Graupel Mass Research Articles

Effects of aerosols on the lifecycle of a mesoscale cloud cluster over the Indian peninsula: A numerical study with a bin-based cloud microphysics scheme

The effects of aerosols (i.e., CCN) on the lifecycle of a well-documented mesoscale cloud cluster (CC) over the Indian peninsula are investigated in this study. The WRF model coupled with a sophisticated spectral bin microphysics scheme is employed to simulate the observed cloud system under various CCN scenarios. The CCN sensitivity experiments were carried out using three different background CCN concentrations (250, 1000, and 3000 cm−3). The prevailing environment featured a relatively dry mid-level. The introduction of more aerosols weakened the convection and moistened the upper troposphere in the initiation and mature phases. The major impacts of the enhanced aerosols include the dissipation of shallow clouds, a decrease in the number of convective cells and their overall coverage, enhanced convective organization in the early phase(s) of the lifecycle, enhancement of the cloud-free area, etc. The key microphysical changes due to enhanced aerosols are the increase in cloud liquid water, presence of numerous smaller cloud droplets, enhancement of condensation and evaporation, formation of smaller ice crystals, reduced snow mass and reduction in the aggregation process, high graupel mass and number and a reduction in graupel size, fewer raindrops with slight enhancement in raindrop size, etc. Cloud growth is significantly limited in the high aerosol scenarios due to large evaporation favored by a relatively dry environment and no invigoration effect is noted. A significant reduction in the rainfall (and associated rainfall-type) from isolated convective cores is noted due to high aerosols, especially in the initiation and mature phases. The eventual impact on the surface precipitation is a decrease in overall rainfall in the enhanced aerosol scenarios, with suppression of heavy rain. The study indicates that in a dry environment, the microphysical changes in various CCN scenarios cumulatively lead to macrophysical changes, which are found to be the primary controller of the overall surface rainfall associated with the CC.

Understanding the Role of Sea Surface Temperature and Urbanization on Severe Thunderstorms Dynamics: A Case Study in Surabaya, Indonesia

AbstractWithin the period 2014–2017, five hail events were reported in the city of Surabaya in Indonesia. Although deep convection commonly develops over the Maritime Continent, severe thunderstorms triggering hail events develop less frequently as specific atmospheric conditions are required. The rapid urbanization in Surabaya might have led to increased heat release to the atmosphere and to the deepening of convection, which raises the question of whether urbanization is the culprit of the recent hail events in Surabaya. Hence, for a selected hail event, we used the high‐resolution Weather Research and Forecasting model to understand the storm dynamics and to explore the role of urbanization, sea surface temperature, and aerosol concentration on the storm dynamics with a total of 11 scenarios. The control simulation reveals that low‐level convergence induced by a sea breeze creates instability. At the same time, the urban heat release enhances the energy supply to induce hail formation and retain the storm's lifetime over the city. A factor separation method revealed that the urbanization (added anthropogenic heat flux, urban aerosol, and the rise in building height) and the sea surface temperature increase contribute to the storm enhancement over Surabaya, producing two times higher updraft velocity, doubling the maximum graupel mass mixing ratio and finally resulting in 15%–30% higher accumulated precipitation over Surabaya, compared to the control simulation.

Assimilation of Meteosat Third Generation (MTG) Lightning Imager (LI) pseudo-observations in AROME-France – proof of concept

Abstract. This study develops a lightning data assimilation (LDA) scheme for the regional, convection-permitting numerical weather prediction (NWP) model AROME-France. The LDA scheme intends to assimilate total lightning, i.e., cloud-to-ground (CG) and inter- and intra-cloud (IC), of the future Meteosat Third Generation (MTG) Lightning Imager (LI; MTG-LI). MTG-LI proxy data are created, and flash extent density (FED) fields are derived. An FED forward observation operator (FFO) is trained based on modeled, column-integrated graupel mass from 24 storm days in 2018. The FFO is successfully verified for 2 independent storm days. With the FFO, the LDA adapts a 1-dimensional Bayesian (1DBay) retrieval followed by a 3-dimensional variational (3DVar) assimilation approach that is currently run operationally in AROME-France for radar reflectivity data. The 1DBay retrieval derives relative humidity profiles from the background by comparing the FED observations to the FED inferred from the background. Retrieved relative humidity profiles are assimilated as sounding data. The evaluation of the LDA comprises different LDA experiments and four case studies. It is found that all LDA experiments can increase the background integrated water vapor (IWV) in regions where the observed FED exceeds the FED inferred from AROME-France outputs. In addition, IWV can be reduced where spurious FED is modeled. A qualitative analysis of 6 h accumulated rainfall fields reveals that the LDA is capable of locating and initiating some local precipitation fields better than a radar data assimilation (RDA) experiment. However, the LDA also leads to rainfall accumulations that are too high at some locations. Fractions skill scores (FSSs) of 6 h accumulated rainfall are overall similar for the developed LDA and RDA experiments. An approach aiming at mitigating effects due to differences in the optical extents of lightning flashes and the area of the corresponding cloud was developed and included in the LDA; however, it does not always improve the FSS.

Development of New Observation Operators for Assimilating GOES-R Geostationary Lightning Mapper Flash Extent Density Data Using GSI EnKF: Tests with Two Convective Events over the United States

Abstract In a prior study, GOES-R Geostationary Lightning Mapper (GLM) flash extent density (FED) data were assimilated using ensemble Kalman filter into a convection-allowing model for a mesoscale convective system (MCS) and a supercell storm. The FED observation operator based on a linear relation with column graupel mass was tuned by multiplying a factor to avoid large FED forecast bias. In this study, new observation operators are developed by fitting a third-order polynomial to GLM FED observations and the corresponding FED forecasts of graupel mass of the MCS and/or supercell cases. The new operators are used to assimilate the FED data for both cases, in three sets of experiments called MCSFit, SupercellFit, and CombinedFit, and their performances are compared with the prior results using the linear operator and with a reference simulation assimilating no FED data. The new nonlinear operators reduce the frequency biases (root-mean-square innovations) in the 0–4-h forecasts of the FED (radar reflectivity) relative to the results using the linear operator for both storm cases. The operator obtained by fitting data from the same case performs slightly better than fitting to data from the other case, while the operator obtained by fitting forecasts of both cases produce intermediate but still very similar results, and the latter is considered more general. In practice, a more general operator can be developed by fitting data from more cases. Significance Statement Prior studies found that assimilation of satellite lightning observation can benefit storm forecasts for up to 4 h. A linear lightning observation operator originally developed for assimilating pseudo-satellite lightning observations was tuned earlier through sensitivity experiments when assimilating real lightning data. However, the linear relation does not fit the model and observational data well and significant bias can exist. This study develops new lightning observation operators by fitting a high-order polynomial to satellite lightning observations and model-predicted quantities that directly relate to lightning. The new operator was found to reduce the frequency biases and root-mean-square innovations for lightning and radar reflectivity forecasts, respectively, up to several hours relative to the linear operator. The methodology can be applied to larger data samples to obtain a more general operator for use in operational data assimilation systems.

Assessment of a Microphysical Ensemble Used to Investigate the OWLeS IOP4 Lake-Effect Storm

AbstractMicrophysical processes within mixed-phase convective clouds can have cascading impacts on cloud properties and resultant precipitation. This paper investigates the role of microphysics in the lake-effect storm (LES) observed during intensive observing period 4 of the Ontario Winter Lake-effect Systems field campaign. A microphysical ensemble is composed of 24 simulations that differ in the microphysics scheme used (e.g., Weather Research and Forecasting Model microphysics options or a choice of two bulk adaptive habit models) along with changes in the representation of aerosol and potential ice nuclei concentrations, ice nucleation parameterizations, rain and ice fall speeds, spectral indices, ice habit assumptions, and the number of moments used for modeling ice-phase hydrometeors in each adaptive habit model. Each of these changes to microphysics resulted in varied precipitation types at the surface; 15 members forecast a mixture of snow, ice, and graupel, 7 members forecast only snow and ice, and the remaining 2 members forecast a combination of snow, ice, graupel, and rain. Observations from an optical disdrometer positioned to the south of the LES core indicate that 92% of the observed particles were snow and ice, 5% were graupel, and 3% were rain and drizzle. Analysis of observations spanning more than a point location, such as polarimetric radar observations and aircraft measurements of liquid water content, provides insight into cloud composition and processes leading to the differences at the surface. Ensemble spread is controlled by hydrometeor type differences spurred by processes or parameters (e.g., ice fall speed) that affect graupel mass.

Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI EnKF for the Analysis and Short-Term Forecast of a Mesoscale Convective System

AbstractThe recently launched Geostationary Operational Environmental Satellite “R-series” (GOES-R) satellites carry the Geostationary Lightning Mapper (GLM) that measures from space the total lightning rate in convective storms at high spatial and temporal frequencies. This study assimilates, for the first time, real GLM total lightning data in an ensemble Kalman filter (EnKF) framework. The lightning flash extent density (FED) products at 10-km pixel resolution are assimilated. The capabilities to assimilate GLM FED data are first implemented into the GSI-based EnKF data assimilation (DA) system and tested with a mesoscale convective system (MCS). FED observation operators based on graupel mass or graupel volume are used. The operators are first tuned through sensitivity experiments to determine an optimal multiplying factor to the operator, before being used in FED DA experiments FEDM and FEDV that use the graupel-mass or graupel-volume-based operator, respectively. Their results are compared to a control experiment (CTRL) that does not assimilate any FED data. Overall, both DA experiments outperform CTRL in terms of the analyses and short-term forecasts of FED and composite/3D reflectivity. The assimilation of FED is primarily effective in regions of deep moist convection, which helps improve short-term forecasts of convective threats, including heavy precipitation and lightning. Direct adjustments to graupel mass via observation operator as well as adjustments to other model state variables through flow-dependent ensemble cross covariance within EnKF are shown to work together to generate model-consistent analyses and overall improved forecasts.

An Evaluation of Relationships between Radar-Inferred Kinematic and Microphysical Parameters and Lightning Flash Rates in Alabama Storms

Lightning flash rate parameterizations based on polarimetric and multi-Doppler radar inferred microphysical (e.g., graupel volume, graupel mass, 35 dBZ volume) and kinematic (e.g., updraft volume, maximum updraft velocity) parameters have important applications in atmospheric science. Although past studies have established relations between flash rate and storm parameters, their expected performance in a variety of storm and flash rate conditions is uncertain due to sample limitations. Radar network and lightning mapping array observations over Alabama of a large and diverse sample of 33 storms are input to hydrometeor identification, vertical velocity retrieval and flash rate algorithms to develop and test flash rate relations. When applied to this sample, prior flash rate linear relations result in larger errors overall, including often much larger bias (both over- and under-estimation) and root mean square errors compared to the new linear relations. At low flash rates, the new flash rate relations based on kinematic parameters have larger errors compared to those based on microphysical ones. Sensitivity of error to the functional form (e.g., zero or non-zero intercept) is also tested. When considering all factors (e.g., low errors including at low flash rate, consistency with past linear relations, and insensitivity to functional form), the flash rate parameterization based on graupel volume has the best overall performance.

Intensification of single cell storms prior to lightning onset

Single cell storms in the United Kingdom can produce lightning, despite apparently only having developed to towering cumulus rather than cumulonimbus. Such marginal thunderstorms still present severe weather hazards but are difficult to identify and predict and therefore provide a warning. Observations from the Met Office radar mosaic and ATDNet (Arrival Time Difference Network) show that these single cell storms demonstrate a characteristic increase in the area of high reflectivity storm core during the 15 min prior to the first lightning. By using the Met Office Unified Model to investigate reflectivity development in modelled storms, a microphysical explanation for the observed reflectivity increase is identified. During a rapid reflectivity increase, the updraft area at the melting layer, the peak updraft velocity and the storm graupel mass increase. The three quantities examined are linked to each other and to the generation of charge within the storm. The production of graupel is promoted by the increase in updraft area and charge separation is enhanced by the faster peak updraft velocity. This explains some of the physical differences between single cell storms that produce lightning and apparently similar storm systems which do not. It also provides a new basis with which to predict lightning hazard for marginal storms.

Examining relationships between cloud‐resolving model parameters and total flash rates to generate lightning density maps

Forecasting the electrical activity of a storm is a difficult task because of the complexity of cloud electrification processes and the unforeseeable characteristics of lightning flashes. Nowadays, very few models are able to simulate explicitly the entire life cycle of the electric charges in clouds, which is a result of the balance between the charge separation rates (microphysics) and the charge neutralization rates by lightning flashes (physics of streamer discharges).The main objective of this study is to investigate which particular dynamical and/or microphysical parameter can serve as the best proxy for the total lightning activity. With this aim, eight storms were simulated with Meso‐NH and its cloud electrical scheme. This model‐to‐model approach guarantees a full consistency between the dynamics, the microphysics and the lightning activity. Two approaches are followed to analyse the results. The first one considers the entire domain of simulation, while the second one concentrates on individual convective cells.Linear regressions between predicted flash rates and recorded parameters or proxies (total graupel mass, updraught volume with vertical velocity higher than 10 m/s, product of precipitating and non‐precipitating ice mass flux and maximum updraught speed) are analysed to show the benefit of the cell‐scale approach. Then, in order to evaluate the relationships, the HyMeX storm case of 24 September 2012 was simulated. The mass of graupel best represents the overall location of the lightning activity (RMSE of the flash rate density better than 10−2 fl min−1km−2) and locates the peak lightning flash rate well. The three other proxies tend to cause false alarms due to the y‐intercept value of the regression equation.

Lightning data assimilation with comprehensively nudging water contents at cloud-resolving scale using WRF model

A new lightning data assimilation (LDA) scheme comprehensively nudging water contents in the WRF model is developed at cloud-resolving scale, which takes the dynamical and thermodynamic conditions into consideration and nudges the low-level water vapor and graupel mass within the mixed-phase region according to the detected total lightning flash rate and model environments (here named C18). The main nudging functions of the LDA scheme in this work are modified based on the work of Fierro et al. (2012, hereafter F12) and Qie et al. (2014, hereafter Q14). To evaluate the application of LDA in high-impact weather simulations and quantitative precipitation forecasts, the three LDA schemes, including F12, Q14 and C18, are tested and compared for two severe squall line cases occurred over the Beijing metropolitan region (BMR). Benefiting from assimilation of lightning data, the simulated storm structure and surface cold pool are improved and closer to the observations for all the three schemes than the control run without LDA. For the F12 scheme, although the simulated thunderstorms are characterized by wide spread stratiform clouds and relatively weaker cold pool intensity and coverage, the positive impacts on both storm evolution and precipitation endures most prominently. For the Q14 scheme, intense downdrafts lead to the strongest cold pool and earlier dissipation of storms comparing with the observations. For the C18 scheme, increased graupel mass affect the cold-cloud processes leading to an earlier onset of rainfall, and the simulated surface cold pool is in better agreement with the observations. Profiting from more moisture added into the lower layers in C18, the storm develops more intensively toward higher altitude and sustains its development over a longer period after LDA, resulting in the best quantitative precipitation forecasts consequently.

A New Parameterization of the Accretion of Cloud Water by Graupel and Its Evaluation through Cloud and Precipitation Simulations

Abstract A new parameterization of the accretion of cloud water by graupel for use in bulk microphysics schemes is derived by analytically integrating the stochastic collection equation (SCE). In this parameterization, the collection efficiency between graupel particles and cloud droplets is expressed in a functional form using the data obtained from a particle trajectory model by a previous study. The new accretion parameterization is evaluated through box model simulations in comparison with a bin-based direct SCE solver and two previously developed accretion parameterizations that employ the continuous collection equation and a simplified SCE, respectively. Changes in cloud water and graupel mass contents via the accretion process predicted by the new parameterization are closest to those predicted by the direct SCE solver. Furthermore, the new parameterization predicts a decrease in the cloud droplet number concentration that is smaller than the decreases predicted by the other accretion parameterizations, consistent with the direct SCE solver. The new and the other accretion parameterizations are implemented into a cloud-resolving model. Idealized deep convective cloud simulations show that among the accretion parameterizations, the new parameterization predicts the largest rate of accretion by graupel and the smallest rate of accretion by snow, which overall enhances rainfall through the largest rate of melting of graupel. Real-case simulations for a precipitation event over the southern Korean Peninsula show that among the examined accretion parameterizations, the new parameterization simulates precipitation closest to observations. Compared to the other accretion parameterizations, the new parameterization decreases the fractions of light and moderate precipitation amounts and increases the fraction of heavy precipitation amount.

Relationships between Electrification and Storm-Scale Properties Based on Idealized Simulations of an Intensifying Hurricane-Like Vortex

AbstractThis study investigates relationships between storm-scale properties and the electrification and lightning of two simulations of an intensifying idealized tropical cyclone (TC) using the cloud-resolving Collaborative Model for Multiscale Atmospheric Simulation (COMMAS). To produce an intensifying storm, an initial weak TC is subjected to a linear increase in sea surface temperature.As the TC intensifies, lightning flash rates increase in both the inner core (r ≤ 100 km) and outer region (100 < r ≤ 300 km). As time progresses, lightning in the outer region gradually decreases, while the inner-core lightning remains relatively steady. Bootstrapped correlation statistics using 1000 random samples between the pressure trace and time series of lightning rates shows a statistically significant negative correlation between inner-core lightning and TC intensification. Lightning rates in the outer bands were found to lag minimum surface pressure by 12 h.The increases in lightning in both the inner core and outer region coincided well with increases in 0.5 g kg−1 graupel and 5 m s−1 updraft volumes in each respective region. Correlation statistics with selected kinematic and microphysical variables known to be associated with lightning in thunderstorms, such as the ice water path, integrated updraft volume, and graupel volume, revealed that their increase in the inner core indicated an ongoing deepening, similar to the lightning. Trends in these proxy variables in the outer bands were also found to lag TC intensification by 12 h.Overall, the best linear relationships with lightning in either the inner core or the outer region were obtained with the 0.5 g kg−1 graupel volume and total graupel mass.

Improving Lightning and Precipitation Prediction of Severe Convection Using Lightning Data Assimilation With NCAR WRF‐RTFDDA

AbstractIn this study, a lightning data assimilation (LDA) scheme was developed and implemented in the National Center for Atmospheric Research Weather Research and Forecasting‐Real‐Time Four‐Dimensional Data Assimilation system. In this LDA method, graupel mixing ratio (qg) is retrieved from observed total lightning. To retrieve qg on model grid boxes, column‐integrated graupel mass is first calculated using an observation‐based linear formula between graupel mass and total lightning rate. Then the graupel mass is distributed vertically according to the empirical qg vertical profiles constructed from model simulations. Finally, a horizontal spread method is utilized to consider the existence of graupel in the adjacent regions of the lightning initiation locations. Based on the retrieved qg fields, latent heat is adjusted to account for the latent heat releases associated with the formation of the retrieved graupel and to promote convection at the observed lightning locations, which is conceptually similar to the method developed by Fierro et al. Three severe convection cases were studied to evaluate the LDA scheme for short‐term (0–6 h) lightning and precipitation forecasts. The simulation results demonstrated that the LDA was effective in improving the short‐term lightning and precipitation forecasts by improving the model simulation of the qg fields, updrafts, cold pool, and front locations. The improvements were most notable in the first 2 h, indicating a highly desired benefit of the LDA in lightning and convective precipitation nowcasting (0–2 h) applications.

Evaluation of Cloud Microphysical Schemes for a Warm Frontal Snowband during the GPM Cold Season Precipitation Experiment (GCPEx)

Detailed observations from the Global Precipitation Measurement (GPM) mission Cold Season Precipitation Experiment (GCPEx) of an intense warm frontal band on 18 February 2012 were used to evaluate several bulk microphysical parameterizations within the NASA-Unified Weather Research and Forecasting (NU-WRF) Model. These included the Predicted Particle Properties (P3), Morrison (MORR), Stony Brook University (SBU), and Goddard four-class ice (4ICE) microphysics schemes. All schemes were able to predict the snowband, but the simulated intensities varied because of various assumptions in these schemes. The saturation adjustment scheme within MORR promoted excessive amounts of cloud water evaporational cooling in the warm sector, which contributed to a decrease in midlevel instability approaching the frontal band and thus a weaker band. In contrast, the explicit calculation of cloud water condensation/evaporation in the P3 scheme produced limited amounts of evaporational cooling, which allowed for greater midlevel instability to support band development. The P3 and SBU schemes produced moderate rime/graupel mass within the band that was confirmed by observations, while the MORR and 4ICE schemes drastically underpredicted the graupel mass. The high-density, fast-falling rimed particles in P3 underwent weak sublimation and melting, which helped promote a stronger horizontal temperature gradient and greater low-level instability along the frontal band compared to the other schemes. Overall, the schemes that use specified thresholds for converting between the predefined ice-phase categories of cloud ice, snow, and graupel had the most unrepresentative hydrometeor types. These results highlight the advantage of predicting ice particle properties and explicitly calculating cloud water condensation/evaporation in the P3 scheme.

Aerosol–Cloud Interaction in Deep Convective Clouds over the Indian Peninsula Using Spectral (Bin) Microphysics

Abstract The Weather Research and Forecasting (WRF) Model coupled with a spectral bin microphysics (SBM) scheme is used to investigate aerosol effects on cloud microphysics and precipitation over the Indian peninsular region. The main emphasis of the study is in comparing simulated cloud microphysical structure with in situ aircraft observations from the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX). Aerosol–cloud interaction over the rain-shadow region is investigated with observed and simulated size distribution spectra of cloud droplets and ice particles in monsoon clouds. It is shown that size distributions as well as other microphysical characteristics obtained from simulations such as liquid water content, cloud droplet effective radius, cloud droplet number concentration, and thermodynamic parameters are in good agreement with the observations. It is seen that in clouds with high cloud condensation nuclei (CCN) concentrations, snow and graupel size distribution spectra were broader compared to clouds with low concentrations of CCN, mainly because of enhanced riming in the presence of a large number of droplets with a diameter of 10–30 μm. The Hallett–Mossop ice multiplication process is illustrated to have an impact on snow and graupel mass. The changes in CCN concentrations have a strong effect on cloud properties over the domain, amounts of cloud water, and the glaciation of the clouds, but the effects on surface precipitation are small when averaged over a large area. Overall enhancement of cold-phase cloud processes in the high-CCN case contributed to slight enhancement (5%) in domain-averaged surface precipitation.

Kinematic and Microphysical Significance of Lightning Jumps versus Non-Jump Increases in Total Flash Rate.

Thirty-nine thunderstorms are examined using multiple-Doppler, polarimetric and total lightning observations to understand the role of mixed phase kinematics and microphysics in the development of lightning jumps. This sample size is larger than those of previous studies on this topic. The principal result of this study is that lightning jumps are a result of mixed phase updraft intensification. Larger increases in intense updraft volume (≥ 10 m s-1) and larger changes in peak updraft speed are observed prior to lightning jump occurrence when compared to other non-jump increases in total flash rate. Wilcoxon-Mann-Whitney Rank Sum testing yields p-values ≤0.05, indicating statistical independence between lightning jump and non-jump distributions for these two parameters. Similar changes in mixed phase graupel mass magnitude are observed prior to lightning jumps and non-jump increases in total flash rate. The p-value for graupel mass change is p=0.096, so jump and non-jump distributions for graupel mass change are not found statistically independent using the p=0.05 significance level. Timing of updraft volume, speed and graupel mass increases are found to be 4 to 13 minutes in advance of lightning jump occurrence. Also, severe storms without lightning jumps lack robust mixed phase updrafts, demonstrating that mixed phase updrafts are not always a requirement for severe weather occurrence. Therefore, the results of this study show that lightning jump occurrences are coincident with larger increases in intense mixed phase updraft volume and peak updraft speed than smaller non-jump increases in total flash rate.

싸락눈 종단 속도의 불확실성이 구름 모의에 미치는 영향

In spite of considerable progress in the recent decades, there still remain large uncertainties in numerical cloud models. In this study, effects of uncertainty in terminal velocity of graupel on cloud simulation are investigated. For this, a two-dimensional bin microphysics cloud model is employed, and deep convective clouds are simulated under idealized environmental conditions. In the sensitivity experiments, the terminal velocity of graupel is changed to twice and half the velocity in the control experiment. In the experiment with fast graupel terminal velocity, a large amount of graupel mass is present in the lower layer. On the other hand, in the experiment with slow graupel terminal velocity, almost all graupel mass remains in the upper layer. The graupel size distribution exhibits that as graupel terminal velocity increases, in the lower layer, the number of graupel particles increases and the peak radius in the graupel mass size distribution decreases. In the experiment with fast graupel terminal velocity, the vertical velocity is decreased mainly due to a decrease in riming that leads to a decrease in latent heat release and an increase in evaporative cooling via evaporation, sublimation, and melting that leads to more stable atmosphere. This decrease in vertical velocity causes graupel particles to fall toward the ground easier. By the changes in graupel terminal velocity, the accumulated surface precipitation amount differs up to about two times. This study reveals that the terminal velocity of graupel should be estimated more accurately than it is now.

Assimilation of Pseudo-GLM Data Using the Ensemble Kalman Filter

Total lightning observations that will be available from the GOES-R Geostationary Lightning Mapper (GLM) have the potential to be useful in the initialization of convection-resolving numerical weather models, particularly in areas where other types of convective-scale observations are sparse or nonexistent. This study used the ensemble Kalman filter (EnKF) to assimilate real-data pseudo-GLM flash extent density (FED) observations at convection-resolving scale for a nonsevere multicell storm case (6 June 2000) and a tornadic supercell case (8 May 2003). For each case, pseudo-GLM FED observations were generated from ground-based lightning mapping array data with a spacing approximately equal to the nadir pixel width of the GLM, and tests were done to examine different FED observation operators and the utility of temporally averaging observations to smooth rapid variations in flash rates. The best results were obtained when assimilating 1-min temporal resolution data using any of three observation operators that utilized graupel mass or graupel volume. Each of these three observation operators performed well for both the weak, disorganized convection of the multicell case and the much more intense convection of the supercell case. An observation operator using the noninductive charging rate performed poorly compared to the graupel mass and graupel volume operators, a result that appears likely to be due to the inability of the noninductive charging rate to account for advection of space charge after charge separation occurs.

Wet scavenging of soluble gases in DC3 deep convective storms using WRF‐Chem simulations and aircraft observations

AbstractWe examine wet scavenging of soluble trace gases in storms observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. We conduct high‐resolution simulations with the Weather Research and Forecasting model with Chemistry (WRF‐Chem) of a severe storm in Oklahoma. The model represents well the storm location, size, and structure as compared with Next Generation Weather Radar reflectivity, and simulated CO transport is consistent with aircraft observations. Scavenging efficiencies (SEs) between inflow and outflow of soluble species are calculated from aircraft measurements and model simulations. Using a simple wet scavenging scheme, we simulate the SE of each soluble species within the error bars of the observations. The simulated SEs of all species except nitric acid (HNO3) are highly sensitive to the values specified for the fractions retained in ice when cloud water freezes. To reproduce the observations, we must assume zero ice retention for formaldehyde (CH2O) and hydrogen peroxide (H2O2) and complete retention for methyl hydrogen peroxide (CH3OOH) and sulfur dioxide (SO2), likely to compensate for the lack of aqueous chemistry in the model. We then compare scavenging efficiencies among storms that formed in Alabama and northeast Colorado and the Oklahoma storm. Significant differences in SEs are seen among storms and species. More scavenging of HNO3 and less removal of CH3OOH are seen in storms with higher maximum flash rates, an indication of more graupel mass. Graupel is associated with mixed‐phase scavenging and lightning production of nitrogen oxides (NOx), processes that may explain the observed differences in HNO3 and CH3OOH scavenging.

Multi-sensor analysis of convective activity in central Italy during the HyMeX SOP 1.1

Abstract. A multi-sensor analysis of convective precipitation events that occurred in central Italy in autumn 2012 during the HyMeX (Hydrological cycle in the Mediterranean experiment) Special Observation Period (SOP) 1.1 is presented. Various microphysical properties of liquid and solid hydrometeors are examined to assess their relationship with lightning activity. The instrumentation used consisted of a C-band dual-polarization weather radar, a 2-D video disdrometer, and the LINET lightning network. Results of T-matrix simulation for graupel were used to (i) tune a fuzzy logic hydrometeor classification algorithm based on Liu and Chandrasekar (2000) for the detection of graupel from C-band dual-polarization radar measurements and (ii) to retrieve graupel ice water content. Graupel mass from radar measurements was related to lightning activity. Three significant case studies were analyzed and linear relations between the total mass of graupel and number of LINET strokes were found with different slopes depending on the nature of the convective event (such as updraft strength and freezing level height) and the radar observational geometry. A high coefficient of determination (R2 = 0.856) and a slope in agreement with satellite measurements and model results for one of the case studies (15 October 2012) were found. Results confirm that one of the key features in the electrical charging of convective clouds is the ice content, although it is not the only one. Parameters of the gamma raindrop size distribution measured by a 2-D video disdrometer revealed the transition from a convective to a stratiform regime. The raindrop size spectra measured by a 2-D video disdrometer were used to partition rain into stratiform and convective classes. These results are further analyzed in relation to radar measurements and to the number of strokes. Lightning activity was not always recorded when the precipitation regime was classified as convective rain. High statistical scores were found for relationships relating lightning activity to graupel aloft.