Is the high N_d of springtime Arctic water clouds an indication of ice algae – aerosol – cloud – Arctic melting feedback?
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clouds↗
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Is the High Droplet Number Density of Late Spring Arctic Water Clouds an Indication of Snow/Ice Algae – Cloud – Arctic Melting Feedback?
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Yongxiang Hu↗
Investigation of Arctic Cloud Properties and Surface Radiation Based on MOSAiC Shipborne Observations
The Arctic is rapidly changing due to changes of the Earth system. This study investigates cloud fraction, phase partition, cloud type, and their relationships with surface radiation based on yearlong shipborne observations in the Arctic regions. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign provided lidar and radar observations of cloud microphysical properties and surface shortwave (SW) and longwave (LW) radiation. Cloud and radiative properties were examined at daily and monthly resolutions in four seasons. Low clouds were found to be most prevalent throughout the year, followed by deep clouds. The ice phase is the dominant phase except for summer (June–August). Liquid and mixed phases show more significant monthly and annual mean radiative effects in SW and LW than the ice phase. The clouds show net warming effects due to LW heating in most months, while the SW cooling effects of clouds become more dominant for July and August. The cloud and radiation observations from MOSAiC were used to evaluate simulations of the atmospheric component of the Energy Exascale Earth System Model version 2. The simulations show large overestimations of the liquid and mixed phases in the Arctic regions from February to September. The simulations also underestimate the percentages of low clouds and overestimate the percentages of deep clouds throughout the year. Altogether, this work provides a unique analysis of cloud and radiation properties based on high-resolution shipborne observations, which can be used to assist future model evaluation and development.
58 GEOSCIENCES↗
The Mixed-Phase Arctic Cloud Experiment (M-PACE)
The Mixed-Phase Arctic Cloud Experiment (M-PACE) was conducted September 27 through October 22, 2004 on the North Slope of Alaska. The primary objective was to collect a data set suitable to study interactions between microphysics, dynamics and radiative transfer in mixed-phase Arctic clouds. Observations taken during the 1997/1998 Surface Heat and Energy Budget of the Arctic (SHEBA) experiment revealed that Arctic clouds frequently consist of one (or more) liquid layers precipitating ice. M-PACE sought to investigate the physical processes of these clouds utilizing two aircraft (an in situ aircraft to characterize the microphysical properties of the clouds and a remote sensing aircraft to constraint the upwelling radiation) over the Department of Energy s Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) on the North Slope of Alaska. The measurements successfully documented the microphysical structure of Arctic mixed-phase clouds, with multiple in situ profiles collected in both single-layer and multi-layer clouds over two ground-based remote sensing sites. Liquid was found in clouds with temperatures down to -30 C, the coldest cloud top temperature below -40 C sampled by the aircraft. Remote sensing instruments suggest that ice was present in low concentrations, mostly concentrated in precipitation shafts, although there are indications of light ice precipitation present below the optically thick single-layer clouds. The prevalence of liquid down to these low temperatures could potentially be explained by the relatively low measured ice nuclei concentrations.
Verlinde, J.↗
Arctic Cloud Radiative Forcing in Contemporary Atmospheric Reanalyses
Arctic clouds play an important role in modifying the surface energy balance. In the Arctic, clouds are thought to influence the underlying sea ice cover through changing downwelling longwave radiative fluxes to the surface and through the selective reflection of the shortwave flux in summer. Atmospheric reanalyses are generally thought to have a poor representation of cloud processes at high latitudes, although the representation of trends over the perennial Arctic sea ice pack is less well known. Here, atmospheric energy fluxes are examined at the top of the atmosphere from contemporary reanalyses in comparison to satellite measurements from the CERES-EBAF version 4.1 product. The principal reanalyses examined are the NASA MERRA-2, the ECMWF ERA5 and ERA-Interim, the JRA-55, and the regional Arctic System Reanalysis version 2. In agreement with previous observation-based studies, changes with time in the shortwave cloud radiative forcing in reanalyses are found to be negligible despite strong trends in the absorbed shortwave. Over the full satellite period, there is large disagreement in the seasonality of longwave cloud forcing trends. These trends are reduced during the CERES-EBAF observing period (2003-present). An examination of these trends with respect to sea ice cover changes in each of the reanalyses is conducted.
Cullather, Richard I.↗
FIRE Arctic Clouds Experiment
An overview is given of the First ISCCP Regional Experiment (FIRE) Arctic Clouds Experiment that was conducted in the Arctic during April through July, 1998. The principal goal of the field experiment was to gather the data needed to examine the impact of arctic clouds on the radiation exchange between the surface, atmosphere, and space, and to study how the surface influences the evolution of boundary layer clouds. The observations will be used to evaluate and improve climate model parameterizations of cloud and radiation processes, satellite remote sensing of cloud and surface characteristics, and understanding of cloud-radiation feedbacks in the Arctic. The experiment utilized four research aircraft that flew over surface-based observational sites in the Arctic Ocean and Barrow, Alaska. In this paper we describe the programmatic and science objectives of the project, the experimental design (including research platforms and instrumentation), conditions that were encountered during the field experiment, and some highlights of preliminary observations, modelling, and satellite remote sensing studies.
Curry, J. A.↗
Tropical and Arctic Cloud Observations From CALIPSO Between 2008-2014 and its Implications
There has been studies (e.g., Schweiger, 2004) suggest significant increase of Arctic clouds during the last three decades, especially in the western Arctic region. Such studies are based on passive remote sensing that are not highly reliable due to the lack of contrasts in temperature and reflectance between clouds and snow/ice surfaces. Changes in the Arctic clouds can be evaluated more accurately using the space-based lidar measurements from CALIPSO during the last nine years since CALIPSO can provide much more accurate detection and classification of both water and ice clouds in the Arctic. Time series of Arctic cloud properties (e.g., cloud fraction, cloud thermodynamic phase, water cloud depolarization ratio and droplet number concentration) from CALIPSO data are analyzed in this study. This study reveals the changes in both cloud fraction and cloud microphysical properties during the last nine years when CALIPSO data are available. We will evaluate the changes in Arctic cloud fraction and cloud microphysical properties, their seasonal and spatial characteristics and the potential impact on the energy budget and the climate of the Arctic.
Hu, Yongxiang↗
Sensitivity of Arctic Clouds to Ice Microphysical Processes in the NorESM2 Climate Model
Abstract Ice formation remains one of the most poorly represented microphysical processes in climate models. While primary ice production (PIP) parameterizations are known to have a large influence on the modeled cloud properties, the representation of secondary ice production (SIP) is incomplete and its corresponding impact is therefore largely unquantified. Furthermore, ice aggregation is another important process for the total cloud ice budget, which also remains largely unconstrained. In this study, we examine the impact of PIP, SIP, and ice aggregation on Arctic clouds, using the Norwegian Earth System Model, version 2 (NorESM2). Simulations with both prognostic and diagnostic PIP show that heterogeneous freezing alone cannot reproduce the observed cloud ice content. The implementation of missing SIP mechanisms (collisional breakup, drop shattering, and sublimation breakup) in NorESM2 improves the modeled ice properties, while improvements in liquid content occur only in simulations with prognostic PIP. However, results are sensitive to the description of collisional breakup. This mechanism, which dominates SIP in the examined conditions, is very sensitive to the treatment of the sublimation correction factor, a poorly constrained parameter that is included in the utilized parameterization. Finally, variations in ice aggregation treatment can also significantly impact cloud properties, mainly through their impact on collisional breakup efficiency. Overall, enhancement in ice production through the addition of SIP mechanisms and the reduction in ice aggregation (in line with radar observations of shallow Arctic clouds) result in enhanced cloud cover and decreased TOA radiation biases, compared to satellite measurements, especially during the cold months. Significance Statement Arctic clouds remain a large source of uncertainty in projections of the future climate due to the poor representation of the microphysical processes that govern their life cycle. Ice formation is among the least understood processes. While it is widely recognized that better constraints on primary ice production (PIP) are needed to improve existing parameterizations, we show that secondary ice production (SIP) and ice aggregation can have also a significant impact on ice number concentrations. Constraining ice formation through the addition of missing SIP mechanisms and reducing ice aggregation can improve the representation of the cloud macrophysical properties and enhance total cloud cover in the Arctic region, which in turn contributes to decreased TOA radiation biases in the cold months.
Meteorology & Atmospheric Sciences↗
Studies of Ice Nucleating Aerosol Particles in Arctic Cloud Systems
The focus of this research is to improve the understanding of ice nucleating aerosol particles (IN) and the role they play in ice formation in Arctic clouds. IN are important for global climate issues in a variety of ways. The primary effect is their role in determining the phase (liquid or solid) of cloud particles. The microscale impact is on cloud particle size, growth rate, shape, fall speed, concentration, radiative properties, and scavenging of gases and aerosols. On a larger scale, ice formation affects the development of precipitation (rate, amount, type, and distribution), latent heat release (rate and altitude), ambient humidity, the persistence of clouds, and cloud albedo. The overall goals of our FIRE 3 research are to characterize the concentrations and variability of Arctic IN during the winter-spring transition, to compare IN measurements with ice concentrations in Arctic clouds, and to examine selected IN samples for particle morphology and chemical there are distinguishable chemical signatures. The results can be combined with other measurements of aerosols, gaseous species, and cloud characteristics in order to understand the processes that determine the phase and concentration of cloud particles.
Rogers, David C.↗
Isolating the Surface Type Influence on Arctic Cloud Properties
In response to anthropogenic climate change, substantial declines in sea ice have been observed. An urgent question is whether and how clouds respond to the changing Arctic surface. Due to the important radiative influence of clouds, the response of clouds to sea ice cover change constitutes a potentially important climate feedback within the Arctic. The sign of this feedback is strongly influenced by the seasonality of the cloud response to sea ice loss. Given the importance of this phenomenon, previous research focused on using observations of inter-annual variability to quantify the cloud-sea ice relationship. However, the reliance on inter-annual variability to assess the covariance between clouds and sea ice make it challenging to control for the influence of large-scale meteorology on the clouds. We have devised an approach that applies an in situ, airborne observational strategy to quantify the influence of surface type on Arctic clouds to satellite data. Our event-based method composites cloud property differences for ocean, marginal ice zone, and sea ice surface types for >5000 MIZ crossing events. We find that cloud properties in non-summer months below ~1.5 km are influenced by surface type such that greater cloud fraction and water content are found over ocean relative to sea ice regions. Results are statistically significantly at the 95% confidence level. During summer, the surface type does not influence the cloud properties. The primary cause of the surface type dependent cloud property differences is the thermodynamic profiles differences that occur between the two surface types: namely, ocean footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their sea ice counterparts. We find that the differences in thermodynamic profiles by surface type that correspond to the cloud property differences also explains a significant portion of the variability across events. Our analysis provides evidence that the influence of surface type on cloud properties fundamentally occurs due to the inherent surface temperature differences between the surface types. Significant surface type influences on cloud properties are only found in the presence of surface temperature differences between the surface types and only non-summer months meet this criterion. A conceptual model of this process is as follows, fundamental properties of the ocean and sea ice surface types (e.g., surface albedo, heat capacity/thermal inertia, surface roughness, and thermal conductance) lead to systematic differences in the surface temperature by surface type. In response to this surface temperature difference, atmosphere boundary layer processes (including turbulent mixing and radiation) communicate the surface temperature differences to the lower atmosphere driving the greater stability over sea ice than ocean. These differences in the background thermodynamic state profiles between the surface types yield atmospheric conditions that are more conducive to cloud development over ocean than sea ice. The details of these boundary layer processes are sensitive to the surface type but may not be fundamental to the resulting thermodynamic structure and cloud differences. Thus, our results indicate that to accurately model that cloud response to sea ice loss in climate models the surface type properties that yield the systematic differences in ocean and sea ice temperature (e.g., surface albedo, surface turbulent fluxes parameters, and thermal conductance) must be accurately represented.
Arctic radiation budget↗
MOSAiC studies of long-lasting mixed-phase cloud events and analysis of the liquid-phase properties of Arctic clouds
Vertically resolved observations of the temporal evolution of mixed-phase clouds (MPCs) were performed over the central Arctic during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, which lasted from October 2019 to September 2020. The research icebreaker Polarstern , drifting with the pack ice for more than 7 months, mostly at latitudes > 85° N, served as a platform for state-of-the-art remote sensing of aerosols and clouds. The use of the recently introduced dual field-of-view (FOV) polarization lidar technique in combination with the well-established lidar-radar retrieval technique provided, for the first time, a robust instrumental basis to monitor the evolution of the liquid and the ice phase of MPCs and the interplay between the two phases. Two long-lasting Arctic MPC events observed close to the North Pole in mid-winter (December 2019) and late summer (September 2020) are discussed to provide new insight into Arctic MPC evolution processes. In the second part of the article, cloud statistics, covering all seasons of a year, are presented. The focus is on the optical and microphysical properties of the liquid phase. These results are solely derived from the dual-FOV lidar observations. The key findings of the study can be summarized as follows: persistent activation of aerosol particles to form water droplets is of great importance for the longevity of MPCs. The observations confirm that ice formation occurs predominantly via immersion freezing. The field studies suggest that the free tropospheric reservoirs of cloud condensation nuclei (CCN) and of ice-nucleating particles (INPs) were always well filled, i.e., the clouds did not exhaust their supply of activatable and activated particles. The observation of long-lasting MPC events, low ice production rates, and a sufficiently large INP reservoir leads to the recommendation to use a time-dependent immersion freezing parameterization in MPC modeling efforts.
Jimenez, Cristofer [Leibniz Inst. for Tropospheric↗
A radar view of ice microphysics and turbulence in Arctic cloud systems
Ice microphysical processes are inherently complex because of their sensitivity to temperature and humidity, the diversity of ice crystal habits, and their interaction with supercooled liquid water (SCL) and turbulence. Long-term surface-based radar observations have been systematically used to unravel the different processes that affect ice particle growth. In this study, we present a statistical analysis of 6.5 years of Ka-band radar observations in Arctic cloud systems, combined with thermodynamic profiles derived from radiosonde measurements. For the first time, ice particle growth and sublimation – diagnosed from vertical gradients of radar reflectivity and mean Doppler velocity – are systematically mapped across a broad range of temperature and moisture conditions. These vertical gradients correspond closely to saturation levels relative to ice and exhibit a strong temperature dependence in supersaturated regions. Notably, distinct signatures near −15 °C are indicative of dendritic growth. Turbulence, quantified via the eddy dissipation rate (EDR), is most frequently observed in regions containing SCL. The co-occurrence of SCL and elevated turbulence results in significantly enhanced ice particle growth compared to conditions in which either is present alone. This work provides new observational constraints that are critical for improving the representation of ice microphysics in atmospheric models.
54 ENVIRONMENTAL SCIENCES↗
Projected Regime Shift in Arctic Cloud and Water Vapor Feedbacks
The Arctic climate is changing faster than any other large-scale region on Earth. A variety of positive feedback mechanisms are responsible for the amplification, most of which are linked with changes in snow and ice cover, surface temperature (T(sub s)), atmospheric water vapor (WV), and cloud properties. As greenhouse gases continue to accumulate in the atmosphere, air temperature and water vapor content also increase, leading to a warmer surface and ice loss, which further enhance evaporation and WV. Many details of these interrelated feedbacks are poorly understood, yet are essential for understanding the pace and regional variations in future Arctic change. We use a global climate model (Goddard Institute for Space Studies, Atmosphere-Ocean Model) to examine several components of these feedbacks, how they vary by season, and how they are projected to change through the 21st century. One positive feedback begins with an increase in T(sub s) that produces an increase in WV, which in turn increases the downward longwave flux (DLF) and T(sub s), leading to further evaporation. Another associates the expected increases in cloud cover and optical thickness with increasing DLF and T(sub s). We examine the sensitivities between DLF and other climate variables in these feedbacks and find that they are strongest in the non-summer seasons, leading to the largest amplification in Ts during these months. Later in the 21st century, however, DLF becomes less sensitive to changes in WV and cloud optical thickness, as they cause the atmosphere to emit longwave radiation more nearly as a black body. This regime shift in sensitivity implies that the amplified pace of Arctic change relative to the northern hemisphere could relax in the future.
Chen, Yonghua↗
Arctic Cloud Response to a Perturbation in Sea Ice Concentration: The North Water Polynya
Surface and atmosphere energy exchanges play an important role in the Arctic climate system by influencing the lower atmospheric stability and humidity, sea ice melt and growth, and surface temperature. Sea ice significantly alters the character of these energy exchanges relative to ice-free ocean. The observed decline in Arctic sea ice since 1979 motivates questions related to the evolving role of surface-atmosphere coupling and potential feedbacks on the Arctic system. Due to the strong wintertime cloud warming effect, a critical question concerns the potential response of low clouds to Arctic sea ice decline. Previous approaches relied on interannual variability to investigate the cloud response to sea ice decline. However, the covariation between atmospheric conditions and sea ice makes it difficult to define an observational control when using interannual variability. To circumvent this difficulty, we exploit the recurring North Water polynya, an episodic opening in the northern Baffin Bay sea ice, as a natural laboratory to isolate the cloud response to a rapid, near-step perturbation in sea ice. Our results show that during the event, (a) low-cloud cover is 10%–33% larger over the polynya than nearby sea ice, (b) cloud liquid water content is up to 400% larger over the polynya than nearby sea ice, and (c) the surface cloud radiative effect is 18 W/sq. m larger over the polynya than nearby sea ice. Our results provide evidence that the low-cloud response during a polynya is a positive feedback lengthening the event.
Emily E. Monroe↗
The Influence of Sea ice on Arctic Cloud Properties: What Can We Learn by Applying a In Situ Observational Strategy to Satellite Data?
Sea ice is declining because of anthropogenic climate change. This change alters many aspects of the Arctic climate system, including the way that the surface and atmosphere interact. Atmosphere-surface coupling processes represent an important cloud feedback mechanism that can alter the Arctic surface energy budget. For the Arctic, it has been hypothesized that a reduction in sea ice cover could lead to an increase in clouds. If this process were to occur as originally hypothesized, sea ice loss in all seasons would lead to an increase in clouds. Recent observational studies find a cloud response to sea ice loss in non-summer months and no cloud response in summer months. However, previous studies rely on inter-annual variability and reanalysis to control for the influence of meteorology, reducing the confidence in the resulting conclusions. We adopt a phenomenological, event-based approach that does not need to use meteorological reanalysis. The approach analyzes cloud properties derived from CALIPSO-CloudSat over sea ice and adjacent ice-free footprints by compositing individual satellite ground tracks that cross the Arctic sea ice edge. The underlying assumption, which we verify, is that footprints that are close to each other in space and time experience similar large-scale meteorological conditions. Our results show larger cloud fraction and more cloud liquid water over ice-free than over sea ice footprints and provide additional evidence for a seasonal dependence of cloud-sea ice coupling that is in line with previous work. We find a different result where the maximum cloud property differences between sea ice and ice-free ocean occurs in spring, not fall as earlier studies suggest. We argue that these cloud differences between sea ice and ice-free ocean are primarily caused by the influence of the surface type on the thermodynamic stability of the lower troposphere and not principally from an increase in surface evaporation. In addition, we explore the sensitivity of these results to marginal ice zone width, season, Atlantic vs. Pacific sector, and the cloud property dependence on the distance from the sea ice edge. Overall, our results provide further evidence that cloud-sea ice coupling processes are not offsetting the observed surface energy budget perturbation due to sea ice loss in summer; thus, the cloud response to declining sea ice appears to contribute to amplified Arctic warming.
Patrick C Taylor↗
The influence of sea ice on Arctic cloud properties: What can we learn by applying an in situ observational strategy to satellite data?
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Patrick C. Taylor↗
Assessments of Arctic Cloud Vertical Structure From AIRS Using Radar‐Lidar Observations
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54 ENVIRONMENTAL SCIENCES↗
Sensitivity of Arctic Clouds to Ice Microphysical Processes in the NorESM2 Climate Model
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54 ENVIRONMENTAL SCIENCES↗