Displays

Cirrus clouds in the tropopause region form via two major different pathways, i.e. freezing super-cooled cloud droplets (liquid origin) or nucleating ice crystals at humidities below water saturation (in situ formation). The latter case takes place in the low temperature regime (T<235K) and it is assumed that in this regime homogeneous freezing of supercooled solution droplets (short: homogeneous nucleation) is the dominant formation pathway. For homogeneous nucleation, a nucleation rate has been derived from laboratory experiments, based on water activity. The formulation of the nucleation rate is reassessed and simple but robust approximations are presented, which can be used in less complex models without a direct interaction with aerosols. The impact of nucleation rates and the formulation of diffusional growth for idealized nucleation rates is investigated. It can be found that the absolute value of the nucleation rate has almost no impact on the produced ice crystal number concentrations, whereas the steepness of the rate is much more important. Finally, it turns out that the formulation of diffusional growth affects nucleation events crucially in terms of produced ice crystal numbers.

How to cite: Spichtinger, P.: Impact of nucleation rates and diffusional growth on ice nucleation events, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19884, https://doi.org/10.5194/egusphere-egu2020-19884, 2020.

We have extended the large-eddy model UCLALES-SALSA (Tonttila et al., 2017) to include formation of ice and mixed-phase clouds. The model has exceptionally detailed aerosol description for both aerosol number and chemical composition. We confirmed the accuracy of newly implemented ice microphysics with a comparison to a previous mixed-phase cloud model intercomparison study.

In a further simulation the model captured the typical layered structure of Arctic mixed-phase clouds: a liquid layer near cloud top and ice within and below the liquid layer. The simulation also demonstrated how larger droplets froze first. Moreover, the simulation showed realistic freezing rates of droplets within the vertical cloud structure. These characteristics were possible to capture with a heterogeneous ice nucleation scheme, where also ice nucleating particles (INP) are prognosed. Here, dust containing particles acted as INPs.

The prognostic simulation showed the importance of the self-adjustment of ice nucleation active particles. This is in good agreement with an observational study where resilient mixed-phase clouds are seen together with relatively high ice nuclei concentrations.

The implemented detailed sectional ice microphysics with prognostic aerosols is essentially important in reproducing the characteristics of mixed-phase clouds. The manuscript of this study is submitted for publication.

How to cite: Ahola, J., Korhonen, H., Tonttila, J., Romakkaniemi, S., Kokkola, H., and Raatikainen, T.: Modelling mixed-phase clouds with large-eddy model UCLALES-SALSA, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13448, https://doi.org/10.5194/egusphere-egu2020-13448, 2020.

We present a simulated simultaneous retrieval of mass mean cloud ice particle effective diameter, ice water content, water vapor, and temperature profiles using a combination of a 94-GHz cloud radar and multi-frequency (118, 183, 240, 310, 380, 664, and 850 GHz) millimeter- and submillimeter-wave radiometers from a space platform. The retrieval capabilities and uncertainties of the combined radar and microwave radiometers are quantified. We show that this combined active and passive remote sensing approach with SmallSat technologies addresses a gap in the current state-of-the-art remote sensing measurements of ice cloud properties, especially deriving vertical profiles of ice cloud particle sizes in the atmosphere together with the ambient thermodynamic conditions. Therefore, this new approach can serve as a plausible candidate for future missions that target cloud and precipitation processes to improve weather forecasts and climate predictions.  

How to cite: Jiang, J., Su, H., Yue, Q., and Kangaslahti, P.: Simulation of remote sensing of clouds and humidity from space using a combined platform of radar and multi-frequency microwave radiometers , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20864, https://doi.org/10.5194/egusphere-egu2020-20864, 2020.

Secondary ice production processes are widely proposed as the pathway by which observed cloud ice number concentration can markedly exceed what is expected from primary ice nucleation alone. These processes play a critical, yet poorly constrained, role in the lifecycle of mixed-phase clouds. Presently, main constraints on secondary ice production come from airborne observations, but the transiency of such observations makes it difficult to paint a complete picture of these processes. Here, we develop a novel method for retrieving ice number concentration in a Lagrangian reference frame, allowing us to unearth information not accessible from existing aircraft observations. Our retrieval method employs an iterative ensemble approach, advanced ice crystal models, and the traditional suite of polarimetric radar observables. We will present examples from the Atmospheric Radiation Measurement (ARM) program Mobile Facility deployment in Finland and evaluations against in-situ observations from the UK Parameterizing Ice Clouds using Airborne obServationS and triple-frequency dOppler radar data (PICASSO) field campaign. We will also present a climatology of cloud ice number concentration from the Finland campaign, shedding light on the spatiotemporal evolution, process rates, and trigger requirements of secondary ice production events.

How to cite: Kedzuf, N., Chiu, J. C., Chandrasekar, V., and Westbrook, C.: Characterizing secondary ice production events in mixed-phase clouds using ground-based polarimetric radar, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12599, https://doi.org/10.5194/egusphere-egu2020-12599, 2020.

Lidar measurement of cirrus at Palau Island (7°N 134°E)

Francesco Cairo [1], Marcel Snels [1], Andrea Scoccione [1,2], Mauro De Muro [1,3], Luca Di Liberto [1], Stefano Ghisu [4], Ajil Kottayl [5], Bernard Legras [6], Silvia Bucci [6].

[1] Institute of Atmospheric Sciences and Climate, ISAC-CNR, Rome, Italy

[2] Now at: Centro Operativo per la Meteorologia, Aeronautica Militare, Pomezia, Italy

[3] Now at: AIT Thales Alenia Space, Roma, Italy

[4] Università degli Studi di Roma "Tor Vergata", Dipartimento di Fisica, Roma, Italy

[5] Cochin University of Science and Technology, CUSAT, Cochin, India

[6] Laboratoire de Météorologie Dynamique, LMD-CNRS, Paris, France

A polarization diversity elastic backscatter lidar has been deployed in the equatorial island of Palau in Feb- Mar 2016. The system operated unattended in the Atmospheric Observatory of Palau Island, from 15 February to 25 March 2016, working automatically 8 hrs per night, delivering 3650 atmospheric profiles (5 min average). Each profile extends from 1 to 30 km height. Here the dataset is presented and discussed in terms of the temperature structure of the UTLS, as derived from co-located PTU soundings. During the timeframe of the campaign it was found that the main convective outflows peaks roughly 3 km below the Cold Point Tropopause, its occurrence associated with cold anomalies in the upper troposphere (UT). When warm UT anomalies occur, presence of particles is restricted to a 5 km wide layer centered 5 km below the CPT. Particles have been detected also slightly above the CPT. These particles are depolarizing, with depolarization values generally lower than those encountered in the TTL. Results show a correlation between presence of optically detectable particles and cold anomalies above the Cold Point. A backtrajectory analysis coupled with satellite observation of convective activity was performed, in order to link the presence of cirrus with their convective origin and inferred lifetime, or possibly with in-situ formation processes. 

How to cite: Cairo, F., Snels, M., Scoccione, A., De Muro, M., Di Liberto, L., Ghisu, S., Kottayl, A., Legras, B., and Bucci, S.: Lidar measurement of cirrus at Palau Island (7°N 134°E), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13353, https://doi.org/10.5194/egusphere-egu2020-13353, 2020.

Particle size distributions (PSDs) for cirrus clouds are important for both climate models as well as many remote sensing retrieval methods. Therefore, PSD parametrizations are required. This study presents parametrizations of Arctic cirrus PSDs. The dataset used for this purpose originates from balloon-borne measurements carried out during winter above Kiruna (Sweden), i.e. north of the Arctic circle. The observations are sorted into two types of cirrus cloud origin, either in-situ or liquid. The cloud origin describes the formation pathway of the ice particles. At temperatures below −38 °C, ice particles form in-situ from solution or ice nucleating-aerosol particles. Liquid origin ice particles have formed at temperatures warmer than or equal to −38 °C, either via ice-nucleating particles embedded in liquid drops or via homogeneous drop freezing, and are then further uplifted to the cirrus temperature regime.

In order to derive parametrizations for each cloud origin, the observed PSDs are represented by gamma functions. The gamma coefficients exhibit large differences with regard to cloud origin. Functions describing the relationships in between the gamma coefficients and with temperature are fitted. These functions for Arctic cirrus confirm established parametrizations for continental cirrus sorted by two particle size modes but differ from others depending only on temperature. We suppose that the agreement between the parametrizations of the geographically different cirrus is because in-situ and liquid origin cirrus also distinguish by particle size modes. Since cloud sorting by their origin is based on physical processes that are independent of geographical region, we further hypothesize that these cloud-type-based parametrizations might be generally valid for use in global models and satellite retrievals, given the distribution of the cloud types is known.

How to cite: Kuhn, T., Wolf, V., and Krämer, M.: On the Dependence of Cirrus Parametrizations on the Cloud Origin, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6733, https://doi.org/10.5194/egusphere-egu2020-6733, 2020.

This study presents airborne in-situ and satellite remote sensing climatologies of cirrus clouds and humidity. The climatologies serve as a guide to the properties of cirrus clouds, with the new in-situ data base providing detailed insights into boreal mid-latitudes and the tropics, while the satellite-borne data set offers a global overview.

To this end, an extensive, quality checked data archive, the Cirrus Guide II in-situ data base, is created from airborne in-situ measurements during 150 flights in 24 campaigns. The archive contains meteorological parameters, IWC, N_ice, R_ice , RH_ice and H₂O (IWC: ice water content, N_ice: number concentration of ice crystals, R_ice : ice crystal mean mass radius, RH_ice: relative humidity with respect to ice, H₂O: water vapor mixing ratio) for each of the flights. Depending on the specific parameter, the data base has extended by about a factor of 5-10 compared to the previous studies of Schiller et al. (2008), JGR, and Krämer et al. (2009), ACP.

An important step in completing the Cirrus Guide II is the provision of the global cirrus N_ice climatology, derived by means of the retrieval algorithm DARDAR-Nice from 10 years of cirrus remote sensing observations from satellite. The in-situ data base has been used to evaluate and adjust the satellite observations.

A specific highlight of the study is the in-situ observations of tropical tropopause layer (TTL) cirrus and humidity in the Asian monsoon anticyclone and the comparison to the surrounding tropics.

How to cite: Krämer, M. and Rolf, C. and the Cirrus Guide II Team: A Microphysics Guide to Cirrus -- Part II: Climatologies of Clouds and Humidity from Observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12982, https://doi.org/10.5194/egusphere-egu2020-12982, 2020.

Substantial efforts have been led over the last decades to improve our understanding of the interactions between clouds and anthropogenic aerosols (aci). The effective radiative forcing associated with these interactions (ERFaci), which combines the radiative forcing (i.e. Twomey effect) and cloud adjustments, still constitutes a large part of our current uncertainties on climate predictions.

Important progress has been made in the assessment of ERFaci for liquid clouds, partly due to advances in the joint use of satellite and modelling data to tackle this problem. More particularly, the retrieval of the droplet number concentration from satellite remote sensing - a property closely related to droplet nucleation processes - has been extremely helpful to better quantify ERFaci. However, similar estimations for ice clouds have for long suffered from a lack of observational constraint on the ice crystal number concentration (N_i), a challenging task due to the high complexity of the physical processes associated with the nucleation and growth of ice crystals. However, a novel long-term global dataset of N_i from active satellite measurements has recently (DARDAR-Nice) opened the door to new observation-based estimates of RFaci for ice clouds.

This study investigates aerosol - ice clouds interactions using N_i profiles from the DARDAR-Nice product together with collocated aerosol information from the Copernicus Atmospheric Monitoring Service (CAMS) reanalyses. A multitude of cloud regimes, subdivided into seasonal and regional bins, are considered in order to disentangle meteorological effects from the aci signature. First results of joint-histograms between N_i and the aerosol mass show an overall positive sensitivity of N_i to the aerosols load. This response is particularly strong towards to cloud-top and flattens towards cloud-base, consistently with expectations for ice nucleation processes. In terms of adjustments, the relation between IWP and Ni is also investigated. Preliminary results suggest a slightly negative global ERFaci for ice clouds, with important regional variations, but a precise quantifications of these effects will require further statistics.

How to cite: Sourdeval, O., Gryspeerdt, E., Mülmenstädt, J., Krämer, M., and Quaas, J.: Satellite-based estimate of the climate forcing due to aerosol - ice cloud interactions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17971, https://doi.org/10.5194/egusphere-egu2020-17971, 2020.

How to cite: Zou, L., Griessbach, S., Hoffmann, L., Gong, B., and Wang, L.: Satellite observations of cirrus clouds in the lower stratosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8953, https://doi.org/10.5194/egusphere-egu2020-8953, 2020.

Ice cloud particle size is important to determining ice cloud radiative effect and precipitating rate. However, there is a lack of accurate ice particle effective radius (R_ei) observation on the global scale and the parameterization of R_ei in climate models is poorly constrained. We conduct a modeling study to assess the sensitivity of climate simulations to R_ei. Perturbations to R_ei are represented in ice fall speed parameterization and radiation scheme, respectively, in NCAR CESM1 model with a slab ocean configuration. We show that an increase in ice fall speed due to a larger R_ei results in a longwave cooling dominating over a shortwave warming, a global mean surface temperature decrease, and precipitation suppression. Similar longwave and shortwave cloud radiative effect changes occur when R_ei is perturbed in the radiation scheme. Perturbing falling snow particle size (R_es) results in much smaller changes in the climate responses. We further show that varying R_ei and R_es by 50% to 200% relative to the control experiment can cause climate sensitivity to differ by +12.3% to −6.2%. A future mission under design with combined multi-frequency microwave radiometers and cloud radar can reduce the uncertainty ranges of R_ei and R_es from a factor of 2 to ±25%, which would help reducing the climate sensitivity uncertainty pertaining to ice cloud particle size by approximately 60%.

How to cite: Su, H., Wang, Y., Jiang, J., Xu, F., and Yung, Y.: Impacts of Ice Cloud Particle Size Uncertainty on Radiation, and Precipitation and Climate Sensitivity and the Significance of Future Satellite-Based Constraints , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5864, https://doi.org/10.5194/egusphere-egu2020-5864, 2020.

Arctic mixed-phase clouds are still not properly represented in weather forecast and climate models. Recent field campaigns in the Arctic have successfully probed low level mixed-phase clouds, however it remains difficult to gain understanding of this complex system from observational datasets alone. Complementary high-resolution simulations, properly constrained by relevant measurements, can serve as a virtual laboratory that provides a deeper insight into a developing boundary layer in the Arctic.

Our study focus on the impact of variability in cloud condensation nuclei (CCN) concentrations on the turbulence in Arctic mixed-phase clouds. Large-Eddy Simulations of convective mixed-phase clouds over open water were performed as observed during the ACLOUD campaign, which took place in Fram Strait west of Svalbard in May and June 2017. The Dutch Atmospheric Large Eddy Simulation (DALES) is used including a well-established double-moment mixed-phase microphysics scheme of Seifert & Beheng.

The results highlight various impact mechanisms of CCN on the boundary layer thermodynamic state, turbulence, and clouds. Lower CCN concentrations generally lead to decreased turbulence near the cloud top. However, they can also enhance the turbulence in the lower part of the boundary layer due to increased amount of sublimation of ice hydrometeors. Further implications for the role of mixed-phase clouds in the Arctic Amplification will be discussed.

How to cite: Chylik, J., Mertes, S., and Neggers, R.: Impacts of Aerosol Concentration Variability on Turbulence in Convective Low Level Mixed-phase Clouds in the Arctic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18426, https://doi.org/10.5194/egusphere-egu2020-18426, 2020.

Ice- and mixed-phase clouds largely contribute to global precipitation due to their high spatiotemporal coverage. It has been highlighted that aerosol-cloud interaction is a critical factor. However, our current understanding of the complexity of their microphysical properties is still rather limited.  

In this talk, we will discuss the impact of perturbations of the cloud condensation nuclei (CCN) and ice-nucleating particle (INP) on the structure and composition of mixed-phase clouds. The main methods are ground-based observations (i.e., Ka-band polarimetric cloud radar) as well as the spectral-bin microphysical methodology called AMPS (Advanced Microphysics Prediction System). Until now, significant efforts have been underway to improve microphysical processes in AMPS, such as the schemes for immersion freezing and habit prediction. Despite these endeavors, it is still challenging using modeling alone to resolve such complexity of microphysical processes due to many parameterizations and assumptions. In particular, the ice habit prediction system in AMPS is sensitive to the 3-D Eulerian advection scheme. Meanwhile, the Doppler-spectra derived from polarimetric cloud radar enables us to retrieve the hydrometeor habit of the significant signal peak in the Doppler spectrum of mixed-phase clouds. The synergy between the above mentioned advanced modeling approach and state-of-the-art observation techniques are in our study used to evaluate the effects of the CCN and INP perturbations on mixed-phase clouds. 

The steps are as follows. First of all, we will present the evaluation of a case study of a mixed-phase cloud by observation data. In the course of the work, AMPS is coupled with the German weather prediction system COSMO (Consortium for Small-scale Modeling) model. We choose an observation dataset from the ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) field campaign in Cabauw, Netherlands, which was conducted during fall 2014. Also, we use the radar forward operator CR-SIM (Cloud Resolving Model Radar Simulator) that translates the dataset of simulation output into radar variables. Therefore, we will present direct comparisons between ground-based observation and modeling datasets. In the next step, AMPS is coupled with a simple 1-D dynamic core KiD (Kinematic Driver for microphysics intercomparison), so-called KiD-AMPS. In doing so, we will discuss the comparison with other schemes (i.e., Morrison 2-moment). Finally, in the frame of KiD-AMPS, we will debate the impact of the CCN and INP perturbations on mixed-phase clouds. 

How to cite: Lee, J., Seifert, P., Hashino, T., Schrödner, R., Weger, M., Senf, F., and Knoth, O.: Assessment of the impact of INP and CCN perturbations on mixed-phase cloud microphysics using a spectral-bin model and reference observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11342, https://doi.org/10.5194/egusphere-egu2020-11342, 2020.

Ice nucleation in the atmosphere leads to the formation of mixed-phase as well as cirrus clouds in the upper troposphere. Cloud glaciation can either occur homogeneously at temperatures below -38°C or heterogeneously in the presence of ice-nucleating particles (INPs) at temperatures higher than -38°C. Depending on the aggregate state of a cloud, it’s life time and radiative properties vary and thus affect regional and global climate. The influence of biogenic INPs on atmospheric processes as well as the transport of these particles from the land surface to the atmosphere remains elusive. Several plants from boreal and alpine forests are known to contain ice-nucleating macromolecules (INMs) to survive in extreme conditions. However, less is known about chemical characteristics and actual emission rates of such INMs.

We present here our investigation of surface extracts from different tree tissues (Betula pendula and Pinus sylvestris). We were able to extract INMs from nearly all samples. Furthermore, we analyzed the ability of these INMs to be released during rain fall events in-situ. To investigate possible transport mechanisms of INMs from the canopy of studied tree species to the atmosphere we sampled aerosols with two small scale drones, carrying our self-build sampling systems called DAPSI (Drone-based Aerosol Particles Sampling Impinger/Impactor). Results indicate that birches and pines outline an important source of airborne biogenic INPs.

How to cite: Seifried, T. M., Bieber, P., Felgitsch, L., and Grothe, H.: Ice-nucleating Macromolecules from Alpine Forests as Possible Contributors to Cloud Glaciation Processes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12018, https://doi.org/10.5194/egusphere-egu2020-12018, 2020.

The Sahara Desert is the major source of mineral dust, which is a significant portion of atmospheric aerosol. Mineral dust particles play a role in radiative balance, with a direct effect and by influencing cloud formation and lifetime. They have been recognized as highly efficient ice nuclei, fostering the development of parameterizations for immersion and deposition freezing involving dust particles. Feldspar minerals have shown to be a significantly more efficient ice nucleating agents than other dust minerals which led to the development of a ‘mineralogy sensitive’ immersion freezing parameterization. The investigation of the relative efficiency of quartz compared to feldspars for the immersion ice nucleation, based upon literature data and new experiments, led to the development of a new parameterization to be applied to mineral dust concentrations. Within numerical models, explicit simulation of mineral dust fractions enables the use of ‘mineralogy sensitive’ immersion parameterizations.

The operational DREAM model calculates the number of ice nuclei,but does not take into consideration the mineral composition of dust. In this study, instead, we use DREAM model to simulate the atmospheric cycle of feldspar and quartz fractions of dust. Dust mineral composition is used to calculate ice nucleating particle concentrations based on mineral-specific immersion freezing parameterizations. A case study related to the observations of geometrical and microphysical characteristics of the clouds formed in the Mediterranean, in April 2016 is considered. We compare the model results with ice nucleating particle concentrations retrieved using lidar and radar ground-based remote sensing observations at Cyprus and Potenza. The analysis explores how the mineral composition of dust and the parameterization of its effects on ice initiation could further improve ice nucleation representation in numerical models.

How to cite: Ilić, L., Jovanović, A., Kuzmanoski, M., Madonna, F., Rosoldi, M., Marinou, E., and Ničković, S.: Mineralogy sensitive ice nucleation parameterizations in Dust Regional Atmospheric Model (DREAM), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15857, https://doi.org/10.5194/egusphere-egu2020-15857, 2020.

Cirrus clouds have a net warming effect on climate due to their high altitude and low optical thickness. Small changes in their properties may however shift this to a stronger warming or a cooling. Aerosol particles can strongly affect cirrus cloud properties since they can act as ice nuclei (IN) for the ice crystals. How downwelling sulfate aerosols from the stratosphere affect cirrus clouds is highly unknown but important both in terms of volcanic impact on climate and possible geoengineering through sulfate injections in the stratosphere. In this study we investigate how the microphysical properties of cirrus clouds change with aerosol loading in the lowermost stratosphere (LMS). The study is focused on the midlatitudes where the descending air motion in the stratosphere result in aerosol downwelling from the stratosphere to the troposphere. The study is conducted during 11 years (2006 - 2016) when the stratosphere had varying levels of aerosol load due to volcanic eruptions. 

The cirrus clouds are studied using the satellite dataset DARDAR (raDAR/liDAR) which combines data from the CloudSat radar and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar. Also the aerosol loading in the LMS is retrieved using a satellite dataset, from CALIPSO (Friberg2018). The first results show that the ice water content of the cirrus clouds decrease when the aerosol loading in the LMS increase. This change occur mainly during spring and autumn for homogeneously frozen cirrus clouds. The results regarding the effective radius of the ice crystals are more uncertain but the effective radius also seem to decrease with increased aerosol loading in the LMS. However, this is mainly seen in the northern hemisphere which has experienced the largest changes in aerosol load due to volcanic eruptions during this period. Also data of ice crystal number concentration are being processed and will be studied to better understand the impact on the cirrus clouds from the downwelling stratospheric aerosol.

References

Friberg, J., Martinsson, B. G., Andersson, S. M., and Sandvik, O. S.: Volcanic impact on the climate - The stratospheric aerosol load in the period 2006-2015, Atmospheric Chemistry and Physics, 18, 11 149–11 169, https://doi.org/10.5194/acp-18-11149-2018, 2018.

How to cite: Sporre, M., Friberg, J., Sourdeval, O., Sandvik, O., and Martinsson, B.: Volcanic impact on cirrus clouds, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7996, https://doi.org/10.5194/egusphere-egu2020-7996, 2020.