AS1.18

How to cite: Samset, B. H., Stjern, C. W., and Lund, M. T.: Climate effects of changing aerosol emissions over the coming decades, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7590, https://doi.org/10.5194/egusphere-egu21-7590, 2021.

Aerosol-cloud interactions (ACIs) continue to be subject to much uncertainty, supporting a large set of parametric and structural variants of a global climate or Earth System Model (ESM), especially regarding its aerosol and cloud microphysics components. This structural model uncertainty is relevant not only for the quantification of the climate response to anthropogenic aerosols: Because aerosol-cloud interactions are at the core of cloud and precipitation formation, they might also affect model-simulated cloud adjustments and feedbacks in response to greenhouse gases, and hence the model’s effective climate sensitivity (ECS). In-situ observations, satellite retrievals, and large-eddy simulations point to discrepancies between the effects of aerosol-cloud interactions in the real world and as modelled in ESMs, with potential implications for the model range also for ECS. 

Here, we explore how different choices in ACI modelling affect the model’s ECS. For this case study the CMIP6-generation Norwegian Earth System Model version 2 (NorESM2) is used, which has a sophisticated aerosol module and in its ‘default’ version contributed to the CMIP6 suite relatively weak positive cloud feedbacks compared to the other models within the 150 years used to calculate the regression-based ECS (EffCS). The climate change feedback and hence ECS of each modified model version compared to that of the default one is estimated by prescribing a uniform rise of 4K in the sea-surface temperature boundary conditions and evaluating the resulting top-of-atmosphere imbalance difference. A similar or better representation of present-day mean climate in general and ACI effects in particular is ensured by comparing a suite of evaluation metrics with their observationally derived pendants and results from the literature.

The ACI effects and relevant model-observation discrepancies targeted with the model modifications include models’ excessive cloud brightening over stratocumulus regions compared to satellite products, excessive increase in liquid water path associated with increased aerosol amount, and model bias in the climatological fraction between supercooled liquid water and cloud ice in mixed-phase clouds. For each of these, experiments with multiple combinations of modifications in the model code are analysed, exemplifying the numerous different processes and parameters that together determine the model response. The findings complement approaches to explore models’ parameter spaces systematically by informing the choices physically and restricting the modifications not only to parametric changes. The range of models obtained sets the default NorESM2 version, with its ECS being part of the CMIP6 ensemble, into the context of ACI uncertainty, informs on the so far possibly underappreciated relevance of ACIs for climate change beyond anthropogenic aerosols, and suggests alternative parameterisations for future ‘default’ model versions.

How to cite: Undorf, S. and Bender, F.: Modelling choices with regard to aerosol-cloud interactions and their impact on effective climate sensitivity in the NorESM2 model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6471, https://doi.org/10.5194/egusphere-egu21-6471, 2021.

Midlatitude storm tracks are a key component of the global atmospheric circulation. Extratropical cyclones associated with and evolving along the storm tracks dominate the day‐to‐day weather variability in the mid-latitudes, and changes in storm track activity or location strongly impact regional climate variations. Baroclinic waves that form the storm tracks are also responsible for transporting much of the heat, moisture, and momentum poleward in the midlatitudes. Therefore, investigating how storm tracks may respond to future changes in anthropogenic forcing is of significant interest. Yet, while most of the studies have focused on the role of increased greenhouse gases and the associated response at the end of the 21^st century, the role of anthropogenic aerosols has been comparatively less studied. Furthermore, identifying robust changes in the atmospheric circulation is challenging and a major source of uncertainty in climate projections given the variety of responses in different models. This study aims to address these two aspects, benefitting from the use of large ensembles of single forcing experiments for the historical period and the future under RCP8.5, which allow to better identify the contribution of internal variability and its interplay with external forcing. We will discuss changes of the northern hemisphere storm tracks over both the Atlantic and Pacific regions, disentangle the contribution of anthropogenic aerosol changes, and build a physical link with large-scale circulation and surface climate over the two-basins.

How to cite: Black, K., Colfescu, I., and Bollasina, M.: Contribution of anthropogenic aerosols to changes in the Northern Hemisphere storm tracks during the 20th and 21st centuries, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10015, https://doi.org/10.5194/egusphere-egu21-10015, 2021.

To mitigate the projected global warming in the 21st century, it is well-recognized that society needs to cut CO2 emissions and other short-lived warming agents aggressively. However, to stabilize the climate at a warming level closer to the present day, such as the “well below 2 ◦C” aspiration in the Paris Agreement, a net-zero carbon emission by 2050 is still insufficient. The recent IPCC special report calls for a massive scheme to extract CO2 directly from the atmosphere, in addition to decarbonization, to reach negative net emissions at the mid-century mark. Another ambitious proposal is solar-radiation-based geoengineering schemes, including injecting sulfur gas into the stratosphere. Despite being in public debate for years, these two leading geoengineering schemes have not been directly compared under a consistent analytical framework using global climate models.

Here we present the first explicit analysis of the hydroclimate impacts of these two geoengineering approaches using two recently available large-ensemble model experiments conducted by a family of state-of-the-art Earth system models. Our analysis focuses on the projected aridity conditions over the Americas in the 21st century in detailed terms of the potential mitigation benefits, the temporal evolution, the spatial distribution (within North and South America), the relative efficiency, and the physical mechanisms. We show that sulfur injection, in contrast to previous notions of leading to excessive terrestrial drying (in terms of precipitation reduction) while offsetting the global mean greenhouse gas (GHG) warming, will instead mitigate the projected drying tendency under RCP8.5. The surface energy balance change induced by sulfur injection, in addition to the well-known response in temperature and precipitation, plays a crucial role in determining the overall terrestrial hydroclimate response. However, when normalized by the same amount of avoided global warming in these simulations, sulfur injection is less effective in curbing the worsening trend of regional land aridity in the Americas under RCP8.5 when compared with carbon capture. Temporally, the climate benefit of sulfur injection will emerge more quickly, even when both schemes are hypothetically started in the same year of 2020. Spatially, both schemes are effective in curbing the drying trend over North America. However, for South America, the sulfur injection scheme is particularly more effective for the sub-Amazon region (southern Brazil), while the carbon capture scheme is more effective for the Amazon region. We conclude that despite the apparent limitations (such as an inability to address ocean acidification) and potential side effects (such as changes to the ozone layer), innovative means of sulfur injection should continue to be explored as a potential low-cost option in the climate solution toolbox, complementing other mitigation approaches such as emission cuts and carbon capture (Cao et al., 2017). Our results demonstrate the urgent need for multi-model comparison studies and detailed regional assessments in other parts of the world.

How to cite: Xu, Y., Lin, L., Tilmes, S., Dagon, K., Xia, L., Diao, C., Cheng, W., Wang, Z., Simpson, I., and Burnell, L.: Climate engineering to mitigate the projected 21st-century terrestrial drying of the Americas: a direct comparison of carbon capture and sulfur injection, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7926, https://doi.org/10.5194/egusphere-egu21-7926, 2021.

In this contribution, a significant reduction of low-level marine clouds (LLCs) in the northeastern Pacific is found over a 20-year period in satellite observations and attributed to increasing sea surface temperatures (SSTs).

LLCs play a key role for the Earth’s energy balance, however, their response to climatic changes is not clear, yet. Here, 20 years of Clouds and the Earth’s Radiant Energy System (CERES) cloud observations are analyzed together with reanalysis data sets in multivariate-regression and machine-learning frameworks to link an observed decrease of LLCs in the subtropical northern Pacific to changes in environmental factors. In the analyses, the observed LCC trend is explained almost exclusively by an increase in SSTs, but counteracted to some extent by increased low-level moisture availability. The influence of other factors such as estimated inversion strength, local winds and aerosols is investigated in the statistical frameworks but found to be negligible when compared to the effect of SST changes. The results provide observational evidence for the low-cloud feedback that back model findings of reduced LCC due to increased SSTs in a changing climate.

How to cite: Andersen, H., Cermak, J., and Zipfel, L.: Observed reduction in low-level clouds over the northeastern Pacific attributed to increase in sea surface temperatures, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9386, https://doi.org/10.5194/egusphere-egu21-9386, 2021.

Radiation in the atmosphere provides the energy that drives atmospheric dynamics and physics on all scales, so determining radiative balance correctly is crucial for understanding processes ranging from cloud particle growth to climate. Radiation schemes in global weather and climate models make assumptions to simplify the complex interaction of radiation with the Earth system, such as treating radiative transfer in only the vertical dimension. Capturing cloud-radiation interactions is particularly challenging since clouds vary strongly on small spatial and temporal scales not resolved in the models, and also interact strongly with radiation. In models, sub-grid atmospheric variables are simplified, describing three-dimensional cloud geometry, cloud particle size and shape and complex scattering functions with a few parameters. Uncertainties in these assumptions contribute to the large lingering uncertainty in the climatic role of clouds.

The new modular radiation scheme ecRad provides the opportunity to vary these parametrisations and assumptions individually to determine their impact. Several options are available for the radiation solver, cloud vertical overlap and horizontal inhomogeneity treatment and cloud ice and water optical property parametrisations. The solver SPARTACUS is the only radiation solver in a global model that can treat 3D radiative effects.

We use ecRad as the new operational radiation scheme in the DWD global model ICON to investigate the sensitivity of radiation results to radiation model assumptions and input variables such as cloud particle size and cloud geometry, as well as the varying role of cloud-radiation interactions in regional cloud regimes. We find that ecRad with an up-to date solar spectrum agrees much better with exact line-by-line radiation calculations than previous radiation models. In ICON, ecRad improves the global radiation balance, model physics and forecast performance.

How to cite: Schäfer, S., Köhler, M., Hogan, R., Klinger, C., Rieger, D., Zängl, G., Ahlgrimm, M., and de Lozar, A.: Addressing radiation and cloud uncertainties with the new radiation scheme ecRad in ICON, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10076, https://doi.org/10.5194/egusphere-egu21-10076, 2021.

How to cite: Maier, R., Mayer, B., Emde, C., and Voigt, A.: Development of a Fast Three-Dimensional Dynamic Radiative Transfer Solver for Numerical Weather Prediction Models
, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16208, https://doi.org/10.5194/egusphere-egu21-16208, 2021.

Interactions between radiation and clouds are a source of significant uncertainty in both numerical weather prediction (NWP) and climate models. Future models need to both incorporate more realistic description of physical processes and be computationally efficient. With the steadily increasing resolution of NWP models, previously neglected effects like the horizontal propagation of radiation become more important.

Here we present a hybrid radiative transfer model that combines a traditional twostream maximum random overlap (twomaxrnd) radiative solver (Črnivec and Mayer, 2019) with a Neighbouring Column Approximation (NCA) model (Klinger and Mayer, 2019), which parametrizes horizontal photon transport between adjacent grid-cells. Thereby the hybrid includes both subgrid-scale effects and grid-scale horizontal transport. In addition we introduced a horizontal cloud overlap scheme to the hybrid model. In order to differentiate between different overlap concepts and deduce optimal overlap coefficients we used high resolution radiative transfer simulations of LES cloud fields (horizontal resolution of 100-300 m) deploying a very accurate Monte Carlo (MYSTIC) model (Mayer, 2009).

Further we assess the performance of the hybrid model at the NWP scale (1-10 km) for various realistic cloud configurations using results from the benchmark MYSTIC model and determine the differences compared to other solvers that only consider either grid-scale or subgrid-scale effects, twomaxrnd, Tripleclouds and NCA.

How to cite: Manev, M., Mayer, B., Emde, C., and Voigt, A.: Introducing cloud horizontal overlap at NWP scales (1-10 km) in a fast 3D radiative transfer model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15810, https://doi.org/10.5194/egusphere-egu21-15810, 2021.

The Beer-Lambert-Bouguer Law of exponential attenuation is ubiquitous in the study of atmospheric radiative transfer. However, previous work has shown that adherence to the classical Beer-Lambert-Bouguer law requires the scatterers in the medium to be spatially uncorrelated. As particulates in the atmosphere are often statistically correlated/clustered, it is useful to identify the magnitude of the deviation from the classical expectation under different degrees of spatial clustering.

Measuring this deviation is difficult in an experimental setting both because it is challenging to measure the spatial clustering and the deviations from the classical expectation are expected to be modest. Thus, we approach this question through a simplified “ballistic-photon” computational simulation.

Here, we use a simplified numerical model to track the extinction of a collimated light source through correlated random media. The geometry is taken to mimic a sub-volume of the Michigan Technological University Pi Chamber, and the scatterers (cloud droplets) are explicitly resolved using a variety of increasingly realistic techniques for a frozen-field representation of the particle positions.

We report on the anticipated deviations from the classical Beer-Lambert-Bouguer law through examination of the resulting intensity of the illumination leaving through different walls of the simulation domain.

How to cite: Blouin, C. K. and Larsen, M.: Numerical Simulations to Explore Deviations from the Beer-Lambert-Bouguer Law in a Correlated Random Medium, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1770, https://doi.org/10.5194/egusphere-egu21-1770, 2021.

Solar radiation modelling is important for the evaluation and deployment of solar renewable energy systems. The amount of solar radiation reaching the ground is influenced by geographical parameters (seasons, latitude and local characteristics of the site) and meteorological and atmospheric parameters (like humidity, clouds or particles). Those parameters have important spatio-temporal variations that make solar radiation hard to model. 

Various radiation models exist in literature. Among them, the 1D radiation model part of the computational fluid dynamics software “Code_Saturne” estimates the global and direct solar irradiances at the ground. It takes into account the impact of meteorology, atmospheric gas, particles and clouds whose influence is represented using the two-stream approximation. 

The model showed satisfactory results during clear-sky days  but not during cloudy-sky days. It is a common problem in solar radiation modelling, because of the complexity to accurately represent  clouds, which are extremely variable in space and time and have a strong influence on the depletion of solar irradiance.  

In the current study, the estimation of radiation during cloudy-sky days is improved by coupling the 1D radiation model of Code_Saturne with on-site and satellite measurements of the cloud optical properties. Meteorological data are obtained from the Weather Research and Forecasting (WRF) model, aerosol’s concentrations from the air-quality modelling platform Polyphemus, and on-site measurements from the SIRTA observational site (close to Paris). Two periods are simulated: 'august 2009' and 'year 2014'. It is shown that the introduction of the measured cloud properties in the computation of the surface radiation fluxes leads to a strong reduction of the simulated errors, compared to the case where these properties are derived from the WRF model.                    

A sensitivity analysis on the parameters representing clouds in the model is conducted. It enabled us to identify the most influencing parameters - cloud optical thickness (COD) and cloud fraction - and instruments that are sufficient and mandatory for a good description of solar radiation during cloudy-sky days. A fitted model is developed to deduce the COD from liquid water path measurements. Satellite and radiometric measurements could both be used, although satellite measurements are not always available.  For the estimation of cloud fraction, the best results are obtained from shortwave radiometric measurements or from a sky imager. Moreover, large error cases in hourly values of solar fluxes are examined to understand their origin. For a large part of these error cases, there is a high variation within the hour of satellite or in situ measurements, or the presence of low clouds (in more than 50% of these cases in august 2009). 

How to cite: Al Asmar, L., Musson-Genon, L., Dupont, E., and Sartelet, K.: Improvement of radiation modelling during cloudy sky days using in-situ and satellite measurements. , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3007, https://doi.org/10.5194/egusphere-egu21-3007, 2021.

The downward longwave radiation (DLR) is a critical parameter for radiation balance, energy budget, and water cycle studies at regional and global scales. The accurate estimation of the all-weather DLR with a high temporal resolution is important for the estimation of the surface net radiation and evapotranspiration. However, the most DLR products involve instantaneous DLR estimates based on polar orbiting satellite data under clear-sky conditions. To obtain an in-depth understanding of the performances of different models in the estimation of the DLR over the Tibetan Plateau, which is a focus area of climate change study, this study tested eight methods under clear-sky conditions and six methods under cloudy conditions based on ground-measured data. The results show that the Dilley and O’Brien model and the Lhomme model are most suitable under clear-sky conditions and cloudy conditions, respectively. For the Dilley and O’Brien model, the average root mean square error (RMSE) of the DLR under clear-sky conditions is approximately 22.5 W/m² at nine ground sites; for the Lhomme model, the average RMSE is approximately 23.2 W/m². Based on the estimated cloud fraction and meteorological data provided by the China land surface data assimilation system (CLDAS), the hourly all-weather daytime DLR with 0.0625° over the Tibetan Plateau was estimated. The results show that the average RMSE of the estimated hourly all-weather DLR was approximately 26.4 W/m². With the combined all-weather DLR model, the hourly all-weather daytime DLR dataset with a 0.0625° resolution from 2008 to 2016 over the Tibetan Plateau was generated. This dataset can better contribute to studies associated with the radiation balance and energy budget, water cycle, and climate change over the Tibetan Plateau.

How to cite: Ding, L., Long, Z., Zhou, J., Wang, S., and Zhang, X.: Estimation of All-weather Downward Longwave Radiation over the Tibetan Plateau, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14096, https://doi.org/10.5194/egusphere-egu21-14096, 2021.

Aerosol particles play an important role in physical and chemical processes that occur in the atmosphere. On the one hand, these particles are able to modify atmospheric optical properties, causing a significant impact on Earth’s energy balance, and consequently their presence is fundamental on the global climate. On the other hand, aerosol particles act as cloud condensation nuclei (CCN) and ice nuclei (IN); making them an essential part of the hydrological cycle.

Atmospheric aerosols can be grouped into two categories depending on their origin: natural or anthropogenic. In our study, we put the focus on atmospheric aerosols of natural origin, in particular on primary biological aerosol particles (PBAPs) such as pollen and spores. These biogenic particles are released in large quantities from terrestrial vegetation into the atmosphere, where they can be transported up to 100-1000 km. Due to their large size (between 10-100 µm pollen grains and 2-10 µm spores) their residence time in the atmosphere is short. For this reason, they are not climate relevant compared to other components in the atmosphere. However, under moist and high humidity conditions or mechanical processes these biological aerosol particles can break into smaller particles known as sub-pollen particles (SPP) and sub-spores particles (SSP). Each pollen grain can rupture releasing a large quantity of these type of sub-particles (10⁶). Wozniak et al. (2018) estimated that, for clean background conditions, high SPPs concentrations can suppress average seasonal precipitation by 32% and shift rates from heavy to light while increasing dry days.

In this study, we have investigated the ability of various pollen and spores types to break into sub-particles and be activated as CCN. To this end we used a CCN counter (CCN-100, DMT) coupled with a Scanning Mobility Particle Sizer (SMPS, TSI) to select SPPs and SSPs of 50, 100 and 200 nm. The results show that not all pollen types have the same activation properties, with critical supersaturations varying between species and particle size. Additionally, SEM images have been performed to confirm the rupture of pollen and spores particles into SPPs and SSPs, respectively. Chemical composition of the different species have been investigated as well.

References:

Wozniak,M. C., Solmon, F., & Steiner, A. L. (2018). Pollen rupture and its impact on precipitation in clean continental conditions. Geophysical Research Letters, 45, 7156–7164. https://doi.org/10.1029/2018GL077692

Acknowledgments: This work was supported by the Spanish Ministry of Science and Innovation through projects CGL2016-81092-R, CGL2017-90884REDT and RTI2018.101154.A.I00, by Junta de Andalucía, UGR and FEDER funds through project B-RNM-474-UGR18 and B-RNM-496-UGR18 and by University of Granada Plan Propio through Visiting Scholars program. Andrea Casans is funded by MINECO under predoctoral program FPI (PRE2019-090827). Thanks to the NOAA Global Monitoring Laboratory for providing the CCN counter.

How to cite: Casans, A., Rejano, F., Ruiz-Peñuela, S., Casquero-Vera, J. A., Lyamani, H., Cazorla, A., Pérez-Ramírez, D., Cariñanos, P., and Titos, G.: Polen and spores as cloud condensation nuclei: results from a laboratory experiment, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12163, https://doi.org/10.5194/egusphere-egu21-12163, 2021.

The Cloud Condensation Nuclei (CCN) budget, the aerosol particles population that could become cloud droplets, can be influenced by primary aerosol particles emitted by different sources (anthropogenic or biogenic) or by secondary particles that have undergone growth processes or chemical transformations. Aerosol particles originated by nucleation of precursor gases in the atmosphere have been identified as an important source of CCN particles. The influence of New Particle Formation (NPF) events to CCN concentrations is highly dependent on the environment where it takes place. Specifically, the study of the influence of NPF events on CCN concentration at high-altitude sites, where atmospheric conditions favor the formation of clouds, is a very interesting scientific goal.

This study presents CCN measurements combined with aerosol size distribution at a high-altitude station in the South East of Spain: a remote high mountain site (Sierra Nevada; SNS, 2500 m a.s.l.). Due to its high altitude, the aerosol particles over SNS station are often representative of pristine free troposphere conditions, especially in winter and nighttime. During summer, SNS station is frequently influenced by transport of pollutants from Granada city to Sierra Nevada station as a result of mixing layer growth and the activation of the mountain-valley breeze phenomenon as well as by NPF events at midday (De Arruda Moreira et al., 2019; Casquero-Vera et al., 2020).

In this study, we analyze the influence of NPF events to CCN concentrations during summer 2019 at the SNS high-altitude station. The study period (from June to August of 2019) was characterized by 67 NPF events, 16 undefined events and 13 non-events days. Following Rose et al. (2017) criteria, only those NPF events referred as type I, i.e. with clear particle growth from smallest sizes, were selected to investigate the contribution of NPF events on CCN concentrations. In this sense, we selected the 15 clearest NPF events for this analysis.

Results show clear differences in the diurnal evolution of CCN concentration between NPF event and non-event days, demonstrating the large influence of NPF to CCN concentrations, especially at high supersaturations (Rejano et al., 2021). NPF events have been estimated to increase the CCN concentrations by 175% at SS=0.5%, evidencing NPF events as one of the major CCN source at this mountain site

Acknowledgments: This work was supported by the European Union's Horizon 2020 research and innovation programme through project ACTRIS 2 (grant agreement No 654109), by the Spanish Ministry of Economy and Competitiveness through projects CGL2016-81092-R, CGL2017-90884-REDT and RTI2018-101154-A-I00 and by University of Granada Plan Propio through Visiting Scholars program. The Spanish Ministry of Universities funds Fernando Rejano under the predoctoral program FPU (FPU19/05340).

References

Casquero-Vera, et al. (2020) Atmos. Chem. Phys. 20, 14253–14271.

De Arruda Moreira et al. (2019) Atmos. Chem. Phys. 19, 1263-1280.

Rejano et al. (2021) Sci. Tot Envi., 762, 143100.

Rose et al. (2017) Atmos. Chem. Phys. 17, 1529-1541.

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How to cite: Rejano Martínez, F., Titos Vela, G., Casquero-Vera, J. A., Lyamani, H., Andrews, E., Sheridan, P., Cazorla, A., Castillo, S., Casans, A., Pérez-Ramírez, D., Alados-Arboledas, L., and Olmo, F. J.: Influence of NPF events on the CCN concentration at a high-altitude site in southern Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15956, https://doi.org/10.5194/egusphere-egu21-15956, 2021.

Fine particulate matter (PM) affects visibility, climate and public health. Organic matter (OM), which is hard to characterize due to its complex chemical composition, can constitute more than half of the PM. Biomass burning from residential wood burning, wildfires, and prescribed burning is a major source of OM with an ever-increasing importance.

    Aerosol mass spectrometry (AMS) and Fourier transform infrared spectroscopy (FTIR) are two complementary methods of identifying the chemical composition of OM. AMS measures the bulk composition of OM with relatively high temporal resolution but provides limited parent compound information. FTIR, carried out on samples collected on Teflon filters, provides detailed functional groupinformation at the expense of relatively low temporal resolution.

    In this study, we used these two methods to better understand the evolution of biomass burning OM in the atmosphere with aging. For this purpose, primary emissions from wood and pellet stoves were injected into the Center for Studies of Air Qualities and Climate Change (C-STACC) environmental chamber at ICE-HT/FORTH. Primary emissions were aged using hydroxyl and nitrate radicals (with atmospherically relevant exposures) simulating atmospheric day-time and night-time oxidation.  A time-of-flight (ToF) AMS reported the composition of non-refractory PM₁ every three minutes and PM₁ was collected on PTFE filters over 20-minute periods before and after aging for off-line FTIR analysis.

    We found that AMS and FTIR measurements agreed well in terms of measured OM mass concentration, the OM:OC ratio, and concentration of biomass burning tracers – lignin and levoglucosan. AMS OM concentration was used to estimate chamber wall loss rates which were then used separate the contribution of primary and secondary organic aerosols (POA and SOA) to the aged OM. AMS mass spectra and FTIR spectra of biomass burning SOA and estimates of bulk composition were obtained by this procedure. FTIR and AMS spectra of SOA produced by OH oxidation of biomass burning volatile organic compounds (VOCs) were dominated by acid signatures. Organonitrates, on the other hand, appeared to be important in the SOA aged by the nitrate radical. The spectra from the two instruments also indicated that the signatures of certain compounds such as levoglucosan, lignin and hydrocarbons, which are abundant in biomass burning POA, diminish with aging significantly more than what can be attributed to chamber wall losses. The latter suggests biomass burning POA chemical composition might change noticeably due to heterogeneous reactions or partitioning in the atmosphere. Therefore, the common assumption of stable POA composition is only partially true. In addition, more stable biomass burning tracers should be used to be able to identify highly aged biomass burning aerosols in the atmosphere.

How to cite: Yazdani, A., Takahama, S., Kodros, J. K., Paglione, M., Masiol, M., Squizzato, S., Florou, K., Pandis, S. N., and Nenes, A.: Differentiating between primary and secondary organic aerosols of biomass burning in an environmental chamber with FTIR and AMS, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9057, https://doi.org/10.5194/egusphere-egu21-9057, 2021.

Low-level mixed-phase clouds are important factors influencing the energy budget of the Arctic boundary layer. The radiative properties of these clouds are determined by their microphysical properties. Aerosol particles that act as Ice Nucleating Particles (INP), impact the primary ice formation inside clouds and thereby affect cloud lifetime, albedo and precipitation formation. The sources of INP in the Arctic, their properties, nature and concentration are poorly understood which results in substantial uncertainties radiative forcing estimates in climate models.

Here, we present ship-based measurements of INP in different environmental compartments (air, sea surface microlayer, bulk sea water, fog water) in the Arctic. From May to July 2017 the PASCAL field campaign took place around and north of Svalbard (up to 84°N, between 0° and 35°E) onboard the RV Polarstern. INP concentrations were measured online with the SPIN instrument (Spectrometer for Ice Nuclei, DMT) and offline through filter sampling and analysis with freezing array techniques. We assess possible connections between the INP in the sea water and air, as well as between INP in the fog water and air through a closure study.

Generally, INP concentrations in the Arctic were found to be lower than in mid-latitudes with the exception of elevated INP concentrations at temperatures above -15°C and below -30°C. We attribute elevated INP concentrations to the presence of biogenic, probably proteinaceous INP, at the warmer, and to the presence of mineral dust at colder temperatures, respectively. The closure studies revealed that:
a) all INP in the air are activated to fog droplets, and
b) the INP concentration in seawater alone cannot explain INP concentration in air without a substantial enrichment of INP (factor 10⁴ to 10⁵) during the transfer of INP from the sea surface to the atmosphere. 
We present indications for a local, marine source of INP from a case study looking at the period when atmospheric INP concentrations were highest in the temperature range above -15°C. These findings highlight the need for future studies to assess especially the production mechanisms and source strength for Arctic INP.

We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Projektnummer 268020496 – TRR 172, within the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)³

How to cite: Hartmann, M., Gong, X., Kecorius, S., van Pinxteren, M., Vogl, T., Welti, A., Wex, H., Zeppenfeld, S., Wiedensohler, A., Herrmann, H., and Stratmann, F.: Is the ocean enough? – Indications towards the origin of Ice Nucleating Particles from May to July in the Arctic, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9789, https://doi.org/10.5194/egusphere-egu21-9789, 2021.

The number of cloud seeds, e.g. cloud condensation nuclei (CCN) and ice nucleation particles (INP), in the pristine Arctic shows a large range throughout the year, thereby influencing the radiative properties of Arctic clouds. However, little is known about the chemical properties of CCN and INP in this region. This study aims to investigate the chemical properties of aerosol particles and trace gases that are of importance for cloud formation in the Arctic environment, with focus on the organic fraction.

Over the course of one full year (fall 2019 until fall 2020), we deployed a filter-inlet for gases and aerosols coupled to a chemical ionization high-resolution time-of-flight mass spectrometer (FIGAERO-CIMS) using iodide as reagent ion at the Zeppelin Observatory in Svalbard (480 m a.s.l.), as part of the Ny-Ålesund Aerosol Cloud Experiment (NASCENT). The FIGAERO-CIMS is able to measure organic trace gases and aerosol particles semi-simultaneously. The instrument was connected to an inlet switching between a counterflow virtual impactor (CVI) inlet and a total air inlet. This setup allows to study the differences in chemical composition of organic aerosol particles and trace gases at molecular level that are involved in Arctic cloud formation compared to ambient non-activated aerosol.

We observed organic signal above background in both gas and particle phase all year round. A comparison between the gas phase mass spectra of cloud-free and cloudy conditions shows lower signal for some organics inside the cloud, indicating that some trace gases are scavenged by cloud hydrometeors whilst others are not. In this presentation we will discuss the chemical characteristics of the gases exhibiting different behavior during clear sky and cloudy conditions, and the implications for partitioning of organic compounds between the gas, aerosol particle and cloud hydrometeor (droplet/ice) phase.

How to cite: Gramlich, Y., Haslett, S., Siegel, K., Freitas, G., Krejci, R., Zieger, P., and Mohr, C.: Year-long observations of chemical properties of organic aerosols and cloud residuals at the Zeppelin Observatory, Svalbard, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13266, https://doi.org/10.5194/egusphere-egu21-13266, 2021.

The strong coupling between dynamic, thermodynamic, and microphysical processes and the numerous environmental parameters on which they depend makes clouds a highly complex system. Adiabatic regions (i.e., undiluted core) in the cloud allow to approximate in a simple way thermodynamic and microphysical profiles and provide local boundary conditions (i.e. core is a source of adiabatic values in each level). Mixing of the cloud with its environment affects both the cloud and the environmental properties. While environmental humidity, temperature and aerosol loading affect the clouds’ buoyancy and droplets size distribution (DSD), clouds simultaneously affect their surrounding via detrainment of droplets, humid air, and processed aerosols. Mixing occurs within a large spectrum of scales and leads to deviation of parts of the cloud from adiabaticity. The level of adiabaticity can be represented continuously by the adiabatic fraction (AF; defined as the ratio of the liquid water content to the theoretical adiabatic value). In this work we used the System of Atmosphere Modeling (SAM) with the Hebrew University Spectral Bin Microphysics to simulate a few isolated non-precipitating trade cumulus clouds (in different sizes and aerosol loading) in high resolution (10m). Passive tracer was added to all the simulations. We found cloudy volumes that contain both high tracer concentration and high AF (up to the clouds’ top), compared these two measures of mixing, and discuss their differences. The accuracy of AF calculations, based on different known methods is tested. For example, we show that the saturation adjustment assumption that is often used in AF calculations can lead to an underestimation of AF in pristine environments. This will mask microphysical effects and cause biases when comparing the adiabaticity of clouds under different aerosols loading. We show that the space spanned by the AF versus height in the cloud is a good measure for describing changes in cloud’s key variables in space and time (like temperature, updraft, and DSD properties). This space of AF vs height demonstrates how certain processes (e.g. in-cloud nucleation, mixing, evaporation, etc.) dominate different regions in the cloud (core, edge), and cause different dependence of the DSD on AF under different aerosols loading.

How to cite: Eytan, E., Koren, I., Khain, A., Altaratz, O., Pinsky, M., and Shpund, J.: The adiabaticity of warm cumulus clouds simulated in high-resolution , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10009, https://doi.org/10.5194/egusphere-egu21-10009, 2021.

Lagrangian, particle-based models are an emerging method for detailed modeling of cloud microphysics. In these models, a relatively small number of "super-droplets" is used to represent all hydrometeors. Each super-droplet represents vast number of hydrometeors that have the same properties. The most popular method for solving collision-coalescence in these particle-based models is the all-or-nothing algorithm. In this algorithm, collision-coalescence of droplets within a spatial cell is modeled with a stochastic process. The number of trials is proportional to the number of super-droplets, which is significantly lower than the number of hydrometeors. Therefore the variance of the number of hydrometeors with a given size is higher in the super-droplet algorithm than it would be if every droplet was modeled separately. The increase of this variability depends on the number of super-droplets. We use the University of Warsaw Lagrangian Cloud Model (UWLCM) to analyse how the randomness in the collision-coalescence algorithm affects the amount of precipitation in large eddy simulations of warm clouds.

How to cite: Zmijewski, P., Dziekan, P., and Pawlowska, H.: Randomness in the amount of rain in LES with Lagrangian microphysics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10326, https://doi.org/10.5194/egusphere-egu21-10326, 2021.

Southwestern France is an important wine region where hail-producing storms could cause considerable economic loss. To study the initiation and growth of hailstone, a new microphysical scheme based on the LIMA (Liquid, Ice, Multiple Aerosols, Vié et al., 2016) has been developed. The original LIMA only contains two-moment scheme for rain water, cloud water, and ice crystal. Whereas, the other ice hydrometeors are described by a single-moment scheme. The new scheme adds a full two-moment framework to snow, graupel, and hailstone, thus allowing a better representation of the microphysical processes than the original partial two-moment approach could offer. An idealized severe storm case has been simulated and have been used to evaluate the performance of the single-moment ICE3 scheme, the partial two-moment LIMA scheme, and the new full two-moment scheme in reproducing the evolution of observed hail-producing storm cases. The difference as well as similarity in modeled structures of the storms including hailstone development by different microphysics schemes and using different aerosol loadings are examined and will be presented.

How to cite: Taufour, M. and Wang, C.: A new 2-moment microphysical scheme for studying hail initiation and growth: schemes comparison, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4285, https://doi.org/10.5194/egusphere-egu21-4285, 2021.

Representing subgrid variability of cloud properties has always been a challenge in global climate models (GCMs). In microphysics schemes, the effects of subgrid cloud variability on warm rain process rates calculated based on mean cloud properties are usually accounted for by scaling process rates by an enhancement factor (EF) that is derived from the subgrid variance of cloud water. In our study, we find that the EF derived from Cloud Layers Unified by Binormals (CLUBB) in Community Earth System Model Version 2 (CESM2) is severely overestimated in most of the oceanic areas, which leads to the strong overestimation in the autoconversion rate. Through an EF formula based on empirical fitting of MODIS, we improve the EF in the liquid phase clouds. Results show that the model has a more reasonable relationship between autoconversion rate, cloud liquid water content (LWC), and droplet number concentration (CDNC) in warm rain simulation. The annual mean liquid cloud fraction (LCF), liquid water path (LWP), and CDNC show obvious increases for marine stratocumulus, where the probability of precipitation (POP) shows an obvious decrease. The annual mean LCF, cloud optical thickness (COT), and shortwave cloud forcing (SWCF) match better with observation. The sensitivity of LWP to aerosol decreases obviously. The sensitivities of LCF, LWP, cloud top droplet effective radius (CER), and COT to aerosol are in better agreement with MODIS, but the model still underestimates the response of cloud albedo to aerosol. These results indicate the importance of representing reasonable subgrid cloud variabilities in the simulation of cloud properties and aerosol-cloud interaction in climate models.

How to cite: Wang, H., Wang, M., Rosenfeld, D., Zhu, Y., and Zhang, Z.: Improving the treatment of subgrid cloud variability in warm rain simulation in CESM2, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2256, https://doi.org/10.5194/egusphere-egu21-2256, 2021.

Processes that convert small cloud droplets, on the order of tens of micrometers, into raindrops, on the order of millimeters, consist of condensational growth and collision-coalescence: the former is efficient for small droplets, whereas the latter becomes predominant later in the growth stage when droplets are larger than about 30 micrometers. Thus, how droplets can quickly grow to 30 micrometers solely by inefficient condensation has been a topic of discussion for a long time. As a result, many parameterizations used in current models that cannot directly resolve these processes are actually based on empirical estimates. Recently, some studies have shown the impact of turbulences that can enhance collision-coalescence for droplets smaller than 30 micrometers, explaining the fast growth of cloud droplets into raindrops as observed. We have implemented these new equations of collision-coalescence in a parcel model where the activation of aerosol particles and their condensational growth are also explicitly calculated based on physical equations across numerous size bins. After the successful implementation of these processes, we have then applied machine-learning algorithms of training a machine to mimic the behavior of the explicit physical model to model-simulated mass and number of raindrops alongside ten dynamical and microphysical variables as input features. The machine-learned results are also compared with those from existing parameterizations frequently used in regional and climate models. Furthermore, the use of this new machine-learning-based parameterization, covering processes from aerosol activation to the formation of raindrops, in a regional model will be discussed.

How to cite: Takeishi, A. and Wang, C.: Machine-learning the parcel-model simulations of the paths from aerosols to raindrops: activation, condensation, and collision-coalescence, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6473, https://doi.org/10.5194/egusphere-egu21-6473, 2021.

This study examines the role played by aerosol in mixed-phase deep convective clouds and torrential rain that occurred in the Seoul area, which is a conurbation area where urbanization has been rapid in the last few decades, using cloud-system resolving model (CSRM) simulations. The model results show that the spatial variability of aerosol concentrations causes the inhomogeneity of the spatial distribution of evaporative cooling and the intensity of associated outflow around the surface. This inhomogeneity generates a strong convergence field and the associated spatial inhomogeneity of condensation, deposition and associated cloud mass, leading to the formation of torrential rain.  With the increases in the variability of aerosol concentrations, the occurrence of torrential rain increases. This study finds that the effects of the increases in the variability play a much more important role in the increases in the intensity of mixed-phase clouds and torrential rain than the much-studied effects of the increases in aerosol loading. Results in this study demonstrate that for a better understanding of extreme weather events such as torrential rain in urban areas, not only changing aerosol loading but also changing aerosol spatial distribution since industrialization should be considered in aerosol-precipitation interactions. 

How to cite: Lee, S. S., Kim, B.-G., and Li, Z.: The role of aerosol spatial inhomogeneity in mixed-phase deep convective clouds and torrential rain in urban areas, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-509, https://doi.org/10.5194/egusphere-egu21-509, 2021.

Stratocumulus (Sc) clouds cover between 25% to 40% of the mid-latitude oceans, where they substantially cool the ocean surface. Many climate models poorly represent these marine boundary layer clouds in the lee of cold fronts in the Southern Ocean (SO), which yields a substantial underestimation of the reflection of short wave radiation. This results in a positive mean bias of 2K in the SO. The representation of stratocumulus clouds, cloud variability, precipitation statistics, and boundary layer dynamics within the ICON-NWP (Icosahedral Nonhydrostatic – Numerical Weather Prediction) model at the km-scale is evaluated in this study over the SO.

Real case simulations forced by ERA5 are performed with a two-way nesting strategy down to a resolution of 1.2 km. The model is evaluated using the soundings, remote sensing and in-situ observations obtained during the CAPRICORN (Clouds, Aerosols, Precipitation, Radiation, and Atmospheric Composition over the Southern Ocean) field campaign that took place during March and April 2016. During two days (26^th to 27^th of March 2016), open-cell stratocumuli were continuously observed by the shipborne radars and lidars between 47^oS 144^oE and 45^oS 146^oE (South of Tasmania). Our simulations are evaluated against the remote sensing retrievals using the forward simulated radar signatures from PAMTRA (Passive and Active Microwave TRAnsfer).

The initial results show that the observed variability of various cloud fields is best captured in simulations where only shallow convection is parameterised at this scale. Furthermore, ICON-NWP captures the observed intermittency of precipitation, yet the precipitation amount is overestimated. We further analyse the sensitivity of the cloud and precipitation statistics with respect to primary and secondary ice-phase processes (such as Hallett–Mossop and collisional breakup) in ICON-NWP. Both processes have previously been shown to improve ice properties of simulated shallow mixed-phase clouds over the Southern Ocean in other models.

How to cite: Ramadoss, V., Pfannkuch, K., Protat, A., Huang, Y., Siems, S., and Possner, A.: An evaluation of kilometre scale ICON simulations of mixed-phase stratocumulus over the Southern Ocean during CAPRICORN, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13110, https://doi.org/10.5194/egusphere-egu21-13110, 2021.

Aircraft icing and turbulence associated with mountain waves events are adverse meteorological phenomena potentially affecting aviation safety and air traffic management. This study analyzes 13 mountain wave events in the vicinity of the Adolfo Suárez Madrid-Barajas airport (Spain) for two years (from 2017 to 2019). Mountain waves are formed in the leeward side of the Guadarrama mountains when the wind flows perpendicular to this orographic barrier (north-northwest winds). The thirteen events are simulated using several parameterizations from the Weather Research and Forecasting (WRF) model. Simulated pseudo-satellite images are validated using the observed brightness temperature from satellite images. Then, a sensitivity analysis is developed through several skill scores applied to brightness temperature in order to select the schemes best performing to forecast mountain waves. Finally, the best parametrization is used to assess several atmospheric variables involved in mountain waves formation. 

How to cite: Díaz Fernández, J., Quitián Hernández, L., Bolgiani, P., Santos Muñoz, D., Sastre, M., González Alemán, J. J., Valero, F., Sebastián Martín, L. I., Lopez, L., Farran, J. I., and Martín, M. L.: Sensitivity analysis to WRF parameterizations for mountain waves near Madrid airport (Spain), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-165, https://doi.org/10.5194/egusphere-egu21-165, 2021.

This research summarizes a numerically efficient aerosol activation scheme and evaluates it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in China, Canada, Brazil, and Chile. The scheme employs a Quasi-steady state approximation of the cloud Droplet Growth Equation (QDGE) to efficiently simulate aerosol activation and vertical profiles of supersaturation and cloud droplet number concentration (CDNC) near the cloud base. We evaluated the scheme by specifying observed environmental thermodynamic variables and aerosol properties from 36 cloud cases as input and comparing the simulated CDNC and other simulated variables with cloud microphysical observations. The relative error (RE) of the mean simulated CDNC ranges from 15.27 % for Chile to 23.97 % for China, with an average of 19.69 %, indicating that the scheme successfully reproduces observed variations in CDNC over a wide range of different meteorological conditions and aerosol regimes. Subsequently, we carried out an error analysis by calculating the Maximum Information Coefficient (MIC) values between RE and individual input variables and sorted them by aerosol properties, pollution degree, environmental humidity, and dynamic condition according to their importance. Based on this analysis we find that the magnitude of the RE is sensitive to the specification of aerosol chemical composition and updraft velocity in the simulation, which can partly explain differences between simulated and observed CDNC in some of the regions.

How to cite: Wang, H., Peng, Y., von Salzen, K., Yang, Y., Zhou, W., and Zhao, D.: Evaluation of a numerically efficient aerosol activation scheme by using worldwide cloud data from multiple field campaigns in continental and marine regions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1673, https://doi.org/10.5194/egusphere-egu21-1673, 2021.

Clouds are of major importance for the climate system, but the radiative forcing resulting from their interaction with aerosols remains uncertain. To improve the representation of clouds in climate models, the parameterisations of cloud microphysical processes (CMPs) have become increasingly detailed. However, more detailed climate models do not necessarily result in improved accuracy for estimates of radiative forcing (Knutti and Sedláček, 2013; Carslaw et al., 2018). On the contrary, simpler formulations are cheaper, sufficient for some applications, and allow for an easier understanding of the respective process' effect in the model.

This study aims to gain an understanding which CMP parameterisation complexity is sufficient through simplification. We gradually phase out processes such as riming or aggregation from the global climate model ECHAM-HAM, meaning that the processes are only allowed to exhibit a fraction of their effect on the model state. The shape of the model response as a function of the artificially scaled effect of a given process helps to understand the importance of this process for the model response and its potential for simplification. For example, if partially removing a process induces only minor alterations in the present day climate, this process presents as a good candidate for simplification. This may be then further investigated, for example in terms of computing time.
The resulting sensitivities to CMP complexity are envisioned to guide CMP model simplifications as well as steer research towards those processes where a more accurate representation proves to be necessary.

Carslaw, Kenneth, Lindsay Lee, Leighton Regayre, and Jill Johnson (Feb. 2018). “Climate Models Are Uncertain, but We Can Do Something About It”. In: Eos 99. doi: 10.1029/2018EO093757

Knutti, Reto and Jan Sedláček (Apr. 2013). “Robustness and Uncertainties in the New CMIP5 Climate Model Projections”. In: Nature Climate Change 3.4, pp. 369–373. doi: 10.1038/nclimate1716

How to cite: Proske, U., Ferrachat, S., Neubauer, D., and Lohmann, U.: How detailed do cloud microphysics need to be in climate models?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7115, https://doi.org/10.5194/egusphere-egu21-7115, 2021.

In this study, the dissipation of fog and low stratus (FLS) over Europe is analyzed based on geostationary satellite data using logistic regression. 
The dissipation of FLS is a result of the interaction of complex physical processes and its timing has implications for environmental systems, traffic at land, sea and in the air, as well as for the production of solar energy. However, the timing of FLS dissipation, as well as its relationship to meteorological and land surface conditions has not been investigated quantitatively over a large spatial and temporal scale yet. 
In this study a 10-year FLS dissipation climatology is created using logistic regression. For this, a binary satellite-based FLS mask for each 15-minute interval from 2006-2015 over Europe, by Egli et al. 2017, is used. A logistic regression is applied to identify the dissipation time of each individual fog event from the binary FLS time series. Marked geographic FLS dissipation patterns are apparent, where FLS is found to dissipate earlier in elevated terrains and persist longer in valleys. Furthermore, the influence of different meteorological and land surface conditions on FLS dissipation are investigated.
In the future, the presented approach will be extended to analyze FLS formation and its dependency on meteorological and land surface conditions.

How to cite: Pauli, E., Cermak, J., and Andersen, H.: A satellite perspective on fog and low stratus dissipation over Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9383, https://doi.org/10.5194/egusphere-egu21-9383, 2021.

The occurrence and characteristics of rainfall events in arid and water scarce regions are of great interest to many, as it is vital to understand the efficient use of this finite resource, for example in terms of water management, agriculture, irrigation, and domestic food security. Fundamental to this is understanding the numerous environmental aspects that affect the generation and persistence of rain. These include the presence of cloud droplets, activation and growth processes,  temperature and relative humidity of the within and below cloud regions, and the cloud base height. Not only must what causes rainfall to be initiated be understood, but also the conditions that allow that rain to reach the surface.

This work examines the conditions required for a successful rain event (i.e. one in which rainfall reaches the ground) to occur in the arid desert region of Al Ain, in the United Arab Emirates (UAE) (annual rainfall 76mm).  The high surface temperatures and dry air mean that rain events at Al Ain commonly occur as virga, as the rain droplets cannot survive evaporation under the local atmospheric conditions.  Here we examine individual rainfall events using backscatter data from a laser ceilometer, in conjunction with C-band radar data, to further understand the processes required for successful rain generation.  During the 2 year period of study, there was a total of 57.5 hours of rain (rainfall 0.5% of the time), with a total of 105 rainfall events.  Here we examine the effect on rainfall of (a) the initial size of the droplets falling from the cloud base, which must be large enough to survive the fall to the surface; and (b) the effect of the below cloud thermodynamic profile on the evaporation of the droplet (which also depends on the height of the cloud base). Preliminary conclusions find that smaller droplets, higher cloud bases, smaller cloud depths, and lower cloud base temperatures all favour the occurrence of a rain event terminating as virga before it reaches the surface. Understanding the details of why many potential rainfall events don’t reach the surface can ultimately lead to the more efficient implementation of rainfall enhancing measures such as cloud seeding.

How to cite: Nicoll, K., Airey, M., Harrison, R. G., and Marlton, G.: Rainfall in the desert: anatomy of rainfall events in the United Arab Emirates, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1793, https://doi.org/10.5194/egusphere-egu21-1793, 2021.

Characterization of small-scale temperature structure of convective clouds and their environment is crucial to understand turbulent entrainment, mixing and its effect on cloud dynamics and microphysics. A newly constructed ultra-fast thermometer UFT2, developed from the former UFT-M, allowing for temperature measurements in clouds with the resolution better than few centimeters, was deployed on the British Antarctic Survey Twin-Otter research aircraft in the course of the EUREC4A research campaign. The goal was to perform first ever fine-scale temperature characterization of subtropical marine warm cumulus clouds.

The prototype instrument worked relatively well and allow to collect data from 7 of 17 research flights, including hundreds of cloud penetrations and segments of flights in the marine surface layer. Data, collected with 20 kHz sampling rate, after filtering and averaging allowed to achieve physical resolution of ~3cm at ~60m/s true air speed of the aircraft.

Performance of the UFT-2 sensor and its calibration will be discussed. The discussion will be illustrated with examples of multi-scale temperature records collected in cloud interiors, cloud edges, cloud shells at various altitudes as well as in the marine surface layer ~30 m above the sea level.

How to cite: Król, S., Malinowski, S., Kumala, W., Nowak, J., Grosz, R., Posyniak, M., Lachlan-Cope, T., Blyth, A., and Boeing, S.: Centimeter-scale-resolution airborne temperature measurements in clouds and in marine surface layer during EUREC4A , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14645, https://doi.org/10.5194/egusphere-egu21-14645, 2021.

Microphysical properties of cloud droplets, such as droplet size distribution and droplet
number concentration have been studied after performing a series of field experiments in
summer 2019 at Umweltforschungsstation Schneefernerhaus (UFS), an environmental
research station located just below the peak of Zugspitze in the German Alps.
“VisiSize D30” manufactured by Oxford Laser Ltd. is a shadowgraph imaging instrument
utilized for the first time to measure the size and velocity of cloud droplets during this
campaign. It applies a method called “Particle/Droplet Image Analysis” (PDIA) which
involves illuminating the region of interest from behind with an infrared pulse laser whilst
collecting shadow images of droplets passing through the measurement volume with a
high-resolution camera. Droplets detected inside the depth of field are then measured
based on their shadow images, and size distribution is built by analyzing a series of
images. Furthermore, while turbulent orographic clouds passing our measurement site
at UFS observatory during the campaign, a Phase Doppler Interferometer (PDI) device,
manufactured by Artium Tech. Inc., was also constantly measuring droplets passing
through its probe volume.
Analysis of simultaneously collected data from the two instruments, and applying
modifications to the original algorithms illustrate a reasonable agreement regarding the
droplet sizing and velocimetry between VisiSize D30 and PDI, at least for diameters
larger than 13 μm. Moreover, discrepancies have been observed concerning the
droplet number concentration results, especially in smaller sizes. Further investigation
by applying appropriate filters on data has allowed the attribution of discrepancies to
the different optical performance of the sensors regarding small droplets, and to high
turbulent velocity fluctuations relative to the mean flow resulting in an uncertain estimate
of the volume of air passing through the PDI probe volume.

How to cite: Mohammadi, M., Nowak, J., Bertens, A., Molacek, J., Kumala, W., and Malinowski, S.: Employing a shadowgraph imaging technique for cloud microphysical measurements on a mountain observatory, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9965, https://doi.org/10.5194/egusphere-egu21-9965, 2021.

During the 2013 Southeast Nexus (SENEX) campaign, in-situ observational data were collected on board the NOAA WP-3D aircraft to study the aerosol-cloud droplet link and examine the sensitivity of the cloud droplet number to aerosol physicochemical parameters. In order to do so, observed aerosol number size distributions, chemical composition and vertical-velocity distributions were introduced into a state-of-the-art cloud droplet parameterization from which cloud droplet number and cloud maximum supersaturations were derived. We find that the standard deviation of the vertical velocity (σ_w) exhibits significant diurnal variability ranging from 0.16 m s^-1 during nighttime to over 1.2 m s^-1 during day. Total aerosol number (N_a) covaries with σ_w , with lower values observed during nighttime. The covariance between σ_w and N_a enhances the apparent response of N_d to changes in N_a levels by a factor of 5. For the same “cleaner” environments where N_a values are limited and not impacted by local sources, the relative response of N_d to σ_w is almost twice as great during night, compared to the day (24% during day vs. 42% during night). On the other hand, in environment with enhanced concentrations, especially of accumulation-mode particles, the majority of droplet number variability is attributed to changes in total aerosol number rather than changes in σ_w. Chemical composition is found to on-average have a limited effect on N_d variability (4%). Finally, we identify an upper limit to the number of droplets that can form in clouds which depends only on σ_w independently from total aerosol number. Doubling σ_w from 0.2 to 0.3 m s^-1increases this limiting droplet number by 52%.When N_d values approach this upper limit the observed droplet variability is driven by σ_w and, subsequently, by vertical-velocity changes only. Therefore only by using this -σ_w relationship in regions where velocity-limited conditions are expected, σ_w can be estimated from retrievals of droplet number and vice versa.

How to cite: Bougiatioti, A., Nenes, A., Lin, J., Brock, C., de Gouw, J., Liao, J., Middlebrook, A., and Welti, A.: Cloud droplet variability in the summertime in the southeast United States: day vs. night, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16245, https://doi.org/10.5194/egusphere-egu21-16245, 2021.

Oceanic low level clouds strongly affect the atmospheric radiation budget. Uncertainties in their microphysical properties and cover currently limit the accuracy of climate predictions. Further, studies quantifying the relative importance of aerosol and dynamics on cloud properties in specific meteorological regimes are poorly constrained by observations in the Western North Atlantic boundary layer.

Low level clouds were measured during the Aerosol Cloud meTereology Interactions oVer the western ATlantic Experiment (ACTIVATE) campaign in winter and summer 2020. The two NASA LaRC research aircraft HU-25 Falcon and UC-12 B-200 King Air conducted 35 simultaneous flights to investigate aerosol-cloud interactions of maritime clouds and their impact on radiation. Number concentration, liquid water content, ice water content, and particle size distribution in the size range of 3 µm to 1460 µm in diameter were measured with the fast forward scattering cloud probe (FCDP) and 2-dimensional optical array imaging probe (2D-S) onboard the Falcon. Here, we present an overview of late winter (February-March) and late summer (August-September) oceanic cloud properties in the region 65°W to 80°W and 30°N to 40°N. We compare cloud properties in these two seasons and investigate their dependence on meteorological parameters and aerosol abundance. In a case study, we present cloud observations in a cold air outbreak event on 1 March 2020 with a specific focus on mixed-phase clouds.

How to cite: Kirschler, S., Voigt, C., Ackerman, A. S., Anderson, B., Chen, G., Corral, A. F., Crosbie, E., Dadashazar, H., Ferrare, R. A., Fridlind, A., Hair, J. W., Li, X., Moore, R., Schollmayer, D., Shook, M. A., Thornhill, K. L., Tornow, F., Wang, H., Ziemba, L. D., and Sorooshian, A.: Survey of microphysical properties of marine boundary-layer clouds in the Western North Atlantic , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12251, https://doi.org/10.5194/egusphere-egu21-12251, 2021.

Water in the atmosphere (in vapour, liquid or ice form) act as a fuel for various atmospheric processes through addition/removal of latent heat. Formation of clouds involves all these processes and thus it greatly affects atmospheric dynamics and thermodynamics. It is important to know the vertical location of clouds in atmosphere in order to understand it’s effect on other important atmospheric variables. The interaction of cloud vertical distribution with other meteorological variables is very significant in determining the hydrological cycle of any region. Therefore, in this study we have found out the cloud vertical structure over Delhi and associated it with the precipitation. The cloud top height, base height and cloud thickness along with their vertical location in the atmosphere is known as cloud vertical structure (CVS). The association of CVS with precipitation involving the amount of precipitation contributed by different layers of cloud could be very helpful in weather prediction models. We have used the balloon based measurements to calculate the CVS and for precipitation we have used CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) data. We have done multiple regressions to determine association between Cloud top height, cloud base height and cloud depth with precipitation. We have also related the monthly average of precipitation with monthly frequency of occurrence of single-layer, double-layer and triple-layer clouds. The frequency of occurrence of clouds classified based on their altitude and depth ( i.e., low-level clouds, middle-level clouds, high-level clouds and deep convective clouds) are also correlated with the monthly average precipitation. 

How to cite: Sharma, S. and Mishra, A. K.: A study of Cloud Vertical Structure and its association with precipitation over Delhi., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16447, https://doi.org/10.5194/egusphere-egu21-16447, 2021.

How to cite: McCoy, I. L., McCoy, D. T., Wood, R., Bretherton, C. S., Regayre, L., Watson-Parris, D., Grosvenor, D. P., Gettelman, A., Bardeen, C. G., Mulcahy, J. P., Hu, Y., Bender, F. A.-M., Field, P. R., Carslaw, K. S., and Gordon, H.: A synthesis of observations of aerosol-cloud interactions over the pristine, biologically active Southern Ocean and their implications for global climate model predictions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8499, https://doi.org/10.5194/egusphere-egu21-8499, 2021.

Concentrations of atmospheric ice nucleating particles (INP) were obtained from weekly filter samples which were collected from May 2019 until March 2020 in southern Chile. Sampling took place at an altitude of 620m above sea level, on top of Cerro Mirador, a mountain directly to the west of Punta Arenas (53°S, 71°W). Additional aerosol properties such as particle number size distributions were measured as well. In parallel, ground-based remote sensing measurements with lidar and cloud radar were made in Punta Arenas.

INP concentrations were obtained from washing atmospheric aerosol particles off from deployed polycarbonate filters and subsequent analysis of the samples on two different freezing arrays which were used and described by us earlier (e.g., in Gong et al., 2019 and Hartmann et al., 2020). INP concentrations could be obtained over a broad temperature range from above -5°C down to -25°C.

INP concentrations were clearly higher than data obtained for the Southern Ocean region as reported in McCluskey et al. (2018) and Welti et al. (2020). Indeed, they were comparable to concentrations measured at Cape Verde (Gong et al., 2020). INP concentrations obtained during the warm season were spreading over ~ 2 orders of magnitude at any temperature. Data obtained for the cold season almost all were at the upper end of the observed INP concentration range, with only one weekly sample featuring low concentrations.

Heating of the samples was also applied, and the heated samples had clearly lower INP concentrations across the examined temperatures, implying a biological fraction among the INP of ~ 80%. Therefore, local terrestrial sources may be the source of the observed INP.

The assumption of local terrestrial sources is strengthened by a case study. For that, two subsequent samples obtained during the cold season were examined in more detail. These were the one sample with low INP concentrations which was obtained during the cold season during the week from August 14 to August 22, and the subsequent sample collected from August 22 to August 29, which was amongst the highest samples. Backward trajectories together with an analysis of Lidar data showed that the low INP concentrations were obtained for a time during which air masses predominantly came in from the south with little contact to land and for calm weather conditions. Conditions were not as stable during the following week which featured air masses mostly coming in from the north-west. The aerosol backscatter coefficient at the height level of the in-situ measurements was obtained from lidar observations for both weeks and shows about 50 % lower aerosol load for the first week, when INP concentrations were low.

All of this hints to local terrestrial sources for the observed highly ice active biogenic INP.

Literature:

Gong et al. (2019), Atmos. Chem. Phys., 19, 10883-10900, doi:10.5194/acp-19-10883-2019.

Gong et al. (2020), Atmos. Chem. Phys., 20, 1451-1468, doi:10.5194/acp-20-1451-2020.

Hartmann et al. (2020), Geophys. Res. Lett., 47, doi:10.1029/2020GL087770.

McCluskey et al. (2018), Geophys. Res. Lett., 45, doi:10.1029/2018gl079981.

Welti et a. (2020), Atmos. Chem. Phys. 20, doi:10.5194/acp-2020-466.

How to cite: Wex, H., Gong, X., Barja, B., Seifert, P., Radenz, M., Ansmann, A., Henning, S., Ataei, F., and Stratmann, F.: Ice Nucleating Particles in Southern Chile and their connection to clouds , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7474, https://doi.org/10.5194/egusphere-egu21-7474, 2021.

Here we use 16-year satellite and reanalysis data in combination with a multivariate regression model to investigate how aerosols affect cloud fraction (CF) over the East Coast of the United States. Cloud droplet number concentrations (N_d), cloud geometrical thickness, lower tropospheric stability, and relative humidity at 950 hPa (RH₉₅₀) are identified as major cloud controlling parameters that explain 97% of the variability in CF. N_d is shown to play an important role in regulating the dependence of cloud fraction on RH₉₅₀. The observed annual-mean CF shows no significant trend due to the cancelation from the opposite trends in N_d and RH₉₅₀. The multivariate regression model revealed that the decline in N_d alone would lead to a about 20% relative decline in CF. Our results indicate the significant aerosol effects on CF and suggest the need to account for pollution-induced cloud changes in quantifying cloud feedback based on long-term observations.

How to cite: Cao, Y., Wang, M., Rosenfeld, D., Zhu, Y., Liang, Y., Liu, Z., and Bai, H.: Strong aerosol effects on cloud amount based on long-term satellite observations over the East Coast of the United States, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2457, https://doi.org/10.5194/egusphere-egu21-2457, 2021.

Here, we present investigations on the impact of absorbing aerosol particles on cloud and radiation fields over Germany. Using advanced high-resolution simulations with grid spacings of 312 and 625 m, numerical experiments with different aerosol optical properties are contrasted using purely-scattering aerosol as control case and realistic absorbing aerosol as perturbation. The combined effect of surface dimming and atmospheric heating induces positive temperature and negative moisture anomalies between 800 and 900 hPa impacting low-level cloud formation. Decreased relative humidity as well as increased atmospheric stability below clouds lead to a reduction of low-level cloud cover, liquid water path and precipitation. It is further found that direct and semi-direct effects of absorbing aerosol forcing have similar magnitudes and equally contribute to a reduction of net radiation at the top of the atmosphere .

How to cite: Senf, F., Quaas, J., and Tegen, I.: Absorbing aerosol decreases cloud cover in cloud-resolving simulations over Germany, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8941, https://doi.org/10.5194/egusphere-egu21-8941, 2021.

Aerosol effects on clouds’ microphysics and dynamics are still considered as an important open question that contributes a major uncertainty to climate research and prediction. Using 7 years of observational and reanalysis data, we show a non-monotonic trend in convective cloud properties and rain intensity as a function of aerosol optical depth (AOD). The invigoration effect shifts into weak suppression beyond an optimal AOD ( of ~ 0.3-0.4). Using a cloud model we explain this shift in trend as the result of a competition between two types of microphysical processes: cloud-core-based invigorating processes vs. peripheral suppressive processes. We show that the optimal AOD, for which cloud and rain reach their maximal values, depends on the environmental thermodynamic conditions and it is higher for more unstable or more humid conditions. Our findings improve the understanding of aerosol-cloud interaction and their link to environmental conditions. It can aid in the improvement of parameterizations of clouds in climate models.

How to cite: Liu, H., Guo, J., Koren, I., Altaratz, O., Dagan, G., Wang, Y., Jiang, J. H., Zhai, P., and Yung, Y. L.: Non-Monotonic Aerosol Effect on Precipitation over the ITCZ, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3892, https://doi.org/10.5194/egusphere-egu21-3892, 2021.

Biomass burning (BB) aerosols can influence regional and global climate through interactions with radiation, clouds, and precipitation. Here, we investigate the impact of BB aerosols on the energy balance and hydrological cycle over the Amazon Basin during the dry season. We performed WRF-Chem simulations for a range of different BB emission scenarios to explore and characterize nonlinear effects and individual contributions from aerosol–radiation interactions (ARIs) and aerosol–cloud interactions (ACIs). For scenarios representing the lower and upper limits of BB emission estimates for recent years (2002–2016), we obtained total regional BB aerosol radiative forcings of -0.2 and 1.5Wm^-2, respectively, showing that the influence of BB aerosols on the regional energy balance can range from modest cooling to strong warming. We find that ACIs dominate at low BB emission rates and low aerosol optical depth (AOD), leading to an increased cloud liquid water path (LWP) and negative radiative forcing, whereas ARIs dominate at high BB emission rates and high AOD, leading to a reduction of LWP and positive radiative forcing. In all scenarios, BB aerosols led to a decrease in the frequency of occurrence and rate of precipitation, caused primarily by ACI effects at low aerosol loading and by ARI effects at high aerosol loading. Overall, our results show that ACIs tend to saturate at high aerosol loading, whereas the strength of ARIs continues to increase and plays a more important role in highly polluted episodes and regions. This should hold not only for BB aerosols over the Amazon, but also for other light-absorbing aerosols such as fossil fuel combustion aerosols in industrialized and densely populated areas. The importance of ARIs at high aerosol loading highlights the need for accurately characterizing aerosol optical properties in the investigation of aerosol effects on clouds, precipitation, and climate.

How to cite: Liu, L., Cheng, Y., Wang, S., Wei, C., Pöhlker, M., Pöhlker, C., Artaxo, P., Shrivastava, M., Andreae, M., Pöschl, U., and Su, H.: The key role of aerosol-radiation-interactions on cloud formation and precipitation in the Amazon, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15593, https://doi.org/10.5194/egusphere-egu21-15593, 2021.

Subtropical low-level marine stratocumulus clouds effectively reflect downwelling shortwave radiation while having a small effect on outgoing longwave radiation. Hence, they impose a strong negative net radiative effect on the Earth’s radiation balance. The optical and microphysical properties of these clouds are susceptible to anthropogenic changes in aerosol abundance. Although these aerosol-cloud-climate interactions (ACI) are generally explicitly treated in state-of-the-art Earth System Models (ESMs), they are accountable for large uncertainties in current climate projections.

Here, we present preliminary work where we exploit Large-Eddy-Simulations (LES) of warm stratocumulus clouds to identify and constrain processes and model assumptions that affect the response of cloud droplet number concentration (N_d) to changes in aerosol number concentration (N_a). Our results are based on simulations with the MISU-MIT Cloud-Aerosol (MIMICA, Savre et al., 2014) LES, which has two-moment bulk microphysics (Seifert and Beheng, 2001) and a two-moment aerosol scheme (Ekman et al., 2006). The reference simulation is based on observations made during the Dynamics and Chemistry of Marine Stratocumulus Field Study (DYCOMS-II, Stevens et al., 2003) which were used extensively during previous LES studies (e.g., Ackerman et al., 2009).

Starting from the reference simulation, we conduct sensitivity experiments to examine how the susceptibility (β=dln(N_d)/dln(N_a)) changes depending on different model setups. We run the model with fixed and interactive aerosol concentrations, with and without saturation adjustment, with different aerosol populations, and with different model parameter choices. Our early results suggest that β is sensitive to these choices and can vary roughly between 0.6 to 0.9 depending on the setup. The overall purpose of our study is to guide future model developments and evaluations concerning aerosol-cloud-climate interactions.  

References

Ackerman, A. S., vanZanten, M. C., Stevens, B., Savic-Jovcic, V., Bretherton, C. S., Chlond, A., et al. (2009). Large-Eddy Simulations of a Drizzling, Stratocumulus-Topped Marine Boundary Layer. Monthly Weather Review, 137(3), 1083–1110. https://doi.org/10.1175/2008MWR2582.1

Ekman, A. M. L., Wang, C., Ström, J., & Krejci, R. (2006). Explicit Simulation of Aerosol Physics in a Cloud-Resolving Model: Aerosol Transport and Processing in the Free Troposphere. Journal of the Atmospheric Sciences, 63(2), 682–696. https://doi.org/10.1175/JAS3645.1

Savre, J., Ekman, A. M. L., & Svensson, G. (2014). Technical note: Introduction to MIMICA, a large-eddy simulation solver for cloudy planetary boundary layers. Journal of Advances in Modeling Earth Systems, 6(3), 630–649. https://doi.org/10.1002/2013MS000292

Stevens, B., Lenschow, D. H., Vali, G., Gerber, H., Bandy, A., Blomquist, B., et al. (2003). Dynamics and Chemistry of Marine Stratocumulus—DYCOMS-II. Bulletin of the American Meteorological Society, 84(5), 579–594. https://doi.org/10.1175/BAMS-84-5-579

How to cite: Schwarz, M., Savre, J., and Ekman, A.: Quantifying how model assumptions affect aerosol-cloud interactions in large-eddy simulations of warm stratocumulus clouds, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11169, https://doi.org/10.5194/egusphere-egu21-11169, 2021.

Mountains play a key role for humanity providing freshwater for the areas downstream. The amount of precipitation at a given location is significantly affected by orography. Since changes of rainfall are expected in the changing climate, understanding how orographic precipitation responds to global warming and to anthropogenic forcing is becoming particularly pressing. To better understand the physical processes at play, in this study we investigate the indirect effects of aerosols on precipitation using the Weather Research Forecasting (WRF) Model: sentivity experiments are run with different numbers of water-friendly and ice-friendly aerosols in the atmospheric boundary layer.  5-years long simulations at high spatial resolution (4Km) have been run in the Great Alpine Region, where orographic lifting plays an important role and precipitation has a large spatial variability due to the complex orography. Results indicate that the indirect effects of aerosols modify cloudiness and precipitation in different ways among the flatlands (Po Valley) and the mountain areas. Physical mechanism at the base of those differences are discussed.

How to cite: napoli, A., pasquero, C., and parodi, A.: High resolution numerical investigation of the indirect effects of aerosols on orographic precipitation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4133, https://doi.org/10.5194/egusphere-egu21-4133, 2021.

It is challenging to separate the cause from effect in aerosol-cloud interactions. Anomalous cloud lines polluted by anthropogenic aerosols help distinguish the cause from effect as properties of polluted clouds can be directly compared to nearby unpolluted clouds’ properties. Pollution tracks in clouds induced by localised aerosol emissions (Toll et al. 2019, Nature, https://doi.org/10.1038/s41586-019-1423-9)  are visually detectable ship-track-like quasi-linear polluted cloud features in satellite snapshots. We detected similar anomalous polluted cloud lines in the long-term average satellite data, where cloud response to aerosol over a long time is recorded. Polluted cloud tracks are induced by various aerosol sources like oil refineries, smelters, coal-fired power plants, smaller industry towns, ships, and volcanoes. We detected polluted cloud tracks at spatial scales varying from tens of kilometres to thousands of kilometres (Trofimov et al. 2020; JGR Atmospheres, https://doi.org/10.1029/2020JD032575).  

Polluted cloud tracks detected in satellite snapshots are excellent for the process-level understanding of aerosol-cloud interactions. Polluted cloud tracks recorded in satellite climatologies are great for estimating the average cloud response to aerosols. MODIS snapshots of polluted cloud tracks show relatively weak cloud water response to aerosols at various spatial scales. High-resolution analysis of South-East Atlantic shipping corridor shows partial off-set of the Twomey effect by decreased cloud water. Cloud fraction sometimes increases in the polluted cloud tracks and sometimes decreases compared to the nearby unpolluted clouds. The temporal evolution of cloud responses in pollution tracks estimated from geostationary SEVIRI data and meteorological conditions favourable for pollution track occurrence is presented. We expect that the utilisation of these real-world laboratories of aerosol impacts on clouds helps to improve global climate models’ physical parameterisations.

How to cite: Toll, V., Trofimov, H., Rahu, J., and Post, P.: Polluted cloud lines in satellite snapshots and satellite climatologies, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7164, https://doi.org/10.5194/egusphere-egu21-7164, 2021.

Reducing uncertainty in aerosol-cloud interactions is necessary for more reliable climate projections. Understanding the effects of anthropogenic aerosols on clouds remains a challenge due to complex processes governing the cloud adjustments to increased cloud droplet numbers. Using SEVIRI data, we study the daily evolution of polluted cloud tracks induced by strong pollution sources in the European part of Russia. We use semi-automated cloud droplet effective radius based statistical classification algorithm to differentiate between polluted and nearby unpolluted pixels in the satellite images. We use the 15-minute resolution Cloud Physical Properties product by KNMI to study changes in polluted cloud properties during the daytime. In some cases, cloud water increases during the day and in some cases decreases in polluted clouds compared to the nearby unpolluted clouds. On average, the diurnal evolution of cloud water is very similar between polluted and unpolluted clouds. Interestingly, there is less cloud water in polluted clouds already in the morning, suggesting that cloud water decreases more in polluted clouds during the night. The relatively weak average decrease in cloud water agrees with MODIS-based estimate (Toll et al 2019, Nature, https://doi.org/10.1038/s41586-019-1423-9).

How to cite: Rahu, J., Post, P., and Toll, V.: The diurnal evolution of anthropogenic aerosol impacts on clouds, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11700, https://doi.org/10.5194/egusphere-egu21-11700, 2021.

Pollution tracks in clouds induced by anthropogenic aerosols (Toll et al 2019, Nature, https://doi.org/10.1038/s41586-019-1423-9) are visually detectable ship-track-like quasi-linear polluted cloud features in satellite imagery. Pollution tracks provide a direct way to study aerosol-cloud interactions, the most uncertain mechanism of anthropogenic climate forcing. Here, we study environmental conditions favourable for pollution tracks’ formation. We use meteorological data from in-situ observations and ERA5 reanalysis and cloud properties derived from MODIS retrievals over the period 2000-2019. We detected pollution track occurrences at the anthropogenic air pollution hot spots of Norilsk and Cherepovec in Russia and Thompson in Canada. In Norilsk, there are large Nickel smelters, in Cherepovec, a steel manufacturing plant, and in Thompson nickel mining and milling operations take place. We compare the meteorological conditions of track-days to cloudy no-track-days. Depending on the studied location, polluted cloud tracks occur 2.7% to 3.5% of the time. Preliminary results show track formation dependence on large-scale dynamical situation, atmospheric stability, unperturbed cloud properties and relative humidity below and above clouds. The track formation could be limited by aerosols, aerosol vertical transport and activation or cloud susceptibility. Our results help to reduce the uncertainty associated with the anthropogenic aerosol impacts on clouds.

How to cite: Trofimov, H. and Toll, V.: Meteorological conditions favourable for strong aerosol impacts on clouds, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11933, https://doi.org/10.5194/egusphere-egu21-11933, 2021.

How to cite: Gryspeerdt, E., Smith, T., and Goren, T.: Observing the timescales of aerosol-cloud interactions in snapshot satellite images, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8642, https://doi.org/10.5194/egusphere-egu21-8642, 2021.

Satellite observations are used in regional machine learning models to quantify sensitivities of marine boundary-layer clouds (MBLC) to aerosol changes.

MBLCs make up a large part of the global cloud coverage as they are persistently present over more than 20% of the Earth’s oceans in the annual mean.They play an important role in Earth’s energy budget by reflecting solar radiation and interacting with thermal radiation from the surface, leading to a net cooling effect. Cloud properties and their radiative characteristics such as cloud albedo, horizontal and vertical extent, lifetime and precipitation susceptibility are dependent on environmental conditions. Aerosols in their role as condensation nuclei affect these cloud radiative properties through changes in the cloud droplet number concentration and subsequent cloud adjustments to this perturbation. However, the magnitude and sign of these effects remain among the largest uncertainties in future climate predictions.

In an effort to help improve these predictions a machine learning approach in combination with observational data is pursued:

Satellite observations from the collocated A-Train dataset (C3M) for 2006-2011 are used in combination with ECMWF atmospheric reanalysis data (ERA5) to train regional Gradient Boosting Regression Tree (GBRT) models to predict changes in key physical and radiative properties of MBLCs. The cloud droplet number concentration (N_d) and the liquid water path (LWP) are simulated for the eastern subtropical oceans, which are characterised by a high annual coverage of MBLC due to the occurrence of semi-permanent stratocumulus sheets. Relative humidity above cloud, cloud top height and temperature below the cloud base and at the surface are identified as important predictors for both N_d and LWP.  The impact of each predictor variable on the GBRT model's output is analysed using Shapley values as a method of explainable machine learning, providing novel sensitivity estimates that will improve process understanding and help constrain the parameterization of MBLC processes in Global Climate Models.

How to cite: Zipfel, L., Andersen, H., and Cermak, J.: Quantification of aerosol effects on marine boundary layer clouds with machine learning, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10754, https://doi.org/10.5194/egusphere-egu21-10754, 2021.

Clouds play a key role in the atmosphere by completing the hydrological cycle and transferring water from the atmosphere to the earth's surface on the one hand, and affecting terrestrial radiation and solar radiation on the other hand. Although cloud properties are primarily affected by atmospheric dynamics, cloud microphysical features, which themselves are influenced by the number and chemical composition of aerosols that act as cloud condensation nuclei (CCN) and ice nuclei (IN) within cloud droplets, also affect cloud formation.

The extent and quality of aerosols impact on cloud formation is one of the important open question of climate science. Volcanoes, which are a rich source of various chemical compounds, can help to improve the understanding of the effects of aerosols on clouds by providing a natural laboratory with locally high aerosol conditions adjacent to an unperturbed environment.

In the present study, the impacts of changing the aerosol number concentration on clouds are investigated using the ICON-ART model. For this purpose, the Holuhraun volcano, which erupted on the island of Iceland in 2014, was simulated. It emitted small amounts of volcanic ash, and large emissions of gases primarily sulfur dioxide (SO2), which formed sulfate particles serving as CCN. Three simulations representing low, control, and high emission conditions were conducted. For the control simulation, the source strength of SO2 was based on the estimate by Malavelle et al. (2017). This rate, then, was reduced to one-fifth for the low emission experiment and increased by a factor of 5 for the high emission experiment.

First results indicate that increasing the source strength of SO2 is associated with an enhancement of sulfate aerosol number concentration and thus an increase of the number of cloud droplets, but with strongly nonlinear effects. For clouds within the volcanic plume, droplet concentrations are already high in the low emission scenario and do not increase significantly with higher emission strengths, partly due to model limitations. In addition, the effect of aerosols on the formation of cloud droplets is strongly dependent on environmental factors