, and hydrohalite precipitate simultaneously in the 3rd phase transition process. The liquid water is reduced in the phase transition process during cooling, and the pore characteristic has been changed significantly. The change of the liquid water content reflects the processes of salt crystallization and ice formation in saline soil, then the amounts of ice and hydrated salt were calculated at different temperatures, and the mechanism of inhibiting the deformation of sulfate saline soil was examined by adding sodium chloride. The results have reference value for those seeking understanding of the deformation in natural composite saline soil, and these findings can provide theoretical basis for the phase transition mechanism of saline soil in cold regions. • Three phase transition process exist in composite saline soil with two salt types. • Ice and salt crystallization decrease the liquid water content of saline soil. • Chloride ion mitigates the saline soil deformation by reducing the freezing point. [ABSTRACT FROM AUTHOR]

Fog is challenging to predict, and the accuracy of fog prediction may depend on location and time of day. Furthermore, accurate detection of fog is difficult, since, historically, it is often carried out based on visual observations which can be biased and are often not very frequent. Furthermore, visual observations are more challenging to make during the night. To overcome these limitations, we detected fog using FM-120 instruments, which continuously measured liquid water content in the air in the Monterey, California (USA), area. We used and compared the prediction performance of logistic regression (LR) and random forest (RF) models each evening between 5 pm and 9 pm, which is often the time when advection fog is generated in this coastal region. The relative performances of the models depended on the hours between 5 pm and 9 pm, and the two models often generated different predictions. In such cases, a consensus approach was considered by revisiting the past performance of each model and weighting more heavily the more trustworthy model for a given hour. The LR resulted in a higher sensitivity (hit rate) than the RF model early in the evening, but the overall performance of the RF was usually better than that of the LR. The consensus approach provided more robust prediction performance (closer to a better accuracy level between the two methods). It was difficult to conclude which of the LR and RF models was superior consistently, and the consensus approach provided robustness in 3 and 2 h forecasts.