Warm Rain Research Articles

An Investigation on Microphysical Characteristics of Early‐, Late‐, and Post‐Mei‐yu Season Rainfall Over Taiwan

AbstractOver Taiwan, Mei‐yu season (May and June), which is primarily linked to frontal systems, is the transition period between winter and summer. Using the Global Precipitation Measurement Mission dual‐frequency precipitation radar (GPM DPR), the current study examined the rain and microphysical characteristics of the Mei‐yu season in Taiwan. In order to examine the areal and intra‐seasonal aspects, May and June months are divided into three sub‐seasons: early‐Mei‐yu, late‐Mei‐yu, and post‐Mei‐yu. The three sub‐seasons exhibited differences in rainfall and raindrop size distributions, with abundance of large drops in the post‐Mei‐yu. Additionally, there were noticeable variations in the raindrop size distributions among the south, central, north, and eastern parts of Taiwan, with more large drops in central Taiwan. To comprehend the microphysical progressions causing the regional and intra‐seasonal fluctuations, CFADs (contoured frequency by altitude diagrams) of rain parameters are utilized. Compared to other two sub‐seasons, the early‐Mei‐yu season exhibited weaker convection. Dominance of stratiform precipitation in late‐Mei‐yu season, and convective precipitation in post‐Mei‐yu season resulted in higher rainfall amounts in these two sub‐seasons (more particularly in post‐Mei‐yu) than the early‐Mei‐yu season. Examination of warm rain microphysical processes (below 5 km height) among these sub‐seasons revealed that the early‐Mei‐yu season is dominated with break‐up process, late‐Mei‐yu season with breakup and coalescence balance, and post‐Mei‐yu with coalescence, size‐sorting and evaporation processes.

The Interaction Between Climate Forcing and Feedbacks

AbstractA Perturbed Parameter Ensemble (PPE) with the Community Atmosphere Model version 6 (CAM6) is used to better understand the sensitivity of aerosol forcing and cloud feedbacks to changes in model processes. Aerosol forcing through aerosol‐cloud interactions is mostly negative (a cooling) due to shortwave radiation, while feedbacks are positive or negative in different regions due to contrasting longwave and shortwave effects. Both forcing and feedbacks are related to the mean climate state. Higher magnitude cloud radiative effects generally mean larger magnitude net negative forcing and larger magnitude net positive feedback. Aerosol forcing is broadly related to the susceptibility of clouds to drop number. Feedbacks also related to susceptibility, but to a lesser extent and in different regions to aerosol forcing. Aerosol forcing and cloud feedbacks are anti‐correlated in the CAM6 PPE such that stronger negative forcing is associated with stronger positive feedbacks. Even the processes governing forcing and feedback sensitivity in the PPE are similar. These include the warm rain formation process, ice loss processes and deep convective intensity.

Large effects of fine and coarse aerosols on tropical deep convective systems throughout their lifecycle

Previous studies have shown that aerosols invigorate deep convective systems (DCS). However, the magnitude or even the existence of aerosol invigoration of DCS remains controversial. Here, we aimed to observationally quantify the full aerosol effects on DCS by tracking their entire lifecycle and spatial extent in tropical regions. We found that fine aerosols (FA) can invigorate DCS, making them taller and longer lived, and resulting in up to ×5 increase in total area and rainfall amount. In contrast, added coarse sea salt aerosols (CSA) over the ocean can inhibit the vertical development of DCS through enhancing warm rain formation, yet resulting in longer lived and extensive DCSs. Notably, combining FA and CSA generates the strongest aerosol invigoration effect at the concentrations of ~5 and ~80 μg/m³, leading up to ×10 increase in rainfall amount. Our results indicate that aerosols significantly redistribute convective precipitation and climate effects, greatly underestimated in previous studies.

Combined effects of fine and coarse marine aerosol on vertical raindrop size distribution

Climate models commonly overestimate warm rain frequency and underestimate its intensity over the ocean, primarily due to insufficient representation of the aerosol effects. This pertains to both fine aerosols (FA) and coarse sea spray aerosols (CSA), where the latter is mostly absent in the models. Here, our observations show that adding CSA enhances vertical warm rain structure, in contrast to the effect of FA. The magnitude of the effect of CSA is larger than the opposite effect of the FA. For rain with top heights of 2–3 km, the raindrop size, concentration, and rain rate can be increased by factors of 1.03, 1.47, and 1.60, respectively. These CSA-induced changes are larger for thicker clouds, reaching a maximum by factors of 1.12, 1.85, and 2.21, respectively. Therefore, the combined FA and CSA effects should be incorporated into climate models for accurately simulated precipitation microphysical processes.

Holocene insolation and sea surface temperature influences on the polar front jet stream and precipitation in the midcontinental United States

Variability in the source and seasonality of precipitation in the midcontinental United States during the Holocene was investigated using isotopic and sedimentological data from Martin Lake, northeastern Indiana, USA. Between 7100 and 4000 years before present (yr BP; present = 1950 CE), high δ18Ocal and δ13Ccal values with low variability indicate that moisture was predominantly derived from subtropical, southerly sources and delivered primarily during the warm season. Mean state shifts toward lower δ18Ocal and δ13Ccal occurred at ca. 4000 and 2550 yr BP, respectively, indicating an increase in northerly-sourced cold-season precipitation during the Late Holocene (i.e., the past 4200 years) and a subsequent reduction in warm season duration after 2550 yr BP. Record low %lithics from ca. 5000 to 4000 yr BP indicates major reductions in warm-season rain storms, consistent with regional evidence of drought at this time. An increase in the amplitude of centennial-scale variability in δ18Ocal, δ13Ccal, and %lithics after 1900 yr BP indicates greater precipitation source variability during the Common Era. During this interval, precipitation fluctuated between southerly-sourced, convective rainstorms when the Northern Hemisphere (NH) was warm (e.g., during the Medieval Climate Anomaly; 700–1000 yr BP) and northerly-sourced rain and snow when the NH was cool (e.g., during the Little Ice Age; 150–550 yr BP). These trends, especially the change at ca. 4000 yr BP, are consistent with other North American paleoclimate records that collectively suggest a continental-scale shift in precipitation seasonality during the Middle to Late Holocene transition as the tropical Pacific Ocean transitioned from La Niña-like conditions to a more El Niño-like mean state. Concurrent NH cooling and persistent El Niño-like conditions during the Late Holocene would have favored a southerly polar front jet stream with enhanced ridge and trough atmospheric circulation over North America – conditions resembling the positive mode of the Pacific-North American teleconnection (PNA). This would have increased interactions between high-latitude and subtropical airmasses over the midcontinent, increasing the proportion of northerly precipitation with low δ18O delivered during the cold season (i.e., snowfall) and during extended periods with +PNA-like atmospheric circulation (e.g., the Little Ice Age).

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.

Reduced‐Order Modeling for Linearized Representations of Microphysical Process Rates

AbstractRepresenting cloud microphysical processes in large scale atmospheric models is challenging because many processes depend on the details of the droplet size distribution (DSD, the spectrum of droplets with different sizes in a cloud). While full or partial statistical moments of droplet size distributions are the typical variables used in bulk models, prognostic moments are limited in their ability to represent microphysical processes across the range of conditions experienced in the atmosphere. Microphysical parameterizations employing prognostic moments are known to suffer from structural uncertainty in their representations of inherently higher dimensional cloud processes, which limit model fidelity and lead to forecasting errors. Here we investigate how data‐driven reduced‐order modeling can be used to learn predictors for microphysical process rates in bulk microphysics schemes in an unsupervised manner from higher dimensional bin distributions. Using simulations characteristic of marine stratiform clouds, we simultaneously learn lower dimensional representations of droplet size distributions and predict the evolution of the microphysical state of the system. Droplet collision‐coalescence, the main process for generating warm rain, is estimated to have an intrinsic dimension of three. This intrinsic dimension provides a lower limit on the number of degrees of freedom needed to accurately represent collision‐coalescence in models. We demonstrate how deep learning based reduced‐order modeling can be used to discover intrinsic coordinates describing the microphysical state of the system, where process rates such as collision‐coalescence are globally linearized. These implicitly learned representations of the DSD retain more information about the DSD than typical moment‐based representations.

A comprehensive analysis of uncertainties in warm rain parameterizations in climate models based on in situ measurements

Abstract Because of the coarse grid size of Earth system models (ESM), representing warm-rain processes in ESMs is a challenging task involving multiple sources of uncertainty. Previous studies evaluated warm-rain parameterizations mainly according to their performance in emulating collision-coalescence rates for local droplet populations over a short period of a few seconds. The representativeness of these local process rates comes into question when applied in ESMs for grid sizes on the order of 100 kilometers and time steps on the order of 20-30 minutes. We evaluate several widely used warm-rain parameterizations in ESM application scenarios. In the comparison of local and instantaneous autoconversion rates, the two parameterization schemes based on numerical fitting to stochastic collection equation (SCE) results perform best. However, because of Jessen’s inequality, their performance deteriorates when grid-mean, instead of locally-resolved, cloud properties are used in their simulations. In contrast, the effect of Jessen’s inequality partly cancels the overestimation problem of two semi-analytical schemes, leading to an improvement in the ESM-like comparison. In the assessment of uncertainty due to the large time step of ESMs, it is found that the rain-water tendency simulated by the SCE is roughly linear for time steps smaller than 10 minutes, but the nonlinearity effect becomes significant for larger time steps, leading to errors up to a factor of 4 for a time step of 20 minutes. After considering all uncertainties, the grid-mean and time-averaged rain-water tendency based on the parameterization schemes are mostly within a factor of 4 of the local benchmark results simulated by SCE.

Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol–cloud interactions

Abstract. Process-oriented observational constraints for the anthropogenic effective radiative forcing due to aerosol–cloud interactions (ERFaci) are highly desirable because the uncertainty associated with ERFaci poses a significant challenge to climate prediction. The contoured frequency by optical depth diagram (CFODD) analysis supports the evaluation of model representation of cloud liquid-to-rain conversion processes because the slope of a CFODD, generated from joint MODerate Resolution Imaging Spectroradiometer (MODIS)-CloudSat cloud retrievals, provides an estimate of cloud droplet collection efficiency in single-layer warm liquid clouds. Here, we present an updated CFODD analysis as an observational constraint on the ERFaci due to warm rain processes and apply it to the U.S. Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2). A series of sensitivity experiments shows that E3SMv2 droplet collection efficiencies and ERFaci are highly sensitive to autoconversion, i.e., the rate of mass transfer from cloud liquid to rain, yielding a strong correlation between the CFODD slope and the shortwave component of ERFaci (ERFaciSW; Pearson's R=-0.91). E3SMv2's CFODD slope (0.20 ± 0.04) is in agreement with observations (0.20 ± 0.03). The strong sensitivity of ERFaciSW to the CFODD slope provides a useful constraint on highly uncertain warm rain processes, whereby ERFaciSW, constrained by MODIS-CloudSat, is estimated by calculating the intercept of the linear association between the ERFaciSW and the CFODD slopes, using the MODIS-CloudSat CFODD slope as a reference.

In-situ observations of cloud microphysics over Arabian Sea during dust transport events

The unique in situ measurements of clouds and precipitation within the shallow and deep cumulus over the north-eastern Arabian Sea region during the Indian monsoon are illustrated in this study with a focus on droplet spectral parameters. The observational period showed a significant incursion of Arabian dust and the presence of giant cloud condensation nuclei (GCCN), modifying the cloud and precipitation spectral properties. Warm rain microphysics supported the mixed-phase development in these clouds and exhibited hydrometeors of snow, graupel and large aggregates as part of ice processes. Cloud base droplet number concentration is about 142 ± 79 cm−3 which is one third of the cloud condensation nuclei (CCN) number concentration at 0.2% supersaturation. A rapid broadening of droplet size distribution (DSD) near to the cloud base was noted in contrast to polluted continental clouds. Relationship between the relative dispersion ( ε; the ratio of DSD spectral width ( σ ) to mean radius ( rm )) and liquid water adiabatic fraction (AF) indicates that the entrainment effect has increased relative dispersion significantly (2–3 times larger) in these clouds. Effective radius ( reff ) is found to be proportional to mean volume radius ( rv ) with a proportionality constant ( β ) that varies between 1.0–1.6, depending on the spectral dispersion parameter. Drop size distributions for the small cloud droplets with size range 2–50 μ m and the large drizzle drops (or ice hydrometeors) with size range 100–6400 μ m are parameterized using the gamma function distributions useful for large-scale cloud models.

Aerosol influence on cloud macrophysical and microphysical properties over the Tibetan Plateau and its adjacent regions.

This study uses aerosol optical depth (AOD) and cloud properties data to investigate the influence of aerosol on the cloud properties over the Tibetan Plateau and its adjacent regions. The study regions are divided as the western part of the Tibetan Plateau (WTP), the Indo-Gangetic Plain (IGP), and the Sichuan Basin (SCB). All three regions show significant cloud effects under low aerosol loading conditions. In WTP, under low aerosol loading conditions, the effective radius of liquid cloud particles (LREF) decreases with the increase of aerosol loading, while the effective radius of ice cloud particles (IREF) and cloud top height (CTH) increase during the cold season. Increased aerosol loading might inhibit the development of warm rain processes, transporting more cloud droplets above the freezing level and promoting ice cloud development. During the warm season, under low aerosol loading conditions, both the cloud microphysical (LREF and IREF) and macrophysical (cloud top height and cloud fraction) properties increase with the increase of aerosol loading, likely due to higher dust aerosol concentration in this region. In IGP, both LREF and IREF increase with the increase in aerosol loading during the cold season. In SCB, LREF increases with the increase in aerosol loading, while IREF decreases, possibly due to the higher hygroscopic aerosol concentration in the SCB during the cold season. Meteorological conditions also modulate the aerosol-cloud interaction. Under different convective available potential energy (CAPE) and relative humidity (RH) conditions, the influence of aerosol on clouds varies in the three regions. Under low CAPE and RH conditions, the relationship between LREF and aerosol in both the cold and warm seasons is opposite in the WTP: LREF decreases with the increase of aerosol in the cold season, while it increases in the warm season. This discrepancy may be attributed to a difference in the moisture condition between the cold and warm seasons in this region. In general, the influence of aerosols on cloud properties in TP and its adjacent regions is characterized by significant nonlinearity and spatial variability, which is likely related to the differences in aerosol types and meteorological conditions between different regions.

Large‐Scale Tropical Circulation Intensification by Aerosol Effects on Clouds

AbstractThis study addresses a critical gap in understanding anthropogenic influences on tropical climate dynamics by investigating the impact of aerosol‐cloud interactions on large‐scale circulation. Despite extensive research on greenhouse gas‐induced warming and its effects on tropical circulation, the impact of aerosols, particularly their interactions with clouds, on large‐scale circulation remains understudied. Utilizing large‐domain radiative convective equilibrium cloud‐resolving simulations, this research demonstrates that increasing aerosol concentration intensifies tropical overturning circulation, evaluated at the mid‐troposphere , strongly correlating with domain mean cloud and radiative properties. Employing a weak temperature gradient approximation, I attribute variations in to changes in clear‐sky radiative cooling rather than stability. These radiative cooling changes are linked to humidity changes driven by warm rain suppression by aerosols. This study's findings underscore the need to take into account microphysical changes, particularly aerosol concentrations, when studying anthropogenic effects on tropical circulation.

Meteorological Characteristics of a Continuous Ice-Covered Event on Ultra-High Voltage Transmission Lines in Yunnan Region in 2021

Yunnan plays a pivotal role in transmitting electricity from west to east within China’s Southern Power Grid. During 7–13 January 2021, a large-scale continuous ice-covering event of ultra-high voltage (UHV) transmission lines occurred in the Qujing area of eastern Yunnan Province. Based on ERA5 reanalysis data and meteorological observation data of UHV transmission line icing in China’s Southern Power Grid, the synoptic causes of the icing are comprehensively analyzed from various perspectives, including weather situations, vertical stratification of temperature and humidity, local meteorological elements, and atmospheric circulation indices. The results indicate a strong East Asian trough and a blocking high directing northern airflow southward ahead of the ridge. Cold air enters the Qujing area and combines with warm and moist air from the subtropical high pressure of 50–110° E. As warm and cold air masses form a quasi-stationary front over the northern mountainous area of Qujing due to topographic uplift, the mechanism of “supercooling and warm rain” caused by the “warm–cold” temperature profile structure leads to freezing rain events. Large-scale circulation indices in the Siberian High, East Asian Trough, and 50–110° E Subtropical High regions provided clear precursor signals within 0–2 days before the icing events.

Turbulence as a Key Driver of Ice Aggregation and Riming in Arctic Low‐Level Mixed‐Phase Clouds, Revealed by Long‐Term Cloud Radar Observations

AbstractTurbulence in clouds is known to enhance particle collision rates, as widely demonstrated for warm rain formation. A similar impact on ice growth processes is expected but a solid observational basis is missing. A statistical analysis of a 15‐month data set of cloud radar observations allows for the first time to quantify the impact of turbulence on ice aggregation and riming in Arctic low‐level mixed‐phase clouds. Increasing eddy dissipation rate (EDR), from below 10−4 to above 10−3 m2 s−3, yields larger ice aggregates, and higher particle concentration, likely caused by increasing fragmentation. In conditions more favorable to riming, higher EDR is associated with dramatically higher particle fall velocities (by up to 125%), under similar liquid water paths, indicative of markedly higher degrees of riming. Our findings thus reveal the key role of turbulence for cold precipitation formation, and highlight the need for an improved understanding of turbulence‐hydrometeor interactions in cold clouds.

A Theory for the Balance between Warm Rain and Ice Crystal Processes of Precipitation in Mixed-Phase Clouds

Abstract Mixed-phase clouds contain both supercooled cloud liquid and ice crystals. In principle, precipitation may be initiated either by the liquid phase or by the ice phase. Ice crystals may grow by vapor diffusion to become snow (“ice crystal process”), forming “cold” precipitation. Equally, cloud droplets, when large enough, coalesce to form “warm” precipitation by the “warm rain process.” Warm rain could be supercooled and freeze as “warm” graupel. In the present paper, a new simplified theoretical analysis is provided to examine the microphysical system consisting of three species of hydrometeor, namely, cloud liquid, “cold ice” (crystals, snow), and “warm rain” (frozen or supercooled). This is obtained by nondimensionalizing and simplifying the evolution equations for the mass of each species. Analytical formulas are given for equilibria. Feedback analysis shows that the sign of the feedback is linked to the abundance of precipitation, with a neutral surface in the 3D phase space. The system’s precipitation amount explodes while in the initial unstable regime, crossing the neutral surface and approaching the equilibrium point that is a stable attractor. Positive and negative feedbacks are elucidated. In a standard case, the cold ice mass is about 1000 times larger than the warm rain mass. To illustrate the physical behavior of the theory, sensitivity tests are performed with respect to environmental conditions (e.g., aerosol, updraft speed) and microphysical parameters (e.g., riming and sedimentation rates for cold ice). Cold ice prevails, especially in fast ascent, due to its low bulk density, favoring slow sedimentation and a wide cross-sectional area for riming. Significance Statement The theory elucidates how the ice phase can prevail in the precipitation from any mixed-phase clouds with supercooled cloud liquid and crystals. The ice phase radically suppresses cloud liquid by riming when active and “wins” the competition against coalescence. This prevalence of ice is shown to arise from the low bulk density of snow. The cloud is viewed as a system of negative and positive feedbacks that prevail in realms of stability and instability in a 3D phase space.

Improving Simulations of Warm Rain in a Bulk Microphysics Scheme

Abstract Current bulk microphysical parameterization schemes underpredict precipitation intensities and drop size distributions (DSDs) during warm rain periods, particularly upwind of coastal terrain. To help address this deficiency, this study introduces a set of modifications, called RCON, to the liquid-phase (warm rain) parameterization currently used in the Thompson–Eidhammer microphysical parameterization scheme. RCON introduces several model modifications, motivated by evaluating simulations from a bin scheme, which together result in more accurate precipitation simulations during periods of warm rain. Among the most significant changes are 1) the use of a wider cloud water DSD of lognormal shape instead of the gamma DSD used by the Thompson–Eidhammer parameterization and 2) enhancement of the cloud-to-rain autoconversion parameterization. Evaluation of RCON is performed for two warm rain events and an extended period during the Olympic Mountains Experiment (OLYMPEX) field campaign of winter 2015/16. We show that RCON modifications produce more realistic precipitation distributions and rain DSDs than the default Thompson–Eidhammer configuration. For the multimonth OLYMPEX period, we show that rain rates, rainwater mixing ratios, and raindrop number concentrations were increased relative to the Thompson–Eidhammer microphysical parameterization, while concurrently decreasing raindrop diameters in liquid-phase clouds. These changes are consistent with an increase in simulated warm rain. Finally, real-time evaluation of the scheme from August 2021 to August 2022 demonstrated improved precipitation prediction over coastal areas of the Pacific Northwest. Significance Statement Although the accurate simulation of warm rain is critical to forecasting the hydrology of coastal areas and windward slopes, many warm rain parameterizations underpredict precipitation in these locations. This study introduces and evaluates modifications to the Thompson–Eidhammer microphysics parameterization scheme that significantly improve the accuracy of rainfall prediction in those regions.

Quantitative Precipitation Estimation using X-Band Radar for Orographic Rainfall in the San Francisco Bay Area

In the San Francisco Bay Area, precipitation occurs in the wintertime, mostly as rain. Wintertime rainfall can be further classified into cold or stratiform rain with a typical radar bright band signature and warm orographic rain with absence of a radar bright band. Vertical Pointing S-Band profiler radar and disdrometer measurements from two of NOAA’s Hydrometeorology Testbed (HMT) sites in California are used to study the differences in microphysical properties between these two types of rain and their implications in radar rainfall estimation. A methodology has been developed to discriminate non bright band (NBB) rainfall from bright band (BB) rainfall using reflectivity (Z) and differential reflectivity (Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DR</sub> ) computed from disdrometer data. Delineating the two rainfall types in this way allowed for an algorithm to be applied to the radar scans to identify rainfall types and apply appropriate reflectivity based and specific differential phase (K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DP</sub> ) based rainfall estimators. Recently, a gap-filling X-Band weather radar with dual-polarization capabilities was deployed in the San Francisco Bay Area in Santa Rosa to aid in weather monitoring and provide high resolution Quantitative Precipitation Estimation (QPE) products. When applied to real radar observations, this method shows great potential for improving the QPE compared to traditional operational products which more often tend to underestimate rainfall in the California coastal region.

Secondary droplet activation during condensational growth in convective clouds and its detection from satellites

By acting as cloud condensation nuclei (CCN), aerosol particles play a key role in the climate system. The CCN can be activated into cloud droplets at the cloud base (i.e., primary activation), or above it (i.e., secondary activation). This study shows the conditions required for secondary activation during the condensational growth phase in convective clouds. It also proposes a methodology for detecting this secondary activation from satellites. Using a spectral bin adiabatic parcel model, we simulate the vertical profile of cloud microphysical properties and demonstrate how different aerosol size distributions and updraft velocities greatly affect the secondary activation initiation and the cloud properties. The secondary activation slows down the cloud drop effective radius (re) growth rate with increasing height, and decreasing temperature (T), due to the relatively larger population of smaller droplets in the cloud parcel. Therefore, the vertical profile of re growth with height is slower than the adiabatic rate when the secondary activation occurs.The proposed physical principle was verified by satellite-retrieved T-re profiles and adiabatic cloud drop number concentrations (Nd) over the Amazon region. The results obtained from this study can be utilized to identify the secondary droplet activation during the condensational growth phase, which can lead to an overestimation of the retrieved Nd as well as suppression of warm rain. This improves our knowledge and observational capabilities of the role of aerosol particles in the microphysics, dynamics, and precipitation behavior of convective clouds. Plain text summarySmall particles serve as sites for cloud droplets' condensation at the cloud base (primary droplet activation) or above it (secondary activation). Once a droplet is activated at the cloud base, the surrounding water vapor condenses on it and the droplet grows - this is called condensational growth. The cloud droplet number concentrations (Nd) can be obtained by the satellite-retrieved vertical growth rate of droplet size in the condensational growth phase. However, new small droplets formed during this phase (i.e., secondary activation), might cause an overestimate in the retrieved Nd. This study presents the physical principle of secondary activation during condensational growth. Using a model, we simulate the condensational growth of aerosol particles, which act as cloud condensation nuclei (CCN), for different particle size distributions and thermodynamic conditions (i.e., vertical velocities). Our simulations show that secondary activation slows the cloud droplet growth rate with height due to the larger competition for the available water vapor promoted by the new drops. Comparisons between satellite-retrieved Nd of convective clouds and in-situ measurements show that the satellite retrievals overestimate Nd when the secondary activation of droplets is neglected. Our findings improve the understanding of aerosols' role in the condensational growth of droplets in convective clouds.

A discontinuous Galerkin approach for atmospheric flows with implicit condensation

We present a discontinuous Galerkin method for moist atmospheric dynamics, with and without warm rain. By considering a combined density for water vapour and cloud water, we avoid the need to model and compute a source term for condensation. We recover the vapour and cloud densities by solving a pointwise non-linear problem each time step. Consequently, we enforce the requirement for the water vapour not to be supersaturated implicitly. Together with an explicit time-stepping scheme, the method is highly parallelisable and can utilise high-performance computing hardware. Furthermore, the discretisation works on structured and unstructured meshes in two and three spatial dimensions. We illustrate the performance of our approach using several test cases in two and three spatial dimensions. In the case of a smooth, exact solution, we illustrate the optimal higher-order convergence rates of the method.

The Kinematic and Microphysical Characteristics of Extremely Heavy Rainfall in Zhengzhou City on 20 July 2021 Observed with Dual-Polarization Radars and Disdrometers

In this study, we utilized dual-polarization weather radar and disdrometer data to investigate the kinematic and microphysical characteristics of an extreme heavy rainfall event that occurred on 20 July 2021, in Zhengzhou. The results are as follows: FY-2G satellite images showed that extremely heavy rainfall mainly occurred during the merging period of medium- and small-scale convective cloud clusters. The merging of these cloud clusters enhanced the rainfall intensity. The refined three-dimensional wind field, as retrieved by the multi-Doppler radar, revealed a prominent mesoscale vortex and convergence structure at the extreme rainfall stage. This led to echo stagnation, resulting in localized extreme heavy rainfall. We explored the formation mechanism of the notable ZDR arc feature of dual-polarization variables during this phase. It was revealed that during the record-breaking hourly rainfall event in Zhengzhou (20 July 2021, 16:00–17:00 Beijing Time), the warm rain process dominated. Effective collision–coalescence processes, producing a high concentration of medium- to large-sized raindrops, significantly contributed to heavy rainfall at the surface. From an observational perspective, it was revealed that raindrops exhibited significant collision interactions during their descent. Moreover, a conceptual model for the kinematic and microphysical characteristics of this extreme rainfall event was established, aiming to provide technical support for monitoring and early warning of similar extreme rainfall events.