The physical properties of the atmosphere in the new Hadley Centre Global Environmental Model (HadGEM1). Part II: Aspects of variability and regional climate

The performance of the atmospheric component of the new Hadley Centre Global Environmental Model (HadGEM1) is assessed in terms of its ability to represent a selection of key aspects of variability in the Tropics and extratropics. These include midlatitude storm tracks and blocking activity, synoptic variability over Europe, and the North Atlantic Oscillation together with tropical convection, the Madden-Julian oscillation, and the Asian summer monsoon. Comparisons with the previous model, the Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3), demonstrate that there has been a considerable increase in the transient eddy kinetic energy (EKE), bringing HadGEM1 into closer agreement with current reanalyses. This increase in EKE results from the increased horizontal resolution and, in combination with the improved physical parameterizations, leads to improvements in the representation of Northern Hemisphere storm tracks and blocking. The simulation of synoptic weather regimes over Europe is also greatly improved compared to HadCM3, again due to both increased resolution and other model developments. The variability of convection in the equatorial region is generally stronger and closer to observations than in HadCM3. There is, however, still limited convective variance coincident with several of the observed equatorial wave modes. Simulation of the Madden-Julian oscillation is improved in HadGEM1: both the activity and interannual variability are increased and the eastward propagation, although slower than observed, is much better simulated. While some aspects of the climatology of the Asian summer monsoon are improved in HadGEM1, the upper-level winds are too weak and the simulation of precipitation deteriorates. The dominant modes of monsoon interannual variability are similar in the two models, although in HadCM3 this is linked to SST forcing, while in HadGEM1 internal variability dominates. Overall, analysis of the phenomena considered here indicates that HadGEM1 performs well and, in many important respects, improves upon HadCM3. Together with the improved representation of the mean climate, this improvement in the simulation of atmospheric variability suggests that HadGEM1 provides a sound basis for future studies of climate and climate change.

Understanding projections of sea level rise in a Hadley Centre coupled climate model

Sea level changes resulting from CO2-induced climate changes in ocean density and circulation have been investigated in a series of idealised experiments with the Hadley Centre HadCM3 AOGCM. Changes in the mass of the ocean were not included. In the global mean, salinity changes have a negligible effect compared with the thermal expansion of the ocean. Regionally, sea level changes are projected to deviate greatly from the global mean (standard deviation is 40% of the mean). Changes in surface fluxes of heat, freshwater and wind stress are all found to produce significant and distinct regional sea level changes, wind stress changes being the most important and the cause of several pronounced local features, while heat and freshwater flux changes affect large parts of the North Atlantic and Southern Ocean. Regional change is related mainly to density changes, with a relatively small contribution in mid and high latitudes from change in the barotropic circulation. Regional density change has an important contribution from redistribution of ocean heat content. In general, unlike in the global mean, the regional pattern of sea level change due to density change appears to be influenced almost as much by salinity changes as by temperature changes, often in opposition. Such compensation is particularly marked in the North Atlantic, where it is consistent with recent observed changes. We suggest that density compensation is not a property of climate change specifically, but a general behavior of the ocean.

How big is your neighbourhood? Spatial implications of market participation among Filipino smallholders

We present a procedure for estimating two quantities defining the spatial externality in discrete-choice commonly referred to as 'the neighbourhood effect'. One quantity, the propensity for neighbours to make the same decision, reflects traditional preoccupations; the other quantity, the magnitude of the neighbourhood itself, is novel. Because both quantities have fundamental bearing on the magnitude of the spatial externality, it is desirable to have a robust algorithm for their estimation. Using recent advances in Bayesian estimation and model comparison, we devise such an algorithm and illustrate its application to a sample of northern-Filipino smallholders. We determine that a significant, positive, neighbourhood effect exists; that, among the 12 geographical units comprising the sample, the neighbourhood spans a three-unit radius; and that policy prescriptions are significantly altered when calculations account for the spatial externality.

Three-centre hydrogen bonds in triphenylphosphine oxide-hydroquinone (1/1)

The title cocrystal, C18H15OP center dot C6H6O2, belongs to a series of molecular systems based on triphenylphosphine P-oxide. The O atom of the oxide group acts as an acceptor for hydrogen bonds from OH groups of two hydroquinone molecules which lie on inversion centres [O center dot center dot center dot O = 2.7451 (17) and 2.681 (2) A S]. The crystal structure is stabilized by weak C-H center dot center dot center dot O hydrogen bonds, forming a C-2(1)(8) chain which runs parallel to the [100] direction.

Strongly nucleophilic RhI centre in square-planar complexes with terdentate (κ3) 2,2′:6′,2′′-terpyridine ligands: crystallographic, electrochemical and density functional theoretical studies

Rh-I-terpyridine complexes have been unambiguously formed for the first time. The 2,21:6',2"-terpyridine (tpy), 4'-chloro-2,2':6',2"-terpyridine (4'-Cl-tpy) and 4'-(tert-butyldimethylsilyl-ortho-carboranyl)-2,2':6',2"-terpyridine (carboranyl-tpy) ligands were used for successful syntheses and characterisation of the corresponding Rh-I complexes with halide coligands, [Rh(X)(4'-Y-terpyridine)] (X = Cl, Y = H, Cl, carboranyl; X = Br, Y = H). All four neutral Rh-tpy complexes are square planar, with Rh-X bonds in the plane of the 4'-Y-terpyridine ligands. Full characterisation of these dark blue, highly air-sensitive compounds was hampered by their poor solubility in various organic solvents. This is mainly due to the formation of pi-stacked aggregates, as evidenced by the crystal structure of [Rh(Cl)(tpy)]; in addition, [Rh(Cl)(carboranyl-tpy)] merely forms discrete dimers. The (bonding) properties of the novel Rh-I-terpyridine complexes have been studied with single-crystal X-ray diffraction, (time-dependent) density functional theoretical (DFT) calculations, far-infrared spectroscopy, electronic absorption spectroscopy and cyclic voltammetry. From DFT calculations, the HOMO of the studied Rh-I-terpyridine complexes involves predominantly the metal centre, while the LUMO resides on the terpyridine ligand. Absorption bands of the studied complexes in the visible region (400-900 nm) can be assigned to MLCT and MLCT/XLCT transitions. The relatively low oxidation potentials of [Rh(X)(tpy)] (X = Cl, Br) point to a high electron density on the metal centre. This makes the Rh-I-terpyridine complexes strongly nucleophilic and (potentially) highly reactive towards various (small) substrate molecules containing carbon-halide bonds.

Mean-tracking clustering algorithm for radial basis function centre selection

Radial basis functions can be combined into a network structure that has several advantages over conventional neural network solutions. However, to operate effectively the number and positions of the basis function centres must be carefully selected. Although no rigorous algorithm exists for this purpose, several heuristic methods have been suggested. In this paper a new method is proposed in which radial basis function centres are selected by the mean-tracking clustering algorithm. The mean-tracking algorithm is compared with k means clustering and it is shown that it achieves significantly better results in terms of radial basis function performance. As well as being computationally simpler, the mean-tracking algorithm in general selects better centre positions, thus providing the radial basis functions with better modelling accuracy