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The thermodynamic phase of clouds in low and middle levels over the Southern Ocean and the Arctic marine regions is poorly known, leading to uncertainties in the radiation budget in weather and climate models. To improve the knowledge of the cloud phase, we analyse 2 years of the raDAR-liDAR (DARDAR) dataset based on active satellite instruments. We classify clouds according to their base and top height and focus on low-, mid-, and mid- to low-level clouds as they are the most frequent in the mixed-phase temperature regime. Low-level single-layer clouds occur in 8 %–15 % of all profiles, but single-layer clouds spanning the mid-level also amount to approx. 15 %. Liquid clouds show mainly a smaller vertical extent but a horizontally larger extent compared to ice clouds. The results show the highest liquid fractions for low-level and mid-level clouds. Two local minima in the liquid fraction are observed around cloud top temperatures of −15 and −5 °C. Mid-level and mid- to low-level clouds over the Southern Ocean and low-level clouds in both polar regions show higher liquid fractions if they occur over sea ice compared to the open ocean. Low-level clouds and mid- to low-level clouds with high sea salt concentrations, used as a proxy for sea spray, show reduced liquid fractions. In mid-level clouds, dust shows the largest correlations with liquid fraction, with a lower liquid fraction for a higher dust aerosol concentration. Low-level clouds clearly show the largest contribution to the shortwave cloud radiative effect in both polar regions, followed by mid- to low-level clouds.

Cloud-radiative heating (CRH) within the atmosphere affects the dynamics and predictability of extratropical cyclones. However, CRH is uncertain in numerical weather prediction and climate models, and this could affect model predictions of extratropical cyclones. In this paper, we present a systematic quantification of CRH uncertainties. To this end, we study an idealized extratropical cyclone simulated at a convection-permitting resolution of 2.5 km and combine large-eddy-model simulations at a 300 m resolution with offline radiative transfer calculations. We quantify four factors contributing to the CRH uncertainty in different regions of the cyclone: 3D cloud-radiative effects, parameterization of ice optical properties, cloud horizontal heterogeneity, and cloud vertical overlap. The last two factors can be considered essentially resolved at 300 m but need to be parameterized at a 2.5 km resolution. Our results indicate that parameterization of ice optical properties and cloud horizontal heterogeneity are the two factors contributing most to the mean uncertainty in CRH at larger spatial scales and can be more relevant for the large-scale dynamics of the cyclone. On the other hand, 3D cloud-radiative effects are much smaller on average, especially for stratiform clouds within the warm conveyor belt of the cyclone. Our analysis in particular highlights the potential to improve the simulation of CRH by better representing ice optical properties. Future work should, in particular, address how uncertainty in ice optical properties affects the dynamics and predictability of extratropical cyclones.

The Intertropical Convergence Zone (ITCZ) is a key circulation and precipitation feature in the tropics. There has been a large spread in the representation of the ITCZ in global weather and climate models for a long time, the reasons for which remain unclear. This paper presents a novel approach with which we disentangle different physical processes responsible for the changeable behavior of the ITCZ in numerical models. The diagnostic tool is based on a conceptual framework developed by Emanuel (2019) and allows for physically consistent estimates of convective mass flux and precipitation efficiency for simulations with explicit and parameterized convection. We apply our diagnostic tool to a set of tropical aquachannel experiments using the ICOsahedral Nonhydrostatic (ICON) model with horizontal grid spacings of 13 and 5 km and with various representations of deep and shallow convection. The channel length corresponds to the Earth's circumference and has rigid walls at 30∘ N/S. Zonally symmetric sea surface temperatures are prescribed. All experiments simulate an ITCZ at the Equator coinciding with the ascending branch of the Hadley circulation and descending branches at 15∘ N/S with subtropical jets and easterly trade wind belts straddling the ITCZ. With explicit deep convection, however, rainfall in the ITCZ increases and the Hadley circulation becomes stronger. Increasing horizontal resolution substantially reduces the rainfall maximum in the ITCZ, while the strength of the Hadley circulation changes only marginally. Our diagnostic framework reveals that boundary-layer quasi-equilibrium (BLQE) is a key to physically understanding those differences. At 13 km, enhanced surface enthalpy fluxes with explicit deep convection are balanced by increased convective downdrafts. As precipitation efficiency is hardly affected, convective updrafts and rainfall increase. The surface enthalpy fluxes are mainly controlled by mean surface winds, closely linked to the Hadley circulation. These links also help understand rainfall differences between different resolutions. At 5 km, the wind–surface-fluxes–convection relation holds, but additionally explicit convection dries the mid-troposphere, which increases the import of air with lower moist static energy into the boundary layer, thereby enhancing surface fluxes. Overall, the different model configurations create little variations in precipitation efficiency and radiative cooling, the effects of which are compensated for by changes in dry stability. The results highlight the utility of our diagnostic tool to pinpoint processes important for rainfall differences between models, suggesting applicability for climate model intercomparison projects.

The formation of ice in clouds is an important process in mixed-phase clouds, and the radiative properties and dynamical developments of clouds strongly depend on their partitioning between the liquid and ice phases. In this study, we investigated the sensitivities of the cloud phase to the ice-nucleating particle (INP) concentration and thermodynamics. Moreover, passive satellite retrieval algorithms and cloud products were evaluated to identify whether they could detect cloud microphysical and thermodynamical perturbations. Experiments were conducted using the ICOsahedral Nonhydrostatic (ICON) model at the convection-permitting resolution of about 1.2 km on a domain covering significant parts of central Europe, and they were compared to two different retrieval products based on Spinning Enhanced Visible and InfraRed Imager (SEVIRI) measurements. We selected a day with multiple isolated deep convective clouds, reaching a homogeneous freezing temperature at the cloud top. The simulated cloud liquid pixel fractions were found to decrease with increasing INP concentration, both within clouds and at the cloud top. The decrease in the cloud liquid pixel fraction was not monotonic and was stronger in high-INP cases. Cloud-top glaciation temperatures shifted toward warmer temperatures with an increasing INP concentration by as much as 8 ∘C. Moreover, the impact of the INP concentration on cloud-phase partitioning was more pronounced at the cloud top than within the cloud. Furthermore, initial and lateral boundary temperature fields were perturbed with increasing and decreasing temperature increments from 0 to ±3 and ±5 K between 3 and 12 km, respectively. Perturbing the initial thermodynamic state was also found to systematically affect the cloud-phase distribution. However, the simulated cloud-top liquid pixel fraction, diagnosed using radiative transfer simulations as input to a satellite forward operator and two different satellite remote-sensing retrieval algorithms, deviated from one of the satellite products regardless of perturbations in the INP concentration or the initial thermodynamic state for warmer subzero temperatures while agreeing with the other retrieval scheme much better, in particular for the high-INP and high-CAPE (convective available potential energy) scenarios. Perturbing the initial thermodynamic state, which artificially increases the instability of the mid- and upper-troposphere, brought the simulated cloud-top liquid pixel fraction closer to the satellite observations, especially in the warmer mixed-phase temperature range.

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.

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.

Extratropical cyclones drive midlatitude weather, including extreme events, and determine midlatitude climate. Their dynamics and predictability are strongly shaped by cloud diabatic processes. While the cloud impact due to latent heating is much studied, little is known about the impact of cloud radiative heating (CRH) on the dynamics and predictability of extratropical cyclones. Here, we address this question by means of baroclinic life cycle simulations performed at a convection-permitting resolution of 2.5 km with the ICON model. The simulations use a newly implemented channel setup with periodic boundary conditions in the zonal direction. Moreover, the simulations apply a new modeling technique for which only CRH interacts with the cyclone, which circumvents changes in the mean state due to clear-sky radiative cooling that has complicated the interpretation of previous work. We find that CRH increases the kinetic energy of the cyclone system. The impact is most prominent at upper levels. To understand the CRH impact on the upper-tropospheric circulation, we diagnose the evolution of differences in potential vorticity between a simulation with and without CRH, and we quantify through which processes these differences grow over the course of the cyclone's life cycle. According to this diagnostic, CRH affects the cyclone mostly via the intensification of latent heating from cloud microphysical processes. Near the tropopause, direct diabatic modification of potential vorticity by intensified latent heat release precedes further changes in the tropopause by the upper-tropospheric divergent flow, which represents an indirect impact of latent heat release. Subsequently, differences in the tropopause structure amplify with the rotational flow during the highly nonlinear stage of the baroclinic wave. Our results show that although CRH is comparably small in magnitude, it can affect extratropical cyclones by changing cloud microphysical heating and subsequently the large-scale flow. The CRH impact follows a previously identified mechanism of multi-stage upscale error growth. At the same time, simulations in which CRH is disabled after certain days show that the CRH impact operates throughout the entire intensification phase of the cyclone. This means that CRH does not merely provide an arbitrary initial perturbation to the cyclone, from which differences grow in a generic way. Instead, our results suggest that uncertainties associated with the representation of CRH in numerical models have a more systematic impact and may more fundamentally influence model predictions of extratropical cyclones.

In June 2019, the Raikoke volcano, Kuril Islands, emitted 0.4–1.8×109 kg of very fine ash and 1–2×109 kg of SO2 up to 14 km into the atmosphere. The eruption was characterized by several eruption phases of different duration and height summing up to a total eruption length of about 5.5 h. Resolving such complex eruption dynamics is required for precise volcanic plume dispersion forecasts. To address this issue, we coupled the atmospheric model system ICON-ART (ICOsahedral Nonhydrostatic with the Aerosols and Reactive Trace gases module) with the 1D plume model FPlume to calculate the eruption source parameters (ESPs) online. The main inputs are the plume heights for the different eruption phases that are geometrically derived from satellite data. An empirical relationship is used to derive the amount of very fine ash (particles µm), which is relevant for long-range transport in the atmosphere. On the first day after the onset of the eruption, the modeled ash loading agrees very well with the ash loading estimated from AHI (Advanced Himawari Imager) observations due to the resolution of the eruption phases and the online treatment of the ESPs. In later hours, aerosol dynamical processes (nucleation, condensation, and coagulation) explain the loss of ash in the atmosphere in agreement with the observations. However, a direct comparison is partly hampered by water and ice clouds overlapping the ash cloud in the observations. We compared 6-hourly means of model and AHI data with respect to the structure, amplitude, and location (SAL method) to further validate the simulated dispersion of SO2 and ash. In the beginning, the structure and amplitude values for SO2 differed largely because the dense ash cloud leads to an underestimation of the SO2 amount in the satellite data. On the second and third day, the SAL values are close to zero for all parameters (except for the structure value of ash), indicating a very good agreement of the model and observations. Furthermore, we found a separation of the ash and SO2 plume after 1 d due to particle sedimentation, chemistry, and aerosol–radiation interaction. The results confirm that coupling the atmospheric model system and plume model enables detailed treatment of the plume dynamics (phases and ESPs) and leads to significant improvement of the ash and SO2 dispersion forecast. This approach can benefit the operational forecast of ash and SO2 especially in the case of complex and noncontinuous volcanic eruptions like that of Raikoke in 2019.

Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth’s changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which a large variety of cloud regimes was present over the selected domain of central Europe. It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from ground-based lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural variability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP > 200 g m−2), the control simulation matches the observations, while the perturbed one shows an LWP which is too large. The model simulations allowed for quantifying the radiative forcing due to aerosol–cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol–cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation −2.6 W m−2. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of −0.8 W m−2.

Severe hailstorms have the potential to damage buildings and crops. However, important processes for the prediction of hailstorms are insufficiently represented in operational weather forecast models. Therefore, our goal is to identify model input parameters describing environmental conditions and cloud microphysics, such as the vertical wind shear and strength of ice multiplication, which lead to large uncertainties in the prediction of deep convective clouds and precipitation. We conduct a comprehensive sensitivity analysis simulating deep convective clouds in an idealized setup of a cloud-resolving model. We use statistical emulation and variance-based sensitivity analysis to enable a Monte Carlo sampling of the model outputs across the multi-dimensional parameter space. The results show that the model dynamical and microphysical properties are sensitive to both the environmental and microphysical uncertainties in the model. The microphysical parameters lead to larger uncertainties in the output of integrated hydrometeor mass contents and precipitation variables. In particular, the uncertainty in the fall velocities of graupel and hail account for more than 65 % of the variance of all considered precipitation variables and for 30 %–90 % of the variance of the integrated hydrometeor mass contents. In contrast, variations in the environmental parameters – the range of which is limited to represent model uncertainty – mainly affect the vertical profiles of the diabatic heating rates.

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.

Abstract We investigate the sensitivity of self‐aggregated radiative‐convective‐equilibrium cloud‐resolving model simulations to the cloud condensation nuclei (CCN) concentration. Experiments were conducted on a long (2,000‐km × 120‐km) channel domain, allowing the emergence of multiple convective clusters and dry regions of subsidence. Increasing the CCN concentration leads to increased moisture in the dry regions, increased midlevel and upper level clouds, decreased radiative cooling, and decreased precipitation. We find that these trends follow from a decrease in the strength of the self‐aggregation as measured by the moist static energy (MSE) variance. In our simulations, precipitation is correlated, both locally and in total, with the distribution of MSE anomalies. We thus quantify changes in the adiabatic/diabatic contributions to MSE anomalies (Wing & Emanuel, 2014, https://doi.org/10.1002/2013MS000269) and relate those changes to changes in precipitation. Through a simple two‐column conceptual model, we argue that the reduction in precipitation can be explained thermodynamically by the reduction in mean net radiative cooling and mechanistically by the weakening of the area‐weighted radiatively driven subsidence velocity—defined as the ratio of the total radiative cooling over the dry regions and the static stability. We interpret the system's response to increasing CCN as a thermodynamically constrained realization of an aerosol indirect effect on clouds and precipitation.

Multilayer clouds (MLCs) occur more often in the Arctic than globally. In this study we present the results of a detection algorithm applied to radiosonde and radar data from an 1-year time period in Ny-Ålesund, Svalbard. Multilayer cloud occurrence is found on 29 % of the investigated days. These multilayer cloud cases are further analysed regarding the possibility of ice crystal seeding, meaning that an ice crystal can survive sublimation in a subsaturated layer between two cloud layers when falling through this layer. For this we analyse profiles of relative humidity with respect to ice to identify super- and subsaturated air layers. Then the sublimation of an ice crystal of an assumed initial size of r=400 µm on its way through the subsaturated layer is calculated. If the ice crystal still exists when reaching a lower supersaturated layer, ice crystal seeding can potentially take place. Seeding cases are found often, in 23 % of the investigated days (100 % includes all days, as well as non-cloudy days). The identification of seeding cases is limited by the radar signal inside the subsaturated layer. Clearly separated multilayer clouds, defined by a clear interstice in the radar image, do not interact through seeding (9 % of the investigated days). There are various deviations between the relative humidity profiles and the radar images, e.g. due to the lack of ice-nucleating particles (INPs) and cloud condensation nuclei (CCN). Additionally, horizontal wind drift of the radiosonde and time restriction when comparing radiosonde and radar data cause further deviations. In order to account for some of these deviations, an evaluation by manual visual inspection is done for the non-seeding cases.

A regional modeling study on the impact of desert dust on cloud formation is presented for a major Saharan dust outbreak over Europe from 2 to 5 April 2014. The dust event coincided with an extensive and dense cirrus cloud layer, suggesting an influence of dust on atmospheric ice nucleation. Using interactive simulation with the regional dust model COSMO-MUSCAT, we investigate cloud and precipitation representation in the model and test the sensitivity of cloud parameters to dust–cloud and dust–radiation interactions of the simulated dust plume. We evaluate model results with ground-based and spaceborne remote sensing measurements of aerosol and cloud properties, as well as the in situ measurements obtained during the ML-CIRRUS aircraft campaign. A run of the model with single-moment bulk microphysics without online dust feedback considerably underestimated cirrus cloud cover over Germany in the comparison with infrared satellite imagery. This was also reflected in simulated upper-tropospheric ice water content (IWC), which accounted for only 20 % of the observed values. The interactive dust simulation with COSMO-MUSCAT, including a two-moment bulk microphysics scheme and dust–cloud as well as dust–radiation feedback, in contrast, led to significant improvements. The modeled cirrus cloud cover and IWC were by at least a factor of 2 higher in the relevant altitudes compared to the noninteractive model run. We attributed these improvements mainly to enhanced deposition freezing in response to the high mineral dust concentrations. This was corroborated further in a significant decrease in ice particle radii towards more realistic values, compared to in situ measurements from the ML-CIRRUS aircraft campaign. By testing different empirical ice nucleation parameterizations, we further demonstrate that remaining uncertainties in the ice-nucleating properties of mineral dust affect the model performance at least as significantly as including the online representation of the mineral dust distribution. Dust–radiation interactions played a secondary role for cirrus cloud formation, but contributed to a more realistic representation of precipitation by suppressing moist convection in southern Germany. In addition, a too-low specific humidity in the 7 to 10 km altitude range in the boundary conditions was identified as one of the main reasons for misrepresentation of cirrus clouds in this model study.

Secondary ice production via processes like rime splintering, frozen droplet shattering, and breakup upon ice hydrometeor collision have been proposed to explain discrepancies between in-cloud ice crystal and ice-nucleating particle numbers. To understand the impact of this additional ice crystal generation on surface precipitation, we present one of the first studies to implement frozen droplet shattering and ice–ice collisional breakup parameterizations in a mesoscale model. We simulate a cold frontal rainband from the Aerosol Properties, PRocesses, And InfluenceS on the Earth's Climate campaign and investigate the impact of the new parameterizations on the simulated ice crystal number concentrations (ICNC) and precipitation. Near the convective regions of the rainband, contributions to ICNC can be as large from secondary production as from primary nucleation, but ICNCs greater than 50 L−1 remain underestimated by the model. The addition of the secondary production parameterizations also clearly intensifies the differences in both accumulated precipitation and precipitation rate between the convective towers and non-convective gap regions. We suggest, then, that secondary ice production parameterizations be included in large-scale models on the basis of large hydrometeor concentration and convective activity criteria.

Primary ice formation, which is an important process for mixed-phase clouds with an impact on their lifetime, radiative balance, and hence the climate, strongly depends on the availability of ice-nucleating particles (INPs). Supercooled droplets within these clouds remain liquid until an INP immersed in or colliding with the droplet reaches its activation temperature. Only a few aerosol particles are acting as INPs and the freezing efficiency varies among them. Thus, the fraction of supercooled water in the cloud depends on the specific properties and concentrations of the INPs. Primary biological aerosol particles (PBAPs) have been identified as very efficient INPs at high subzero temperatures, but their very low atmospheric concentrations make it difficult to quantify their impact on clouds.Here we use the regional atmospheric model COSMO–ART to simulate the heterogeneous ice nucleation by PBAPs during a 1-week case study on a domain covering Europe. We focus on three highly ice-nucleation-active PBAP species, Pseudomonas syringae bacteria cells and spores from the fungi Cladosporium sp. and Mortierella alpina. PBAP emissions are parameterized in order to represent the entirety of bacteria and fungal spores in the atmosphere. Thus, only parts of the simulated PBAPs are assumed to act as INPs. The ice nucleation parameterizations are specific for the three selected species and are based on a deterministic approach. The PBAP concentrations simulated in this study are within the range of previously reported results from other modeling studies and atmospheric measurements. Two regimes of PBAP INP concentrations are identified: a temperature-limited and a PBAP-limited regime, which occur at temperatures above and below a maximal concentration at around −10 °C, respectively. In an ensemble of control and disturbed simulations, the change in the average ice crystal concentration by biological INPs is not statistically significant, suggesting that PBAPs have no significant influence on the average state of the cloud ice phase. However, if the cloud top temperature is below −15 °C, PBAP can influence the cloud ice phase and produce ice crystals in the absence of other INPs. Nevertheless, the number of produced ice crystals is very low and it has no influence on the modeled number of cloud droplets and hence the cloud structure.

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 50 m (1.6 km  ×  1.6 km domain) and 100 m (6.4 km  ×  6.4 km 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 800 m, 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.

We perform a model intercomparison of summertime high Arctic ( >  80° N) clouds observed during the 2008 Arctic Summer Cloud Ocean Study (ASCOS) campaign, when observed cloud condensation nuclei (CCN) concentrations fell below 1 cm−3. Previous analyses have suggested that at these low CCN concentrations the liquid water content (LWC) and radiative properties of the clouds are determined primarily by the CCN concentrations, conditions that have previously been referred to as the tenuous cloud regime. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). We test the sensitivities of the model results to different treatments of cloud droplet activation, including prescribed cloud droplet number concentrations (CDNCs) and diagnostic CCN activation based on either fixed aerosol concentrations or prognostic aerosol with in-cloud processing.There remains considerable diversity even in experiments with prescribed CDNCs and prescribed ice crystal number concentrations (ICNC). The sensitivity of mixed-phase Arctic cloud properties to changes in CDNC depends on the representation of the cloud droplet size distribution within each model, which impacts autoconversion rates. Our results therefore suggest that properly estimating aerosol–cloud interactions requires an appropriate treatment of the cloud droplet size distribution within models, as well as in situ observations of hydrometeor size distributions to constrain them.The results strongly support the hypothesis that the liquid water content of these clouds is CCN limited. For the observed meteorological conditions, the cloud generally did not collapse when the CCN concentration was held constant at the relatively high CCN concentrations measured during the cloudy period, but the cloud thins or collapses as the CCN concentration is reduced. The CCN concentration at which collapse occurs varies substantially between models. Only one model predicts complete dissipation of the cloud due to glaciation, and this occurs only for the largest prescribed ICNC tested in this study. Global and regional models with either prescribed CDNCs or prescribed aerosol concentrations would not reproduce these dissipation events. Additionally, future increases in Arctic aerosol concentrations would be expected to decrease the frequency of occurrence of such cloud dissipation events, with implications for the radiative balance at the surface. Our results also show that cooling of the sea-ice surface following cloud dissipation increases atmospheric stability near the surface, further suppressing cloud formation. Therefore, this suggests that linkages between aerosol and clouds, as well as linkages between clouds, surface temperatures, and atmospheric stability need to be considered for weather and climate predictions in this region.

Disparities between the measured concentrations of ice-nucleating particles (INPs) and in-cloud ice crystal number concentrations (ICNCs) have led to the hypothesis that mechanisms other than primary nucleation form ice in the atmosphere. Here, we model three of these secondary production mechanisms – rime splintering, frozen droplet shattering, and ice–ice collisional breakup – with a six-hydrometeor-class parcel model. We perform three sets of simulations to understand temporal evolution of ice hydrometeor number (Nice), thermodynamic limitations, and the impact of parametric uncertainty when secondary production is active. Output is assessed in terms of the number of primarily nucleated ice crystals that must exist before secondary production initiates (NINP(lim)) as well as the ICNC enhancement from secondary production and the timing of a 100-fold enhancement. Nice evolution can be understood in terms of collision-based nonlinearity and the phasedness of the process, i.e., whether it involves ice hydrometeors, liquid ones, or both. Ice–ice collisional breakup is the only process for which a meaningful NINP(lim) exists (0.002 up to 0.15 L−1). For droplet shattering and rime splintering, a warm enough cloud base temperature and modest updraft are the more important criteria for initiation. The low values of NINP(lim) here suggest that, under appropriate thermodynamic conditions for secondary ice production, perturbations in cloud concentration nuclei concentrations are more influential in mixed-phase partitioning than those in INP concentrations.

The Arctic climate is changing; temperature changes in the Arctic are greater than at midlatitudes, and changing atmospheric conditions influence Arctic mixed-phase clouds, which are important for the Arctic surface energy budget. These low-level clouds are frequently observed across the Arctic. They impact the turbulent and radiative heating of the open water, snow, and sea-ice-covered surfaces and influence the boundary layer structure. Therefore the processes that affect mixed-phase cloud life cycles are extremely important, yet relatively poorly understood. In this study, we present sensitivity studies using semi-idealized large eddy simulations (LESs) to identify processes contributing to the dissipation of Arctic mixed-phase clouds. We found that one potential main contributor to the dissipation of an observed Arctic mixed-phase cloud, during the Arctic Summer Cloud Ocean Study (ASCOS) field campaign, was a low cloud droplet number concentration (CDNC) of about 2 cm−3. Introducing a high ice crystal concentration of 10 L−1 also resulted in cloud dissipation, but such high ice crystal concentrations were deemed unlikely for the present case. Sensitivity studies simulating the advection of dry air above the boundary layer inversion, as well as a modest increase in ice crystal concentration of 1 L−1, did not lead to cloud dissipation. As a requirement for small droplet numbers, pristine aerosol conditions in the Arctic environment are therefore considered an important factor determining the lifetime of Arctic mixed-phase clouds.

Abstract In model studies of aerosol‐dependent immersion freezing in clouds, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one cloud droplet. In contrast, the immersion freezing of larger drops—“rain”—is usually represented by a liquid volume‐dependent approach, making the parameterizations of rain freezing independent of specific aerosol types and concentrations. This may lead to inconsistencies when aerosol effects on clouds and precipitation shall be investigated, since raindrops consist of the cloud droplets—and corresponding aerosol particles—that have been involved in drop‐drop‐collisions. Here we introduce an extension to a two‐moment microphysical scheme in order to account explicitly for particle accumulation in raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective clouds, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from cloud droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust‐based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol‐dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.

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.

This paper assesses the resolution dependance of clouds and precipitation over Germany by numerical simulations with the COnsortium for Small-scale MOdeling (COSMO) model. Six intensive observation periods of the HOPE (HD(CP)2 Observational Prototype Experiment) measurement campaign conducted in spring 2013 and 1 summer day of the same year are simulated. By means of a series of grid-refinement resolution tests (horizontal grid spacing 2.8, 1 km, 500, and 250 m), the applicability of the COSMO model to represent real weather events in the gray zone, i.e., the scale ranging between the mesoscale limit (no turbulence resolved) and the large-eddy simulation limit (energy-containing turbulence resolved), is tested. To the authors' knowledge, this paper presents the first non-idealized COSMO simulations in the peer-reviewed literature at the 250–500 m scale. It is found that the kinetic energy spectra derived from model output show the expected −5/3 slope, as well as a dependency on model resolution, and that the effective resolution lies between 6 and 7 times the nominal resolution. Although the representation of a number of processes is enhanced with resolution (e.g., boundary-layer thermals, low-level convergence zones, gravity waves), their influence on the temporal evolution of precipitation is rather weak. However, rain intensities vary with resolution, leading to differences in the total rain amount of up to +48 %. Furthermore, the location of rain is similar for the springtime cases with moderate and strong synoptic forcing, whereas significant differences are obtained for the summertime case with air mass convection. Domain-averaged liquid water paths and cloud condensate profiles are used to analyze the temporal and spatial variability of the simulated clouds. Finally, probability density functions of convection-related parameters are analyzed to investigate their dependance on model resolution and their impact on cloud formation and subsequent precipitation.

Fungal spores as a prominent type of primary biological aerosol particles (PBAP) have been incorporated into the COSMO-ART (Consortium for Small-scale Modelling-Aerosols and Reactive Trace gases) regional atmospheric model. Two literature-based emission rates for fungal spores derived from fungal spore colony counts and chemical tracer measurements were used as a parameterization baseline for this study. A third, new emission parameterization for fluorescent biological aerosol particles (FBAP) was adapted to field measurements from four locations across Europe. FBAP concentrations can be regarded as a lower estimate of total PBAP concentrations. Size distributions of FBAP often show a distinct mode at approx. 3 μm, corresponding to a diameter range characteristic for many fungal spores. Previous studies for several locations have suggested that FBAP are in many cases dominated by fungal spores. Thus, we suggest that simulated FBAP and fungal spore concentrations obtained from the three different emission parameterizations can be compared to FBAP measurements. The comparison reveals that simulated fungal spore concentrations based on literature emission parameterizations are lower than measured FBAP concentrations. In agreement with the measurements, the model results show a diurnal cycle in simulated fungal spore concentrations, which may develop partially as a consequence of a varying boundary layer height between day and night. Temperature and specific humidity, together with leaf area index (LAI), were chosen to drive the new emission parameterization which is fitted to the FBAP observations. The new parameterization results in similar root mean square errors (RMSEs) and correlation coefficients compared to the FBAP observations as the previously existing fungal spore emission parameterizations, with some improvements in the bias. Using the new emission parameterization on a model domain covering western Europe, FBAP in the lowest model layer comprise a fraction of 15% of the total aerosol mass over land and reach average number concentrations of 26 L−1. The results confirm that fungal spores and biological particles may account for a major fraction of supermicron aerosol particle number and mass concentration over vegetated continental regions and should thus be explicitly considered in air quality and climate studies.

Deposition nucleation experiments with Arizona Test Dust (ATD) as a surrogate for mineral dusts were conducted at the AIDA cloud chamber at temperatures between 220 and 250 K. The influence of the aerosol size distribution and the cooling rate on the ice nucleation efficiencies was investigated. Ice nucleation active surface site (INAS) densities were calculated to quantify the ice nucleation efficiency as a function of temperature, humidity and the aerosol surface area concentration. Additionally, a contact angle parameterization according to classical nucleation theory was fitted to the experimental data in order to relate the ice nucleation efficiencies to contact angle distributions. From this study it can be concluded that the INAS density formulation is a very useful tool to describe the temperature- and humidity-dependent ice nucleation efficiency of ATD particles. Deposition nucleation on ATD particles can be described by a temperature- and relative-humidity-dependent INAS density function ns(T, Sice) with ns(xtherm) = 1.88 ×105 · exp(0.2659 · xtherm) [m−2] , (1) where the temperature- and saturation-dependent function xtherm is defined as xtherm = −(T−273.2)+(Sice−1) ×100, (2) with the saturation ratio with respect to ice Sice >1 and within a temperature range between 226 and 250 K. For lower temperatures, xtherm deviates from a linear behavior with temperature and relative humidity over ice. Also, two different approaches for describing the time dependence of deposition nucleation initiated by ATD particles are proposed. Box model estimates suggest that the time-dependent contribution is only relevant for small cooling rates and low number fractions of ice-active particles.

Dust aerosols are thought to be the main contributor to atmospheric ice nucleation. While there are case studies supporting this, a climatological sense of the importance of dust to atmospheric ice nucleating particle (INP) concentrations and its seasonal variability over Europe is lacking. Here, we use a mesoscale model to estimate Saharan dust concentrations over Europe in 2008. There are large differences in median dust concentrations between seasons, with the highest concentrations and highest variability in the lower to mid-troposphere. Laboratory-based ice nucleation parameterisations are applied to these simulated dust number concentrations to calculate the potential INP resulting from immersion freezing and deposition nucleation on these dust particles. The potential INP concentrations increase exponentially with height due to decreasing temperatures in the lower and mid-troposphere. When the ice-activated fraction increases sufficiently, INP concentrations follow the dust particle concentrations. The potential INP profiles exhibit similarly large differences between seasons, with the highest concentrations in spring (median potential immersion INP concentrations nearly 105 m−3, median potential deposition INP concentrations at 120% relative humidity with respect to ice over 105 m−3), about an order of magnitude larger than those in summer. Using these results, a best-fit function is provided to estimate the potential INPs for use in limited-area models, which is representative of the normal background INP concentrations over Europe. A statistical evaluation of the results against field and laboratory measurements indicates that the INP concentrations are in close agreement with observations.

A new heterogeneous ice nucleation parameterization that covers a wide temperature range (−36 to −78 °C) is presented. Developing and testing such an ice nucleation parameterization, which is constrained through identical experimental conditions, is important to accurately simulate the ice nucleation processes in cirrus clouds. The ice nucleation active surface-site density (ns) of hematite particles, used as a proxy for atmospheric dust particles, were derived from AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber measurements under water subsaturated conditions. These conditions were achieved by continuously changing the temperature (T) and relative humidity with respect to ice (RHice) in the chamber. Our measurements showed several different pathways to nucleate ice depending on T and RHice conditions. For instance, almost T-independent freezing was observed at −60 °C < T < −50 °C, where RHice explicitly controlled ice nucleation efficiency, while both T and RHice played roles in other two T regimes: −78 °C < T < −60 °C and −50 °C < T < −36 °C. More specifically, observations at T lower than −60 °C revealed that higher RHice was necessary to maintain a constant ns, whereas T may have played a significant role in ice nucleation at T higher than −50 °C. We implemented the new hematite-derived ns parameterization, which agrees well with previous AIDA measurements of desert dust, into two conceptual cloud models to investigate their sensitivity to the new parameterization in comparison to existing ice nucleation schemes for simulating cirrus cloud properties. Our results show that the new AIDA-based parameterization leads to an order of magnitude higher ice crystal concentrations and to an inhibition of homogeneous nucleation in lower-temperature regions. Our cloud simulation results suggest that atmospheric dust particles that form ice nuclei at lower temperatures, below −36 °C, can potentially have a stronger influence on cloud properties, such as cloud longevity and initiation, compared to previous parameterizations.

Stratocumulus clouds are important for climate as they reflect large amounts of solar radiation back into space. However they are difficult to simulate in global climate models because they form under a sharp inversion and are thin. A comparison of model simulations with the ECHAM6-HAM2 global aerosol climate model to observations, reanalysis and literature data revealed too strong turbulent mixing at the top of stratocumulus clouds and a lack of vertical resolution. Further reasons for cloud biases in stratocumulus regions are the too "active" shallow convection scheme, the cloud cover scheme and possibly too low subsidence rates. To address some of these issues and improve the representation of stratocumulus clouds, we made three distinct changes to ECHAM6-HAM2. With a "sharp" stability function in the turbulent mixing scheme we have observed, similar to previous studies, increases in stratocumulus cloud cover and liquid water path. With an increased vertical resolution in the lower troposphere in ECHAM6-HAM2 the stratocumulus clouds form higher up in the atmosphere and their vertical extent agrees better with reanalysis data. The recently implemented in-cloud aerosol processing in stratiform clouds is used to improve the aerosol representation in the model. Including the improvements also affects the anthropogenic aerosol effect. In-cloud aerosol processing in ECHAM6-HAM2 leads to a decrease in the anthropogenic aerosol effect in the global annual mean from −1.19 Wm−2 in the reference simulation to −1.08 Wm−2, while using a "sharp" stability function leads to an increase to −1.34 Wm−2. The results from the simulations with increased vertical resolution are diverse but increase the anthropogenic aerosol effect to −2.08 Wm−2 at 47 levels and −2.30 Wm−2 at 95 levels.

In order to investigate the impact of different treatments for the contact angle (α) in heterogeneous ice nucleating properties of natural dust and black carbon (BC) particles, we implement the classical-nucleation-theory-based parameterization of heterogeneous ice nucleation (Hoose et al., 2010) in the Community Atmospheric Model version 5 (CAM5) and then improve it by replacing the original single-contact-angle model with the probability-density-function-of-α (α-PDF) model to better represent the ice nucleation behavior of natural dust found in observations. We refit the classical nucleation theory (CNT) to constrain the uncertain parameters (i.e., onset α and activation energy in the single-α model; mean contact angle and standard deviation in the α-PDF model) using recent observation data sets for Saharan natural dust and BC (soot). We investigate the impact of the time dependence of droplet freezing on mixed-phase clouds and climate in CAM5 as well as the roles of natural dust and soot in different nucleation mechanisms. Our results show that, when compared with observations, the potential ice nuclei (IN) calculated by the α-PDF model show better agreement than those calculated by the single-α model at warm temperatures (T; T > −20 °C). More ice crystals can form at low altitudes (with warm temperatures) simulated by the α-PDF model than compared to the single-α model in CAM5. All of these can be attributed to different ice nucleation efficiencies among aerosol particles, with some particles having smaller contact angles (higher efficiencies) in the α-PDF model. In the sensitivity tests with the α-PDF model, we find that the change in mean contact angle has a larger impact on the active fraction at a given temperature than a change in standard deviation, even though the change in standard deviation can lead to a change in freezing behavior. Both the single-α and the α-PDF model indicate that the immersion freezing of natural dust plays a more important role in the heterogeneous nucleation than that of soot in mixed-phase clouds. The new parameterizations implemented in CAM5 induce more significant aerosol indirect effects than the default parameterization.

The distribution, abundance and nature of ice nucleation active particles in the atmosphere are major sources of uncertainty in the prediction of cloud coverage, precipitation patterns and climate. Some biological ice nuclei (IN) induce freezing at temperatures at which most other atmospheric particles exhibit no detectable activity (> −10 °C). Their actual contribution to the pool of IN in clouds remains poorly known, but numerical studies have suggested a probable significance of biological IN in atmospheric processes. In this study, cloud water was collected aseptically from the summit of Puy de Dôme (1465 m a.s.l., France) within contrasted meteorological and physico-chemical situations. Total and biological (i.e. heat-sensitive) IN were quantified by droplet-freezing assay between −5 °C and −14 °C. We observed that freezing was systematically induced by biological material, between −6 °C and −8 °C in 92% of the samples. Its removal by heat treatment consistently led to a decrease of the onset freezing temperature, by 3 °C or more in most samples. At −10 °C, 0 to ~ 220 biological IN mL−1 of cloud water were measured (i.e. 0 to ~ 22 m−3 of cloud air based on cloud liquid water content estimates), and these represented 65% to 100% of the total IN. Based on back-trajectories and on physico-chemical analyses, the high variability observed resulted probably from a source effect, with IN originating mostly from continental sources. Assuming that biological IN were all bacteria, at maximum 0.6% of the bacterial cells present in cloud water samples could have acted as IN at −8 °C, 1.5% at −10 °C, and 3.1% at −12 °C. The data set generated here will help elucidate the role of biological and bacterial IN on cloud microphysics by numeric modelling, and their impact on precipitation at local scale.

The core version of the Norwegian Climate Center's Earth System Model, named NorESM1-M, is presented. The NorESM family of models are based on the Community Climate System Model version 4 (CCSM4) of the University Corporation for Atmospheric Research, but differs from the latter by, in particular, an isopycnic coordinate ocean model and advanced chemistry–aerosol–cloud–radiation interaction schemes. NorESM1-M has a horizontal resolution of approximately 2° for the atmosphere and land components and 1° for the ocean and ice components. NorESM is also available in a lower resolution version (NorESM1-L) and a version that includes prognostic biogeochemical cycling (NorESM1-ME). The latter two model configurations are not part of this paper. Here, a first-order assessment of the model stability, the mean model state and the internal variability based on the model experiments made available to CMIP5 are presented. Further analysis of the model performance is provided in an accompanying paper (Iversen et al., 2013), presenting the corresponding climate response and scenario projections made with NorESM1-M.

The objective of this study is to document and evaluate recent changes and updates to the module for aerosols and aerosol–cloud–radiation interactions in the atmospheric module CAM4-Oslo of the core version of the Norwegian Earth System Model (NorESM), NorESM1-M. Particular attention is paid to the role of natural organics, sea salt, and mineral dust in determining the gross aerosol properties as well as the anthropogenic contribution to these properties and the associated direct and indirect radiative forcing. The aerosol module is extended from earlier versions that have been published, and includes life-cycling of sea salt, mineral dust, particulate sulphate, black carbon, and primary and secondary organics. The impacts of most of the numerous changes since previous versions are thoroughly explored by sensitivity experiments. The most important changes are: modified prognostic sea salt emissions; updated treatment of precipitation scavenging and gravitational settling; inclusion of biogenic primary organics and methane sulphonic acid (MSA) from oceans; almost doubled production of land-based biogenic secondary organic aerosols (SOA); and increased ratio of organic matter to organic carbon (OM/OC) for biomass burning aerosols from 1.4 to 2.6. Compared with in situ measurements and remotely sensed data, the new treatments of sea salt and dust aerosols give smaller biases in near-surface mass concentrations and aerosol optical depth than in the earlier model version. The model biases for mass concentrations are approximately unchanged for sulphate and BC. The enhanced levels of modeled OM yield improved overall statistics, even though OM is still underestimated in Europe and overestimated in North America. The global anthropogenic aerosol direct radiative forcing (DRF) at the top of the atmosphere has changed from a small positive value to −0.08 W m−2 in CAM4-Oslo. The sensitivity tests suggest that this change can be attributed to the new treatment of biomass burning aerosols and gravitational settling. Although it has not been a goal in this study, the new DRF estimate is closer both to the median model estimate from the AeroCom intercomparison and the best estimate in IPCC AR4. Estimated DRF at the ground surface has increased by ca. 60%, to −1.89 W m−2. We show that this can be explained by new emission data and omitted mixing of constituents between updrafts and downdrafts in convective clouds. The increased abundance of natural OM and the introduction of a cloud droplet spectral dispersion formulation are the most important contributions to a considerably decreased estimate of the indirect radiative forcing (IndRF). The IndRF is also found to be sensitive to assumptions about the coating of insoluble aerosols by sulphate and OM. The IndRF of −1.2 W m−2, which is closer to the IPCC AR4 estimates than the previous estimate of −1.9 W m−2, has thus been obtained without imposing unrealistic artificial lower bounds on cloud droplet number concentrations.

Ice nuclei impact clouds, but their sources and distribution in the atmosphere are still not well known. Particularly little attention has been paid to IN sources in marine environments, although evidence from field studies suggests that IN populations in remote marine regions may be dominated by primary biogenic particles associated with sea spray. In this exploratory model study, we aim to bring attention to this long-neglected topic and identify promising target regions for future field campaigns. We assess the likely global distribution of marine biogenic ice nuclei using a combination of historical observations, satellite data and model output. By comparing simulated marine biogenic immersion IN distributions and dust immersion IN distributions, we predict strong regional differences in the importance of marine biogenic IN relative to dust IN. Our analysis suggests that marine biogenic IN are most likely to play a dominant role in determining IN concentrations in near-surface-air over the Southern Ocean, so future field campaigns aimed at investigating marine biogenic IN should target that region. Climate-related changes in the abundance and emission of biogenic marine IN could affect marine cloud properties, thereby introducing previously unconsidered feedbacks that influence the hydrological cycle and the Earth's energy balance. Furthermore, marine biogenic IN may be an important aspect to consider in proposals for marine cloud brightening by artificial sea spray production.

The uncertainties associated with the wet removal of aerosols entrained above convective cloud bases are investigated in a global aerosol-climate model (ECHAM5-HAM) under a set of limiting assumptions for the wet removal of the entrained aerosols. The limiting assumptions for the wet removal of entrained aerosols are negligible scavenging and vigorous scavenging (either through activation, with size-dependent impaction scavenging, or with the prescribed fractions of the standard model). To facilitate this process-based study, an explicit representation of cloud-droplet-borne and ice-crystal-borne aerosol mass and number, for the purpose of wet removal, is introduced into the ECHAM5-HAM model. This replaces and is compared with the prescribed cloud-droplet-borne and ice-crystal-borne aerosol fraction scavenging scheme of the standard model. A 20% to 35% uncertainty in simulated global, annual mean aerosol mass burdens and optical depth (AOD) is attributed to different assumptions for the wet removal of aerosols entrained above convective cloud bases. Assumptions about the removal of aerosols entrained above convective cloud bases control modeled upper tropospheric aerosol concentrations by as much as one order of magnitude. Simulated aerosols entrained above convective cloud bases contribute 20% to 50% of modeled global, annual mean aerosol mass convective wet deposition (about 5% to 10% of the total dry and wet deposition), depending on the aerosol species, when including wet scavenging of those entrained aerosols (either by activation, size-dependent impaction, or with the prescribed fraction scheme). Among the simulations, the prescribed fraction and size-dependent impaction schemes yield the largest global, annual mean aerosol mass convective wet deposition (by about two-fold). However, the prescribed fraction scheme has more vigorous convective mixed-phase wet removal (by two to five-fold relative to the size-dependent impaction scheme) since nearly all entrained accumulation and coarse mode aerosols are assumed to be cloud-droplet borne or ice-crystal borne, and evaporation due to the Bergeron-Findeisen process is neglected. The simulated convective wet scavenging of entrained accumulation and coarse mode aerosols has feedbacks on new particle formation and the number of Aitken mode aerosols, which control stratiform and convective cloud droplet number concentrations and yield precipitation changes in the ECHAM5-HAM model. However, the geographic distribution of aerosol annual mean convective wet deposition change in the model is driven by changes to the assumptions regarding the scavenging of aerosols entrained above cloud bases rather than by precipitation changes, except for sea salt deposition in the tropics. Uncertainty in the seasonal, regional cycles of AOD due to assumptions about entrained aerosol wet scavenging is similar in magnitude to the estimated error in the AOD retrievals. The uncertainty in aerosol concentrations, burdens, and AOD attributed to different assumptions for the wet scavenging of aerosols entrained above convective cloud bases in a global model motivates the ongoing need to better understand and model the activation and impaction processes that aerosols undergo after entrainment into convective updrafts.

A small subset of the atmospheric aerosol population has the ability to induce ice formation at conditions under which ice would not form without them (heterogeneous ice nucleation). While no closed theoretical description of this process and the requirements for good ice nuclei is available, numerous studies have attempted to quantify the ice nucleation ability of different particles empirically in laboratory experiments. In this article, an overview of these results is provided. Ice nucleation "onset" conditions for various mineral dust, soot, biological, organic and ammonium sulfate particles are summarized. Typical temperature-supersaturation regions can be identified for the "onset" of ice nucleation of these different particle types, but the various particle sizes and activated fractions reported in different studies have to be taken into account when comparing results obtained with different methodologies. When intercomparing only data obtained under the same conditions, it is found that dust mineralogy is not a consistent predictor of higher or lower ice nucleation ability. However, the broad majority of studies agrees on a reduction of deposition nucleation by various coatings on mineral dust. The ice nucleation active surface site (INAS) density is discussed as a simple and empirical normalized measure for ice nucleation activity. For most immersion and condensation freezing measurements on mineral dust, estimates of the temperature-dependent INAS density agree within about two orders of magnitude. For deposition nucleation on dust, the spread is significantly larger, but a general trend of increasing INAS densities with increasing supersaturation is found. For soot, the presently available results are divergent. Estimated average INAS densities are high for ice-nucleation active bacteria at high subzero temperatures. At the same time, it is shown that INAS densities of some other biological aerosols, like certain pollen grains, fungal spores and diatoms, tend to be similar to those of dust. These particles may owe their high ice nucleation onsets to their large sizes. Surface-area-dependent parameterizations of heterogeneous ice nucleation are discussed. For immersion freezing on mineral dust, fitted INAS densities are available, but should not be used outside the temperature interval of the data they were based on. Classical nucleation theory, if employed with only one fitted contact angle, does not reproduce the observed temperature dependence for immersion nucleation, the temperature and supersaturation dependence for deposition nucleation, and the time dependence of ice nucleation. Formulations of classical nucleation theory with distributions of contact angles offer possibilities to overcome these weaknesses.

During the eruption of the Eyjafjallajökull volcano in the south of Iceland in April/May 2010, about 40 Tg of ash mass were emitted into the atmosphere. It was unclear whether volcanic ash particles with d < 10 μm facilitate the glaciation of clouds. Thus, ice nucleation properties of volcanic ash particles were investigated in AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber experiments simulating atmospherically relevant conditions. The ash sample that was used for our experiments had been collected at a distance of 58 km from the Eyjafjallajökull during the eruption period in April 2010. The temperature range covered by our ice nucleation experiments extended from 219 to 264 K, and both ice nucleation via immersion freezing and deposition nucleation could be observed. Immersion freezing was first observed at 252 K, whereas the deposition nucleation onset lay at 242 K and RHice =126%. About 0.1% of the volcanic ash particles were active as immersion freezing nuclei at a temperature of 249 K. For deposition nucleation, an ice fraction of 0.1% was observed at around 233 K and RHice =116%. Taking ice-active surface site densities as a measure for the ice nucleation efficiency, volcanic ash particles are similarly efficient ice nuclei in immersion freezing mode (ns,imm ~ 109 m−2 at 247 K) compared to certain mineral dusts. For deposition nucleation, the observed ice-active surface site densities ns,dep were found to be 1011 m−2 at 224 K and RHice =116%. Thus, volcanic ash particles initiate deposition nucleation more efficiently than Asian and Saharan dust but appear to be poorer ice nuclei than ATD particles. Based on the experimental data, we have derived ice-active surface site densities as a function of temperature for immersion freezing and of relative humidity over ice and temperature for deposition nucleation.

In this paper we describe and summarize the main achievements of the European Aerosol Cloud Climate and Air Quality Interactions project (EUCAARI). EUCAARI started on 1 January 2007 and ended on 31 December 2010 leaving a rich legacy including: (a) a comprehensive database with a year of observations of the physical, chemical and optical properties of aerosol particles over Europe, (b) comprehensive aerosol measurements in four developing countries, (c) a database of airborne measurements of aerosols and clouds over Europe during May 2008, (d) comprehensive modeling tools to study aerosol processes fron nano to global scale and their effects on climate and air quality. In addition a new Pan-European aerosol emissions inventory was developed and evaluated, a new cluster spectrometer was built and tested in the field and several new aerosol parameterizations and computations modules for chemical transport and global climate models were developed and evaluated. These achievements and related studies have substantially improved our understanding and reduced the uncertainties of aerosol radiative forcing and air quality-climate interactions. The EUCAARI results can be utilized in European and global environmental policy to assess the aerosol impacts and the corresponding abatement strategies.

We use global models to explore the microphysical effects of carbonaceous aerosols on liquid clouds. Although absorption of solar radiation by soot warms the atmosphere, soot may cause climate cooling due to its contribution to cloud condensation nuclei (CCN) and therefore cloud brightness. Six global models conducted three soot experiments; four of the models had detailed aerosol microphysical schemes. The average cloud radiative response to biofuel soot (black and organic carbon), including both indirect and semi-direct effects, is −0.11 Wm−2, comparable in size but opposite in sign to the respective direct effect. In a more idealized fossil fuel black carbon experiment, some models calculated a positive cloud response because soot provides a deposition sink for sulfuric and nitric acids and secondary organics, decreasing nucleation and evolution of viable CCN. Biofuel soot particles were also typically assumed to be larger and more hygroscopic than for fossil fuel soot and therefore caused more negative forcing, as also found in previous studies. Diesel soot (black and organic carbon) experiments had relatively smaller cloud impacts with five of the models −2 from clouds. The results are subject to the caveats that variability among models, and regional and interrannual variability for each model, are large. This comparison together with previously published results stresses the need to further constrain aerosol microphysical schemes. The non-linearities resulting from the competition of opposing effects on the CCN population make it difficult to extrapolate from idealized experiments to likely impacts of realistic potential emission changes.

A diagnostic cloud nucleation scavenging scheme, which determines stratiform cloud scavenging ratios for both aerosol mass and number distributions, based on cloud droplet, and ice crystal number concentrations, is introduced into the ECHAM5-HAM global climate model. This scheme is coupled with a size-dependent in-cloud impaction scavenging parameterization for both cloud droplet-aerosol, and ice crystal-aerosol collisions. The aerosol mass scavenged in stratiform clouds is found to be primarily (>90%) scavenged by cloud nucleation processes for all aerosol species, except for dust (50%). The aerosol number scavenged is primarily (>90%) attributed to impaction. 99% of this impaction scavenging occurs in clouds with temperatures less than 273 K. Sensitivity studies are presented, which compare aerosol concentrations, burdens, and deposition for a variety of in-cloud scavenging approaches: prescribed fractions, a more computationally expensive prognostic aerosol cloud processing treatment, and the new diagnostic scheme, also with modified assumptions about in-cloud impaction and nucleation scavenging. Our results show that while uncertainties in the representation of in-cloud scavenging processes can lead to differences in the range of 20–30% for the predicted annual, global mean aerosol mass burdens, and near to 50% for accumulation mode aerosol number burden, the differences in predicted aerosol mass concentrations can be up to one order of magnitude, particularly for regions of the middle troposphere with temperatures below 273 K where mixed and ice phase clouds exist. Different parameterizations for impaction scavenging changed the predicted global, annual mean number removal attributed to ice clouds by seven-fold, and the global, annual dust mass removal attributed to impaction by two orders of magnitude. Closer agreement with observations of black carbon profiles from aircraft (increases near to one order of magnitude for mixed phase clouds), mid-troposphere 210Pb vertical profiles, and the geographic distribution of aerosol optical depth is found for the new diagnostic scavenging scheme compared to the prescribed scavenging fraction scheme of the standard ECHAM5-HAM. The diagnostic and prognostic schemes represent the variability of scavenged fractions particularly for submicron size aerosols, and for mixed and ice phase clouds, and are recommended in preference to the prescribed scavenging fractions method.

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (τa) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between τa and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and τa as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld–τa relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between τa and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR–τa relationship show a strong positive correlation between τa and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of τa, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5 Wm−2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clear- and cloudy-sky forcings with estimates of anthropogenic τa and satellite-retrieved Nd–τa regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2 Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5 Wm−2, with a total estimate of −1.2±0.4 Wm−2.

Aerosols affect the climate system by changing cloud characteristics. Using the global climate model ECHAM5-HAM, we investigate different aerosol effects on mixed-phase clouds: The glaciation effect, which refers to a more frequent glaciation due to anthropogenic aerosols, versus the de-activation effect, which suggests that ice nuclei become less effective because of an anthropogenic sulfate coating. The glaciation effect can partly offset the indirect aerosol effect on warm clouds and thus causes the total anthropogenic aerosol effect to be smaller. It is investigated by varying the parameterization for the Bergeron-Findeisen process and the threshold coating thickness of sulfate (SO4-crit), which is required to convert an externally mixed aerosol particle into an internally mixed particle. Differences in the net radiation at the top-of-the-atmosphere due to anthropogenic aerosols between the different sensitivity studies amount up to 0.5 W m−2. This suggests that the investigated mixed-phase processes have a major effect on the total anthropogenic aerosol effect.

An explicit and detailed representation of in-droplet and in-crystal aerosol particles in stratiform clouds has been introduced in the global aerosol-climate model ECHAM5-HAM. The new scheme allows an evaluation of the cloud cycling of aerosols and an estimation of the relative contributions of nucleation and collision scavenging, as opposed to evaporation of hydrometeors in the global aerosol processing by clouds. On average an aerosol particle is cycled through stratiform clouds 0.5 times. The new scheme leads to important changes in the simulated fraction of aerosol scavenged in clouds, and consequently in the aerosol wet deposition. In general, less aerosol is scavenged into clouds with the new prognostic treatment than what is prescribed in standard ECHAM5-HAM. Aerosol concentrations, size distributions, scavenged fractions and cloud droplet concentrations are evaluated and compared to different observations. While the scavenged fraction and the aerosol number concentrations in the marine boundary layer are well represented in the new model, aerosol optical thickness, cloud droplet number concentrations in the marine boundary layer and the aerosol volume in the accumulation and coarse modes over the oceans are overestimated. Sensitivity studies suggest that a better representation of below-cloud scavenging, higher in-cloud collision coefficients, or a reduced water uptake by seasalt aerosols could reduce these biases.

The double-moment cloud microphysics scheme from ECHAM4 that predicts both the mass mixing ratios and number concentrations of cloud droplets and ice crystals has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass, number concentrations and mixing state. The simulated liquid, ice and total water content and the cloud droplet and ice crystal number concentrations as a function of temperature in stratiform mixed-phase clouds between 0 and −35° C agree much better with aircraft observations in the ECHAM5 simulations. ECHAM5 performs better because more realistic aerosol concentrations are available for cloud droplet nucleation and because the Bergeron-Findeisen process is parameterized as being more efficient. The total anthropogenic aerosol effect includes the direct, semi-direct and indirect effects and is defined as the difference in the top-of-the-atmosphere net radiation between present-day and pre-industrial times. It amounts to −1.9 W m−2 in ECHAM5, when a relative humidity dependent cloud cover scheme and aerosol emissions representative for the years 1750 and 2000 from the AeroCom emission inventory are used. The contribution of the cloud albedo effect amounts to −0.7 W m−2. The total anthropogenic aerosol effect is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed because the cloud lifetime effect increases.