Clouds at Arctic Atmospheric Observatories. Part I Shupe, Matthew D.; Walden, Von P.; Eloranta, Edwin ...
Journal of applied meteorology and climatology,
03/2011, Letnik:
50, Številka:
3
Journal Article
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Cloud observations over the past decade from six Arctic atmospheric observatories are investigated to derive estimates of cloud occurrence fraction, vertical distribution, persistence in time, ...diurnal cycle, and boundary statistics. Each observatory has some combination of cloud lidar, radar, ceilometer, and/or interferometer for identifying and characterizing clouds. By optimally combining measurements from these instruments, it is found that annual cloud occurrence fractions are 58%–83% at the Arctic observatories. There is a clear annual cycle wherein clouds are least frequent in the winter and most frequent in the late summer and autumn. Only in Eureka, Nunavut, Canada, is the annual cycle shifted such that the annual minimum is in the spring with the maximum in the winter. Intersite monthly variability is typically within 10%–15% of the all-site average. Interannual variability at specific sites is less than 13% for any given month and, typically, is less than 3% for annual total cloud fractions. Low-level clouds are most persistent at the observatories. The median cloud persistence for all observatories is 3–5 h; however, 5% of cloud systems at far western Arctic sites are observed to occur for longer than 100 consecutive hours. Weak diurnal variability in cloudiness is observed at some sites, with a daily minimum in cloud occurrence near solar noon for those seasons for which the sun is above the horizon for at least part of the day.
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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Over the Arctic Ocean, little is known on cloud-generated buoyant overturning vertical motions within mixed-phase stratocumulus clouds. Characteristics of such motions are important for understanding ...the diabatic processes associated with the vertical motions, the lifetime of the cloud layer and its micro- and macrophysical characteristics. In this study, we exploit a suite of surface-based remote sensors over the high-Arctic sea ice during a weeklong period of persistent stratocumulus in August 2008 to derive the in-cloud vertical motion characteristics. In-cloud vertical velocity skewness and variance profiles are found to be strikingly different from observations within lower-latitude stratocumulus, suggesting these Arctic mixed-phase clouds interact differently with the atmospheric thermodynamics (cloud tops extending above a stable temperature inversion base) and with a different coupling state between surface and cloud. We find evidence of cloud-generated vertical mixing below cloud base, regardless of surface–cloud coupling state, although a decoupled surface–cloud state occurred most frequently. Detailed case studies are examined, focusing on three levels within the cloud layer, where wavelet and power spectral analyses are applied to characterize the dominant temporal and horizontal scales associated with cloud-generated vertical motions. In general, we find a positively correlated vertical motion signal amongst vertical levels within the cloud and across the full cloud layer depth. The coherency is dependent upon other non-cloud controlled factors, such as larger, mesoscale weather passages and radiative shielding of low-level stratocumulus by one or more cloud layers above. Despite the coherency in vertical velocity across the cloud, the velocity variances were always weaker near cloud top, relative to cloud middle and base. Taken in combination with the skewness, variance and thermodynamic profile characteristics, we observe vertical motions near cloud top that behave differently than those from lower within the cloud layer. Spectral analysis indicates peak cloud-generated w variance timescales slowed only modestly during decoupled cases relative to coupled; horizontal wavelengths only slightly increased when transitioning from coupling to decoupling. The similarities in scales suggests that perhaps the dominant forcing for all cases is generated from the cloud layer, and it is not the surface forcing that characterizes the time- and space scales of in-cloud vertical velocity variance. This points toward the resilient nature of Arctic mixed-phase clouds to persist when characterized by thermodynamic regimes unique to the Arctic.
A novel method for classifying Arctic precipitation using ground based remote sensors is presented. Using differences in the spectral variation of microwave absorption and scattering properties of ...cloud liquid water and ice, this method can distinguish between different types of snowfall events depending on the presence or absence of condensed liquid water in the clouds that generate the precipitation. The classification reveals two distinct, primary regimes of precipitation over the Greenland Ice Sheet (GIS): one originating from fully glaciated ice clouds and the other from mixed-phase clouds. Five years of co-located, multi-instrument data from the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit (ICECAPS) are used to examine cloud and meteorological properties and patterns associated with each precipitation regime. The occurrence and accumulation of the precipitation regimes are identified and quantified. Cloud and precipitation observations from additional ICECAPS instruments illustrate distinct characteristics for each regime. Additionally, reanalysis products and back-trajectory analysis show different synoptic-scale forcings associated with each regime. Precipitation over the central GIS exhibits unique microphysical characteristics due to the high surface elevations as well as connections to specific large-scale flow patterns. Snowfall originating from the ice clouds is coupled to deep, frontal cloud systems advecting up and over the southeast Greenland coast to the central GIS. These events appear to be associated with individual storm systems generated by low pressure over Baffin Bay and Greenland lee cyclogenesis. Snowfall originating from mixed-phase clouds is shallower and has characteristics typical of supercooled cloud liquid water layers, and slowly propagates from the south and southwest of Greenland along a quiescent flow above the GIS.
We used wide-area surveys over 39 deg2 by the HerMES (Herschel Multi-tiered Extragalactic Survey) collaboration, performed with the Herschel
Observatory SPIRE multiwavelength camera, to estimate the ...low-redshift, 0.02 < z < 0.5, monochromatic luminosity functions (LFs) of galaxies at 250, 350 and 500 μm. Within this redshift interval, we detected 7087 sources in five independent sky areas, ∼40 per cent of which have spectroscopic redshifts, while for the remaining objects photometric redshifts were used. The SPIRE LFs in different fields did not show any field-to-field variations beyond the small differences to be expected from cosmic variance. SPIRE flux densities were also combined with Spitzer photometry and multiwavelength archival data to perform a complete spectral energy distribution fitting analysis of SPIRE detected sources to calculate precise k-corrections, as well as the bolometric infrared (IR; 8–1000 μm) LFs and their low-z evolution from a combination of statistical estimators. Integration of the latter prompted us to also compute the local luminosity density and the comoving star formation rate density (SFRD) for our sources, and to compare them with theoretical predictions of galaxy formation models. The LFs show significant and rapid luminosity evolution already at low redshifts, 0.02 < z < 0.2, with L
$_{\text{IR}}^{\ast } \propto (1+z)^{6.0\pm 0.4}$
and
$\Phi _{\text{IR}}^{\ast } \propto (1+z)^{-2.1\pm 0.4}$
, L
$_{250}^{\ast } \propto (1+z)^{5.3\pm 0.2}$
and
$\Phi _{250}^{\ast } \propto (1+z)^{-0.6\pm 0.4}$
estimated using the IR bolometric and the 250 μm LFs, respectively. Converting our IR LD estimate into an SFRD assuming a standard Salpeter initial mass function and including the unobscured contribution based on the UV dust-uncorrected emission from local galaxies, we estimate an SFRD scaling of SFRD0 + 0.08z, where SFRD0 ≃ (1.9 ± 0.03) × 10−2 M⊙ Mpc−3 is our total SFRD estimate at z ∼ 0.02.
Understanding the rapidly changing climate in the Arctic is limited by a lack of understanding of underlying strong feedback mechanisms that are specific to the Arctic. Progress in this field can ...only be obtained by process-level observations; this is the motivation for intensive ice-breaker-based campaigns such as the Arctic Summer Cloud-Ocean Study (ASCOS), described here. However, detailed field observations also have to be put in the context of the larger-scale meteorology, and short field campaigns have to be analysed within the context of the underlying climate state and temporal anomalies from this. To aid in the analysis of other parameters or processes observed during this campaign, this paper provides an overview of the synoptic-scale meteorology and its climatic anomaly during the ASCOS field deployment. It also provides a statistical analysis of key features during the campaign, such as key meteorological variables, the vertical structure of the lower troposphere and clouds, and energy fluxes at the surface. In order to assess the representativity of the ASCOS results, we also compare these features to similar observations obtained during three earlier summer experiments in the Arctic Ocean: the AOE-96, SHEBA and AOE-2001 expeditions. We find that these expeditions share many key features of the summertime lower troposphere. Taking ASCOS and the previous expeditions together, a common picture emerges with a large amount of low-level cloud in a well-mixed shallow boundary layer, capped by a weak to moderately strong inversion where moisture, and sometimes also cloud top, penetrate into the lower parts of the inversion. Much of the boundary-layer mixing is due to cloud-top cooling and subsequent buoyant overturning of the cloud. The cloud layer may, or may not, be connected with surface processes depending on the depths of the cloud and surface-based boundary layers and on the relative strengths of surface-shear and cloud-generated turbulence. The latter also implies a connection between the cloud layer and the free troposphere through entrainment at cloud top.
Snowfall is the major source of mass for the Greenland ice sheet (GrIS) but the spatial and temporal variability of snowfall and the connections between snowfall and mass balance have so far been ...inadequately quantified. By characterizing local atmospheric circulation and utilizing CloudSat spaceborne radar observations of snowfall, we provide a detailed spatial analysis of snowfall variability and its relationship to Greenland mass balance, presenting first-of-their-kind maps of daily spatial variability in snowfall from observations across Greenland. For identified regional atmospheric circulation patterns, we show that the spatial distribution and net mass input of snowfall vary significantly with the position and strength of surface cyclones. Cyclones west of Greenland driving southerly flow contribute significantly more snowfall than any other circulation regime, with each daily occurrence of the most extreme southerly circulation pattern contributing an average of 1.66 Gt of snow to the Greenland ice sheet. While cyclones east of Greenland, patterns with the least snowfall, contribute as little as 0.58 Gt each day. Above 2 km on the ice sheet where snowfall is inconsistent, extreme southerly patterns are the most significant mass contributors, with up to 1.20 Gt of snowfall above this elevation. This analysis demonstrates that snowfall over the interior of Greenland varies by up to a factor of 5 depending on regional circulation conditions. Using independent observations of mass changes made by the Gravity Recovery and Climate Experiment (GRACE), we verify that the largest mass increases are tied to the southerly regime with cyclones west of Greenland. For occurrences of the strongest southerly pattern, GRACE indicates a net mass increase of 1.29 Gt in the ice sheet accumulation zone (above 2 km elevation) compared to the 1.20 Gt of snowfall observed by CloudSat. This overall agreement suggests that the analytical approach presented here can be used to directly quantify snowfall mass contributions and their most significant drivers spatially across the GrIS. While previous research has implicated this same southerly regime in ablation processes during summer, this paper shows that ablation mass loss in this circulation regime is nearly an order of magnitude larger than the mass gain from associated snowfall. For daily occurrences of the southerly circulation regime, a mass loss of approximately 11 Gt is observed across the ice sheet despite snowfall mass input exceeding 1 Gt. By analyzing the spatial variability of snowfall and mass changes, this research provides new insight into connections between regional atmospheric circulation and GrIS mass balance.
A 10 year record of Arctic cloud fraction and radiative forcing has been generated using data collected at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska site and the nearby NOAA ...Barrow Observatory (BRW) from June 1998 to May 2008. The cloud fractions (CFs) derived from ARM radar‐lidar and ceilometer measurements increase significantly from March to May (0.57→0.84), remain relatively high (∼0.80–0.9) from May to October, and then decrease from November to the following March (0.8→0.57), having an annual average of 0.76. These CFs are comparable to those derived from ground‐based radar‐lidar observations during the Surface Heat Budget of the Arctic Ocean experiment and from satellite observations over the western Arctic regions. The monthly means of estimated clear‐sky and measured all‐sky shortwave (SW)‐down and longwave (LW)‐down fluxes at the two facilities are almost identical with the annual mean differences less than 1.6 Wm−2. Values of LW cloud radiative forcing (CRF) are minimum (6 Wm−2) in March, then increase monotonically to reach maximum (63 Wm−2) in August, then decrease continuously to the following March. The cycle of SW CRF mirrors its LW counterpart with the greatest negative impact occurring during the snow‐free months of July and August. On annual average, the negative SW CRFs and positive LW CRFs nearly cancel, resulting in annual average NET CRF of about 3.5 Wm−2 on the basis of the combined ARM and BRW analysis. Compared with other studies, we find that LW CRF does not change over the Arctic regions significantly, but NET CRFs change from negative to positive from Alaska to the Beaufort Sea, indicating that Barrow is at a critical latitude for neutral NET CRF. The sensitivity study has shown that LW CRFs increase with increasing cloud fraction, liquid water path, and radiating temperature with high positive correlations (0.8–0.9). Negative correlations are found for SW CRFs, but a strong positive correlation between SW CRF and surface albedo exists.
The temporal distributions of cloudiness, vertical distribution of cloud boundary heights, and occurrence of liquid phase in clouds are determined from radar and lidar data sets collected from ...October 1997 to October 1998 during the Surface Heat Budget of the Arctic Ocean (SHEBA) project. The radar/lidar combination was necessary for comprehensive cloud detection over a variety of physical conditions and is significantly more detailed (5–9 s temporal resolution, 30–40 m vertical resolution) than measurements made by surface observers or satellites. The combined measurements revealed that clouds were almost continuously present, with an annual average occurrence of 85%, and displayed an overall annual trend of a cloudier summer and clearer winter. A monthly averaged cloud occurrence maximum of 97% was observed in September and a minimum of 63% was observed in February. Monthly averaged lowest cloud base heights were between 0.25 and 1.0 km above ground level (agl) and monthly averaged highest cloud top heights were between 2.5 and 5.5 km agl, and displayed no significant seasonal variation. The number of cloud layers was typically 1 or 2, with the summer months tending to be multilayered. The lidar utilized depolarization ratios to detect liquid water; the percentage of lidar‐observed clouds containing liquid was 73% for the year. The least amount of liquid water phase was observed during December in 25% of the lidar‐detected clouds and the maximum was observed during July in 95% of the lidar‐detected clouds. Liquid was distributed in a combination of all‐liquid and mixed phase clouds, and was detected at altitudes as high as 6.5 km agl and at temperatures as low as −34°C.
Abstract
Macro- and microphysical properties of single-layer stratiform mixed-phase clouds are derived from multiple years of lidar, radar, and radiosonde observations. Measurements were made as part ...of the Mixed-Phase Arctic Clouds Experiment (MPACE) and the Study of Environmental Arctic Change (SEARCH) in Barrow, Alaska, and Eureka, Nunavut, Canada, respectively. Single-layer mixed-phase clouds occurred between 4% and 26% of the total time observed, varying with season and location. They had mean cloud-base heights between ∼700 and 2100 m and thicknesses between ∼200 and 700 m. Seasonal mean cloud optical depths ranged from 2.2 up. The clouds existed at temperatures of ∼242–271 K and occurred under different wind conditions, depending on season. Utilizing retrievals from a combination of lidar, radar, and microwave radiometer, mean cloud microphysical properties were derived, with mean liquid effective diameters estimated from 16 to 49 μm, mean liquid number densities on the order of 104–105 L−1, and mean water contents estimated between 0.07 and 0.28 g m−3. Ice precipitation was shown to have mean ice effective diameters of 50–125 μm, mean ice number densities on the order of 10 L−1, and mean water contents estimated between 0.012 and 0.031 g m−3. Mean cloud liquid water paths ranged from 25 to 100 g m−2. All results are compared to previous studies, and potential retrieval errors are discussed. Additionally, seasonal variation in macro- and microphysical properties was highlighted. Finally, fraction of liquid water to ice mass was shown to decrease with decreasing temperature.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We use the Spitzer Wide-area InfraRed Extragalactic Legacy Survey (SWIRE) to explore the specific star formation activity of galaxies and their evolution near the peak of the cosmic far-infrared ...(FIR) background at 70 and 160 μm. We use a stacking analysis to determine the mean FIR properties of well-defined subsets of galaxies at flux levels well below the FIR catalogue detection limits of SWIRE and other Spitzer surveys. We tabulate the contribution of different subsets of galaxies to the FIR background at 70 and 160 μm. These long wavelengths provide a good constraint on the bolometric obscured emission. The large area provides good constraints at low z and in finer redshift bins than previous work. At all redshifts we find that the specific FIR luminosity decreases with increasing mass, following a trend LFIR/M*∝Mβ* with β=−0.38 ± 0.14. This is a more continuous change than expected from the De Lucia & Blaizot semi-analytic model suggesting modifications to the feedback prescriptions. We see an increase in the specific FIR luminosity by about a factor of ∼100 from 0 < z < 2 and find that the specific FIR luminosity evolves as (1 +z)α with α= 4.4 ± 0.3 for galaxies with 10.5 < log10M*/M⊙≤ 12. This is considerably steeper than the De Lucia & Blaizot semi-analytic model (α∼ 2.5). When separating galaxies into early and late types on the basis of the optical/IR spectral energy distributions we find that the decrease in specific FIR luminosity with stellar mass is stronger in early-type galaxies (β∼−0.46), while late-type galaxies exhibit a flatter trend (β∼−0.15). The evolution is strong for both classes but stronger for the early-type galaxies. The early types show a trend of decreasing strength of evolution as we move from lower to higher masses while the evolution of the late-type galaxies has little dependence on stellar mass. We suggest that in late-type galaxies we are seeing a consistently declining specific star formation rate α= 3.36 ± 0.16 through a common phenomenon, for example, exhaustion of gas supply, i.e. not systematically dependent on the local properties of the galaxy.
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