41 research outputs found

    R&D Business Investment in the EU ICT Sector

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    The EU spends only about half as much on R&D in ICT as the US. This holds true both in absolute amounts and relative to the size of the economy. Indeed, the ICT sector alone is responsible for as much of the overall R&D investment gap as all other sectors combined. From the current data analysis, there are no signs of the ICT R&D investment gap closing. At ICT sector level, the R&D investment gap exists partly because the ICT sector is smaller in the EU than in the US and partly because of the lower R&D intensity of the sector in the EU. The lower R&D intensity is, in turn, primarily due to two sub-sectors: computer services and software on the one hand, and electronic measurement instruments on the other hand. On the positive side, and contrary to the rest of the ICT sector, these two sub-sectors also show strong R&D growth in the EU. Company data indicates that EU companies have R&D intensities similar to their US counterparts in every sub-sector, but are concentrated in less R&D intensive sub-sectors (e.g. telecom services). The US companies are also larger and more numerous in most sub-sectors. These data suggest that the ICT R&D gap between the US and the EU reflects, more than anything, a lack of European firms in the ICT sector. Among the member states, Finland and Sweden make the highest R&D effort in this sector, relative to their size. In general, Northern member states invest more than Southern member states, and the Western member states invest much more than the Eastern ones, which display very low levels of ICT R&D.JRC.J.4-Information Societ

    Estimation of Convective Extreme Events over Germany based on Large Scale Parameters

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    Strong convective events can produce extreme precipitation, hail, lightning or gusts, potentially inducing severe socio-economic impacts. These events have a relatively small spatial extension and, in most cases, a short lifetime. In this study, a model is developed for estimating convective extreme events based on large scale conditions. It is shown that strong convective events can be characterized by a Weibull distribution of radar-based rainfall with a low shape and high scale parameter value. A radius of 90km around a station reporting a convective situation turned out to be suitable. A methodology is developed to estimate the Weibull parameters and thus the occurrence probability of convective events from large scale atmospheric instability and enhanced near-surface humidity, which are usually found on a larger scale than the convective event itself. Here, the probability for the occurrence of extreme convective events is estimated from the KO-index indicating the stability, and relative humidity at 1000hPa. Both variables are computed from ERA-Interim reanalysis. In a first version of the methodology, these two variables are applied to estimate the spatial rainfall distribution and to estimate the occurrence of a convective event. The developed method shows significant skill in estimating the occurrence of convective events as observed at synoptic stations, lightning measurements, and severe weather reports. In order to take frontal influences into account, a scheme for the detection of atmospheric fronts is implemented. While generally higher instability is found in the vicinity of fronts, the skill of this approach is largely unchanged. Additional improvements were achieved by a bias-correction and the use of ERA-Interim precipitation. The resulting estimation method is applied to the ERA-Interim period (1979-2014) to establish a ranking of estimated convective extreme events. Two strong estimated events that reveal a frontal influence are analysed in detail. As a second application, the method is applied to GCM-based decadal predictions in the period 1979-2014, which were initialized every year. It is shown that decadal predictive skill for convective event frequencies over Germany is found for the first 3-4 years after the initialization

    Evaluation of moisture sources for the Central European summer flood of May/June 2013 based on regional climate model simulations

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    Heavy precipitation affected Central Europe in May/June 2013, triggering damaging floods both on the Danube and the Elbe rivers. Based on a modelling approach with COSMO-CLM, moisture fluxes, backward trajectories, cyclone tracks and precipitation fields are evaluated for the relevant time period 30 May–2 June 2013. We identify potential moisture sources and quantify their contribution to the flood event focusing on the Danube basin through sensitivity experiments: Control simulations are performed with undisturbed ERA-Interim boundary conditions, while multiple sensitivity experiments are driven with modified evaporation characteristics over selected marine and land areas. Two relevant cyclones are identified both in reanalysis and in our simulations, which moved counter-clockwise in a retrograde path from Southeastern Europe over Eastern Europe towards the northern slopes of the Alps. The control simulations represent the synoptic evolution of the event reasonably well. The evolution of the precipitation event in the control simulations shows some differences in terms of its spatial and temporal characteristics compared to observations. The main precipitation event can be separated into two phases concerning the moisture sources. Our modelling results provide evidence that the two main sources contributing to the event were the continental evapotranspiration (moisture recycling; both phases) and the North Atlantic Ocean (first phase only). The Mediterranean Sea played only a minor role as a moisture source. This study confirms the importance of continental moisture recycling for heavy precipitation events over Central Europe during the summer half year

    Objective climatology of cyclones in the Mediterranean region: a consensus view among methods with different system identification and tracking criteria

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    The Mediterranean storm track constitutes a well-defined branch of the North Hemisphere storm track and is characterised by small but intense features and frequent cyclogenesis. The goal of this study is to assess the level of consensus among cyclone detection and tracking methods (CDTMs), to identify robust features and to explore sources of disagreement. A set of 14 CDTMs has been applied for computing the climatology of cyclones crossing the Mediterranean region using the ERA-Interim dataset for the period 1979–2008 as common testbed. Results show large differences in actual cyclone numbers identified by different methods, but a good level of consensus on the interpretation of results regarding location, annual cycle and trends of cyclone tracks. Cyclogenesis areas such as the north-western Mediterranean, North Africa, north shore of the Levantine basin, as well as the seasonality of their maxima are robust features on which methods show a substantial agreement. Differences among methods are greatly reduced if cyclone numbers are transformed to a dimensionless index, which, in spite of disagreement on mean values and interannual variances of cyclone numbers, reveals a consensus on variability, sign and significance of trends. Further, excluding ‘weak’ and ‘slow’ cyclones from the computation of cyclone statistics improves the agreement among CDTMs. Results show significant negative trends of cyclone frequency in spring and positive trends in summer, whose contrasting effects compensate each other at annual scale, so that there is no significant long-term trend in total cyclone numbers in the Mediterranean basin in the 1979–2008 period

    Robustness of serial clustering of extratropical cyclones to the choice of tracking method

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    Cyclone clusters are a frequent synoptic feature in the Euro-Atlantic area. Recent studies have 24 shown that serial clustering of cyclones generally occurs on both flanks and downstream 25 regions of the North Atlantic storm track, while cyclones tend to occur more regulary on the 26 eastern side of the North Atlantic basin near Newfoundland. This study explores the 27 sensitivity of serial clustering to the choice of cyclone tracking method using cyclone track 28 data from 15 methods derived from ERA-Interim data (1979-2010). Clustering is estimated by 29 the dispersion (ratio of variance to mean) of winter (DJF) cyclones passages near each grid 30 point over the Euro-Atlantic area. The mean number of cyclone counts and their variance are 31 compared between methods, revealing considerable differences, particularly for the latter. 32 Results show that all different tracking methods qualitatively capture similar large-scale 33 spatial patterns of underdispersion / overdispersion over the study region. The quantitative 34 differences can primarily be attributed to the differences in the variance of cyclone counts 35 between the methods. Nevertheless, overdispersion is statistically significant for almost all 36 methods over parts of the Eastern North Atlantic and Western Europe, and is therefore 37 considered as a robust feature. The influence of the North Atlantic Oscillation on cyclone 38 clustering displays a similar pattern for all tracking methods, with one maximum near Iceland 39 and another between the Azores and Iberia. The differences in variance between methods are 40 not related with different sensitivities to the NAO, which can account to over 50% of the 41 clustering in some regions. We conclude that the general features of underdispersion / 42 overdispersion of extra-tropical cyclones over the North Atlantic and Western Europe is 43 robust to the choice of tracking method. The same is true for the influence of the North 44 Atlantic Oscillation on cyclone dispersion

    The Socio-economic Impact of Social Computing: Proceedings of a Validation and Policy Options Workshop

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    This report presents the major outcomes of a validation and policy options workshop on social computing, held at IPTS in Seville, on 26-27 February 2008. It points to a number of relevant issues (including methodological and conceptual ones) that need to be taken into account in a study of the socio-economic impacts of social computing. It argues that there is little room for direct policy interventions in social computing but that framework conditions and impacts at sector-level (e.g. education, government) need to be considered. The report also discusses the future of social computing and the opportunities it offers Europe.JRC.J.4-Information Societ

    Are greenhouse gas signals of Northern Hemisphere winter extra-tropical cyclone activity dependent on the identification and tracking algorithm?

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    For Northern Hemisphere extra-tropical cyclone activity, the dependency of a potential anthropogenic climate change signal on the identification method applied is analysed. This study investigates the impact of the used algorithm on the changing signal, not the robustness of the climate change signal itself. Using one single transient AOGCM simulation as standard input for eleven state-of-the-art identification methods, the patterns of model simulated present day climatologies are found to be close to those computed from re-analysis, independent of the method applied. Although differences in the total number of cyclones identified exist, the climate change signals (IPCC SRES A1B) in the model run considered are largely similar between methods for all cyclones. Taking into account all tracks, decreasing numbers are found in the Mediterranean, the Arctic in the Barents and Greenland Seas, the mid-latitude Pacific and North America. Changing patterns are even more similar, if only the most severe systems are considered: the methods reveal a coherent statistically significant increase in frequency over the eastern North Atlantic and North Pacific. We found that the differences between the methods considered are largely due to the different role of weaker systems in the specific methods

    IMILAST: a community effort to intercompare extratropical cyclone detection and tracking algorithms

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    The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases

    Air pumping for alleviation of heavy smog in Beijing

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    Beijing often suffers under heavy smog. During such events which occur mostly in autumn and winter, people are desperate for fresh air. The formation of heavy smog is due to foremost human induced air pollution, but geographic and meteorological conditions, especially below a surface inversion, play an important role. We propose to destroy the inversion by pumping air from above the inversion layer to the surface layer to alleviate the severity of the smog. While long-term air quality improvement depends on the reduction of air pollution emission, air pumping may provide relief in the interim for the Beijing citizens. We estimate that an air pumping at a rate 2x10(7) m(3) s(-1) can lead to significantly improved air quality in Beijing, due to (1) direct clean air input; (2) increased instability and vertical mixing and (3) a positive radiation-mixing feedback. The pumping requires an energy input of 10 GW, comparable with the energy consumption in Beijing for air conditioning in summer. We propose to use wind energy from Inner Mongolia for the pumping, which has currently an installed wind energy capacity of 70 GW

    Mapping R&D Investment by the European ICT Business Sector

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    The paper shows that the ICT sector alone is responsible for about half the R&D investment gap between the EU and the US, i.e. the fact that EU invests a much smaller share of its GDP in R&D. It argues that this is partly because the ICT sector is a smaller part of the economy in the EU than it is in the US. More important, however, is the lower R&D intensity (business R&D / value added) of the ICT sector in the EU. This is mainly due to lower R&D intensity in two sub-sectors: Computer Services and Software, and Electronic Measurement Instruments. Current data analysis gives no indication that the ICT R&D gap is closing. The analysis further finds that among EU member states, Northern member states show higher ICT R&D intensity than Southern member states, and the Western member states a much higher intensity than the Eastern member states. The bulk of the paper then takes a closer look at each of the ICT sub-sectors, mapping out the R&D effort in each of them.JRC.J.4-Information Societ
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