Aircraft produce contrail in suitable atmospheric conditions, and these may spread out into cirrus. However, it is unclear how large this effect and its implied radiative forcing is. Here we use the opportunity of the COVID-19 related aircraft traffic reduction in boreal spring 2020 in comparison to the traffic in 2019 to assess satellite data. MODIS retrievals are examined for 2020 vs. the climatology 2011 to 2019. In order to account for weather variability, circulation analogues are defined for each region and day of the Spring 2020 period, and the cirrus coverage and emissivity in springtimes 2011 - 2019 is assessed for comparison to 2020. In conclusion, we find that cirrus are reduced by 9±1.5% in absolute terms. This is consistent with a trend analysis. The implied radiative forcing by aviation-induced cirrus is assessed at 49±28 Wm-2. 

How to cite: Quaas, J., Gryspeerdt, E., Vautard, R., and Boucher, O.: Climate impact of aircraft-induced cirrus assessed from satellite observations before and during COVID-19, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14495, https://doi.org/10.5194/egusphere-egu21-14495, 2021.

Besides their strong contribution to weather forecast improvement through data assimilation in clear-sky conditions, thermal infrared sounders on board polar orbiting platforms are now playing a key role in monitoring changes in atmospheric composition. However, it is known that clear sky observations are only a small part of the entire set of measurements, the remaining part is only slightly used as they are contaminated by either aerosols and/or clouds. Moreover, ice or liquid cloud retrieval of column and profile properties from passive and active measurements respectively help us in reaching a better understanding of climate processes. If the information provided by the latter has allowed a significant advance in our knowledge of the vertical distribution of condensed water, it suffers from spatial coverage compared to passive measurements. It is therefore fundamental to better characterize cloud properties from passive measurements by using, for example, high spectral resolution instruments such as IASI and the future IASI-NG.

An information content analysis based on Shannon's formalism has been used to determine the level and the spectral repartition of the information about the ice cloud properties in the IASI and IASI-NG spectra. Based on this analysis, we have developped and tested an algorithm which allows to retrieve from an optimal estimation approach the cloud integrated ice water content together with the cloud layer altitude. We have taken into account the Signal-to-Noise ratio of each specific instrument and the uncertainties due to the non-retrieved atmospheric and surface parameters. The forward model is the fast radiative transfer model RTTOV which has been developped for satellite data assimilation in Numerical Weather Prediction (NWP) models. The ice cloud microphysical model is based on the ensemble model of Baran and Labonnote (2007), where the bulk ice optical properties have been parametrized as a function of the ice water content (expressed in g/m³) and in cloud temperature.

The present study aims to quantify the potential and limits of thermal infrared sounders such as IASI or IASI-NG to retrieve ice cloud properties by using a representative dataset from the global operational short range forecast of the european center of medium-range weather forecast.

How to cite: Leonarski, L., C.-Labonnote, L., Compiègne, M., Vidot, J., Baran, A. J., and Dubuisson, P.: Ice cloud retrieval from high spectral resolution measurements in the thermal infrared : Application to IASI and IASI-NG, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2284, https://doi.org/10.5194/egusphere-egu21-2284, 2021.

Cirrus clouds contribute to the general radiation budget of the Earth, playing an important role in climate projections. Of special interest are optically thin cirrus clouds close to the tropopause due to the fact that they are difficult to capture and thus their impact is not yet well understood. This study presents a characterization of cirrus clouds observed by the limb sounder GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) aboard the German research aircraft HALO during the WISE (Wave-driven ISentropic Exchange) campaign in September/October 2017. This campaign took place in Shannon, Ireland (52.70°N, 8.86°W).  We developed an optimized cloud detection method and derived macro-physical characteristics of the detected cirrus clouds: cloud top height, cloud bottom height, vertical extent and cloud top position with respect to the tropopause. The fraction of cirrus clouds detected above the tropopause (> 0 km) is in the order of 13% to 27%, depending on the detection method and the definition of the tropopause. In general, good agreement with the clouds predicted by the ERA5 reanalysis dataset is obtained. However, cloud occurrence is ≈50% higher in the observations for the region close to and above the tropopause. Cloud bottom heights are also detected above the tropopause. Considering the uncertainties for the tropopause height, cloud top height and cloud bottom height determination we could not find unambiguous evidence for the formation of cirrus layers above the tropopause. In addition, for a better understanding of the tropopause cirrus properties and life conditions, two cirrus cases observed during two scientific flights were selected from  the observations and compared with cirrus simulations performed with the 3D Lagrangian microphysical model  CLaMS-Ice, which is based on the two-moment bulk  cirrus model by Spichtinger and Gierens (2009) (doi: 10.5194/acp-9-685-2009). The model is fed by backward trajectories computed from high resolution ERA5 data (hourly, spatial grid 30 km). This contribution summarizes and extends on work described by Bartolome Garcia et al. (2020) (doi:10.5194/amt-2020-394).

How to cite: Bartolome Garcia, I., Spang, R., Ungermann, J., Griessbach, S., Höpfner, M., Krämer, M., Rolf, C., and Riese, M.: Characterization of Cirrus Clouds in the Mid-Latitude Tropopause Region, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7167, https://doi.org/10.5194/egusphere-egu21-7167, 2021.

Cirrus clouds in the stratosphere (SCCs) regulate the water vapor budget in the stratosphere, impact the stratosphere and tropopshere exchange, and affect the surface energy balance. But the knowledge of its occurrence and formation mechanism is limited, especially in middle and high latitudes. In this study, we aim to assess the occurrence frequencies of SCC over North America based on The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) instrument during the years 2006 to 2018. Possible driving forces such as deep convection are assessed based on Atmospheric Infrared Sounder (AIRS) observations during the same time. 

Results show that at nighttime, SCCs are most frequently observed during the thunderstorm season over the Great Plains from May to August (MJJA) with maximum occurrence frequency of 6.2%. During the months from November to February (NDJF), the highest SCCs occurrence frequencies are 5.5% over the North-Eastern Pacific, western Canada and 4.4% over the western North Atlantic. Occurrence frequencies of deep convection and strong storm systems from AIRS show similar hotspots like the SCCs, with highest occurrence frequencies being observed over the Great Plains in MJJA (4.4%) and over the North-Eastern Pacific, western Canada and the western North Atlantic in NDJF (~2.5%). Both, seasonal patterns and daily time series of SCCs and deep convection show a high degree of spatial and temporal correlation. As further analysis indicates that the maximum fraction of SCCs generated by deep convection is 74% over the Great Plains in MJJA and about 50% over the western North Atlantic, the North-Eastern Pacific and western Canada in NDJF, we conclude that, locally and regionally, deep convection is a leading factor for the formation of SCCs over North America. Other studies stressed the relevance of isentropic transport, double tropopause events, or gravity waves for the formation of SCCs. 

In this study, we also analyzed the impact of gravity waves as a secondary formation mechanism for SCCs, as the Great Plains is a well-known hotspot for stratospheric gravity waves. In case of SCCs that are not directly linked to deep convection, we found that stratospheric gravity wave observations correlate in as much as 30% of the cases over the Great Plains in MJJA, about 50% over the North-Eastern Pacific, western Canada and maximally 90% over eastern Canada and the north-west Atlantic in NDJF. 

Our results provide better understanding of the physical processes and climate variability related to SCCs and will be of interest for modelers as SCC sources such as deep convection and gravity waves are small-scale processes that are difficult to represent in global general circulation models. 

How to cite: Zou, L., Hoffmann, L., Griessbach, S., and Wang, L.: Stratospheric cirrus clouds related to deep convection over North America observed by satellite measurements, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-242, https://doi.org/10.5194/egusphere-egu21-242, 2020.

The role played by tropical storms in the tropical tropopause layer (TTL), the transitional layer regulating the flux into the stratosphere of trace gases affecting radiation and the ozone layer, has been a long-standing open question. Progress has been slow because of computational limitations and challenging conditions for measurements and most numerical studies have used simulations over limited domains whose results must be upscaled to the tropical surface to infer global impacts. We compute the first global observational estimate of the convective ice flux at near tropical tropopause levels by using spaceborne lidar measurements from CALIOP. The calculation uses a method to convert from lidar extinction to sedimenting ice flux and uses error propagation to provide margins of uncertainty. We show that, at any given level in the TTL, the sedimenting ice flux exceeds the inflow of vapor computed from ERA5 reanalysis, revealing additional ice transport and allowing to deduce the advective ice flux as a function of altitude. The contribution to this flux of large-scale motions (resolved by ERA5) is computed and the residual is hypothesized to represent the flux of ice on the convective scale. Results show without ambiguity that the upward ice flux in deep convection dominates moisture transport up to close to the level of the cold point tropopause.

How to cite: Bolot, M. and Fueglistaler, S.: Moisture fluxes in the tropics dominated by deep convection up to near tropical tropopause levels, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3133, https://doi.org/10.5194/egusphere-egu21-3133, 2021.

The challenge of the ice microphysical processes representation in numerical weather models is a well-known phenomenon as it can lead to high uncertainty due to the variety of ice microphysics. As ice microphysical properties can strongly affect the initiation of precipitation as well as the type and amount of it, we need to better understand the complexity of ice processes. To accomplish this, better microphysics information through ice retrievals from measurements is needed. The multi-wavelength radar method is nowadays becoming more and more popular in such microphysics retrievals. Taking advantage of different scattering regimes (Rayleigh or Mie), information about the size of atmospheric hydrometeors can be inferred using different radar bands. For this study, dual-wavelength reflectivity ratio measurements were combined with polarimetric measurements to estimate the size of ice hydrometeors. The measurements were obtained by using the synergy of the C-band POLDIRAD weather radar from the German Aerospace Center, located in Oberpfaffenhofen, and the Ka-band MIRA-35 cloud radar from the Ludwig Maximilian University of Munich. Along with the dual-wavelength dataset, the Differential Reflectivity (Z_DR) from POLDIRAD was used as a polarimetric contribution for the shape estimation of the detected ice particles. The radar observations were compared with T-matrix scattering simulations for the development of a retrieval scheme of ice microphysics. In the course of these studies, different assumptions were considered in the simulations. To capture the size variability, a Gamma particle size distribution (PSD) with different values of median volume diameter (MVD) was used. The soft spheroid approximation was used to approximate the ice particle shapes and to simplify the calculation and variation of their aspect ratios and effective densities. The selection of the most representative mass-size relation was the most crucial for the scattering simulations. In this study, we explored the modified Brown and Francis as well as the aggregates mass-size relation. After comparing the simulations to radar observations, we selected the better fitting one, i.e. aggregates, excluding the Brown and Francis as the simulated particles appeared to be too fluffy. Using the aggregates formulas, Look-Up tables (LUTs) for MVD, aspect ratio, and IWC were developed and used in the ice microphysics retrieval scheme. Here, we present preliminary microphysics retrievals of the median size, shape, and IWC of the detected hydrometeors combining the simulations in LUTs with the radar observations from different precipitation events over the Munich area.

How to cite: Tetoni, E., Ewald, F., Möller, G., Hagen, M., Zinner, T., Mayer, B., Knote, C., and Gross, S.: Advantages and limitations on combining radar dual - wavelength and polarimetric observations for ice microphysics retrievals, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12158, https://doi.org/10.5194/egusphere-egu21-12158, 2021.

The representation of microphysical processes in numerical weather prediction models remains a main source of uncertainty. To tackle this issue, we exploit the synergy of two polarimetric radars to provide novel observations of model microphysics parameterizations. In the framework of the IcePolCKa project (Investigation of the initiation of Convection and the Evolution of Precipitationusing simulatiOns and poLarimetric radar observations at C- and Ka-band) we use these observations to study the initiation of convection as well as the evolution of precipitation. At a distance of 23 km between the C-band PoldiRad radar of the German Aerospace Center (DLR) in Oberpfaffenhofen and the Ka-band Mira35 radar of the Ludwig-Maximilians-University of Munich (LMU), the two radar systems allow targeted observations and coordinated scan patterns. A second C-band radar located in Isen and operated by the German Weather Service (DWD) provides area coverage and larger spatial context. By tracking the precipitation movement, the dual-frequency and polarimetric radar observations allow us to characterize important microphysical parameters, such as predominant hydrometeor class or conversion rates between these classes over a significant fraction of the life time of a convective cell. A WRF (Weather Research and Forecasting Model) simulation setup has been established including a Europe-, a nested Germany- and a nested Munich- domain. The Munich domain covers the overlap area of our two radars Mira35 and Poldirad with a horizontal resolution of 400 m. For each of our measurement days we conduct a WRF hindcast simulation with differing microphysics schemes. To allow for a comparison between model world and observation space, we make use of the radar forward-simulator CR-SIM. The measurements so far include 240 coordinated scans of 36 different convective cells over 10 measurement days between end of April and mid July 2019 as well as 40 days of general dual-frequency volume scans between mid April and early October 2020. The performance of each microphysics scheme is analyzed through a comparison to our radar measurements on a statistical basis over all our measurements.

How to cite: Möller, G., Ewald, F., Groß, S., Hagen, M., Knote, C., Mayer, B., Tetoni, E., and Zinner, T.: The Life-Cycle of Cloud and Precipitation Microphysics in Radar Observation and Numerical Model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15328, https://doi.org/10.5194/egusphere-egu21-15328, 2021.

A specific highlight of the Cirrus Guide II (Krämer et al., 2020, ACP) is the in-situ observation of tropical tropopause layer (TTL) cirrus and humidity in the Asian monsoon anticyclone during the Airborne StratoClim field campaign in 2017, in comparison to observations in the surrounding tropics from the campaigns POSIDON 2016, ATTREX 2014, SCOUT 2005, TROCCINOX 2005, etc. This is of importance, because water vapor is a greenhouse gas that has a significant impact on the surface climate of the Earth, especially in the tropics. The tropics are the main gate for water transport from the upper troposphere to the lower stratosphere, as gaseous component and also as ice particles. Our measurements show that the amount of water injected into the convectively very active Asian monsoon TTL is significantly larger (peak values of N_ice and IWC of 30 cm^-3 and 1000 ppmv are detected around the cold point tropopause, CPT) than in the surrounding calmer tropical regions. Above the CPT, ice particles that are convectively injected might locally add a significant amount of water available for exchange with the stratosphere. We found IWCs of up to 8 ppmv above the Asian monsoon anticyclone in comparison to only 2 ppmv in the surrounding tropics. Also, the highest RH_ice inside of the clouds as well as in clear sky are observed around and above the Asian monsoon CPT. We attribute this to the high amount of H₂O (3–5 ppmv) in comparison to 1.5–3 ppmv in other tropical regions. Outside of the Asian monsoon, in the regions of weak convective activity, the supersaturations above the CPT are 10–20 %, while above the Asian monsoon anticyclone, supersaturations of up to about 50 % has been found. As saturation at the coldest point of an air mass was assumed to be the regulator of water vapor transport to the stratosphere, these supersaturations, especially above the Asian monsoon anticyclone CPT, suggest that the water exchange with the stratosphere is higher than expected.

How to cite: Krämer, M. and the Cirrus Guide II team: Tropical tropopause layer (TTL) cirrus and humidity in the Asian monsoon anticyclone and the surrounding tropics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12052, https://doi.org/10.5194/egusphere-egu21-12052, 2021.

A nascent in situ cirrus was observed on 11 January 2019 in the tropical tropopause layer (TTL) over the southwestern Indian Ocean, with the use of balloon-borne instruments. Data from CFH (Cryogenic Frost Point Hygrometer) and COBALD (Compact Optical Backscatter and AerosoL Detector) instruments were used to characterize the cirrus and its environment. Optical modeling was employed to estimate the cirrus microphysical
properties from the COBALD backscatter measurements. Newly-formed ice crystals with radius <1 μm and concentration ∼500 L ⁻¹ were reported at the tropopause. The relatively low concentration and CFH ice supersaturation (1.5) suggests a homogeneous freezing event stalled by a high-frequency gravity wave. The observed vertical wind speed and temperature anomalies that triggered the cirrus formation were due to a 1.5-km vertical-
scale wave, as shown by a spectral analysis. This cirrus observation shortly after nucleation is beyond remote sensing capabilities and presents a type of cirrus never reported before.

How to cite: Evan, S., Reinares Martinez, I., Wienhold, F. G., Brioude, J., Jensen, E. J., Thornberry, T. D., Heron, D., Verreyken, B., Korner, S., Vomel, H., Metzger, J.-M., and Posny, F.: Evidence of in Situ Cirrus Formation in the Tropical Tropopause Layer over the Southwestern Indian Ocean , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14156, https://doi.org/10.5194/egusphere-egu21-14156, 2021.

Cirrus clouds have widespread coverage over Earth's surface area. Cirrus cloud radiative forcings are directly affected by the microphysical properties of cirrus clouds, including ice water content (IWC), ice crystal number concentration (Nice), and mean diameter (Dice). In this work, in-situ observations obtained from seven flight campaigns funded by the U.S. National Science Foundation are used to examine key factors controlling the formation and evolution of cirrus clouds. These key factors include thermodynamic conditions (i.e., temperature and relative humidity), dynamic conditions (i.e., vertical velocity), and aerosol indirect effects from larger and smaller aerosols (> 500 nm and > 100 nm, respectively). After isolating the effects from thermodynamic and dynamic conditions, we found that when aerosol number concentrations (Na₅₀₀ and Na₁₀₀) increase, IWC, Nice and Dice all increase. In particular, IWC and Nice increase significantly when Na is about 3 – 10 times larger than the average Na conditions (Patnaude and Diao, GRL, 2020).

Simulations of cirrus clouds by a global climate model – the U.S. National Center for Atmospheric Research (NCAR) Community Atmosphere Model version 6 (CAM6) are evaluated against in-situ observations (Patnaude, Diao, Liu and Chu, ACP, accepted). Observations show higher Nice in the northern hemisphere (NH) midlatitude than southern hemisphere (SH) midlatitude. CAM6 simulations show “too many” and “too small” ice crystals in most of the regions except NH midlatitude, where simulations show lower Nice than the observations. Weaker aerosol indirect effects on cirrus clouds are also seen in the simulations compared with observations.

How to cite: Diao, M., Patnaude, R., Liu, X., and Chu, S.: Global-scale Aircraft Observations and Simulations of Cirrus Clouds and Aerosol Indirect Effects, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-420, https://doi.org/10.5194/egusphere-egu21-420, 2021.

We present and discuss the comparison between particle depolarization measurement observed in-situ by a backscattersonde (MAS) and particle asphericity measured by an optical particle counter and sizer with detector for particle asphericity (NIXE-CAPS), in high altitude clouds.

To our knowledge, this is the first time the in situ measurements of particle asphericity are directly compared with particle depolarization, an optical parameter usually accessible in remote sensing.

The two instruments flew together on the high altitude research aircraft M55 Geophysica, during the STRATOCLIM campaing in 2017, over Nepal. Particle asphericiy and depolarization measured in cirrus clouds will be compared and their dependence on the particle size distribution parameters will be studied. While relationships have been found between depolarization, asphericity and some microphysical parameters of the particle size distribution, quantitative correlations between asphericity and depolarization do not appear. We will discuss possible explanations for this apparent lack of quantitative correlation.

How to cite: Lucaferri, L., Di Liberto, L., Snels, M., Afchine, A., Kraemer, M., and Cairo, F.: A comparison of lidar depolarization and particle asphericity in high altitude clouds, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15971, https://doi.org/10.5194/egusphere-egu21-15971, 2021.

Clouds are an important contributor to the uncertainty of future climate predictions, partly because cloud microphysical processes are still not fully understood. Interhemispheric observations, providing a dataset to investigate these cloud microphysical processes, are surprisingly rare - in particular observations using the same instrumentation on a global scale.

Between 2016 and 2018, the ATom (Atmospheric Tomography; 2016-2018) mission and the A-LIFE (Absorbing aerosol layers in a changing climate: aging, lifetime and dynamics; 2017) field experiment performed extensive airborne in-situ measurements of aerosol and cloud microphysical properties in the atmosphere up to approx. 13km altitude on a global scale. Profiling of the remote atmosphere over the Pacific and Atlantic Oceans from about 80°N to 86°S during ATom and systematic sampling of the region in the Mediterranean during A-LIFE provides a combined dataset of nearly 60h of measurements inside clouds.

We developed a novel cloudindicator algorithm, which utilizes measurements of a second-generation Cloud, Aerosol and Precipitation Spectrometer (CAPS, Droplet Measurement Technologies), relative humidity and temperature. It automatically detects clouds and classifies them according to their cloud phase.

In this study we present the novel cloudindicator algorithm and the combined dataset of ATom and A-LIFE global scale in-situ cloud observations. Furthermore, we show results of the cloud phase analysis of the extensive dataset.

How to cite: Dollner, M., Gasteiger, J., Schöberl, M., Diskin, G., Bui, T. P., Brock, C. A., and Weinzierl, B.: Global in-situ cloud phase observations during the airborne Atmospheric Tomography mission and A-LIFE field experiment, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9595, https://doi.org/10.5194/egusphere-egu21-9595, 2021.

Accurately representing ice clouds in radiative transfer models is extremely challenging due to the high diversity of the shapes and habits of ice crystals found in these clouds. In addition, the impact of cloud conditions on microphysical processes and resulting crystal morphologies cannot be studied without having reliable measurements on the relative proportion of crystal habits inside a cloud. Although airborne optical array probes have existed for decades to address these issues, our ability to extract meaningful information out of the images produced by these probes has been limited because we were missing automatic, unbiased and reliable classification tools. Many attempts have been made, starting in the 1980s (Rahman et al. (1981) and Duroure (1982)) with feature-based decision trees. At the time, image recognition was only starting to take shape as a field of computer science and computational power was still a limiting factor. With the recent uprising of computer vision (Krizhevsky et al. (2017)), it is now possible to reproduce the human ability to identify complex objects without creating huge sets of parameters around specific data sets and trying to minimize inter-class variability and maximize intra-class variabilities, as has been recently documented in Praz et al. (2018). However, we believe that this leads inevitably to large bias and uncertainties when applied to actual data. In the presented study, a methodology for automatic ice crystal recognition using innovative machine learning was developed for the PIP instrument (and is currently under development for the 2DS). 6 classes have been defined specifically for the PIP to account for the 3 ice crystal formation processes (vapor deposition, riming and aggregation) for particles of max diameter above 2mm. More than 3000 images were used along with some data augmentation to provide a diverse and solid database that includes various types of aggregates found in Mesoscale Convective Systems (MCS) which will be a major focus in our future applications of this classification tool. In contrast, to the work of Xiao et al. (2019) we included classes such as fragile aggregates or rimed aggregates with high intra-class diversity in their shapes. Convolutional Neural Network (CNN) has been chosen as the method to achieve the best results together with the use of finely tuned dropout layers which guarantee higher quality in the classification results by creating multiple confirmation paths for a single habit. The network has been tested through random inspections on actual data, part of which was then assimilated in order to improve intra-class variability and reduce confusion. It showed accuracy above 93% on an independent test set with most of its confusions being explained by the assumed porosity/transition between certain classes for instance between rimed aggregates and fragile aggregates. We believe once this tool is ready for other airborne optical array probes, it will be able to foster an improved insight in ice clouds microphysical processes.

How to cite: Jaffeux, L.: Automatic classification tool for Ice crystal images from Optical Array Probe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8612, https://doi.org/10.5194/egusphere-egu21-8612, 2021.

Crystal habits encode atmospheric conditions. Temperature and relative humidity with respect to ice and liquid water are the microphysical drivers of the growth of snow crystals in terms of shape, size and degree of riming, while cloud thickness and the related growth time of crystals are the dynamical drivers. According to current versions of Nakaya’s habit diagram, rather large and eventually rimed crystals are formed above supersaturation. Below supersaturation compact and unrimed snow crystals are to be expected. In this study, we combine radiosonde profiles with snowflake images captured at the surface by a multi-angle snowflake camera during two-and-a-half winter seasons in Northern Finland (67.367 °N, 26.629 °E). Our objective is to quantify how well crystal habits correspond with what would be expected from radiosonde profiles at this continental site in the Arctic.

How to cite: Mignani, C., Zimmermann, L., Kivi, R., Berne, A., and Conen, F.: Matching crystal habits and radiosonde profiles in Northern Finland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16007, https://doi.org/10.5194/egusphere-egu21-16007, 2021.

We use aircraft observation data to investigate the microphysical characters of wintertime mixed-phase clouds in North China, including the cloud particle number concentration (N_c), the liquid water content (LWC), the ice particle number concentration (N_i), the ice water content (IWC), the particle spectrum distributions (PSDs) and the effective diameter (D_e). For wintertime mixed-phase clouds, the average N_c and N_i were 170±154 cm^-3 and 26±39 L^-1, respectively; the average LWC and IWC were 0.05±0.06 and 0.07±0.09g/m³, respectively; the D_e for cloud particles was 10±4 μm. When compared to the results from other regions, including East Europe, North America, Southern Ocean and Tibetan Plateau, we found that the wintertime mixed-phase cloud in North China has larger N_c, smaller LWC, IWC and D_e, and narrower PSDs. The main reason might be the larger aerosol loading and smaller water content in the atmosphere in winter in North China. With increasing temperature, N_c and LWC increased, but N_i and D_e decreased. The dominate physical processes in wintertime mixed-phase cloud were aggregation process and riming process. As the temperature increased, the peak concentration of ice PSD decreased, but N_i increased and the ice PSD became wider, indicating more ice crystals and the ice crystals became larger at higher temperature. With temperature increasing, the ice habit also changed, and the amount of plates, irregular crystals and their aggregates increased. What’s more, with the existence of larger LWC at higher temperature, the ice crystals gradually tightened and their surface became more complicated as well. Therefore, both aggregation process and riming process were more active at higher temperature, but riming process changed much more. This work fills the gap in the observation of wintertime mixed-phase clouds in north China, and the results suggest that the wintertime mixed-phase clouds have some unique microphysical characters.

How to cite: Wu, X., Wang, M., Rosenfeld, D., Zhao, D., and Ding, D.: The microphysical characters of wintertime mixed-phase clouds in North China., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3691, https://doi.org/10.5194/egusphere-egu21-3691, 2021.

The proper representation of Arctic mixed-phased clouds remains a challenge in both weather forecast and climate models. Amongst the contributing factors is the complexity of turbulent properties of clouds. While the effect of evaporating hydrometeors on turbulent properties of the boundary layer has been identified in other latitudes, the extent of similar studies in the Arctic has been so far limited.

Our study focus on the impact of heat release from mixed-phase microphysical processes on the turbulent properties of the convective low-level clouds in the Arctic. We  employ high-resolution simulations, properly constrained by relevant measurements.
Semi-idealised model cases are based on convective clouds observed during the recent campaign in the Arctic: ACLOUD, which took place May--June 2017 over Fram Strait. The simulations are performed in Dutch Atmospheric Large Eddy Simulation (DALES) with double-moment mixed-phase microphysics scheme of Seifert & Beheng.

The results indicate an enhancement of boundary layer turbulence is some convective regimes.
Furthermore, results are sensitive to aerosols concentrations. Additional implications for the role of mixed-phase clouds in the Arctic Amplification will be discussed.

How to cite: Chylik, J. and Neggers, R.: The Impact of Mixed-Phase Microphysical Processes on the Turbulence in Low-level Clouds in the Arctic, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13693, https://doi.org/10.5194/egusphere-egu21-13693, 2021.

During the campaigns CyCyare (Limassol, Cyprus) and DACAPO-PESO (Punta Arenas, Chile), remote sensing methods were applied to study mixed-phase clouds. The two sites show contrasting aerosol loads with very clean, marine atmosphere over southern Chile and higher aerosol mass and number concentrations over Cyprus, which frequently are dust-laden. The observations suggest differing cloud properties. To further study the properties and evolution of the observed clouds as well as their relation to the ambient aerosol, the detailed coupled cloud microphysical model COSMO-SPECS is applied for selected real case studies.

The SPECtral bin cloud microphysicS model SPECS was developed to simulate cloud processes using fixed-bin size distributions of aerosol particles and of liquid and frozen hydrometeors. It was implemented in the numerical weather prediction model COSMO. COSMO-SPECS has been used for idealized case studies with horizontally periodic boundary conditions. Recently, the model system has been enhanced by considering lateral boundary conditions for the hydrometeor spectra allowing for high-resolution real case studies on nested domains. The simulations are carried out by first applying the meteorological driver COSMO using its standard two-moment microphysics scheme on multiple nests with increasing horizontal resolution. Finally, the COSMO-SPECS model system is applied on the innermost domain with a horizontal resolution of a few hundred meters using boundary data derived from the finest driving COSMO domain. For this purpose, the bulk hydrometeor fields of the driving model need to be translated into the corresponding hydrometeor mass and number distributions of SPECS’ hydrometeor spectra.

In this work, we present first results for selected case-studies of mixed-phase clouds observed during CyCyare and DACAPO-PESO. The results of the model simulations are compared against the LIDAR and cloud radar observations at the two sites.

How to cite: Schrödner, R., Bühl, J., Senf, F., Knoth, O., Stoll, J., Simmel, M., and Tegen, I.: Application of COSMO-SPECS for remote sensing observations of mixed-phase clouds during CyCare and DACAPO-PESO, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14558, https://doi.org/10.5194/egusphere-egu21-14558, 2021.

Recent studies have shown that primary marine organics which are emitted as sea spray aerosol can be the main driver of ice nucleation in remote boundary layer clouds. Here we examine this by using a state-of-the-art large eddy simulator UCLALES-SALSA. The model describes aerosol, cloud and ice size distributions and chemical compositions using several dry size bins. This allowed the implementation of prognostic ice nucleation approach where cloud droplet freezing rate is calculated based on ambient conditions and chemical composition of the droplets. Specifically, ice nucleating particles (INPs) for the immersion freezing mode can be identified and tracked by the insoluble compounds they contain.

Development of mixed-phase clouds is sensitive to INP concentration, which depends on the balance between sources (free troposphere and marine emissions), sinks (removal with precipitation) and vertical transport. Simulations show that turbulent vertical transport of marine INPs is efficient when the boundary layer is coupled. On the other hand, almost constant boundary layer height means limited import of background INPs from the free troposphere. For the simulated cases, most INPs originate from the sea surface rather than free troposphere. Typically cloud droplet freezing starts at the very top of updrafts. First these newly formed ice crystals grow with the expense of cloud droplets, but soon precipitation and downdrafts redistribute ice more evenly. The largest ice particles can fall though the sublimation region, which means that these INPs are permanently removed with precipitation. Smaller particles are released back to aerosol when the ice has sublimated, and those particles can act as INP in the following updrafts. In general, our simulations show that marine aerosol emissions can be efficiently mixed and re-circulated within the boundary layer while free troposphere can be isolated from the clouds.

How to cite: Raatikainen, T., Prank, M., Ahola, J., Tonttila, J., Kokkola, H., and Romakkaniemi, S.: Modelling the effects of primary marine organic aerosol on mixed-phase clouds, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8694, https://doi.org/10.5194/egusphere-egu21-8694, 2021.

Sea spray emissions are an important source for ice nucleating particles (INPs) over remote ocean regions. Over the past years, our understanding of marine organic surfactants acting as INPs has advanced a lot. However, there are still significant knowledge gaps regarding the role of larger marine biogenic particles (e.g. polymers, diatom fragments, protists and bacteria) which are potentially the drivers of episodically observed high INP concentrations.
In this study, we use a combination of ARM (Atmospheric Radiation Measurement) observations and output from E3SM (Energy Exascale Earth System Model) simulation runs to investigate the impact of larger marine biogenic particles acting as INPs. We use heterotrophic bacteria and nanogels (polymeric particles) as two hypothesized classes of marine INPs which can get transported across the sea-air interface. Based on the offline-calculated concentrations of these ice nucleating entities in the ocean surface layer, we conduct sensitivity studies to estimate INP concentration ranges, relying on current knowledge of enrichment factors and ice nucleation activities (e.g., n_s values from McCluskey et al. (2018)). In comparison to observations of episodic high INP concentrations, our estimated concentrations are consistently lower. However, one of the main conclusions of our study is that large uncertainties regarding the links between ocean biology, organic matter in sea spray and ice nucleation properties, remain. Therefore, comprehensive observational datasets, including sea spray size distributions, aerosol and INP compositions, and ice nucleation efficiencies of individual marine species, are needed. 

How to cite: Steinke, I., DeMott, P., Deane, G., Hill, T., Maltrud, M., Raman, A., and Burrows, S. M.: Challenges in constructing a source function for high-temperature marine INPs, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10410, https://doi.org/10.5194/egusphere-egu21-10410, 2021.

Homogeneous nucleation of ice crystals via freezing of small supercooled solution particles represents a major pathway in the formation of cirrus clouds with high ice water content at low temperatures. A reasonable physical explanation of this type of freezing is provided by Koop's nucleation theory, relating the homogeneous nucleation rate to the water activity of the solution particles. While the homogeneous nucleation rate encodes the probability of freezing of solution particles, the water activity represents the ratio of water vapor saturation pressures over the solution to that over pure water in Koop's portrayal.

By using the ice microphysics model "CLaMS-Ice", we investigate the effect of various formulations of the water activity and the water vapor saturation pressure on the resulting cirrus clouds. Although CLaMS-Ice is a two-moment bulk model, it implements a comparatively detailed ice microphysics formulated by Spichtinger and Gierens. Such a microphysics scheme is suitable to be implemented in full three dimensional atmospheric models in contrast to even more detailed bin microphysics schemes.

We performed sensitivity simulations over a wide range of temperatures and vertical velocities by using two different direct parameterizations of water activity based on thermodynamic models in addition to the one used by Koop. Also, three different formulations of the water vapor saturation pressure are applied in the simulations. The results are evaluated regarding the predicted number of ice crystals and the ice onset humidities. In particular, one major finding is that the freezing thresholds are increased compared to Koop's freezing lines.

How to cite: Baumgartner, M., Krämer, M., and Rolf, C.: How does a Homogeneous Nucleation Event respond to changes of Parameterizations of Water Activity and Saturation Vapor Pressure?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-654, https://doi.org/10.5194/egusphere-egu21-654, 2021.

Mineral dust particles in the atmosphere have a large influence on the physical properties of clouds and their lifecycle. Findings from field experiments, modeling, and laboratory studies suggest that mineral dust particles are very efficient ice-nucleating particles (INPs) even in regions distant from the desert sources. The major sources of mineral dust present in the Mediterranean basin are located in the Sahara Desert. Understanding the significance of mineral dust in ice initiation led to the development of INPC parameterizations in presence of dust for immersion freezing and deposition nucleation processes. These parameterizations were mineralogically indifferent, estimating the dust ice nucleating particle concentrations (INPCs) based on dust concentration and thermodynamic parameters. In recent studies, feldspar and quartz minerals have shown to be significantly more efficient INPs than other minerals found in dust. These findings led to the development of mineralogy-sensitive immersion freezing parameterizations. In this study, we implement mineralogy-sensitive and mineralogically-indifferent INPC parameterizations into a regional coupled atmosphere-dust numerical model. We use the Dust Regional Atmospheric Model (DREAM) to perform one month of simulations of the atmospheric cycle of dust and its feldspar and quartz fractions during Saharan dust intrusion events in the Mediterranean. EARLINET (European Aerosol Lidar Network) and AERONET (AErosol RObotic NETwork) measurements are used with POLIPHON algorithm (Polarization Lidar Photometer Networking) to derive cloud-relevant dust concentration profiles. We compare DREAM results with lidar-based vertical profiles of dust mass concentration, surface area concentration, number concentration, and INPCs. This analysis is a step towards the systematic analysis of dust concentration and INPC parameterizations performance when compared to lidar derived vertical profiles.

How to cite: Ilić, L., Marinou, E., Jovanović, A., Kuzmanoski, M., and Ničković, S.: Ice nucleating particle concentrations in Dust Regional Atmospheric Model (DREAM) – going one step further, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7754, https://doi.org/10.5194/egusphere-egu21-7754, 2021.

Aerosol-cloud interactions are an important source of uncertainty in current climate models. In particular, the role of mineral dust and soot particles in cloud glaciation is poorly understood. This lack of understanding leads to high uncertainty in climate predictions.

To estimate the global co-variability between mineral dust aerosol and cloud glaciation, we combined an aerosol model reanalysis with satellite retrievals of cloud thermodynamic phase. Our results confirmed that the cloud thermodynamic phase increases with higher mineral dust concentrations.

To better understand and quantify the impact of ice-nucleating particles on cloud glaciation, it is crucial to have a reliable estimation of the hemispheric and seasonal contrast in cloud top phase, which is believed to result from the higher dust aerosol loading in boreal spring. For this reason, we locate and quantify these contrasts by combining three different A-Train cloud-phase products for the period 2007-2010. These products rely on a spaceborne lidar, a lidar-radar synergy, and a radiometer-polarimeter synergy. We used these observations to constrain the droplet freezing in the ECHAM-HAM climate model. After tuning, the model leads to more realistic cloud-top-phase contrasts and a dust-driven glaciation effect of 0.14 ± 0.13 Wm−2 between 30–60°N. Our results show that using observations of cloud-top phase contrasts provide a strong constraint for ice formation in mixed-phase clouds and a weak constraint for the associated impact on radiation and precipitation.

Besides mineral dust, it has been under debate whether black carbon also contributes to cloud glaciation. Therefore, we studied the cloud top phase retrieved by CALIOP during the Australian wildfires in 2020. After repeating the tuning strategy for black carbon, we were able to replicate the increase in ice cloud frequency observed during the wildfires.

How to cite: Villanueva, D.: Constraining ice nuclei freezing efficiency using cloud phase observations together with climate models., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8478, https://doi.org/10.5194/egusphere-egu21-8478, 2021.