2,142 research outputs found
HerMES: deep number counts at 250 ÎŒm, 350 ÎŒm and 500 ÎŒm in the COSMOS and GOODS-N fields and the build-up of the cosmic infrared background
Aims. The Spectral and Photometric Imaging REceiver (SPIRE) onboard the Herschel space telescope has provided confusion limited maps of deep fields at 250 ÎŒm, 350 ÎŒm, and 500 ÎŒm, as part of the Herschel Multi-tiered Extragalactic Survey (HerMES). Unfortunately, due to confusion, only a small fraction of the cosmic infrared background (CIB) can be resolved into individually-detected sources. Our goal is to produce deep galaxy number counts and redshift distributions below the confusion limit at SPIRE wavelengths (~20 mJy), which we then use to place strong constraints on the origins of the cosmic infrared background and on models of galaxy evolution.
Methods. We individually extracted the bright SPIRE sources (>20 mJy) in the COSMOS field with a method using the positions, the flux densities, and the redshifts of the 24 ÎŒm sources as a prior, and derived the number counts and redshift distributions of the bright SPIRE sources. For fainter SPIRE sources (<20 mJy), we reconstructed the number counts and the redshift distribution below the confusion limit using the deep 24 ÎŒm catalogs associated with photometric redshift and information provided by the stacking of these sources into the deep SPIRE maps of the GOODS-N and COSMOS fields. Finally, by integrating all these counts, we studied the contribution of the galaxies to the CIB as a function of their flux density and redshift.
Results. Through stacking, we managed to reconstruct the source counts per redshift slice down to ~2 mJy in the three SPIRE bands, which lies about a factor 10 below the 5Ï confusion limit. Our measurements place tight constraints on source population models. None of the pre-existing models are able to reproduce our results at better than 3-Ï. Finally, we extrapolate our counts to zero flux density in order to derive an estimate of the total contribution of galaxies to the CIB, finding 10.1_(-2.3)^(+2.6)ânWâm^(-2)âsr^(-1), 6.5_(-1.6)^(+1.7)ânWâm^(-2)âsr^(-1), and 2.8_(-0.8)^(+0.9)ânWâm^(-2)âsr^(-1) at 250 ÎŒm, 350 ÎŒm, and 500 ÎŒm, respectively. These values agree well with FIRAS absolute measurements, suggesting our number counts and their extrapolation are sufficient to explain the CIB. We find that half of the CIB is emitted at z = 1.04, 1.20, and 1.25, respectively. Finally, combining our results with other works, we estimate the energy budget contained in the CIB between 8 ÎŒm and 1000 ÎŒm: 26_(-3)^(+7)ânWâm^(-2)âsr^(-1)
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Improved cloud-phase determination of low-level liquid and mixed-phase clouds by enhanced polarimetric lidar
The unambiguous retrieval of cloud phase from polarimetric lidar observations is dependent on the assumption that only cloud scattering processes affect polarization measurements. A systematic bias of the traditional lidar depolarization ratio can occur due to a lidar system's inability to accurately measure the entire backscattered signal dynamic range, and these biases are not always identifiable in traditional polarimetric lidar systems. This results in a misidentification of liquid water in clouds as ice, which has broad implications on evaluating surface energy budgets. The Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland employs multiple planes of linear polarization, and photon counting and analog detection schemes, to self evaluate, correct, and optimize signal combinations to improve cloud classification. Using novel measurements of diattenuation that are sensitive to both horizontally oriented ice crystals and counting system nonlinear effects, unambiguous measurements are possible by over constraining polarization measurements. This overdetermined capability for cloud-phase determination allows for system errors to be identified and quantified in terms of their impact on cloud properties. It is shown that lidar system dynamic range effects can cause errors in cloud-phase fractional occurrence estimates on the order of 30âŻ% causing errors in attribution of cloud radiative effects on the order of 10â30âŻ%. This paper presents a method to identify and remove lidar system effects from atmospheric polarization measurements and uses co-located sensors at Summit to evaluate this method. Enhanced measurements are achieved in this work with non-orthogonal polarization retrievals as well as analog and photon counting detection facilitating a more complete attribution of radiative effects linked to cloud properties
In-flight calibration of the Herschel-SPIRE instrument
SPIRE, the Spectral and Photometric Imaging REceiver, is the Herschel Space Observatory's submillimetre camera and spectrometer. It contains a three-band imaging photometer operating at 250, 350 and 500 ÎŒm, and an imaging Fourier-transform spectrometer (FTS) covering 194â671 ÎŒm (447-1550 GHz). In this paper we describe the initial approach taken to the absolute calibration of the SPIRE instrument using a combination of the emission from the Herschel telescope itself and the modelled continuum emission from solar system objects and other astronomical targets. We present the photometric, spectroscopic and spatial accuracy that is obtainable in data processed through the âstandardâ pipelines. The overall photometric accuracy at this stage of the mission is estimated as 15% for the photometer and between 15 and 50% for the spectrometer. However, there remain issues with the photometric accuracy of the spectra of low flux sources in the longest wavelength part of the SPIRE spectrometer band. The spectrometer wavelength accuracy is determined to be better than 1/10th of the line FWHM. The astrometric accuracy in SPIRE maps is found to be 2 arcsec when the latest calibration data are used. The photometric calibration of the SPIRE instrument is currently determined by a combination of uncertainties in the model spectra of the astronomical standards and the data processing methods employed for map and spectrum calibration. Improvements in processing techniques and a better understanding of the instrument performance will lead to the final calibration accuracy of SPIRE being determined only by uncertainties in the models of astronomical standards
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Cloud vertical distribution from combined surface and space radarâlidar observations at two Arctic atmospheric observatories
Detailed and accurate vertical distributions of cloud properties
(such as cloud fraction, cloud phase, and cloud water content) and their
changes are essential to accurately calculate the surface radiative flux and
to depict the mean climate state. Surface and space-based active sensors
including radar and lidar are ideal to provide this information because of
their superior capability to detect clouds and retrieve cloud microphysical
properties. In this study, we compare the annual cycles of cloud property
vertical distributions from space-based active sensors and surface-based
active sensors at two Arctic atmospheric observatories, Barrow and Eureka.
Based on the comparisons, we identify the sensors' respective strengths and
limitations, and develop a blended cloud property vertical distribution by
combining both sets of observations. Results show that surface-based
observations offer a more complete cloud property vertical distribution from
the surface up to 11âŻkm above mean sea level (a.m.s.l.) with limitations in the
middle and high altitudes; the annual mean total cloud fraction from
space-based observations shows 25â40âŻ% fewer clouds below 0.5âŻkm than from
surface-based observations, and space-based observations also show much fewer
ice clouds and mixed-phase clouds, and slightly more liquid clouds, from the
surface to 1âŻkm. In general, space-based observations show comparable cloud
fractions between 1 and 2âŻkmâŻa.m.s.l., and larger cloud fractions above 2âŻkmâŻa.m.s.l. than from surface-based observations. A blended product combines the
strengths of both products to provide a more reliable annual cycle of cloud
property vertical distributions from the surface to 11âŻkmâŻa.m.s.l. This
information can be valuable for deriving an accurate surface radiative budget
in the Arctic and for cloud parameterization evaluation in weather and
climate models. Cloud annual cycles show similar evolutions in total cloud
fraction and ice cloud fraction, and lower liquid-containing cloud fraction
at Eureka than at Barrow; the differences can be attributed to the generally
colder and drier conditions at Eureka relative to Barrow
Keck spectroscopy of z=1-3 ULIRGs from the Spitzer SWIRE survey
(Abridged) High-redshift ultra luminous infrared galaxies contribute the bulk
of the cosmic IR background and are the best candidates for very massive
galaxies in formation at z>1.5. We present Keck/LRIS optical spectroscopy of 35
z>1.4 luminous IR galaxies in the Spitzer Wide-area Infra-Red Extragalactic
survey (SWIRE) northern fields (Lockman Hole, ELAIS-N1, ELAIS-N2). The primary
targets belong to the ``IR-peak'' class of galaxies, having the 1.6 micron
(restframe) stellar feature detected in the IRAC Spitzer channels.The spectral
energy distributions of the main targets are thoroughly analyzed, by means of
spectro-photometric synthesis and multi-component fits (stars + starburst dust
+ AGN torus). The IR-peak selection technique is confirmed to successfully
select objects above z=1.4, though some of the observed sources lie at lower
redshift than expected. Among the 16 galaxies with spectroscopic redshift, 62%
host an AGN component, two thirds being type-1 and one third type-2 objects.
The selection, limited to r'<24.5, is likely biased to optically-bright AGNs.
The SEDs of non-AGN IR-peakers resemble those of starbursts (SFR=20-500
Msun/yr) hosted in massive (M>1e11 Msun) galaxies. The presence of an AGN
component provides a plausible explanation for the spectroscopic/photometric
redshift discrepancies, as the torus produces an apparent shift of the peak to
longer wavelengths. These sources are analyzed in IRAC and optical-IR color
spaces. In addition to the IR-peak galaxies, we present redshifts and spectral
properties for 150 objects, out of a total of 301 sources on slits.Comment: Accepted for publications on Astronomy and Astrophysics (acceprance
date March 8th, 2007). 33 pages. The quality of some figures have been
degrade
Moisture and dynamical interactions maintaining decoupled Arctic mixed-phase stratocumulus in the presence of a humidity inversion
Observations suggest that processes maintaining subtropical and Arctic stratocumulus differ, due to the different environments in which they occur. For example, specific humidity inversions (specific humidity increasing with height) are frequently observed to occur near cloud top coincident with temperature inversions in the Arctic, while they do not occur in the subtropics. In this study we use nested LES simulations of decoupled Arctic Mixed-Phase Stratocumulus (AMPS) clouds observed during the DOE Atmospheric Radiation Measurement Program's Indirect and SemiDirect Aerosol Campaign (ISDAC) to analyze budgets of water components, potential temperature, and turbulent kinetic energy. These analyses quantify the processes that maintain decoupled AMPS, including the role of humidity inversions. Key structural features include a shallow upper entrainment zone at cloud top that is located within the temperature and humidity inversions, a mixed layer driven by cloud-top cooling that extends from the base of the upper entrainment zone to below cloud base, and a lower entrainment zone at the base of the mixed layer. The surface layer below the lower entrainment zone is decoupled from the cloud mixed-layer system. Budget results show that cloud liquid water is maintained in the upper entrainment zone near cloud top (within a temperature and humidity inversion) due to a down gradient transport of water vapor by turbulent fluxes into the cloud layer from above and direct condensation forced by radiative cooling. Liquid water is generated in the updraft portions of the mixed-layer eddies below cloud top by buoyant destabilization. These processes cause at least 20% of the cloud liquid water to extend into the inversion. The redistribution of water vapor from the top of the humidity inversion to its base maintains the cloud layer, while the mixed layer-entrainment zone system is continually losing total water. In this decoupled system, the humidity inversion is the only source of water vapor for the cloud system, since water vapor from the surface layer is not efficiently transported into the mixed layer. Sedimentation of ice is the dominant sink of moisture from the mixed layer
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