Diameter Dm Research Articles

Estimating ice water content for winter storms from millimeter-wavelength radar measurements using a synthesis of polarimetric and dual-frequency radar observations

Abstract The potential of millimeter-wavelength radar-based Ice Water Content (IWC) estimation is demonstrated using a Ka-band Scanning Polarimetric Radar (KASPR) for the U.S northeast coast winter storms. Two IWC relations for Ka-band polarimetric radar measurements are proposed: one that uses a combination of the radar reflectivity Z and the estimated total number concentration of snow particles Nt and the other based on the joint use of Z, specific differential phase KDP, and the degree of riming frim. A key element of the algorithms is to obtain the “Rayleigh-equivalent” value of Z measured at Ka band, i.e., the corresponding Z at longer radar wavelength for which Rayleigh scattering takes place. This is achieved via polarimetric retrieval of the mean volume diameter Dm and incorporating the relationship between the dual wavelength ratio DWRS/Ka and Dm. Those techniques allow for retrievals from single millimeter-wavelength radar measurements and do not necessarily require the DWR measurements, if the DWR-Dm relation and Rayleigh assumption for Ka-band KDP are valid. Comparison between the quasi-vertical profile product obtained from KASPR and the columnar vertical profile product generated from the nearby WSR-88D S-band radar measurements demonstrates that the DWRS/Ka can be estimated from the two close radars without the need for collocated radar beams and synchronized antenna scanning and can be used for determining the “Rayleigh-equivalent” value of Z. The performance of the suggested techniques is evaluated for seven winter storms using surface disdrometer and snow accumulation measurements.

The Ice Cloud Imager: retrieval of frozen water column properties

Abstract. The Ice Cloud Imager (ICI) aboard the second generation of the EUMETSAT Polar System (EPS-SG) will provide novel measurements of ice hydrometeors. ICI is a passive conically scanning radiometer that will operate within a frequency range of 183 to 664 GHz, helping to cover the present wavelength gap between microwave and infrared observations. Reliable global data will be produced on a daily basis. This paper presents the retrieval database to be used operationally and performs a final pre-launch assessment of ICI retrievals. Simulations are performed within atmospheric states that are consistent with radar reflectivities and represent the three-dimensional (3D) variability of clouds. The radiative transfer calculations use empirically based hydrometeor models. Azimuthal orientation of particles is mimicked, allowing for the consideration of polarisation. The degrees of freedom (DoFs) of the ICI retrieval database are shown to vary according to cloud type. The simulations are considered to be the most detailed performed to this date. Simulated radiances are shown to be statistically consistent with real observations. Machine learning is applied to perform inversions of the simulated ICI observations. The method used allows for the estimation of non-Gaussian uncertainties for each retrieved case. Retrievals of ice water path (IWP), mean mass height (Zm), and mean mass diameter (Dm) are presented. Distributions and zonal means of both database and retrieved IWP show agreement with DARDAR. Retrieval tests indicate that ICI will be sensitive to IWP between 10−2 and 101 kg m−2. Retrieval performance is shown to vary with climatic region and surface type, with the best performance achieved over tropical regions and over ocean. As a consequence of this study, retrievals from real observations will be possible from day one of the ICI operational phase.

Microphysical characteristics of torrential predecessor rain events over the Yangtze River Delta Area and the related tropical cyclones

The precipitation structures and microphysical characteristics of predecessor rain events (PREs) over the Yangtze River Delta area and related tropical cyclones (TCs) from 2014 to 2019 were investigated using Dual-frequency Precipitation radar data from Global Precipitation Measurement (GPM) for drop size distributions (DSDs). Results showed that the total mean rain rate of PREs was larger than that of TCs, primarily due to higher convective and stratiform rain rates, with enhanced fractional coverage of convective rain in PREs. Examination of microphysical characteristics revealed that a greater quantity of small-sized droplets and a smaller quantity of medium- as well as large-sized droplets contributed towards PREs in comparison with TCs. The conclusion still holds when partitioning DSDs based on different precipitation rate categories. Further investigation of DSDs using gamma functions illustrated that precipitation in PREs had lower average mass-weighted diameters (Dm) and enhanced normalized number concentration (Nw) compared with TCs; partitioning precipitation into convective and stratiform components illustrated a larger Dm and lower Nw in TCs than PREs. The analysis of microphysical and thermodynamical processes using the reanalysis data indicates that relatively intense convective activity with drier conditions may be favorable to enhancing raindrop growth through collision-coalescence processes, as a result of larger Dm in TCs than PREs. The empirical relations (Z–R algorithms) applied in different rain regimes (stratiform, convective, and total PREs) revealed significant diversities, relying on weather conditions and geographical locations. Plain language summaryThe Yangtze River Delta area is an important economic belt in China. Under climate change, observed frequent occurrences of weather extremes of heavy rainfall and tropical cyclones (TCs) exert adverse effects on economic development in this region. Thus, a deep understanding of the mechanism of TCs torrential rainfall in the Yangtze River Delta area is urgently necessary. In this study, we investigated the precipitation patterns and microphysical characteristics of predecessor rain events (PREs) in the Yangtze River Delta region, and their association with TCs in the South China Sea-Western North Pacific Ocean (SCS-WNPO) area from 2014 to 2019. We found that PREs had a higher total mean precipitation rate than TCs. Further examination using gamma functions demonstrated that PREs exhibited lower average mass-weighted diameters (Dm) and higher normalized intercept parameters (Nw) than TCs. This pattern persisted when distinguishing between convective and stratiform precipitation components. We believe that our study makes a significant contribution to the literature because these results provide valuable insights into the distinct precipitation characteristics of PREs and TCs in the study region and contribute to a better understanding of tropical cyclone-related rainfall patterns, and act as a scientific basis for disaster mitigation.

Vertical Profile Climatology of Polarimetric Radar Variables and Retrieved Microphysical Parameters in Synoptic and Lake Effect Snowstorms

AbstractThis study derives polarimetric radar vertical profiles and microphysical retrievals for 25 Synoptic Snow (SS) and 23 Lake Effect Snow (LES) cases using the Range‐Defined Quasi‐Vertical Profiles (RD‐QVP), Columnar Vertical Profiles (CVP), and Process‐oriented Vertical Profiles (POVP) methods. For all vertical profile techniques, SS cases exhibit a near‐linear increase in reflectivity from −30 to 0°C whereas ZDR and Kdp locally peak in the dendritic growth layer. LES cases universally exhibit negative ZDR, rather high Z, negligible Kdp, and near‐unity ρhv. Ground measurements from the past OWLeS campaign provide direct evidence that conical graupel may strongly affect these polarimetric measurements in LES bands. Aggregation efficiencies for SS cases are estimated by optimizing the theoretical number concentration (Nt) and mean volume diameter (Dm) steady‐state vertical profiles against radar‐retrieved profiles derived from 20 of the 25 synoptic storm RD‐QVPs. The median estimated aggregation efficiency is approximately 0.15 with a relatively narrow interquartile range that spans from 0.1 to just over 0.2. Values of optimized aggregation efficiencies are nearly independent of the assumed gamma distribution shape parameter. These results are used to derive temperature‐dependent, climatological steady‐state relations for vertical profiles of Nt, Dm, and liquid‐equivalent snowfall rates. These results can be used in numerical weather prediction model aggregation parameterizations and can also provide climatologically representative vertical profiles of radar and microphysical quantities.

Contrasts in the raindrop size distributions of pre-monsoon polluted and non-polluted rainy days over Rourkela, India

Raindrop size distribution (RSD) is crucial for accurate quantitative precipitation estimation and forecasting and is fundamental to precipitation microphysics. This study examines the microphysical characteristics of RSD at Rourkela, Odisha, under polluted and non-polluted conditions. This investigation utilized pre-monsoon in-situ (disdrometer) and reanalysis (ERA5) data for 2018–2021, to identify the pollution impact on precipitation over Rourkela. The polluted rainfall day has been determined based on the air quality index (AQI) value provided by the Central Pollution Control Board (CPCB), Government of India, over the Rourkela region. Classifying the rainfall in polluted and non-polluted days into stratiform and convective types showed that convective rainfall had a higher raindrop concentration and higher mean diameter (Dm) in both polluted and non-polluted days. Convective rainfall has a lower normalized intercept parameter (log10Nw) in polluted rainfall days. The RSD empirical relations (Z-R, μ – λ, Dm-R, Nw-R) also showed a noteworthy difference between the polluted and non-polluted rainfall days. The results disclosed that non-polluted rainfall has higher concentration of small-diameter raindrops, whereas polluted day rain has higher concentrations of midsize and large-diameter raindrops.

Combining functional and morphological retinal vascular characteristics achieves high-precision diagnosis of mild non-proliferative diabetic retinopathy

BackgroundTo explore the functional and morphological variations of retinal vessels in diabetes with no clinically detectable retinopathy (NDR) and mild non-proliferative diabetic retinopathy (NPDR) and to establish a high-performance mild NPDR diagnostic model.MethodsNormal subjects and type 2 diabetes patients with NDR and mild NPDR were recruited. Oxygen-saturation-related functional parameter (optical density ratio ODR) and morphological characteristics (fractal dimension Df, vessel area rate VAR, mean vascular diameter Dm, vessel tortuosity τ) of different vascular areas were extracted with single fundus photography and comprehensively analyzed among groups. An interpretable model combining marine predator algorithm (MPA) and support vector machine (SVM) based on characteristic selection was proposed for mild NPDR diagnosis.ResultsA total of 91 NDR subjects, 75 mild NPDR subjects, and 111 sex- and age-matched normal controls were analyzed. Increased main vessels ODR, while lower VAR of all areas except outer ring macula, lower Dm of all vessels and decreased τ of all areas were associate with NDR (e.g. main vessels ODR: OR [95%CI] 1.42[1.07–1.89], full macula τ:0.53[0.38–0.74]). Increased ODR of all areas, higher Dm of all areas except inner ring macula, increased inner ring macula τ, while decreased Df of full and inner ring macula, lower VAR of all areas were associate with mild NPDR (e.g. main vessels ODR:5.68[3.03–10.65], inner ring macula VAR: 0.48[0.33–0.69]). The MPA-SVM model with selected characteristics obtained the best diagnosis performance (AUC:0.940 ± 0.014; Accuracy:90.4 ± 3.9%; Sensitivity:89.2 ± 6.4%; Specificity:91.3 ± 6.4%).ConclusionsMore significant retinal vascular variations are associate with the incidence of mild NPDR than NDR. High-precision mild NPDR diagnosis is achieved combining the morphological and functional vascular characteristics based on characteristic selection.

Inter-seasonal variation of rainfall microphysics as observed over New Delhi, India

This study analyzes the raindrop size distribution (RSD) characteristics over New Delhi by dividing the year into three seasons: PreM (March–May), monsoon (June–September), and PostM (October–February). Data from a Joss-Waldvogel Disdrometer, installed at IITM New Delhi, Rajendra Nagar, was used for three years (2021–2023). The observed raindrop spectra were fitted with three-parameter Gamma functions to obtain the RSD. ERA-5 and satellite data were also employed to establish atmospheric and cloud properties for the three seasons. The RSD for the monsoon season shows the highest concentration of midsize (1–3 mm diameter) drops and the highest mean rain rate. PostM has the least concentration of midsize and large (diameter >3 mm) drops. General statistics of rain integral parameters reveal high variability in rain rate (R) and mass-weighted mean diameter (Dm) values during the monsoon season. The mu-lambda scatter plots show considerable differences among the three seasons, indicating slightly distinct rainfall mechanisms in the three seasons. Z-R relations of the form Z = aRb were derived, with the highest coefficient (a) values observed for the PreM precipitation. The exponent (b) is found to be greater than unity in all three seasons. Rainfall was stratified based on rain rate. RSD gets broader with increasing R. Large drops are not found appreciably in the spectrum for R < 20 mm/h. A notable disparity between convective and stratiform RSD is evident. The values of rain integral parameters show considerable differences between the convective and stratiform regimes. A higher fraction of large drops is found for the stratiform rainfall in the PreM season compared to the other two seasons. CAPE, water vapor, surface temperature, and surface winds were higher during PreM and monsoon months compared to PostM. The distribution of differential temperature (δT) indicates that clouds with significant depth are found in PreM and monsoon seasons but are often lacking during PostM.

Improving the predictions of black carbon (BC) optical properties at various aging stages using a machine-learning-based approach

Abstract. It is necessary to accurately determine the optical properties of highly absorbing black carbon (BC) aerosols to estimate their climate impact. In the past, there has been hesitation about using realistic fractal morphologies when simulating BC optical properties due to the complexity involved in the simulations and the cost of the computations. In this work, we demonstrate that, by using a benchmark machine learning (ML) algorithm, it is possible to make fast and highly accurate predictions of the optical properties for BC fractal aggregates. The mean absolute errors (MAEs) for the optical efficiencies ranged between 0.002 and 0.004, whereas they ranged between 0.003 and 0.004 for the asymmetry parameter. Unlike the computationally intensive simulations of complex scattering models, the ML-based approach accurately predicts optical properties in a fraction of a second. Physiochemical properties of BC, such as total particle size (number of primary particles (Npp), outer volume equivalent radius (ro), mobility diameter (Dm), outer primary particle size (ao), fractal dimension (Df), wavelength (λ), and fraction of coating (fcoating), were used as input parameters for the developed ML algorithm. An extensive evaluation procedure was carried out in this study while training the ML algorithms. The ML-based algorithm compared well with observations from laboratory-generated soot, demonstrating how realistic morphologies of BC can improve their optical properties. Predictions of optical properties like single-scattering albedo (ω) and mass absorption cross-section (MAC) were improved compared to the conventional Mie-based predictions. The results indicate that it is possible to generate optical properties in the visible spectrum using BC fractal aggregates with any desired physicochemical properties within the range of the training dataset, such as size, morphology, or organic coating. Based on these findings, climate models can improve their radiative forcing estimates using such comprehensive parameterizations for the optical properties of BC based on their aging stages.

Raindrop size distribution characteristics of pre-monsoon precipitation observed over eastern India

The knowledge of raindrop size distribution (DSD) is crucial for understanding the microphysical processes involved with the precipitation. Different empirical relationships established with DSD parameters, like radar reflectivity– rainfall rate (Z–R) relationships and shape–slope (μ–Ʌ) relationships, can progress the rainfall estimation algorithms and cloud modeling simulations. In the present study, long-term (2018–2021) measurements of a Laser Precipitation Monitor (LPM) disdrometer installed at the National Institute of Technology, Rourkela, India is used to investigate the DSD characteristics of pre-monsoon (March–May) rainfall. Along with the disdrometer data, auxiliary parameters like convective available potential energy (CAPE), total column water vapor (TCWV), vertical profiles of temperature and relative humidity from reanalysis data sets of ECMWF (European Centre for Medium-Range Weather Forecasts) fifth-generation reanalysis (ERA5) are also used in this study. Based on standardized rainfall anomaly, the pre-monsoon precipitation days are classified into strong, moderate, and weak rainy days, and they contributed to 58.69%, 32.7%, and 8.61% of total rainfall, respectively. The average DSD indicated noteworthy variations among strong, moderate, and weak rainy days with maximum (minimum) concentration of raindrops in strong (weak) rainy days. The mean value of rain rate (R), normalized intercept parameter (Nw), and mass-weighted mean diameter (Dm) is maximum during days of strong rainfall. Strong rainy days showed high-value CAPE, TCWV and vertical profile of relative humidity. The majority of R is contributed by moderate-sized raindrops with a significant difference in the Z–R and μ–Λ relationships among three types of rainy days.

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.

Land-sea contrast of vertical structure of precipitation over Sumatra revealed by GPM DPR observations

This study examines the land-sea contrast in the vertical structure of precipitation over Sumatra and its surrounding ocean using eight years (2014–2021) of dual-frequency precipitation radar (DPR) data from the Global Precipitation Measurement (GPM) mission. The study area is segmented into Ocean, Coast I (west coast), Land I (west of Barisan Mountains), Land II (east of Barisan Mountains), and Coast II (east coast). The effective reflectivity factor (Ze), rainfall rate (R), and two raindrop size distribution (DSD) parameters, namely the mass-weighted mean diameter (Dm) and the normalized intercept (Nw), were analyzed. Stratiform and deep convective rainfall were the most frequent types in Coast I, followed by Ocean, Land I, Land II, and Coast II. In contrast, shallow convective rainfall was the most common type in Ocean, followed by Coast I, Land I, Land II, and Coast II. The average rain top height (RTH) was found to be higher in Land II and Coast II than in Ocean, Coast I, and Land I, in accordance with the surface rainfall intensity pattern previously reported by other studies. Furthermore, the data on heavy ice precipitation demonstrated an increase from the ocean to the coast and land, with a significant number of instances observed in Land I, Land II, and Coast II, in addition to Coast I. This contrast in heavy ice precipitation and RTH influences DSD. The land-sea contrast of DSD is more pronounced for deep convective rains. Deep convective exhibited a lower frequency of large raindrops over the ocean than over the coast and land, as reflected in the Dm profile. Conversely, raindrop concentration, particularly small drops, was higher at sea. The percentage of Dm > 2 mm at sea was approximately 2%, rising to 4–6% in Land II and Coast II. The land-sea contrast in the vertical structure of precipitation over Sumatra exhibited apparent diurnal variation. Larger Dm and smaller Nw were observed over Land I and Coast I, particularly in the afternoon and evening, correlating with peak rainfall. This pattern aligns with heavy ice precipitation profiles, vertical relative humidity (RH), and wind profiles. This study highlights the complexities and potential discrepancies between vertical precipitation profiles and surface precipitation data, underscoring the nuanced nature of land-sea precipitation migration.

Precipitation Characteristics at Different Developmental Stages of the Tibetan Plateau Vortex in July 2021 Based on GPM-DPR Data

The Tibetan Plateau vortex (TPV), as an α-scale mesoscale weather system, often brings severe weather conditions like torrential rain and severe convective storms. Based on the detections from the Global Precipitation Measurement (GPM) Core Observatory’s Dual-frequency Precipitation Radar (DPR) and the FY-4A satellite’s Advanced Geostationary Radiation Imager (AGRI), combined with ERA5 reanalysis data, the precipitation characteristics of a TPV moving eastward during 8–13 July 2021 at different developmental stages are explored in this study. It was clear that the near-surface precipitation rate of the TPV during the initial stage at the eastern Tibetan Plateau (TP) was below 1 mm·h−1, implying overall weak precipitation dominated by stratiform clouds. After moving out of the TP, the radar reflectivity factor (Ze), precipitation rate, and normalized intercept parameter (dBNw) significantly increased, while the proportion of convective clouds gradually rose. Following the TPV movement, the distribution range and vertical thickness of Ze, mass-weighted mean diameter (Dm), and dBNw tended to increase. The high-frequency region of Ze appeared at 15–20 dBZ, while Dm and dBNw occurred at around 1 mm and 33 mm−1·m−3, respectively. Near the melting layer, Ze was characterized by a significant increase due to the aggregation and melting of ice crystals. The precipitation rate of convective clouds was generally greater than that of stratiform clouds, whilst both of them increased during the movement of the TPV. Particularly, at 01:00 on 12 July, there was a significant increase in the precipitation rate and Dm of convective clouds, while dBNw noticeably decreased. These findings could provide valuable insights into the three-dimensional structure and microphysical characteristics of the precipitation during the movement of the TPV, contributing to a better understanding of cloud precipitation mechanisms.

Exploring the statistical characteristics of coastal winter precipitation measured using a Parsivel2 disdrometer: A case study in North Carolina

A drop size distribution (DSD) of a precipitation event is a key characteristic and plays a critical role in quantitative precipitation estimation. In this study, DSD datasets were collected by a Parsivel2 disdrometer in Elizabeth City, North Carolina, U.S. from October 2021 to April 2022. The microphysical and statistical characteristics of the DSD were examined. For this period, the contribution of small raindrops (< 1 mm) to the total number concentration (Nt) was the largest, while the contribution of large raindrops (3―8 mm) to Nt was the smallest. As expected, large raindrops had the largest impact on rain rate (R), liquid water content (W), and radar reflectivity factor (Z), while small raindrops had the least. The shape of the averaged DSDs was similar for different rain rates while the width of the raindrop concentration spectrum increased as rain rates increased. The average mass-weighted diameter Dm (log10Nw, generalized intercept parameter) value for all rain events was found to be 1.11 mm (4.54), while for stratiform rains Dm was 1.18 mm (4.65), and for convective rains, it was 0.89 mm (4.17). The empirical relationships between rain intercept parameter (N0) vs shape factor (μ), μ vs slope factor (Λ), log10Nw vs median volume diameter (D0), D0 vs R, R vs kinetic energy (KE), and Z―R relationship were also derived. These findings are useful for design of rainfall simulators and for better understanding erosive properties of rainfall that contribute to contaminant fate and transport.

Microphysical Characteristics of Precipitation Over Eastern China and Its Coastal Regions

AbstractMany studies have investigated the macro‐ and micro‐physical properties of precipitation, but few classified precipitation into warm‐ and cold‐topped, which affects precipitation phase and precipitation type significantly. Furthermore, the impact of moisture and dynamics on microphysical characteristics of precipitation has been less studied. Using precipitation data from the GPM 2A DPR between May and September from 2015 to 2023, this study conducts a systematic study on microphysical characteristics of precipitation over eastern China and its coastal areas. This study divides precipitation cases into 20 categories, including warm‐/cold‐topped (CTP/WTP) convective/stratiform light/moderate/heavy/extreme/the most extreme precipitation. The findings reveal distinct differences along with similarities in various precipitation categories between eastern China and its coastal regions. The convection ratio for CTP increases with higher precipitation intensity, while WTP is dominated by convective precipitation. The more CTP, the higher the solid water content. The heavier precipitation, the higher liquid water content contributes. The mass‐weighted diameter (Dm) for CTP shows three variations from high to low with little or slight decrease with altitude at upper‐layer, followed by a rapid increase at middle‐layer and finally decreasing slightly at low‐layer. The CTP Dm grows rapidly with temperature from −18.58 (−13.93)°C for convective (stratiform) precipitation and their maximum growth rate are almost located in melting layer. Dm (raindrop density) is larger (lower) over land than ocean and larger (lower) for CTP than WTP. Dm shows positive relation to vertical velocity and specific humidity, especially sensitive to the middle‐ and upper‐layers meteorological conditions.

A New Melting Model and Its Implementation in Parameterized Forward Operators for Polarimetric Radar Data Simulation With Double Moment Microphysics Schemes

AbstractTo improve short‐term severe weather forecasts through assimilation of polarimetric radar data (PRD), the use of accurate and efficient forward operators for polarimetric radar variables is required. In this study, a new melting model is proposed to estimate the mixing ratio and number concentration of melting hydrometeor species and incorporated in a set of parameterized polarimetric radar forward operators. The new melting model depends only on the mixing ratio and number concentration of rain and ice species and is characterized by its independence from ambient temperature and its simplicity and ease of linearization. To assess the impact of this newly proposed melting model on the simulated polarimetric radar variables, a real mesoscale convective system is simulated using three double‐moment microphysics schemes. Compared with the output of the original implementation of the parameterized forward operators (PFO_Old) that rely on an “old” melting model which only estimates the mixing ratio of the melting species, the updated implementation with the new melting model (PFO_New) that estimates both the mixing ratio and number concentration of melting species eliminates the very large mass/volume‐weighted mean diameter (Dm) at the bottom of the melting layer and produces more reasonable melting layer signatures for all three double‐moment microphysics schemes that more closely match the corresponding radar observations. This suggests that the new melting model has more reasonable implicit estimates of mixing ratios and number concentrations of melting hydrometeor species than the “old” melting model.

Exploring mm-Wavelength Radar Capabilities for Raindrop Size Distribution Retrieval: Estimating Mass-weighted Mean Diameter from the Differential Backscatter Phase

Abstract Accurate precipitation characterization relies on the estimation of raindrop size distribution (RDSD) from observations. While various techniques using cm-wavelength radars have been proposed for RDSD retrieval, the potential of mm-wavelength polarimetric radars, offering enhanced spatial and temporal resolution while capturing light to moderate rain, remains unexplored. This study focuses on retrieving the mass-weighted mean volume diameter (Dm) using a dual frequency cloud radar. Since the differential reflectivity (Zdr) is ineffective for Dm retrieval at 94 GHz, and simulations demonstrate a strong dependence of the differential backscatter phase (δco) on Dm, the estimation of δco takes precedence in this paper. Notably, δco remains unaffected by attenuation and polarimetric calibration. Addressing the initial requirement of disentangling backscattering and propagation effects at mm-wavelength, an automatic algorithm is proposed to detect Rayleigh plateaus in the spectral domain. Subsequently, a methodology for estimating δco and its associated error is presented. Leveraging simulation results, confidence intervals for Dm that align with δco confidence intervals are retrieved. The assessment of Dm and its confidence interval at 35 and 94 GHz is conducted employing disdrometer-derived Dm. The results demonstrate a comprehensive concordance within a margin of 0.2 mm, underscoring the cloud radar's efficacy in delineating nuanced variations in raindrop mean diameter versus altitude. The validation process encounters difficulties for Dm below 1 mm, as the disdrometer-derived Dm may exhibit an overestimation, while the cloud radar-derived Dm may exhibit an underestimation. The combination of 35 and 94 GHz serves to diminish the confidence interval associated with the retrieved Dm.

Dasometric variables that determine fuel load in oak forests in Guerrero, Mexico

Climate change and the lack of fuel management in oak forests promote favorable conditions for the occurrence of forest fires. The objective of the present research was to know the relationship of dasometric variables, terrain slope (Pe), depth of leaf litter (Ph) and depth of mulch (Pm) on the fuel load in oak forests in the Mountain region of Guerrero. The dasometric variables mean diameter (Dm), mean height (Am), number of trees ha-1 (Na) and basal área ha-1 (Ab) were evaluated according to the sampling design of the 2015 National Forest and Soil Inventory; At each sampling site, three planar intersection lines were established for sampling woody material (Ml), leaf litter (Ho) and mulch (Ma) were collected in 0.09 m2. The total fuel load ranged from 23.2 to 46.5 t ha-1 (p &lt; 0.05), the Ma presented the highest load with 43%, followed by woody material (Ml) and leaf litter (Ho) with 31 and 26%. The total charge (Ct) showed a relationship with Ma, Ho and Ml (r = 0.81 to 0.41), Ho with Ph and Pe (r = 0.71 and -0.72). The c1h showed a relationship with Na, Ma, Pe and Dm (r = 0.72 to -0.41), the c10h showed a correlation with Ab, Pe and Na (r = 0.51 to 0.42). The dasometric variables only explain the fuel load with a diameter less than or equal to 2.5 cm.

Confinement effects of mandrel degradation in ICF target fabrication.

Understanding and further regulating the degradation of mandrel materials is a key aspect of target fabrication in inertial confinement fusion (ICF). Here, a quasi-one-dimensional confinement model is developed using a series of single-walled carbon nanotubes with varying diameters (Dm), and the degradation of poly-α-methylstyrene (PAMS) as a typical mandrel material is investigated under such confined conditions by using the combined method of quantum mechanics and molecular mechanics. In comparison to the isolated system, the calculations show that confinement can decrease or increase the energy barriers of PAMS degradation, which directly depends on Dm. Following which a clear exponential relationship between the degradation rate of PAMS and its own density is derived, indicating that the density of PAMS can be used to regulate mandrel degradation. This work highlights the important effects of confinement on degradation and provides a valuable reference for further development of polymer degradation technologies in ICF target fabrication and other fields.

Flow three-dimensionality of wavy elliptic cylinder: vortex shedding bifurcation

The three-dimensional flow of a wavy elliptic cylinder and its wake are investigated for wavelength (λ) to hydraulic diameter (Dm) ratio λ/Dm = 3.43, 4.58, and 6.01. The study aims to gain insights into flow separation, flow dynamics, and three-dimensional flow topologies for the selected wavelengths. Three-dimensional flow structures are visualized through time-averaged streamlines with critical point theory. The results for λ/Dm = 3.43 show spiral flow directed from the node to the saddle, counter-rotating vortices, and a wavy vortex structure. On the contrary, the flows for λ/Dm = 4.58 and 6.01 respectively undergo bifurcation in stable recirculation and vortex shedding on a half-span of the cylinder wavelength. The bifurcation results in a spiral flow toward the saddle and the other spiral flow toward the node. The bifurcations of recirculation and vortex shedding are revealed for the first time. The findings contribute to an improved understanding of the insight into intricate flow physics around wavy elliptic cylinders.

Micro Rain Radar and Radiometric Measurements to Unravel Contrasting Features of Rain Microstructure Below and Above the Boundary Layer

AbstractKa‐band Micro rain Doppler radar is an effective tool to investigate the profiles of precipitation microstructure in terms of the raindrop size distribution (DSD). The DSD parameters that vary appreciably with height are indicative of the associated atmospheric phenomena. Hence the present investigation endeavors to put light on the underlying physical processes responsible for the evolution of varied rain microstructure profiles using micro rain radar (MRR), and radiometric measurements complemented with re‐analysis outputs over an urban tropical location, Kolkata (22.57°N, 88.37°E), India. MRR unravels the prevalence of significant biases in the typical power law relationship (Dm = aRb) between rain rate (R) and mass‐weighted mean drop diameter (Dm) along the rain height, especially during intense convective rain events, above the atmospheric boundary layer (ABL). Consequently, an alternative empirical relation appropriate to account for the R‐Dm variability above the ABL is proposed. Further, radiometric measurements and re‐analysis outputs reveal that the presence of atmospheric instabilities coupled with wind shear impacts above the ABL contributes to the enhanced breakup of raindrops and the deviations in the usual R‐Dm relationship. Thus, the present study intends to highlight the applicability of ground‐based radar measurements over the tropics to devise quantitative precipitation algorithms for reliable rain estimates.