The design of aircraft using the decision support problem technique

The Decision Support Problem Technique for unified design, manufacturing and maintenance is being developed at the Systems Design Laboratory at the University of Houston. This involves the development of a domain-independent method (and the associated software) that can be used to process domain-dependent information and thereby provide support for human judgment. In a computer assisted environment, this support is provided in the form of optimal solutions to Decision Support Problems

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 μm, and an imaging Fourier-transform spectrometer (FTS) covering 194–671 μm (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 “standard” 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

The Herschel-SPIRE instrument and its in-flight performance

The Spectral and Photometric Imaging REceiver (SPIRE), is the Herschel Space Observatory`s submillimetre camera and spectrometer. It contains a three-band imaging photometer operating at 250, 350 and 500 μm, and an imaging Fourier-transform spectrometer (FTS) which covers simultaneously its whole operating range of 194–671 μm (447–1550 GHz). The SPIRE detectors are arrays of feedhorn-coupled bolometers cooled to 0.3 K. The photometer has a field of view of 4´× 8´, observed simultaneously in the three spectral bands. Its main operating mode is scan-mapping, whereby the field of view is scanned across the sky to achieve full spatial sampling and to cover large areas if desired. The spectrometer has an approximately circular field of view with a diameter of 2.6´. The spectral resolution can be adjusted between 1.2 and 25 GHz by changing the stroke length of the FTS scan mirror. Its main operating mode involves a fixed telescope pointing with multiple scans of the FTS mirror to acquire spectral data. For extended source measurements, multiple position offsets are implemented by means of an internal beam steering mirror to achieve the desired spatial sampling and by rastering of the telescope pointing to map areas larger than the field of view. The SPIRE instrument consists of a cold focal plane unit located inside the Herschel cryostat and warm electronics units, located on the spacecraft Service Module, for instrument control and data handling. Science data are transmitted to Earth with no on-board data compression, and processed by automatic pipelines to produce calibrated science products. The in-flight performance of the instrument matches or exceeds predictions based on pre-launch testing and modelling: the photometer sensitivity is comparable to or slightly better than estimated pre-launch, and the spectrometer sensitivity is also better by a factor of 1.5–2

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 30 % causing errors in attribution of cloud radiative effects on the order of 10–30 %. 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

HerMES: The submillimeter spectral energy distributions of Herschel/SPIRE-detected galaxies

We present colours of sources detected with the Herschel/SPIRE instrument in deep extragalactic surveys of the Lockman Hole, Spitzer-FLS, and GOODS-N fields in three photometric bands at 250, 350 and 500 μm. We compare these with expectations from the literature and discuss associated uncertainties and biases in the SPIRE data. We identify a 500 μm flux limited selection of sources from the HerMES point source catalogue that appears free from neighbouring/blended sources in all three SPIRE bands. We compare the colours with redshift tracks of various contemporary models. Based on these spectral templates we show that regions corresponding to specific population types and redshifts can be identified better in colour-flux space. The redshift tracks as well as the colour-flux plots imply a majority of detected objects with redshifts at 1 < z < 3.5, somewhat depending on the group of model SEDs used. We also find that a population of sources with S_(250)/S_(350) < 0.8 at fluxes above 50 mJy as observed by SPIRE are not well represented by contemporary models and could consist of a mix of cold and lensed galaxies

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

HerMES: deep number counts at 250 μm, 350 μm and 500 μm 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 μm, 350 μm, and 500 μm, 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 μm 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 μm 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 5σ 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-σ. 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) nW m^(-2) sr^(-1), 6.5_(-1.6)^(+1.7) nW m^(-2) sr^(-1), and 2.8_(-0.8)^(+0.9) nW m^(-2) sr^(-1) at 250 μm, 350 μm, and 500 μm, 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 μm and 1000 μm: 26_(-3)^(+7) nW m^(-2) sr^(-1)