Two-moment Microphysics Research Articles

A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images

Abstract. In combination with observations from visible satellite channels, near-infrared channels can provide valuable additional cloud information, e.g. on cloud phase and particle sizes, which is also complementary to the information content of thermal infrared channels. Exploiting near-infrared channels for operational data assimilation and model evaluation requires a sufficiently fast and accurate forward operator. This study presents an extension to the method for fast satellite image synthesis (MFASIS) that allows for simulating reflectances of the 1.6 µm near-infrared channel based on a computationally efficient neural network with the same accuracy that has already been achieved for visible channels. For this purpose, it is important to better represent vertical variations in effective cloud particle radii, as well as mixed-phase clouds and molecular absorption in the idealized profiles used to train the neural network. A new approach employing a two-layer model of water, ice and mixed-phase clouds is described, and the relative importance of the different input parameters characterizing the idealized profiles is analysed. A comprehensive data set sampled from Integrated Forecasting System (IFS) forecasts together with different parameterizations of the effective water and ice particle radii is used for the development and evaluation of the method. Further evaluation uses a month of ICOsahedral Non-hydrostatic development based on version 2.6.1 (ICON-D2) hindcasts with effective radii directly determined by the two-moment microphysics scheme of the model. In all cases, the mean absolute reflectance error achieved is about 0.01 or smaller, which is an order of magnitude smaller than typical differences between reflectance observations and corresponding model values. The errors related to the imperfect training of the neural networks present only a small contribution to the total error, and evaluating the networks takes less than a microsecond per column on standard CPUs. The method is also applicable for many other visible and near-infrared channels with weak water vapour sensitivity.

Biases and Skill of Four Two-Moment Bulk Microphysics Schemes in Convection-Allowing Forecasts for the 2018 Hazardous Weather Testbed Spring Forecasting Experiment Period

Abstract A proof-of-concept systematic evaluation of convective hazards is applied to short-term (1–6 h) forecasts using the Morrison, National Severe Storms Laboratory (NSSL), Predicted Particle Properties (P3), and Thompson two-moment microphysics schemes for the 2018 NOAA Hazardous Weather Testbed Spring Forecasting Experiment (HWT SFE) period (hereafter “MORR,” “NSSL,” “P3,” and “THOM” experiments, respectively). Four convective line cases are highlighted to elaborate on relative experiment biases/skill. Composite reflectivity and 1-h accumulated precipitation are examined to determine storm coverage/precipitation biases/skill utilizing point-based verification with a neighborhood. Simulated 1–6-km updraft helicity and observed 3–6-km azimuthal shear and MESH are examined to consider simulated rotation and hail core prediction with object-based scores. Over the full season, MORR displays little overall storm coverage bias relative to NSSL, P3, and THOM underprediction. The equitable threat score (ETS) and fractions skill score (FSS) of P3 are lower than the other experiments. P3 and THOM underpredict convective regions with intense reflectivity relative to MORR and NSSL overprediction. All experiments underpredict precipitation amounts. P3 light precipitation FSS is lower than other experiments. Rotation object verification exhibits sensitivity to microphysics experiments, as microphysics has an indirect influence on storm dynamics. While P3 has the largest hail object underprediction, all experiments grossly overpredict the number of hail objects in convective line cases despite forecast objects defined with the same product (MESH) and threshold as observations. The importance of microphysics ice parameterization and ongoing scheme updates highlight the need to apply this verification framework to optimal/updated schemes before optimizing ensemble design.

Interaction of microphysics and dynamics in a warm conveyor belt simulated with the ICOsahedral Nonhydrostatic (ICON) model

Abstract. Warm conveyor belts (WCBs) produce a major fraction of precipitation in extratropical cyclones and modulate the large-scale extratropical circulation. Diabatic processes, in particular associated with cloud formation, influence the cross-isentropic ascent of WCBs into the upper troposphere and additionally modify the potential vorticity (PV) distribution, which influences the larger-scale flow. In this study we investigate heating and PV rates from all diabatic processes, including microphysics, turbulence, convection, and radiation, in a case study that occurred during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) campaign using the Icosahedral Nonhydrostatic (ICON) modeling framework. In particular, we consider all individual microphysical process rates that are implemented in ICON's two-moment microphysics scheme, which sheds light on (i) which microphysical processes dominate the diabatic heating and PV structure in the WCB and (ii) which microphysical processes are the most active during the ascent and influence cloud formation and characteristics, providing a basis for detailed sensitivity experiments. For this purpose, diabatic heating and PV rates are integrated for the first time along online trajectories across nested grids with different horizontal resolutions. The convection-permitting simulation setup also takes the reduced aerosol concentrations over the North Atlantic into account. Our results confirm that microphysical processes are the dominant diabatic heating source during ascent. Near the cloud top longwave radiation cools WCB air parcels. Radiative heating and corresponding PV modification in the upper troposphere are non-negligible due to the longevity of the WCB cloud band. In the WCB ascent region, the process rates from turbulent heating and microphysics partially counteract each other. From all microphysical processes condensational growth of cloud droplets and vapor deposition on frozen hydrometeors most strongly influence diabatic heating and PV, while below-cloud evaporation strongly cools WCB air parcels prior to their ascent and increases their PV value. PV production is the strongest near the surface with substantial contributions from condensation, melting, evaporation, and vapor deposition. In the upper troposphere, PV is reduced by diabatic heating from vapor deposition, condensation, and radiation. Activation of cloud droplets as well as homogeneous and heterogeneous freezing processes have a negligible diabatic heating contribution, but their detailed representation is important for, e.g., hydrometeor size distributions. Generally, faster-ascending WCB trajectories are heated markedly more than more slowly ascending WCB trajectories, which is linked to larger initial specific humidity content providing a thermodynamic constraint on total microphysical heating. Yet, the total diabatic heating contribution of convectively ascending trajectories is relatively small due to their small fraction in this case study. Our detailed case study documents the effect of different microphysical processes implemented in ICON's two-moment scheme for heating and PV rates in a WCB from a joint Eulerian and Lagrangian perspective. It emphasizes the predominant role of microphysical processes and provides a framework for future experiments on cloud microphysical sensitivities in WCBs.

Climate response to off-equatorial stratospheric sulfur injections in three Earth system models – Part 1: Experimental protocols and surface changes

Abstract. There is now substantial literature on climate model studies of equatorial or tropical stratospheric SO2 injections that aim to counteract the surface warming produced by rising concentrations of greenhouse gases. Here we present the results from the first systematic intercomparison of climate responses in three Earth system models wherein the injection of SO2 occurs at different latitudes in the lower stratosphere: CESM2-WACCM6, UKESM1.0 and GISS-E2.1-G. The first two use a modal aerosol microphysics scheme, while two versions of GISS-E2.1-G use a bulk aerosol (One-Moment Aerosol, OMA) and a two-moment (Multiconfiguration Aerosol TRacker of mIXing state, MATRIX) microphysics approach, respectively. Our aim in this work is to determine commonalities and differences between the climate model responses in terms of the distribution of the optically reflective sulfate aerosols produced from the oxidation of SO2 and in terms of the surface response to the resulting reduction in solar radiation. A focus on understanding the contribution of characteristics of models transport alongside their microphysical and chemical schemes, and on evaluating the resulting stratospheric responses in different models, is given in the companion paper (Bednarz et al., 2023). The goal of this exercise is not to evaluate these single-point injection simulations as stand-alone proposed strategies to counteract global warming; instead we determine sources and areas of agreement and uncertainty in the simulated responses and, ultimately, the possibility of designing a comprehensive intervention strategy capable of managing multiple simultaneous climate goals through the combination of different injection locations. We find large disagreements between GISS-E2.1-G and the CESM2-WACCM6 and UKESM1.0 models regarding the magnitude of cooling per unit of aerosol optical depth (AOD) produced, which varies from 4.7 K per unit of AOD in CESM2-WACCM6 to 16.7 K in the GISS-E2.1-G version with two-moment aerosol microphysics. By normalizing the results with the global mean response in each of the models and thus assuming that the amount of SO2 injected is a free parameter that can be managed independently, we highlight some commonalities in the overall distributions of the aerosols, in the inter-hemispheric surface temperature response and in shifts to the Intertropical Convergence Zone, as well as some areas of disagreement, such as the extent of the aerosol confinement in the equatorial region and the efficiency of the transport to polar latitudes. In conclusion, we demonstrate that it is possible to use these simulations to produce more comprehensive injection strategies in multiple climate models. However, large differences in the injection magnitudes can be expected, potentially increasing inter-model spreads in some stratospheric quantities (such as aerosol distribution) while reducing the spread in the surface response in terms of temperature and precipitation; furthermore, the selection of the injection locations may be dependent on the models' specific stratospheric transport.

Direct Assimilation of Radar Reflectivity Data Using Ensemble Kalman Filter Based on a Two-Moment Microphysics Scheme for the Analysis and Forecast of Typhoon Lekima (2019)

We investigate the impact of directly assimilating radar reflectivity data using an ensemble Kalman filter (EnKF) based on a double-moment (DM) microphysics parameterization (MP) scheme in GSI-EnKF data assimilation (DA) framework and WRF model for a landfall typhoon Lekima (2019). Observations from a single operational coastal Doppler are quality-controlled and assimilated. Compared with the baseline experiment initialized by GFS analysis, the reflectivity data assimilation experiment (Z-DA) resulted in an obvious improvement in both structural analysis and typhoon forecast skills in terms of intensity, precipitation, and track. Sensitivity experiments were conducted to evaluate the ability of EnKF to update certain state variables considering that the degree of freedom of analytical variables increased with a DM MP scheme. When either the total number concentration or other large-scale state variables that are not directly linked to reflectivity observations via the observation operator are not updated, the tendency of RMSIs and PS to be imbalanced is significantly increased during DA cycles compared to those of Z-DA with updating a full set of state variables, resulting in increased intensity and track forecast errors. These results indicate that the reliable ensemble covariance could handle the underconstraint issue associated with the DM scheme, and helps in obtaining more physically balanced analytical fields.

New investigations on homogeneous ice nucleation: the effects of water activity and water saturation formulations

Abstract. Laboratory measurements at the AIDA cloud chamber and airborne in situ observations suggest that the homogeneous freezing thresholds at low temperatures are possibly higher than expected from the so-called “Koop line”. This finding is of importance, because the ice onset relative humidity affects the cirrus cloud coverage and, at the very low temperatures of the tropical tropopause layer, together with the number of ice crystals also the transport of water vapor into the stratosphere. Both the appearance of cirrus clouds and the amount of stratospheric water feed back to the radiative budget of the atmosphere. In order to explore the enhanced ice onset humidities, we re-examine the entire homogeneous ice nucleation process, ice onset, and nucleated crystal numbers, by means of a two-moment microphysics scheme embedded in the trajectory-based model (CLaMS-Ice) as follows: the well-understood and described theoretical framework of homogeneous ice nucleation includes certain formulations of the water activity of the freezing aerosol particles and the saturation vapor pressure of water with respect to liquid water. However, different formulations are available for both parameters. Here, we present extensive sensitivity simulations testing the influence of three different formulations for the water activity and four for the water saturation on homogeneous ice nucleation. We found that the number of nucleated ice crystals is almost independent of these formulations but is instead sensitive to the size distribution of the freezing aerosol particles. The ice onset humidities, also depending on the particle size, are however significantly affected by the choices of the water activity and water saturation, in particular at cold temperatures ≲205 K. From the CLaMS-Ice sensitivity simulations, we here provide combinations of water saturation and water activity formulations suitable to reproduce the new, enhanced freezing line.

Improving the representation of aggregation in a two-moment microphysical scheme with statistics of multi-frequency Doppler radar observations

Abstract. Aggregation is a key microphysical process for the formation of precipitable ice particles. Its theoretical description involves many parameters and dependencies among different variables that are either insufficiently understood or difficult to accurately represent in bulk microphysics schemes. Previous studies have demonstrated the valuable information content of multi-frequency Doppler radar observations to characterize aggregation with respect to environmental parameters such as temperature. Comparisons with model simulations can reveal discrepancies, but the main challenge is to identify the most critical parameters in the aggregation parameterization, which can then be improved by using the observations as constraints. In this study, we systematically investigate the sensitivity of physical variables, such as number and mass density, as well as the forward-simulated multi-frequency and Doppler radar observables, to different parameters in a two-moment microphysics scheme. Our approach includes modifying key aggregation parameters such as the sticking efficiency or the shape of the size distribution. We also revise and test the impact of changing functional relationships (e.g., the terminal velocity–size relation) and underlying assumptions (e.g., the definition of the aggregation kernel). We test the sensitivity of the various components first in a single-column “snowshaft” model, which allows fast and efficient identification of the parameter combination optimally matching the observations. We find that particle properties, definition of the aggregation kernel, and size distribution width prove to be most important, while the sticking efficiency and the cloud ice habit have less influence. The setting which optimally matches the observations is then implemented in a 3D model using the identical scheme setup. Rerunning the 3D model with the new scheme setup for a multi-week period revealed that the large overestimation of aggregate size and terminal velocity in the model could be substantially reduced. The method presented is expected to be applicable to constrain other ice microphysical processes or to evaluate and improve other schemes.

Preconditioning of overcast-to-broken cloud transitions by riming in marine cold air outbreaks

Abstract. Marine cold air outbreaks (CAOs) commonly form overcast cloud decks that transition into broken cloud fields downwind, dramatically altering the local radiation budget. In this study, we investigate the impact of frozen hydrometeors on these transitions. We focus on a CAO case in the NW Atlantic, the location of the multi-year flight campaign ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment). We use MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, version 2) reanalysis fields to drive large eddy simulations with mixed-phase two-moment microphysics in a Lagrangian framework. We find that transitions are triggered by substantial rain (rainwater paths >25 g m−2), and only simulations that allow for aerosol depletion result in sustained breakups, as observed. Using a range of diagnostic ice nucleating particle concentrations, Ninp, we find that increasing ice progressively accelerates transitions, thus abbreviating the overcast state. Ice particles affect the cloud-topped boundary layer evolution, primarily through riming-related processes prior to substantial rain, leading to (1) a reduction in cloud liquid water, (2) early consumption of cloud condensation nuclei, and (3) early and light precipitation cooling and moistening below cloud. We refer to these three effects collectively as “preconditioning by riming”. Greater boundary layer aerosol concentrations available as cloud condensation nuclei (CCN) delay the onset of substantial rain. However, cloud breakup and low CCN concentration final stages are found to be inevitable in this case, due, primarily, to liquid water path buildup. An ice-modulated cloud transition speed suggests the possibility of a negative cloud–climate feedback. To address prevailing uncertainties in the model representation of mixed-phase processes, the magnitude of ice formation and riming impacts and, thereby, the strength of an associated negative cloud–climate feedback process, requires further observational evaluation by targeting riming hot spots with in situ imaging probes that allow for both the characterization of ice particles and abundance of supercooled droplets.

Improvement of aerosol activation/ice nucleation in a source-oriented WRF-Chem model to study a winter Storm in California

Abstract The source-oriented Weather Research and Forecasting chemistry (SOWC) model is modified to improve mixed-phase cloud parameterization by including aerosol aging processes (external mixture) in cloud activation/nucleation. The improved SOWC model is applied to investigate how aerosol mixing state influences cloud and ice formation and atmospheric optical properties during a winter storm. SOWC tracks 6-dimensional chemical variables (X, Z, Y, Size Bins, Source Types, Species) through an explicit simulation of atmospheric chemistry and physics. A new module is implemented into the enhanced SOWC model to simulate microphysics processes with all source-oriented hydrometeors (cloud, ice, rain, snow and graupel) by using the modified Morrison two-moment microphysics scheme. In this study, all aerosol source types can activate to form cloud droplets based on the Kohler theory, but the dust source type is the only source of ice nuclei (IN). The Goddard shortwave and longwave radiation schemes are modified to use a new geometric optics method to estimate cloud optical properties by considering the chemistry components and the physical shape of each hydrometeor. The improved SOWC model is used to study a winter storm event that occurred on 6 March 2011, along the western coast of the United States. Compared to ground-based observations, SOWC with the modified Morrison microphysics scheme and modified Goddard radiation schemes predicts reasonable rainfall but the onset of precipitation is delayed by 6 h. Contact freezing is the main mechanism for ice nuclei formation over the ocean because of the number of collisions and large radius gaps between cloud droplets and ice nuclei. However, immersion freezing becomes the dominant nucleation process when the storm approached over land due to increased CCN concentrations and smaller radius gaps between cloud droplets and ice nuclei, especially for the internally mixed simulation, as well as the orographic lifting effect. Increasing CCN and IN in the internal mixing experiment results in 1.7% less rainfall and snowfall over the western coast of the United States.

A representation of the collisional ice break-up process in the two-moment microphysics LIMA v1.0 scheme of Meso-NH

Abstract. The paper describes a switchable parameterization of collisional ice break-up (CIBU), an ice multiplication process that fits in with the two-moment microphysical Liquid Ice Multiple Aerosols (LIMA) scheme. The LIMA scheme with three ice types (pristine cloud ice crystals, snow aggregates, and graupel hail) was developed in the cloud-resolving mesoscale model (Meso-NH). Here, the CIBU parameterization assumes that collisional break-up is mostly efficient for the small and fragile snow aggregate class of particles when they are hit by large, dense graupel particles. The increase of cloud ice number concentration depends on a prescribed number (or a random number) of fragments being produced per collision. This point is discussed and analytical expressions of the newly contributing CIBU terms in LIMA are given. The scheme is run in the cloud-resolving mesoscale model (Meso-NH) to simulate a first case of a three-dimensional deep convective event with heavy production of graupel. The consequence of dramatically changing the number of fragments produced per collision is investigated by examining the rainfall rates and the changes in small ice concentrations and mass mixing ratios. Many budgets of the ice phase are shown and the sensitivity of CIBU to the initial concentration of freezing nuclei is explored. The scheme is then tested for another deep convective case where, additionally, the convective available potential energy (CAPE) is varied. The results confirm the strong impact of CIBU with up to a 1000-fold increase in small ice concentrations, a reduction of the rainfall or precipitating area, and an invigoration of the convection with higher cloud tops. Finally, it is concluded that the efficiency of the ice crystal fragmentation needs to be tuned carefully. The proposed parameterization of CIBU is easy to implement in any two-moment microphysics scheme. It could be used in this form to simulate deep tropical cloud systems where anomalously high concentrations of small ice crystals are suspected.

Using an Object-Based Approach to Quantify the Spatial Structure of Reflectivity Regions in Hurricane Isabel (2003). Part I: Comparisons between Radar Observations and Model Simulations

Abstract When a hurricane undergoes extratropical transition (ET), its rainbands evolve from a circular and compact shape to a more elongated, fragmented, and dispersed configuration with an exposed circulation center. This study calculates five metrics to measure these spatial changes in reflectivity regions as Hurricane Isabel (2003) underwent ET. A mosaic of observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network is compared to reflectivity simulated by the Advanced Research Weather Research and Forecasting (WRF-ARW) Model. Six simulations are performed by varying the cumulus and microphysics parameterizations to produce a range of reflectivity configurations. A bias correction is applied to model-simulated reflectivity prior to the calculation of spatial metrics because lower reflectivity values are generally underrepresented, while higher values are generally overrepresented. However, the simulation with Kain–Fritsch cumulus and Morrison two-moment microphysics overpredicts reflectivity by 3–4 dBZ at all levels. We demonstrate that the spatial metrics effectively capture structural changes as reflectivity regions became more fragmented and dispersed and the center became more exposed. In this case study, the results were more sensitive to the choice of cumulus physics, compared with the choice of microphysics. The Kain–Fritsch simulations produce shapes that are too circular and solid when compared with WSR-88D observations, as the hurricanes lack distinct outer rainbands. Simulations with Tiedtke cumulus produce an elongated main reflectivity region as in WSR-88D, but with separate inner and outer rainbands that are too dispersed and fragmented. These results demonstrate the value in measuring spatial patterns rather than assessing model performance using visual inspection alone.

A representation of the collisional ice break-up process in the two-moment microphysics scheme LIMA v1.0 of Meso-NH

A representation of the collisional ice break-up process in the two-moment microphysics scheme LIMA v1.0 of Meso-NH

Prediction and Ensemble Forecast Verification of Hail in the Supercell Storms of 20 May 2013

AbstractDespite recent advances in storm-scale ensemble NWP, short-term (0–90 min) explicit forecasts of severe hail remain a major challenge as a result of the fast evolution and short time scales of hail-producing convective storms and the substantial uncertainty associated with the microphysical representation of hail. In this study, 0–90-min ensemble hail forecasts for the supercell storms of 20 May 2013 over central Oklahoma are examined and verified, with the goals of 1) evaluating ensemble forecast performance, 2) comparing the advantages and limitations of different forecast fields potentially suitable for the prediction of hail and severe hail in a Warn-on-Forecast setting, and 3) evaluating the use of dual-polarization radar observations for hail forecast validation. To address the challenges of hail prediction and to produce skillful forecasts, the ensemble uses a two-moment microphysics scheme that explicitly predicts a hail-like rimed-ice category and is run with a grid spacing of 500 m. Radar reflectivity factor and radial velocity, along with surface observations, are assimilated every 5 min for 1 h as the storms were developing to maturity, followed by a 90-min ensemble forecast. Several methods of hail prediction and hail forecast verification are then examined, including the prediction of the maximum hail size compared to Storm Prediction Center (SPC) and Meteorological Phenomena Identification Near the Ground (mPING) hail observations, and verification of model data against single- and dual-polarization radar-derived fields including hydrometeor classification algorithm (HCA) output and the maximum estimated size of hail (MESH). The 0–90-min ensemble hail predictions are found to be marginally to moderately skillful depending on the verification method used.

Incorporating Diagnosed Intercept Parameters and the Graupel Category within the ARPS Cloud Analysis System for the Initialization of Double-Moment Microphysics: Testing with a Squall Line over South China

Abstract In this study, a new set of reflectivity equations are introduced into the Advanced Regional Prediction System (ARPS) cloud analysis system. This set of equations incorporates double-moment microphysics information in the analysis by adopting a set of diagnostic relationships between the intercept parameters and the corresponding mass mixing ratios. A reflectivity- and temperature-based graupel classification scheme is also implemented according to a hydrometeor identification (HID) diagram. A squall line that occurred on 23 April 2007 over southern China containing a pronounced trailing stratiform precipitation region is used as a test case to evaluate the impacts of the enhanced cloud analysis scheme. The results show that using the enhanced cloud analysis scheme is able to better capture the characteristics of the squall line in the forecast. The predicted squall line exhibits a wider stratiform region and a more clearly defined transition zone between the leading convection and the trailing stratiform precipitation region agreeing better with observations in general, when using the enhanced cloud analysis together with the two-moment microphysics scheme. The quantitative precipitation forecast skill score is also improved.

Effects of Convective Microphysics Parameterization on Large-Scale Cloud Hydrological Cycle and Radiative Budget in Tropical and Midlatitude Convective Regions

Abstract A two-moment microphysics scheme for deep convection was previously implemented in the NCAR Community Atmosphere Model version 5 (CAM5) by Song et al. The new scheme improved hydrometeor profiles in deep convective clouds and increased deep convective detrainment, reducing the negative biases in low and midlevel cloud fraction and liquid water path compared to observations. Here, the authors examine in more detail the impacts of this improved microphysical representation on regional-scale water and radiation budgets. As a primary source of cloud water for stratiform clouds is detrainment from deep and shallow convection, the enhanced detrainment leads to larger stratiform cloud fractions, higher cloud water content, and more stratiform precipitation over the ocean, particularly in the subtropics where convective frequency is also increased. This leads to increased net cloud radiative forcing. Over land regions, cloud amounts are reduced as a result of lower relative humidity, leading to weaker cloud forcing and increased OLR. Comparing the water budgets to cloud-resolving model simulations shows improvement in the partitioning between convective and stratiform precipitation, though the deep convection is still too active in the GCM. The addition of convective microphysics leads to an overall improvement in the regional cloud water budgets.

On the Mechanisms of Rain Formation in an Idealized Supercell Storm

Abstract Deep convective storms produce raindrops through three mechanisms: condensation and coalescence growth of cloud liquid droplets (i.e., warm processes), melting of ice hydrometeors, and shedding from wet hailstones. To investigate the relative importance of these mechanisms and their contributions to exotic drop size distributions (DSDs) observed near the surface in supercell storms, an idealized simulation of a supercell is performed using a modified version of the Morrison two-moment microphysics scheme. The modified scheme includes separate categories for warm, shed, and melted rain. Rain originating from melting ice dominates the rain mass at low levels, especially along the right forward-flank precipitation shield, whereas shed-rain drops dominate a region within the left forward flank. Warm rain is only dominant in the upshear portion of the rear flank of the storm at low levels, though it dominates the total rain mass within the main updraft aloft. The warm-rain mass at low levels is associated with strong low-level downdrafts, consistent with previously published hypotheses based on polarimetric radar observations. Raindrops produced via warm processes are smaller on average than those produced by shedding and melting; drops in the latter class tend to be the largest. Overall, the simulations fail to reproduce the diverse nature of observed supercell DSDs, although the modified microphysics scheme does increase the variability of surface DSDs compared to the Control run. This implies that more sophisticated treatment of rain microphysics is needed to capture the natural variability of supercell DSDs, including the ability to evolve the DSD spectral shape through sedimentation and collisional processes.

Numerical Simulations of Lightning and Storm Charge of the 29–30 May 2004 Geary, Oklahoma, Supercell Thunderstorm Using EnKF Mobile Radar Data Assimilation

Abstract Results from simulations are compared with dual-Doppler and total lightning observations of the 29–30 May 2004 high-precipitation supercell storm from the Thunderstorm Electrification and Lightning Experiment (TELEX). The simulations use two-moment microphysics with six hydrometeor categories and parameterizations for electrification and lightning while employing an ensemble Kalman filter for mobile radar data assimilation. Data assimilation was utilized specifically to produce a storm similar to the observed for ancillary analysis of the electrification and lightning associated with the supercell storm. The simulated reflectivity and wind fields well approximated that of the observed storm. Additionally, the simulated lightning flash rates were very large, as was observed. The simulation reveals details of the charge distribution and dependence of lightning on storm kinematics, characteristics that could not be observed directly. Storm electrification was predominately confined to the updraft core, but the persistence of both positive and negative charging of graupel in this region, combined with the kinematic evolution, limited the extent of charged areas of the same polarity. Thus, the propagation length of lightning flashes in this region was also limited. Away from the updraft core, regions of charge had greater areal extent, allowing flashes to travel farther without termination due to unfavorable charge potential. Finally, while the simulation produced the observed lightning holes and high-altitude lightning seen in the observations, it failed to produce the observed lightning initiations (or even lightning channels) in the distant downstream anvil as seen in the observed storm. Instead, the simulated lightning was confined to the main body of the storm.

Adapting Two-Moment Microphysics Schemes across Model Resolutions: Subgrid Cloud and Precipitation Fraction and Microphysical Sub–Time Step

Abstract Two-moment multiclass microphysics schemes are very promising tools to be used in high-resolution NWP models. However, they must be adapted for coarser resolutions. Here, a twofold solution is proposed—namely, a simple representation of subgrid cloud and precipitation fraction—as well as a microphysical sub-time-stepping method. The scheme is easy to implement, allows supersaturation in ice cloud, and exhibits flexibility for adoption across model grid spacing. It is implemented in the Milbrandt and Yau two-moment microphysics scheme with prognostic precipitation in the context of a simple 1D kinematic model as well as a mesoscale NWP model [the Canadian regional Global Environmental Multiscale model (GEM)]. Sensitivity tests were performed and the results highlighting the advantages and disadvantages of the two-moment multiclass cloud scheme relative to the classical Sundqvist scheme. The respective roles of subgrid cloud fraction, precipitation fraction, and time splitting were also studied. When compared to the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)/CloudSat-retrieved cloud mask, cloud fraction, and ice water content, it is found that the proposed solutions significantly improve the behavior of the Milbrandt and Yau microphysics scheme at the regional NWP scale, suggesting that the subgrid cloud and precipitation fraction technique can be used across model resolutions.

Influence of aerosols on the life cycle of a radiation fog event. A numerical and observational study

Despite the knowledge gained on the physical processes dominating the formation, development and dissipation of radiation fog events, uncertainties still exist about the role of the microphysical processes related to aerosol characteristics. The objective of this work is to analyze the sensitivity of fog to aerosols through their impacts on the fog droplets. A radiation fog event that formed on 15/11/2011 at the SIRTA Observatory near Paris in the context of the 2011–2012 ParisFog field campaign is the basis of this study. The selected case is one that initially forms a few hundred meters above the surface and within half an hour lowers down to the surface. A combination of SIRTA's sophisticated observations and 1D numerical simulations is employed with the aim of better understanding the influence of thermodynamics and microphysics on the life-cycle of the fog event and the degree to which aerosol characteristics such as concentration of potentially activated aerosols, size and solubility affect its characteristics. It results that the model simulates fairly well the fog life cycle, with only one half hour advance in the onset and one hour in the dissipation at the surface. The quality of the reference simulation is evaluated against several in-situ and remote sensing measurements. A numerical sensitivity analysis shows that the fog characteristics are strongly influenced by the aerosols. Doubling (halving) the cloud condensation nuclei (CCN) number translates into a 160% increase (65% decrease) in the production of fog droplets, and a 60% increase (40% decrease) of the liquid water path (LWP). The aerosols influence up to 10% the fog geometrical thickness. The necessity for more detailed local forcings that will produce better thermohygrometric conditions in the upper levels above the formed fog layer is underlined, as well as the addition of microphysical measurements in the vertical that will allow to improve two-moment microphysics schemes.

Squall-Line Intensification via Hydrometeor Recirculation

Abstract Many studies have demonstrated the intimate connection between microphysics and deep moist convection, especially for squall lines via cold pool pathways. The present study examines four numerically simulated idealized squall lines using the Regional Atmospheric Modeling System (RAMS) and includes a control simulation that uses full two-moment microphysics and three sensitivity experiments that vary the mean diameter of the hail hydrometeor size distribution. Results suggest that a circulation centered at the freezing level supports midlevel convective updraft invigoration through increased latent heating. The circulation begins with hail hydrometeors that initiate within the convective updraft above the freezing level and are then ejected upshear because of the front-to-rear flow of the squall line. As the hail falls below the freezing level, the rear-inflow jet (RIJ) advects the hail hydrometeors downshear and into the upshear flank of the midlevel convective updraft. Because the advection occurs below the freezing level, some of the hail melts and sheds raindrops. The addition of hail and rain to the updraft increases latent heating owing to both an enhancement in riming and vapor deposition onto hail and rain. The increase in latent heating enhances buoyancy within the updraft, which leads to an increase in precipitation and cold pool intensity that promote a positive feedback on squall-line strength. The upshear-tilted simulated squall lines in this study indicate that as hail size is decreased, squall lines are invigorated through the recirculation mechanism.