Precipitation Microphysics Research Articles

Retrieval of Parameters of Constrained Gamma Raindrop Size Distribution in South China

Abstract Raindrop size distributions (RSDs) retrieved from polarimetric radar observations have proven to be effective for understanding precipitation microphysics. However, the current RSD retrieval scheme from polarimetric radar observations (using radar reflectivity ZHH and differential reflectivity ZDR) in South China has been established for monsoon precipitation only. Using abundant RSD observations from 2D video disdrometers (2DVDs), this study constructs the high-precision shape–slope (μ–Λ) relationships of the constrained gamma (C-G) model for subgroups of ZHH and ZDR for not only monsoon but also premonsoon, typhoon, and dry seasons. The current RSD retrieval is only applicable for precipitation with rain rate: R > 5.0 mm h−1, and total raindrop number concentration: Nt > 1000 m−3. This study expanded the applicability of rain rate and number concentration with R > 0.5 mm h−1 and Nt > 100 m−3. The new retrieval scheme was tested in four typical rainfall cases and provided better accuracy in estimating mass-weighted mean diameters and normalized intercept parameters. The new scheme was also better suited for analyzing precipitation microphysics in South China, which helps to gain a better understanding of microphysics in various types of precipitation in this region.

X-Band Radar and Surface-Based Observations of Cold-Season Precipitation in Western Colorado’s Complex Terrain

Abstract Hydrologic processes associated with intermountain cold-season precipitation in the Upper Colorado River basin have important impacts on avalanche forecasting and water resource management. However, traditional weather radar networks struggle with observations in this complex terrain. Data collected during the Study of Precipitation, the Lower Atmosphere, and the Surface for Hydrometeorology (SPLASH) and its sister campaign, Surface Atmosphere Integrated Field Laboratory (SAIL) in the East River watershed of western Colorado, are used to examine a multistorm period from 23 December 2021 to 1 January 2022 that contributed 35% of the total winter precipitation in this watershed. Dual-polarization X-band radar and disdrometer measurements show ∼30-mm differences in precipitation amount at two sites in proximity over four distinct storm events within the period. Wind patterns, synoptic forcings, microphysical characteristics of precipitation, and surface meteorology are analyzed to explain the observed spatial variability of cold-season precipitation in complex mountainous terrain. Analysis shows that differences over time within this event are mainly accounted for by synoptic forcings, such as frontal passages; differences between sites are accounted for by the impact of variations in local wind patterns on precipitation microphysics. Patterns of surface precipitation intensity are compared and found to be correlated with X-band radar signatures; a relationship between a strong dendritic growth stage and intense low-density surface precipitation is reinforced by this study. This relationship demonstrates the importance of particle growth mechanisms on surface snowfall patterns in high-altitude complex terrain, underscoring the importance of realistic microphysical parameterizations. Significance Statement The amount and density of snowpack from western Colorado winter storms have significant impacts on water resources in the Upper Colorado River basin. Snowpack characteristics are affected by small-scale differences in how snow forms in the atmosphere. These differences are hard to study in the complex terrain of the Rockies, but data from the SPLASH and SAIL field campaigns allows us to investigate how snow crystal formation and mountain-driven wind patterns affect snow near the surface. Our study finds that snow crystal growth varies over small space and time scales and is likely controlled by the terrain beneath a given location and resultant local wind patterns. These results imply that predicting snowpack in the Rockies requires properly representing local wind patterns and crystal growth processes in models.

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

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

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.

Raindrop size distribution (DSD) retrieval from polarimetric radar observations using neural networks

As a key component of rainfall estimation, the understanding of raindrop size distribution (DSD) is a long-standing goal in meteorology and hydrology. Given that weather radar can observe the precipitation microphysics over large spatial and temporal scales, it has been broadly applied in DSD estimation. Traditional polynomial regression algorithms that correlate DSD parameters and radar signatures are still widely applied due to their simple structure and acceptable accuracy. This study proposes a new DSD retrieval model using dual-polarization radar observations based on long short-term memory (LSTM) network techniques. Three schemes able to retrieve the parameters of a normalized gamma DSD (LSTM-D0, LSTM-Nw, and LSTM-μ) are proposed with different combinations of polarimetric radar measurement inputs. All LSTM estimators exhibit better performance than the polynomial regression method. The Nash-Sutcliffe efficiency coefficient for estimates of drop median diameter (D0) and intercept parameter (Nw) increases from 0.93 and 0.70 to 0.95 and 0.93 respectively at Chilbolton station. Poor estimates of the shape parameter (μ) using the polynomial regression estimator complicate real applications, whereas the remarkable improvement of LSTM model estimation facilitates practical applications. The temporal and spatial predictability is then estimated to investigate long-term estimator performance for various radars, or at least for all radar pixels of a single radar. The predictability, measured by the Nash coefficient, increases temporally by 0.08, 0.31, and 0.39 and spatially by 0.03, 0.19, and 0.23 for the parameters D0, log10Nw, and μ respectively. This study contributes to improving quantitative precipitation estimates from radar polarimetry, enabling a better understanding of precipitation microphysics.

Top-Down Phenomenon Observed in the Outer Rainbands of Typhoon Maysak (2020): Insights from the Comparative Analysis of Cloud and Precipitation Microphysics with a Typical Precipitation Event in Northeast China

Abstract Cloud and precipitation microphysics in tropical cyclones (TCs) moving toward Northeast China may exhibit significant distinctions compared with the typical precipitation of this region. In this study, observations from ground-based particle size velocity (Parsivel) disdrometers in Liaoning Province, China, and cloud property data from the Himawari geostationary satellite were utilized to analyze the raindrop size distribution (DSD) characteristics and cloud vertical evolution associated with the outer rainbands of Typhoon Maysak (2020). A comparative analysis was conducted with a typical precipitation event in Northeast China induced by a cold vortex (cold-core low). Our findings reveal distinctive DSD characteristics related to the TC, where medium-sized raindrops dominate, with a smaller diameter but higher concentration in the TC case compared to the typical cold-vortex-induced precipitation case in Northeast China. Convective precipitation falls between maritime-like and continental-like patterns, leaning more toward continental convection. This varies significantly with TCs in Southeast China but is similar to that observed in coastal-front-like rainbands, suggesting extratropical influence. A detailed analysis of the vertical profile of cloud droplets shows a unique “top-down” phenomenon during the extratropical transition process of the TC, where the development of lower-level clouds follows that of upper-level clouds, inconsistent with previous studies and the case for comparison. Further investigation indicates the significant role of the intrusion of dry and cold air from upper levels and the presence of high humidity in low levels in driving this phenomenon. Our results will provide novel insights into cloud and precipitation microphysics associated with TCs in midlatitude regions.

Investigating Temporal Characteristics of Polarimetric and Electrical Signatures in Three Severe Storms: Insights from the VORTEX-Southeast Field Campaign

Abstract The dual-polarization radar characteristics of severe storms are commonly used as indicators to estimate the size and intensity of deep convective updrafts. In this study, we track rapid fluctuations in updraft intensity and size by objectively identifying polarimetric fingerprints such as ZDR and KDP columns, which serve as proxies for mixed-phase updraft strength. We quantify the volume of ZDR and KDP columns to evaluate their utility in diagnosing temporal variability in lightning flash characteristics. Specifically, we analyze three severe storms that developed in environments with low-to-moderate instability and strong 0–6-km wind shear in northern Alabama during the 2016–17 VORTEX-Southeast field campaign. In these three cases (a tornadic supercell embedded in stratiform precipitation, a nontornadic supercell, and a supercell embedded within a quasi-linear convective system), we find that the volume of the KDP columns exhibits a stronger correlation with the total flash rate. The higher covariability of the KDP column volume with the total flash rate suggests that the overall electrification and precipitation microphysics were dominated by cold cloud processes. The lower covariability with the ZDR column volume indicates the presence of nonsteady updrafts or a less prominent role of warm rain processes in graupel growth and subsequent electrification. Furthermore, we observe that the majority of cloud-to-ground (CG) lightning strikes a carried negative charge to the ground. In contrast to findings from a tornadic supercell over the Great Plains, lightning flash initiations in the Alabama storms primarily occurred outside the footprint of the ZDR and KDP column objects. Significance Statement This study quantifies the correlation between mixed-phase updraft intensity and total lightning flash rate in three severe storms in northern Alabama. In the absence of direct updraft velocity measurements, we use polarimetric signatures, such as ZDR and KDP columns, as proxies for updraft strength. Our analysis of polarimetric radar and lightning mapping array data reveals that the lightning flash rate is more highly correlated with the KDP column volume than with the ZDR column volume in all three storms examined. This contrasts with previous findings in storms over the central Great Plains, where the ZDR column volume showed higher covariability with flash rate. Interestingly, lightning initiation in the Alabama storms mainly occurred outside the ZDR and KDP column areas, contrary to previous findings.

Seasonal variations in microphysics of convective and stratiform precipitation over North China revealed by GPM dual-frequency precipitation radar

Seasonal variations in microphysics of convective and stratiform precipitation over North China revealed by GPM dual-frequency precipitation radar

In situ observations of rain rate and precipitation microphysics over the coastal area of South China: Perspectives for satellite validation

Abstract This study investigates precipitation observed by a set of collocated ground-based instruments in Zhuhai, a coastal city located at the southern tip of the Pearl River Delta of Guangdong Province in South China. Seven months of ground-based observations from a tipping-bucket rain gauge (RG), two laser disdrometers (PARSIVEL and PWS), and a vertically-pointing Doppler Micro Rain Radar-2 (MRR), spanning from December 2021 to July 2022, are statistically evaluated to provide a reliable reference for China’s spaceborne precipitation measurement mission. Rainfall measurement discrepancies are found between the instruments, though the collocated deployment mitigates uncertainties originating from spatial/temporal variabilities of precipitation. The RG underestimates hourly rain amounts at the observation site, opposite to previous studies, leading to 18.2% percent bias (Pbias) of hourly rain amounts when compared to the PARSIVEL. With the same measurement principle, the hourly-accumulated rain between the two laser disdrometers has a Pbias of 15.3%. Discrepancies between MRR and disdrometers are assumed to be due to different temporal/spatial resolution, instrument sensitivities and observation geometry, with a Pbias of mass-weighted mean diameter and normalized intercept parameter of gamma size distribution less than 9%. The vertical profiles of drop size distribution (DSD) derived from the MRR are further examined during extreme rainfalls in the East Asia monsoon season (May, June, and July). Attributed to the abundant moisture which favors the growth of raindrops, coalescence is identified as the predominant effective process and the raindrop mass-weighted mean diameter increases by 33.7% when falling from 2000 m to 600 m during the extreme precipitation event in May.

An Airborne Multifrequency Microwave Analysis of Precipitation within Two Winter Cyclones

Abstract NASA’s Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign gathered data using “satellite-simulating” (albeit with higher-resolution data than satellites currently provide) and in situ aircraft to study snowstorms, with an emphasis on banding. This study used three IMPACTS microwave instruments—two passive and one active—chosen for their sensitivity to precipitation microphysics. The 10–37-GHz passive frequencies were well suited for detecting light precipitation and differentiating rain intensities over water. The 85–183-GHz frequencies were more sensitive to cloud ice, with higher cloud tops manifesting as lower brightness temperatures, but this did not necessarily correspond well to near-surface precipitation. Over land, retrieving precipitation information from radiometer data is more difficult, requiring increased reliance on radar to assess storm structure. A dual-frequency ratio (DFR) derived from the radar’s Ku- and Ka-band frequencies provided greater insight into storm microphysics than reflectivity alone. Areas likely to contain mixed-phase precipitation (often the melting layer/bright band) generally had the highest DFR, and high-altitude regions likely to contain ice usually had the lowest DFR. The DFR of rain columns increased toward the ground, and snowbands appeared as high-DFR anomalies. Significance Statement Winter precipitation was studied using three airborne microwave sensors. Two were passive radiometers covering a broad range of frequencies, while the other was a two-frequency radar. The radiometers did a good job of characterizing the horizontal structure of winter storms when they were over water, but struggled to provide detailed information about winter storms when they were over land. The radar was able to provide vertically resolved details of storm structure over land or water, but only provided information at nadir, so horizontal structure was less well described. The combined use of all three instruments compensated for individual deficiencies, and was very effective at characterizing overall winter storm structure.

Study of Microphysical Signatures Based on Spectral Polarimetry during the RELAMPAGO Field Experiment in Argentina

Abstract Weather radars with dual-polarization capabilities enable the study of various characteristics of hydrometeors, including their size, shape, and orientation. Radar polarimetric measurements, coupled with Doppler information, allow for analysis in the spectral domain. This analysis can be leveraged to reveal valuable insight into the microphysics and kinematics of hydrometeors in precipitation systems. This paper uses spectral polarimetry to investigate precipitation microphysics and kinematics in storm environments observed during the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) field experiment in Argentina. This study uses range–height indicator scan measurements from a C-band polarimetric Doppler weather radar deployed during the field campaign. In this work, the impact of storm dynamics on hydrometeors is studied, including the size sorting of hydrometeors due to vertical wind shear. In addition, particle microphysical processes because of aggregation and growth of ice crystals in anvil clouds, as well as graupel formation resulting from the riming of ice crystals and dendrites, are also analyzed here. The presence of different particle size distributions because of the mixing of hydrometeors in a sheared environment and resulting size sorting has been reported using spectral differential reflectivity (sZdr) slope. Spectral reflectivity sZh and sZdr have also been used to understand the signature of ice crystal aggregation in an anvil cloud. The regions of pristine ice crystals are identified from vertical profiles of spectral polarimetric variables in anvil cloud because of sZh < 0 dB and sZdr values around 2 dB. It is also found that the growth process of these ice crystals causes a skewed bimodal sZh spectrum due to the presence of both pristine ice crystals and dry snow. Next, graupel formation due to riming has been studied, and it is found that the riming process produces sZh values of about 10 dB and corresponding sZdr values of 1 dB. This positive sZdr indicates the presence of needle/columnar secondary ice particles formed by ice multiplication processes in the riming zones. Last, the temporal evolution of a storm is investigated by analyzing changes in hydrometeor types with time and their influence on the spectral polarimetric variables.

Diurnal Variation Characteristics of Raindrop Size Distribution Observed by a Parsivel2 Disdrometer in the Ili River Valley

The diurnal variation characteristics of raindrop size distribution (RSD) in the Ili River Valley are investigated in this study, using the RSD data from May to September during 2020-2021 collected by a Parsivel2 disdrometer in Zhaosu. Significant diurnal variations (02–07, 08–13, 14–19, and 20-01 local standard time (LST)) of precipitation and RSD in Zhaosu are revealed during the rainy seasons. Precipitation mainly occurs in the late afternoon and early evening. A higher concentration of small raindrops is observed in the morning, whereas more mid-size and large raindrops are observed in the afternoon. The RSD exhibits diurnal differences between different rainfall rate classes; the diurnal difference of RSD is more pronounced in the case of high rainfall rates. Stratiform precipitation can occur at any time of the day, yet convective precipitation mainly occurs during the late afternoon and early evening. The RSD of stratiform rainfall shows a similar distribution over the four time periods. For convective rainfall, the concentration of small raindrops is the highest (lowest) over 02–07 (14–19) LST, while the highest (lowest) concentration of medium and large drops is observed over 14–19 (02–07) LST. Convective rain in the Ili River Valley over 14–19 LST can be characterized as the continental convective cluster, while in the rest time of the day, it is neither in the maritime cluster nor in the continental cluster. The empirical relationships between the radar reflectivity factor and rainfall rate (Z-R) for stratiform and convective rain types are also derived. The purpose of this study is to advance our understanding of precipitation microphysics in arid mountainous region.

Influences of Summer Precipitation Occurrence Time on Raindrop Spectrum Characteristics over the Northeastern Tibetan Plateau

The impact of unique terrain on the microphysics of nighttime precipitation on the Tibetan Plateau (TP) has not been fully appreciated, due to a lack of observation. In this study, we used three raindrop spectrometers deployed in the northeastern TP to analyze the characteristics of the raindrop spectrum during two types of summer precipitation. These two types are classified according to their occurrence times: one starting in the daytime and lasting into the night (DP), while the other started at night and continuing into the daytime (NP). The results show that precipitation with a rain rate ranging from 1.0 to 5.0 mm h−1 contributes the most to the total precipitation, with this contribution rate being higher in the NP than in the DP. All the raindrop spectra follow a single-peak distribution pattern, and the logarithm of the generalized intercept parameter (lgNw) rises with the rain rate. The spectral widths of the DP-n (the nighttime part of the DP) are broader than those of the DP-d (the daytime part of the DP). Moreover, the average lgNw and mass-weighted mean diameter (Dm) over the northeastern TP were 2.65 mm−1 mm−3 and 1.04 mm, respectively, both of which are smaller than their equivalents in the plains. In addition, the gamma distribution can better fit the raindrop size distributions of the two types of precipitation. It is found that precipitation is more likely to occur over the TP at night. The characteristics of NP are reflected in two aspects. First, the sample size of the precipitation at the rain rate of 1.0–5.0 mm h−1 is higher in the NP-n (the nighttime part of the NP), and the precipitation at this rain rate contributes the most to the total precipitation. Second, for the same rain rate, the precipitation particles in the NP-n are larger.

Helios and Juliette: Two falsely acclaimed medicanes?

The present work analyzes the synoptic, thermodynamic, and microphysics characteristics of two Mediterranean cyclones that occurred in February–March 2023. The analysis is mainly carried out through the use of passive microwave (PMW) satellite measurements, which allow us to follow the cyclones' evolution and state whether Helios and Juliette can be considered as Mediterranean tropical-like cyclones (i.e., medicanes). Both cyclones show a very similar evolution, with a low-stratospheric warm air anomaly during the development phase, followed by the development of a warm anomaly in the low−/mid-troposphere. This feature is often observed in medicanes (e.g., Qendresa, Zorbas), except for few cases (i.e., Medicane Ianos, which shows a warm core (WC) development clearly driven by diabatic processes without a preliminary warming signal in the lower stratosphere and upper troposphere). The analysis carried out highlights that, while Helios maintains this setting through its whole lifetime, Juliette undergoes tropical transition in the final stage of its evolution. As opposed to most medicane cases, the PMW precipitation microphysics diagnostics shows the predominance of shallow clouds, with almost total absence of ice hydrometeors and deep convection in the proximity of the WC center (i.e., within 100 km radius) for Helios and during the initial stage of Juliette. PMW radiometry provides strong indication that diabatic heating plays a role in the WC development when the onset of deep convection features is identified in the proximity of the Juliette cyclone center. Moreover, the PMW cloud-top height product does not show a closed cloud-free eye for Helios, while it is observed for the final stage of Juliette as often happens during medicanes' mature phase. Therefore, we deem that while Helios can be labeled as a warm seclusion, Juliette can be included in the tropical-like cyclone category.

Distinct secondary ice production processes observed in radar Doppler spectra: insights from a case study

Abstract. Secondary ice production (SIP) has an essential role in cloud and precipitation microphysics. In recent years, substantial insights were gained into SIP by combining experimental, modeling, and observational approaches. Remote sensing instruments, among them meteorological radars, offer the possibility of studying clouds and precipitation in extended areas over long time periods and are highly valuable to understand the spatiotemporal structure of microphysical processes. Multi-modal Doppler spectra measured by vertically pointing radars reveal the coexistence, within a radar resolution volume, of hydrometeor populations with distinct properties; as such, they can provide decisive insight into precipitation microphysics. This paper leverages polarimetric radar Doppler spectra as a tool to study the microphysical processes that took place during a snowfall event on 27 January 2021 in the Swiss Jura Mountains during the ICE GENESIS campaign. A multi-layered cloud system was present, with ice particles sedimenting through a supercooled liquid water (SLW) layer in a seeder–feeder configuration. Building on a Doppler peak detection algorithm, we implement a peak labeling procedure to identify the particle type(s) that may be present within a radar resolution volume. With this approach, we can visualize spatiotemporal features in the radar time series that point to the occurrence of distinct mechanisms during different stages of the event. By focusing on three 30 min phases of the case study and by using the detailed information contained in the Doppler spectra, together with dual-frequency radar measurements, aircraft in situ images, and simulated profiles of atmospheric variables, we narrow down the possible processes that could be responsible for the observed signatures. Depending on the availability of SLW and the droplet sizes, on the temperature range, and on the interaction between the liquid and ice particles, various SIP processes are identified as plausible, with distinct fingerprints in the radar Doppler spectra. A simple modeling approach suggests that the ice crystal number concentrations likely exceed typical concentrations of ice-nucleating particles by 1 to 4 orders of magnitude. While a robust proof of occurrence of a given SIP mechanism cannot be easily established, the multi-sensor data provide various independent elements each supporting the proposed interpretations.

Particle inertial effects on radar Doppler spectra simulation

Abstract. Radar Doppler spectra observations provide a wealth of information about cloud and precipitation microphysics and dynamics. The interpretation of these measurements depends on our ability to simulate these observations accurately using a forward model. The effect of small-scale turbulence on the radar Doppler spectra shape has been traditionally treated by implementing the convolution process on the hydrometeor reflectivity spectrum and environmental turbulence. This approach assumes that all the particles in the radar sampling volume respond the same to turbulent-scale velocity fluctuations and neglects the particle inertial effect. Here, we investigate the inertial effects of liquid-phase particles on the forward modeled radar Doppler spectra. A physics-based simulation (PBS) is developed to demonstrate that big droplets, with large inertia, are unable to follow the rapid change of the velocity field in a turbulent environment. These findings are incorporated into a new radar Doppler spectra simulator. Comparison between the traditional and newly formulated radar Doppler spectra simulators indicates that the conventional simulator leads to an unrealistic broadening of the spectrum, especially in a strong turbulent environment. This study provides clear evidence to illustrate the droplet inertial effect on radar Doppler spectrum and develops a physics-based simulator framework to accurately emulate the Doppler spectrum for a given droplet size distribution (DSD) in a turbulence field. The proposed simulator has various potential applications for the cloud and precipitation studies, and it provides a valuable tool to decode the cloud microphysical and dynamical properties from Doppler radar observation.

Seasonal variations in precipitation microphysics over East China based on GPM DPR observations

The disdrometer-observed raindrop size distribution (DSD) in East China has been shown to vary across seasons and rainfall types. In this study, as an extensive research, the seasonal variations of vertical structures and associated microphysical processes of precipitation were investigated using nine-year measurements of dual-frequency precipitation radar on board the Global Precipitation Measurement satellite. The spatial distribution and vertical profiles of the reflectivity factor (Ze), mass-weighted mean diameter (Dm), and generalized intercept parameter (Nw) showed different magnitudes of variability among seasons (and rain types). Generally, the collisional-coalescence process was dominant for sufficient raindrop growth in convective precipitation, followed by the breakup of melted large ice particles. Summer convective precipitation exhibited typical monsoonal features with the largest Ze and Dm values, whereas extremely weak winter convective precipitation exhibited stratiform-like characteristics. For stratiform precipitation, the major microphysical processes were competitive between the breakup and coalescence processes during different seasons. In contrast, collisional coalescence was predominant in the shallow convective precipitation throughout the year. The distribution of rainfall and DSD parameters with respect to storm top height also varied. Specifically, the storm (convective core) top converged around the upper (middle) troposphere during extreme rainfall, indicating moderate convection where Dm reached its maximum with moderate log10Nw. Warm-rain processes also play an important role in raindrop growth. Moreover, the discrepancies between the extreme rainfall and the highest echo top suggest a weak linkage between the heaviest rainfall and tallest storms. This study provides a comprehensive picture of the seasonal variability in precipitation microphysics in East China.

Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product

Abstract. The Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission is a joint endeavour developed by the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) and features a 94 GHz Doppler Cloud Profiling Radar. This paper presents the theoretical basis of the cloud and precipitation microphysics (C-CLD) EarthCARE Level 2 (L2) algorithm. The C-CLD algorithm provides the best estimates of the vertical profiles of water mass content and hydrometeor characteristic size, obtained from radar reflectivity, path-integrated signal attenuation and hydrometeor sedimentation Doppler velocity estimates using optimal estimation (OE) theory. To obtain the forward model relations and the associated uncertainty, an ensemble-based method is used. This ensemble consists of a collection of in situ measured drop size distributions that cover natural microphysical variability. The ensemble mean and standard deviation represent the forward model relations and their microphysics-based uncertainty. The output variables are provided on the joint standard grid horizontal and EarthCARE Level 1b (L1b) vertical grid (1 km along track and 100 m vertically). The OE framework is not applied to liquid-only clouds in drizzle-free and lightly drizzling conditions, where a more statistical approach is preferred.

Precipitation Microphysics of Locally-Originated Typhoons in the South China Sea Based on GPM Satellite Observations

Locally-originated typhoons in the South China Sea (SCS) are characterized by long duration, complex track, and high probability of landfall, which tend to cause severe wind, rainstorm, and flood disasters in coastal regions. Therefore, it is of great significance to conduct research on typhoon precipitation microphysics in the SCS. Using GPM satellite observations, the precipitation microphysics of typhoons in the SCS are analyzed by combining case and statistical studies. The precipitation of Typhoon Ewiniar (2018) in the SCS is found to be highly asymmetric. In the eyewall, the updraft is strong, the coalescence process of particles is distinct, and the precipitation is mainly concentrated in large raindrops. In the outer rainbands, the “bright-band” of melting layer is distinct, the melting of ice particles and the evaporation of raindrops are distinct, and there exist a few large raindrops in the precipitation. Overall, the heavy precipitation of typhoons in the SCS is composed of higher concentration of smaller raindrops than that in the western Pacific (WP), leading to a more “oceanic deep convective” feature of typhoons in the SCS. While the heavy precipitation of typhoons in the SCS is both larger in drop size and number concentration than that in the North Indian Ocean (NIO), leading to more abundant rainwater of typhoons in the SCS. For the relatively weak precipitation (R < 10 mm h−1), the liquid water path (LWP) of typhoons in the SCS is higher than that of the NIO, while the ice water path (IWP) of the locally-originated typhoons in the SCS is lower than that of the WP. For the heavy precipitation (R ≥ 10 mm h−1), the LWP and IWP of typhoons in the SCS are significantly higher than those in the WP and NIO.

Evaluating Simulated Microphysics of Stratiform and Convective Precipitation in a Squall Line Event Using Polarimetric Radar Observations

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 (ZDR) and specific differential phase (KDP) 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.