In Part I of this two-part paper, a formulation was developed to treat fragmentation in ice–ice collisions. In the present Part II, the formulation is implemented in two microphysically advanced cloud models simulating a convective line observed over the U.S. high plains. One model is 2D with a spectral bin microphysics scheme. The other has a hybrid bin–two-moment bulk microphysics scheme in 3D. The case consists of cumulonimbus cells with cold cloud bases (near 0°C) in a dry troposphere. Only with breakup included in the simulation are aircraft observations of particles with maximum dimensions >0.2 mm in the storm adequately predicted by both models. In fact, breakup in ice–ice collisions is by far the most prolific process of ice initiation in the simulated clouds (95%–98% of all nonhomogeneous ice), apart from homogeneous freezing of droplets. Inclusion of breakup in the cloud-resolving model (CRM) simulations increased, by between about one and two orders of magnitude, the average concentration of ice between about 0° and −30°C. Most of the breakup is due to collisions of snow with graupel/hail. It is broadly consistent with the theoretical result in Part I about an explosive tendency for ice multiplication. Breakup in collisions of snow (crystals >~1 mm and aggregates) with denser graupel/hail was the main pathway for collisional breakup and initiated about 60%–90% of all ice particles not from homogeneous freezing, in the simulations by both models. Breakup is predicted to reduce accumulated surface precipitation in the simulated storm by about 20%–40%.

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Various improvements were made to a state‐of‐the‐art aerosol–cloud model and comparison of the model results with observations from field campaigns was performed. The strength of this aerosol–cloud model is in its ability to explicitly resolve all the known modes of heterogeneous cloud droplet activation and ice crystal nucleation. The model links cloud particle activation with the aerosol loading and chemistry of seven different aerosol species. These improvements to the model resulted in more accurate prediction especially of droplet and ice crystal number concentrations in the upper troposphere and enabled the model to directly sift the aerosol indirect effects based on the chemistry and concentration of the aerosols. In addition, continental and maritime cases were simulated for the purpose of validating the aerosol–cloud model and for investigating the critical microphysical and dynamical mechanisms of aerosol indirect effects from anthropogenic solute and solid aerosols, focusing mainly on glaciated clouds. The simulations showed that increased solute aerosols reduced cloud particle sizes by about 5 μm and inhibited warm rain processes. Cloud fractions and their optical thicknesses were increased quite substantially in both cases. Although liquid mixing ratios were boosted, there was however a substantial reduction of ice mixing ratios in the upper troposphere owing to the increase in snow production aloft. These results are detailed in the subsequent parts of this study.

A new parameterization of sticking efficiency for aggregation of ice crystals onto snow and graupel is presented. This parameter plays a crucial role for the formation of ice precipitation and for electrification processes. The parameterization is intended to be used in atmospheric models simulating the aggregation of ice particles in glaciated clouds. It should improve the ability to forecast snow. Based on experimental results and general considerations of collision processes, dependencies of the sticking efficiency on temperature, surface area, and collision kinetic energy of impacting particles are derived. The parameters have been estimated from some laboratory observations by simulating the experiments and minimizing the squares of the errors of the prediction of observed quantities. The predictions from the new scheme are compared with other available laboratory and field observations. The comparisons show that the parameterization is able to reproduce the thermal behavior of sticking efficiency, observed in published laboratory studies, with a peak around −15°C corresponding to dendritic vapor growth of ice. Finally, a new theory of sticking efficiency is proposed. It explains the empirically derived parameterization in terms of a probability distribution of the work that would be required to separate two contacting particles colliding in all possible ways among many otherwise identical collisions of the same pair with a given initial collision kinetic energy. For each collision, if this work done would exceed the initial collision kinetic energy, then there is no separation after impact. The probability of that occurring equals the sticking efficiency.

In this study a one-dimensional numerical cloud electrification model, called the Explicit Microphysics Thunderstorm Model (EMTM), is used to find quantitative relationships between the simulated electrical activity and microphysical properties in convective clouds. The model, based on an explicit microphysics scheme coupled to an ice–ice noninductive electrification scheme, allows us to interpret the connection of cloud microphysical structure with charge density distribution within the cloud, and to study the full evolution of the lightning activity (intracloud and cloud-to-ground) in relation to different environmental conditions. Thus, we apply the model to a series of different case studies over continental Europe and the Mediterranean region. We first compare, for selected case studies, the simulated lightning activity with the data provided by the ground-based Lightning Detection Network (LINET) in order to verify the reliability of the model and its limitations, and to assess its ability to reproduce electrical activity consistent with the observations. Then, using all simulations, we find a correlation between some key microphysical properties and cloud electrification, and derive quantitative relationships relating simulated flash rates to minimum thresholds of graupel mass content and updrafts. Finally, we provide outlooks on the use of such relationships and comments on the future development of this study

In this two-part paper, influences from environmental factors on lightning in a convective storm are assessed with a model. In Part I, an electrical component is described and applied in the Aerosol-Cloud model (AC). AC treats many types of secondary (e.g. breakup in ice-ice collisions, raindrop-freezing fragmentation, rime-splintering) and primary (heterogeneous, homogeneous freezing) ice initiation. AC represents lightning flashes with a statistical treatment of branching from a fractal law constrained by video imagery. The storm simulated is from the Severe Thunderstorm Electrification and Precipitation Study (STEPS, 19/20 June 2000). The simulation was validated microphysically (e.g., ice/droplet concentrations and mean sizes, liquid water content [LWC], reflectivity, surface precipitation) and dynamically (e.g., ascent) in our 2017 paper. Predicted ice concentrations (~10 L-1) agreed—to within a factor of about two—with aircraft data at flight levels (−10 to −15 °C). Here, electrical statistics of the same simulation are compared with observations. Flash rates (to within a factor of two), triggering altitudes and polarity of flashes, and electric fields, agree with STEPS observations. The ‘normal’ tripole of charge structure observed during an electrical balloon sounding is reproduced by AC. It is related to reversal of polarity of non-inductive charging in ice-ice collisions seen in lab experiments when temperature or LWC are varied. Positively charged graupel and negatively charged snow at most mid-levels, charged away from the fastest updrafts, is predicted to cause the normal tripole. Total charge separated in the simulated storm is dominated by collisions involving secondary ice from fragmentation in graupel-snow collisions.

Abstract. Precipitation retrievals based on measurements from microwave (MW) radiometers onboard low-Earth-orbit (LEO) satellites can reach high level of accuracy -especially regarding convective precipitation. At the present stage though, these observations cannot provide satisfactory coverage of the evolution of intense and rapid precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications -especially in supporting authorities for flood alerts and weather warnings. To tackle this problem, over the past two decades several techniques have been developed combining accurate MW estimates with frequent infrared (IR) observations from geosynchronous (GEO) satellites, such as the European Meteosat Second Generation (MSG). In this framework, we have developed a new fast and simple precipitation retrieval technique which we call Passive Microwave -Global Convective Diagnostic, (PM-GCD). This method uses MW retrievals in conjunction with the Global Convective Diagnostic (GCD) technique which discriminates deep convective clouds based on the difference between the MSG water vapor (6.2 µm) and thermal-IR (10.8 µm) channels. Specifically, MSG observations and the GCD technique are used to identify deep convective areas. These areas are then calibrated using MW precipitation estimates based on observations from the Advanced Microwave Sounding Unit (AMSU) radiometers onboard operational NOAA and Eumetsat satellites, and then finally propagated in time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique, analyzing its results for a case study that refers to a flood event that struck the island of Sicily in southern Italy on 1-2 October 2009.

Abstract. This paper describes a new multi-sensor approach for continuously monitoring convective rain cells. It exploits lightning data from surface networks to propagate rain fields estimated from multi-frequency brightness temperature measurements taken by the AMSU/MHS microwave radiometers onboard NOAA/EUMETSAT low Earth orbiting operational satellites. Specifically, the method allows inferring the development (movement, morphology and intensity) of convective rain cells from the spatial and temporal distribution of lightning strokes following any observation by a satellite-borne microwave radiometer. Obviously, this is particularly attractive for real-time operational purposes, due to the sporadic nature of the low Earth orbiting satellite measurements and the continuous availability of ground-based lightning measurements -as is the case in most of the Mediterranean region. A preliminary assessment of the lightning-based rainfall propagation algorithm has been successfully made by using two pairs of consecutive AMSU observations, in conjunction with lightning measurements from the ZEUS network, for two convective events. Specifically, we show that the evolving rain fields, which are estimated by applying the algorithm to the satellite-based rainfall estimates for the first AMSU overpass, show an overall agreement with the satellite-based rainfall estimates for the second AMSU overpass.