Microphysical Pathways Active Within Thunderstorms and Their Sensitivity to CCN Concentration and Wind Shear

The impact of cloud condensation nuclei (CCN) concentration on microphysical processes within thunderstorms and the resulting surface precipitation is not fully understood yet. In this work, an analysis of the microphysical pathways occurring in these clouds is proposed to systematically investigate and understand these sensitivities. Thunderstorms were simulated using convection-permitting (1 km horizontal grid spacing) idealized simulations with the ICON model, which included a 2-moment microphysics parameterization. Cloud condensation nuclei concentrations were increased from 100 to 3,200 CCN/cm3, in five different wind shear environments ranging from 18 to 50 m/s. Large and systematic decreases of surface precipitation (up to 35%) and hail (up to 90%) were found as CCN was increased. Wind shear changes the details, but not the sign, of the sensitivity to CCN. The microphysical process rates were tracked throughout each simulation, closing the mass budget for each hydrometeor class, and collected together into “microphysical pathways,” which quantify the different growth processes leading to surface precipitation. Almost all surface precipitation occurred through the mixed-phase pathway, where graupel and hail grow by riming and later melt as they fall to the surface. The mixed-phase pathway is sensitive to CCN concentration changes as a result of changes to the riming rate, which were systematically evaluated. Supercooled water content was almost insensitive to increasing CCN concentration, but decreased cloud drop size led to a large reduction in the riming efficiency (from 0.79 to 0.24) between supercooled cloud drops and graupel or hail, resulting in less surface precipitation

Partitioning the primary ice formation modes in large eddy simulations of mixed-phase clouds

State-of-the-art aerosol-dependent parameterisations describing each heterogeneous ice nucleation mode (contact, immersion, and deposition ice nucleation), as well as homogeneous nucleation, were incorporated into a large eddy simulation model. Several cases representing commonly occurring cloud types were simulated in an effort to understand which ice nucleation modes contribute the most to total concentrations of ice crystals. The cases include a completely idealised warm bubble, semi-idealised deep convection, an orographic cloud, and a stratiform case. Despite clear differences in thermodynamic conditions between the cases, the results are remarkably consistent between the different cloud types. In all the investigated cloud types and under normal aerosol conditions, immersion freezing dominates and contact freezing also contributes significantly. At colder temperatures, deposition nucleation plays only a small role, and homogeneous freezing is important. To some extent, the temporal evolution of the cloud determines the dominant freezing mechanism and hence the subsequent microphysical processes. Precipitation is not correlated with any one ice nucleation mode, instead occurring simultaneously when several nucleation modes are active. Furthermore, large variations in the aerosol concentration do affect the dominant ice nucleation mode; however, they have only a minor influence on the precipitation amount

Temperature and cloud condensation nuclei (CCN) sensitivity of orographic precipitation enhanced by a mixed-phase seeder–feeder mechanism: a case study for the 2015 Cumbria flood

The formation of orographic precipitation in mixed-phase clouds depends on a complex interplay of processes. This article investigates the microphysical response of orographic precipitation to perturbations of temperature and cloud condensation nuclei (CCN) concentration. A case study for the 2015 Cumbria flood in northern England is performed with sensitivities using a realization of the “piggybacking” method implemented into a limited-area setup of the Icosahedral Nonhydrostatic (ICON) model. A 6 % K−1 enhancement of precipitation results for the highest altitudes, caused by a “mixed-phase seeder–feeder mechanism”, i.e. the interplay of melting and accretion. Total 24 h precipitation is found to increase by only 2 % K−1, significantly less than the 7 % K−1 increase in atmospheric water vapour. A rain budget analysis reveals that the negative temperature sensitivity of the condensation ratio and the increase in rain evaporation dampen the precipitation enhancement. Decreasing the CCN concentration speeds up the microphysical processing, which leads to an increase in total precipitation. At low CCN concentration the precipitation sensitivity to temperature is systematically smaller. It is shown that the CCN and temperature sensitivities are to a large extent independent (with a ±3 % relative error) and additive

Parameterizing cloud condensation nuclei concentrations during HOPE

An aerosol model was used to simulate the generation and transport of aerosols over Germany during the HD(CP)2 Observational Prototype Experiment (HOPE) field campaign of 2013. The aerosol number concentrations and size distributions were evaluated against observations, which shows satisfactory agreement in the magnitude and temporal variability of the main aerosol contributors to cloud condensation nuclei (CCN) concentrations. From the modelled aerosol number concentrations, number concentrations of CCN were calculated as a function of vertical velocity using a comprehensive aerosol activation scheme which takes into account the influence of aerosol chemical and physical properties on CCN formation. There is a large amount of spatial variability in aerosol concentrations; however the resulting CCN concentrations vary significantly less over the domain. Temporal variability is large in both aerosols and CCN. A parameterization of the CCN number concentrations is developed for use in models. The technique involves defining a number of best fit functions to capture the dependence of CCN on vertical velocity at different pressure levels. In this way, aerosol chemical and physical properties as well as thermodynamic conditions are taken into account in the new CCN parameterization. A comparison between the parameterization and the CCN estimates from the model data shows excellent agreement. This parameterization may be used in other regions and time periods with a similar aerosol load; furthermore, the technique demonstrated here may be employed in regions dominated by different aerosol species

Relative impact of aerosol, soil moisture, and orography perturbations on deep convection

The predictability of deep moist convection depends on many factors, such as the synoptic-scale flow, the geographical region (i.e., the presence of mountains), and land surface–atmosphere as well as aerosol–cloud interactions. This study addresses all these factors by investigating the relative impact of orography, soil moisture, and aerosols on precipitation over Germany in different weather regimes. To this end, we conduct numerical sensitivity studies with the COnsortium for Small-sale MOdelling (COSMO) model at high spatial resolution (500 m grid spacing) for 6 days with weak and strong synoptic forcing. The numerical experiments consist of (i) successive smoothing of topographical features, (ii) systematic changes in the initial soil moisture fields (spatially homogeneous increase/decrease, horizontal uniform soil moisture, different realizations of dry/wet patches), and (iii) different assumptions about the ambient aerosol concentration (spatially homogeneous and heterogeneous fields). Our results show that the impact of these perturbations on precipitation is on average higher for weak than for strong synoptic forcing. Soil moisture and aerosols are each responsible for the maximum precipitation response for three of the cases, while the sensitivity to terrain forcing always shows the smallest spread. For the majority of the analyzed cases, the model produces a positive soil moisture–precipitation feedback when averaged over the entire model domain. Furthermore, the amount of soil moisture affects precipitation more strongly than its spatial distribution. The precipitation response to changes in the CCN concentration is more complex and case dependent. The smoothing of terrain shows weaker impacts on days with strong synoptic forcing because surface fluxes are less important and orographic ascent is still simulated reasonably well, despite missing fine-scale orographic features. We apply an object-based characterization to identify whether and how the perturbations affect the structure, location, timing, and intensity of precipitation. These diagnostics reveal that the structure component, comparing the size and shape of precipitating objects to the reference simulation, is on average highest in the soil moisture and aerosol simulations, often due to changes in the maximum precipitation amounts. This indicates that the dominant mechanisms for convection initiation remain but that precipitation amounts depend on the strength of the trigger mechanisms. Location and amplitude parameters both vary over a much smaller range. Still, the temporal evolution of the amplitude component correlates well with the rain rate. Our results suggest that for quantitative precipitation forecasting, both aerosols and soil moisture are of similar importance and that their inclusion in convective-scale ensemble forecasting containing classical sources of uncertainty should be assessed in the future

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

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\u27s 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\u27s 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

Simulated and observed horizontal inhomogeneities of optical thickness of Arctic stratus

Two-dimensional horizontal fields of cloud optical thickness τ derived from airborne measurements of solar spectral, cloud-reflected radiance are compared with semi-idealized large eddy simulations (LESs) of Arctic stratus performed with the Consortium for Small-scale Modeling (COSMO) atmospheric model. The measurements were collected during the Vertical Distribution of Ice in Arctic Clouds (VERDI) campaign carried out in Inuvik, Canada, in April/May 2012. The input for the LESs is obtained from collocated airborne dropsonde observations of a persistent Arctic stratus above the sea-ice-free Beaufort Sea. Simulations are performed for spatial resolutions of 50m (1.6km × 1.6km domain) and 100m (6.4km × 6.4km domain). Macrophysical cloud properties, such as cloud top altitude and vertical extent, are well captured by the COSMO simulations. However, COSMO produces rather homogeneous clouds compared to the measurements, in particular for the simulations with coarser spatial resolution. For both spatial resolutions, the directional structure of the cloud inhomogeneity is well represented by the model. Differences between the individual cases are mainly associated with the wind shear near cloud top and the vertical structure of the atmospheric boundary layer. A sensitivity study changing the wind velocity in COSMO by a vertically constant scaling factor shows that the directional, small-scale cloud inhomogeneity structures can range from 250 to 800m, depending on the mean wind speed, if the simulated domain is large enough to capture also large-scale structures, which then influence the small-scale structures. For those cases, a threshold wind velocity is identified, which determines when the cloud inhomogeneity stops increasing with increasing wind velocity