Bulk Microphysical Parameterization Research Articles

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.

Evaluation of bulk microphysics parameterizations for simulating the vertical structure of heavy rainfall between Korea and the United States

The Korean Peninsula and the United States (US) have many contrasting precipitation characteristics that are part of the oceanic monsoon and continental convection. This study evaluated 11 microphysics schemes in the Weather Research and Forecasting model in terms of vertical reflectivity structure for heavy rainfall during the summer in Korea and the US. Compared to satellite radar observation, the correlation coefficients for the reflectivity structure for 11 microphysics schemes were 0.581–0.906 and 0.745–0.918 for the Korean and US domains, respectively. We observed that a simple scheme (such as the use of single moment and limited ice categories) does not always fail, and complex methods do not always succeed. The relatively low correlation over Korea versus the US was assumed because many microphysics parameterizations were developed and tuned over the US. Consequently, some microphysics schemes exhibited a severe overestimation of reflectivity in both the upper and lower levels over the Korean Peninsula. In contrast, a microphysics scheme that was evaluated and improved for both continental and maritime convection regions, showed the best performance on the Korean Peninsula too. This highlights the importance of evaluation for various regions with different precipitation characteristics to improve parameterization of cloud microphysics. Because Korean and US domains are representative areas of oceanic monsoon and continental convection, we expect that this study can serve as a conceptual guide to suggest which microphysics parameterizations should be used for a realistic simulation in continental and oceanic monsoon precipitation regimes.

Considering Various Multimoment Bulk Microphysics Schemes for Simulation of Passive Microwave Radiative Signatures

Passive microwave radiative transfer models are strongly influenced by the cloud and precipitation hydrometeor properties. Particularly, they can sensitively interact with frozen hydrometeors through multiple high-frequency channels. However, frozen hydrometeors are one of the most difficult parameters to comprehend due to the lack of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> data. Until recently, studies have attempted to describe more reasonable hydrometeor distributions using various microphysics parameterizations coupled with the weather research and forecasting (WRF) models. Herein, we aim to apply the proposed methods to passive microwave radiative transfer simulations. We implemented a passive microwave radiative transfer simulation that considers various microphysical assumptions by creating a new Mie scattering lookup table. Furthermore, we evaluated the bulk microphysics parameterizations [WDM6, Morrison (MORR), Thompson (THOM), and P3 schemes] for the tropical cyclone Krosa (2019) that were observed by the global precipitation measurement microwave imager instrument, specifically concentrating on the rimed and aggregated ice categories (snow, graupel, and P3 ice). Based on the evaluation results, we concluded the following: WDM6 graupel and MORR snow afford excessive scattering signals at 37 GHz. However, at 166 GHz, none of the parameterizations produces sufficient scattering signals for comparison with the observations. The P3 ice affords significantly underestimated scattering signals at 89 GHz and above, despite its sophisticated assumptions. On the contrary, THOM snow affords scattering signals similar to the observations, despite a shape-related error. In summary, this study introduced a method for implementing a microphysical-consistent radiative transfer computation and successfully showed how various microphysical assumptions of clouds can change the passive microwave radiative signatures.

WRF Rainfall Modeling Post-Processing by Adaptive Parameterization of Raindrop Size Distribution: A Case Study on the United Kingdom

Raindrop size distribution (RSD) is a key parameter in the Weather Research and Forecasting (WRF) model for rainfall estimation, with gamma distribution models commonly used to describe RSD under WRF microphysical parameterizations. The RSD model sets the shape parameter (μ) as a constant of gamma distribution in WRF double-moment bulk microphysics schemes. Here, we propose to improve the gamma RSD model with an adaptive value of μ based on the rainfall intensity and season, designed using a genetic algorithm (GA) and the linear least-squares method. The model can be described as a piecewise post-processing function that is constant when rainfall intensity is &lt;1.5 mm/h and linear otherwise. Our numerical simulation uses the WRF driven by an ERA-interim dataset with three distinct double-moment bulk microphysical parameterizations, namely, the Morrison, WDM6, and Thompson aerosol-aware schemes for the period of 2013–2017 over the United Kingdom at a 5 km resolution. Observations were made using a disdrometer and 241 rain gauges, which were used for calibration and validation. The results show that the adaptive-μ model of the gamma distribution was more accurate than the gamma RSD model with a constant shape parameter, with the root-mean-square error decreasing by averages of 23.62%, 11.33%, and 22.21% for the Morrison, WDM6, and Thompson aerosol-aware schemes, respectively. This model improves the accuracy of WRF rainfall simulation by applying adaptive RSD parameterization and can be integrated into the simulation of WRF double-moment microphysics schemes. The physical mechanism of the RSD model remains to be determined to improve its performance in WRF bulk microphysics schemes.

A Comparison of Two Bulk Microphysics Parameterizations for the Study of Aerosol Impacts on an Idealized Supercell

A Comparison of Two Bulk Microphysics Parameterizations for the Study of Aerosol Impacts on an Idealized Supercell

Evaluating Warm and Cold Rain Processes in Cloud Microphysical Schemes Using OLYMPEX Field Measurements

AbstractField observations from the Olympic Mountain Experiment (OLYMPEX) around western Washington State during two atmospheric river (AR) events in November 2015 were used to evaluate several bulk microphysical parameterizations (BMPs) within the Weather Research and Forecasting (WRF) Model. These AR events were characterized by a prefrontal period of stable, terrain-blocked flow with an abundance of cold rain over the lowland region followed by less stable, unblocked flow with more warm rain, and a shift in the largest precipitation amounts to over the windward Olympic slopes. Our WRF simulations underpredicted the precipitation by 19%–36% in the Morrison (MORR) and Thompson (THOM) BMPs and 10%–23% in the predicted particle properties (P3) BMP, with the largest underpredictions over the windward slopes during the more convective, unblocked flow conditions. Several important processes related to the BMPs led to the differences in simulated precipitation. First, the prognostic single ice category parameterization in the P3 scheme promoted a more realistic evolution of rimed particles and larger cold rain production, which led to the lowest underpredictions in precipitation among the schemes. Second, efficient melting processes associated with the production of nonspherical ice and snow in the P3 and THOM BMPs, respectively, promoted a more realistic transition to rain fall speeds within the warm layer compared to the spherical snow assumption in MORR. Last, all BMPs underpredict the contribution of warm rain processes to the surface precipitation, particularly during the unblocked flow period, which may be partly explained by too weak condensational and collisional growth processes due to the neglect of turbulence parameterizations within the schemes.

Sensitivity of Summer Precipitation Simulation to Microphysics Parameterization Over Eastern China: Convection‐Permitting Regional Climate Simulation

AbstractWith a six‐year (2009–2014) summer climate simulation using the Weather Research and Forecasting model at convection‐permitting resolution (4‐km grid spacing), the effects of microphysics parameterization (MP) schemes on precipitation characteristics are investigated in this study. The convection‐permitting simulations employ three popular MP schemes, namely, Lin (single‐moment bulk MP), Weather Research and Forecasting Single‐Moment 5‐class (one‐moment and mixed‐phased MP), and Thompson (two‐moment and mixed‐phase MP) scheme. By evaluating the simulations against the CMORPH, rain gauge (Station), and ERA‐Interim data, it is found that the convection‐permitting model reproduce well the summer precipitation amount and the associated large‐scale atmospheric circulations, which are insensitive to the choice of MP schemes. The simulations with three MP schemes overestimate the precipitation amount, especially over the Yangtze‐Huaihe River Valley. The overestimations may be due to the systematic biases, and cannot be significantly reduced by using different MP schemes. Moreover, all simulations capture well the major features of precipitation diurnal variations and their transition characteristics, but they significantly overestimate the precipitation frequency while underestimate the precipitation intensity. The analysis on the microphysical hydrometeors shows that the model‐simulated precipitation amount is considerably affected by the vertical profiles of solid hydrometeors, especially the snow and graupel particles. The Thompson scheme creates more snow particles and less graupel than the other schemes, while produces the least precipitation amount that best matches the CMORPH.

Sensitivity of a Simulated Squall Line During Southern China Monsoon Rainfall Experiment to Parameterization of Microphysics

AbstractA squall line on 22 May 2014 during the Southern China Monsoon Rainfall Experiment period is simulated with four bulk microphysical parameterizations (BMPs) using the Weather Research and Forecasting (WRF) model. Although most BMPs are able to capture the basic features of the squall line, the movement, morphology, and especially the length of the simulated squall lines differ significantly among BMPs. Morrison scheme tends to simulate a slower moving squall line with a weaker cold pool and better trailing stratiform cloud and precipitation due to the smaller snow fall speed and faster generation of snow particles than other schemes. Assuming hail or graupel in different schemes could result in different melting profiles of rimed‐ice particles, with hail melted substantially below the 0°C isotherm and contributing to the cold pool production significantly in WRF double‐moment six‐class microphysics scheme because of its use of larger fall speed for hail. Although ice‐phase particles simulated differ significantly among BMPs, it is rain evaporation that dominates the cold pool generation and maintenance of the squall line in this case. Stronger rain evaporation generally contributes to stronger cold pools and thus faster movement and longer simulated squall lines. Failure of the Stony Brook University‐YLin scheme in capturing the squall line was identified to be related to the turnoff of rain evaporation once environmental relative humidity is larger than 90%. With modifications of rain evaporation calculation and saturation adjustment method, the scheme is able to simulate this squall line reasonably well.

Partitioning Ice Water Content from Retrievals and Its Application in Model Comparison

Abstract Retrieved bulk microphysics from remote sensing observations is a composite of ice, snow, and graupel in the three-species ice-phase bulk microphysics parameterization. In this study, density thresholds are used to partition the retrieved ice particle size distribution (PSD) into small, median, and large particle size modes from millimeter cloud radar (MMCR) observations in the tropics and global CloudSat and CALIPSO ice cloud property product (2C-ICE) observations. It shows that the small mode can contribute to more than 60% of the total ice water content (IWC) above 12 km (colder than 220 K). Below that, dominant small mode transitions to dominant median mode. The large mode contributes to less than 10%–20% at all height levels. The PSD assumption in retrieval may cause about 10% error in the IWC partition ratio. The lidar-only region in 2C-ICE is dominated by the small mode, while the median mode dominates the radar-only region. For the three-species ice-phase bulk microphysics parameterizations, the cloud ice mass mainly consists of the small mode. But snow and graupel in the models are not equivalent to the median and large modes in the observations, respectively. Therefore, they need to be repartitioned with rebuilt PSDs from the model assumptions using the same partition technique as the observations. The repartitioned IWCs in each mode from different ice species need to be added together and then compared with the corresponding mode from observations.

Sensitivity of Numerical Simulations of a Mesoscale Convective System to Ice Hydrometeors in Bulk Microphysical Parameterization

Mesoscale convective systems (MCSs) and their associated cloud properties are the important factors that influence the aviation activities, yet they present a forecasting challenge in numerical weather prediction. In this study, the sensitivity of numerical simulations of an MCS over the US Southern Great Plains to ice hydrometeors in bulk microphysics (MP) schemes has been investigated using the Weather Research and Forecasting (WRF) model. It is found that the simulated structure, life cycle, cloud coverage, and precipitation of the convective system as well as its associated cold pools are sensitive to three selected MP schemes, namely, the WRF single-moment 6-class (WSM6), WRF double-moment 6-class (WDM6, with the double-moment treatment of warm-rain only), and Morrison double-moment (MORR, with the double-moment representation of both warm-rain and ice) schemes. Compared with observations, the WRF simulation with WSM6 only produces a less organized convection structure with a short lifetime, while WDM6 can produce the structure and length of the MCS very well. Both simulations heavily underestimate the precipitation amount, the height of the radar echo top, and stratiform cloud fractions. With MORR, the model performs well in predicting the lifetime, cloud coverage, echo top, and precipitation amount of the convection. Overall results demonstrate the importance of including double-moment representation of ice hydrometeors along with warm-rain. Additional experiments are performed to further examine the role of ice hydrometeors in numerical simulations of the MCS. Results indicate that replacing graupel with hail in the MORR scheme improves the prediction of the convective structure, especially in the convective core region.

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.

Sensitivity of WRF Cloud Microphysics to Simulations of a Convective Storm Over the Nepal Himalayas

Background:This paper investigates sensitivity of bulk microphysical parameterization (BMP) schemes within the Weather Research and Forecasting (WRF) model to simulate a convective storm that generally evolves during pre-monsoon season (March – May) across the foothills of the Himalayas.Method:Four mixed-phase BMP schemes (Morrison, Lin, WDM6, and WSM6), which are parameterized with an increasing complexity from single to double moments of particle distribution to represent cloud processes, are used with an explicit convection permitting grid resolution (3 km x 3 km). Experiments are set up to simulate a convective storm that occurred in the late afternoon of 18thMay 2011 and compared with i) Satellite-based tropical rainfall measuring mission (TRMM) 3B42 v7 data, and ii) Ground-based observations at Nagarkot (27.7°N, 85.5°E), Nepal.Result:Our results show that the simulated storm characteristics are not overly sensitive to the chosen BMP schemes. In general, all the BMP schemes produce similar rainfall characteristics and compares reasonably well with the observations across Siwalik Hills and Middle Mountains, which act as a topographic barrier to low level circulations and receive more rain. The schemes, however, show negative bias across central Nepal including the Kathmandu Valley, albeit the magnitude and spatial distribution of bias are different between the schemes. In contrast, upper level total water condensate and cloud fraction show a strong sensitivity to the BMP schemes.Conclusion:Overall, the Morrison scheme, in addition to warm clouds which also predict double moment distribution of all hydrometeors in the cold-cloud processes, a dominant cloud forming process in the Himalayas, accurately represents the mechanism and outperforms the simplified schemes based on root mean square error (RMSE) analysis.

Improvements to the snow melting process in a partially double moment microphysics parameterization

AbstractPolarimetric upgrades to the U.S. radar network have allowed new insight into the precipitation processes of tropical cyclones. Previous work by the authors compared the reflectivity at horizontal polarization and differential reflectivity observations from two hurricanes to simulated radar observations from the WRF model, and found that the aerosol‐aware Thompson‐Eidhammer microphysical scheme performed the best of several commonly used bulk microphysical parameterizations. Here we expand our investigation of the Thompson‐Eidhammer scheme, and find that though it provided the most accurate forecast in terms of wind speed and simulated radar signatures, the scheme produces areas in which the differential reflectivity was much higher than observed. We conclude that the Thompson‐Eidhammer scheme produces drop size distributions that have a larger median drop size than observed in regions of light stratiform precipitation. Examination of the vertical structure of simulated differential reflectivity indicates that the source of the discrepancy between the model and radar observations likely originates within the melting layer. The treatment of number production of rain drops from melting snow in the microphysical scheme is shown to be the ultimate source of the enhancement of differential reflectivity. A modification to the scheme is shown to result in better fidelity of the radar variables with the observations without degrading the short‐term intensity forecast. Additional tests with an idealized squall line simulation are consistent with the hurricane results, suggesting the modification is generally applicable. The modifications to the Thompson‐Eidhammer scheme shown here have been incorporated into updates of the WRF model starting with version 3.8.1.

A comparative study between bulk and bin microphysical schemes of a simulated squall line in East China

AbstractA squall line occurred in East China during 12 July 2014 was simulated with the Weather Research and Forecasting (WRF) model using spectral bin and two‐moment bulk microphysical parameterization scheme, respectively. Comparative study showed that significant differences existed in the dynamic, thermodynamic and microphysical structures of squall line between bulk and bin simulation results. The bulk scheme produced a well‐organized but shorter radar structure while bin scheme simulated scattered but stronger radar echo which was more consistent with observation. Bulk scheme had a better performance in predicting the strong rainfall areas and amount. The strong rear‐to‐front (RTF) inflow and convective updrafts were identified in bulk scheme by comparison with weak RTF and updrafts in bin scheme. In addition, bulk simulated a deeper cold pool than bin. Much higher cloud droplet number concentration was simulated by bulk scheme, while higher raindrop mass and number concentration was generated by bin scheme. Detailed analysis and sensitivity tests are needed in future to further investigate the possible mechanisms that responsible for the distinctive results.

Comparisons of Modeled and Observed Reflectivities and Fall Speeds for Snowfall of Varied Riming Degrees during Winter Storms on Long Island, New York.

Derived radar reflectivities and fall speeds for four Weather Research and Forecasting (WRF) Model bulk microphysical parameterizations (BMPs) run at 1.33-km grid spacing are compared with ground-based, vertically pointing Ku-band radar, scanning S-band radar, and in situ measurements at Stony Brook, New York. Simulations were partitioned into periods of observed riming degree as determined manually using a stereo microscope and camera during nine winter storms. Simulations were examined to determine whether the selected BMPs captured the effects of varying riming intensities, provided a reasonable match to the vertical structure of radar reflectivity or fall speed, and whether they produced reasonable surface fall speed distributions. Schemes assuming nonspherical mass-diameter relationships yielded reflectivity distributions closer to observed values. All four schemes examined in this study provided a better match to the observed, vertical structure of reflectivity during moderate riming than light riming periods. The comparison of observed and simulated snowfall speeds had mixed results. One BMP produced episodes of excessive cloud water at times, resulting in fall speeds that were too large. However, most schemes had frequent periods of little or no cloud water during moderate riming periods and thus underpredicted the snowfall speeds at lower levels. Short, 1-4-h periods with relatively steady snow conditions were used to compare BMP and observed size and fall speed distributions. These limited data suggest the examined BMPs underpredict fall speeds of cold-type snow habits and underrepresent aggregates larger than 4-mm diameter.

Coupling spectral‐bin cloud microphysics with the MOSAIC aerosol model in WRF‐Chem: Methodology and results for marine stratocumulus clouds

AbstractAerosol‐cloud interaction processes can be represented more physically with bin cloud microphysics relative to bulk microphysical parameterizations. However, due to computational power limitations in the past, bin cloud microphysics was often run with very simple aerosol treatments. The purpose of this study is to represent better aerosol‐cloud interaction processes in the Chemistry version of Weather Research and Forecast model (WRF‐Chem) at convection‐permitting scales by coupling spectral‐bin cloud microphysics (SBM) with the MOSAIC sectional aerosol model. A flexible interface is built that exchanges cloud and aerosol information between them. The interface contains a new bin aerosol activation approach, which replaces the treatments in the original SBM. It also includes the modified aerosol resuspension and in‐cloud wet removal processes with the droplet loss tendencies and precipitation fluxes from SBM. The newly coupled system is evaluated for two marine stratocumulus cases over the Southeast Pacific Ocean with either a simplified aerosol setup or full‐chemistry. We compare the aerosol activation process in the newly coupled SBM‐MOSAIC against the SBM simulation without chemistry using a simplified aerosol setup, and the results show consistent activation rates. A longer time simulation reinforces that aerosol resuspension through cloud drop evaporation plays an important role in replenishing aerosols and impacts cloud and precipitation in marine stratocumulus clouds. Evaluation of the coupled SBM‐MOSAIC with full‐chemistry using aircraft measurements suggests that the new model works realistically for the marine stratocumulus clouds, and improves the simulation of cloud microphysical properties compared to a simulation using MOSAIC coupled with the Morrison two‐moment microphysics.

Comparison of observed and simulated spatial patterns of ice microphysical processes in tropical oceanic mesoscale convective systems

AbstractTo equitably compare the spatial pattern of ice microphysical processes produced by three microphysical parameterizations with each other, observations, and theory, simulations of tropical oceanic mesoscale convective systems (MCSs) in the Weather Research and Forecasting (WRF) model were forced to develop the same mesoscale circulations as observations by assimilating radial velocity data from a Doppler radar. The same general layering of microphysical processes was found in observations and simulations with deposition anywhere above the 0°C level, aggregation at and above the 0°C level, melting at and below the 0°C level, and riming near the 0°C level. Thus, this study is consistent with the layered ice microphysical pattern portrayed in previous conceptual models and indicated by dual‐polarization radar data. Spatial variability of riming in the simulations suggests that riming in the midlevel inflow is related to convective‐scale vertical velocity perturbations. Finally, this study sheds light on limitations of current generally available bulk microphysical parameterizations. In each parameterization, the layers in which aggregation and riming took place were generally too thick and the frequency of riming was generally too high compared to the observations and theory. Additionally, none of the parameterizations produced similar details in every microphysical spatial pattern. Discrepancies in the patterns of microphysical processes between parameterizations likely factor into creating substantial differences in model reflectivity patterns. It is concluded that improved parameterizations of ice‐phase microphysics will be essential to obtain reliable, consistent model simulations of tropical oceanic MCSs.

Implementation of the WSM5 and WSM6 Single Moment Microphysics Scheme into the RAMS Model: Verification for the HyMeX-SOP1

This paper shows the results of the implementation of two widely used bulk microphysics parameterizations (BMP) into the Regional Atmospheric Modeling System to improve the Quantitative Precipitation Forecast (QPF). The schemes are the WSM5 and WSM6 (WRF-single-moment-microphysics classes 5 and 6). The RAMS is run at high horizontal resolution (4 km) over the whole Italian territory and, to mimic the operational context, it is initialized by the analysis/forecast cycle issued at 12 UTC by the European Centre for Medium Weather Range Forecast (ECMWF). The performance of the BMP is analysed for the period of September 11 to October 31, 2012, which span most of the Special Observing Period 1 (SOP1) of the hydrological cycle in the Mediterranean experiment (HyMeX). For this period a database of daily precipitation of thousands of rain gauges over the Italian territory is available. In SOP1 few hazardous events occurred over Italy and, for one of them, the model performance is shown in detail. The potential improvement gained by combining the model outputs with different BMP in a single forecast is finally explored.

Evaluation of double-moment representation of ice hydrometeors in bulk microphysical parameterization: comparison between WRF numerical simulations and UND-Citation data during MC3E

The influence of double-moment representation of warm-rain and ice hydrometeors on the numerical simulations of a mesoscale convective system (MCS) over the US Southern Great Plains has been evaluated. The Weather Research and Forecasting (WRF) model is used to simulate the MCS with three different microphysical schemes, including the WRF single-moment 6-class (WSM6), WRF double-moment 6-class (WDM6), and Morrison double-moment (MORR) schemes. It is found that the double-moment schemes outperform the single-moment schemes in terms of the simulated structure, life cycle, cloud coverage, precipitation, and microphysical properties of the MCS. However, compared with UND-Citation observations, collected during the Midlatitude Continental Convective Clouds Experiment (MC3E), the WRF simulated ice hydrometeors with all three schemes do not agree well with the observations. Overall results from this study suggest that uncertainty in microphysical schemes could still be a productive area of future research from perspective of both model improvements and observations.

A Lagrangian drop model to study warm rain microphysical processes in shallow cumulus

AbstractIn this study, we introduce a Lagrangian drop (LD) model to study warm rain microphysical processes in shallow cumulus. The approach combines Large‐Eddy Simulations (LES) including a bulk microphysics parameterization with an LD model for raindrop growth. The LD model is one‐way coupled with the Eulerian LES and represents all relevant rain microphysical processes such as evaporation, accretion, and selfcollection among LDs as well as dynamical effects such as sedimentation and inertia. To test whether the LD model is fit for purpose, a sensitivity study for isolated shallow cumulus clouds is conducted. We show that the surface precipitation rate and the development of the raindrop size distribution are sensitive to the treatment of selfcollection in the LD model. Some uncertainty remains for the contribution of the subgrid‐scale turbulence to the relative velocity difference of a pair of LDs, which appears as a factor in the collision kernel. Sensitivities to other model parameters such as the initial multiplicity or the initial mass distribution are small. Overall, sensitivities of the LD model are small compared to the uncertainties in the assumptions of the bulk rain microphysics scheme, and the LD model is well suited for particle‐based studies of raindrop growth and dynamics. This opens up the opportunity to study effects like recirculation, deviations from terminal fall velocity and other microphysical phenomena that so far were not accessible for bin, bulk, or parcel models.