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Ice clouds and falling snow are ubiquitous globally and play important roles in the Earth's radiation budget and precipitation processes. Ice particle microphysical properties (e.g., size, habit and orientation) are not only influenced by the ambient environment's dynamic and thermodynamic conditions, but are also intimately connected to the cloud radiative effects and particle fall speeds, which therefore have an impact on future climate projection as well as on the details of the surface precipitation (e.g., onset time, location, type and strength). Our previous work revealed that high-frequency (> 150 GHz) polarimetric radiance difference (PD) from passive microwave sensors is a good indicator of the bulk aspect ratio of horizontally oriented ice particles that often occur inside anvil clouds and/or stratiform precipitation. In this current work, we further investigate the dynamic and thermodynamic mechanisms and cloud–precipitation structures associated with ice-phase microphysics corresponding to different PD signals. In order to do so, collocated CloudSat radar (W-band) and Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM DPR, Ku–Ka-bands) observations as well as European Centre for Medium-Range Weather Forecasts (ECMWF) atmosphere background profiles are grouped according to the magnitude of PD for only stratiform precipitation and/or anvil cloud scenes. We found that horizontally oriented snow aggregates or large snow particles are likely the major contributor to the high-PD signals at 166 GHz, while low-PD magnitudes can be attributed to small cloud ice, randomly oriented snow aggregates, riming snow or supercooled water. Further, high-PD (low-PD) scenes are found to be associated with stronger (weaker) wind shear and higher (lower) ambient humidity, both of which help promote (prohibit) the growth of frozen particles and the organization of convective systems. An ensemble of squall line cases is studied at the end to demonstrate that the PD asymmetry in the leading and trailing edges of the deep convection line is closely tied to the anvil cloud and stratiform precipitation layers, respectively, suggesting the potential usefulness of PD as a proxy of stratiform–convective precipitation flag, as well as a proxy of convection life stage.

The Dynamical-microphysical-electrical Processes in Severe Thunderstorms and Lightning Hazards (STORM973) project conducted coordinated comprehensive field observations of thunderstorms in the Beijing metropolitan region (BMR) during the warm season from 2014 to 2018. The aim of the project was to understand how dynamical, microphysical and electrical processes interact in severe thunderstorms in the BMR, and how to assimilate lightning data in numerical weather prediction models to improve severe thunderstorm forecasts. The platforms used in the field campaign included the Beijing Lightning Network (BLNET, consisting of 16 stations), 2 X-band dual linear polarimetric Doppler radars, and 4 laser raindrop spectrometers. The collaboration also made use of the China Meteorological Administration’s mesoscale meteorological observation network in the Beijing-Tianjin-Hebei region. Although diverse thunderstorm types were documented, it was found that squall lines and multicell storms were the two major categories of severe thunderstorms with frequent lightning activity and extreme rainfall or unexpected local short-duration heavy rainfall resulting in inundations in the central urban area, influenced by the terrain and environmental conditions. The flash density maximums were found in eastern Changping District, central and eastern Shunyi District, and the central urban area of Beijing, suggesting that the urban heat island effect has a crucial role in the intensification of thunderstorms over Beijing. In addition, the flash rate associated with super thunderstorms can reach hundreds of flashes per minute in the central city regions. The super (5% of the total), strong (35%), and weak (60%) thunderstorms contributed about 37%, 56%, and 7% to the total flashes in the BMR, respectively. Owing to the close connection between lightning activity and the thermodynamic and microphysical characteristics of the thunderstorms, the lightning flash rate can be used as an indicator of severe weather events, such as hail and short-duration heavy rainfall. Lightning data can also be assimilated into numerical weather prediction models to help improve the forecasting of severe convection and precipitation at the cloud-resolved scale, through adjusting or correcting the thermodynamic and microphysical parameters of the model.

In a mesoscale convective system (MCS), convection that redevelops over (i.e., back-builds), and/or repeatedly passes over (i.e., trains) a region for an extended period of time can contribute to extreme rainfall and flash flooding. Past studies have indicated that both mesoscale ascent and lifting of the inflow layer by a cold pool or bore are important when this back-building/training convection is displaced from the leading line [sometimes called rearward off-boundary development (ROD)]. However, Plains Elevated Convection At Night (PECAN) field campaign observations suggest that the stability of the nocturnal boundary layer is highly variable and some MCSs with ROD have only a weak surface cold pool. Numerical simulations presented in this study suggest that in an environment with strong boundary layer stability, ROD can be supported by mechanisms other than those mentioned above. Simulations were initialized using a sounding from ahead of a PECAN MCS with a strong stable layer and ROD, and the three-dimensional simulation produced an MCS similar to that observed despite the homogeneous initial conditions. Some of the findings presented herein challenge existing understanding of nocturnal MCSs, and especially how downdrafts interact with a stable boundary layer. Notably, downdrafts can reach the surface, and different regions of the MCS may have different propagation mechanisms and different relevant inflow layers. Unlike previous studies of ROD, parcel lifting may be supported by an intrusion (an elevated layer of downdraft air) modified by the three-dimensional vertical wind shear.

In this research a newly developed terrain-resolving four-dimensional variational (4DVar)-based data assimilation system, Immersed Boundary Method_Variational Doppler Radar Analysis System (IBM_VDRAS), is applied to investigate the mechanisms leading to a heavy precipitation event that occurred in Taiwan during the Southwesterly Monsoon Experiment (SoWMEX) conducted in 2008. The multivariate analyses using IBM_VDRAS and surface observations reveal that the warm and moist southwesterly flow from the ocean decelerates after making landfall, forming a surface convergence zone along the coast, which is further strengthened during the passage of a prefrontal rainband. The flow ascends as it advances inland until reaching the mountains, producing persistent precipitation and the enhancement of evaporative cooling as well as a widespread high pressure zone. A very shallow (

The West African summer monsoon features multiple, complex interactions between African easterly waves (AEWs), moist convection, variable land surface properties, dust aerosols, and the diurnal cycle. One aspect of these interactions, the coupling between convection and AEWs, is explored using observations obtained during the 2006 African Monsoon Multidisciplinary Analyses (AMMA) field campaign. During AMMA, a research weather radar operated at Niamey, Niger, where it surveilled 28 squall-line systems characterized by leading convective lines and trailing stratiform regions. Nieto Ferreira et al. found that the squall lines were linked with the passage of AEWs and classified them into two tracks, northerly and southerly, based on the position of the African easterly jet (AEJ). Using AMMA sounding data, we create a composite of northerly squall lines that tracked on the cyclonic shear side of the AEJ. Latent heating within the trailing stratiform regions produced a midtropospheric positive potential vorticity (PV) anomaly centered at the melting level, as commonly observed in such systems. However, a unique aspect of these PV anomalies is that they combined with a 400–500-hPa positive PV anomaly extending southward from the Sahara. The latter feature is a consequence of the deep convective boundary layer over the hot Saharan Desert. Results provide evidence of a coupling and merging of two PV sources—one associated with the Saharan heat low and another with latent heating—that ends up creating a prominent midtropospheric positive PV maximum to the rear of West African squall lines.

This article reviews the advances in severe convection research and operation in China during the past several decades. The favorable synoptic situations for severe convective weather (SCW), the major organization modes of severe convective storms (SCSs), the favorable environmental conditions and characteristics of weather radar echoes and satellite images of SCW and SCSs, and the forecasting and nowcasting techniques of SCW, are emphasized. As a whole, Chinese scientists have achieved a profound understanding of the synoptic patterns, organization, and evolution characteristics of SCW from radar and satellite observations, and the mechanisms of different types of convective weather in China. Specifically, in-depth understanding of the multiple types of convection triggers, along with the environmental conditions, structures and organization modes, and maintenance mechanisms of supercell storms and squall lines, has been obtained. The organization modes and climatological distributions of mesoscale convective systems and different types of SCW, and the multiscale characteristics and formation mechanisms of large hail, tornadoes, downbursts, and damaging convective wind gusts based on radar, satellite, and lightning observations, as well as the related features from damage surveys, are elucidated. In terms of operational applications, different types of identification and mesoanalysis techniques, and various forecasting and nowcasting techniques using methods such as the “ingredients-based” and deep learning algorithms, have been developed. As a result, the performance of operational SCW forecasts in China has been significantly improved.

The velocity dealiasing is an essential work of automatic weather phenomenon identification, nowcasting, and disaster monitoring based on radial velocity data. The noise data, strong wind shear, and isolated echo region in the Doppler radar radial velocity data severely interfere with the velocity dealiasing algorithm. This paper proposes a two-step velocity dealiasing algorithm based on the minimization of velocity differences between regions to solve this problem. The first step is to correct aliased velocities by minimizing the sum of gradients in every region to eliminate abnormal velocity gradients between points. The interference of noise data and strong wind shear can be reduced by minimizing the whole gradients in a region. The second step is to dealiase velocities by the velocity differences between different isolated regions. The velocity of an unknown isolated region is determined by the velocities of all known regions. This step improves the dealiasing results of isolated regions. In this paper, 604 volume scan samples, including typhoons, squall lines, and heavy precipitation, were used to test the algorithm. The statistical results and analysis show that the proposed algorithm can dealiase the velocity field with a high probability of detection and a low false alarm rate.

Observational studies indicate that northern Jiangsu Province is the most active area for the occurrence of squall lines in east China. While the roles of the large-scale atmospheric environment have been investigated, the effects of the terrain and lakes on the squall line in northern Jiangsu Province have not been well understood. In this study, the squall line occurring on 14 June 2009 is simulated to investigate the influences of the terrain and lakes. The squall line occurred under the influence of a short westerly trough at 500 hPa, one of the typical synoptic-scale patterns favorable for the development of squall lines in east China. Using the grid spacings of 3 km, 1 km and 333 m, the Weather Research and Forecast model (WRF) reasonably well simulates the evolution of the squall line and the extreme rainfall. Sensitivity experiments are conducted to examine the effects of Mountain Meng, Hongze Lake and Gaoyou Lake. It is found that the valley wind associated with Mountain Meng plays an important role in the early development of the squall line by enhancing the vertical wind shear at the low levels. The presence of the lakes leads to a relatively cold area, resulting in a temperature gradient toward the southeast at the low levels. The horizontal temperature gradient enhances the low-level vertical wind shear and promotes the development of the squall line.

Warm-sector torrential rainfall (WSTR) events that occur in the annually first rainy season in south China are characterized by high rainfall intensity and low radar echo centroids. To understand the synoptic characteristics related to these features, 16 WSTR events that occurred in 2013-2017 were examined with another 16 squall line (SL) events occurred during the same period as references. Composite analysis derived from ERA-Interim reanalysis data indicated the importance of the deep layer of warm and moist air for WSTR events. The most significant difference between WSTR and SL events lies in their low-level convergence and lifting; for WSTR events, the low-level convergence and lifting is much shallower with comparable or stronger intensity. The trumpet-shaped topography to the north of the WSTR centers is favorable for the development of such shallow convergences in WSTR events. Results in this study will provide references for future studies to improve the predictability of WSTR.

The impacts of different moisture profiles on the structure and vertical motion of squall lines were investigated by conducting a set of numerical simulations. The base state was determined by an observational sounding, with high precipitable water representing moist environmental conditions in the East Asian monsoon region. To reveal the impact of moisture at different levels, the moisture content at the middle and low levels were changed in the numerical simulations. The numerical results showed that more convective cells developed and covered a larger area in the high moisture experiments, which was characteristic of the convection during the Meiyu season in China. In addition, high moisture content at low levels favored the development of updrafts and triggered convection of greater intensity. This was demonstrated by the thermodynamic parameters, including Convective Available Potential Energy (CAPE), Lifted Index (LI), Lift Condensation Level (LCL), and Level of Free Convection (LFC). Dry air at middle levels led to strong downdrafts in the environment and updrafts in clouds. This could be because dry air at middle levels favors the release of latent heat, thereby promoting updrafts in clouds and downdrafts in the environment. Therefore, high relative humidity (RH) at low levels and low RH at middle levels favors updrafts in the cloud cores. Additionally, moist air at low levels and dry air at middle levels promotes the development of convective cells and the intensification of cold pool. The squall line can be organized by the outflow boundary induced by cold pool. The balance of cold pool and environmental wind shear is favorable for the maintenance and strengthening of squall lines.

From 17:00 to 18:00 local standard time (LST) on 3 July 2019, a rare strong tornado occurred in Kaiyuan, Liaoning Province, northeast China. NCEP/NCAR 0.25° × 0.25° reanalysis data and WRF4.0 numerical prediction models were used to carry out the numerical simulation. Double nesting was adopted, and the horizontal grid distance was 9 km by 3 km. Based on the observation data of China meteorological observation stations, surface and upper charts, Doppler radar data, Himawari(HMW)-8 satellite images and numerical simulation results, the mesoscale structure and mechanism of the tornado were studied. The results show that: (1) At the northwest edge of the subtropical high, and the northeast cold vortex located in Northeast China, when the transverse trough moves southward, cold air is supplied continuously. Under the joint influence of the surface northeast cyclone, these are the main synoptic features of the tornado; (2) The northeast cold vortex cloud system was located at the junction of Heilongjiang and Jilin Provinces, and a squall line cloud system is formed. The tornado occurred at the tail of the squall line, and the strongest echo reached 65 dBZ. A mesocyclone, a 20 km northwest–southeast convergence belt, V-shaped gap, echo overhang structure and tornado vortex feature (TVS) were detected by the Doppler radar; (3) Before the tornado occurred, dry and cold air intruded from the northwest of the cold vortex, and a water vapor convergence zone appeared south of the squall line. The water vapor saturation zone with 80% relative humidity in northeast China was concentrated at 700 hPa, and the 20% dry column dropped down to 500 hPa between 115 and 124° E from the west. On the 850 hPa physical fields, there was a −20 × 10−5 s−1 convergence zone, and a 16 × 10−5 s−1 divergence belt appeared south and north of the squall line. A negative vorticity belt and a positive vorticity belt appeared south and north of the squall line, respectively. Kaiyuan is located at the smallest vertical shear, which is the junction place of three large vertical shear belts; (4) After 10:00 LST, the westerly wind 20 (10) m·s−1 dropped to 400 (800) hPa between 126 and 127° E. The northerly gale at 300 hPa north of 45° N moved southward. The rising center of the low level at 17:00 LST at approximately 45° N moved southward, and a sinking center appeared above it; (5) Several pairs of positive and negative vorticity columns formed between the lower troposphere and the place where the tornado occurred. There was convective instability at the lower level. CAPE increased, 0–3 km vertical wind shear increased, and LCL decreased remarkably during the afternoon.

Simulations of a squall line observed on 20 May 2011 during the Midlatitude Continental Convective Clouds Experiment (MC3E) using 750- and 250-m horizontal grid spacing are performed. The higher-resolution simulation has less upshear-tilted deep convection and a more elevated rear inflow jet than the coarser-resolution simulation in better agreement with radar observations. A stronger cold pool eventually develops in the 250-m run; however, the more elevated rear inflow counteracts the cold pool circulation to produce more upright convective cores relative to the 750-m run. The differing structure in the 750-m run produces excessive midlevel front-to-rear detrainment, reinforcing excessive latent cooling and rear inflow descent at the rear of the stratiform region in a positive feedback. The contrasting mesoscale circulations are connected to early stage deep convective draft differences in the two simulations. Convective downdraft condensate mass, latent cooling, and downward motion all increase with downdraft area similarly in both simulations. However, the 750-m run has a relatively greater number of wide and fewer narrow downdrafts than the 250-m run averaged to the same 750-m grid, a consequence of downdrafts being under-resolved in the 750-m run. Under-resolved downdrafts in the 750-m run are associated with under-resolved updrafts and transport mid–upper-level zonal momentum downward to low levels too efficiently in the early stage deep convection. These results imply that under-resolved convective drafts in simulations may vertically transport air too efficiently and too far vertically, potentially biasing buoyancy and momentum distributions that impact mesoscale convective system evolution.

In this work, we verified the formation of the South Atlantic Convergence Zone (SACZ) during the active, unfavorable, and transition phases of the Madden–Julian Oscillation (MJO), as well as the diurnal spatial variability in the estimated Outgoing Longwave Radiation (OLR) data. The real-time multivariate index (RMM) and the composites of meteorological variables were used, along with the temporal average of the estimated OLR data. All the different patterns for the average period of SACZ showed classic behavior: well-organized and with meteorological variables in phases throughout the troposphere. However, some differences were evident in the organization of each phase of the MJO: at 200 hPa, the Bolivian High (BH) was more flattened during the active phase pattern than in the unfavorable and transition phases, being wider and with a wavier trough embedded in the western flow, at medium levels, the subtropical highs appeared more defined and with a very wide trough, the trough supported the frontal systems on the surface and, together with the subtropical highs, concentrated all the moisture in this layer. In the OLR dataset, the formation of the Coast Squall Line (CSL) occurred during SACZ events in the active phase and MJO transition, whereas in the unfavorable phase, this system was not observed.

The Rapid Refresh Forecast System (RRFS) is currently under development and aims to replace the National Centers for Environmental Prediction (NCEP) operational suite of regional and convective scale modeling systems in the next upgrade. In order to achieve skillful forecasts comparable to the current operational suite, each component of the RRFS needs to be configured through exhaustive testing and evaluation. The current data assimilation component uses the Gridpoint Statistical Interpolation (GSI) system. In this study, various data assimilation algorithms and configurations in GSI are assessed for their impacts on RRFS analyses and forecasts of a squall line over Oklahoma on 4 May 2020. Results show that a baseline RRFS run without data assimilation is able to represent the observed convection, but with stronger cells and large location errors. With data assimilation, these errors are reduced, especially in the 4 and 6 h forecasts using 75 % of the ensemble background error covariance (BEC) and with the supersaturation removal function activated in GSI. Decreasing the vertical ensemble localization radius in the first 10 layers of the hybrid analysis results in overall less skillful forecasts. Convection and precipitation are overforecast in most forecast hours when using planetary boundary layer pseudo-observations, but the root mean square error and bias of the 2 h forecast of 2 m dew point temperature are reduced by 1.6 K during the afternoon hours. Lighter hourly accumulated precipitation is predicted better when using 100 % ensemble BEC in the first 4 h forecast, but heavier hourly accumulated precipitation is better predicted with 75 % ensemble BEC. Our results provide insight into current capabilities of the RRFS data assimilation system and identify configurations that should be considered as candidates for the first version of RRFS.

One way to test our understanding of the impact of convective processes on the isotopic composition of water vapor and precipitation is to analyze the isotopic mesoscale variations during...

Squall lines are known to be the consequence of the interaction of low-level shear with cold pools associated with convective downdrafts. Also, as the magnitude of the shear increases beyond a critical shear, squall lines tend to orient themselves. The existing literature suggests that this orientation reduces incoming wind shear to the squall line, and maintains equilibrium between wind shear and cold pool spreading. Although this theory is widely accepted, very few quantitative studies have been conducted on supercritical regime especially. Here, we test this hypothesis with tropical squall lines obtained by imposing a vertical wind shear in cloud resolving simulations in radiative convective equilibrium. In the sub-critical regime, squall lines are perpendicular to the shear. In the super-critical regime, their orientation maintain the equilibrium, supporting existing theories. We also find that as shear increases, cold pools become more intense. However, this intensification has little impact on squall line orientation.

This research uses image classification and machine learning methods on radar reflectivity mosaics to segment, classify, and track quasi-linear convective systems (QLCSs) in the United States for a 22-yr period. An algorithm is trained and validated using radar-derived spatial and intensity information from thousands of manually labeled QLCS and non-QLCS event slices. The algorithm is then used to automate the identification and tracking of over 3000 QLCSs with high accuracy, affording the first, systematic, long-term climatology of QLCSs. Convective regions determined by the procedure to be QLCSs are used as foci for spatiotemporal filtering of observed severe thunderstorm reports; this permits an estimation of the number of severe storm hazards due to this morphology. Results reveal that nearly 32% of MCSs are classified as QLCSs. On average, 139 QLCSs occur annually, with most of these events clustered from April through August in the eastern Great Plains and central/lower Mississippi and Ohio River Valleys. QLCSs are responsible for a spatiotemporally variable proportion of severe hazard reports, with a maximum in QLCS-report attribution (30%–42%) in the western Ohio and central Mississippi River Valleys. Over 21% of tornadoes, 28% of severe winds, and 10% of severe hail reports are due to QLCSs across the central and eastern United States. The proportion of QLCS-affiliated tornado and severe wind reports maximize during the overnight and cool season, with more than 50% of tornadoes and wind reports in some locations due to QLCSs. This research illustrates the utility of automated storm-mode classification systems in generating extensive, systematic climatologies of phenomena, reducing the need for time-consuming and spatiotemporal-limiting methods where investigators manually assign morphological classifications.

The evolution and microphysical structures of a squall line in South China are investigated by combining S-band polarimetric radar datasets with 2D-Video-Disdrometer measurements. The evolution of the squall line is partitioned into formative, intensifying, and mature stages based on convection patterns. Contrary to previous studies, the radar-retrieved drop size distribution in the convective area is found to be maritime-like [small mass-weighted diameter (Dm) and high logarithmic normalized intercept (log10Nw)] in the formative stage and it slowly evolves into a cluster with characteristics in between maritime and continental storms (large Dm and low log10Nw). The leading edge of the convective area is characterized by a differential reflectivity (ZDR) column, with high ZDR values (> 2 dB) extending vertically to over 4 km above the ground. This region contains large raindrops and wet graupel carried by the updraft. Due to warm rain processes (collision and coalescence) and ice rain processes (melting of graupel), log10Nw and liquid water content decrease steadily, but Dm increases from the ground to melting level. The results gained herein appear to have vital implications for understanding the cloud microphysical processes by S-band polarimetric radar and 2D-Video-Disdrometer observations, and provide guidance for cloud microphysics scheme verification in numerical models.

Three bulk microphysics schemes with different complexities in the Weather Research and Forecasting Model are compared in terms of the individual microphysical process terms of the hydrometeor mass and number mixing ratio tendency equations in an idealized 2D squall-line case. Through evaluation of these process terms and of hydrometeor size distributions, it is shown that the differences in the simulated population characteristics of snow, graupel, and rainwater are the prominent factors contributing to the differences in the development of the simulated squall lines using these schemes. In this particular case, the gust front propagation speed produced by the Thompson scheme is faster than in the other two schemes during the first 2 h of the simulation because it has a larger dominant graupel size. After 2 h into the simulation, the initially less intense squall lines in the runs using the WSM6 and Morrison schemes start to catch up in intensity and development to the run using the Thompson scheme. Because the dominant size of graupel particles in the runs using the WSM6 and Morrison schemes is smaller, these particles take more time to fall below the freezing level and enhance the rainwater production and its evaporative cooling. In the run using the Thompson scheme, the graupel production slows down at later times while the snow particle growth increases, leading to more snow falling below the freezing level to melt and surpass graupel particle melting in the production of rainwater.

This study investigates how multifrequency cloud radar observations can be used to evaluate the representation of rain microphysics in the WRF Model using two bulk microphysics schemes. A squall line observed over Oklahoma on 12 June 2011 is used as a case study. A recently developed retrieval technique combining observations of two vertically pointing cloud radars provides quantitative description of the drop size distribution (DSD) properties of the transition and stratiform regions of the squall-line system. For the first time, the results of this multifrequency cloud radar retrieval are compared to more conventional retrievals from a nearby polarimetric radar, and a supplementary result of this work is that this new methodology provides a much more detailed description of the DSD vertical and temporal variations. While the extent and evolution of the squall line is well reproduced by the model, the 1-h low-reflectivity transition region is not. In the stratiform region, simulations with both schemes are able to reproduce the observed downdraft and the associated significative subsaturation below the melting level, but with a slight overestimation of the relative humidity. Under this subsaturated air, the simulated rain mixing ratio continuously decreases toward the ground, in agreement with the observations. Conversely, the profiles of the mean volume diameter and the concentration parameter of the DSDs are not well reproduced. These discrepancies pinpoint at an issue in the representation of rain microphysics. The companion paper, investigates the sources of the biases in the microphysics processes in the rain layer by performing numerical sensitivity studies.

A comparison between retrieved properties of the rain drop size distributions (DSDs) from multifrequency cloud radar observations and WRF Model results using either the Morrison or the Thompson bulk microphysics scheme is performed in order to evaluate the model’s ability to predict the rain microphysics. This comparison reveals discrepancies in the vertical profile of the rain DSDs for the stratiform region of the squall-line system observed on 12 June 2011 over Oklahoma. Based on numerical sensitivity analyses, this study addresses the bias at the top of the rain layer and the vertical evolution of the DSD properties (i.e., of Dm and N0*). In this way, the Thompson scheme is used to explore the sensitivity to the melting process. Moreover, using the Thompson and Morrison schemes, the sensitivity of the DSD vertical evolution to different breakup and self-collection parameterizations is studied. Results show that the DSDs are strongly dependent on the representation of the melting process in the Thompson scheme. In the Morrison scheme, the simulations with more efficient breakup reproduce the DSD properties with better fidelity. This study highlights how the inaccuracies in simulated Dm and N0* for both microphysics schemes can impact the evaporation rate, which is systematically underestimated in the model.