Search Results (74)

This study, conducted in the framework of the LIAISE field campaign in NE Spain (May–September 2021), investigates how near-surface relative humidity influences early-stage rainfall characteristics when precipitation is most affected by temperature and relative humidity before rainfall onset. Two instrumented sites were examined, using disdrometers, Micro Rain Radar (MRR), C-band weather radar data, and automatic weather stations. Rainfall events were first classified as stratiform or convective using weather radar data based on a texture analysis of the reflectivity field. Then, only stratiform events were selected and further classified into dry and moist categories according to the upper and lower terciles of near-surface (2 m) relative humidity at the rainfall onset (dry < 54%; moist > 72%). Results show that during dry events, the time delay between the detection of precipitation at ~750 m above ground level (AGL) (by MRR or C-band radar) and its arrival at the surface (measured by the disdrometer) is consistently longer than during moist events, indicating possible evaporation of raindrops during their descent. Surface drop size distributions also differ: dry cases have generally fewer small drops (with diameters < 0.8 mm) but relatively more large drops, leading to higher radar reflectivity values despite similar surface rainfall amounts. However, reflectivity observed aloft by C-band radar and MRR does not present the dependence on relative humidity found at ground level. Findings reported here increase our understanding of the impact of low-level conditions on precipitation characteristics and microphysical associated processes and may contribute to improve correction schemes in operational weather radar quantitative precipitation estimates. Full article

The accurate retrieval of the raindrop size distribution (DSD) is a longstanding objective in meteorology because it underpins reliable quantitative precipitation estimation. Among remote sensors, weather radars are the primary tool for mapping DSD over wide areas, and phased-array systems in particular have demonstrated unique advantages owing to their high temporal and spatial resolution together with agile beam steering. Exploiting the underused high-resolution capability of an X-band phased-array radar, this study induced a Rainfall Regression Model (RRM). The RRM assumes a normalized gamma DSD model and retrieves its three parameters. It was then applied to a rain event influenced by the remnant circulation of Typhoon Haikui that affected Guangzhou on 8 September 2023. First, collocated disdrometer observations and T-matrix scattering simulations are used to build polynomial regressions between DSD parameters (D₀, N_w, μ) and the polarimetric variables. Validation against independent disdrometer samples yields Nash–Sutcliffe efficiencies of 0.93 for D₀ and 0.91 for log₁₀N_w. The RRM is then applied to the full volumetric radar data. Horizontal maps reveal that the surface elevation angle consistently exhibited the largest standard deviation for all three parameters. A vertical profile analysis shows that large-drop cores (D₀ > 2 mm) can reside above 2 km and that iso-value contours tilt rather than align vertically, implying an appreciable horizontal drift of raindrops within the complex remnant typhoon–monsoon wind field. By demonstrating the ability of X-band phased-array radar to resolve the three-dimensional microphysical structure of remnant typhoon precipitation, this study advances our understanding of the vertical characteristics of raindrops and provides high-resolution DSD information that can be directly ingested into severe weather monitoring and nowcasting systems. Full article

The impact of wind on precipitation measurements from the OTT Parsivel² optical transmission disdrometer is quantified using computational fluid dynamics simulations. The numerical velocity field around the instrument body and above the instrument sensing area (the laser beam) shows significant disturbance that depends heavily on the wind direction. By computing the trajectories of raindrops approaching the instrument, the wind-induced bias is quantified for a wide range of environmental conditions. Adjustments are derived in terms of site-independent catch ratios, which can be used to correct measurements in post-processing. The impact on two integral rainfall variables, the rainfall intensity and radar reflectivity, is calculated in terms of collection and radar retrieval efficiency assuming a sample drop size distribution. For rainfall intensity measurements, the OTT Parsivel² shows significant bias, even much higher than the wind-induced bias typical of catching-type rain gauges. Large underestimation is shown for wind parallel to the laser beam, while limited bias occurs for wind perpendicular to it. The intermediate case, with wind at 45°, presents non negligible overestimation. Proper alignment of the instrument with the laser beam perpendicular to the prevailing wind direction at the installation site and the use of windshields may significantly reduce the overall wind-induced bias. Full article

This study examines a Mei-Yu rainfall event using rain gauges (RG) and OTT Parsivel disdrometers to observe precipitation characteristics and raindrop size distributions (RSD), with comparisons made against Weather Research and Forecasting (WRF) model simulations. Results show that Parsivel-derived rain rates (RR) are slightly underestimated relative to RG measurements. Both observations and simulations identify 1–3 mm raindrops as the dominant precipitation contributors, though the model overestimates small and large drop contributions. At low RR, decreased small-drop and increased large-drop concentrations cause corresponding leftward and rightward RSD shifts with decreasing altitude—a pattern well captured by simulations. However, at elevated rainfall rates, the simulated concentration of large raindrops shows no significant increase, resulting in negligible rightward shifting of RSD in the model outputs. Autoconversion from cloud droplets to raindrops (ATcr), collision and breakup between raindrops (AGrr), ice melting (MLir), and evaporation of raindrops (VDrv) contribute more to the number density of raindrops. At 0.1 < RR < 1 mm·h⁻¹, ATcr dominates, while VDrv peaks in this intensity range before decreasing. At higher intensities (RR > 20 mm·h⁻¹), AGrr contributes most, followed by MLir. When the RR is high enough, the breakup of raindrops plays a more important role than collision, leading to a decrease in the number density of raindrops. The overestimation of raindrop breakup from the numerical parameterization may be one of the reasons why the RSD does not shift significantly to the right toward the surface under the heavy RR grade. The RSD near the surface varies with the RR and characterizes surface precipitation well. Toward the surface, ATcr and VDrv, but not AGrr, become similar when precipitation approaches. Full article

Rainfall simulators are essential tools in soil research, providing a controlled and repeatable approach to studying rainfall-induced erosion. However, the development of high-fidelity rainfall simulators remains a challenge. This study aimed to design, construct, and calibrate a spraying-type rainfall simulator and validate assessment criteria optimized for soil erosion research. The simulator’s design is based on a modified simulator model previously described in the literature and following the defined criteria. The calibration of the simulator was conducted in two phases, on slopes of 0° and 15°, measuring rainfall intensity, drop size, and its spatial distribution, and calculating drop falling velocity, kinetic energy, and momentum. The simulator consists of structural support, a water tank, a water-moving mechanism, a flow regulation system, and sprayers, contributing to its simplicity, cost-effectiveness, durability, rigidity, and stability, ensuring smooth simulator operation. The calibration of the rainfall simulator demonstrated that rainfall intensity increased from 1.4 mm·min⁻¹ to 4.6 mm·min⁻¹ with higher pressure in the hydraulic system (1.0 to 2.0 bar), while spatial uniformity remained within 79–91% across different nozzle configurations. The selected Rain Bird HE-VAN series nozzles proved highly effective in simulating rainfall, achieving drop diameters ranging from 0.8 mm to 1.9 mm, depending on pressure and nozzle type. The rainfall simulator successfully replicates natural rainfall characteristics, offering a controlled environment for investigating soil erosion processes. Drop velocity values varied between 2.5 and 2.9 m·s⁻¹, influencing kinetic energy, which ranged from 0.6 J·min⁻¹·m⁻² to 2.9 J·min⁻¹·m⁻², and impact momentum, which was measured between 0.005 N·s and 0.032 N·s. The simulator design suggests that it is suitable for future applications in both field and laboratory soil erosion research, ensuring repeatability and adaptability for various experimental conditions. Calibration results emphasized the significance of nozzle selection and water pressure adjustments. These factors significantly affect rainfall intensity, drop size, kinetic energy, and momentum, parameters that are critical for accurate erosion modeling. Full article

The evaluation of raindrop size distribution (DSD) is a crucial subject in radar meteorology, as it determines the relationship between radar reflectivity (Z) and rainfall rate (R). The coefficients (a and b) of the Z-R relationship vary significantly due to several factors (e.g., climate and rainfall intensity), rendering the characterization of local DSD essential for improving radar quantitative precipitation estimation. This study used a unique network of 21 disdrometers with high spatio-temporal resolution in Mexico City to investigate changes in the local drop size distribution (DSD) resulting from seasonal fluctuations, rain rates, and topographical regions (flat urban and mountainous). The results indicate that the DSD modeling utilizing the normalized gamma distribution provides an adequate fit in Mexico City, regardless of geographical location and season. Regional variation in DSD’s slope, shape, and parameters was detected in flat urban and mountainous areas, indicating that distinct precipitation mechanisms govern rainfall in each season. Severe rain intensities (R > 20 mm/h) exhibited a more uniform and flatter DSD shape, accompanied by increased dispersion of DSD parameter values among disdrometer locations, particularly for intensities exceeding R > 60 mm/h. The coefficients a and b of the Z-R relationship exhibit significant geographic variability, dependent on the city’s topographic gradient, underscoring the necessity for regionalization of both coefficients within the metropolis. Full article

Quantitative precipitation estimation using polarimetric radar in attenuation-prone frequency (X-band) in tropical regions characterized by convective rain systems with high intensities is a major challenge due to strong attenuations that can lead to total signal extinction over short distances. However, some authors have addressed this issue in Benin since 2006 in the framework of the African Monsoon Multidisciplinary Analysis program. Thus, with an experimental setup consisting of an X-band polarimetric weather radar (Xport) and a network of rain gauges, investigations have started on the subject with the aim of improving rainfall estimates. Based on simulated polarimetric variables and using a Multilayer Perceptron artificial neural network, several bi-variable and tri-variable algorithms were assessed in this study. The data used in this study are of two categories: (i) simulated polarimetric variables (Rayleigh reflectivity $Z$, horizontal attenuation $A_h$, horizontal reflectivity $Z_h$, differential reflectivity $Z_{dr}$, and specific differential phase $K_{dp}$) and rainfall intensity (R) obtained from Rain Drop Size Distribution (DSD) measurements used for algorithm evaluation (training and testing); (ii) polarimetric variables measured by the Xport radar and rainfall intensity measured by rain gauges used for algorithm validation. The simulations are performed using the T-matrix code, which leverages the scattering properties of spheroidal particles. The DSD measurements taken in northwest Benin were used as input for this code. For each spectrum, the T-matrix code simulates multiple variables. The simulated data (first category) were divided into two parts: one for training and one for testing. Subsequently, the best algorithms were validated with the second category of data. The performance of the algorithms during training, testing, and validation was evaluated using metrics. The best selected algorithms are $A1:R(Z,K_{dp})$ and $A12:R(Z_{dr},K_{dp})$ (among the bi-variable); $B2:R(Z_h,Z_{dr},K_{dp})$ and $B3:R(A_h,Z_{dr},K_{dp})$ (among the tri-variable). Tri-variable algorithms outperform bi-variable algorithms. Validation with observation data (Xport measurements and rain gauge network) showed that the algorithm $B3:R(A_h,Z_{dr},K_{dp})$ performs better than $B2:R(Z_h,Z_{dr},K_{dp})$. Full article

The Tianshan Mountains are known as the “Water Tower of Central Asia” and are of significant strategic importance for Xinjiang as well as the Central Asian region. Accurately monitoring the spatiotemporal distribution of precipitation in the Tianshan Mountains is crucial for understanding global water cycles and climate change. Raindrop Size Distribution (DSD) parameters play an important role in improving quantitative precipitation estimation with radar and understanding microphysical precipitation processes. In this study, DSD parameters in the Tianshan Mountains were evaluated on the basis of Global Precipitation Measurement mission (GPM) dual-frequency radar data (DPR) and ground-based laser disdrometer observations from 2019 to 2024. With the disdrometer observations as the true values, we performed spatiotemporal matching between the satellite radar and laser disdrometer data. The droplet spectrum parameters retrieved with the GPM dual-frequency radar system were compared with those calculated from the laser disdrometer observations. The reflectivity observations from the GPM DPR in both the Ku and Ka bands (ZKu and ZKa) were greater than the actual observations, with ZKa displaying a greater degree of overestimation than ZKu. In the applied single-frequency retrieval algorithm (SFA), the rainfall parameters retrieved from the Ka band outperformed those retrieved from the Ku band, indicating that the Ka band has stronger detection capability in the Tianshan Mountains area, where light rain predominates. The dual-frequency ratio (DFR), i.e., the differences in the reflectivity of the raindrop spectra obtained from both the Ku and Ka bands, fluctuated more greatly than those of the GPM DPR. DFR is a monotonically increasing function of the mass-weighted mean drop diameter (Dm). Rainfall rate (R) and Dm exhibited a strong positive correlation, and the fitted curve followed a power function distribution. Full article

Mêdog is located at the entrance of the water vapor channel of the Yarlung Tsangpo Great Canyon on the southeastern Tibetan Plateau (TP). In this study, the seasonal variation in the microphysical vertical structure of stratiform precipitation at the Mêdog site in 2022 was investigated using micro rain radar (MRR) observations, as there is a lack of similar studies in this region. The average melting layer height is the lowest in February, after which it gradually increases, reaches its peak in August, and then gradually decreases. For lower rain categories, the vertical distribution of small drops remains uniform in winter below the melting layer. The medium-sized drops show slight increases, leading to negative gradients in the microphysical profiles. Slight or evident decreases in concentrations of small drops are observed with decreasing height in the premonsoon, monsoon, and postmonsoon seasons, likely due to significant evaporation. The radar reflectivity, rain rate, and liquid water content profiles decrease with decreasing height according to the decrease in concentrations of small drops. With increasing rain rate, the drop size distribution (DSD) displays significant variations in winter, and the fall velocity decreases rapidly with decreasing height. In the premonsoon, monsoon, and postmonsoon seasons, the concentrations of large drops significantly decrease below the melting layer because of the breakup mechanism, leading to the decreases in the fall velocity profiles with decreasing height during these seasons. Raindrops with sizes ranging from 0.3–0.5 mm are predominant in terms of the total drop number concentration in all seasons. Precipitation in winter and postmonsoon seasons is mainly characterized by small raindrops, while that in premonsoon and monsoon seasons mainly comprises medium-sized raindrops. Understanding the seasonal variation in the vertical structure of precipitation in Mêdog will improve the radar quantitative estimation and the use of microphysical parameterization schemes in numerical weather forecast models over the TP. Full article

Rain attenuation based on the drop size distribution (DSD) with different rainfall rates (R) at low THz frequencies is investigated in this paper. The rain attenuation is calculated using the DSD measured for one year and the extinction cross-section (ECS) by the Mie scattering theory. Moreover, the obtained specific rain attenuation is verified by the empirical model using the measurement system consisting of a transmitter, a receiver, and weather measurement units. We measured the received power against the uniform transmitted power at 240, 270, and 300 GHz on the rooftop of the National Radio Research Agency (RRA) in Korea during the same period as the DSD measurement period. After curve fitting by regression analysis, we compared both rain attenuations obtained in two methods with the recommendation International Telecommunication Union Radiocommunication Sector (ITU-R) P.838-3. The root mean square errors (RMSEs) of the DSD model are 2.8977, 2.8646, and 2.8331 at 240, 270, and 300 GHz, respectively. The calculated result using the Mie scattering and the measured DSD methods shows the best fit to the data of the ITU-R recommendation for a rainfall rate of up to 5 mm/h. On the other hand, the empirical results using the T/Rx antenna system are slightly higher compared to the data of the ITU-R recommendation. As the rainfall rate increases, the difference between our results and ITU-R recommendation increases. This study will be useful for predicting rain attenuation for terrestrial wireless links operating at low THz frequencies. Full article

We examine several different features of DSDs based on data and observations from two mid-latitude coastal locations: (a) the Delmarva peninsula, USA, and (b) Incheon, South Korea. In each case, the full DSD spectra were obtained from two collocated disdrometers. Two events from location (a) and one event from location (b) are presented. For (a), observations and retrievals from NASA’s S-band polarimetric radar are included in the analyses as well as retrieved DSD parameters from the dual-wavelength precipitation radar onboard the Global Precipitation Measurement satellite. For (b), the disdrometer-based DSD data are compared with measurements from another sensor. Our main aim is to examine the underlying shape of the DSDs and their representation by the generalized gamma model. Full article

As a key component of the hydrological cycle, knowledge and comprehension of precipitation formation and evolution are of leading significance. This study investigates the statistical characteristics of raindrop size distribution for heavy precipitation events with observations collected by a Present Weather Sensor (PWS100) disdrometer located in the alpine area of eastern Tianshan, China. The characteristics are quantified based on heavy rain, heavy snow, and hail precipitation events classified using the rainfall intensity and the precipitation-related weather codes (US National Weather Service). On average, the heavy precipitation events in the headwaters of the Urumqi River are dominated by medium-sized (2–4 mm) raindrops. As well, we investigate mass-weighted mean diameter–normalized intercept parameter scatterplots, which demonstrate that the heavy precipitation events in alpine regions of the Tianshan Mountains can be identified as maritime-like clusters. The concentration of raindrops in heavy precipitation is the highest overall, while the concentration of raindrops in heavy snow is the lowest when the diameter is lower than 1.3 mm. The power–law relationships of radar reflectivity (Z) and rain rate (R) [Z = AR^b] for the heavy rain, heavy snow, and hail precipitation events are also calculated. The Z–R relationship of heavy rain and heavy snow in this work has a lower coefficient value of A (10 and 228.7, respectively) and a higher index value of b (2.6 and 2.1, respectively), and the hail events are the opposite (A = 551.5, b = 1.3), compared to the empirical relation (Z = 300R^1.4). Furthermore, the possible thermodynamics and general atmospheric circulation that cause the distinctions in the raindrop size distribution characteristics between alpine areas and other parts of the Tianshan Mountains are also debated in this work. The headwaters of the Urumqi River in alpine areas have relatively colder and wetter surroundings in the near-surface layer than the foothills of the Tianshan Mountains during the precipitation process. Meanwhile, a lower temperature, a higher relative humidity, a more efficient collision coalescence mechanism, and glacier local microclimate effects (temperature jump, inverse glacier temperature, glacier wind) at the headwaters of the Urumqi River during the precipitation process are probably partly responsible for more medium- and large-size drops in the mountains. Full article

This study presents a year-long (January 2019–April 2020) analysis of the Z–R relationship and drop size distribution (DSD) scaling parameters for size, concentration, and shape of rain events over Santa Clara Valley, CA. External influences were analyzed based on synoptic variability and seasons. For the former, 850 hPa winds were separated into groups based on direction and magnitude. Results show that greater drop size, lower concentration, and larger shape parameters for spring, while winter and fall showed smaller drop sizes, higher concentrations, and smaller shape parameters. For synoptic variability, southeasterly-to-southwesterly flow was associated with larger drop sizes, larger concentrations, and smaller shape parameters relative to northwesterly flow. Differences in the DSD scaling parameter values and Z–R relationship were also observed between strong and weak low-level flow. The results of this study suggest that it is beneficial to derive specific microphysical relationships based on seasons and different synoptic events to improve radar rain rate retrieval algorithms using the Z–R relationship. Full article

Rainfall simulators represent often-used equipment for soil research. Depending on their performance, they could be appropriate for some soil research or not. The aim of this research is to provide insight into the capabilities of existing dripping rainfall simulators (DRS) to mimic natural rainfall and the frequency of simulated rainfalls of certain characteristics, facilitate the selection of rain simulators that would best meet the needs of soil research and to reach a step closer to the standardization of rainfall simulators. DRS performance was analyzed integrally, for simulators with more than one dripper (DRS_>1) and with one dripper (DRS₌₁). A statistical analysis was performed for the performance of the DRS, wetted area, drop size, rainfall intensity, duration and kinetic energy. The analysis showed that DRS can provide rainfall that corresponds to natural rainfall, except in terms of the drop size distribution and wetted area. However, usually there are more factors that do not correspond to natural rainfall, such as the median drop size, volume and kinetic energy. Metal and plastic tubes (MT and PT) as the most present dripper types showed a strong relation between the outer diameter (OD) and drop size, while the inner diameter (ID) relation was moderate-to-weak. However, when increasing the range of MT drippers, for diameter size, the relation significance becomes very strong for bouts ID and OD. With the increase in the ID of PT, the relation deviates from the logarithmic curve that represents all drippers together. The sizes of the drops generated by the drippers are mostly in the range between 2 and 6 mm, while the number of drops smaller than 2 mm is relatively small. The intensity and duration of the simulated rain can be successfully produced to match natural values, with the most frequently simulated short-term rainfall of a high intensity. Most simulations were conducted at a fall height of up to 2 m, and then their number gradually decreases as the height gets closer to 5 m. Most simulations (58.6%) occur in the range between 20-90% KE, then 33.0% in a range of 90-100%, with only 8.4% lower than 20% KE. Full article

Recent upgrades to China’s radar network now allow for polarimetric measurements of convective systems in central China, providing an effective data set with which to evaluate the microphysics schemes employed in local squall line simulations. We compared polarimetric radar variables derived by Weather Research and Forecasting (WRF) and radar forward models and the corresponding hydrometeor species with radar observations and retrievals for a severe squall line observed over central China on 16 March 2022. Two microphysics schemes were tested and were able to accurately depict the contrast between convective and stratiform regions in terms of the drop size distribution (DSD) and reproduce the classical polarimetric signatures of the observed differential reflectivity (Z_DR) and specific differential phase (K_DP) columns. However, for the convective region, the simulated DSDs in both schemes exhibited lower proportions of large drops and lower liquid water content; by contrast, for the stratiform region, the proportion of large drops was found to be too high in the Morrison (MORR) scheme. The underprediction of ice-phase processes in the convective region, particularly the riming processes associated with graupel and hail, was likely responsible for the bias toward large raindrops at low levels. In the stratiform region, raindrop evaporation in the WRF Double-Moment 6-Class (WDM6) scheme, which partially offsets the overestimation of ice-phase processes, produced ground DSDs that more closely matched the observational data, and did not exhibit the overly strong warm-rain collisional growth processes of MORR. Full article