Shortwave aerosol optical depth of Arctic haze measured on board the NOAA WP-3D during AGASP-II, April 1986

Dutton, Ellsworth G; Deluisi, John; Herbert, Gary A.

doi:10.1007/bf00052825

Cited by 21 publications

(15 citation statements)

References 8 publications

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“…Air in the vicinity of Svalbard in early April was significantly less turbid than air over the Beaufort Sea region during the third week of the field campaign in April 2009. Despite relatively high values of total light extinction, black carbon concentrations were moderately low during the flights (Figure 7(c,f) in [25]) compared with historical observations [61]. Similar measurements of BC were obtained from a series of flights during the Arctic Gas and Aerosol Sampling Program (AGASP) in 1983 and 1986 [62].…”

Section: Aerosol Load In the Central Arcticsupporting

confidence: 65%

The Spring-Time Boundary Layer in the Central Arctic Observed during PAMARCMiP 2009

et al. 2012

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Abstract:The Arctic atmospheric boundary layer (AABL) in the central Arctic was characterized by dropsonde, lidar, ice thickness and airborne in situ measurements during Above sea ice, a low AABL top, low near-surface temperatures, strong surface-based temperature inversions and an increase of moisture with altitude were observed. AABL properties and particle concentrations were modified by a frontal system, allowing vertical mixing with the free atmosphere. Above areas with many leads, the potential temperature decreased with height in the lowest 50 m and was nearly constant above, up to an altitude of 100-200 m, indicating vertical mixing. The increase of the backscatter coefficient towards the surface was high. Above sea ice with few refrozen leads, the stably stratified boundary layer extended up to 200-300 m altitude. It was characterized by low specific humidity and a smaller increase of the backscatter coefficient towards the surface.

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Section: Aerosol Load In the Central Arcticsupporting

confidence: 65%

The Spring-Time Boundary Layer in the Central Arctic Observed during PAMARCMiP 2009

et al. 2012

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“…We use a liquid water cloud with lognormal droplet size distribution, with base height and geometrical thickness both 500 m. Commensurate with the changes in r e , changes in droplet concentration were accounted for when computing the cloud single scattering albedo, asymmetry factor, and volume extinction coefficients. Consistent with observations of significant Arctic haze opacity at aircraft altitudes [e.g., Dutton et al, 1989], which indicate that Arctic haze is not confined to the boundary layer, we specify the aerosol burden as well mixed in the lower 3 km. These same aircraft studies also indicate a wide variety of aerosol layering, both above and below cloud, as opposed to a simple well-mixed scenario.…”

supporting

confidence: 55%

Expected magnitude of the aerosol shortwave indirect effect in springtime Arctic liquid water clouds

Lubin

Vogelmann

2007

Geophysical Research Letters

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[1] Radiative transfer simulations are used to assess the expected magnitude of the diurnally-averaged shortwave aerosol first indirect effect in Arctic liquid water clouds, in the context of recently discovered longwave surface heating of order 3 to 8 W m À2 by this same aerosol effect detected at the Barrow, Alaska, ARM Site. We find that during March and April, shortwave surface cooling by the first indirect effect is comparable in magnitude to the longwave surface heating. During May and June, the shortwave surface cooling exceeds the longwave heating. Due to multiple reflection of photons between the snow or sea ice surface and cloud base, the shortwave first indirect effect may be easier to detect in surface radiation measurements than from space. Citation: Lubin, D., and A. M. Vogelmann [2] The search for indirect aerosol effects has taken a unique turn in the Arctic, in emphasizing longwave radiation before shortwave [Garrett et al., 2002]. This is in part due to the greater importance of longwave radiation relative to shortwave at high latitudes [e.g., Intrieri et al., 2002], and also due to the availability of high quality longwave spectral radiation measurements in the Arctic from which the indirect effect can be readily identified [Garrett and Zhao, 2006;Lubin and Vogelmann, 2006]. To date, the deployment in the high Arctic of advanced longwave spectroradiometers [Turner et al., 2003;Knuteson et al., 2004] has not been matched by similar instrumentation that cover the visible through near-IR wavelengths at which clouds both absorb and scatter radiation. We therefore do not yet have a comparable spectral capability in the Arctic to rigorously identify and quantify the shortwave aerosol for all applicable liquid water paths (LWP), as has been done recently for the longwave. The purpose of this study is to demonstrate the expected relative importance of the shortwave and longwave manifestations of the aerosol first indirect effect on the springtime Arctic radiative energy balance.[3] Garrett and Zhao [2006] analyzed Fourier Transform Infrared (FTIR) spectroradiometer data from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program North Slope of Alaska (NSA) site at Barrow, Alaska, and found that the presence of Arctic ''haze'' -an anthropogenic aerosol primarily of Eurasian industrial origin trapped in the Arctic winter and spring troposphere [Barrie, 1986] -reduces the mean effective droplet radius r e of Arctic liquid water clouds by 3 mm. This results in an increase in mean cloud emissivity for all LWP < 80 g m À2 such that downwelling longwave radiation at the Arctic surface increases by 3.3 to 5.5 W m À2 , with all other meteorological variables held constant. Lubin and Vogelmann [2006] performed a similar analysis of NSA FTIR spectroradiometer data, and found a reduction in mean cloud droplet effective radius of 4 mm in Arctic haze relative to background aerosol, and found an increase of 8.2 W m À2 in the downwelling surface longwave flux under liquid water clouds in the ...

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“…This is in agreement with cluster 3 of the ASTAR database. The determined mean values for cluster 2 are in the range of AOD measurements reported from other authors for high Arctic aerosol loadings (Shaw, 1975;Freud, 1983;Dutton et al, 1989;Leiterer et al, 1992;Herber et al, 2002;Eneroth et al, 2003).…”

Section: Long-term Time-series From Koldewey and Zeppelin Mountainsupporting

confidence: 71%

“…For example, Clarke et al (1984) determined the mean scattering coefficient and absorption coefficient (at 550 nm) for haze layers of around 0.016 km −1 and 0.0026 km −1 , respectively. Dutton et al (1989) reported extinction values (500 nm) for layers with high aerosol loadings from less than 0.005 to 0.2 km −1 and typical values were around 0.03 km −1 . Leiterer et al (1997) calculated similar extinction coefficients for haze layers.…”

Section: Vertical Time-series During Astarmentioning

confidence: 99%

“…For a month each spring during 1983, 1986, 1989 and 1991, an aircraft was operated in the Arctic covering the region from Alaska to Norway to study Arctic haze, air chemistry and solar radiation issues (e.g. Clarke et al, 1984;Raatz and Schnell, 1984;Radke et al, 1984;Dutton et al, 1989;Parungo et al, 1990). Three German-Russian measuring campaigns during the spring and summer of 1994 and spring of 1995 provided an opportunity to investigate the pollution of the Arctic atmosphere (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Interpretation of Arctic aerosol properties using cluster analysis applied to observations in the Svalbard area

Treffeisen

Herber

Ström

et al. 2004

Tellus B: Chemical and Physical Meteorology

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A B S T R A C T Atmospheric aerosols play an important role in global climate change, directly through radiative forcing and indirectly through their effect on cloud properties. Numerous measurements have been performed in the last three decades in order to characterize polar aerosols. Information about aerosol characteristics is needed to calculate induced changes in the Earth's heat balance. However, this forcing is highly variable in space and time. Accurate quantification of forcing by aerosols will require combined efforts, assimilating information from different sources such as satellite, aircraft and surface-based observations. Adding to the complexity of the problem is that the measurements themselves are often not directly comparable as they vary in spatial/temporal resolution and in the basic properties of the aerosol that they measure. Therefore it is desirable to close the gap between the differences in temporal and spatial resolution and coverage among the observational approaches. In order to keep the entire information content and to treat aerosol variability in a consistent and manageable way an approach has to be achieved which enables one to combine these data. This study presents one possibility for linking together a complex Arctic aerosol data set in terms of parameters, timescale and place of measurement as well as meteorological parameters. A cluster analysis was applied as a pattern recognition technique. The data set is classified in clusters and expressed in terms of mean statistical values, which represent the entire database and its variation. For this study, different time-series of microphysical, optical and chemical aerosol parameters as well as meteorological parameters were analysed. The database was obtained during an extensive aerosol measurement campaign, the ASTAR 2000 (Arctic Study of Tropospheric Aerosol and Radiation) field campaign, with coordinated simultaneous ground-based and airborne measurements in the vicinity of Spitsbergen (Svalbard). Furthermore, longterm measurements at two ground-based sites situated at different altitudes were incorporated into the analysis. The approach presented in this study allows the necessary linking of routine long-term measurements with short-term extensive observations. It also involves integration of intermittent vertical aerosol profile measurements. This is useful for many applications, especially in climate research where the required data coverage is large.

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Shortwave aerosol optical depth of Arctic haze measured on board the NOAA WP-3D during AGASP-II, April 1986

Cited by 21 publications

References 8 publications

The Spring-Time Boundary Layer in the Central Arctic Observed during PAMARCMiP 2009

The Spring-Time Boundary Layer in the Central Arctic Observed during PAMARCMiP 2009

Expected magnitude of the aerosol shortwave indirect effect in springtime Arctic liquid water clouds

Interpretation of Arctic aerosol properties using cluster analysis applied to observations in the Svalbard area

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