Precipitation Type Research Articles

Scanning electron microscopy and atom probe tomography characterization of laser powder bed fusion precipitation strengthening nickel-based superalloy

Atom probe tomography (APT) was utilized to supplement scanning electron microscopy (SEM) characterization of a precipitation strengthening nickel-based superalloy, Alloy 247LC, processed by laser powder bed fusion (L-PBF). It was observed that the material in the as-built condition had a relatively high strength. Using both SEM and APT, it was concluded that the high strength was not attributed to the typical precipitation strengthening effect of γ’. In the absence of γ’ it could be reasonably inferred that the numerous black dots observed in the cells/grains with SEM were dislocations and as such should be contributing significantly to the strengthening. Thus, the current investigation demonstrated that relatively high strengthening can be attained in L-PBF even in the absence of precipitated γ’. Even though γ’ was not precipitated, the APT analysis displayed a nanometer scale partitioning of Cr that could be contributing to the strengthening. After heat-treatment, γ’ was precipitated and it demonstrated the expected high strengthening behavior. Al, Ta and Ti partitioned to γ’. The strong partitioning of Ta in γ’ is indicative that the element, together with Al and Ti, was contributing to the strain-age cracking occurring during heat-treatment. Cr, Mo and Co partitioned to the matrix γ phase. Hf, Ta, Ti and W were found in the carbides corroborating previous reports that they are MC.

Examining moisture contribution for precipitation in response to climate change and anthropogenic factors in Hengduan Mountain Region, China

Climate change and anthropogenic factors have resulted in intense and frequent droughts and floods in the Hengduan Mountain Region (HMR). Exploring the source supply of evaporation and transportation processes for the precipitation in the HMR can help us understand regional precipitation characteristics and provide valuable insights regarding effective water resource management, disaster prevention, and mitigation. Based on the ERA5 reanalysis data, we identified the annual and seasonal precipitationsheds of the HMR, using the Water Accounting Model-2layer, to investigate the potential mechanisms that drive the changes in the precipitation in the HMR, in terms of external moisture contribution and local recycling. The identified precipitationshed in the HMR varied in response to different types of precipitation during the different seasons. The decrease in the annual precipitation was mainly attributed to the reduced moisture supply from the extended southwest (SW) and northwest (NW) regions, portraying a decreasing trend of −2.08 mm/yr/yr and −0.92 mm/yr/yr, respectively. The detected difference in the moisture sources and transport pathways, in terms of the response of wet and dry precipitation years, can improve our understanding of the moisture patterns of wet and dry years. We could conclude that the increase in moisture from the SW regions, due to El Niño, may have triggered the heavy precipitation in the HMR in 1998. Additionally, the reduction in moisture from the SW regions, due to La Niña, may have triggered an extreme drought in the HMR in 2011. Notably, woodland and water surface expansion tend to weaken local recycling (−0.07 %/yr) after 2000. In the future, the decreasing trend of local recycling will likely be intensified owing to large-scale artificial reservoir construction and the surface changes caused by underlying impoundment.

Optimization of Targeted Plant Proteomics Using Liquid Chromatography with Tandem Mass Spectrometry (LC-MS/MS).

This study was conducted to optimize a targeted plant proteomics approach from signature peptide selection and liquid chromatography with tandem mass spectrometry (LC-MS/MS) analytical method development and optimization to sample preparation method optimization. Three typical protein extraction and precipitation methods, including trichloroacetic acid (TCA)/acetone method, phenol method, and TCA/acetone/phenol method, and two digestion methods, including trypsin digestion and LysC/trypsin digestion, were evaluated for selected proteins related to the impact of engineered nanomaterials (ENMs) on wheat (Triticum aestivum) plant growth. In addition, we compared two plant tissue homogenization methods: grinding freeze-dried tissue and fresh tissue into a fine powder using a mortar and pestle aided with liquid nitrogen. Wheat plants were grown under a 16 h photoperiod (light intensity 150 μmol·m-2·s-1) for 4 weeks at 22 °C with a relative humidity of 60% and were watered daily to maintain a 70-90% water content in the soil. Processed samples were analyzed with an optimized LC-MS/MS method. The concentration of selected signature peptides for the wheat proteins of interest indicated that the phenol extraction method using fresh plant tissue, coupled with trypsin digestion, was the best sample preparation method for the targeted proteomics study. Overall, the optimized approach yielded the highest total peptide concentration (68,831 ng/g, 2.4 times the lowest concentration) as well as higher signature peptide concentrations for most peptides (19 out of 28). In addition, three of the signature peptides could only be detected using the optimized approach. This study provides a workflow for optimizing targeted proteomics studies.

Forecasting the Weather and its Visualization using Augmented Reality

-In the recent period, many real-world applications and institutions generates a huge amount of data which is unstructured i.e., in the form of images containing data, receipts, invoices, forms, statements, contracts etc. This rich and detailed information presented in the text is of great significance in computer vision-based applications (driverless cars, assisting blind and visually impaired people, detecting labels and packages, automatic number plate recognition etc.). Recently, there has been a hike in the efforts, This project presents AR Weather, a simulation application, which can simulate three types of precipitation: rain, snow, and hail. We examined a range of weather phenomenon and how they may be simulated in a mobile augmented reality system. AR Weather was developed and deployed on the Tinmith wearable computer system to enable autonomous and free movement for the user. The user can move freely inside the simulated weather without limitation. The result of this work, the AR Weather application, has been evaluated with a user study to determine the user’s acceptance and draw conclusions to the applicability of augmented reality simulated weather Keywords- Mobile augmented reality, environmental sensor networks, mobile visualization

Hails in Ny Alesund, Svalbard-atmospheric vertical structure and dependence on circulation

Hails observed at Ny Alesund, Svalbard in the Arctic during December–February 2018–19 is examined along with the atmospheric circulation patterns. When hail was noticed, surface warming and southwesterly—westerly winds were noticed. Atmospheric circulation pattern was characterised by high pressure anomaly over northwestern Europe. High clouds as well as excess liquid water were present when the high pressure systems were active over northwestern Europe. This is because winds blowing over ocean collect more moisture as well as transport nucleating particles to Svalbard. Also, hourly winds from ERA 5 reanalysis indicated vertical shear required for hail formation. When hails were observed, mixed precipitation types were recorded with the maximum intensities arising from the hails. The West Spitzbergen Current (WSC) induces a strong east west sea surface temperature (SST) gradient in the ocean west of Svalbard. A corresponding gradient in the atmospheric temperature is also maintained by the WSC in the west to east direction in the lower atmosphere. Moisture laden westerlies cross the SST gradient and induce strong frontal activity in the lower atmosphere resulting intense precipitation and hail. The upward vertical velocity noted in the lower troposphere supports the frontal activity. Human activities in the Arctic as elsewhere are bound to increase. Hence, there is a need to study the intense precipitation in the Arctic as well as its reasons as it can impact the Arctic environment and human activity. This calls for more continuous observations to clearly identify mechanisms and frequency of intense precipitation in the Arctic.

Microstructural insights into creep of Ni-based alloy 617 at 700 °C provided by electron microscopy and modelling

In this work, microstructural changes during creep of Ni-based alloy 617 at 700 °C and 165 MPa have been investigated by electron microscopy, and complementarily modelled. Precipitate types, sizes and chemistry were determined by transmission- (TEM) and scanning electron microscopy (SEM). Apart from γ’ particles, MX and carbides, coarse μ-phase was found. Grain size, frequency of twins, deformation patterns and geometrically necessary dislocations were characterized by electron backscatter diffraction (EBSD). Based on measurements and literature data, creep behavior and a time-to-rupture (TTR) diagram of A617 have been numerically simulated at 700 °C in a range of 165 to 215 MPa with a new physical model. Our new creep model achieved excellent agreement with measured data and literature in terms of predicted creep life, times to 1% strain, minimum creep rate and microstructural evolution. We also succeeded in considering the varying ductility of the material in a novel damage law by implementing the reduction of area from fractured creep samples. Diffusion creep (coble creep) is considered in addition to dislocation creep in the model. The impact of diffusion creep is mostly visible at low stresses, leading to significant improvements within the TTR diagram.

A dataset of ecological factors in the distribution area of Tianshan spruce in Yili region in 2014

Tianshan spruce (Picea schrenkiana var. tianschanica ) is an important tree for water conservation, windbreak and sand fixation in the mountains of Xinjiang, and plays an important role in the formation and maintenance of forest ecosystem in Xinjiang. Ecological factors such as temperature, precipitation, soil and topography are important data bases for studying forest ecosystem. Based on multi-source data such as remote sensing image, DEM, meteorological data and soil data in Yili region of Xinjiang, we used multi-scale segmentation, nearest neighbor classification and spatial analysis to generate a dataset of ecological factors in the distribution area of Tianshan spruce in Yili region in 2014, covering six ecological factors, namely temperature, precipitation, sunshine duration, slope, slope direction and soil type. In this dataset, strict procedures of data quality control were carried out by TTA Mask accuracy verification and other methods to ensure the accuracy and reliability of the data. The dataset can provide data support for forest ecosystem health assessment.

Determination of precipitation intensity based on data from dual polarisation radar

The paper presents the results of a preliminary study of cloudiness area with hail precipitationbased on data from a dual-polarisation electromagnetic wave radar operating in Rzeszów-Jasionkawhich is one of eight meteorological radars belonging to the POLRAD managed by the Institute ofMeteorology and Water Management – National Research Institute. Atmospheric dual-polarisationwave scanning provides a significant radar data that accurately describes detected meteorologicalobjects, including the sizes of cloud and precipitation particles. The conducted research enabled usa qualitative and quantitative description of cloudy zones with precipitation of variable intensity andvariable spatial and temporal distribution. Obtaining data on the structure of the cloud cover zonerequires the creation of new and non-standard imagery showing horizontal and vertical distributionsof radar reflectivity determined on the basis of measurements in the classic radar channel. Radar datawere processed using RAINBOW DART and RAPOK software. Completely new rainfall datasetswere generated for the selected region with consistency of location and observation date, in whichprecipitation intensity, phase state, and environmental factors were taken into account. Developedvertical cross-sections of the atmosphere along the set route provided information on the structureand activity of the studied storm cell and the precipitation core present. Precipitation intensity wasdetermined from the Marshall‒Palmer, Joss and Muchnik correlations, which used radar reflectivityat heights of 1 km, 1.5 km, and 2 km above the ground surface, taking into account the freezing level.The paper presents a comprehensive analysis of the hail situation based on synoptic data and imagesof hail intensity and hail probability. It was shown that, available in the meteorological data exchangenetwork, the standard images of precipitation intensity generated in each case based on the Marshall‒Palmer correlation for radar reflectivity at a height of 1 km above the ground surface may containerrors, which require changes in calculation algorithms to be minimised. At this stage of the research,other dependencies were used in the calculations, which took into account the type of precipitation.On the other hand, data on the structure of the studied storm cell allowed us calculations based on thevalues of radar reflectivity determined at different levels in the rain core. The analysis of the obtainedradar precipitation data was carried out on the basis of both syn-optic and climatic data for the studiedregion. In the next stage of research, the results of field meas-urements carried out in regions with anextensive network of direct precipitation measurements will be used. The results of these studies willallow us to recommend empirical relationships for determining precipitation intensity dependingon the type of precipitation, the structure of the precipitation cloud and environmental conditions.Keywords: civil engineering, geodesy and transport, remote sensing of the atmosphere, dual polarisationradar, radar reflectivity, rainfall intensity, hail

Dynamic comparative analysis of different types of precipitation caused by landfalling strong typhoons over South China

Based on multiple datasets, a comparative analysis has investigated the different rainfall distributions and the factors related to strong (weak) rainfall induced by landfalling strong typhoons moving northwest (SR-NWLFSTYs, WR-NWLFSTYs) which are defined from the tracks, the locations, and intensities of the rainfall center of LFSTYs based on a dynamic composite analysis method.The obviously stronger rainfall induced by SR-NWLFSTYs, with the intensive rainfall center presenting a cyclonic rotation in the lifecycle of typhoons, tends to be accompanied by the pronouncedly enhanced low-level jet and a warmer SST before and during landfall. Owing to the enhanced low-level jet, moisture convergence experiences an intensification, resulting in a warmer and more humid circulation. Sufficient water vapor and latent heat is favorable for the enhancement of the mid-troposphere warm core structure with longer maintenance which can prolong the impact period of typhoons, leading to continuous precipitation. Simultaneously, the coupling of low-level convergence and upper-level divergence provides favorable dynamic conditions, thus further promoting the upward transportation of moisture through Ekman pumping, which tends to increase the mid-troposphere moisture through moisture advection. The changes in the mid-troposphere moisture coincide well with the evolution of rainfall over the same region during the lifecycle of typhoons.Comparatively, the asymmetric rainfall features of WR-NWLFSTYs with intense rainfall center mainly placed in the northeast quarter of the TC center during the lifecycle of TCs is likely related to the relatively weaker low-level jet which remains almost constant during and after landfall. The weaker low-level flow transports less moisture into the cyclone, and prohibits the weakening of vertical wind shear after landfall, leading to reduced precipitation with an obvious asymmetric distribution. Concurrently, the configuration of the weakening upper-level divergence and low-level convergence after landfall has been unable to maintain the upward motion for precipitation, resulting in relatively weaker rainfall for WR-NWLFSTYs.

Flood Susceptibility Mapping Using Image-Based 2D-CNN Deep Learning: Overview and Case Study Application Using Multiparametric Spatial Data in Data-Scarce Urban Environments

This study presents results for urban flood susceptibility mapping (FSM) using image-based 2D-convolutional neural networks (2D-CNN). The model input multiparametric spatial data comprised of land-useland-cover (LULC), digital elevation model (DEM), and the topographic and hydrologic conditioning derivatives, precipitation, and soil types. The implemented dropout regularization 2D-CNN with ReLU activation function, categorical cross-entropy loss function, and AdaGrad optimizer produced the case study area FSM with overall accuracy (OA) of 82.5%. The image-based 2D-CNN outperformed the multilayer perceptron (MLP) neural network by 18.4% in terms of overall accuracy and with corresponding lower MAE and higher F1-measures of 10.9% and 0.989, as compared to 25.6% and 0.877, respectively, for MLP-ANN results. The accuracy of the 2D-CNN that produced FSM map and the model efficiency were evaluated using area under the ROC curve (AUC) with respective success and prediction rates of 0.827 and 0.809. Using image-based 2D-CNN, 27% of the 247.7 km2 of the studied area was mapped with a high risk of flooding, with MLP-ANN overestimating the degree of high flood risk by 4.7%. Based on the gain ratio index analysis of the flood conditioning factors (FCFs), the most significant FCFs were LULC (18.5%), precipitation (14.9%), proximity to river (13.3%), and elevation (12.4%). Soil types contributed 8.6%, slope 9.1%, and the DEM-derived hodological conditioning indicators contributed 23.2%. The study results demonstrate that in urban areas with scarce hydrological monitoring networks, the use of image-based 2D-CNN with multiparametric spatial data can produce high-quality flood susceptibility maps for flood management in urban environments.

Evaluation of different parameters affecting the performance of asphaltene controlling chemical additives in crude oils using multiple experimental approaches assisted with image processing technique

Asphaltene deposition problem in oil field is a major flow assurance problem which is affecting petroleum industry for decades. This issue not only affects sustainable production of crude oil but poses severe impacts to the integrity of production system. There are several methods available for the treatment of asphaltene problem. Among different treatment methods, chemical treatment is the most effective, reliable and flexible method. However, before implementation of this method in field conditions, this technique requires rigorous evaluation of chemical additives in lab environment for final selection of most efficient chemical additive. In this research work, we have applied simultaneous multiple experimented approaches namely; Asphaltene dispersant test and spot test to evaluate chemical additive tendency to reduce asphaltene deposition and enhance asphaltene precipitates dispersion respectively. To improve the interpretation and eliminate uncertainties associated with spot test results, the spot test results were analyzed by image processing tool and precipitation intensities were calculated. Generally, precipitation intensity represents the dispersion ability of chemical additive which in turn is inversely proportional to the deposition. Moreover, the impact of parameters like precipitant type (Molecular Weight of precipitant), volume percentage of precipitant in crude oil, chemical additive dosage and experimental time on precipitation intensities were determined using statistical metric namely relevancy factor. In this study, two precipitants namely; n-pentane and n-heptane were used in two different volume percentages i.e. 75 vol percent and 95 vol percent in three crude oil samples namely; crude oil 1 (CO1), crude oil 2 (CO2) and crude oil 3 (CO3). The final results concluded that chemical additive performance was poor in crude oil 1 as it unable to prevent deposition in most of the conditions. The chemical additive performs equally well for CO2 and CO3 having slightly better results obtained in CO2. Among all studied input parameters, precipitant to crude oil ratio was the most important parameter impacting the performance of chemical additive adversely. The performance of chemical additive was largely negatively affected when precipitant used in crude oil at higher proportion. Secondly, the effect of Molecular weight of precipitant found in strong positive relationship with precipitation intensity the case of CO1 while negligibly negative in case of CO2 and CO3. Precipitation intensities were found to decrease with increasing experimental time and chemical dosage in CO1. However, the positive trend was found in CO2 and CO3 between precipitation intensity with time and chemical dosage. These suggests that chemical additive depend upon the type of crude oil and the underlying operating conditions and cannot be applied for the equal and effective treatment of asphaltene precipitation problem in various crude oils.

Long-term trends and drivers of biological invasion in Central European streams

Rates of biological invasion continue to accelerate and threaten the structure and function of ecosystems worldwide. High habitat connectivity, multiple pathways, and inadequate monitoring have rendered aquatic ecosystems vulnerable to species introductions. Past riverine invasion dynamics were largely restricted to large rivers, leaving out smaller rivers that commonly harbour high freshwater biodiversity. Moreover, biodiversity time series have rarely been used to investigate invasions across larger spatial-temporal scales, limiting our understanding of aquatic invasion dynamics. Here, we used 6067 benthic invertebrate samples from streams and small rivers from the EU Water Framework Directive monitoring program collected across Central Europe between 2000 and 2018 to assess temporal changes to benthic invertebrate communities as well as non-native species. We assessed invasion rates according to temperature, precipitation, elevation, latitude, longitude, and stream type. Overall, average daily temperatures significantly increased by 0.02 °C per annum (0.34 °C in total) while annual precipitation significantly decreased by 0.01 mm per annum (−67.8 mm over the study period), paralleled with significant increases in overall species richness (12.3 %) and abundance (14.9 %); water quality was relatively stable. Non-native species richness increased 5-fold and abundance 40-fold, indicating an ongoing community shift from native to non-native species. The observed increase in invasions was stronger in low mountain rivers compared to low mountain streams, with the share of non-native species abundance and richness declining with increasing elevation and latitude but increasing with temperature. We found thermophilic non-native species invasion success was greatest in larger sized streams, at lower latitudes, lower elevations and higher temperatures. These results indicate that widespread environmental characteristics (i.e., temperature) could heighten invasion success and confer refuge effects (i.e., elevation and latitude) in higher sites. High altitude and latitude environments should be prioritised for prevention efforts, while biosecurity and management should be improved in lowland areas subject to greater anthropogenic pressure, where non-native introductions are more likely.

Sources and Risk Characteristics of Heavy Metals in Plateau Soils Predicted by Geo-Detectors

The ecological environment of the remote plateaus has been a challenge plaguing many countries due to global warming, increased human activities, and frequent occurrence of various heavy metal (HM) pollutants. This paper analyzes the primary factors and potential susceptible regions’ characteristics related to soil HMs (As, Cd, Pb, Cr, Ni, and Zn) in the southern Tibet Plateau (TP) using Geo-detectors and a set of multi-source data from remote sensing and geographic and geological information. The geoaccumulation index showed that the As pollution was the most serious. The precipitation, pH, geological age (GA), and rock type (RT) were the most critical factors affecting HMs. Additionally, soil HMs were relatively unaffected by land use and clay. Based on the risk detector, the most key impact types (range) of the predominant factors of HM’s sources were identified. For example, precipitation (100–200 mm), pH (7–7.5), DEM (>5500 m), RT (ophiolite), and GA (Ordovician) had the highest average concentration of As in each type (ranges) of the predominant factors. This work provides new data on the extent of soil HM contamination in the southern TP and predicts vulnerable areas of HM contamination, providing an important scientific basis for monitoring and managing HM in remote areas at high altitudes.

Study on the Deposition Reduction Effect of the Sediment–Sluice Tunnel in Zengwen Reservoir

Reservoirs are a crucial part of the human water supply system. The effectiveness and service life of a reservoir is decided mainly by its storage capacity, and as such, preventing reservoir capacity loss is of high interest worldwide. Due to climate change in recent years, precipitation types have changed, and heavy rainfall events have become more severe and frequent. Rainfall causes soil erosion in slope lands and transports large amounts of sediment downstream, forming deposition. This causes reservoir storage capacity to fall rapidly and decreases reservoir service life. The Sediment–Sluice Tunnel can reduce rapid deposition in reservoirs and is, thus, widely employed. By simulating sediment transportation in reservoirs, deposition reduction after building the Sediment–Sluice Tunnel can be evaluated. This study used the Physiographic Soil Erosion–Deposition (PSED) model to simulate the flow discharge and suspended sediment discharge flowing into the Zengwen reservoir then used the depth-averaged two-dimensional bed evolution model to simulate the sediment transportation and deposition in a hydrological process. Simulation results showed that the Sediment–Sluice Tunnel effectively reduced deposition and transported sediment closer to the spillway and Sediment–Sluice Tunnel gate. The deposition distribution with the Sediment–Sluice Tunnel built is more beneficial to the deployment of other dredging works.

Genetic design of new aluminum alloys to overcome strength-ductility trade-off dilemma

In this study, machine learning and inverse design based on a genetic algorithm was used to design three aluminum wrough alloy types to overcome the strength-ductility trade-off. The composition of the new alloys was advantageous in relation to that of commercial alloys, and this was experimentally validated using samples produced by a semi-mass-production-scale process. The relationship between microstructures and mechanical properties was exploited to characterize the alloys, and each alloy exhibited different precipitation types. The major precipitate of alloy 1 was the spheroidal α-AlMnSi phase, which contributed to the Orowan mechanism. In contrast, the major precipitate of alloys 2 and 3 was the fine needle-type θ-series phase, which contributed to the dislocation shearing mechanism. The new alloys showed outstanding tensile strength (431.69, 527.03, and 527.79 MPa) without a decrease in ductility. These findings suggest that machine learning and inverse design methods are suitable for discovering new aluminum alloy types.

How much organic carbon have UK lakes stored in the Holocene? A preliminary estimate

Temperate lake sediments store a substantial amount of organic carbon (OC) over millennia. Despite the importance of quantifying terrestrial carbon budgets for Nature-based Solutions, the long-term accumulation of OC in European temperate lakes is poorly constrained. In this study, we analyzed 30 lake sediment records to generate a preliminary first-order estimate of Holocene OC accumulation rate (OCAR) and OC storage in UK lakes. We also examined the environmental variables that influence OCAR and produced synthesized Holocene records of %OC and z-scores of log-transformed OCAR and sediment accumulation rate (SAR) at 500-year resolution. Based on our estimation, we report an average Holocene OCAR of 7.4 ± 5.5 g C m−2 yr−1 and a Holocene total OC storage of 0.24 ± 0.18 Pg C in UK lakes. Apart from latitude, no relationship was found between the average Holocene OCAR and the various environmental variables (i.e. temperature, precipitation, surface area, catchment area, depth, altitude, and geology type). During the Holocene, OCAR closely resembles variations in SAR, whereas the increase in %OC is likely explained by the warming climate. Early Holocene variations in OCAR were primarily climate-driven. In contrast, the anthropogenic impact on the landscape exerted a predominant influence on OC burial during the middle-late Holocene. Our results improve the current understanding of terrestrial carbon budgets in the UK and demonstrate the under-appreciated importance of lakes as long-term OC stores.

A study on the forecast model of winter precipitation type in Liaocheng based on physical parameters

AbstractIn this study, 46 physical parameters are first calculated by using the hourly ground observational data of Liaocheng Airport station and the daily sounding data of Xingtai station and Zhangqiu station in the winters of 2016–2020. After the significance test of the correlation coefficients between the physical parameters and the precipitation types, six physical parameters that could be used in the operational weather forecast at Zhangqiu station and Xingtai station are selected by the methods of box‐plot and skill score based on the distribution characteristics of physical parameters under different precipitation types. Moreover, the judgment criteria for the winter precipitation forecast in Liaocheng are obtained by analyzing the indication effect and thresholds of each physical parameter in different precipitation types. In addition, a forecast model of winter precipitation type in Liaocheng is established by using the extended membership function transformation method with the sounding data from the nearest upstream and downstream stations. The verification with observations shows that the forecast accuracy is above 85% and the model performs quite well. We hope this study can provide a good reference for related operational forecasts in the areas without local sounding data or numerical forecast product receiving.

Characteristics of Raindrop Size Distributions in the Southwest Mountain Areas of China According to Seasonal Variation and Rain Types

The precipitation and raindrop size distribution (RSD) characteristics of the four seasons and different rain types were studied using a PARSIVEL2 raindrop disdrometer set in the southwest mountain areas of China from 2019 to 2021. The seasonal precipitation in the southwest mountain areas was mainly stratiform rain. The peaks of the RSD were about 1–2 orders of magnitude higher than those in the plains. The convective rain in spring and autumn was very close to the ocean-like convective mass. The local shape–slope (μ–Λ), radar reflectivity–rain rate (Z–R), and kinetic energy–rain rate (KE–R) relationships were further derived, and the diversity of these relationships was mainly due to the variability of the RSDs. In addition, the differences in the RSD characteristics between the top and the foot of the mountain during a typical precipitation process in the summer of 2020 were further compared. It was found that the number density of the small particles at the top of the mountain was higher than that at the foot of the mountain due to the broken large raindrops caused by the high wind speed, while the high evaporation rate, strong convective available potential energy (CPAE), and water vapor content at the foot of the mountain could strengthen the RSD, making the number density of the large raindrops at the foot of the mountain higher than that at the top.

Comprehensive Analysis of Typhoon Nangka Based on the Satellite Data from the GPM, CloudSat and Himawari-8

A typhoon or hurricane is one of the most destructive high-impact weather events. In this study, the genesis and development processes of Typhoon Nangka (2015), which occurred over the Western Pacific in 2015, were investigated based on the comprehensive observation data from three satellites, i.e., the Himawari-8 satellite, the CloudSat satellite and the Global Precipitation Measurement mission satellite (GPM), focusing on the characteristics of typhoon structure, precipitation and cloud. The results (Results) show that during the developing stage of Typhoon Nangka, the cloud system was relatively complex and changed significantly, with large raindrops dominating the precipitation around the eyewall in the first quadrant, and the convection in the eyewall and outer rainband burst upward to 17 km. In addition, three features were obvious: stratiform precipitation was dominant in the inner rainband, both the precipitation type (stratiform or convective) and intensity were distributed unevenly in the outer rainband, and large water content was located in the warm layer of clouds. Moreover, the collision growth and breakup of water droplets tended to be stable. The precipitation in the typhoon eyewall, inner rainband and outer rainband was significantly different; stratiform precipitation mainly occurred in the inner rainband, while convective precipitation mainly appeared in the eyewall and outer rainband. The cloud system was distributed asymmetrically, and the upper-layer and lower-layer clouds were closely related, dominated by single-layer clouds. There were deep convective clouds in the eyewall, and cirrus clouds with the broadest range across the eyewall. The coverage range of cirrus clouds was close to the radius of the typhoon. There were stratocumulus, altostratus and cumulus in the low levels.

Моніторинг погодних умов осінньо-зимового періоду та їх вплив на морозостійкість рослин ожини звичайної (Rubus fruticosus L.)

Goal. To determine the resistance of blackberry varieties to low temperatures in field and laboratory conditions; to select the most resistant varieties and to investigate the influence of weather conditions on the state of their overwintering. Methods. Laboratory, field, analytical. Results. Weather conditions were monitored in the autumn–winter period of 2019/20 and 2020/21. It was established that the winter months of these years differ significantly in terms of temperature, amount, and type of precipitation. It was noted that the Cacanska Bestrna variety (12.2 points) was characterized by the highest level of frost resistance in field conditions. The average level of frost resistance was fixed for Heaven Can Wait (17.0 points), Loch Tay (14.5 points), and Triple Crown (19.2 points) varieties. The results of the experiment on freezing under artificial conditions showed that the bud and part of the stem on the section through the bud were the most vulnerable to low temperatures, and the middle part of the shoot was the least vulnerable. The buds of the Triple Crown and Loch Tay varieties experienced the least freezing during artificial freezing to–25°C, which indicated their potential frost resistance and more stable fruiting. Conclusions. Coming from the weather conditions in the winter, the period of 2020/21 was a good period for conducting field research on the frost resistance of blackberry varieties, which was characterized by significant temperature changes (minimum temperature in January –20°C, February — –18°C) and sharp thaws (up to +4.5°C). It was determined that the weather conditions of the winter of 2019/20 did not negatively affect the plants in field conditions. However, we assume that the autumn weather conditions of 2019 contributed to a longer period of growth of shoots, which caused a decrease in the resistance of plants to low temperatures. The potential level of frost resistance of the researched varieties under laboratory conditions of freezing to temperatures of–25 and–30°C was established.