Reflectivity Factor Research Articles

An advanced dorsiventral leaf radiative transfer model for simulating multi-angular and spectral reflection: Considering asymmetry of leaf internal and surface structure

Understanding the optical properties of dorsiventral leaves and quantifying leaf biochemical traits through physical models are important for interpreting canopy radiative transfer and monitoring plant growth. Previous models, such as the dorsiventral leaf model (DLM), have effectively accounted for the inner asymmetry of the leaf but neglected the asymmetry of surface structures between the upper and lower epidermis. In this study, we found marked differences in bidirectional reflectance factors (BRF) between the adaxial and abaxial surfaces of leaves under multi-angular measurements due to surface structural distinctions. To address this asymmetry in both internal and surface leaf structures, we subsequently proposed an advanced DLM model (MADLM) for simulating both multi-angular and spectral BRF of two leaf sides, linking the angular reflection of leaf adaxial and abaxial sides to surface structural parameters (roughness and refractive index) based on microfacet theory. Results show that MADLM accurately simulates multi-angular and spectral BRF for both sides of dorsiventral leaves, and yields satisfactory retrieval accuracy of leaf traits from all observation geometries. For close-range hyperspectral imaging applications, we further introduced a simplified version, sMADLM, which characterizes the surface reflection of two leaf sides in terms of the product of a leaf-side dependent parameter and the wavelength-dependent Fresnel factor. The sMADLM improves the mapping accuracy of leaf biochemical traits by effectively reducing the surface reflection effects in dorsiventral leaves. The MADLM and sMADLM deepen our understanding of the optical properties of dorsiventral leaves and provide practical methods for retrieving leaf biochemical traits via optical remote sensing.

Microphysical Characteristics of Precipitation for Four Types of Typical Weather Systems on Hainan Island

The microphysical characteristics of precipitation and their differences among four typical weather systems over Hainan Island were investigated via multi-source observations from 2019 to 2023. We find that the cold fronts (CFs) have the greatest concentration of small raindrops, with a more substantial raindrop condensation process. The subtropical highs (SHs), with primarily deep convection and more prominent evaporation at low levels, lead to greater medium-to-large raindrops (diameters > 1 mm). Tropical cyclones (TCs) are characterized mainly by raindrop condensation and breakup, resulting in high concentrations of small raindrops and low concentrations of large raindrops. The trough of low pressures (TLPs) produces the lowest concentration of small raindrops because of evaporation processes. The convective clusters of the SHs are between maritime-like and continental-like convective clusters, and those of the other three types of weather systems are closer to maritime-like convective clusters. The relationships between the shape parameter (μ) and the slope parameter (Λ), as well as between the reflectivity factors (Z) and the rain rates (R), were established for the four weather systems. These results could improve the accuracy of radar quantitative precipitation estimation and the microphysical parameterizations of numerical models for Hainan Island.

Strain effect on the physical properties of novel Mg3NI3 perovskite material: First principle DFT analysis

Inorganic perovskite-based substances have become a major attraction to solar technology. Inorganic cubic Mg3NI3 perovskites have generated a heap of fascination owing to their distinctive optical, electrical, and structural features. The photovoltaic and optoelectronic industries prioritize lead-free, atomically tailored metal halide perovskites due to the need to address lead (Pb) toxicity and instability. This study assessed the optical, structural, and electrical parameters of Pb-free inorganic halide perovskites Mg3NI3 as a function of biaxial compressive and tensile strain, leveraging first-principles density-functional theory (FP-DFT). Refractive index, absorption coefficient, reflectivity, dielectric function, and tolerance factor are a few additional optical parameters that are computed and processed. The bandgap of the planar Mg3NI3 molecule is 0.412 eV (PBE) when SOC is not applied. The bandgap reduces to 0.363 eV (PBE) at its Γ(gamma) and R-point when the subjective SOC effect is taken into consideration. This compound's bandgap will narrow under tensile strain and expand under compressive strain, depending on whether the SOC effect is applied or not. Several elastic factors are anticipated, including the bulk modulus, Pugh's ratio, elastic constants, anisotropic factors, and Poisson's ratio. Electronic property calculations using band mechanism and density of states (DOS) suggest that Mg3NI3 have a bandgap that is indirect and semiconductive. The elastic properties of this material were found to be mechanically stable, anisotropic, and ductile. In the photon energy range suitable for solar cells, the spikes in the dielectric constant of Mg3NI3 are seen. Our findings point to the prospect of Mg3NI3 as a non-toxic, high-performance, low-cost material for implementation in solar cells and different semiconductor devices.

Silicon rich nitride: a platform for controllable structural colors

Abstract High refractive index dielectric materials like silicon rich nitride (SRN) are critical for constructing advanced dielectric metasurfaces but are limited by transparency and complementary metal oxide semiconductor (CMOS) process compatibility. SRN’s refractive index can be adjusted by varying the silicon to nitride ratio, although this increases absorption, particularly in the blue spectrum. Dielectric metasurfaces, which utilize the material’s high dielectric constant and nano-resonator geometry, experience loss amplification due to resonance, affecting light reflection, light transmission, and quality factor. This study explores the impact of varying the silicon ratio on structural color applications in metasurfaces, using metrics such as gamut coverage, saturation, and reflection amplitude. We found that a higher SRN ratio enhances these metrics, making it ideal for producing vivid structural colors. Our results show that SRN can produce a color spectrum covering up to 166 % of the sRGB space and a resolution of 38,000 dots per inch. Fabricated samples vividly displayed a parrot, a flower, and a rainbow, illustrating SRN’s potential for high-resolution applications. We also show that SRN can provide a better CIE diagram coverage than other popular metasurfaces materials. These findings highlight the advantages of SRN for photonic devices, suggesting pathways for further material and application development.

Detection of Serratia marcescens and Mierococcus lysodeikticus Bacterial Cells Using Cerium Oxide/Transition Metal Dichalcogenides Heterostructure‐Based Surface Plasmon Resonance Sensor

This article explores a novel surface plasmon resonance sensor for detecting the Serratia marcescens and Mierococcus lysodeikticus bacteria cells employing the cerium oxide (CeO2) and transition metal dichalcogenides heterostructure. The proposed sensor is designed based on the Kretschmann configuration, where silver (Ag) is deposited over a prism's surface to excite the surface plasmons. The transfer matrix method and angular interrogation technique are exploited for analyzing the sensor's performance at a wavelength of 633 nm. Firstly, the optimization of the prism and metal film is analyzed by selecting the minimum reflectance, better sensitivity, and quality factor. Secondly, the influence of the proposed structure in the sensor is executed by the performances of different structures, which are made with defined layers. Thirdly, different sensing parameters are analyzed for the considered bacterial cells, resulting in the maximum attained parameters being a sensitivity of 369.40° RIU−1, QF of 151.35 RIU−1, and detection accuracy of 7.57. Finally, the comparative study also shows the noteworthy enhancement using the proposed sensor compared with existing work. Therefore, the proposed sensor can be used as a carrier for detecting the bacterial cells and establishing a new platform for biomolecular and biomedical applications.

The Moderating Effect of Gender Role in Relationship Between Emotional Divorce and Marital Satisfaction: Comparison of Partial Least Square (PLS) and Consistent Partial Least Square Methods (PlSc) Methods.

Emotional divorce refers to a state of emotional disengagement from one's spouse, which can lead to marital dissatisfaction. Gender role conflict is a predictor of marital dissatisfaction and ultimately, divorce. The literature suggests that rigid adherence to traditional gender roles may contribute to emotional divorce. In this article, the authors aim to investigate the moderating effect of gender roles in the relationship between emotional divorce and marital satisfaction by using two multivariate methods in statistical analysis. This cross-sectional study was conducted on 539 women aged 18-65 years. The standard questionnaires used include 1) Bem Sex Role Inventory (Short form), 2) Gutman's Emotional Divorce Questionnaire, and 3) Evaluation and Nurturing Relationship Issues, Communication and Happiness (ENRICH) Marital Satisfaction (EMS) Scale. To achieve the purpose of the study, PLS and PLSc methods have been used. The mean age and time of marriage were 33.88 ± 6.6 and 13.03 ± 7.29 years. There is a significant negative relationship between emotional divorce and marital satisfaction. The gender role of most participants in the study has been androgenic and feminine, which has increased the moderating effect of this relationship. Also, when there is a common (reflective) factor model, Consistent Partial Least Square is more likely to provide a better fit than Partial Least Square. The results showed that higher women's marital satisfaction would be associated with lower emotional divorce. On the other hand, the role of gender is a mediating factor in marital satisfaction and emotional divorce. Having good male and female characteristics can have a positive impact on marital satisfaction, so increasing couples' knowledge of gender roles and trying to reduce traditional extreme roles can help increase marital satisfaction and reduce emotional divorce.

The Characteristics of Precipitation with and without Bright Band in Summer Tibetan Plateau and Central-Eastern China

The bright band (BB) is an important symbol of the ice–water transition zone in stratiform precipitation, and the presence or absence of BB will lead to different microphysical processes. In this paper, the characteristics of BB and precipitation characteristics with and without BB in summer at Tibetan Plateau (TP) as well as Central-eastern China (CEC) are analyzed by using Global Precipitation Measurement (GPM) and the fifth generation ECMWF atmospheric reanalysis of the global climates (ERA5) datasets. The results show the freezing level height and BB height in TP are 0.5 km higher than those in CEC. With the increase in rain rate, the BB height decreases in TP but increases in CEC. The BB width becomes wider with the increase in maximum radar reflectivity. Secondly, the maximum reflectivity factor and particle diameter of stratiform precipitation with BB appear at 5 km, while the maximum reflectivity factor of stratiform precipitation without BB and convective precipitation appear near the ground. The particle diameter first decreases and then increases from the cloud top to the ground. Thirdly, the land surface temperature of convective precipitation is about 2.5 °C higher than stratiform precipitation with BB, indicating higher land surface temperatures are more likely to trigger convection. Lastly, BB can lead to a decrease in brightness temperature and an increase in polarized difference at 89 GHZ and 166 GHZ in CEC, likely due to the increasing ice particles in stratiform precipitation with BB.

Inference of the acoustic properties of transversely isotropic porous materials

Transversely isotropic porous materials are well represented by equivalent fluid models based on semi-phenomenological models such as the Johnson-Champoux-Allard-Lafarge (JCAL) model and a set of material parameters. Direct measurements of these parameters, however, are often difficult or time consuming. As an alternative, inverse estimation methods provide a simple and fast framework to identify the JCAL model parameters, since they can be performed on single impedance tube measurements. In this work, we present a stochastic inverse identification method of the JCAL parameters for transversely isotropic materials. We consider the flow resistance and characteristic viscous length and the static tortuosity to be anisotropic and the frame to be fully rigid, resulting in nine unique parameters to be identified. The method is based on reflection factor measurements of a material in different orientations corresponding the transverse and isotropic principal axes. Hence, a priori knowledge of the orientation of the principal axes of the material is required. Results of the parameter inference are presented based on experimental data for a glass wool sample.

Investigation of soil resistivity impacts on the electrodes of grounding system subjected to lightning strikes

AbstractIn this paper, the study of the homogeneous resistivity and two‐layer soil influences on the performance of the electrodes of grounding systems subjected to lightning strikes is carried out considering soil ionization. The study is done on the behaviour of the ground electrodes while the resistivity of the soil is altered from small to high value in the case of homogeneous soil, while the study is obtained on two‐layer soils in the case of diverse values of the reflection factor. In the suggested algorithm for two‐layer soils, each layer has its resistivity and dielectric constant, where the dielectric constant and soil resistivity depend on the lightning frequency. The field resulting from lightning strikes, which causes soil ionization, has been studied, and the results have been used to understand the behaviour of ground rods under the influence of lightning strikes. The credibility of the results has been strengthened by comparing it with what others have obtained recently. The article's novelty can be summarized in the investigation of the performance of the electrodes of grounding grids that are installed in high soil resistivity of uniform and two‐layer soils containing the impacts of soil ionization, lightning frequency, soil resistivity, and permittivity variations.

Queering Critical Consciousness: Measurement and Implications of Critical Consciousness Among Sexual and Gender Minority Youth

We consider critical consciousness among sexual and gender minority (SGM) youth. Factor analytic and measurement invariance analyses were conducted across straight Black and Latinx youth (N = 254), SGM Black and Latinx youth (N = 111), and SGM white youth (N = 458). Factors of critical reflection and political efficacy emerged in all groups. Configural and partial metric invariance, but not scalar or residual invariance, were established. Correlations between political efficacy and wellbeing and grades replicated across groups. Critical reflection was associated with grades only for white youth, while critical action was associated with grades only for non-white youth. Implications for measurement and generalizable application of CC with an intersectional lens are discussed.

Spectro-environmental factors integrated ensemble learning for urban river network water quality remote sensing

Remote sensing water quality monitoring technology can effectively supplement the shortcomings of traditional water quality monitoring methods in spatiotemporal dynamic monitoring capabilities. At present, although the spectral feature-based remote sensing water quality inversion models have achieved many successes, there could still be a problem of insufficient generalization ability in monitoring the water quality of complex river networks in large cities. In this paper, we propose a spectro-environmental factors integrated ensemble learning model for urban river network water quality inversion. We analyzed the correlation between water quality parameters, spectral reflectance, and environmental factors based on an in-situ dataset collected in the northern part of Shanghai. Using the Hot Spot Analysis (Getis-Ord Gi*), we found that river network water quality parameters have different patterns in different urban functional zones. Furthermore, daily average temperature, total rainfall within the seven days, and several band combinations were also selected as the environmental and spectral features using factor analysis and Pearson correlation coefficient analysis. After the feature analysis, the spectro-environmental factors integrated ensemble learning model was trained. Compared with the spectral-based machine learning inversion models, the coefficients of determination R2 increased by about 0.50. Our model was also tested in three different test areas within and outside the in-situ sampling areas in Shanghai based on low-altitude multispectral remote sensing images. The R2 results for total phosphorus (TP), ammonia nitrogen (NH3-N), and chemical oxygen demand (COD) within the in-situ sampling areas were 0.52, 0.58, and 0.56 respectively. The mean absolute percentage error (MAPE) results were 53.36%, 63.95%, and 22.46% respectively. After adding the area outside the in-situ sampling areas, the R2 results for TP, NH3-N, and COD were 0.47, 0.47, and 0.53. The MAPE were 49.38%, 74.46%, and 20.49%. Our research provided a new remote sensing water quality inversion method to be utilized in complex urban river networks which exhibited solid accuracy and generalization ability.

Bitemporal Radiative Transfer Modeling Using Bitemporal 3D-Explicit Forest Reconstruction from Terrestrial Laser Scanning

Radiative transfer models (RTMs) are often used to retrieve biophysical parameters from earth observation data. RTMs with multi-temporal and realistic forest representations enable radiative transfer (RT) modeling for real-world dynamic processes. To achieve more realistic RT modeling for dynamic forest processes, this study presents the 3D-explicit reconstruction of a typical temperate deciduous forest in 2015 and 2022. We demonstrate for the first time the potential use of bitemporal 3D-explicit RT modeling from terrestrial laser scanning on the forward modeling and quantitative interpretation of: (1) remote sensing (RS) observations of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and canopy light extinction, and (2) the impact of canopy gap dynamics on light availability of explicit locations. Results showed that, compared to the 2015 scene, the hemispherical-directional reflectance factor (HDRF) of the 2022 forest scene relatively decreased by 3.8% and the leaf FAPAR relatively increased by 5.4%. At explicit locations where canopy gaps significantly changed between the 2015 scene and the 2022 scene, only under diffuse light did the branch damage and closing gap significantly impact ground light availability. This study provides the first bitemporal RT comparison based on the 3D RT modeling, which uses one of the most realistic bitemporal forest scenes as the structural input. This bitemporal 3D-explicit forest RT modeling allows spatially explicit modeling over time under fully controlled experimental conditions in one of the most realistic virtual environments, thus delivering a powerful tool for studying canopy light regimes as impacted by dynamics in forest structure and developing RS inversion schemes on forest structural changes.

Early Mission Calibration Performance of NOAA-21 VIIRS Reflective Solar Bands

The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key instruments on the recently launched NOAA-21 (previously known as JPSS-2) satellite. The VIIRS, like its predecessors on the SNPP and NOAA-20 satellites, provides daily global coverage in 22 spectral bands from 412 nm to 12 μm. The geometrically and radiometrically calibrated observations are the basis for many operational applications and scientific research studies. A total of 14 of the 22 bands are reflective solar bands (RSBs), covering photon wavelengths from 412 nm to 2.25 μm. The RSBs were radiometrically calibrated prelaunch and have been regularly calibrated on orbit through the onboard solar diffuser (SD) and scheduled lunar observations. The on-orbit SD’s reflectance change is determined by the onboard solar diffuser stability monitor (SDSM). We review the calibration algorithms and present the early mission performance of the NASA N21 VIIRS RSBs. Using the calibration data collected at both the yaw maneuver and regular times, we derive the screen transmittance functions. The visible and near-infrared bands’ radiometric gains have been stable, nearly independent of time, and so were the radiometric gains of the shortwave-infrared bands after the second mid-mission outgassing. Further, we assess the Earth-view striping observed in the immediate prior collection (Collection 2.0) and apply a previously developed algorithm to mitigate the striping. The N21 VIIRS RSB detector signal-to-noise ratios are all above the design values with large margins. Finally, the uncertainties of the retrieved Earth-view top-of-the-atmosphere spectral reflectance factors at the respective typical spectral radiance levels are estimated to be less than 1.5% for all the RSBs, except band M11 whose reflectance factor uncertainty is 2.2%.

Raindrop Size Distribution Characteristics of the Precipitation Process of 2216 Typhoon “Noru” in the Xisha Region

This study focuses on the comparative analysis and research of the raindrop size distribution (DSD) in the outer rainband and inner rainband of Typhoon “Noru” in 2022, using the OTT-Parsivel raindrop spectrometer deployed on Yongxing Island, Sansha City. The results indicate that precipitation intensity is lower when composed mainly of small and medium raindrops and increases with the presence of larger raindrops. Stronger precipitation is associated with a higher number of large raindrops. Due to the interaction of cold and warm air masses, the raindrop concentration is higher, and the raindrop diameters are larger compared to Typhoons “LEKIMA” and “RUMBIA”. The entire process predominantly consists of numerous small- to medium-sized raindrops, characteristic of a tropical typhoon. The precipitation in the inner and outer rainbands exhibits consistent types, characterized by a unimodal raindrop size distribution with a narrow spectral width, typical of stratiform-mixed cloud precipitation, where stratiform precipitation constitutes a significant portion. Strong echo reflectivity factors are often associated with higher raindrop number concentrations and larger particle sizes. The Z-R relationship of the precipitation shows a smaller coefficient but a consistent exponent compared to the standard. The calculated shape parameter slope relationship is Λ=0.02μ2+0.696μ+1.539, providing a reference for localizing the Z-R relationship in the South China Sea.

Automatic Identification of Three-Body Scatter Spike Based on Jensen–Shannon Divergence and Support Vector Machine

Abstract The three-body scatter spike (TBSS), an echo artifact in radar imagery, manifests as a weak, linear echo extending radially from a core of high reflectivity. Adequately, though not indispensably, indicating the presence of large hail in convective storms, the automatic identification of the TBSS proves advantageous in significantly improving the effectiveness of hailstorm detection. This study introduces an algorithm that synergizes Jensen–Shannon divergence (JSD) and support vector machine (SVM) for rapid TBSS detection in two decades’ worth of single-polarization radar data across China. The algorithm, tested on data from 50 S-band China Next Generation Weather Radar (CINRAD) in central and eastern China, utilized reflectivity factor images for sample extraction. An application in Chenzhou, China, demonstrates the algorithm’s efficacy in improving hailstorm detection resolution. Significance Statement In recent years, China’s hail recordkeeping, primarily based on manual observations at national surface meteorological stations, has suffered from limited spatial and temporal detail. However, the advent of the China Next Generation Weather Radar (CINRAD) network offers a new avenue for hailstorm detection. TBSS, a secondary but significant indicator for large hail in S-band radar, presents an opportunity for enhanced hail warning capabilities. By automating TBSS detection in radar archives spanning two decades, this research significantly enhances the resolution of hailstorm climatology, contributing to more effective hail disaster mitigation and management.

Detection and Retrieval of Supercooled Water in Stratocumulus Clouds over Northeastern China Using Millimeter-Wave Radar and Microwave Radiometer

Supercooled water in mixed-phase clouds plays a significant role in precipitation formation, atmospheric radiation, weather modification, and aircraft flight safety. Identifying supercooled water in mixed-phase clouds is a crucial-frontier scientific issue in atmospheric detection research. In this study, we propose a new algorithm for identifying supercooled water based on the multi-spectral peak characteristics in cloud radar power spectra, combined with radar reflectivity factor and mean Doppler velocity. Using microwave radiometer data, we conducted retrieval analyses on two stratocumulus cases in the spring over the northeastern Daxing’anling region, China. The retrieval results show that the supercooled water in the spring stratocumulus clouds over the region is widespread, with liquid water content (LWC) ranging around 0.1 ± 0.05 g/m3, and particle sizes not exceeding 10 μm. The influence of updrafts on supercooled water is evident, with both showing good consistency in spatiotemporal variation trends. Comparing the liquid water path (LWP) variations retrieved from cloud radar and microwave radiometer, both showed good consistency in variation trends and high LWC areas, indicating the reliability of the identification algorithm developed in this study.

Photometric stereo multi-information fusion unsupervised anomaly detection algorithm

Due to different materials, product surfaces are susceptible to light, shadow, reflection, and other factors. Coupled with the appearance of defects of various shapes and types, as well as dust, impurities, and other interfering influences, normal and abnormal samples are difficult to distinguish and a common problem in the field of defect detection. Given this, this paper proposes an end-to-end photometric stereo multi-information fusion unsupervised anomaly detection model. First, the photometric stereo feature generator is used to obtain normal, reflectance, depth, and other information to reconstruct the 3D topographic details of the object’s surface. Second, a multi-scale channel attention mechanism is constructed to fully use the feature associations of different layers of the backbone network, and the limited feature information is used to enhance the defect characterization ability. Finally, the original image is fused with normal and depth features to find the feature variability between defects and defects, as well as between defects and background. The feature differences between the source and clone networks are utilized to achieve multi-scale detection and improve detection accuracy. In this paper, the model performance is verified on the PSAD dataset. The experimental results show that the algorithm in this paper has higher detection accuracy compared with other algorithms. Among them, the multi-scale attention mechanism and multi-information fusion input improve the detection accuracy by 2.56% and 1.57%, respectively. In addition, the ablation experiments further validate the effectiveness of the detection algorithm in this paper.

Effective Visualization of Radar Data for Users Impacted by Color Vision Deficiency

Abstract Color vision deficiency (CVD) is a decreased ability to discern between particular colors. Eight percent of genetic males and half a percent of genetic females have some form of CVD, with many in the radar community falling into this group. When presenting data on a two-dimensional plane, it is common to use colors to represent values via a colormap. Colormap choice in the radar community is influenced by the ability to highlight scientifically interesting features in data, institutional choices, and domain dominance of legacy colormaps. The problem with these current colormaps is that many do not project well for those with CVD (i.e., green next to red). In working with the CVD community to address this problem, multiple colormaps for moments such as equivalent reflectivity factor and Doppler velocity were created for users with forms of CVD such as deuteranomaly, protanomaly, protanopia, and deuteranopia using Python tools such as colorspacious and viscm. We show how these colormaps can improve interpretability for four cases: a mesoscale convective system, a pyrocumulonimbus storm, a wintertime midlatitude cyclone, and widespread storms with a large bird migration. These new radar equivalent reflectivity factor, Doppler velocity, and polarization colormaps are designed to highlight rain, frozen precipitation, nonmeteorological targets, and velocity-based items, are perceptually uniform, and are visually friendly for those with CVD.

Analysis of a Rainstorm Process in Nanjing Based on Multi-Source Observational Data and Lagrangian Method

Using multi-source observation data including automatic stations, radar, satellite, new detection equipment, and the Fifth Generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA-5) data, along with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) platform, an analysis was conducted on a rainstorm process that occurred in Nanjing on 15 June 2020, with the aim of providing reference for future urban flood control planning and heavy rainfall forecasting and early warning. The results showed that this rainstorm process was generated under the background of an eastward-moving northeast cold vortex and a southward retreat of the Western Pacific Subtropical High. Intense precipitation occurred near the region of large top brightness temperature (TBB) gradient values or the center of low TBB values on the northern side of the convective cloud cluster. During the heavy precipitation period, the differential propagation phase shift rate (KDP), differential reflectivity factor (ZDR), and zero-lag correlation coefficient (ρHV) detected by the S-band dual-polarization radar all increased significantly. The vertical structure of the wind field detected by the wind profile radar provided a good indication of changes in precipitation intensity, showing a strong correspondence between the timing of maximum precipitation and the intrusion of upper-level cold air. The abrupt increase in the integrated liquid water content observed by the microwave radiometer can serve as an important indicator of the onset of stronger precipitation. During the Meiyu season in Nanjing, convective precipitation was mainly composed of small to medium raindrops with diameters less than 3 mm, with falling velocities of raindrops mainly clustering between 2 and 6 m·s−1. The rainstorm process featured four water vapor transport channels: the mid-latitude westerly channel, the Indian Ocean channel, the South China Sea channel, and the Pacific Ocean channel. During heavy rainfall, the Pacific Ocean water vapor channel was the main channel at the middle and lower levels, while the South China Sea water vapor channel was the main channel at the upper level, both accounting for a trajectory proportion of 34.2%.

Validation of GPM DPR Rainfall and Drop Size Distributions Using Disdrometer Observations in the Western Mediterranean

Dual-frequency precipitation radar (DPR) on the Core GPM satellite provides spaceborne three-dimensional observations of precipitation fields and surface rainfall rate with quasi-global coverage. The present study evaluates the behavior of liquid precipitation intensity, radar reflectivity factor (ZKu and ZKa) and drop size distribution (DSD) parameters (weighted mean diameter Dm and intercept parameter Nw) of the GPM DPR-derived products, version 07, from 2014 to 2023. Observations from seven Parsivel disdrometers located in different topographic zones in the Western Mediterranean are taken as ground references. Four matching techniques between satellite estimates and ground level observations were tested, and the best results were found for the so-called optimal comparison approach. Overall, GPM DPR products captured the variability of the observed DSD well at different rainfall intensities. However, overestimation of the mean Dm and underestimation of the mean Nw were observed, being much more sensitive to errors in drop diameters larger than 1.5 mm. Moreover, the lowest errors were found for radar reflectivity factor and Dm, and the highest for Nw and rainfall rate. In addition, the GPM DPR convective and stratiform classification was tested, and a substantial overestimation of stratiform cases compared to disdrometer observations were found.