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1
Zamora, Lauren M., Ralph A. Kahn, Sabine Eckhardt, Allison McComiskey, Patricia Sawamura, Richard Moore, and Andreas Stohl. "Aerosol indirect effects on the nighttime Arctic Ocean surface from thin, predominantly liquid clouds." Atmospheric Chemistry and Physics 17, no. 12 (June 20, 2017): 7311–32. http://dx.doi.org/10.5194/acp-17-7311-2017.
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Abstract. Aerosol indirect effects have potentially large impacts on the Arctic Ocean surface energy budget, but model estimates of regional-scale aerosol indirect effects are highly uncertain and poorly validated by observations. Here we demonstrate a new way to quantitatively estimate aerosol indirect effects on a regional scale from remote sensing observations. In this study, we focus on nighttime, optically thin, predominantly liquid clouds. The method is based on differences in cloud physical and microphysical characteristics in carefully selected clean, average, and aerosol-impacted conditions. The cloud subset of focus covers just ∼ 5 % of cloudy Arctic Ocean regions, warming the Arctic Ocean surface by ∼ 1–1.4 W m−2 regionally during polar night. However, within this cloud subset, aerosol and cloud conditions can be determined with high confidence using CALIPSO and CloudSat data and model output. This cloud subset is generally susceptible to aerosols, with a polar nighttime estimated maximum regionally integrated indirect cooling effect of ∼ −0.11 W m−2 at the Arctic sea ice surface (∼ 8 % of the clean background cloud effect), excluding cloud fraction changes. Aerosol presence is related to reduced precipitation, cloud thickness, and radar reflectivity, and in some cases, an increased likelihood of cloud presence in the liquid phase. These observations are inconsistent with a glaciation indirect effect and are consistent with either a deactivation effect or less-efficient secondary ice formation related to smaller liquid cloud droplets. However, this cloud subset shows large differences in surface and meteorological forcing in shallow and higher-altitude clouds and between sea ice and open-ocean regions. For example, optically thin, predominantly liquid clouds are much more likely to overlay another cloud over the open ocean, which may reduce aerosol indirect effects on the surface. Also, shallow clouds over open ocean do not appear to respond to aerosols as strongly as clouds over stratified sea ice environments, indicating a larger influence of meteorological forcing over aerosol microphysics in these types of clouds over the rapidly changing Arctic Ocean.
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Tjernström, Michael, Joseph Sedlar, and Matthew D. Shupe. "How Well Do Regional Climate Models Reproduce Radiation and Clouds in the Arctic? An Evaluation of ARCMIP Simulations." Journal of Applied Meteorology and Climatology 47, no. 9 (September 1, 2008): 2405–22. http://dx.doi.org/10.1175/2008jamc1845.1.
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Abstract Downwelling radiation in six regional models from the Arctic Regional Climate Model Intercomparison (ARCMIP) project is systematically biased negative in comparison with observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment, although the correlations with observations are relatively good. In this paper, links between model errors and the representation of clouds in these models are investigated. Although some modeled cloud properties, such as the cloud water paths, are reasonable in a climatological sense, the temporal correlation of model cloud properties with observations is poor. The vertical distribution of cloud water is distinctly different among the different models; some common features also appear. Most models underestimate the presence of high clouds, and, although the observed preference for low clouds in the Arctic is present in most of the models, the modeled low clouds are too thin and are displaced downward. Practically all models show a preference to locate the lowest cloud base at the lowest model grid point. In some models this happens also to be where the observations show the highest occurrence of the lowest cloud base; it is not possible to determine if this result is just a coincidence. Different factors contribute to model surface radiation errors. For longwave radiation in summer, a negative bias is present both for cloudy and clear conditions, and intermodel differences are smaller when clouds are present. There is a clear relationship between errors in cloud-base temperature and radiation errors. In winter, in contrast, clear-sky cases are modeled reasonably well, but cloudy cases show a very large intermodel scatter with a significant bias in all models. This bias likely results from a complete failure in all of the models to retain liquid water in cold winter clouds. All models overestimate the cloud attenuation of summer solar radiation for thin and intermediate clouds, and some models maintain this behavior also for thick clouds.
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Sotiropoulou, G., J. Sedlar, M. Tjernström, M. D. Shupe, I. M. Brooks, and P. O. G. Persson. "The thermodynamic structure of summer Arctic stratocumulus and the dynamic coupling to the surface." Atmospheric Chemistry and Physics Discussions 14, no. 3 (February 11, 2014): 3815–74. http://dx.doi.org/10.5194/acpd-14-3815-2014.
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Abstract. The vertical structure of Arctic low-level clouds and Arctic boundary layer is studied, using observations from ASCOS (Arctic Summer Cloud Ocean Study), in the central Arctic, in late summer 2008. Two general types of cloud structures are examined: the "neutrally-stratified" and "stably-stratified" clouds. Neutrally-stratified are mixed-phase clouds where radiative-cooling near cloud top produces turbulence that creates a cloud-driven mixed layer. When this layer mixes with the surface-generated turbulence, the cloud layer is coupled to the surface, whereas when such an interaction does not occur, it remains decoupled; the latter state is most frequently observed. The decoupled clouds are usually higher compared to the coupled; differences in thickness or cloud water properties between the two cases are however not found. The surface fluxes are also very similar for both states. The decoupled clouds exhibit a bimodal thermodynamic structure, depending on the depth of the sub-cloud mixed layer (SML): clouds with shallower SMLs are disconnected from the surface by weak inversions, whereas those that lay over a deeper SML are associated with stronger inversions at the decoupling height. Neutrally-stratified clouds generally precipitate; the evaporation/sublimation of precipitation often enhances the decoupling state. Finally, stably-stratified clouds are usually lower, geometrically and optically thinner, non-precipitating liquid-water clouds, not containing enough liquid to drive efficient mixing through cloud-top cooling.
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Sotiropoulou, G., J. Sedlar, M. Tjernström, M. D. Shupe, I. M. Brooks, and P. O. G. Persson. "The thermodynamic structure of summer Arctic stratocumulus and the dynamic coupling to the surface." Atmospheric Chemistry and Physics 14, no. 22 (November 28, 2014): 12573–92. http://dx.doi.org/10.5194/acp-14-12573-2014.
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Abstract. The vertical structure of Arctic low-level clouds and Arctic boundary layer is studied, using observations from ASCOS (Arctic Summer Cloud Ocean Study), in the central Arctic, in late summer 2008. Two general types of cloud structures are examined: the "neutrally stratified" and "stably stratified" clouds. Neutrally stratified are mixed-phase clouds where radiative-cooling near cloud top produces turbulence that generates a cloud-driven mixed layer. When this layer mixes with the surface-generated turbulence, the cloud layer is coupled to the surface, whereas when such an interaction does not occur, it remains decoupled; the latter state is most frequently observed. The decoupled clouds are usually higher compared to the coupled; differences in thickness or cloud water properties between the two cases are however not found. The surface fluxes are also very similar for both states. The decoupled clouds exhibit a bimodal thermodynamic structure, depending on the depth of the sub-cloud mixed layer (SCML): clouds with shallower SCMLs are disconnected from the surface by weak inversions, whereas those that lay over a deeper SCML are associated with stronger inversions at the decoupling height. Neutrally stratified clouds generally precipitate; the evaporation/sublimation of precipitation often enhances the decoupling state. Finally, stably stratified clouds are usually lower, geometrically and optically thinner, non-precipitating liquid-water clouds, not containing enough liquid to drive efficient mixing through cloud-top cooling.
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Baek, Eun-Hyuk, Joo-Hong Kim, Sungsu Park, Baek-Min Kim, and Jee-Hoon Jeong. "Impact of poleward heat and moisture transports on Arctic clouds and climate simulation." Atmospheric Chemistry and Physics 20, no. 5 (March 12, 2020): 2953–66. http://dx.doi.org/10.5194/acp-20-2953-2020.
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Abstract. Many general circulation models (GCMs) have difficulty simulating Arctic clouds and climate, causing substantial inter-model spread. To address this issue, two Atmospheric Model Intercomparison Project (AMIP) simulations from the Community Atmosphere Model version 5 (CAM5) and Seoul National University (SNU) Atmosphere Model version 0 (SAM0) with a unified convection scheme (UNICON) are employed to identify an effective mechanism for improving Arctic cloud and climate simulations. Over the Arctic, SAM0 produced a larger cloud fraction and cloud liquid mass than CAM5, reducing the negative Arctic cloud biases in CAM5. The analysis of cloud water condensation rates indicates that this improvement is associated with an enhanced net condensation rate of water vapor into the liquid condensate of Arctic low-level clouds, which in turn is driven by enhanced poleward transports of heat and moisture by the mean meridional circulation and transient eddies. The reduced Arctic cloud biases lead to improved simulations of surface radiation fluxes and near-surface air temperature over the Arctic throughout the year. The association between the enhanced poleward transports of heat and moisture and increase in liquid clouds over the Arctic is also evident not only in both models, but also in the multi-model analysis. Our study demonstrates that enhanced poleward heat and moisture transport in a model can improve simulations of Arctic clouds and climate.
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Loewe, Katharina, Annica M. L. Ekman, Marco Paukert, Joseph Sedlar, Michael Tjernström, and Corinna Hoose. "Modelling micro- and macrophysical contributors to the dissipation of an Arctic mixed-phase cloud during the Arctic Summer Cloud Ocean Study (ASCOS)." Atmospheric Chemistry and Physics 17, no. 11 (June 8, 2017): 6693–704. http://dx.doi.org/10.5194/acp-17-6693-2017.
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Abstract. The Arctic climate is changing; temperature changes in the Arctic are greater than at midlatitudes, and changing atmospheric conditions influence Arctic mixed-phase clouds, which are important for the Arctic surface energy budget. These low-level clouds are frequently observed across the Arctic. They impact the turbulent and radiative heating of the open water, snow, and sea-ice-covered surfaces and influence the boundary layer structure. Therefore the processes that affect mixed-phase cloud life cycles are extremely important, yet relatively poorly understood. In this study, we present sensitivity studies using semi-idealized large eddy simulations (LESs) to identify processes contributing to the dissipation of Arctic mixed-phase clouds. We found that one potential main contributor to the dissipation of an observed Arctic mixed-phase cloud, during the Arctic Summer Cloud Ocean Study (ASCOS) field campaign, was a low cloud droplet number concentration (CDNC) of about 2 cm−3. Introducing a high ice crystal concentration of 10 L−1 also resulted in cloud dissipation, but such high ice crystal concentrations were deemed unlikely for the present case. Sensitivity studies simulating the advection of dry air above the boundary layer inversion, as well as a modest increase in ice crystal concentration of 1 L−1, did not lead to cloud dissipation. As a requirement for small droplet numbers, pristine aerosol conditions in the Arctic environment are therefore considered an important factor determining the lifetime of Arctic mixed-phase clouds.
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Xie, Shaocheng, Xiaohong Liu, Chuanfeng Zhao, and Yuying Zhang. "Sensitivity of CAM5-Simulated Arctic Clouds and Radiation to Ice Nucleation Parameterization." Journal of Climate 26, no. 16 (August 6, 2013): 5981–99. http://dx.doi.org/10.1175/jcli-d-12-00517.1.
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Abstract Sensitivity of Arctic clouds and radiation in the Community Atmospheric Model, version 5, to the ice nucleation process is examined by testing a new physically based ice nucleation scheme that links the variation of ice nuclei (IN) number concentration to aerosol properties. The default scheme parameterizes the IN concentration simply as a function of ice supersaturation. The new scheme leads to a significant reduction in simulated IN concentration at all latitudes while changes in cloud amounts and properties are mainly seen at high- and midlatitude storm tracks. In the Arctic, there is a considerable increase in midlevel clouds and a decrease in low-level clouds, which result from the complex interaction among the cloud macrophysics, microphysics, and large-scale environment. The smaller IN concentrations result in an increase in liquid water path and a decrease in ice water path caused by the slowdown of the Bergeron–Findeisen process in mixed-phase clouds. Overall, there is an increase in the optical depth of Arctic clouds, which leads to a stronger cloud radiative forcing (net cooling) at the top of the atmosphere. The comparison with satellite data shows that the new scheme slightly improves low-level cloud simulations over most of the Arctic but produces too many midlevel clouds. Considerable improvements are seen in the simulated low-level clouds and their properties when compared with Arctic ground-based measurements. Issues with the observations and the model–observation comparison in the Arctic region are discussed.
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Stapf, Johannes, André Ehrlich, Evelyn Jäkel, Christof Lüpkes, and Manfred Wendisch. "Reassessment of shortwave surface cloud radiative forcing in the Arctic: consideration of surface-albedo–cloud interactions." Atmospheric Chemistry and Physics 20, no. 16 (August 26, 2020): 9895–914. http://dx.doi.org/10.5194/acp-20-9895-2020.
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Abstract. The concept of cloud radiative forcing (CRF) is commonly applied to quantify the impact of clouds on the surface radiative energy budget (REB). In the Arctic, specific radiative interactions between microphysical and macrophysical properties of clouds and the surface strongly modify the warming or cooling effect of clouds, complicating the estimate of CRF obtained from observations or models. Clouds tend to increase the broadband surface albedo over snow or sea ice surfaces compared to cloud-free conditions. However, this effect is not adequately considered in the derivation of CRF in the Arctic so far. Therefore, we have quantified the effects caused by surface-albedo–cloud interactions over highly reflective snow or sea ice surfaces on the CRF using radiative transfer simulations and below-cloud airborne observations above the heterogeneous springtime marginal sea ice zone (MIZ) during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign. The impact of a modified surface albedo in the presence of clouds, as compared to cloud-free conditions, and its dependence on cloud optical thickness is found to be relevant for the estimation of the shortwave CRF. A method is proposed to consider this surface albedo effect on CRF estimates by continuously retrieving the cloud-free surface albedo from observations under cloudy conditions, using an available snow and ice albedo parameterization. Using ACLOUD data reveals that the estimated average shortwave cooling by clouds almost doubles over snow- and ice-covered surfaces (−62 W m−2 instead of −32 W m−2), if surface-albedo–cloud interactions are considered. As a result, the observed total (shortwave plus longwave) CRF shifted from a warming effect to an almost neutral one. Concerning the seasonal cycle of the surface albedo, it is demonstrated that this effect enhances shortwave cooling in periods when snow dominates the surface and potentially weakens the cooling by optically thin clouds during the summertime melting season. These findings suggest that the surface-albedo–cloud interaction should be considered in global climate models and in long-term studies to obtain a realistic estimate of the shortwave CRF to quantify the role of clouds in Arctic amplification.
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Eastman, Ryan, and Stephen G. Warren. "Interannual Variations of Arctic Cloud Types in Relation to Sea Ice." Journal of Climate 23, no. 15 (August 1, 2010): 4216–32. http://dx.doi.org/10.1175/2010jcli3492.1.
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Abstract Sea ice extent and thickness may be affected by cloud changes, and sea ice changes may in turn impart changes to cloud cover. Different types of clouds have different effects on sea ice. Visual cloud reports from land and ocean regions of the Arctic are analyzed here for interannual variations of total cloud cover and nine cloud types, and their relation to sea ice. Over the high Arctic, cloud cover shows a distinct seasonal cycle dominated by low stratiform clouds, which are much more common in summer than winter. Interannual variations of cloud amounts over the Arctic Ocean show significant correlations with surface air temperature, total sea ice extent, and the Arctic Oscillation. Low ice extent in September is generally preceded by a summer with decreased middle and precipitating clouds. Following a low-ice September there is enhanced low cloud cover in autumn. Total cloud cover appears to be greater throughout the year during low-ice years. Multidecadal trends from surface observations over the Arctic Ocean show increasing cloud cover, which may promote ice loss by longwave radiative forcing. Trends are positive in all seasons, but are most significant during spring and autumn, when cloud cover is positively correlated with surface air temperature. The coverage of summertime precipitating clouds has been decreasing over the Arctic Ocean, which may promote ice loss.
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Sartori, Ernani. "The Arctic ice melting confirms the new theory." Journal of Water and Climate Change 10, no. 2 (October 5, 2018): 321–43. http://dx.doi.org/10.2166/wcc.2018.153.
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Abstract The new theory shows that the global and the Arctic atmospheres behave as an open atmosphere (few clouds) or as a ‘closed’ atmosphere (fully cloudy), which explains the Arctic ice melting. Within the closed atmosphere the solar radiation, wind and evaporation are reduced while the water and air temperatures and the humidity increase. Real data confirm these effects for the planet and for the Arctic. Many authors did not understand these apparent inconsistencies, but this paper solves many intriguing problems, and provides solutions that led the present author to discover the new hydrological cycle. Some human activities increase the formation of clouds and precipitation or of droughts. The sun is not the only heat source for the atmosphere. Several real data confirm that clouds have increased over decades globally and at the Arctic. These intensifications also confirm the operation of the new hydrological cycle and of the Sartori theory. Many real data show that while the Arctic ice has melted, the cloud cover has pushed the temperatures up above freezing and has raised them by 2–3 °C compared to cloudless skies as well as acting to warm the Arctic for most of the annual cycles.
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Zuidema, P., B. Baker, Y. Han, J. Intrieri, J. Key, P. Lawson, S. Matrosov, M. Shupe, R. Stone, and T. Uttal. "An Arctic Springtime Mixed-Phase Cloudy Boundary Layer Observed during SHEBA." Journal of the Atmospheric Sciences 62, no. 1 (January 1, 2005): 160–76. http://dx.doi.org/10.1175/jas-3368.1.
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Abstract The microphysical characteristics, radiative impact, and life cycle of a long-lived, surface-based mixed-layer, mixed-phase cloud with an average temperature of approximately −20°C are presented and discussed. The cloud was observed during the Surface Heat Budget of the Arctic experiment (SHEBA) from 1 to 10 May 1998. Vertically resolved properties of the liquid and ice phases are retrieved using surface-based remote sensors, utilize the adiabatic assumption for the liquid component, and are aided by and validated with aircraft measurements from 4 and 7 May. The cloud radar ice microphysical retrievals, originally developed for all-ice clouds, compare well with aircraft measurements despite the presence of much greater liquid water contents than ice water contents. The retrieved time-mean liquid cloud optical depth of 10.1 ± 7.8 far surpasses the mean ice cloud optical depth of 0.2, so that the liquid phase is primarily responsible for the cloud’s radiative (flux) impact. The ice phase, in turn, regulates the overall cloud optical depth through two mechanisms: sedimentation from a thin upper ice cloud, and a local ice production mechanism with a time scale of a few hours, thought to reflect a preferred freezing of the larger liquid drops. The liquid water paths replenish within half a day or less after their uptake by ice, attesting to strong water vapor fluxes. Deeper boundary layer depths and higher cloud optical depths coincide with large-scale rising motion at 850 hPa, but the synoptic activity is also associated with upper-level ice clouds. Interestingly, the local ice formation mechanism appears to be more active when the large-scale subsidence rate implies increased cloud-top entrainment. Strong cloud-top radiative cooling rates promote cloud longevity when the cloud is optically thick. The radiative impact of the cloud upon the surface is significant: a time-mean positive net cloud forcing of 41 W m−2 with a diurnal amplitude of ∼20 W m−2. This is primarily because a high surface reflectance (0.86) reduces the solar cooling influence. The net cloud forcing is primarily sensitive to cloud optical depth for the low-optical-depth cloudy columns and to the surface reflectance for the high-optical-depth cloudy columns. Any projected increase in the springtime cloud optical depth at this location (76°N, 165°W) is not expected to significantly alter the surface radiation budget, because clouds were almost always present, and almost 60% of the cloudy columns had optical depths >6.
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Stramler, Kirstie, Anthony D. Del Genio, and William B. Rossow. "Synoptically Driven Arctic Winter States." Journal of Climate 24, no. 6 (March 15, 2011): 1747–62. http://dx.doi.org/10.1175/2010jcli3817.1.
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Abstract The dense network of the Surface Heat Budget of the Arctic (SHEBA) observations is used to assess relationships between winter surface and atmospheric variables as the SHEBA site came under the influence of cyclonic and anticyclonic atmospheric circulation systems. Two distinct and preferred states of subsurface, surface, atmosphere, and clouds occur during the SHEBA winter, extending from the oceanic mixed layer through the troposphere and preceded by same-sign variations in the stratosphere. These states are apparent in distributions of surface temperature, sensible heat and longwave radiation fluxes, ocean heat conduction, cloud-base height and temperature, and in the atmospheric humidity and temperature structure. Surface and atmosphere are in radiative–turbulent–conductive near-equilibrium during a warm opaquely cloudy-sky state, which persists up to 10 days and usually occurs during the low surface pressure phase of a baroclinic wave, although occasionally occurs during the high surface pressure phase because of low, scattered clouds. Clouds occurring in this state have near-unity emissivity and the lowest bases in the vicinity of, or below, the temperature inversion peak. A cold radiatively clear-sky state persists up to two weeks, and occurs only in the high surface pressure phase of a baroclinic wave. The radiatively clear state has clouds that are too tenuous when surface based or, irrespective of opacity, located too far aloft to contribute significantly to the surface energy budget. There is a 13-K surface temperature difference between the two states, and atmospheric inversion peak temperatures are linearly related to the surface temperature in both states. The snow–sea ice interface temperature oscillates over the course of the winter season, as it cools during the radiatively clear state and is warmed from atmospheric emission above and ocean heat conduction from below during the opaquely cloudy state. Analysis of satellite data over the Arctic from 70°–90°N indicates that the radiatively clear and opaquely cloudy states observed at SHEBA may be representative of the entire Arctic basin. The results suggest that model formulation inadequacies should be easier to diagnose if modeled energy transfers are compared with observations using process-based metrics that acknowledge the bimodal nature of the Arctic ocean–ice–snow–atmosphere column, rather than monthly and regionally averaged quantities. Climate change projections of thinner Arctic sea ice and larger advective water vapor influxes into the Arctic could yield different frequencies of occupation of the radiatively clear and opaquely cloudy states and higher wintertime temperatures of SHEBA ocean, ice, snow, atmosphere, and clouds—in particular, a wintertime warming of the snow–sea ice interface temperature.
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Wendisch, Manfred, Andreas Macke, André Ehrlich, Christof Lüpkes, Mario Mech, Dmitry Chechin, Klaus Dethloff, et al. "The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multiplatform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification." Bulletin of the American Meteorological Society 100, no. 5 (May 2019): 841–71. http://dx.doi.org/10.1175/bams-d-18-0072.1.
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AbstractClouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, and surface properties, as well as turbulent and radiative fluxes that inhibit accurate model simulations of clouds in the Arctic climate system. In an attempt to resolve this so-called Arctic cloud puzzle, two comprehensive and closely coordinated field studies were conducted: the Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) aircraft campaign and the Physical Feedbacks of Arctic Boundary Layer, Sea Ice, Cloud and Aerosol (PASCAL) ice breaker expedition. Both observational studies were performed in the framework of the German Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)3 project. They took place in the vicinity of Svalbard, Norway, in May and June 2017. ACLOUD and PASCAL explored four pieces of the Arctic cloud puzzle: cloud properties, aerosol impact on clouds, atmospheric radiation, and turbulent dynamical processes. The two instrumented Polar 5 and Polar 6 aircraft; the icebreaker Research Vessel (R/V) Polarstern; an ice floe camp including an instrumented tethered balloon; and the permanent ground-based measurement station at Ny-Ålesund, Svalbard, were employed to observe Arctic low- and mid-level mixed-phase clouds and to investigate related atmospheric and surface processes. The Polar 5 aircraft served as a remote sensing observatory examining the clouds from above by downward-looking sensors; the Polar 6 aircraft operated as a flying in situ measurement laboratory sampling inside and below the clouds. Most of the collocated Polar 5/6 flights were conducted either above the R/V Polarstern or over the Ny-Ålesund station, both of which monitored the clouds from below using similar but upward-looking remote sensing techniques as the Polar 5 aircraft. Several of the flights were carried out underneath collocated satellite tracks. The paper motivates the scientific objectives of the ACLOUD/PASCAL observations and describes the measured quantities, retrieved parameters, and the applied complementary instrumentation. Furthermore, it discusses selected measurement results and poses critical research questions to be answered in future papers analyzing the data from the two field campaigns.
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Turner, D. D. "Arctic Mixed-Phase Cloud Properties from AERI Lidar Observations: Algorithm and Results from SHEBA." Journal of Applied Meteorology 44, no. 4 (April 1, 2005): 427–44. http://dx.doi.org/10.1175/jam2208.1.
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Abstract A new approach to retrieve microphysical properties from mixed-phase Arctic clouds is presented. This mixed-phase cloud property retrieval algorithm (MIXCRA) retrieves cloud optical depth, ice fraction, and the effective radius of the water and ice particles from ground-based, high-resolution infrared radiance and lidar cloud boundary observations. The theoretical basis for this technique is that the absorption coefficient of ice is greater than that of liquid water from 10 to 13 μm, whereas liquid water is more absorbing than ice from 16 to 25 μm. MIXCRA retrievals are only valid for optically thin (τvisible < 6) single-layer clouds when the precipitable water vapor is less than 1 cm. MIXCRA was applied to the Atmospheric Emitted Radiance Interferometer (AERI) data that were collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment from November 1997 to May 1998, where 63% of all of the cloudy scenes above the SHEBA site met this specification. The retrieval determined that approximately 48% of these clouds were mixed phase and that a significant number of clouds (during all 7 months) contained liquid water, even for cloud temperatures as low as 240 K. The retrieved distributions of effective radii for water and ice particles in single-phase clouds are shown to be different than the effective radii in mixed-phase clouds.
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Shupe, Matthew D. "Clouds at Arctic Atmospheric Observatories. Part II: Thermodynamic Phase Characteristics." Journal of Applied Meteorology and Climatology 50, no. 3 (March 1, 2011): 645–61. http://dx.doi.org/10.1175/2010jamc2468.1.
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Abstract Cloud phase defines many cloud properties and determines the ways in which clouds interact with other aspects of the climate system. The occurrence fraction and characteristics of clouds distinguished by their phase are examined at three Arctic atmospheric observatories. Each observatory has the basic suite of instruments that are necessary to identify cloud phase, namely, cloud radar, depolarization lidar, microwave radiometer, and twice-daily radiosondes. At these observatories, ice clouds are more prevalent than mixed-phase clouds, which are more prevalent than liquid-only clouds. Cloud ice occurs 60%–70% of the time over a typical year, at heights up to 11 km. Liquid water occurs at temperatures above −40°C and is increasingly more likely as temperatures increase. Within the temperature range from −40° to −30°C, liquid water occurs in 3%–5% of the observed cloudiness. Liquid water is found higher in the atmosphere when accompanied by ice; there are few liquid-only clouds above 3 km, although liquid in mixed-phase clouds occurs at heights up to about 7–8 km. Regardless of temperature or height, liquid water occurs 56% of the time at Barrow, Alaska, and at a western Arctic Ocean site, but only 32% of the time at Eureka, Nunavut, Canada. This significant difference in liquid occurrence is due to a relatively dry lower troposphere during summer at Eureka in addition to warmer cloud temperatures with more persistent liquid water layers at the far western locations. The most persistent liquid clouds at these locations occur continuously for more than 70 h in the autumn and more than 30 h in the winter. Ice clouds persist for much longer than do liquid clouds at Eureka and occur more frequently in the winter season, leading to a total cloud occurrence annual cycle that is distinct from the other observatories.
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Kravitz, Ben, Hailong Wang, Philip J. Rasch, Hugh Morrison, and Amy B. Solomon. "Process-model simulations of cloud albedo enhancement by aerosols in the Arctic." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2031 (December 28, 2014): 20140052. http://dx.doi.org/10.1098/rsta.2014.0052.
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A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN), either through geoengineering or other increased sources of Arctic aerosols. An updated cloud microphysical scheme is employed, with prognostic CCN and cloud particle numbers in both liquid and mixed-phase marine low clouds. Injection of CCN into the marine boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. Albedo increases are stronger for pure liquid clouds than mixed-phase clouds. Liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less; thus, the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. CCN injection into a clean regime results in a greater albedo increase than injection into a polluted regime, consistent with current knowledge about aerosol–cloud interactions. Unlike previous studies investigating warm clouds, dynamical changes in circulation owing to precipitation changes are small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering is unlikely to be effective as the sole means of altering the global radiation budget but could have substantial local radiative effects.
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Shupe, Matthew D., Pavlos Kollias, P. Ola G. Persson, and Greg M. McFarquhar. "Vertical Motions in Arctic Mixed-Phase Stratiform Clouds." Journal of the Atmospheric Sciences 65, no. 4 (April 1, 2008): 1304–22. http://dx.doi.org/10.1175/2007jas2479.1.
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Abstract The characteristics of Arctic mixed-phase stratiform clouds and their relation to vertical air motions are examined using ground-based observations during the Mixed-Phase Arctic Cloud Experiment (MPACE) in Barrow, Alaska, during fall 2004. The cloud macrophysical, microphysical, and dynamical properties are derived from a suite of active and passive remote sensors. Low-level, single-layer, mixed-phase stratiform clouds are typically topped by a 400–700-m-deep liquid water layer from which ice crystals precipitate. These clouds are strongly dominated (85% by mass) by liquid water. On average, an in-cloud updraft of 0.4 m s−1 sustains the clouds, although cloud-scale circulations lead to a variability of up to ±2 m s−1 from the average. Dominant scales-of-variability in both vertical air motions and cloud microphysical properties retrieved by this analysis occur at 0.5–10-km wavelengths. In updrafts, both cloud liquid and ice mass grow, although the net liquid mass growth is usually largest. Between updrafts, nearly all ice falls out and/or sublimates while the cloud liquid diminishes but does not completely evaporate. The persistence of liquid water throughout these cloud cycles suggests that ice-forming nuclei, and thus ice crystal, concentrations must be limited and that water vapor is plentiful. These details are brought together within the context of a conceptual model relating cloud-scale dynamics and microphysics.
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Griesche, Hannes J., Kevin Ohneiser, Patric Seifert, Martin Radenz, Ronny Engelmann, and Albert Ansmann. "Contrasting ice formation in Arctic clouds: surface-coupled vs. surface-decoupled clouds." Atmospheric Chemistry and Physics 21, no. 13 (July 9, 2021): 10357–74. http://dx.doi.org/10.5194/acp-21-10357-2021.
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Abstract. In the Arctic summer of 2017 (1 June to 16 July) measurements with the OCEANET-Atmosphere facility were performed during the Polarstern cruise PS106. OCEANET comprises amongst other instruments the multiwavelength polarization lidar PollyXT_OCEANET and for PS106 was complemented with a vertically pointed 35 GHz cloud radar. In the scope of the presented study, the influence of cloud height and surface coupling on the probability of clouds to contain and form ice is investigated. Polarimetric lidar data were used for the detection of the cloud base and the identification of the thermodynamic phase. Both radar and lidar were used to detect cloud top. Radiosonde data were used to derive the thermodynamic structure of the atmosphere and the clouds. The analyzed data set shows a significant impact of the surface-coupling state on the probability of ice formation. Surface-coupled clouds were identified by a quasi-constant potential temperature profile from the surface up to liquid layer base. Within the same minimum cloud temperature range, ice-containing clouds have been observed more frequently than surface-decoupled clouds by a factor of up to 6 (temperature intervals between −7.5 and −5 ∘C, 164 vs. 27 analyzed intervals of 30 min). The frequency of occurrence of surface-coupled ice-containing clouds was found to be 2–3 times higher (e.g., 82 % vs. 35 % between −7.5 and −5 ∘C). These findings provide evidence that above −10 ∘C heterogeneous ice formation in Arctic mixed-phase clouds occurs by a factor of 2–6 more often when the cloud layer is coupled to the surface. In turn, for minimum cloud temperatures below −15 ∘C, the frequency of ice-containing clouds for coupled and decoupled conditions approached the respective curve for the central European site of Leipzig, Germany (51∘ N, 12∘ E). This corroborates the hypothesis that the free-tropospheric ice nucleating particle (INP) reservoir over the Arctic is controlled by continental aerosol. Two sensitivity studies, also using the cloud radar for detection of ice particles and applying a modified coupling state detection, both confirmed the findings, albeit with a lower magnitude. Possible explanations for the observations are discussed by considering recent in situ measurements of INP in the Arctic, of which much higher concentrations were found in the surface-coupled atmosphere in close vicinity to the ice shore.
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Mauritsen, T., J. Sedlar, M. Tjernström, C. Leck, M. Martin, M. Shupe, S. Sjogren, et al. "Aerosols indirectly warm the Arctic." Atmospheric Chemistry and Physics Discussions 10, no. 7 (July 6, 2010): 16775–96. http://dx.doi.org/10.5194/acpd-10-16775-2010.
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Abstract. On average, airborne aerosol particles cool the Earth's surface directly by absorbing and scattering sunlight and indirectly by influencing cloud reflectivity, life time, thickness or extent. Here we show that over the central Arctic Ocean, where there is frequently a lack of aerosol particles upon which clouds may form, a small increase in aerosol loading may enhance cloudiness thereby likely causing a climatologically significant warming at the ice-covered Arctic surface. Under these low concentration conditions cloud droplets grow to drizzle sizes and fall, even in the absence of collisions and coalescence, thereby diminishing cloud water. Evidence from a case study suggests that interactions between aerosol, clouds and precipitation could be responsible for attaining the observed low aerosol concentrations.
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Tietze, K., J. Riedi, A. Stohl, and T. J. Garrett. "Space-based evaluation of interactions between aerosols and low-level Arctic clouds during the Spring and Summer of 2008." Atmospheric Chemistry and Physics 11, no. 7 (April 8, 2011): 3359–73. http://dx.doi.org/10.5194/acp-11-3359-2011.
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Abstract. This study explores the indirect effects of anthropogenic and biomass burning aerosols on Arctic clouds by co-locating a combination of MODIS and POLDER cloud products with output from the FLEXPART tracer transport model. During the activities of the International Polar Year for the Spring and Summer of 2008, we find a high sensitivity of Arctic cloud radiative properties to both anthropogenic and biomass burning pollution plumes, particularly at air temperatures near freezing or potential temperatures near 286 K. However, the sensitivity is much lower at both colder and warmer temperatures, possibly due to increases in the wet and dry scavenging of cloud condensation nuclei: the pollution plumes remain but the component that influences Arctic clouds has been removed along transport pathways. The analysis shows that, independent of local temperature, cloud optical depth is approximately four times more sensitive to changes in pollution levels than is cloud effective radius. This suggests that some form of feedback mechanism amplifies the radiative response of Arctic clouds to pollution through changes in cloud liquid water path.
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Sedlar, Joseph. "Implications of Limited Liquid Water Path on Static Mixing within Arctic Low-Level Clouds." Journal of Applied Meteorology and Climatology 53, no. 12 (December 2014): 2775–89. http://dx.doi.org/10.1175/jamc-d-14-0065.1.
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AbstractObservations of cloud properties and thermodynamics from two Arctic locations, Barrow, Alaska, and Surface Heat Budget of the Arctic (SHEBA), are examined. A comparison of in-cloud thermodynamic mixing characteristics for low-level, single-layer clouds from nearly a decade of data at Barrow and one full annual cycle over the sea ice at SHEBA is performed. These cloud types occur relatively frequently, evident in 27%–30% of all cloudy cases. To understand the role of liquid water path (LWP), or lack thereof, on static in-cloud mixing, cloud layers are separated into optically thin and optically thick LWP subclasses. Clouds with larger LWPs tend to have a deeper in-cloud mixed layer relative to optically thinner clouds. However, both cloud LWP subclasses are frequently characterized by an in-cloud stable layer above the mixed layer top. The depth of the stable layer generally correlates with an increased temperature gradient across the layer. This layer often contains a specific humidity inversion, but it is more frequently present when cloud LWP is optically thinner (LWP < 50 g m−2). It is suggested that horizontal thermodynamic advection plays a key role modifying the vertical extent of in-cloud mixing and likewise the depth of in-cloud stable layers. Furthermore, longwave atmospheric opacity above the cloud top is generally enhanced during cases with optically thinner clouds. Thermodynamic advection, cloud condensate distribution within the stable layer, and enhanced atmospheric radiation above the cloud are found to introduce a thermodynamic–radiative feedback that potentially modifies the extent of LWP and subsequent in-cloud mixing.
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Zhao, Xiaoyi, Kristof Bognar, Vitali Fioletov, Andrea Pazmino, Florence Goutail, Luis Millán, Gloria Manney, Cristen Adams, and Kimberly Strong. "Assessing the impact of clouds on ground-based UV–visible total column ozone measurements in the high Arctic." Atmospheric Measurement Techniques 12, no. 4 (April 18, 2019): 2463–83. http://dx.doi.org/10.5194/amt-12-2463-2019.
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Abstract. Zenith-Sky scattered light Differential Optical Absorption Spectroscopy (ZS-DOAS) has been used widely to retrieve total column ozone (TCO). ZS-DOAS measurements have the advantage of being less sensitive to clouds than direct-sun measurements. However, the presence of clouds still affects the quality of ZS-DOAS TCO. Clouds are thought to be the largest contributor to random uncertainty in ZS-DOAS TCO, but their impact on data quality still needs to be quantified. This study has two goals: (1) to investigate whether clouds have a significant impact on ZS-DOAS TCO, and (2) to develop a cloud-screening algorithm to improve ZS-DOAS measurements in the Arctic under cloudy conditions. To quantify the impact of weather, 8 years of measured and modelled TCO have been used, along with information about weather conditions at Eureka, Canada (80.05∘ N, 86.41∘ W). Relative to direct-sun TCO measurements by Brewer spectrophotometers and modelled TCO, a positive bias is found in ZS-DOAS TCO measured in cloudy weather, and a negative bias is found for clear conditions, with differences of up to 5 % between clear and cloudy conditions. A cloud-screening algorithm is developed for high latitudes using the colour index calculated from ZS-DOAS spectra. The quality of ZS-DOAS TCO datasets is assessed using a statistical uncertainty estimation model, which suggests a 3 %–4 % random uncertainty. The new cloud-screening algorithm reduces the random uncertainty by 0.6 %. If all measurements collected during cloudy conditions, as identified using the weather station observations, are removed, the random uncertainty is reduced by 1.3 %. This work demonstrates that clouds are a significant contributor to uncertainty in ZS-DOAS TCO and proposes a method that can be used to screen clouds in high-latitude spectra.
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Vüllers, Jutta, Peggy Achtert, Ian M. Brooks, Michael Tjernström, John Prytherch, Annika Burzik, and Ryan Neely III. "Meteorological and cloud conditions during the Arctic Ocean 2018 expedition." Atmospheric Chemistry and Physics 21, no. 1 (January 13, 2021): 289–314. http://dx.doi.org/10.5194/acp-21-289-2021.
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Abstract. The Arctic Ocean 2018 (AO2018) took place in the central Arctic Ocean in August and September 2018 on the Swedish icebreaker Oden. An extensive suite of instrumentation provided detailed measurements of surface water chemistry and biology, sea ice and ocean physical and biogeochemical properties, surface exchange processes, aerosols, clouds, and the state of the atmosphere. The measurements provide important information on the coupling of the ocean and ice surface to the atmosphere and in particular to clouds. This paper provides (i) an overview of the synoptic-scale atmospheric conditions and their climatological anomaly to help interpret the process studies and put the detailed observations from AO2018 into a larger context, both spatially and temporally; (ii) a statistical analysis of the thermodynamic and near-surface meteorological conditions, boundary layer, cloud, and fog characteristics; and (iii) a comparison of the results to observations from earlier Arctic Ocean expeditions – in particular AOE1996 (Arctic Ocean Expedition 1996), SHEBA (Surface Heat Budget of the Arctic Ocean), AOE2001 (Arctic Ocean Experiment 2001), ASCOS (Arctic Summer Cloud Ocean Study), ACSE (Arctic Clouds in Summer Experiment), and AO2016 (Arctic Ocean 2016) – to provide an assessment of the representativeness of the measurements. The results show that near-surface conditions were broadly comparable to earlier experiments; however the thermodynamic vertical structure was quite different. An unusually high frequency of well-mixed boundary layers up to about 1 km depth occurred, and only a few cases of the “prototypical” Arctic summer single-layer stratocumulus deck were observed. Instead, an unexpectedly high amount of multiple cloud layers and mid-level clouds were present throughout the campaign. These differences from previous studies are related to the high frequency of cyclonic activity in the central Arctic in 2018.
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Shupe, Matthew D., David D. Turner, Alexander Zwink, Mandana M. Thieman, Eli J. Mlawer, and Timothy Shippert. "Deriving Arctic Cloud Microphysics at Barrow, Alaska: Algorithms, Results, and Radiative Closure." Journal of Applied Meteorology and Climatology 54, no. 7 (July 2015): 1675–89. http://dx.doi.org/10.1175/jamc-d-15-0054.1.
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AbstractCloud phase and microphysical properties control the radiative effects of clouds in the climate system and are therefore crucial to characterize in a variety of conditions and locations. An Arctic-specific, ground-based, multisensor cloud retrieval system is described here and applied to 2 yr of observations from Barrow, Alaska. Over these 2 yr, clouds occurred 75% of the time, with cloud ice and liquid each occurring nearly 60% of the time. Liquid water occurred at least 25% of the time, even in winter, and existed up to heights of 8 km. The vertically integrated mass of liquid was typically larger than that of ice. While it is generally difficult to evaluate the overall uncertainty of a comprehensive cloud retrieval system of this type, radiative flux closure analyses were performed in which flux calculations using the derived microphysical properties were compared with measurements at the surface and the top of the atmosphere. Radiative closure biases were generally smaller for cloudy scenes relative to clear skies, while the variability of flux closure results was only moderately larger than under clear skies. The best closure at the surface was obtained for liquid-containing clouds. Radiative closure results were compared with those based on a similar, yet simpler, cloud retrieval system. These comparisons demonstrated the importance of accurate cloud-phase and cloud-type classification, and specifically the identification of liquid water, for determining radiative fluxes. Enhanced retrievals of liquid water path for thin clouds were also shown to improve radiative flux calculations.
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Achtert, P., M. Karlsson Andersson, F. Khosrawi, and J. Gumbel. "Do tropospheric clouds influence Polar Stratospheric cloud occurrence in the Arctic?" Atmospheric Chemistry and Physics Discussions 11, no. 12 (December 7, 2011): 32065–84. http://dx.doi.org/10.5194/acpd-11-32065-2011.
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Abstract. The type of Polar stratospheric clouds (PSCs) as well as their temporal and spatial extent are important for the occurrence of heterogeneous reactions in the polar stratosphere. The formation of PSCs depends strongly on temperature. However, the mechanisms of the formation of solid PSCs are still poorly understood. Recent satellite studies of Antarctic PSCs have shown that their formation can be associated with deep-tropospheric clouds which have the ability to cool the lower stratosphere radiatively and/or adiabatically. In the present study, lidar measurements aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite were used to investigate whether the formation of Arctic PSCs can be associated with deep-tropospheric clouds as well. Deep-tropospheric cloud systems have a vertical extent of more than 6.5 km with a cloud top height above 7 km altitude. PSCs observed by CALIPSO during the Arctic winter 2007/2008 were classified according to their type (STS, NAT, or ice) and to the kind of underlying tropospheric clouds. Our analysis reveals that 172 out of 211 observed PSCs occurred in connection with tropospheric clouds. 72% of these 172 observed PSCs occured above deep-tropospheric clouds. We also find that the type of PSC seems to be connected to the characteristics of the underlying tropospheric cloud system. During the Arctic winter 2007/2008 PSCs consisting of ice were mainly observed in connection with deep-tropospheric cloud systems while no ice PSC was detected above cirrus. Furthermore, we find no correlation between the occurrence of PSCs and the top temperature of tropospheric clouds. These findings suggest that Arctic PSC formation is connected to adiabatice cooling, i.e. dynamic effects rather than radiative cooling.
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Curry, J. A., P. V. Hobbs, M. D. King, D. A. Randall, P. Minnis, G. A. Isaac, J. O. Pinto, et al. "FIRE Arctic Clouds Experiment." Bulletin of the American Meteorological Society 81, no. 1 (January 2000): 5—old—30. http://dx.doi.org/10.1175/1520-0477(2000)081<0005:face>2.0.co;2.
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Curry, J. A., P. V. Hobbs, M. D. King, D. A. Randall, P. Minnis, G. A. Isaac, J. O. Pinto, et al. "FIRE Arctic Clouds Experiment." Bulletin of the American Meteorological Society 81, no. 1 (January 2000): 5–29. http://dx.doi.org/10.1175/1520-0477(2000)081<0005:face>2.3.co;2.
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Kretzschmar, Jan, Marc Salzmann, Johannes Mülmenstädt, and Johannes Quaas. "Arctic clouds in ECHAM6 and their sensitivity to cloud microphysics and surface fluxes." Atmospheric Chemistry and Physics 19, no. 16 (August 21, 2019): 10571–89. http://dx.doi.org/10.5194/acp-19-10571-2019.
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Abstract. Compared to other climate models, the MPI-ESM/ECHAM6 is one of the few models that is able to realistically simulate the typical two-state radiative structure of the Arctic boundary layer and also is able to sustain liquid water at low temperatures as is often observed in high latitudes. To identify processes in the model that are responsible for the abovementioned features, we compare cloud properties from ECHAM6 to observations from CALIPSO-GOCCP using the COSP satellite simulator and perform sensitivity runs. The comparison shows that the model is able to reproduce the spatial distribution and cloud amount in the Arctic to some extent but a positive bias in cloud fraction is found in high latitudes, which is related to an overestimation of low- and high-level clouds. We mainly focus on low-level clouds and show that the overestimated cloud amount is connected to surfaces that are covered with snow or ice and is mainly caused by an overestimation of liquid-containing clouds. The overestimated amount of Arctic low-level liquid clouds can be related to insufficient efficiency of the Wegener–Bergeron–Findeisen (WBF) process but revising this process alone is not sufficient to improve cloud phase on a global scale as it also introduces a negative bias over oceanic regions in high latitudes. Additionally, this measure transformed the positive bias in low-level liquid clouds into a positive bias of low-level ice clouds, keeping the amount of low-level clouds almost unchanged. To avoid this spurious increase in ice clouds, we allowed for supersaturation with respect to ice using a temperature-weighted scheme for saturation vapor pressure but this measure, together with a more effective WBF process, might already be too efficient at removing clouds as it introduces a negative cloud cover bias. We additionally explored the sensitivity of low-level cloud cover to the strength of surface heat fluxes; by increasing surface mixing, the observed cloud cover and cloud phase bias could also be reduced. As ECHAM6 already mixes too strongly in the Arctic regions, it is questionable if one can physically justify it to increase mixing even further.
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Stevens, Robin G., Katharina Loewe, Christopher Dearden, Antonios Dimitrelos, Anna Possner, Gesa K. Eirund, Tomi Raatikainen, et al. "A model intercomparison of CCN-limited tenuous clouds in the high Arctic." Atmospheric Chemistry and Physics 18, no. 15 (August 8, 2018): 11041–71. http://dx.doi.org/10.5194/acp-18-11041-2018.
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Abstract. We perform a model intercomparison of summertime high Arctic (> 80∘ N) clouds observed during the 2008 Arctic Summer Cloud Ocean Study (ASCOS) campaign, when observed cloud condensation nuclei (CCN) concentrations fell below 1 cm−3. Previous analyses have suggested that at these low CCN concentrations the liquid water content (LWC) and radiative properties of the clouds are determined primarily by the CCN concentrations, conditions that have previously been referred to as the tenuous cloud regime. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). We test the sensitivities of the model results to different treatments of cloud droplet activation, including prescribed cloud droplet number concentrations (CDNCs) and diagnostic CCN activation based on either fixed aerosol concentrations or prognostic aerosol with in-cloud processing. There remains considerable diversity even in experiments with prescribed CDNCs and prescribed ice crystal number concentrations (ICNC). The sensitivity of mixed-phase Arctic cloud properties to changes in CDNC depends on the representation of the cloud droplet size distribution within each model, which impacts autoconversion rates. Our results therefore suggest that properly estimating aerosol–cloud interactions requires an appropriate treatment of the cloud droplet size distribution within models, as well as in situ observations of hydrometeor size distributions to constrain them. The results strongly support the hypothesis that the liquid water content of these clouds is CCN limited. For the observed meteorological conditions, the cloud generally did not collapse when the CCN concentration was held constant at the relatively high CCN concentrations measured during the cloudy period, but the cloud thins or collapses as the CCN concentration is reduced. The CCN concentration at which collapse occurs varies substantially between models. Only one model predicts complete dissipation of the cloud due to glaciation, and this occurs only for the largest prescribed ICNC tested in this study. Global and regional models with either prescribed CDNCs or prescribed aerosol concentrations would not reproduce these dissipation events. Additionally, future increases in Arctic aerosol concentrations would be expected to decrease the frequency of occurrence of such cloud dissipation events, with implications for the radiative balance at the surface. Our results also show that cooling of the sea-ice surface following cloud dissipation increases atmospheric stability near the surface, further suppressing cloud formation. Therefore, this suggests that linkages between aerosol and clouds, as well as linkages between clouds, surface temperatures, and atmospheric stability need to be considered for weather and climate predictions in this region.
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Achtert, P., M. Karlsson Andersson, F. Khosrawi, and J. Gumbel. "On the linkage between tropospheric and Polar Stratospheric clouds in the Arctic as observed by space–borne lidar." Atmospheric Chemistry and Physics 12, no. 8 (April 25, 2012): 3791–98. http://dx.doi.org/10.5194/acp-12-3791-2012.
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Abstract. The type of Polar stratospheric clouds (PSCs) as well as their temporal and spatial extent are important for the occurrence of heterogeneous reactions in the polar stratosphere. The formation of PSCs depends strongly on temperature. However, the mechanisms of the formation of solid PSCs are still poorly understood. Recent satellite studies of Antarctic PSCs have shown that their formation can be associated with deep-tropospheric clouds which have the ability to cool the lower stratosphere radiatively and/or adiabatically. In the present study, lidar measurements aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite were used to investigate whether the formation of Arctic PSCs can be associated with deep-tropospheric clouds as well. Deep-tropospheric cloud systems have a vertical extent of more than 6.5 km with a cloud top height above 7 km altitude. PSCs observed by CALIPSO during the Arctic winter 2007/2008 were classified according to their type (STS, NAT, or ice) and to the kind of underlying tropospheric clouds. Our analysis reveals that 172 out of 211 observed PSCs occurred in connection with tropospheric clouds. 72% of these 172 observed PSCs occurred above deep-tropospheric clouds. We also find that the type of PSC seems to be connected to the characteristics of the underlying tropospheric cloud system. During the Arctic winter 2007/2008 PSCs consisting of ice were mainly observed in connection with deep-tropospheric cloud systems while no ice PSC was detected above cirrus. Furthermore, we find no correlation between the occurrence of PSCs and the top temperature of tropospheric clouds. Thus, our findings suggest that Arctic PSC formation is connected to adiabatice cooling, i.e. dynamic effects rather than radiative cooling.
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Coopman, Quentin, Timothy J. Garrett, Jérôme Riedi, Sabine Eckhardt, and Andreas Stohl. "Effects of long-range aerosol transport on the microphysical properties of low-level liquid clouds in the Arctic." Atmospheric Chemistry and Physics 16, no. 7 (April 14, 2016): 4661–74. http://dx.doi.org/10.5194/acp-16-4661-2016.
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Abstract. The properties of low-level liquid clouds in the Arctic can be altered by long-range pollution transport to the region. Satellite, tracer transport model, and meteorological data sets are used here to determine a net aerosol–cloud interaction (ACInet) parameter that expresses the ratio of relative changes in cloud microphysical properties to relative variations in pollution concentrations while accounting for dry or wet scavenging of aerosols en route to the Arctic. For a period between 2008 and 2010, ACInet is calculated as a function of the cloud liquid water path, temperature, altitude, specific humidity, and lower tropospheric stability. For all data, ACInet averages 0.12 ± 0.02 for cloud-droplet effective radius and 0.16 ± 0.02 for cloud optical depth. It increases with specific humidity and lower tropospheric stability and is highest when pollution concentrations are low. Carefully controlling for meteorological conditions we find that the liquid water path of arctic clouds does not respond strongly to aerosols within pollution plumes. Or, not stratifying the data according to meteorological state can lead to artificially exaggerated calculations of the magnitude of the impacts of pollution on arctic clouds.
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Ehrlich, A., E. Bierwirth, M. Wendisch, J. F. Gayet, G. Mioche, A. Lampert, and J. Heintzenberg. "Cloud phase identification of Arctic boundary-layer clouds from airborne spectral reflection measurements: test of three approaches." Atmospheric Chemistry and Physics 8, no. 24 (December 16, 2008): 7493–505. http://dx.doi.org/10.5194/acp-8-7493-2008.
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Abstract. Arctic boundary-layer clouds were investigated with remote sensing and in situ instruments during the Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR) campaign in March and April 2007. The clouds formed in a cold air outbreak over the open Greenland Sea. Beside the predominant mixed-phase clouds pure liquid water and ice clouds were observed. Utilizing measurements of solar radiation reflected by the clouds three methods to retrieve the thermodynamic phase of the cloud are introduced and compared. Two ice indices IS and IP were obtained by analyzing the spectral pattern of the cloud top reflectance in the near infrared (1500–1800 nm wavelength) spectral range which is characterized by ice and water absorption. While IS analyzes the spectral slope of the reflectance in this wavelength range, IS utilizes a principle component analysis (PCA) of the spectral reflectance. A third ice index IA is based on the different side scattering of spherical liquid water particles and nonspherical ice crystals which was recorded in simultaneous measurements of spectral cloud albedo and reflectance. Radiative transfer simulations show that IS, IP and IA range between 5 to 80, 0 to 8 and 1 to 1.25 respectively with lowest values indicating pure liquid water clouds and highest values pure ice clouds. The spectral slope ice index IS and the PCA ice index IP are found to be strongly sensitive to the effective diameter of the ice crystals present in the cloud. Therefore, the identification of mixed-phase clouds requires a priori knowledge of the ice crystal dimension. The reflectance-albedo ice index IA is mainly dominated by the uppermost cloud layer (τ<1.5). Therefore, typical boundary-layer mixed-phase clouds with a liquid cloud top layer will be identified as pure liquid water clouds. All three methods were applied to measurements above a cloud field observed during ASTAR 2007. The comparison with independent in situ microphysical measurements shows the ability of the three approaches to identify the ice phase in Arctic boundary-layer clouds.
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Eliasson, Salomon, Karl-Göran Karlsson, and Ulrika Willén. "A simulator for the CLARA-A2 cloud climate data record and its application to assess EC-Earth polar cloudiness." Geoscientific Model Development 13, no. 1 (January 29, 2020): 297–314. http://dx.doi.org/10.5194/gmd-13-297-2020.
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Abstract. This paper describes a new satellite simulator for the CLARA-A2 climate data record (CDR). This simulator takes into account the variable skill in cloud detection in the CLARA-A2 CDR by using a different approach to other similar satellite simulators to emulate the ability to detect clouds. In particular, the paper describes three methods to filter out clouds from climate models undetectable by observations. The first method is comparable to the current simulators in the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP), since it relies on a single visible cloud optical depth at 550 nm (τc) threshold applied globally to delineate cloudy and cloud-free conditions. Methods two and three apply long/lat-gridded values separated by daytime and nighttime conditions. Method two uses gridded varying τc as opposed to method one, which uses just a τc threshold, and method three uses a cloud probability of detection (POD) depending on the model τc. The gridded POD values are from the CLARA-A2 validation study by Karlsson and Håkansson (2018). Methods two and three replicate the relative ease or difficulty for cloud retrievals depending on the region and illumination. They increase the cloud sensitivity where the cloud retrievals are relatively straightforward, such as over midlatitude oceans, and they decrease the sensitivity where cloud retrievals are notoriously tricky, such as where thick clouds may be inseparable from cold snow-covered surfaces, as well as in areas with an abundance of broken and small-scale cumulus clouds such as the atmospheric subsidence regions over the ocean. The simulator, together with the International Satellite Cloud Climatology Project (ISCCP) simulator of the COSP, is used to assess Arctic clouds in the EC-Earth climate model compared to the CLARA-A2 and ISCCP H-Series (ISCCP-H) CDRs. Compared to CLARA-A2, EC-Earth generally underestimates cloudiness in the Arctic. However, compared to ISCCP and its simulator, the opposite conclusion is reached. Based on EC-Earth, this paper shows that the simulated cloud mask of CLARA-A2, using method three, is more representative of the CDR than method one used for the ISCCP simulator. The simulator substantially improves the simulation of the CLARA-A2-detected clouds, especially in the polar regions, by accounting for the variable cloud detection skill over the year. The approach to cloud simulation based on the POD of clouds depending on their τc, location, and illumination is the preferred one as it reduces cloudiness over a range of cloud optical depths. Climate model comparisons with satellite-derived information can be significantly improved by this approach, mainly by reducing the risk of misinterpreting problems with satellite retrievals as cloudiness features. Since previous studies found that the CLARA-A2 CDR performs well in the Arctic during the summer months, and that method three is more representative than method one, the conclusion is that EC-Earth likely underestimates clouds in the Arctic summer.
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Bourdages, L., T. J. Duck, G. Lesins, J. R. Drummond, and E. W. Eloranta. "Physical properties of High Arctic tropospheric particles during winter." Atmospheric Chemistry and Physics Discussions 9, no. 2 (March 24, 2009): 7781–823. http://dx.doi.org/10.5194/acpd-9-7781-2009.
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Abstract. A climatology of particle properties in the wintertime High Arctic troposphere is constructed using measurements from a lidar and cloud radar located at Eureka, Nunavut Territory (80° N, 86° W). Four different particle groupings are considered: aerosols, mixed-phase clouds, ice clouds and boundary-layer ice crystals. Two-dimensional histograms of occurrence probabilities against depolarization and radar/lidar colour ratio, as well as their vertical distributions, are presented. The largest ice crystals originate from mixed-phase clouds, whereas the smallest are topographic blowing snow residuals in the boundary layer. Ice cloud crystals have depolarization and size decreasing with height. The depolarization trend is associated with the large ice crystal sub-population. Small crystals depolarize more than large ones in ice clouds at a given altitude, and show constant modal depolarization with height. Ice clouds in the mid-troposphere are sometimes observed to precipitate to the ground. Water clouds are constrained to the lower troposphere and are associated with the surface inversion layer depth. Aerosols are most abundant near the ground and are frequently mixed with the other particle types. The data are used to construct a classification chart for particle scattering in wintertime Arctic conditions.
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Shupe, Matthew D., Sergey Y. Matrosov, and Taneil Uttal. "Arctic Mixed-Phase Cloud Properties Derived from Surface-Based Sensors at SHEBA." Journal of the Atmospheric Sciences 63, no. 2 (February 1, 2006): 697–711. http://dx.doi.org/10.1175/jas3659.1.
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Abstract Arctic mixed-phase cloud macro- and microphysical properties are derived from a year of radar, lidar, microwave radiometer, and radiosonde observations made as part of the Surface Heat Budget of the Arctic Ocean (SHEBA) Program in the Beaufort Sea in 1997–98. Mixed-phase clouds occurred 41% of the time and were most frequent in the spring and fall transition seasons. These clouds often consisted of a shallow, cloud-top liquid layer from which ice particles formed and fell, although deep, multilayered mixed-phase cloud scenes were also observed. On average, individual cloud layers persisted for 12 h, while some mixed-phase cloud systems lasted for many days. Ninety percent of the observed mixed-phase clouds were 0.5–3 km thick, had a cloud base of 0–2 km, and resided at a temperature of −25° to −5°C. Under the assumption that the relatively large ice crystals dominate the radar signal, ice properties were retrieved from these clouds using radar reflectivity measurements. The annual average ice particle mean diameter, ice water content, and ice water path were 93 μm, 0.027 g m−3, and 42 g m−2, respectively. These values are all larger than those found in single-phase ice clouds at SHEBA. Vertically resolved cloud liquid properties were not retrieved; however, the annual average, microwave radiometer–derived liquid water path (LWP) in mixed-phase clouds was 61 g m−2. This value is larger than the average LWP observed in single-phase liquid clouds because the liquid water layers in the mixed-phase clouds tended to be thicker than those in all-liquid clouds. Although mixed-phase clouds were observed down to temperatures of about −40°C, the liquid fraction (ratio of LWP to total condensed water path) increased on average from zero at −24°C to one at −14°C. The observations show a range of ∼25°C at any given liquid fraction and a phase transition relationship that may change moderately with season.
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Libois, Quentin, Liviu Ivanescu, Jean-Pierre Blanchet, Hannes Schulz, Heiko Bozem, W. Richard Leaitch, Julia Burkart, et al. "Airborne observations of far-infrared upwelling radiance in the Arctic." Atmospheric Chemistry and Physics 16, no. 24 (December 20, 2016): 15689–707. http://dx.doi.org/10.5194/acp-16-15689-2016.
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Abstract. The first airborne measurements of the Far-InfraRed Radiometer (FIRR) were performed in April 2015 during the panarctic NETCARE campaign. Vertical profiles of spectral upwelling radiance in the range 8–50 µm were measured in clear and cloudy conditions from the surface up to 6 km. The clear sky profiles highlight the strong dependence of radiative fluxes to the temperature inversion typical of the Arctic. Measurements acquired for total column water vapour from 1.5 to 10.5 mm also underline the sensitivity of the far-infrared greenhouse effect to specific humidity. The cloudy cases show that optically thin ice clouds increase the cooling rate of the atmosphere, making them important pieces of the Arctic energy balance. One such cloud exhibited a very complex spatial structure, characterized by large horizontal heterogeneities at the kilometre scale. This emphasizes the difficulty of obtaining representative cloud observations with airborne measurements but also points out how challenging it is to model polar clouds radiative effects. These radiance measurements were successfully compared to simulations, suggesting that state-of-the-art radiative transfer models are suited to study the cold and dry Arctic atmosphere. Although FIRR in situ performances compare well to its laboratory performances, complementary simulations show that upgrading the FIRR radiometric resolution would greatly increase its sensitivity to atmospheric and cloud properties. Improved instrument temperature stability in flight and expected technological progress should help meet this objective. The campaign overall highlights the potential for airborne far-infrared radiometry and constitutes a relevant reference for future similar studies dedicated to the Arctic and for the development of spaceborne instruments.
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Morrison, H., J. A. Curry, M. D. Shupe, and P. Zuidema. "A New Double-Moment Microphysics Parameterization for Application in Cloud and Climate Models. Part II: Single-Column Modeling of Arctic Clouds." Journal of the Atmospheric Sciences 62, no. 6 (June 1, 2005): 1678–93. http://dx.doi.org/10.1175/jas3447.1.
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Abstract The new double-moment microphysics scheme described in Part I of this paper is implemented into a single-column model to simulate clouds and radiation observed during the period 1 April–15 May 1998 of the Surface Heat Budget of the Arctic (SHEBA) and First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment–Arctic Clouds Experiment (FIRE–ACE) field projects. Mean predicted cloud boundaries and total cloud fraction compare reasonably well with observations. Cloud phase partitioning, which is crucial in determining the surface radiative fluxes, is fairly similar to ground-based retrievals. However, the fraction of time that liquid is present in the column is somewhat underpredicted, leading to small biases in the downwelling shortwave and longwave radiative fluxes at the surface. Results using the new scheme are compared to parallel simulations using other microphysics parameterizations of varying complexity. The predicted liquid water path and cloud phase is significantly improved using the new scheme relative to a single-moment parameterization predicting only the mixing ratio of the water species. Results indicate that a realistic treatment of cloud ice number concentration (prognosing rather than diagnosing) is needed to simulate arctic clouds. Sensitivity tests are also performed by varying the aerosol size, solubility, and number concentration to explore potential cloud–aerosol–radiation interactions in arctic stratus.
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Costa, Anja, Jessica Meyer, Armin Afchine, Anna Luebke, Gebhard Günther, James R. Dorsey, Martin W. Gallagher, et al. "Classification of Arctic, midlatitude and tropical clouds in the mixed-phase temperature regime." Atmospheric Chemistry and Physics 17, no. 19 (October 13, 2017): 12219–38. http://dx.doi.org/10.5194/acp-17-12219-2017.
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Abstract. The degree of glaciation of mixed-phase clouds constitutes one of the largest uncertainties in climate prediction. In order to better understand cloud glaciation, cloud spectrometer observations are presented in this paper, which were made in the mixed-phase temperature regime between 0 and −38 °C (273 to 235 K), where cloud particles can either be frozen or liquid. The extensive data set covers four airborne field campaigns providing a total of 139 000 1 Hz data points (38.6 h within clouds) over Arctic, midlatitude and tropical regions. We develop algorithms, combining the information on number concentration, size and asphericity of the observed cloud particles to classify four cloud types: liquid clouds, clouds in which liquid droplets and ice crystals coexist, fully glaciated clouds after the Wegener–Bergeron–Findeisen process and clouds where secondary ice formation occurred. We quantify the occurrence of these cloud groups depending on the geographical region and temperature and find that liquid clouds dominate our measurements during the Arctic spring, while clouds dominated by the Wegener–Bergeron–Findeisen process are most common in midlatitude spring. The coexistence of liquid water and ice crystals is found over the whole mixed-phase temperature range in tropical convective towers in the dry season. Secondary ice is found at midlatitudes at −5 to −10 °C (268 to 263 K) and at higher altitudes, i.e. lower temperatures in the tropics. The distribution of the cloud types with decreasing temperature is shown to be consistent with the theory of evolution of mixed-phase clouds. With this study, we aim to contribute to a large statistical database on cloud types in the mixed-phase temperature regime.
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Bourdages, L., T. J. Duck, G. Lesins, J. R. Drummond, and E. W. Eloranta. "Physical properties of High Arctic tropospheric particles during winter." Atmospheric Chemistry and Physics 9, no. 18 (September 21, 2009): 6881–97. http://dx.doi.org/10.5194/acp-9-6881-2009.
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Abstract. A climatology of particle scattering properties in the wintertime High Arctic troposphere, including vertical distributions and effective radii, is presented. The measurements were obtained using a lidar and cloud radar located at Eureka, Nunavut Territory (80° N, 86° W). Four different particle groupings are considered: boundary-layer ice crystals, ice clouds, mixed-phase clouds, and aerosols. Two-dimensional histograms of occurrence probabilities against depolarization, radar/lidar colour ratio and height are given. Colour ratios are related to particle minimum dimensions (i.e., widths rather than lengths) using a Mie scattering model. Ice cloud crystals have effective radii spanning 25–220 µm, with larger particles observed at lower altitudes. Topographic blowing snow residuals in the boundary layer have the smallest crystals at 15–70 µm. Mixed-phase clouds have water droplets and ice crystal precipitation in the 5–40 µm and 40–220 µm ranges, respectively. Ice cloud crystals have depolarization decreasing with height. The depolarization trend is associated with the large ice crystal sub-population. Small crystals depolarize more than large ones in ice clouds at a given altitude, and show constant modal depolarization with height. Ice clouds in the mid-troposphere are sometimes observed to precipitate to the ground. Water clouds are constrained to the lower troposphere (0.5–3.5 km altitude). Aerosols are most abundant near the ground and are frequently mixed with the other particle types. The data are used to construct a classification chart for particle scattering in wintertime Arctic conditions.
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Tietze, K., J. Riedi, A. Stohl, and T. J. Garrett. "Space-based evaluation of interactions between pollution plumes and low-level Arctic clouds during the spring and summer of 2008." Atmospheric Chemistry and Physics Discussions 10, no. 11 (November 26, 2010): 29113–52. http://dx.doi.org/10.5194/acpd-10-29113-2010.
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Abstract. This study explores the indirect effects of anthropogenic and biomass burning aerosols on Arctic clouds by co-locating a combination of MODIS and POLDER cloud products with output from the FLEXPART tracer transport model. During the activities of the International Polar Year for the Spring and Summer of 2008, we find a high sensitivity of Arctic cloud radiative properties to both anthropogenic and biomass burning pollution plumes, particularly at air temperatures near freezing or potential temperatures near 286 K. However, the sensitivity is much lower at both colder and warmer temperatures, likely due increases in the wet scavenging of cloud condensation nuclei: the pollution plumes remain but the component that influences clouds has been removed along transport pathways. The analysis shows that, independent of temperature, cloud optical depth is approximately four times more sensitive to changes in pollution levels than is cloud effective radius. This suggests that some form of feedback mechanism amplifies the radiative response of Arctic clouds to pollution through changes in cloud liquid water path.
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Achtert, Peggy, Ewan J. O'Connor, Ian M. Brooks, Georgia Sotiropoulou, Matthew D. Shupe, Bernhard Pospichal, Barbara J. Brooks, and Michael Tjernström. "Properties of Arctic liquid and mixed-phase clouds from shipborne Cloudnet observations during ACSE 2014." Atmospheric Chemistry and Physics 20, no. 23 (December 4, 2020): 14983–5002. http://dx.doi.org/10.5194/acp-20-14983-2020.
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Abstract. This study presents Cloudnet retrievals of Arctic clouds from measurements conducted during a 3-month research expedition along the Siberian shelf during summer and autumn 2014. During autumn, we find a strong reduction in the occurrence of liquid clouds and an increase for both mixed-phase and ice clouds at low levels compared to summer. About 80 % of all liquid clouds observed during the research cruise show a liquid water path below the infrared black body limit of approximately 50 g m−2. The majority of mixed-phase and ice clouds had an ice water path below 20 g m−2. Cloud properties are analysed with respect to cloud-top temperature and boundary layer structure. Changes in these parameters have little effect on the geometric thickness of liquid clouds while mixed-phase clouds during warm-air advection events are generally thinner than when such events were absent. Cloud-top temperatures are very similar for all mixed-phase clouds. However, more cases of lower cloud-top temperature were observed in the absence of warm-air advection. Profiles of liquid and ice water content are normalized with respect to cloud base and height. For liquid water clouds, the liquid water content profile reveals a strong increase with height with a maximum within the upper quarter of the clouds followed by a sharp decrease towards cloud top. Liquid water content is lowest for clouds observed below an inversion during warm-air advection events. Most mixed-phase clouds show a liquid water content profile with a very similar shape to that of liquid clouds but with lower maximum values during events with warm air above the planetary boundary layer. The normalized ice water content profiles in mixed-phase clouds look different from those of liquid water content. They show a wider range in maximum values with the lowest ice water content for clouds below an inversion and the highest values for clouds above or extending through an inversion. The ice water content profile generally peaks at a height below the peak in the liquid water content profile – usually in the centre of the cloud, sometimes closer to cloud base, likely due to particle sublimation as the crystals fall through the cloud.
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Knudsen, Erlend M., Bernd Heinold, Sandro Dahlke, Heiko Bozem, Susanne Crewell, Irina V. Gorodetskaya, Georg Heygster, et al. "Meteorological conditions during the ACLOUD/PASCAL field campaign near Svalbard in early summer 2017." Atmospheric Chemistry and Physics 18, no. 24 (December 18, 2018): 17995–8022. http://dx.doi.org/10.5194/acp-18-17995-2018.
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Abstract. The two concerted field campaigns, Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL), took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL) and a tethered balloon, as well as ground-based stations. Here, we present the synoptic development during the 35-day period of the campaigns, using near-surface and upper-air meteorological observations, as well as operational satellite, analysis, and reanalysis data. Over the campaign period, short-term synoptic variability was substantial, dominating over the seasonal cycle. During the first campaign week, cold and dry Arctic air from the north persisted, with a distinct but seasonally unusual cold air outbreak. Cloudy conditions with mostly low-level clouds prevailed. The subsequent 2 weeks were characterized by warm and moist maritime air from the south and east, which included two events of warm air advection. These synoptical disturbances caused lower cloud cover fractions and higher-reaching cloud systems. In the final 2 weeks, adiabatically warmed air from the west dominated, with cloud properties strongly varying within the range of the two other periods. Results presented here provide synoptic information needed to analyze and interpret data of upcoming studies from ACLOUD/PASCAL, while also offering unprecedented measurements in a sparsely observed region.
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Gallegos, Sonia C., Jeffrey D. Hawkins, and Chiu Fu Cheng. "Cloud screening in AVHRR digital data over Arctic regions." Annals of Glaciology 17 (1993): 386–90. http://dx.doi.org/10.1017/s0260305500013148.
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A cloud screening method initially generated to mask cloud contaminated pixels over the ocean in visible/infrared imagery, has been revised and adapted to detect clouds over Arctic regions with encouraging results. Although the method is quite successful in eliminating very cold clouds, it underestimates low level clouds. However, this does not appear to interfere with monitoring of ice related features such as leads or the ice edge in Advanced Very High Resolution Radiometer (AVHRR) scenes. The method uses: a multiple-band approach to produce signatures not readily available in single channel data, an edge detection/dilation technique to locate features in the clouds and to join isolated edges, and a polygon identification technique to remove noise in the form of isolated pixels and separate clear regions from cloud contaminated areas. The method has been tested over a limited set of data with consistent results. Initial evaluation of the usefulness of this cloud-detection algorithm in data-fusion experiments indicate a potential in locating areas in AVHRR data which are cloud contaminated and which could yield a far superior representation of the ice features if replaced with data from a different sensor such as the Special Sensor Microwave/lmager (SSM/I).
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Gallegos, Sonia C., Jeffrey D. Hawkins, and Chiu Fu Cheng. "Cloud screening in AVHRR digital data over Arctic regions." Annals of Glaciology 17 (1993): 386–90. http://dx.doi.org/10.3189/s0260305500013148.
Full textAbstract:
A cloud screening method initially generated to mask cloud contaminated pixels over the ocean in visible/infrared imagery, has been revised and adapted to detect clouds over Arctic regions with encouraging results. Although the method is quite successful in eliminating very cold clouds, it underestimates low level clouds. However, this does not appear to interfere with monitoring of ice related features such as leads or the ice edge in Advanced Very High Resolution Radiometer (AVHRR) scenes. The method uses: a multiple-band approach to produce signatures not readily available in single channel data, an edge detection/dilation technique to locate features in the clouds and to join isolated edges, and a polygon identification technique to remove noise in the form of isolated pixels and separate clear regions from cloud contaminated areas. The method has been tested over a limited set of data with consistent results. Initial evaluation of the usefulness of this cloud-detection algorithm in data-fusion experiments indicate a potential in locating areas in AVHRR data which are cloud contaminated and which could yield a far superior representation of the ice features if replaced with data from a different sensor such as the Special Sensor Microwave/lmager (SSM/I).
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Mauritsen, T., J. Sedlar, M. Tjernström, C. Leck, M. Martin, M. Shupe, S. Sjogren, et al. "An Arctic CCN-limited cloud-aerosol regime." Atmospheric Chemistry and Physics 11, no. 1 (January 10, 2011): 165–73. http://dx.doi.org/10.5194/acp-11-165-2011.
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Abstract. On average, airborne aerosol particles cool the Earth's surface directly by absorbing and scattering sunlight and indirectly by influencing cloud reflectivity, life time, thickness or extent. Here we show that over the central Arctic Ocean, where there is frequently a lack of aerosol particles upon which clouds may form, a small increase in aerosol loading may enhance cloudiness thereby likely causing a climatologically significant warming at the ice-covered Arctic surface. Under these low concentration conditions cloud droplets grow to drizzle sizes and fall, even in the absence of collisions and coalescence, thereby diminishing cloud water. Evidence from a case study suggests that interactions between aerosol, clouds and precipitation could be responsible for attaining the observed low aerosol concentrations.
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Tjernström, M., C. Leck, C. E. Birch, J. W. Bottenheim, B. J. Brooks, I. M. Brooks, L. Bäcklin, et al. "The Arctic Summer Cloud Ocean Study (ASCOS): overview and experimental design." Atmospheric Chemistry and Physics 14, no. 6 (March 19, 2014): 2823–69. http://dx.doi.org/10.5194/acp-14-2823-2014.
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Abstract. The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol–cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007–2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87°21' N, 01°29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations, and the balance between local and remote aerosols sources remains open. Lack of cloud condensation nuclei (CCN) was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets.
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Kretzschmar, Jan, Johannes Stapf, Daniel Klocke, Manfred Wendisch, and Johannes Quaas. "Employing airborne radiation and cloud microphysics observations to improve cloud representation in ICON at kilometer-scale resolution in the Arctic." Atmospheric Chemistry and Physics 20, no. 21 (November 9, 2020): 13145–65. http://dx.doi.org/10.5194/acp-20-13145-2020.
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Abstract. Clouds play a potentially important role in Arctic climate change but are poorly represented in current atmospheric models across scales. To improve the representation of Arctic clouds in models, it is necessary to compare models to observations to consequently reduce this uncertainty. This study compares aircraft observations from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign around Svalbard, Norway, in May–June 2017 and simulations using the ICON (ICOsahedral Non-hydrostatic) model in its numerical weather prediction (NWP) setup at 1.2 km horizontal resolution. By comparing measurements of solar and terrestrial irradiances during ACLOUD flights to the respective properties in ICON, we showed that the model systematically overestimates the transmissivity of the mostly liquid clouds during the campaign. This model bias is traced back to the way cloud condensation nuclei (CCN) get activated into cloud droplets in the two-moment bulk microphysical scheme used in this study. This process is parameterized as a function of grid-scale vertical velocity in the microphysical scheme used, but in-cloud turbulence cannot be sufficiently resolved at 1.2 km horizontal resolution in Arctic clouds. By parameterizing subgrid-scale vertical motion as a function of turbulent kinetic energy, we are able to achieve a more realistic CCN activation into cloud droplets. Additionally, we showed that by scaling the presently used CCN activation profile, the hydrometeor number concentration could be modified to be in better agreement with ACLOUD observations in our revised CCN activation parameterization. This consequently results in an improved representation of cloud optical properties in our ICON simulations.
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Chan, Mark Aaron, and Josefino C. Comiso. "Arctic Cloud Characteristics as Derived from MODIS, CALIPSO, and CloudSat." Journal of Climate 26, no. 10 (May 8, 2013): 3285–306. http://dx.doi.org/10.1175/jcli-d-12-00204.1.
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Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), and CloudSat Cloud Profiling Radar (CPR) set of sensors, all in the Afternoon Constellation (A-Train), has been regarded as among the most powerful tools for characterizing the cloud cover. While providing good complementary information, the authors also observed that, at least for the Arctic region, the different sensors provide significantly different statistics about cloud cover characteristics. Data in 2007 and 2010 were analyzed, and the annual averages of cloud cover in the Arctic region were found to be 66.8%, 78.4%, and 63.3% as derived from MODIS, CALIOP, and CPR, respectively. A large disagreement between MODIS and CALIOP over sea ice and Greenland is observed, with a cloud percentage difference of 30.9% and 31.5%, respectively. In the entire Arctic, the average disagreement between MODIS and CALIOP increased from 13.1% during daytime to 26.7% during nighttime. Furthermore, the MODIS cloud mask accuracy has a high seasonal dependence, in that MODIS–CALIOP disagreement is the lowest during summertime at 10.7% and worst during winter at 28.0%. During nighttime the magnitude of the bias is higher because cloud detection is limited to the use of infrared bands. The clouds not detected by MODIS are typically low-level (top height <2 km) and high-level clouds (top height >6 km) and, especially, those that are geometrically thin (<2 km). Geometrically thin clouds (<2 km) accounted for about 95.5% of all clouds that CPR misses. As reported in a similar study, very low and thin clouds (<0.3 km) over sea ice that are detected by MODIS are sometimes not observed by CPR and misclassified by CALIOP.
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Zamora, L. M., R. A. Kahn, M. J. Cubison, G. S. Diskin, J. L. Jimenez, Y. Kondo, G. M. McFarquhar, et al. "Aircraft-measured indirect cloud effects from biomass burning smoke in the Arctic and subarctic." Atmospheric Chemistry and Physics 16, no. 2 (January 21, 2016): 715–38. http://dx.doi.org/10.5194/acp-16-715-2016.
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Abstract. The incidence of wildfires in the Arctic and subarctic is increasing; in boreal North America, for example, the burned area is expected to increase by 200–300 % over the next 50–100 years, which previous studies suggest could have a large effect on cloud microphysics, lifetime, albedo, and precipitation. However, the interactions between smoke particles and clouds remain poorly quantified due to confounding meteorological influences and remote sensing limitations. Here, we use data from several aircraft campaigns in the Arctic and subarctic to explore cloud microphysics in liquid-phase clouds influenced by biomass burning. Median cloud droplet radii in smoky clouds were ∼ 40–60 % smaller than in background clouds. Based on the relationship between cloud droplet number (Nliq) and various biomass burning tracers (BBt) across the multi-campaign data set, we calculated the magnitude of subarctic and Arctic smoke aerosol–cloud interactions (ACIs, where ACI = (1∕3) × dln(Nliq)∕dln(BBt)) to be ∼ 0.16 out of a maximum possible value of 0.33 that would be obtained if all aerosols were to nucleate cloud droplets. Interestingly, in a separate subarctic case study with low liquid water content ( ∼ 0.02 g m−3) and very high aerosol concentrations (2000–3000 cm−3) in the most polluted clouds, the estimated ACI value was only 0.05. In this case, competition for water vapor by the high concentration of cloud condensation nuclei (CCN) strongly limited the formation of droplets and reduced the cloud albedo effect, which highlights the importance of cloud feedbacks across scales. Using our calculated ACI values, we estimate that the smoke-driven cloud albedo effect may decrease local summertime short-wave radiative flux by between 2 and 4 W m−2 or more under some low and homogeneous cloud cover conditions in the subarctic, although the changes should be smaller in high surface albedo regions of the Arctic. We lastly explore evidence suggesting that numerous northern-latitude background Aitken particles can interact with combustion particles, perhaps impacting their properties as cloud condensation and ice nuclei.
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English, Jason M., Jennifer E. Kay, Andrew Gettelman, Xiaohong Liu, Yong Wang, Yuying Zhang, and Helene Chepfer. "Contributions of Clouds, Surface Albedos, and Mixed-Phase Ice Nucleation Schemes to Arctic Radiation Biases in CAM5." Journal of Climate 27, no. 13 (July 2014): 5174–97. http://dx.doi.org/10.1175/jcli-d-13-00608.1.
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The Arctic radiation balance is strongly affected by clouds and surface albedo. Prior work has identified Arctic cloud liquid water path (LWP) and surface radiative flux biases in the Community Atmosphere Model, version 5 (CAM5), and reductions to these biases with improved mixed-phase ice nucleation schemes. Here, CAM5 net top-of-atmosphere (TOA) Arctic radiative flux biases are quantified along with the contributions of clouds, surface albedos, and new mixed-phase ice nucleation schemes to these biases. CAM5 net TOA all-sky shortwave (SW) and outgoing longwave radiation (OLR) fluxes are generally within 10 W m−2 of Clouds and the Earth’s Radiant Energy System Energy Balanced and Filled (CERES-EBAF) observations. However, CAM5 has compensating SW errors: Surface albedos over snow are too high while cloud amount and LWP are too low. Use of a new CAM5 Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar simulator that corrects an error in the treatment of snow crystal size confirms insufficient cloud amount in CAM5 year-round. CAM5 OLR is too low because of low surface temperature in winter, excessive atmospheric water vapor in summer, and excessive cloud heights year-round. Simulations with two new mixed-phase ice nucleation schemes—one based on an empirical fit to ice nuclei observations and one based on classical nucleation theory with prognostic ice nuclei—improve surface climate in winter by increasing cloud amount and LWP. However, net TOA and surface radiation biases remain because of increases in midlevel clouds and a persistent deficit in cloud LWP. These findings highlight challenges with evaluating and modeling Arctic cloud, radiation, and climate processes.