Top Height Research Articles

Summer and Winter Anomalies of Day and Night Cloud Parameters over Western Siberia Using MODIS Data and ERA5 Reanalysis During 2001–2022

We present the results of analysis of multiyear variability of cloud parameters (day and night) over Western Siberia in summer and winter during 2001-2022 based on MODIS data and ERA5 reanalysis. Three latitude zones of the target region are considered: northern (66-72° N, 68-82° E), transitional (60-65° N, 62-88° E) and southern (54-59° N, 62-88° E). We have plotted time series and on their basis we have identified trends of the following cloud parameters: fraction, top height, top pressure, top temperature and effective emissivity. It was found that in 2010, 2012, 2014 and 2016, the largest number of anomalies in the time series of the above cloud features was observed. The comparison results for the considered cloud parameters with the variability of the land surface temperature and geopotential heights at the baric levels of 500, 700, 850 and 1000 hPa are presented. We discuss hypotheses about the causes of anomalous values in time series of investigated cloud parameters at different times of day in summer and winter, related to the specific features of atmospheric circulation over Western Siberia in different years.

Analysis of Macro- and Microphysical Characteristics of Ice Clouds over the Tibetan Plateau Using CloudSat/CALIPSO Data

Utilizing CloudSat/CALIPSO satellite data and ERA5 reanalysis data from 2007 to 2016, this study analyzed the distributions of optical and physical characteristics and change characteristics of ice clouds over the Tibetan Plateau (TP). The results show that the frequency of ice clouds in the cold season (November to March) on the plateau is over 80%, while in the warm season (May to September) it is around 60%. The average cloud base height of ice clouds in the warm season is 3–5 km, and mostly around 2 km in the cold season. The average cloud top height in the warm season is around 5–8 km, while in the cold season it is mainly around 4.5 km. The average thickness of ice clouds in both seasons is around 2 km. The statistical results of microphysical characteristics show that the ice water content is around 10−1 to 103 mg/m3, and the effective radius of ice clouds is mainly in the range of 10–90 μm. Both have their highest frequency in the west of the TP and lowest in the northeast. A comprehensive analysis of the change in temperature, water vapor, and ice cloud occurrence frequency shows that the rate of increase in water vapor in the warm season is greater than that in the cold season, while the rates of increase in both surface temperature and ice cloud occurrence are smaller than in the cold season. The rate of increase in temperature in the warm season is around 0.038 °C/yr, and that in the cold season is around 0.095 °C/yr. The growth rate of thin ice clouds in the warm season is around 0.15% per year, while that in the cold season is as high as 1% per year. The results suggest that the surface temperature change may be related to the occurrence frequency of thin ice clouds, with the notable increase in temperature during the cold season possibly being associated with a significant increase in the occurrence frequency of thin ice clouds.

Cloud classification through machine learning and global horizontal irradiance data analysis

AbstractCloud observations and characterization are crucial owing to their influence on energy balance, climate, and weather. Their particular effects on radiation vary depending on different cloud parameters, such as cloud base or top height, water content, and cloud optical thickness, all of them closely related to the specific cloud type. Cloud classification therefore becomes a crucial task in meteorology, although it remains challenging for weather services worldwide owing to the intensive associated labor and cost. In this study we introduce a new low‐cost method for automating cloud classification based on a combination of ground‐based global horizontal irradiance (GHI) measurements, a clear‐sky model, and machine learning. Based on the hypothesis that different cloud types have their own GHI signatures, we trained different supervised learning algorithms using GHI data manually labeled by meteorological observers from time‐synchronized all‐sky images. Multiple time windows were extracted from each GHI series, with eight features defined in each case to characterize the sequence. The best outcome was achieved using an XGBoost model on features extracted on time windows of 33 min, obtaining an accuracy of 0.88 and a Cohen's kappa of 0.84 in a held‐out test set. The development presented in this study has the ability to provide low‐cost cloud classification from ground‐based observations, which is a challenge for weather services worldwide owing to intensive labor and cost.

The Non-Monotonic Response of Cumulus Congestus to the Concentration of Cloud Condensation Nuclei

This study uses idealized simulations to investigate the impact of cloud condensation nuclei (CCN) on a cumulus congestus. Thirteen cases with the initial CCN_C, which is the CCN concentration at 1% supersaturation with respect to water, from 10 to 10,000 cm−3 are simulated. The analysis focuses on the liquid phase due to the negligible ice phase in this study. A non-monotonic response of cloud properties and precipitation to CCN concentration is observed. When CCN_C is increased from 10 to 50 cm−3, the enhanced condensation due to the more numerous droplets invigorates the cumulus congestus. The delayed precipitation formation due to the smaller droplets also facilitates the cloud development. The two processes together lead to a higher liquid water path (LWP), higher cloud top, and heavier precipitation. The cumulus congestus has the highest cloud top, the strongest updraft, and the most accumulated precipitation and at CCN_C = 50 cm−3. When CCN_C is increased from 50 to 500 cm−3, the condensation near the cloud base is further enhanced and the precipitation is further delayed, both of which lead to more liquid water remaining in the cloud, and thus an even higher LWP and heavier precipitation rate in the later stage. However, the significantly enhanced evaporation near the cloud top limits the vertical development of the cumulus congestus, leading to a lower cloud top. When CCN_C is further increased to be higher than 1000 cm−3, the cumulus congestus is strongly suppressed, and no precipitation forms. The ratio of the precipitation production rate to vertical cloud water flux in the updraft is not a constant, as is generally assumed in cumulus parameterization schemes, but decreases significantly with increasing CCN concentration. It is also found that the CCN effect on the cumulus congestus relies on which parameters are used to describe the cloud strength. In this study, as CCN_C increases, the LWP and the maximum precipitation rate peak at CCN_C = 500 cm−3, while the cloud top height, maximum updraft, and accumulated precipitation amount peak at CCN_C = 50 cm−3.

Monitoring Earth's atmosphere with Sentinel-5 TROPOMI and Artificial Intelligence: Quantifying volcanic SO2 emissions

Identifying changes in volcanic unrest and tracking eruptive activity are fundamental for volcanic surveillance and monitoring. Magmatic gases, particularly sulphur dioxide (SO2), play a crucial role in influencing eruptive styles, making the monitoring of SO2 emissions essential. Recent advancements in satellite remote sensing technology, including higher spatial resolution and sensitivity, have enhanced our ability to detect SO2 emissions from volcanoes worldwide. However, traditional fixed-threshold algorithms struggle to automatically distinguish volcanic SO2 emissions from non-volcanic sources. Additionally, accurately quantifying SO2 emissions is challenging due to their dependence on plume height, particularly when reaching high altitudes. To address these challenges, we developed an Artificial Intelligence (AI) algorithm that detects and quantifies volcanic SO2 emissions in near real-time. Our approach utilizes a Random Forest (RF) model, a supervised Machine Learning (ML) algorithm, to identify volcanic SO2 emissions and integrates Cloud Top Height (CTH) data to enhance the accuracy of SO2 mass quantification during intense volcanic eruptions. This AI algorithm, fully implemented in Google Earth Engine (GEE), leverages data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5 Precursor (S5P) satellite to automatically retrieve daily volcanic SO2 plumes and CTH. We validated the model's performance against the Radius classifier, a state-of-the-art tool, and generalized its application across various volcanoes (Etna, Villarrica, Fuego, Pacaya, and Cumbre Vieja) with differing degassing activities, SO2 emission rates, and plume geometries. Our findings demonstrate that the proposed AI approach effectively identifies and quantifies SO2 plumes emitted by different volcanoes, enabling the investigation of SO2 emission time series that reflect magma dynamics.

A low-cost alternative to LiDAR for site index models: applying repeated digital aerial photogrammetry data in the modelling of forest top height growth

Abstract Environmental and forest structural information derived from remote sensing data has been found suitable for modelling forest height growth and site index and therefore forest productivity assessment, with the advances in airborne laser scanning (ALS) playing a major role in this development. While there is growing interest in the use of ALS-derived point clouds, point clouds from high-resolution digital aerial photography (DAP) are also often used for mapping and estimating forest ecosystem properties due to their lower acquisition costs. In this study, we document the applicability of bi-temporal DAP data for developing top height (TH) growth models for Scots pine stands. Our results indicate that DAP data can function as an alternative to traditional TH measurements used in growth modelling when corrected based on a limited sample of field-measured reference TH values. As the correction cannot be constant for each DAP dataset due to the different parameters during data acquisition, we propose a straightforward method for the bias correction of DAP-derived TH estimates. By undertaking iterative random sampling, we were able to find the minimum number of reference measurements needed to calculate the TH correction in order to achieve the desired accuracy of the TH estimations based on DAP. Here, we used ALS data as the reference data; however, the ALS measurements can be replaced by any other reliable source of TH values. The presented method for determining TH can be used not only for site index and forest growth modelling but also in forest inventories.

Cirrus cloud occurrence and its geometrical and optical properties during the transient monsoon conditions

Knowledge of variation in the percentage occurrence of the cirrus clouds (POC) during transient monsoon conditions is essential for understanding the role of the monsoon in transporting the water vapor into the lower stratosphere which is vital in quantifying the radiation budget of the earth–atmosphere system. In this paper, we present the spatial structure of the POC, the geometrical properties such as cloud top and base height (CTH & CBH), cloud thickness (CTH-CBH), optical properties such as optically thick, thin, and subvisible cirrus clouds during the active and break phases of the Asian summer monsoon using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) during July–August 2006–2018. The active and break phases are identified based on the central India rainfall from the India Meteorological Department dataset. The POC is found to be higher by 10–30 % over central India and some parts of the eastern Arabian Sea (AS) and Bay of Bengal (BoB) during the active phase compared to the break phase which shows enhancement in POC over the foothill of Himalaya and southern part of BoB and AS. The higher POC is attributed to the increase in the convective activities associated with the increase in tropical easterly jet during the active phase. The CTH and CBH range ~14–18 km and 12–16 km, respectively during the active phase compared to the break phase. The contributions of optically thick and thin clouds are higher in POC during both phases compared to subvisible clouds. Both convectively generated and in situ-formed cirrus clouds dominate during the active phase compared to the break phase indicating the dominance of the freeze-drying processes during the active phase.

Initiation and evolution of urban-induced precipitation under different background wind speeds: Roles of urban breeze circulation and cold pool

Urban-enhanced precipitation is often observed far downwind of cities, suggesting important roles of background wind. This study examines the impacts of background wind on the initiation and evolution of urban-induced precipitation through idealized ensemble large-eddy simulations with different initial background wind speeds of 0, 1, 2, 3, 4, and 5 m s−1. Without background wind, a strong urban breeze circulation (UBC) initiates a relatively large number of cumulus clouds in the urban area, which exhibit greater cloud top heights than those in the rural area. The early-initiated clouds do not produce precipitation but moisten the middle troposphere, assisting later-initiated clouds to develop into deep convective clouds and produce concentrated precipitation in the urban area. As the background wind speed increases, the UBC weakens. Also, the high-humidity area generated by early-initiated clouds is continuously advected away from the urban area. Consequently, the precipitation initiation is delayed as the background wind speed increases. Precipitating clouds are advected downwind and generate a cold pool, and updrafts are repeatedly produced at the downwind boundary of the cold pool. The downwind-advected clouds are fed by the newly produced updrafts, being a long-lived organized precipitation system that produces a considerable amount of precipitation in the downwind area. This feeding effect is most prominent for a moderate background wind (3 m s−1), causing the precipitation amount and duration to be maximized. For stronger background winds, precipitation is initiated by the mechanical lifting of the warm air of the urban boundary layer over the cool rural boundary layer around sunset.

Microphysical Characteristics of Monsoon Precipitation over Yangtze-and-Huai River Basin and South China: A Comparative Study from GPM DPR Observation

It is rare to conduct a comparative analysis of precipitation characteristics across regions based on long-term homogeneous active satellite observations. By collocating the Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM DPR) observations with European Centre for Medium-Range Weather Forecasts 5th Reanalysis (ERA5) data, this study comparatively examines the microphysics of monsoon precipitation in the rainy season over the Yangtze-and-Huai River Basin (YHRB) and South China (SC) from 2014 to 2023. The comparative analysis is made in terms of precipitation types and intensities, precipitation efficiency index (PEI), and ice phase layer (IPL) width. The results show that the mean near-surface precipitation rate and PEI are generally higher over SC (2.87 mm/h, 3.43 h−1) than over YHRB (2.27 mm/h, 3.22 h−1) due to the more frequent occurrence of convective precipitation. The DSD characteristics of heavy precipitation in the wet season for both regions are similar to those of deep ocean convection, which is associated with a greater amount of water vapor. However, over SC, there are larger but fewer raindrops in the near-surface precipitation. Moreover, moderate PEI precipitation is the main contributor to heavy precipitation (>8 mm/h). Stratiform precipitation over YHRB is frequent enough to contribute more than convective precipitation to heavy precipitation (8–20 mm/h). The combined effect of stronger convective available potential energy and low-level vertical wind favors intense convection over SC, resulting in a larger storm top height (STH) than that over YHRB. Consequently, it is conducive to enhancing the microphysical processes of the ice and melt phases within the precipitation. The vertical wind can also influence the liquid phase processes below the melting layer. Collectively, these dynamic microphysical processes are important in shaping the efficiency and intensity of precipitation.

SAMPO-P: A prototypical scale low-temperature experiment on two-layer melt pool heat transfer in LWR lower head

To better understand the thermal behavior of a two-layer melt pool with a high Rayleigh number—a pattern observed in the RASPLAV study, which indicates a significant risk to pressure vessel integrity and the success of in-vessel retention (IVR) strategies—this paper reports experimental findings from a 2D, full-scale (1:1 ratio) prototypical stratified melt pool (SAMPO-P). A series of experimental tests were carried out with varying heating powers and top layer heights, achieving a Rayleigh number of 3.77×1015, comparable to that found in light water reactors (LWR). Water was used to simulate the bottom layer, while n-octanol represented the top layer. Internal decay heat was modeled in the bottom layer using electric heating rods. After analyzing the main heat transfer parameters from the experiment, this paper derived several useful heat transfer correlations. The normalized temperature and heat flux distributions remained consistent across different power levels, and the normalized heat flux in the bottom layer aligned well with existing experimental correlations. In the bottom layer, the downward heat transfer coefficient was lower compared to other single-layer correlations, likely due to increased upward heat transfer.

Distinct structure, radiative effects, and precipitation characteristics of deep convection systems in the Tibetan Plateau compared to the tropical Indian Ocean

Abstract. Using spaceborne lidar and radar observations, this study identifies deep convection systems (DCSs), including deep convection cores (DCCs) and anvils, over the Tibetan Plateau (TP) and tropical Indian Ocean (TO) and finds that DCSs over the TP are less frequent, exhibiting narrower and thinner DCCs and anvils compared to those over the TO. The thinner DCCs over the TP exert weaker radiative cooling effects at the top of atmosphere (TOA) compared to the TO. But, the shortwave TOA cloud radiative effect (CRE) of TP anvils is stronger than that of the TO possibly due to more densely packed cloud tops over the TP. It results in a stronger TOA CRE of DCSs over the TP than that of TO. In particular, the longwave CRE of DCSs over the TP is notably greater at surface and low-level atmosphere due to the distinct lower temperature and less water vapour. The width of DCSs shows a positive correlation with wind shear and atmospheric instability, and the underlying mechanisms are discussed. We also find that the impact of aerosols on cloud top heights and precipitation displays significant discrepancies between the two regions. It is because that the aerosol invigoration effect is less efficient on the TP DCSs, mainly attributed to the significantly colder cloud base. Due to competition between invigoration and direct/semi-direct radiative effects of aerosols, the correlation between precipitation and aerosols over the TP is not obvious. However, precipitation in the TO experiences invigoration followed by suppression with increasing aerosols, due to the dominance of aerosol radiative effects and enhancement entrainment under polluted conditions.

Differences in Thunderstorms' Ice Microphysics Between the Amazon and Central Africa Inferred From Spaceborne Passive Microwave and Radar Observations

AbstractThis study examines the differences related to microphysical properties of ice in thunderstorms over the Amazon and Congo Basin using the Precipitation Feature (PF) data sets derived from passive microwave and radar observations from the Tropical Rainfall Measuring Mission and Global Precipitation Mission Core Satellites. Analysis reveals that Amazon thunderstorms are likely composed of ice crystals smaller but more numerous than those in the Congo Basin, resulting in half as many flashes per PF on average in the Amazon, for similar Ice Water Content (IWC) or Area of 30 dBZ at −10°C (Acharge). The increase of the flash count following an increase of the IWC (Acharge) is only 72% (61%) as effective in the Amazon as it would be in the Congo Basin area. PFs with similar 30 dBZ radar echo top heights exhibit lower Brightness Temperatures (TBs) in the 85/89, 165, and 183 GHz frequencies over the Amazon, indicating more numerous smaller ice particles compared to those over the Congo Basin, which tend to show colder TBs at 37 GHz, possibly due to more numerous large graupel or hail particles. Comparisons of TBs in PFs with similar 30 dBZ echo top temperature between the Amazon and 3 × 3º global grids show that the median TB in Amazon is higher than that in most oceanic areas but is comparable to areas having high oceanic lightning activity (e.g., South Pacific Convergence Zone). It suggests that systems in the Amazon have similarities with maritime precipitation systems, yet with distinct characteristics indicative of land systems.

Diurnal cycles of rain storms over South China during the presummer rainy season

The variation characteristics of rain storms (RSs) are closely related to complex internal physical processes and external dynamic and thermodynamic conditions. Using a 17-year observational rainfall dataset from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), the diurnal cycles of various RS characteristics and their responses to the South China Sea Summer Monsoon (SCSSM) are investigated in South China (SC) during the presummer rainy season (PSRS). Before SCSSM outbreaks, the RSs in the western inland region of SC (WSC) have stronger precipitation intensities and convective features due to orographic lifting, especially at night, while those in the eastern inland region of SC (ESC) have higher RS occurrence frequencies with higher moisture transport, especially in the afternoon. The onset of the SCSSM leads to abundant moisture and sufficient convective available potential energy over the entire SC area, resulting in significant increases in the occurrence frequency, convective fraction, and precipitation top height of RSs. In the WSC, the weakened upward motion and smaller convective inhibition limit RS development, resulting in weaker rainfall intensity. In the ESC, a particularly unstable atmosphere and enhanced low-level moisture transport in the afternoon lead to a larger three-dimensional size, more active convection, and greater precipitation intensity in the RSs. These results offer fresh insight into the diurnal variation in rainfall during the PSRS and can be effectively used to evaluate numerical model simulations.

Analysis of the Effect of Layer Height on the Interlayer Bond in Self-Compacting Concrete Mix in Slab Elements.

This paper presents a study on the influence of the layered casting technology of self-compacting concrete (SCC) on the load-bearing capacity of interlayer bond in slab elements. The research was conducted on slab elements with dimensions of 750 × 750 × 150 mm, concreted from a single point of concrete delivery. The aim of this study was to analyse the influence of the height of the concreting top layer on the bond strength between the layers. The study utilised top layer heights of 50, 75, and 100 mm, which, according to the authors' experience, are the most common cases when making slab elements. The interlayer bond was determined by investigating the splitting tensile strength of cubic specimens cut from the concrete slabs. Computed tomography (CT) was employed to image the contact zone between the concrete layers. Based on the analysis of the CT imaging and the results of the strength tests, it was shown that the interlayer bond is influenced by both the height of the top layer and its free-spread distance from the casting point. A reduction in the interlayer bond strength was observed with decreasing the height of the top layer and increasing distance from the mixture supply point. The relationships obtained were linear and had a clearly negative slope. It was concluded that the valid recommendations and standards for the multilayer casting of SCC are too general. Therefore, we propose to detail the recommendations to reduce the risk of cold joints, which diminish the bond strength of the interlayer joints.

Combined effects of fine and coarse marine aerosol on vertical raindrop size distribution

Climate models commonly overestimate warm rain frequency and underestimate its intensity over the ocean, primarily due to insufficient representation of the aerosol effects. This pertains to both fine aerosols (FA) and coarse sea spray aerosols (CSA), where the latter is mostly absent in the models. Here, our observations show that adding CSA enhances vertical warm rain structure, in contrast to the effect of FA. The magnitude of the effect of CSA is larger than the opposite effect of the FA. For rain with top heights of 2–3 km, the raindrop size, concentration, and rain rate can be increased by factors of 1.03, 1.47, and 1.60, respectively. These CSA-induced changes are larger for thicker clouds, reaching a maximum by factors of 1.12, 1.85, and 2.21, respectively. Therefore, the combined FA and CSA effects should be incorporated into climate models for accurately simulated precipitation microphysical processes.

Evaluation and Improvement of a CALIPSO-Based Algorithm for Cloud Base Height in China

Clouds are crucial in regulating the Earth’s energy budget. Global cloud top heights have been easily retrieved from satellite measurements, but there are few methods for determining cloud base height (CBH) from satellite measurements. The Cloud Base Altitude Spatial Extrapolator (CBASE) algorithm was proposed to derive the height of the lower-troposphere liquid cloud base by using the Cloud-Aerosol Lidar with Orthogonal polarization cloud aerosol LiDAR (CALIOP) profiles and weather observations at airports from aviation routine and special weather report (METARs and SPECIs, called METAR) observation data in the United States. A modification to the CBASE algorithm over China (CNMETAR-CBASE) is presented in this paper. In this paper, the ability of the CBASE algorithm to calculate CBH in China is evaluated, and METAR observations over China (CNMETAR) were then used to modify the CBASE algorithm. The results including CNMETAR observation data in China can better retrieve CBH over China compared with the results using the original CBASE algorithm, and the accuracy of the global CBH results has been improved. Overestimations of CBH with the original algorithm range from 500 to 800 m in China, which have been reduced to about 300 m with an improved algorithm. The deviations calculated by the algorithm also have a significant reduction, from 480 m (CBASE) to 420 m (CNMETAR-CBASE). In conclusion, the modified CBASE algorithm not only calculates the CBH more accurately in China but also improves the results of the global CBH retrieved from satellites.

Comparing Distributions of Overshooting Convection in HRRR Forecasts to Observations

AbstractOvershooting convection can significantly impact the chemical and radiative properties of the upper troposphere and lower stratosphere through the transport of various chemical species. These impacts include enhancements of water vapor and ozone‐depleting halocarbons, which both have important consequences for climate change. Therefore, accurate prediction of the Earth's climate system requires convective overshooting to be included. To better understand how convective transport is represented in current state‐of‐the‐art models, approximately 75,000 individual updrafts in the central and eastern United States are analyzed from High‐Resolution Rapid Refresh (HRRR) simulations and NEXRAD radar observations during May and July 2021. Distributions of echo top potential temperatures and heights, as well as diurnal cycles of overshooting frequency, are compared to observations. These distributions show mean, median, and maximum echo tops 2–3 km lower than observations, both in absolute and tropopause‐relative space, with evidence of updrafts losing momentum too rapidly above the tropopause. Diurnal cycles show accurate times of maximum and minimum overshooting, but significant errors at model initialization and evidence that some simulated overshoots continue too late into the overnight hours. Despite these deficiencies, distributions of simulated levels of maximum detrainment show decent agreement with observations. All results, including the severe underprediction of echo top heights, persist at shorter forecast lead times. This indicates a need to improve representation of overshooting storms in weather and climate models, even those that are convection‐permitting, or introduce a transport parameterization.

An Improved Remote Sensing Retrieval Method for Elevated Duct in the South China Sea

Elevated duct is an atmospheric structure characterized by abnormal refractive index gradients, which can significantly affect the performance of radar, communication, and other systems by capturing a portion of electromagnetic waves. The South China Sea (SCS) is a high-incidence area for elevated duct, so conducting detection and forecasts of the elevated duct in the SCS holds important scientific significance and practical value. This paper attempts to utilize remote sensing techniques for extracting elevated duct information. Based on GPS sounding data, a lapse rate formula (LRF) model and an empirical formula (EF) model for the estimation of the cloud top height of Stratocumulus were obtained, and then remote sensing retrieval methods of elevated duct were established based on the Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data. The results of these two models were compared with results from the elevated duct remote sensing retrieval model developed by the United States Naval Postgraduate School. It is shown that the probability of elevated duct events was 79.1% when the presence of Stratocumulus identified using GPS sounding data, and the trapping layer bottom height of elevated duct well with the cloud top height of Stratocumulus, with a correlation coefficient of 0.79, a mean absolute error of 289 m, and a root mean square error of 598 m. Among the different retrieval models applied to MODIS satellite data, the LRF model emerged as the optimal remote sensing retrieval method for elevated duct in the SCS, showing a correlation coefficient of 0.51, a mean absolute error of 447 m, and a root mean square error of 658 m between the trapping layer bottom height and the cloud top height. Consequently, the encouraging validation results demonstrate that the LRF model proposed in this paper offers a novel method for diagnosing and calculating elevated ducts information over large-scale marine areas from remote sensing data.

Precipitation and cloud Parameters's characteristics of stratus in summer in Ningxia, eastern of northwest China

Stratus is the main artificial seeding target for weather modification in Ningxia. Meteorological satellites can detect macro and microcosmic physical parameters of large-scale stratus. Researching precipitation and cloud parameter characteristics of stratus can provide scientific and technological support for understanding the development and evolution of stratus to identify seeding conditions and effects. Eight typical stratus precipitation events of the summers of 2016–2021 of Ningxia were selected, using the nine point average method, that matched characteristic cloud parameters retrieved by FY-2G satellite with precipitation classification data of 25 national meteorological observation stations in Ningxia. These stratus precipitation characteristics were correlated with cloud parameters. The results indicate that precipitation decreased rapidly from the southeast to the northwest of Ningxia. In the synoptic background of precipitation, the cloud top height, super-cooled layer thickness, cloud optical thickness, cloud particle effective radius, and cloud liquid water content were all larger than those in the synoptic background of no precipitation. The spatial distribution feature manifests as gradually increased from southeast to northwest. The cloud top temperature and cloud blackbody temperature were smaller than those in the synoptic background of no precipitation. The cloud top temperature was near the cloud “seeding temperature window”, and the depth of the super-cooled layer was thick. This was in line with the “Seeder-Feeder” structure characteristic of cold stratus.

Ejecta splashing and scaling of projectile oblique impact on granular media

Ejecta splashing is accompanied by the formation of impact craters in oblique impact of a sphere onto a granular target. We investigated the morphology and scaling of the ejection, together with the evolution and final size of crater by performing a series of experiments, varying the impact angle θ and impact speed V0. The experiment categorized the crater shapes in the space parameters Fr and θ and revealed that the maximum ejecta height exhibits two regimes related to Froude number, while the crater length, width, and depth are all collapsed to a master line. Then, the evolution characteristics of the corolla dimensions (top diameter, neck size, bottom diameter, and height) are determined. Moreover, a simple ballistic model taking into account the air drag force acting on the ejecta has been proposed to predict the dynamic processes of the corolla in oblique impacts. Furthermore, the opening of the crater formation deduced by the dynamics of the corolla formed and the collapsing process (i.e., the splashed sand avalanching down along the wall of the crater) have been investigated in detail using a simplified Bouchaud–Cates–Ravi–Edwards model. Our theoretical model demonstrated high accuracy in reproducing the evolution of a crater during impacting and in predicting the final crater scaling after avalanching.