Ice Multiplication in Polar Mixed-Phase Clouds

Mixed-phase clouds in polar regions play a crucial role in surface ice melting. To accurately predict their radiative impact in climate models, an accurate representation of their microphysical structure is required. However, cloud ice content is generally underpredicted in models when primary ice nucleation is constrained with measurements. Moreover, flight measurements often indicate that the observed Ice Crystal Number Concentrations are order(s) of magnitude larger than the available Ice Nucleation Particles. Ice multiplication has been suggested as a possible cause for this discrepancy, yet the underlying mechanisms and their relative importance remain unknown. In this study we investigate the impact of two ice multiplication mechanisms, rime-splintering and mechanical break-up upon ice-ice collisions, on polar mixed-phase clouds using modeling tools. The sensitivity of these processes to uncertainties in primary ice formation is further examined

Secondary Ice Formation Processes in climate models

Athanasios Nenes, Georgia Sotiropoulou

Mixed-phase clouds in polar regions play a crucial role in surface ice melting. To accurately predict their radiative impact in climate models, an accurate representation of their microphysical structure is required. However, cloud ice content is generally underpredicted in models, when primary ice nucleation is constrained with measurements. Apart from uncertainties in primary ice formation, another possible explanation for this discrepancy is that most models underestimate secondary ice production. In this study we implement missing secondary ice production mechanisms in the Norwegian Earth System Model version 2 and investigate their impact on the representation of Arctic clouds observed at Ny-Alesund.

2021

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system

Athanasios Nenes

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

National Academy of Sciences2016

Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements

Dimitra Mamali, Athanasios Nenes

Aerosols that are efficient ice-nucleating particles (INPs) are crucial for the formation of cloud ice via heterogeneous nucleation in the atmosphere. The distribution of INPs on a large spatial scale and as a function of height determines their impact on clouds and climate. However, in situ measurements of INPs provide sparse coverage over space and time. A promising approach to address this gap is to retrieve INP concentration profiles by combining particle concentration profiles derived by lidar measurements with INP efficiency parameterizations for different freezing mechanisms (immersion freezing, deposition nucleation). Here, we assess the feasibility of this new method for both ground-based and spaceborne lidar measurements, using in situ observations collected with unmanned aerial vehicles (UAVs) and subsequently analyzed with the FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment) INP counter from an experimental campaign at Cyprus in April 2016. Analyzing five case studies we calculated the cloud-relevant particle number concentrations using lidar measurements (n(250,dry) with an uncertainty of 20 % to 40 % and S-dry with an uncertainty of 30 % to 50 %), and we assessed the suitability of the different INP parameterizations with respect to the temperature range and the type of particles considered. Specifically, our analysis suggests that our calculations using the parameterization of Ullrich et al. (2017) (applicable for the temperature range -50 to -33 degrees C) agree within 1 order of magnitude with the in situ observations of n(INp); thus, the parameterization of Ullrich et al. (2017) can efficiently address the deposition nucleation pathway in dust-dominated environments. Additionally, our calculations using the combination of the parameterizations of DeMott et al. (2015, 2010) (applicable for the temperature range -35 to -9 degrees C) agree within 2 orders of magnitude with the in situ observations of INP concentrations (n(INP)) and can thus efficiently address the immersion/condensation pathway of dust and nondust particles. The same conclusion is derived from the compilation of the parameterizations of DeMott et al. (2015) for dust and Ullrich et al. (2017) for soot. Furthermore, we applied this methodology to estimate the INP concentration profiles before and after a cloud formation, indicating the seeding role of the particles and their subsequent impact on cloud formation and characteristics. More synergistic datasets are expected to become available in the future from EARLINET (European Aerosol Research Lidar Network) and in the frame of the European ACTRIS-RI (Aerosols, Clouds, and Trace gases Research Infrastructure). Our analysis shows that the developed techniques, when applied on CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations, are in agreement with the in situ measurements. This study gives us confidence for the production of global 3D products of cloud-relevant particle number concentrations (n(250,dry,) S-dry and n(INP)) using the CALIPSO 13-year dataset. This could provide valuable insight into the global height-resolved distribution of INP concentrations related to mineral dust, as well as possibly other aerosol types.

2019

Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements

Dimitra Mamali, Athanasios Nenes

2019