The Relationship between Clouds Containing Multiple Layers 7.5–30 m Thick and Surface Weather Conditions

Previous studies have identified finely laminated, or layered, features within Arctic clouds. This study focuses on quasi-horizontal layers that are 7.5 to 30 m thick, within clouds from 0 to 5 km altitude. No pre-selection for any particular cloud types was made prior to the identification of laminations. We capitalize on the 4-year measurement record available from Eureka, Nunavut (79.6∘ N, 85.6∘ W), using the Canadian Network for the Detection of Atmospheric Composition Change (CANDAC) Rayleigh–Mie–Raman Lidar (CRL; 1 min, 7.5 m resolution). Laminated features are identified on 18% of all days, from 2016–2019. Their presence is conclusively excluded on 12% of days. March, April, and May have a higher measurement cadence and show laminations on 41% of days. Individual months show laminations on up to 50% of days. Our results suggest that laminations are not rare phenomena at Eureka. To determine laminations’ likely contribution to Arctic weather and climate, local weather reports were obtained from the nearby Environment and Climate Change Canada (ECCC) weather station. Days with laminated clouds are strongly correlated with precipitating snow (r = 0.63), while days with non-laminated clouds (r = −0.40) and clear sky days (r = −0.43) are moderately anti-correlated with snow precipitation.

Stability dependent increases in liquid water with droplet number in the Arctic

The effects of aerosols on cloud microphysical properties are a large source of uncertainty when assessing anthropogenic climate change. The aerosol-cloud relationship is particularly unclear in high-latitude polar regions due to a limited number of observations. Cloud liquid water path (LWP) is an important control on cloud radiative properties, particularly in the Arctic, where clouds play a central role in the surface energy budget. Therefore, understanding how aerosols may alter cloud LWP is important, especially as aerosol sources such as industry and shipping move further north in a warming Arctic. Using satellite data, this work investigates the effects of aerosols on liquid Arctic clouds over open ocean by considering the relationship between cloud droplet number concentration (Nd) and LWP, an important component of the aerosol-LWP relationship. The LWP response to Nd varies significantly across the region, with increases in LWP with Nd observed at very high latitudes in multiple satellite datasets, with this positive signal observed most strongly during the summer months. This result is in contrast to the negative response typically seen in global satellite studies and previous work on Arctic clouds showing little LWP response to aerosols. The lower tropospheric stability (LTS) was found to be the driving force behind the spatial variations in LWP response, strongly influencing the sign and magnitude of the Nd-LWP relationship, with increases in LWP in high stability environments. The influence of humidity varied depending on the stability, with little impact at low LTS but a strong influence at high. The background Nd state does not seem to dominate the LWP response, despite the non-linearities in the relationship. As the LTS is projected to decrease in a future, warmer Arctic, these results show that increases may produce lower cloud water paths, offsetting their shortwave cooling effect.

Ship-based estimates of momentum transfer coefficient over sea ice and recommendations for its parameterization

A major source of uncertainty in both climate projections and seasonal forecasting of sea ice is inadequate representation of surface–atmosphere exchange processes. The observations needed to improve understanding and reduce uncertainty in surface exchange parameterizations are challenging to make and rare. Here we present a large dataset of ship-based measurements of surface momentum exchange (surface drag) in the vicinity of sea ice from the Arctic Clouds in Summer Experiment (ACSE) in July–October 2014, and the Arctic Ocean 2016 experiment (AO2016) in August–September 2016. The combined dataset provides an extensive record of momentum flux over a wide range of surface conditions spanning the late summer melt and early autumn freeze-up periods, and a wide range of atmospheric stabilities. Surface exchange coefficients are estimated from in situ eddy covariance measurements. The local sea-ice fraction is determined via automated processing of imagery from ship-mounted cameras. The surface drag coefficient, CD10n, peaks at local ice fractions of 0.6–0.8, consistent with both recent aircraft-based observations and theory. Two state-of-the-art parameterizations have been tuned to our observations with both providing excellent fits to the measurements.

Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System

By synthesising remote-sensing measurements made in the central Arctic into a model-gridded Cloudnet cloud product, we evaluate how well the Met Office Unified Model (UM) and European Centre for Medium-Range Weather Forecasting Integrated Forecasting System (IFS) capture Arctic clouds and their associated interactions with the surface energy balance and the thermodynamic structure of the lower troposphere. This evaluation was conducted using a four-week observation period from the Arctic Ocean 2018 expedition, where the transition from sea ice melting to freezing conditions was measured. Three different cloud schemes were tested within a nested limited area model (LAM) configuration of the UM – two regionally-operational single-moment schemes (UM_RA2M and UM_RA2T), and one novel double-moment scheme (UM_CASIM-100) – while one global simulation was conducted with the IFS, utilising its default cloud scheme (ECMWF_IFS). Consistent weaknesses were identified across both models, with both the UM and IFS overestimating cloud occurrence below 3 km. This overestimation was also consistent across the three cloud configurations used within the UM framework, with > 90 % mean cloud occurrence simulated between 0.15 and 1 km in all model simulations. However, the cloud microphysical structure, on average, was modelled reasonably well in each simulation, with the cloud liquid water content (LWC) and ice water content (IWC) comparing well with observations over much of the vertical profile. The key microphysical discrepancy between the models and observations was in the LWC between 1 and 3 km, where most simulations (all except UM_RA2T) overestimated the observed LWC. Despite this reasonable performance in cloud physical structure, both models failed to adequately capture cloud-free episodes: this consistency in cloud cover likely contributes to the ever-present near-surface temperature bias simulated in every simulation. Both models also consistently exhibited temperature and moisture biases below 3 km, with particularly strong cold biases coinciding with the overabundant modelled cloud layers. These biases are likely due to too much cloud top radiative cooling from these persistent modelled cloud layers and were interestingly consistent across the three UM configurations tested, despite differences in their parameterisations of cloud on a sub-grid-scale. Alarmingly, our findings suggest that these biases in the regional model were inherited from the driving model, thus triggering too much cloud formation within the lower troposphere. Using representative cloud condensation nuclei concentrations in our double-moment UM configuration, while improving cloud microphysical structure, does little to alleviate these biases; therefore, no matter how comprehensive we make the cloud physics in the nested LAM configuration used here, its cloud and thermodynamic structure will continue to be overwhelmingly biased by the meteorological conditions of its driving model.

Year-long observations of chemical properties of organic aerosols and cloud residuals at the Zeppelin Observatory, Svalbard

<p>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.</p><p>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.</p><p>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.</p>

Secondary ice production in NorESM2 climate model: quantifying the impact on Arctic clouds

<p>Arctic clouds are among the largest sources of uncertainty in predictions of Arctic weather and climate. This is mainly due to errors in the representation of the cloud thermodynamic phase and the associated radiative impacts, which largely depends on the parameterization of cloud microphysical processes. Secondary ice processes (SIP) are among the microphysical processes that are poorly represented, or completely absent, in climate models. In most models, including the Norwegian Earth System Model -version 2 (NorESM2), Hallet-Mossop (H-M) is the only SIP mechanism available. In this study we further improve the description of H-M and include two additional SIP mechanisms (collisional break-up and drop-shattering) in NorESM2. Our results indicate that these additions improve the agreement between observed and modeled ice crystal number concentrations and liquid water path in mixed-phase clouds observed at Ny-Alesund in 2016-2017. We then conclude by quantifying the impact of these overlooked SIP mechanisms for cloud microphysical characteristics, properties and the radiative balance throughout the Arctic.</p><p> </p>

Airborne in-situ observations of Arctic clouds in spring and summer above sea ice and the open ocean

<p>Two airborne campaigns (AFLUX and MOSAiC-ACA) were conducted in spring 2019 and late summer 2020 to investigate low- and midlevel clouds and related atmospheric parameters in the central Arctic. The measurements aim at better understanding the role of Arctic clouds and their interactions with the surface - open ocean or sea ice - in light of amplified climate change in the Arctic.<br>During the campaigns the Basler BT-67 research aircraft Polar 5 based in Svalbard (78.24 N, 15.49 E) equipped with a comprehensive in-situ cloud payload performed in total 24 flights over the Arctic ocean and in the Fram Strait. A combination of size spectrometers (CDP and CAS) and 2-dimensional imaging probes (CIP and PIP) covering the size range of Arctic cloud hydrometeors from 0.5µm to 6.2mm measured the total particle number concentration, the particle size distribution and the median volume diameter. Liquid water content and ice water content were measured with the Nevzorov bulk probe. The cloud water content (liquid and ice water content) from the Nevzorov probe is compared to the cloud water content derived from particle size measurements using consistent mass-dimension relationships.<br>Here we give an overview of the microphysical cloud properties measured in spring and late summer in high northern latitudes at altitudes up to 4 km. We derive the temperature and altitude dependence of liquid, mixed phase and ice cloud properties and investigate their seasonal variability. Differences in cloud properties above the sea ice and the open ocean are examined, supporting the hypothesis of an enhanced median volume diameter over open ocean compared to clouds formed over the sea ice. The comprehensive data set on microphysical cloud properties enhances our understanding of cloud formation and mixed phase cloud processes over the Arctic ocean, it can be used to validate remote sensing retrievals and models and helps to assess the role of clouds for stronger impact of climate change in the Arctic. </p>