Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5

The new Max-Planck-Institute Earth System Model (MPI-ESM) is used in the Coupled Model Intercomparison Project phase 5 (CMIP5) in a series of climate change experiments for either idealized CO2-only forcing or forcings based on observations and the Representative Concentration Pathway (RCP) scenarios. The paper gives an overview of the model configurations, experiments related forcings, and initialization procedures and presents results for the simulated changes in climate and carbon cycle. It is found that the climate feedback depends on the global warming and possibly the forcing history. The global warming from climatological 1850 conditions to 2080–2100 ranges from 1.5°C under the RCP2.6 scenario to 4.4°C under the RCP8.5 scenario. Over this range, the patterns of temperature and precipitation change are nearly independent of the global warming. The model shows a tendency to reduce the ocean heat uptake efficiency toward a warmer climate, and hence acceleration in warming in the later years. The precipitation sensitivity can be as high as 2.5% K−1 if the CO2 concentration is constant, or as small as 1.6% K−1, if the CO2 concentration is increasing. The oceanic uptake of anthropogenic carbon increases over time in all scenarios, being smallest in the experiment forced by RCP2.6 and largest in that for RCP8.5. The land also serves as a net carbon sink in all scenarios, predominantly in boreal regions. The strong tropical carbon sources found in the RCP2.6 and RCP8.5 experiments are almost absent in the RCP4.5 experiment, which can be explained by reforestation in the RCP4.5 scenario.

A parallel formulation for the simulation of a generic branch predictor

A parallel formulation for the simulation of a branch prediction algorithm is presented. This parallel formulation identifies independent tasks in the algorithm which can be executed concurrently. The parallel implementation is based on the multithreading model and two parallel programming platforms: pthreads and Cilk++. Improvement in execution performance by up to 7 times is observed for a generic 2-bit predictor in a 12-core multiprocessor system.

Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model

Operational forecasting centres are currently developing data assimilation systems for coupled atmosphere-ocean models. Strongly coupled assimilation, in which a single assimilation system is applied to a coupled model, presents significant technical and scientific challenges. Hence weakly coupled assimilation systems are being developed as a first step, in which the coupled model is used to compare the current state estimate with observations, but corrections to the atmosphere and ocean initial conditions are then calculated independently. In this paper we provide a comprehensive description of the different coupled assimilation methodologies in the context of four dimensional variational assimilation (4D-Var) and use an idealised framework to assess the expected benefits of moving towards coupled data assimilation. We implement an incremental 4D-Var system within an idealised single column atmosphere-ocean model. The system has the capability to run both strongly and weakly coupled assimilations as well as uncoupled atmosphere or ocean only assimilations, thus allowing a systematic comparison of the different strategies for treating the coupled data assimilation problem. We present results from a series of identical twin experiments devised to investigate the behaviour and sensitivities of the different approaches. Overall, our study demonstrates the potential benefits that may be expected from coupled data assimilation. When compared to uncoupled initialisation, coupled assimilation is able to produce more balanced initial analysis fields, thus reducing initialisation shock and its impact on the subsequent forecast. Single observation experiments demonstrate how coupled assimilation systems are able to pass information between the atmosphere and ocean and therefore use near-surface data to greater effect. We show that much of this benefit may also be gained from a weakly coupled assimilation system, but that this can be sensitive to the parameters used in the assimilation.

Dual semiosis analysis model managing customer-focused service innovation

Customers will not continue to pay for a service if it is perceived to be of poor quality, and/or of no value. With a paradigm shift towards business dependence on service orientated IS solutions [1], it is critical that alignment exists between service definition, delivery, and customer expectation, businesses are to ensure customer satisfaction. Services, and micro-service development, offer businesses a flexible structure for solution innovation, however, constant changes in technology, business and societal expectations means an iterative analysis solution is required to i) determine whether provider services adequately meet customer segment needs and expectations, and ii) to help guide business service innovation and development. In this paper, by incorporating multiple models, we propose a series of steps to help identify and prioritise service gaps. Moreover, the authors propose the Dual Semiosis Analysis Model, i.e. a tool that highlights where within the symbiotic customer / provider semiosis process, requirements misinterpretation, and/or service provision deficiencies occur. This paper offers the reader a powerful customer-centric tool, designed to help business managers highlight both what services are critical to customer quality perception, and where future innovation

Improving the TanDEM-X Digital Elevation Model for flood modelling using flood extents from Synthetic Aperture Radar images

The topography of many floodplains in the developed world has now been surveyed with high resolution sensors such as airborne LiDAR (Light Detection and Ranging), giving accurate Digital Elevation Models (DEMs) that facilitate accurate flood inundation modelling. This is not always the case for remote rivers in developing countries. However, the accuracy of DEMs produced for modelling studies on such rivers should be enhanced in the near future by the high resolution TanDEM-X WorldDEM. In a parallel development, increasing use is now being made of flood extents derived from high resolution Synthetic Aperture Radar (SAR) images for calibrating, validating and assimilating observations into flood inundation models in order to improve these. This paper discusses an additional use of SAR flood extents, namely to improve the accuracy of the TanDEM-X DEM in the floodplain covered by the flood extents, thereby permanently improving this DEM for future flood modelling and other studies. The method is based on the fact that for larger rivers the water elevation generally changes only slowly along a reach, so that the boundary of the flood extent (the waterline) can be regarded locally as a quasi-contour. As a result, heights of adjacent pixels along a small section of waterline can be regarded as samples with a common population mean. The height of the central pixel in the section can be replaced with the average of these heights, leading to a more accurate estimate. While this will result in a reduction in the height errors along a waterline, the waterline is a linear feature in a two-dimensional space. However, improvements to the DEM heights between adjacent pairs of waterlines can also be made, because DEM heights enclosed by the higher waterline of a pair must be at least no higher than the corrected heights along the higher waterline, whereas DEM heights not enclosed by the lower waterline must in general be no lower than the corrected heights along the lower waterline. In addition, DEM heights between the higher and lower waterlines can also be assigned smaller errors because of the reduced errors on the corrected waterline heights. The method was tested on a section of the TanDEM-X Intermediate DEM (IDEM) covering an 11km reach of the Warwickshire Avon, England. Flood extents from four COSMO-SKyMed images were available at various stages of a flood in November 2012, and a LiDAR DEM was available for validation. In the area covered by the flood extents, the original IDEM heights had a mean difference from the corresponding LiDAR heights of 0.5 m with a standard deviation of 2.0 m, while the corrected heights had a mean difference of 0.3 m with standard deviation 1.2 m. These figures show that significant reductions in IDEM height bias and error can be made using the method, with the corrected error being only 60% of the original. Even if only a single SAR image obtained near the peak of the flood was used, the corrected error was only 66% of the original. The method should also be capable of improving the final TanDEM-X DEM and other DEMs, and may also be of use with data from the SWOT (Surface Water and Ocean Topography) satellite.

Using data insertion with the NAME model to simulate the 8 May 2010 Eyjafjallajökull volcanic ash cloud

A data insertion method, where a dispersion model is initialized from ash properties derived from a series of satellite observations, is used to model the 8 May 2010 Eyjafjallajökull volcanic ash cloud which extended from Iceland to northern Spain. We also briefly discuss the application of this method to the April 2010 phase of the Eyjafjallajökull eruption and the May 2011 Grímsvötn eruption. An advantage of this method is that very little knowledge about the eruption itself is required because some of the usual eruption source parameters are not used. The method may therefore be useful for remote volcanoes where good satellite observations of the erupted material are available, but little is known about the properties of the actual eruption. It does, however, have a number of limitations related to the quality and availability of the observations. We demonstrate that, using certain configurations, the data insertion method is able to capture the structure of a thin filament of ash extending over northern Spain that is not fully captured by other modeling methods. It also verifies well against the satellite observations according to the quantitative object-based quality metric, SAL—structure, amplitude, location, and the spatial coverage metric, Figure of Merit in Space.

Comparison of terrain following and cut cell grids using a non-hydrostatic model

Terrain following coordinates are widely used in operational models but the cut cell method has been proposed as an alternative that can more accurately represent atmospheric dynamics over steep orography. Because the type of grid is usually chosen during model implementation, it becomes necessary to use different models to compare the accuracy of different grids. In contrast, here a C-grid finite volume model enables a like-for-like comparison of terrain following and cut cell grids. A series of standard two-dimensional tests using idealised terrain are performed: tracer advection in a prescribed horizontal velocity field, a test starting from resting initial conditions, and orographically induced gravity waves described by nonhydrostatic dynamics. In addition, three new tests are formulated: a more challenging resting atmosphere case, and two new advection tests having a velocity field that is everywhere tangential to the terrain following coordinate surfaces. These new tests present a challenge on cut cell grids. The results of the advection tests demonstrate that accuracy depends primarily upon alignment of the flow with the grid rather than grid orthogonality. A resting atmosphere is well-maintained on all grids. In the gravity waves test, results on all grids are in good agreement with existing results from the literature, although terrain following velocity fields lead to errors on cut cell grids. Due to semi-implicit timestepping and an upwind-biased, explicit advection scheme, there are no timestep restrictions associated with small cut cells. We do not find the significant advantages of cut cells or smoothed coordinates that other authors find.

Closed-loop feedback computation model of dynamical reputation based on the local trust evaluation in business-to-consumer e-commerce

Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC) e-commerce is the “all good reputation” problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers’ local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce.