Cloud clearing techniques over land for land surface temperature retrieval from the Advanced Along Track Scanning Radiometer

We present five new cloud detection algorithms over land based on dynamic threshold or Bayesian techniques, applicable to the Advanced Along Track Scanning Radiometer (AATSR) instrument and compare these with the standard threshold based SADIST cloud detection scheme. We use a manually classified dataset as a reference to assess algorithm performance and quantify the impact of each cloud detection scheme on land surface temperature (LST) retrieval. The use of probabilistic Bayesian cloud detection methods improves algorithm true skill scores by 8-9 % over SADIST (maximum score of 77.93 % compared to 69.27 %). We present an assessment of the impact of imperfect cloud masking, in relation to the reference cloud mask, on the retrieved AATSR LST imposing a 2 K tolerance over a 3x3 pixel domain. We find an increase of 5-7 % in the observations falling within this tolerance when using Bayesian methods (maximum of 92.02 % compared to 85.69 %). We also demonstrate that the use of dynamic thresholds in the tests employed by SADIST can significantly improve performance, applicable to cloud-test data to provided by the Sea and Land Surface Temperature Radiometer (SLSTR) due to be launched on the Sentinel 3 mission (estimated 2014).

Ordering on multiple lengthscales in a series of side group liquid crystal block copolymers containing a cholesteryl-based mesogen

Hierarchical ordering in a side group liquid crystal block copolymer is investigated by differential scanning calorimetry, polarized optical microscopy, small-angle X-ray and neutron scattering (SAXS and SANS) and transmission electron microscopy (TEM). A series of block copolymers with a range of compositions was prepared by atom transfer radical polymerization, comprising a polystyrene block and a poly(methyl methacrylate) block bearing chiral cholesteryl mesogens. Smectic ordering is observed as well as microphase separation of the block copolymer. Lamellar structures were observed for far larger volume fractions than for coil-coil copolymers (up to a volume fraction of liquid crystal block, f(LC) = 0.8). A sample with f(LC) = 0.86 exhibited a hexagonal-packed cylinder morphology, as confirmed by SAXS and TEM. The matrix comprised the liquid crystal block, with the mesogens forming smectic layers. For the liquid crystal homopolymer and samples with high f(LC), a smectic-smectic phase transition was observed below the clearing point. At low temperature, the smectic phase comprises coexisting domains with monolayer S-A,S-1 coexisting with interdigitated S-A,S-d domains. At high temperature a SA,1 phase is observed. This is the only structure observed for samples with lower f(LC). These unprecedented results point to the influence of block copolymer microphase separation on the smectic ordering.

Cinnamate ester containing liquid crystalline side chain polymers

The synthesis of methacrylate esters of 4-cyanophenyl-(4-(ω-hydroxyalkyloxy)) cinnamates, with spacer lengths of 2 and 6 methylene units and the synthesis of the corresponding acrylate ester with a spacer of 2 methylene units are described. The methacrylate monomers were polymerized by free radical polymerization, both as homopolymers and as copolymers with the analogous benzoate monomer of spacer length 6. The acrylate ester could not be polymerized successfully under the same reaction conditions. Polymers were characterized by NMR spectroscopy, gel permeation chromatography, differential scanning calorimetry, and thermo-optic observations. Of the monomers prepared, only the cinnamate with a hexamethylene spacer shows a mesophase, seen on supercooling of the melt. All of the polymers prepared were liquid crystalline, with smectic behavior predominating in the polymethacrylates with the longer spacer group. A narrow nematic region is seen just below the clearing temperature with a range of 3–9°C, nematic character is increased in the copolymer series with the degree of incorporation of the cinnamate monomer with the spacer group of length 2.

Approaches to the synthesis of novel photoactive side chain liquid crystalline polymers containing analogues of the cinnamate ester group

A series of chain liquid crystalline copolymers of 4-cyanophenyl 4′-(6-methacryloyloxyhexyloxy)benzoate and 2-methacryloyloxyethyl β-(1-naphthyl)-propenoate were prepared by free radical polymerization. The corresponding polyacrylates could not be prepared in the same way and an alternative method was used for their preparation involving the synthesis of copolymers of the mesogenic monomer and 2-hydroxyethyl acrylate followed by treatment of the resulting polymers with β-(1-naphthyl)propenoyl chloride. The materials are of interest as photoactive liquid crystalline polymers. The effect of introducing a bulky nonmesogenic group into a liquid crystalline copolymer generally lowers the clearing temperature and raises Tg but also gives rise to contrasting phase behaviour in these two series of polymers. Polymethacrylates which show mesomorphism have sharp transitions and continue to exhibit a highly ordered smectic phase over the bulk of their liquid crystal range. Polyacrylates, on the other hand, exhibit a weakening and broadening-out of their thermal transitions consistent with a lowering of order. These results emphasize the effect of the polymer backbone on phase behaviour.

Non-existence of competitive equilibria with dynamically inconsistent preferences

This paper shows the robust non-existence of competitive equilibria even in a simple three period representative agent economy with dynamically inconsistent preferences. We distinguish between a sophisticated and naive representative agent. Even when underlying preferences are monotone and convex, at given prices, we show by example that the induced preference of the sophisticated representative agent over choices in first-period markets is both non-convex and satiated. Even allowing for negative prices, the market-clearing allocation is not contained in the convex hull of demand. Finally, with a naive representative agent, we show that perfect foresight is incompatible with market clearing and individual optimization at given prices.

Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products

Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties – the sill and the mean length scale metric – provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R2 = 0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R2 = 0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets.

Modelling the effects of gravity waves on stratocumulus clouds observed during VOCALS-UK

During the VOCALS campaign spaceborne satellite observations showed that travelling gravity wave packets, generated by geostrophic adjustment, resulted in perturbations to marine boundary layer (MBL) clouds over the south-east Pacific Ocean (SEP). Often, these perturbations were reversible in that passage of the wave resulted in the clouds becoming brighter (in the wave crest), then darker (in the wave trough) and subsequently recovering their properties after the passage of the wave. However, occasionally the wave packets triggered irreversible changes to the clouds, which transformed from closed mesoscale cellular convection to open form. In this paper we use large eddy simulation (LES) to examine the physical mechanisms that cause this transition. Specifically, we examine whether the clearing of the cloud is due to (i) the wave causing additional cloud-top entrainment of warm, dry air or (ii) whether the additional condensation of liquid water onto the existing drops and the subsequent formation of drizzle are the important mechanisms. We find that, although the wave does cause additional drizzle formation, this is not the reason for the persistent clearing of the cloud; rather it is the additional entrainment of warm, dry air into the cloud followed by a reduction in longwave cooling, although this only has a significant effect when the cloud is starting to decouple from the boundary layer. The result in this case is a change from a stratocumulus to a more patchy cloud regime. For the simulations presented here, cloud condensation nuclei (CCN) scavenging did not play an important role in the clearing of the cloud. The results have implications for understanding transitions between the different cellular regimes in marine boundary layer (MBL) clouds.

Managing a duopolistic water market with confirmed proposals. An experiment

We report results from experimental water markets in which owners of two different sources of water supply water to households and farmers. The final water quality consumed by each type of consumer is determined through mixing of qualities from two different resources. We compare the standard duopolistic market structure with an alternative market clearing mechanism inspired by games with confirmed strategies (which have been shown to yield collusive outcomes). As in the static case, complex dynamic markets operating under a confirmed proposals protocol yield less efficient outcomes because coordination among independent suppliers has the usual effects of restricting output and increasing prices to the users. Our results suggest that, when market mechanisms are used to allocate water to its users, the rule of thumb used by competition authorities can also serve as a guide towards water market regulation.

Sea surface temperature climate change initiative: alternative image classification algorithms for sea-ice affected oceans

We present a Bayesian image classification scheme for discriminating cloud, clear and sea-ice observations at high latitudes to improve identification of areas of clear-sky over ice-free ocean for SST retrieval. We validate the image classification against a manually classified dataset using Advanced Along Track Scanning Radiometer (AATSR) data. A three way classification scheme using a near-infrared textural feature improves classifier accuracy by 9.9 % over the nadir only version of the cloud clearing used in the ATSR Reprocessing for Climate (ARC) project in high latitude regions. The three way classification gives similar numbers of cloud and ice scenes misclassified as clear but significantly more clear-sky cases are correctly identified (89.9 % compared with 65 % for ARC). We also demonstrate the poetential of a Bayesian image classifier including information from the 0.6 micron channel to be used in sea-ice extent and ice surface temperature retrieval with 77.7 % of ice scenes correctly identified and an overall classifier accuracy of 96 %.