310 resultados para Global model


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Abstract We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global Energy Forecasting Competition (GEFCom 2012). We begin by motivating and presenting a simple parametric model, treating the electricity demand as a function of the temperature and day of the data. We then set out a series of refinements of the model, explaining the rationale for each, and using the competition scores to demonstrate that each successive refinement step increases the accuracy of the model’s predictions. These refinements include combining models from multiple weather stations, removing outliers from the historical data, and special treatments of public holidays.

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The “cotton issue” has been a topic of several academic discussions for trade policy analysts. However the design of trade and agricultural policy in the EU and the USA has become a politically sensitive matter throughout the last five years. This study utilizing the Agricultural Trade Policy Simulation Model (ATPSM) aims to gain insights into the global cotton market, to explain why domestic support for cotton has become an issue, to quantify the impact of the new EU agricultural policy on the cotton sector, and to measure the effect of eliminating support policies on production and trade. Results indicate that full trade liberalization would lead the four West African countries to better terms of trade with the EU. If tariff reduction follows the so-called Swiss formula, world prices would increase by 3.5%.

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The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project, using PRACE (Partnership for Advanced Computing in Europe) resources, constructed and ran an ensemble of atmosphere-only global climate model simulations, using the Met Office Unified Model GA3 configuration. Each simulation is 27 years in length for both the present climate and an end-of-century future climate, at resolutions of N96 (130 km), N216 (60 km) and N512 (25 km), in order to study the impact of model resolution on high impact climate features such as tropical cyclones. Increased model resolution is found to improve the simulated frequency of explicitly tracked tropical cyclones, and correlations of interannual variability in the North Atlantic and North West Pacific lie between 0.6 and 0.75. Improvements in the deficit of genesis in the eastern North Atlantic as resolution increases appear to be related to the representation of African Easterly Waves and the African Easterly Jet. However, the intensity of the modelled tropical cyclones as measured by 10 m wind speed remain weak, and there is no indication of convergence over this range of resolutions. In the future climate ensemble, there is a reduction of 50% in the frequency of Southern Hemisphere tropical cyclones, while in the Northern Hemisphere there is a reduction in the North Atlantic, and a shift in the Pacific with peak intensities becoming more common in the Central Pacific. There is also a change in tropical cyclone intensities, with the future climate having fewer weak storms and proportionally more stronger storms

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We present a new parameterisation that relates surface mass balance (SMB: the sum of surface accumulation and surface ablation) to changes in surface elevation of the Greenland ice sheet (GrIS) for the MAR (Modèle Atmosphérique Régional: Fettweis, 2007) regional climate model. The motivation is to dynamically adjust SMB as the GrIS evolves, allowing us to force ice sheet models with SMB simulated by MAR while incorporating the SMB–elevation feedback, without the substantial technical challenges of coupling ice sheet and climate models. This also allows us to assess the effect of elevation feedback uncertainty on the GrIS contribution to sea level, using multiple global climate and ice sheet models, without the need for additional, expensive MAR simulations. We estimate this relationship separately below and above the equilibrium line altitude (ELA, separating negative and positive SMB) and for regions north and south of 77� N, from a set of MAR simulations in which we alter the ice sheet surface elevation. These give four “SMB lapse rates”, gradients that relate SMB changes to elevation changes. We assess uncertainties within a Bayesian framework, estimating probability distributions for each gradient from which we present best estimates and credibility intervals (CI) that bound 95% of the probability. Below the ELA our gradient estimates are mostly positive, because SMB usually increases with elevation: 0.56 (95% CI: −0.22 to 1.33) kgm−3 a−1 for the north, and 1.91 (1.03 to 2.61) kgm−3 a−1 for the south. Above the ELA, the gradients are much smaller in magnitude: 0.09 (−0.03 to 0.23) kgm−3 a−1 in the north, and 0.07 (−0.07 to 0.59) kgm−3 a−1 in the south, because SMB can either increase or decrease in response to increased elevation. Our statistically founded approach allows us to make probabilistic assessments for the effect of elevation feedback uncertainty on sea level projections (Edwards et al., 2014).

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We compare the quasi-equilibrium heat balances, as well as their responses to 4×CO2 perturbation, among three global climate models with the aim to identify and explain inter-model differences in ocean heat uptake (OHU) processes. We find that, in quasi-equilibrium, convective and mixed layer processes, as well as eddy-related processes, cause cooling of the subsurface ocean. The cooling is balanced by warming caused by advective and diapycnally diffusive processes. We also find that in the CO2-perturbed climates the largest contribution to OHU comes from changes in vertical mixing processes and the mean circulation, particularly in the extra-tropics, caused both by changes in wind forcing, and by changes in high-latitude buoyancy forcing. There is a substantial warming in the tropics, a significant part of which occurs because of changes in horizontal advection in extra-tropics. Diapycnal diffusion makes only a weak contribution to the OHU, mainly in the tropics, due to increased stratification. There are important qualitative differences in the contribution of eddy-induced advection and isopycnal diffusion to the OHU among the models. The former is related to the different values of the coefficients used in the corresponding scheme. The latter is related to the different tapering formulations of the isopycnal diffusion scheme. These differences affect the OHU in the deep ocean, which is substantial in two of the models, the dominant region of deep warming being the Southern Ocean. However, most of the OHU takes place above 2000 m, and the three models are quantitatively similar in their global OHU efficiency and its breakdown among processes and as a function of latitude.

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Mass loss by glaciers has been an important contributor to sea level rise in the past, and is projected to contribute a substantial fraction of total sea level rise during the 21st century. Here, we use a model of the world's glaciers to quantify equilibrium sensitivities of global glacier mass to climate change, and to investigate the role of changes in glacier hypsometry for long-term mass changes. We find that 21st century glacier-mass loss is largely governed by the glacier's response to 20th century climate change. This limits the influence of 21st century climate change on glacier-mass loss, and explains why there are relatively small differences in glacier-mass loss under greatly different scenarios of climate change. The projected future changes in both temperature and precipitation experienced by glaciers are amplified relative to the global average. The projected increase in precipitation partly compensates for the mass loss caused by warming, but this compensation is negligible at higher temperature anomalies since an increasing fraction of precipitation at the glacier sites is liquid. Loss of low-lying glacier area, and more importantly, eventual complete disappearance of glaciers, strongly limit the projected sea level contribution from glaciers in coming centuries. The adjustment of glacier hypsometry to changes in the forcing strongly reduces the rates of global glacier-mass loss caused by changes in global mean temperature compared to rates of mass loss when hypsometric changes are neglected. This result is a second reason for the relatively weak dependence of glacier-mass loss on future climate scenario, and helps explain why glacier-mass loss in the first half of the 20th century was of the same order of magnitude as in the second half of the 20th century, even though the rate of warming was considerably smaller.

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Incomplete understanding of three aspects of the climate system—equilibrium climate sensitivity, rate of ocean heat uptake and historical aerosol forcing—and the physical processes underlying them lead to uncertainties in our assessment of the global-mean temperature evolution in the twenty-first century1,2. Explorations of these uncertainties have so far relied on scaling approaches3,4, large ensembles of simplified climate models1,2, or small ensembles of complex coupled atmosphere–ocean general circulation models5,6 which under-represent uncertainties in key climate system properties derived from independent sources7–9. Here we present results from a multi-thousand-member perturbed-physics ensemble of transient coupled atmosphere–ocean general circulation model simulations. We find that model versions that reproduce observed surface temperature changes over the past 50 years show global-mean temperature increases of 1.4–3 K by 2050, relative to 1961–1990, under a mid-range forcing scenario. This range of warming is broadly consistent with the expert assessment provided by the Intergovernmental Panel on Climate Change Fourth Assessment Report10, but extends towards larger warming than observed in ensemblesof-opportunity5 typically used for climate impact assessments. From our simulations, we conclude that warming by the middle of the twenty-first century that is stronger than earlier estimates is consistent with recent observed temperature changes and a mid-range ‘no mitigation’ scenario for greenhouse-gas emissions.

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Purpose – Multinationals have always needed an operating model that works – an effective plan for executing their most important activities at the right levels of their organization, whether globally, regionally or locally. The choices involved in these decisions have never been obvious, since international firms have consistently faced trade‐offs between tailoring approaches for diverse local markets and leveraging their global scale. This paper seeks a more in‐depth understanding of how successful firms manage the global‐local trade‐off in a multipolar world. Design methodology/approach – This paper utilizes a case study approach based on in‐depth senior executive interviews at several telecommunications companies including Tata Communications. The interviews probed the operating models of the companies we studied, focusing on their approaches to organization structure, management processes, management technologies (including information technology (IT)) and people/talent. Findings – Successful companies balance global‐local trade‐offs by taking a flexible and tailored approach toward their operating‐model decisions. The paper finds that successful companies, including Tata Communications, which is profiled in‐depth, are breaking up the global‐local conundrum into a set of more manageable strategic problems – what the authors call “pressure points” – which they identify by assessing their most important activities and capabilities and determining the global and local challenges associated with them. They then design a different operating model solution for each pressure point, and repeat this process as new strategic developments emerge. By doing so they not only enhance their agility, but they also continually calibrate that crucial balance between global efficiency and local responsiveness. Originality/value – This paper takes a unique approach to operating model design, finding that an operating model is better viewed as several distinct solutions to specific “pressure points” rather than a single and inflexible model that addresses all challenges equally. Now more than ever, developing the right operating model is at the top of multinational executives' priorities, and an area of increasing concern; the international business arena has changed drastically, requiring thoughtfulness and flexibility instead of standard formulas for operating internationally. Old adages like “think global and act local” no longer provide the universal guidance they once seemed to.

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Using a numerical implementation of the Cowley and Lockwood (1992) model of flow excitation in the magnetosphere–ionosphere (MI) system, we show that both an expanding (on a _12-min timescale) and a quasiinstantaneous response in ionospheric convection to the onset of magnetopause reconnection can be accommodated by the Cowley–Lockwood conceptual framework. This model has a key feature of time dependence, necessarily considering the history of the coupled MI system. We show that a residual flow, driven by prior magnetopause reconnection, can produce a quasi-instantaneous global ionospheric convection response; perturbations from an equilibrium state may also be present from tail reconnection, which will superpose constructively to give a similar effect. On the other hand, when the MI system is relatively free of pre-existing flow, we can most clearly see the expanding nature of the response. As the open-closed field line boundary will frequently be in motion from such prior reconnection (both at the dayside magnetopause and in the cross-tail current sheet), it is expected that there will usually be some level of combined response to dayside reconnection.

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Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.

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This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

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We use a stratosphere–troposphere composition–climate model with interactive sulfur chemistry and aerosol microphysics, to investigate the effect of the 1991 Mount Pinatubo eruption on stratospheric aerosol properties. Satellite measurements indicate that shortly after the eruption, between 14 and 23 Tg of SO2 (7 to 11.5 Tg of sulfur) was present in the tropical stratosphere. Best estimates of the peak global stratospheric aerosol burden are in the range 19 to 26 Tg, or 3.7 to 6.7 Tg of sulfur assuming a composition of between 59 and 77 % H2SO4. In light of this large uncertainty range, we performed two main simulations with 10 and 20 Tg of SO2 injected into the tropical lower stratosphere. Simulated stratospheric aerosol properties through the 1991 to 1995 period are compared against a range of available satellite and in situ measurements. Stratospheric aerosol optical depth (sAOD) and effective radius from both simulations show good qualitative agreement with the observations, with the timing of peak sAOD and decay timescale matching well with the observations in the tropics and mid-latitudes. However, injecting 20 Tg gives a factor of 2 too high stratospheric aerosol mass burden compared to the satellite data, with consequent strong high biases in simulated sAOD and surface area density, with the 10 Tg injection in much better agreement. Our model cannot explain the large fraction of the injected sulfur that the satellite-derived SO2 and aerosol burdens indicate was removed within the first few months after the eruption. We suggest that either there is an additional alternative loss pathway for the SO2 not included in our model (e.g. via accommodation into ash or ice in the volcanic cloud) or that a larger proportion of the injected sulfur was removed via cross-tropopause transport than in our simulations. We also critically evaluate the simulated evolution of the particle size distribution, comparing in detail to balloon-borne optical particle counter (OPC) measurements from Laramie, Wyoming, USA (41° N). Overall, the model captures remarkably well the complex variations in particle concentration profiles across the different OPC size channels. However, for the 19 to 27 km injection height-range used here, both runs have a modest high bias in the lowermost stratosphere for the finest particles (radii less than 250 nm), and the decay timescale is longer in the model for these particles, with a much later return to background conditions. Also, whereas the 10 Tg run compared best to the satellite measurements, a significant low bias is apparent in the coarser size channels in the volcanically perturbed lower stratosphere. Overall, our results suggest that, with appropriate calibration, aerosol microphysics models are capable of capturing the observed variation in particle size distribution in the stratosphere across both volcanically perturbed and quiescent conditions. Furthermore, additional sensitivity simulations suggest that predictions with the models are robust to uncertainties in sub-grid particle formation and nucleation rates in the stratosphere.

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We report on the first realtime ionospheric predictions network and its capabilities to ingest a global database and forecast F-layer characteristics and "in situ" electron densities along the track of an orbiting spacecraft. A global network of ionosonde stations reported around-the-clock observations of F-region heights and densities, and an on-line library of models provided forecasting capabilities. Each model was tested against the incoming data; relative accuracies were intercompared to determine the best overall fit to the prevailing conditions; and the best-fit model was used to predict ionospheric conditions on an orbit-to-orbit basis for the 12-hour period following a twice-daily model test and validation procedure. It was found that the best-fit model often provided averaged (i.e., climatologically-based) accuracies better than 5% in predicting the heights and critical frequencies of the F-region peaks in the latitudinal domain of the TSS-1R flight path. There was a sharp contrast however, in model-measurement comparisons involving predictions of actual, unaveraged, along-track densities at the 295 km orbital altitude of TSS-1R In this case, extrema in the first-principle models varied by as much as an order of magnitude in density predictions, and the best-fit models were found to disagree with the "in situ" observations of Ne by as much as 140%. The discrepancies are interpreted as a manifestation of difficulties in accurately and self-consistently modeling the external controls of solar and magnetospheric inputs and the spatial and temporal variabilities in electric fields, thermospheric winds, plasmaspheric fluxes, and chemistry.

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ERA-Interim/Land is a global land surface reanalysis data set covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land is the result of a single 32-year simulation with the latest ECMWF (European Centre for Medium-Range Weather Forecasts) land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanalysis and precipitation adjustments based on monthly GPCP v2.1 (Global Precipitation Climatology Project). The horizontal resolution is about 80 km and the time frequency is 3-hourly. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim data set, which makes it more suitable for climate studies involving land water resources. The quality of ERA-Interim/Land is assessed by comparing with ground-based and remote sensing observations. In particular, estimates of soil moisture, snow depth, surface albedo, turbulent latent and sensible fluxes, and river discharges are verified against a large number of site measurements. ERA-Interim/Land provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models.

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We present a simple, generic model of annual tree growth, called "T". This model accepts input from a first-principles light-use efficiency model (the "P" model). The P model provides values for gross primary production (GPP) per unit of absorbed photosynthetically active radiation (PAR). Absorbed PAR is estimated from the current leaf area. GPP is allocated to foliage, transport tissue, and fine-root production and respiration in such a way as to satisfy well-understood dimensional and functional relationships. Our approach thereby integrates two modelling approaches separately developed in the global carbon-cycle and forest-science literature. The T model can represent both ontogenetic effects (the impact of ageing) and the effects of environmental variations and trends (climate and CO2) on growth. Driven by local climate records, the model was applied to simulate ring widths during the period 1958–2006 for multiple trees of Pinus koraiensis from the Changbai Mountains in northeastern China. Each tree was initialised at its actual diameter at the time when local climate records started. The model produces realistic simulations of the interannual variability in ring width for different age cohorts (young, mature, and old). Both the simulations and observations show a significant positive response of tree-ring width to growing-season total photosynthetically active radiation (PAR0) and the ratio of actual to potential evapotranspiration (α), and a significant negative response to mean annual temperature (MAT). The slopes of the simulated and observed relationships with PAR0 and α are similar; the negative response to MAT is underestimated by the model. Comparison of simulations with fixed and changing atmospheric CO2 concentration shows that CO2 fertilisation over the past 50 years is too small to be distinguished in the ring-width data, given ontogenetic trends and interannual variability in climate.