The global response to tropical heating in the Madden-Julian oscillation during the northern winter

A life cycle of the Madden–Julian oscillation (MJO) was constructed, based on 21 years of outgoing long-wave radiation data. Regression maps of NCEP–NCAR reanalysis data for the northern winter show statistically significant upper-tropospheric equatorial wave patterns linked to the tropical convection anomalies, and extratropical wave patterns over the North Pacific, North America, the Atlantic, the Southern Ocean and South America. To assess the cause of the circulation anomalies, a global primitive-equation model was initialized with the observed three-dimensional (3D) winter climatological mean flow and forced with a time-dependent heat source derived from the observed MJO anomalies. A model MJO cycle was constructed from the global response to the heating, and both the tropical and extratropical circulation anomalies generally matched the observations well. The equatorial wave patterns are established in a few days, while it takes approximately two weeks for the extratropical patterns to appear. The model response is robust and insensitive to realistic changes in damping and basic state. The model tropical anomalies are consistent with a forced equatorial Rossby–Kelvin wave response to the tropical MJO heating, although it is shifted westward by approximately 20° longitude relative to observations. This may be due to a lack of damping processes (cumulus friction) in the regions of convective heating. Once this shift is accounted for, the extratropical response is consistent with theories of Rossby wave forcing and dispersion on the climatological flow, and the pattern correlation between the observed and modelled extratropical flow is up to 0.85. The observed tropical and extratropical wave patterns account for a significant fraction of the intraseasonal circulation variance, and this reproducibility as a response to tropical MJO convection has implications for global medium-range weather prediction. Copyright © 2004 Royal Meteorological Society

North Atlantic Oscillation response to transient greenhouse gas forcing and the impact on European winter climate: a CMIP2 multi-model assessment

This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO2) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO2, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5-10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970-1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO2 concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061 +/- 0.0036 hPa per %CO2. Although an increase of 0.61 hPa in NAO for a doubling in CO2 represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models' inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to 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.

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.

A kinematically distorted flux rope model for magnetic clouds

Constant-α force-free magnetic flux rope models have proven to be a valuable first step toward understanding the global context of in situ observations of magnetic clouds. However, cylindrical symmetry is necessarily assumed when using such models, and it is apparent from both observations and modeling that magnetic clouds have highly noncircular cross sections. A number of approaches have been adopted to relax the circular cross section approximation: frequently, the cross-sectional shape is allowed to take an arbitrarily chosen shape (usually elliptical), increasing the number of free parameters that are fit between data and model. While a better “fit” may be achieved in terms of reducing the mean square error between the model and observed magnetic field time series, it is not always clear that this translates to a more accurate reconstruction of the global structure of the magnetic cloud. We develop a new, noncircular cross section flux rope model that is constrained by observations of CMEs/ICMEs and knowledge of the physical processes acting on the magnetic cloud: The magnetic cloud is assumed to initially take the form of a force-free flux rope in the low corona but to be subsequently deformed by a combination of axis-centered self-expansion and heliocentric radial expansion. The resulting analytical solution is validated by fitting to artificial time series produced by numerical MHD simulations of magnetic clouds and shown to accurately reproduce the global structure.

Changes in the global sulfate burden due to perturbations in global CO2 concentrations

A large ensemble of general circulation model (GCM) integrations coupled to a fully interactive sulfur cycle scheme were run on the climateprediction.net platform to investigate the uncertainty in the climate response to sulfate aerosol and carbon dioxide (CO2) forcing. The sulfate burden within the model (and the atmosphere) depends on the balance between formation processes and deposition (wet and dry). The wet removal processes for sulfate aerosol are much faster than dry removal and so any changes in atmospheric circulation, cloud cover, and precipitation will feed back on the sulfate burden. When CO2 is doubled in the Hadley Centre Slab Ocean Model (HadSM3), global mean precipitation increased by 5%; however, the global mean sulfate burden increased by 10%. Despite the global mean increase in precipitation, there were large areas of the model showing decreases in precipitation (and cloud cover) in the Northern Hemisphere during June–August, which reduced wet deposition and allowed the sulfate burden to increase. Further experiments were also undertaken with and without doubling CO2 while including a future anthropogenic sulfur emissions scenario. Doubling CO2 further enhanced the increases in sulfate burden associated with increased anthropogenic sulfur emissions as observed in the doubled CO2-only experiment. The implications are that the climate response to doubling CO2 can influence the amount of sulfate within the atmosphere and, despite increases in global mean precipitation, may act to increase it.

Global scale water stages from SAR imagery (GlosSARi) to support global flood forecasting

Despite the success of studies attempting to integrate remotely sensed data and flood modelling and the need to provide near-real time data routinely on a global scale as well as setting up online data archives, there is to date a lack of spatially and temporally distributed hydraulic parameters to support ongoing efforts in modelling. Therefore, the objective of this project is to provide a global evaluation and benchmark data set of floodplain water stages with uncertainties and assimilation in a large scale flood model using space-borne radar imagery. An algorithm is developed for automated retrieval of water stages with uncertainties from a sequence of radar imagery and data are assimilated in a flood model using the Tewkesbury 2007 flood event as a feasibility study. The retrieval method that we employ is based on possibility theory which is an extension of fuzzy sets and that encompasses probability theory. In our case we first attempt to identify main sources of uncertainty in the retrieval of water stages from radar imagery for which we define physically meaningful ranges of parameter values. Possibilities of values are then computed for each parameter using a triangular ‘membership’ function. This procedure allows the computation of possible values of water stages at maximum flood extents along a river at many different locations. At a later stage in the project these data are then used in assimilation, calibration or validation of a flood model. The application is subsequently extended to a global scale using wide swath radar imagery and a simple global flood forecasting model thereby providing improved river discharge estimates to update the latter.

The impact of global freshwater forcing on the thermohaline circulation: adjustment of North Atlantic convection sites in a CGCM

On the time scale of a century, the Atlantic thermohaline circulation (THC) is sensitive to the global surface salinity distribution. The advection of salinity toward the deep convection sites of the North Atlantic is one of the driving mechanisms for the THC. There is both a northward and a southward contributions. The northward salinity advection (Nsa) is related to the evaporation in the subtropics, and contributes to increased salinity in the convection sites. The southward salinity advection (Ssa) is related to the Arctic freshwater forcing and tends on the contrary to diminish salinity in the convection sites. The THC changes results from a delicate balance between these opposing mechanisms. In this study we evaluate these two effects using the IPSL-CM4 ocean-atmosphere-sea-ice coupled model (used for IPCC AR4). Perturbation experiments have been integrated for 100 years under modern insolation and trace gases. River runoff and evaporation minus precipitation are successively set to zero for the ocean during the coupling procedure. This allows the effect of processes Nsa and Ssa to be estimated with their specific time scales. It is shown that the convection sites in the North Atlantic exhibit various sensitivities to these processes. The Labrador Sea exhibits a dominant sensitivity to local forcing and Ssa with a typical time scale of 10 years, whereas the Irminger Sea is mostly sensitive to Nsa with a 15 year time scale. The GIN Seas respond to both effects with a time scale of 10 years for Ssa and 20 years for Nsa. It is concluded that, in the IPSL-CM4, the global freshwater forcing damps the THC on centennial time scales.

Global hydrology modelling and uncertainty: running multiple ensembles with a campus grid.

Uncertainties associated with the representation of various physical processes in global climate models (GCMs) mean that, when projections from GCMs are used in climate change impact studies, the uncertainty propagates through to the impact estimates. A complete treatment of this ‘climate model structural uncertainty’ is necessary so that decision-makers are presented with an uncertainty range around the impact estimates. This uncertainty is often underexplored owing to the human and computer processing time required to perform the numerous simulations. Here, we present a 189-member ensemble of global river runoff and water resource stress simulations that adequately address this uncertainty. Following several adaptations and modifications, the ensemble creation time has been reduced from 750 h on a typical single-processor personal computer to 9 h of high-throughput computing on the University of Reading Campus Grid. Here, we outline the changes that had to be made to the hydrological impacts model and to the Campus Grid, and present the main results. We show that, although there is considerable uncertainty in both the magnitude and the sign of regional runoff changes across different GCMs with climate change, there is much less uncertainty in runoff changes for regions that experience large runoff increases (e.g. the high northern latitudes and Central Asia) and large runoff decreases (e.g. the Mediterranean). Furthermore, there is consensus that the percentage of the global population at risk to water resource stress will increase with climate change.

Global estimates of snow water equivalent from passive microwave instruments: history, challenges and future developments

Snow properties have been retrieved from satellite data for many decades. While snow extent is generally felt to be obtained reliably from visible-band data, there is less confidence in the measurements of snow mass or water equivalent derived from passive microwave instruments. This paper briefly reviews historical passive microwave instruments and products, and compares the large-scale patterns from these sources to those of general circulation models and leading reanalysis products. Differences are seen to be large between the datasets, particularly over Siberia. A better understanding of the errors in both the model-based and measurement-based datasets is required to exploit both fully. Techniques to apply to the satellite measurements for improved large-scale snow data are suggested.

Recent changes in solar outputs and the global mean surface temperature. III. Analysis of contributions to global mean air surface temperature rise

A multivariate fit to the variation in global mean surface air temperature anomaly over the past half century is presented. The fit procedure allows for the effect of response time on the waveform, amplitude and lag of each radiative forcing input, and each is allowed to have its own time constant. It is shown that the contribution of solar variability to the temperature trend since 1987 is small and downward; the best estimate is -1.3% and the 2sigma confidence level sets the uncertainty range of -0.7 to -1.9%. The result is the same if one quantifies the solar variation using galactic cosmic ray fluxes (for which the analysis can be extended back to 1953) or the most accurate total solar irradiance data composite. The rise in the global mean air surface temperatures is predominantly associated with a linear increase that represents the combined effects of changes in anthropogenic well-mixed greenhouse gases and aerosols, although, in recent decades, there is also a considerable contribution by a relative lack of major volcanic eruptions. The best estimate is that the anthropogenic factors contribute 75% of the rise since 1987, with an uncertainty range (set by the 2sigma confidence level using an AR(1) noise model) of 49–160%; thus, the uncertainty is large, but we can state that at least half of the temperature trend comes from the linear term and that this term could explain the entire rise. The results are consistent with the intergovernmental panel on climate change (IPCC) estimates of the changes in radiative forcing (given for 1961–1995) and are here combined with those estimates to find the response times, equilibrium climate sensitivities and pertinent heat capacities (i.e. the depth into the oceans to which a given radiative forcing variation penetrates) of the quasi-periodic (decadal-scale) input forcing variations. As shown by previous studies, the decadal-scale variations do not penetrate as deeply into the oceans as the longer term drifts and have shorter response times. Hence, conclusions about the response to century-scale forcing changes (and hence the associated equilibrium climate sensitivity and the temperature rise commitment) cannot be made from studies of the response to shorter period forcing changes.

Constraining a North Atlantic Ocean general circulation model with chlorofluorocarbon observations

Measurements of anthropogenic tracers such as chlorofluorocarbons and tritium must be quantitatively combined with ocean general circulation models as a component of systematic model development. The authors have developed and tested an inverse method, using a Green's function, to constrain general circulation models with transient tracer data. Using this method chlorofluorocarbon-11 and -12 (CFC-11 and -12) observations are combined with a North Atlantic configuration of the Miami Isopycnic Coordinate Ocean Model with 4/3 degrees resolution. Systematic differences can be seen between the observed CFC concentrations and prior CFC fields simulated by the model. These differences are reduced by the inversion, which determines the optimal gas transfer across the air-sea interface, accounting for uncertainties in the tracer observations. After including the effects of unresolved variability in the CFC fields, the model is found to be inconsistent with the observations because the model/data misfit slightly exceeds the error estimates. By excluding observations in waters ventilated north of the Greenland-Scotland ridge (sigma (0) < 27.82 kg m(-3); shallower than about 2000 m), the fit is improved, indicating that the Nordic overflows are poorly represented in the model. Some systematic differences in the model/data residuals remain and are related, in part, to excessively deep model ventilation near Rockall and deficient ventilation in the main thermocline of the eastern subtropical gyre. Nevertheless, there do not appear to be gross errors in the basin-scale model circulation. Analysis of the CFC inventory using the constrained model suggests that the North Atlantic Ocean shallower than about 2000 m was near 20% saturated in the mid-1990s. Overall, this basin is a sink to 22% of the total atmosphere-to-ocean CFC-11 flux-twice the global average value. The average water mass formation rates over the CFC transient are 7.0 and 6.0 Sv (Sv = 10(6) m(3) s(-1)) for subtropical mode water and subpolar mode water, respectively.

Orography in a contour dynamics model of large-scale atmospheric flow

The influence of orography on the structure of stationary planetary Rossby waves is studied in the context of a contour dynamics model of the large-scale atmospheric flow. Orography of infinitesimal and finite amplitude is studied using analytical and numerical techniques. Three different types of orography are considered: idealized orography in the form of a global wave, idealized orography in the form of a local table mountain, and the earth's orography. The study confirms the importance of resonances, both in the infinitesimal orography and in the finite orography cases. With finite orography the stationary waves organize themselves into a one-dimensional set of solutions, which due to the resonances, is piecewise connected. It is pointed out that these stationary waves could be relevant for atmospheric regimes.

A review of growth for construction service companies in global markets

Throughout the developed world, professional services play an increasingly important part in an economy, with many countries showing a substantial positive trade balance for services. Yet, there has been relatively little research on construction services (CS) and, in particular, how well professional service companies (PSFs) perform in the international arena. The method for collecting services export information differs to the way in which goods and products exports data are gathered because of the intangible nature of services. Organisational growth of companies aims to share risks across different regions and sectors, however, the rapidly changing business environment challenges companies with the increasing foreign ownership and changes in procurement. The complexity of today’s international construction services organisations raises two questions: how the organisations can successfully manage growth and what are their motives for international trade. The research focuses on top UK consulting engineering companies to understand their organisational strategy, their export strategy, and drivers for overseas activities. The data will feed a model of professional services exports, which can help to inform the way services export data could be collected to better reflect the industry’s performance.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.