The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

Quasi-biennial oscillation and tracer distributions in a coupled chemistry-climate model

[ 1] We have used a fully coupled chemistry-climate model (CCM), which generates its own wind and temperature quasi-biennial oscillation (QBO), to study the effect of coupling on the QBO and to examine the QBO signals in stratospheric trace gases, particularly ozone. Radiative coupling of the interactive chemistry to the underlying general circulation model tends to prolong the QBO period and to increase the QBO amplitude in the equatorial zonal wind in the lower and middle stratosphere. The model ozone QBO agrees well with Stratospheric Aerosol and Gas Experiment II and Total Ozone Mapping Spectrometer satellite observations in terms of vertical and latitudinal structure. The model captures the ozone QBO phase change near 28 km over the equator and the column phase change near +/- 15 degrees latitude. Diagnosis of the model chemical terms shows that variations in NOx are the main chemical driver of the O-3 QBO around 35 km, i.e., above the O-3 phase change.

Evaluation of the sea ice simulation in a new coupled atmosphere-ocean climate model (HadGEM1)

[ 1] A rapid increase in the variety, quality, and quantity of observations in polar regions is leading to a significant improvement in the understanding of sea ice dynamic and thermodynamic processes and their representation in global climate models. We assess the simulation of sea ice in the new Hadley Centre Global Environmental Model (HadGEM1) against the latest available observations. The HadGEM1 sea ice component uses elastic-viscous-plastic dynamics, multiple ice thickness categories, and zero-layer thermodynamics. The model evaluation is focused on the mean state of the key variables of ice concentration, thickness, velocity, and albedo. The model shows good agreement with observational data sets. The variability of the ice forced by the North Atlantic Oscillation is also found to agree with observations.

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.

Mechanisms of ocean heat uptake in a coupled climate model and the implications for tracer based predictions of ocean heat uptake

The distribution of tracers in the ocean is often taken as an indication of the ventilation pathways for oceanic water masses. It has been suggested that under anthropogenic forcing heat will be taken up into the interior of the ocean along isopycnal ventilation pathways. This notion is investigated by examining distributions of potential temperature and a passive anomaly temperature tracer in a coupled climate experiment where CO2 is increased at a rate of 2% per year. We show that interior temperature changes cannot be explained solely by passive tracer transport along isopycnals. Heat uptake is strongly affected by changes in circulation and has a substantial diapycnal component.

Model catalyst studies of the strong metal-support interaction: Surface structure identified by STM on Pd nanoparticles on TiO2(110)

Model catalysts of Pd nanoparticles and films on TiO2 (I 10) were fabricated by metal vapour deposition (MVD). Molecular beam measurements show that the particles are active for CO adsorption, with a global sticking probability of 0.25, but that they are deactivated by annealing above 600 K, an effect indicative of SMSI. The Pd nanoparticles are single crystals oriented with their (I 11) plane parallel to the surface plane of the titania. Analysis of the surface by atomic resolution STM shows that new structures have formed at the surface of the Pd nanoparticles and films after annealing above 800 K. There are only two structures, a zigzag arrangement and a much more complex "pinwheel" structure. The former has a unit cell containing 7 atoms, and the latter is a bigger unit cell containing 25 atoms. These new structures are due to an overlayer of titania that has appeared on the surface of the Pd nanoparticles after annealing, and it is proposed that the surface layer that causes the SMSI effect is a mixed alloy of Pd and Ti, with only two discrete ratios of atoms: Pd/Ti of 1: 1 (pinwheel) and 1:2 (zigzag). We propose that it is these structures that cause the SMSI effect. (c) 2005 Elsevier Inc. All rights reserved.