Thermal Fractionation and isothermal crystallization of polyethylene nanocomposites prepared by in situ polymerization

Nanocomposites of high-density polyethylene (HDPE) and carbon nanotubes (CNT) of different geometries (single wall, double wall, and multiwall; SWNT, DWNT, and MWNT) were prepared by in situ polymerization of ethylene on CNT whose surface had been previously treated with a metallocene catalytic system. In this work, we have studied the effects of applying the successive self-nucleation and annealing thermal fractionation technique (SSA) to the nanocomposites and have also determined the influence of composition and type of CNT on the isothermal crystallization behavior of the HDPE. SSA results indicate that all types of CNT induce the formation of a population of thicker lamellar crystals that melt at higher temperatures as compared to the crystals formed in neat HDPE prepared under the same catalytic and polymerization conditions and subjected to the same SSA treatment. Furthermore, the peculiar morphology induced by the CNT on the HDPE matrix allows the resolution of thermal fractionation to be much better. The isothermal crystallization results indicated that the strong nucleation effect caused by CNT reduced the supercooling needed for crystallization. The interaction between the HDPE chains and the surface of the CNT is probably very strong as judged by the results obtained, even though it is only physical in nature. When the total crystallinity achieved during isothermal crystallization is considered as a function of CNT content, it was found that a competition between nucleation and topological confinement could account for the results. At low CNT content the crystallinity increases (because of the nucleating effect of CNT on HDPE), however, at higher CNT content there is a dramatic reduction in crystallinity reflecting the increased confinement experienced by the HDPE chains at the interfaces which are extremely large in these nanocomposites. Another consequence of these strong interactions is the remarkable decrease in Avrami index as CNT content increases. When the Avrami index reduces to I or lower, nucleation dominates the overall kinetics as a consequence of confinement effects. Wide-angle X-ray experiments were performed at a high-energy synchrotron source and demonstrated that no change in the orthorhombic unit cell of HDPE occurred during crystallization with or without CNT.

Deprotection, tethering, and activation of a catalytically active metalloporphyrin to a chemically active metal surface: [SAc](4)P-Mn(III)Cl on Ag(100)

The adsorption and subsequent thermal chemistry of the acetyl-protected manganese porphyrin, [SA(C)](4)P-Mn(III)Cl on Ag(100) have been studied by high resolution XPS and temperature-programmed desorption. The deprotection event, leading to formation of the covalently bound thioporphyrin, has been characterized and the conditions necessary for removal of the axial chlorine ligand have been determined, thus establishing a methodology for creating tethered activated species that could serve as catalytic sites for delicate oxidation reactions. Surface-mediated acetyl deprotection occurs at 298 K, at which temperature porphyrin diffusion is limited. At temperatures above similar to 425 K porphyrin desorption, diffusion and deprotection occur and at >470 K the axial chlorine is removed.

Integrated optics for nulling interferometry in the thermal infrared

Modal filtering is based on the capability of single-mode waveguides to transmit only one complex amplitude function to eliminate virtually any perturbation of the interfering wavefronts, thus making very high rejection ratios possible in a nulling interferometer. In the present paper we focus on the progress of Integrated Optics in the thermal infrared [6-20 mu m] range, one of the two candidate technologies for the fabrication of Modal Filters, together with fiber optics. In conclusion of the European Space Agency's (ESA) "Integrated Optics for Darwin" activity, etched layers of clialcogenide material deposited on chalcogenide glass substrates was selected among four candidates as the technology with the best potential to simultaneously meet the filtering efficiency, absolute and spectral transmission, and beam coupling requirements. ESA's new "Integrated Optics" activity started at mid-2007 with the purpose of improving the technology until compliant prototypes can be manufactured and validated, expectedly by the end of 2009. The present paper aims at introducing the project and the components requirements and functions. The selected materials and preliminary designs, as well as the experimental validation logic and test benches are presented. More details are provided on the progress of the main technology: vacuum deposition in the co-evaporation mode and subsequent etching of chalcogenide layers. In addition., preliminary investigations of an alternative technology based on burying a chalcogenide optical fiber core into a chalcogenide substrate are presented. Specific developments of anti-reflective solutions designed for the mitigation of Fresnel losses at the input and output surface of the components are also introduced.

Spatio-temporal surface soil heat flux estimates from satellite data: results for the AMMA experiment at the Fakara (Niger) supersite

This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.

Incorporation of water vapour transfer in the JULES Land Surface Model: implications for key soil variables and land surface fluxes

This study focuses on the mechanisms underlying water and heat transfer in upper soil layers, and their effects on soil physical prognostic variables and the individual components of the energy balance. The skill of the JULES (Joint UK Land Environment Simulator) land surface model (LSM) to simulate key soil variables, such as soil moisture content and surface temperature, and fluxes such as evaporation, is investigated. The Richards equation for soil water transfer, as used in most LSMs, was updated by incorporating isothermal and thermal water vapour transfer. The model was tested for three sites representative of semi-arid and temperate arid climates: the Jornada site (New Mexico, USA), Griffith site (Australia) and Audubon site (Arizona, USA). Water vapour flux was found to contribute significantly to the water and heat transfer in the upper soil layers. This was mainly due to isothermal vapour diffusion; thermal vapour flux also played a role at the Jornada site just after rainfall events. Inclusion of water vapour flux had an effect on the diurnal evolution of evaporation, soil moisture content and surface temperature. The incorporation of additional processes, such as water vapour flux among others, into LSMs may improve the coupling between the upper soil layers and the atmosphere, which in turn could increase the reliability of weather and climate predictions.

Topographic and thermal mapping of volcanic terrain using AVTIS ground-based 94-GHz dual-mode radar/radiometric imager

The All-Weather Volcano Topography Imaging Sensor remote sensing instrument is a custom-built millimeter-wave (MMW) sensor that has been developed as a practical field tool for remote sensing of volcanic terrain at active lava domes. The portable instrument combines active and passive MMW measurements to record topographic and thermal data in almost all weather conditions from ground-based survey points. We describe how the instrument is deployed in the field, the quality of the primary ranging and radiometric measurements, and the postprocessing techniques used to derive the geophysical products of the target terrain, surface temperature, and reflectivity. By comparison of changing topography, we estimate the volume change and the lava extrusion rate. Validation of the MMW radiometry is also presented by quantitative comparison with coincident infrared thermal imagery.

Cooled infrared filters and dichroics for the sea and land surface temperature radiometer (SLSTR)

The Sea and Land Surface Temperature Radiometer (SLSTR) is a nine channel visible and infrared high precision radiometer designed to provide climate data of global sea and land surface temperatures. The SLSTR payload is destined to fly on the Ocean and Medium-Resolution Land Mission for the ESA/EU Global Monitoring for Environment and Security (GMES) Programme Sentinel-3 mission to measure the sea and land temperature and topography for near real-time environmental and atmospheric climate monitoring of the Earth. In this paper we describe the optical layout of infrared optics in the instrument, spectral thin-film multilayer design, and system channel throughput analysis for the combined interference filter and dichroic beamsplitter coatings to discriminate wavelengths at 3.74, 10.85 & 12.0 μm. The rationale for selection of thin-film materials, deposition technique, and environmental testing, inclusive of humidity, thermal cycling and ionizing radiation testing are also described.

The GODAE high resolution sea surface temperature pilot project

Sea surface temperature (SST) measurements are required by operational ocean and atmospheric forecasting systems to constrain modeled upper ocean circulation and thermal structure. The Global Ocean Data Assimilation Experiment (GODAE) High Resolution SST Pilot Project (GHRSST-PP) was initiated to address these needs by coordinating the provision of accurate, high-resolution, SST products for the global domain. The pilot project is now complete, but activities continue within the Group for High Resolution SST (GHRSST). The pilot project focused on harmonizing diverse satellite and in situ data streams that were indexed, processed, quality controlled, analyzed, and documented within a Regional/Global Task Sharing (R/GTS) framework implemented in an internationally distributed manner. Data with meaningful error estimates developed within GHRSST are provided by services within R/GTS. Currently, several terabytes of data are processed at international centers daily, creating more than 25 gigabytes of product. Ensemble SST analyses together with anomaly SST outputs are generated each day, providing confidence in SST analyses via diagnostic outputs. Diagnostic data sets are generated and Web interfaces are provided to monitor the quality of observation and analysis products. GHRSST research and development projects continue to tackle problems of instrument calibration, algorithm development, diurnal variability, skin temperature deviation, and validation/verification of GHRSST products. GHRSST also works closely with applications and users, providing a forum for discussion and feedback between SST users and producers on a regular basis. All data within the GHRSST R/GTS framework are freely available. This paper reviews the progress of GHRSST-PP, highlighting achievements that have been fundamental to the success of the pilot project.

Sea surface temperature from a geostationary satellite by optimal estimation

Optimal estimation (OE) is applied as a technique for retrieving sea surface temperature (SST) from thermal imagery obtained by the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on Meteosat 9. OE requires simulation of observations as part of the retrieval process, and this is done here using numerical weather prediction fields and a fast radiative transfer model. Bias correction of the simulated brightness temperatures (BTs) is found to be a necessary step before retrieval, and is achieved by filtered averaging of simulations minus observations over a time period of 20 days and spatial scale of 2.5° in latitude and longitude. Throughout this study, BT observations are clear-sky averages over cells of size 0.5° in latitude and longitude. Results for the OE SST are compared to results using a traditional non-linear retrieval algorithm (“NLSST”), both validated against a set of 30108 night-time matches with drifting buoy observations. For the OE SST the mean difference with respect to drifter SSTs is − 0.01 K and the standard deviation is 0.47 K, compared to − 0.38 K and 0.70 K respectively for the NLSST algorithm. Perhaps more importantly, systematic biases in NLSST with respect to geographical location, atmospheric water vapour and satellite zenith angle are greatly reduced for the OE SST. However, the OE SST is calculated to have a lower sensitivity of retrieved SST to true SST variations than the NLSST. This feature would be a disadvantage for observing SST fronts and diurnal variability, and raises questions as to how best to exploit OE techniques at SEVIRI's full spatial resolution.

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.

A cross-calibration of GMS-5 thermal channels against ATSR-2

Motivated by the importance to weather and climate of the Indo-Pacific seas, we present a new calibration of the Visible Infrared Spin-Scan Radiometer (VISSR) on the geostationary meteorological satellite, GMS-5. VISSR imagery has significant potential for exploring the dynamics of the ocean and air–sea interactions in this poorly characterized region, by virtue of the VISSR's surface temperature retrieval capability and hourly sampling. However, the calibration of the thermal imagery supplied by the Japanese Meteorological Agency (JMA) is inconsistent with the spectral characteristics of the channels, and published details of the JMA calibration procedure are scant. We use the well-characterized Along-Track Scanning Radiometer 2 (ATSR-2) as a reference, and determine calibration corrections for GMS-5 VISSR. We obtain more credible VISSR brightness temperatures and demonstrate sea surface temperature (SST) retrieval that validates well against in situ measurements (bias ∼0.3 and scatter ∼0.4 K). Comparison with a widely used sea surface temperature analysis shows that the GMS-5 VISSR SST fields capture important spatial structure, absent in the analysis.

Importance of initial state and atmospheric conditions for urban land surface models' performance

Urban land surface models (LSM) are commonly evaluated for short periods (a few weeks to months) because of limited observational data. This makes it difficult to distinguish the impact of initial conditions on model performance or to consider the response of a model to a range of possible atmospheric conditions. Drawing on results from the first urban LSM comparison, these two issues are considered. Assessment shows that the initial soil moisture has a substantial impact on the performance. Models initialised with soils that are too dry are not able to adjust their surface sensible and latent heat fluxes to realistic values until there is sufficient rainfall. Models initialised with too wet soils are not able to restrict their evaporation appropriately for periods in excess of a year. This has implications for short term evaluation studies and implies the need for soil moisture measurements to improve data assimilation and model initialisation. In contrast, initial conditions influencing the thermal storage have a much shorter adjustment timescale compared to soil moisture. Most models partition too much of the radiative energy at the surface into the sensible heat flux at the probable expense of the net storage heat flux.

Simulation of long-term thermal characteristics of three Estonian lakes

A one-dimensional surface energy-balance lake model, coupled to a thermodynamic model of lake ice, is used to simulate variations in the temperature of and evaporation from three Estonian lakes: Karujärv, Viljandi and Kirjaku. The model is driven by daily climate data, derived by cubic-spline interpolation from monthly mean data, and was run for periods of 8 years (Kirjaku) up to 30 years (Viljandi). Simulated surface water temperature is in good agreement with observations: mean differences between simulated and observed temperatures are from −0.8°C to +0.1°C. The simulated duration of snow and ice cover is comparable with observed. However, the model generally underpredicts ice thickness and overpredicts snow depth. Sensitivity analyses suggest that the model results are robust across a wide range (0.1–2.0 m−1) of lake extinction coefficient: surface temperature differs by less than 0.5°C between extreme values of the extinction coefficient. The model results are more sensitive to snow and ice albedos. However, changing the snow (0.2–0.9) and ice (0.15–0.55) albedos within realistic ranges does not improve the simulations of snow depth and ice thickness. The underestimation of ice thickness is correlated with the overestimation of snow cover, since a thick snow layer insulates the ice and limits ice formation. The overestimation of snow cover results from the assumption that all the simulated winter precipitation occurs as snow, a direct consequence of using daily climate data derived by interpolation from mean monthly data.

A critical evaluation of the ability of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) thermal infrared red-green-blue rendering to identify dust events: theoretical analysis

Using a combination of idealized radiative transfer simulations and a case study from the first field campaign of the Saharan Mineral Dust Experiment (SAMUM) in southern Morocco, this paper provides a systematic assessment of the limitations of the widely used Spinning Enhanced Visible and Infrared Imager (SEVIRI) red-green-blue (RGB) thermal infrared dust product. Both analyses indicate that the ability of the product to identify dust, via its characteristic pink coloring, is strongly dependent on the column water vapor, the lower tropospheric lapse rate, and dust altitude. In particular, when column water vapor exceeds ∼20–25 mm, dust presence, even for visible optical depths of the order 0.8, is effectively masked. Variability in dust optical properties also has a marked impact on the imagery, primarily as a result of variability in dust composition. There is a moderate sensitivity to the satellite viewing geometry, particularly in moist conditions. The underlying surface can act to confound the signal seen through variations in spectral emissivity, which are predominantly manifested in the 8.7μm SEVIRI channel. In addition, if a temperature inversion is present, typical of early morning conditions over the Sahara and Sahel, an increased dust loading can actually reduce the pink coloring of the RGB image compared to pristine conditions. Attempts to match specific SEVIRI observations to simulations using SAMUM measurements are challenging because of high uncertainties in surface skin temperature and emissivity. Recommendations concerning the use and interpretation of the SEVIRI RGB imagery are provided on the basis of these findings.

Land surface temperature retrieval from Sentinel 2 and 3 Missions

In this work we explore the synergistic use of future MSI instrument on board Sentinel-2 platform and OLCI/SLSTR instruments on board Sentinel-3 platform in order to improve LST products currently derived from the single AATSR instrument on board the ENVI- SAT satellite. For this purpose, the high spatial resolu- tion data from Setinel2/MSI will be used for a good characterization of the land surface sub-pixel heteroge- neity, in particular for a precise parameterization of surface emissivity using a land cover map and spectral mixture techniques. On the other hand, the high spectral resolution of OLCI instrument, suitable for a better characterization of the atmosphere, along with the dual- view available in the SLTSR instrument, will allow a better atmospheric correction through improved aero- sol/water vapor content retrievals and the implementa- tion of novel cloud screening procedures. Effective emissivity and atmospheric corrections will allow accu- rate LST retrievals using the SLSTR thermal bands by developing a synergistic split-window/dual-angle algo- rithm. ENVISAT MERIS and AATSR instruments and different high spatial resolution data (Landsat/TM, Proba/CHRIS, Terra/ASTER) will be used as bench- mark for the future OLCI, SLSTR and MSI instruments. Results will be validated using ground data collected in the framework of different field campaigns organized by ESA.