The evaluation of CloudSat and CALIPSO ice microphysical products using ground-based cloud radar and lidar observations

In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 μm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m−2 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from −81.6 to −82.8 W m−2. Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method using CloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.

Global retrieval of ATSR cloud parameters and evaluation (GRAPE): dataset assessment

The Along-Track Scanning Radiometers (ATSRs) provide a long time-series of measurements suitable for the retrieval of cloud properties. This work evaluates the freely-available Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) dataset (version 3) created from the ATSR-2 (1995�2003) and Advanced ATSR (AATSR; 2002 onwards) records. Users are recommended to consider only retrievals flagged as high-quality, where there is a good consistency between the measurements and the retrieved state (corresponding to about 60% of converged retrievals over sea, and more than 80% over land). Cloud properties are found to be generally free of any significant spurious trends relating to satellite zenith angle. Estimates of the random error on retrieved cloud properties are suggested to be generally appropriate for optically-thick clouds, and up to a factor of two too small for optically-thin cases. The correspondence between ATSR-2 and AATSR cloud properties is high, but a relative calibration difference between the sensors of order 5�10% at 660 nm and 870 nm limits the potential of the current version of the dataset for trend analysis. As ATSR-2 is thought to have the better absolute calibration, the discussion focusses on this portion of the record. Cloud-top heights from GRAPE compare well to ground-based data at four sites, particularly for shallow clouds. Clouds forming in boundary-layer inversions are typically around 1 km too high in GRAPE due to poorly-resolved inversions in the modelled temperature profiles used. Global cloud fields are compared to satellite products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements, and a climatology of liquid water content derived from satellite microwave radiometers. In all cases the main reasons for differences are linked to differing sensitivity to, and treatment of, multi-layer cloud systems. The correlation coefficient between GRAPE and the two MODIS products considered is generally high (greater than 0.7 for most cloud properties), except for liquid and ice cloud effective radius, which also show biases between the datasets. For liquid clouds, part of the difference is linked to choice of wavelengths used in the retrieval. Total cloud cover is slightly lower in GRAPE (0.64) than the CALIOP dataset (0.66). GRAPE underestimates liquid cloud water path relative to microwave radiometers by up to 100 g m�2 near the Equator and overestimates by around 50 g m�2 in the storm tracks. Finally, potential future improvements to the algorithm are outlined.

Performance of palm- based fat blends with a low saturated fat content in puff pastry

Four fat blends based on palm fractions in combination with high oleic sunflower oil (HOSF) with a relatively low saturated fatty acid content (29.2±0.85%, i.e. less than 50% of that of butter) were prepared. The saturated fat was located in different triacylglycerols (TAG) structures in each blend. Principal saturated TAG were derived from palm stearin (POs, containing tripalmitoyl glycerol - PPP), palm mid fraction (PMF, containing 1,3-dipalmitoyl-2-oleoyl glycerol - POP) and interesterified PMF (inPMF, containing PPP, POP and rac-1,2-dipalmitoyl-3-oleoyl glycerol - PPO). Thus, in blend 1, composed of POs and HOSF, the saturates resided principally in PPP. In blend 2, composed of POs, PMF and HOSF, the principal saturate-containing TAG were PPP and POP. Blend 3, composed of inPMF and HOSF, was similar to blend 2 except that the disaturated TAG comprised a 2:1 mixture of PPO:POP. Finally, blend 4, a mixture of PMF and HOSF, had saturates present mainly as POP. The physical properties and the functionality of blends, as shortenings for puff pastry laminated in a warm bakery environment (20-30°C), were compared with each other, and with butter. Puff pastry prepared with blend 1 (POs:HOSF 29:71) and blend 4 (PMF:HOSF 41:59), was very hard; blend 2 (POs:PMF:HOSF 13:19:68) was most similar to butter in the compressibility of the baked product and it performed well in an independent baking trial; blend 3 (inPMF:HOSF 40:60) gave a product that required a higher force for compression than butter.

Development of novel methods to determine crystalline glucose content of honey based on DSC, HPLC, and viscosity measurements and their use to examine the setting propensity of honey

Crystallization must occur in honey in order to produce set or creamed honey; however, the process must occur in a controlled manner in order to obtain an acceptable product. As a consequence, reliable methods are needed to measure the crystal content of honey (φ expressed as kg crystal per kg honey), which can also be implemented with relative ease in industrial production facilities. Unfortunately, suitable methods do not currently exist. This article reports on the development of 2 independent offline methods to measure the crystal content in honey based on differential scanning calorimetry and high-performance liquid chromatography. The 2 methods gave highly consistent results on the basis of paired t-test involving 143 experimental points (P > 0.05, r**2 = 0.99). The crystal content also correlated with the relative viscosity, defined as the ratio of the viscosity of crystal containing honey to that of the same honey when all crystals are dissolved, giving the following correlation: μr = 1 + 1398.8∅**2.318. This correlation can be used to estimate the crystal content of honey in industrial production facilities. The crystal growth rate at a temperature of 14 ◦C—the normal crystallization temperature used in practice—was linear, and the growth rate also increased with the total glucose content in the honey.

Probabilistic physically-based cloud screening of satellite infra-red imagery for operational sea surface temperature retrieval

We propose and demonstrate a fully probabilistic (Bayesian) approach to the detection of cloudy pixels in thermal infrared (TIR) imagery observed from satellite over oceans. Using this approach, we show how to exploit the prior information and the fast forward modelling capability that are typically available in the operational context to obtain improved cloud detection. The probability of clear sky for each pixel is estimated by applying Bayes' theorem, and we describe how to apply Bayes' theorem to this problem in general terms. Joint probability density functions (PDFs) of the observations in the TIR channels are needed; the PDFs for clear conditions are calculable from forward modelling and those for cloudy conditions have been obtained empirically. Using analysis fields from numerical weather prediction as prior information, we apply the approach to imagery representative of imagers on polar-orbiting platforms. In comparison with the established cloud-screening scheme, the new technique decreases both the rate of failure to detect cloud contamination and the false-alarm rate by one quarter. The rate of occurrence of cloud-screening-related errors of >1 K in area-averaged SSTs is reduced by 83%. Copyright © 2005 Royal Meteorological Society.

Retrieval of sea surface temperature from space based on modeling of infrared radiative transfer: capabilities and limitations

The retrieval (estimation) of sea surface temperatures (SSTs) from space-based infrared observations is increasingly performed using retrieval coefficients derived from radiative transfer simulations of top-of-atmosphere brightness temperatures (BTs). Typically, an estimate of SST is formed from a weighted combination of BTs at a few wavelengths, plus an offset. This paper addresses two questions about the radiative transfer modeling approach to deriving these weighting and offset coefficients. How precisely specified do the coefficients need to be in order to obtain the required SST accuracy (e.g., scatter <0.3 K in week-average SST, bias <0.1 K)? And how precisely is it actually possible to specify them using current forward models? The conclusions are that weighting coefficients can be obtained with adequate precision, while the offset coefficient will often require an empirical adjustment of the order of a few tenths of a kelvin against validation data. Thus, a rational approach to defining retrieval coefficients is one of radiative transfer modeling followed by offset adjustment. The need for this approach is illustrated from experience in defining SST retrieval schemes for operational meteorological satellites. A strategy is described for obtaining the required offset adjustment, and the paper highlights some of the subtler aspects involved with reference to the example of SST retrievals from the imager on the geostationary satellite GOES-8.

Analysing the factors that influence tag choice based on semiotic analysis and activity theory

Social tagging has become very popular around the Internet as well as in research. The main idea behind tagging is to allow users to provide metadata to the web content from their perspective to facilitate categorization and retrieval. There are many factors that influence users' tag choice. Many studies have been conducted to reveal these factors by analysing tagging data. This paper uses two theories to identify these factors, namely the semiotics theory and activity theory. The former treats tags as signs and the latter treats tagging as an activity. The paper uses both theories to analyse tagging behaviour by explaining all aspects of a tagging system, including tags, tagging system components and the tagging activity. The theoretical analysis produced a framework that was used to identify a number of factors. These factors can be considered as categories that can be consulted to redirect user tagging choice in order to support particular tagging behaviour, such as cross-lingual tagging.

Independent uncertainty estimates for coefficient based sea surface temperature retrieval from the Along-Trck Scanning Radiometer instruments

We establish a methodology for calculating uncertainties in sea surface temperature estimates from coefficient based satellite retrievals. The uncertainty estimates are derived independently of in-situ data. This enables validation of both the retrieved SSTs and their uncertainty estimate using in-situ data records. The total uncertainty budget is comprised of a number of components, arising from uncorrelated (eg. noise), locally systematic (eg. atmospheric), large scale systematic and sampling effects (for gridded products). The importance of distinguishing these components arises in propagating uncertainty across spatio-temporal scales. We apply the method to SST data retrieved from the Advanced Along Track Scanning Radiometer (AATSR) and validate the results for two different SST retrieval algorithms, both at a per pixel level and for gridded data. We find good agreement between our estimated uncertainties and validation data. This approach to calculating uncertainties in SST retrievals has a wider application to data from other instruments and retrieval of other geophysical variables.

An enhanced content selection mechanism for personalization of video news programmes

In this paper, we propose a content selection framework that improves the users` experience when they are enriching or authoring pieces of news. This framework combines a variety of techniques to retrieve semantically related videos, based on a set of criteria which are specified automatically depending on the media`s constraints. The combination of different content selection mechanisms can improve the quality of the retrieved scenes, because each technique`s limitations are minimized by other techniques` strengths. We present an evaluation based on a number of experiments, which show that the retrieved results are better when all criteria are used at time.

A dislocation based theory for the deformation hardening behavior of DP steels : Impact of martensite content and ferrite grain size

A dislocation model, accurately describing the uniaxial plastic stress-strain behavior of dual phase (DP) steels, is proposed and the impact of martensite content and ferrite grain size in four commercially produced DP steels is analyzed. It is assumed that the plastic deformation process is localized to the ferrite. This is taken into account by introducing a non-homogeneity parameter, f(e), that specifies the volume fraction of ferrite taking active part in the plastic deformation process. It is found that the larger the martensite content the smaller the initial volume fraction of active ferrite which yields a higher initial deformation hardening rate. This explains the high energy absorbing capacity of DP steels with high volume fractions of martensite. Further, the effect of ferrite grain size strengthening in DP steels is important. The flow stress grain size sensitivity for DP steels is observed to be 7 times larger than that for single phase ferrite.

Ontology-based metadata for e-learning content

Nowadays, the popularity of the Web encourages the development of Hypermedia Systems dedicated to e-learning. Nevertheless, most of the available Web teaching systems apply the traditional paper-based learning resources presented as HTML pages making no use of the new capabilities provided by the Web. There is a challenge to develop educative systems that adapt the educative content to the style of learning, context and background of each student. Another research issue is the capacity to interoperate on the Web reusing learning objects. This work presents an approach to address these two issues by using the technologies of the Semantic Web. The approach presented here models the knowledge of the educative content and the learner’s profile with ontologies whose vocabularies are a refinement of those defined on standards situated on the Web as reference points to provide semantics. Ontologies enable the representation of metadata concerning simple learning objects and the rules that define the way that they can feasibly be assembled to configure more complex ones. These complex learning objects could be created dynamically according to the learners’ profile by intelligent agents that use the ontologies as the source of their beliefs. Interoperability issues were addressed by using an application profile of the IEEE LOM- Learning Object Metadata standard.

Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System

In this paper an alternative method based on artificial neural networks is presented to determine harmonic components in the load current of a single-phase electric power system with nonlinear loads, whose parameters can vary so much in reason of the loads characteristic behaviors as because of the human intervention. The first six components in the load current are determined using the information contained in the time-varying waveforms. The effectiveness of this method is verified by using it in a single-phase active power filter with selective compensation of the current drained by an AC controller. The proposed method is compared with the fast Fourier transform.

Effect of ceria content on the sintering of ZrO2 based ceramics synthesized from a polymeric precursor

Zirconia-ceria powders with ceria concentration varying from 0 to 12 mol% were synthesized using a polymeric precursor route based on the Pechini process. Powder characteristics were evaluated with regard to the crystallite size, BET surface area, phase distribution, nitrogen adsorption/desorption behavior, and agglomeration state. Sintering was studied considering the shrinkage rate, densification, grain size, and phase evolution. It was demonstrated that the synthesis method is effective to prepare nanosized powders of tetragonal zirconia single-phase. Sinterability mainly depended on the agglomeration state of powders and the monoclinic phase content, fully tetragonal zirconia ceramic, with grain size of 2.4 mu m, was obtained after addition of at least 9 mol% ceria and sintering at 1500 degrees C for 4 h. (C) 2000 Elsevier B.V. Ltd. All rights reserved.

NDACC/SAOZ UV-visible total ozone measurements: improved retrieval and comparison with correlative ground-based and satellite observations

Accurate long-term monitoring of total ozone is one of the most important requirements for identifying possible natural or anthropogenic changes in the composition of the stratosphere. For this purpose, the NDACC (Network for the Detection of Atmospheric Composition Change) UV-visible Working Group has made recommendations for improving and homogenizing the retrieval of total ozone columns from twilight zenith-sky visible spectrometers. These instruments, deployed all over the world in about 35 stations, allow measuring total ozone twice daily with limited sensitivity to stratospheric temperature and cloud cover. The NDACC recommendations address both the DOAS spectral parameters and the calculation of air mass factors (AMF) needed for the conversion of O-3 slant column densities into vertical column amounts. The most important improvement is the use of O-3 AMF look-up tables calculated using the TOMS V8 (TV8) O-3 profile climatology, that allows accounting for the dependence of the O-3 AMF on the seasonal and latitudinal variations of the O-3 vertical distribution. To investigate their impact on the retrieved ozone columns, the recommendations have been applied to measurements from the NDACC/SAOZ (Systeme d'Analyse par Observation Zenithale) network. The revised SAOZ ozone data from eight stations deployed at all latitudes have been compared to TOMS, GOMEGDP4, SCIAMACHY-TOSOMI, SCIAMACHY-OL3, OMI-TOMS, and OMI-DOAS satellite overpass observations, as well as to those of collocated Dobson and Brewer instruments at Observatoire de Haute Provence (44 degrees N, 5.5 degrees E) and Sodankyla (67 degrees N, 27 degrees E), respectively. A significantly better agreement is obtained between SAOZ and correlative reference ground-based measurements after applying the new O-3 AMFs. However, systematic seasonal differences between SAOZ and satellite instruments remain. These are shown to mainly originate from (i) a possible problem in the satellite retrieval algorithms in dealing with the temperature dependence of the ozone cross-sections in the UV and the solar zenith angle (SZA) dependence, (ii) zonal modulations and seasonal variations of tropospheric ozone columns not accounted for in the TV8 profile climatology, and (iii) uncertainty on the stratospheric ozone profiles at high latitude in the winter in the TV8 climatology. For those measurements mostly sensitive to stratospheric temperature like TOMS, OMI-TOMS, Dobson and Brewer, or to SZA like SCIAMACHY-TOSOMI, the application of temperature and SZA corrections results in the almost complete removal of the seasonal difference with SAOZ, improving significantly the consistency between all ground-based and satellite total ozone observations.

Case-based system: Indexing and retrieval with fuzzy hypercube

In some applications with case-based system, the attributes available for indexing are better described as linguistic variables instead of receiving numerical treatment. In these applications, the concept of fuzzy hypercube can be applied to give a geometrical interpretation of similarities among cases. This paper presents an approach that uses geometrical properties of fuzzy hypercube space to make indexing and retrieval processes of cases.