66 resultados para Slow potentials


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During the past decade, brain–computer interfaces (BCIs) have rapidly developed, both in technological and application domains. However, most of these interfaces rely on the visual modality. Only some research groups have been studying non-visual BCIs, primarily based on auditory and, sometimes, on somatosensory signals. These non-visual BCI approaches are especially useful for severely disabled patients with poor vision. From a broader perspective, multisensory BCIs may offer more versatile and user-friendly paradigms for control and feedback. This chapter describes current systems that are used within auditory and somatosensory BCI research. Four categories of noninvasive BCI paradigms are employed: (1) P300 evoked potentials, (2) steady-state evoked potentials, (3) slow cortical potentials, and (4) mental tasks. Comparing visual and non-visual BCIs, we propose and discuss different possible multisensory combinations, as well as their pros and cons. We conclude by discussing potential future research directions of multisensory BCIs and related research questions

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A statistical-dynamical downscaling method is used to estimate future changes of wind energy output (Eout) of a benchmark wind turbine across Europe at the regional scale. With this aim, 22 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble are considered. The downscaling method uses circulation weather types and regional climate modelling with the COSMO-CLM model. Future projections are computed for two time periods (2021–2060 and 2061–2100) following two scenarios (RCP4.5 and RCP8.5). The CMIP5 ensemble mean response reveals a more likely than not increase of mean annual Eout over Northern and Central Europe and a likely decrease over Southern Europe. There is some uncertainty with respect to the magnitude and the sign of the changes. Higher robustness in future changes is observed for specific seasons. Except from the Mediterranean area, an ensemble mean increase of Eout is simulated for winter and a decreasing for the summer season, resulting in a strong increase of the intra-annual variability for most of Europe. The latter is, in particular, probable during the second half of the 21st century under the RCP8.5 scenario. In general, signals are stronger for 2061–2100 compared to 2021–2060 and for RCP8.5 compared to RCP4.5. Regarding changes of the inter-annual variability of Eout for Central Europe, the future projections strongly vary between individual models and also between future periods and scenarios within single models. This study showed for an ensemble of 22 CMIP5 models that changes in the wind energy potentials over Europe may take place in future decades. However, due to the uncertainties detected in this research, further investigations with multi-model ensembles are needed to provide a better quantification and understanding of the future changes.

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Decadal predictions on timescales from one year to one decade are gaining importance since this time frame falls within the planning horizon of politics, economy and society. The present study examines the decadal predictability of regional wind speed and wind energy potentials in three generations of the MiKlip (‘Mittelfristige Klimaprognosen’) decadal prediction system. The system is based on the global Max-Planck-Institute Earth System Model (MPI-ESM), and the three generations differ primarily in the ocean initialisation. Ensembles of uninitialised historical and yearly initialised hindcast experiments are used to assess the forecast skill for 10 m wind speeds and wind energy output (Eout) over Central Europe with lead times from one year to one decade. With this aim, a statistical-dynamical downscaling (SDD) approach is used for the regionalisation. Its added value is evaluated by comparison of skill scores for MPI-ESM large-scale wind speeds and SDD-simulated regional wind speeds. All three MPI-ESM ensemble generations show some forecast skill for annual mean wind speed and Eout over Central Europe on yearly and multi-yearly time scales. This forecast skill is mostly limited to the first years after initialisation. Differences between the three ensemble generations are generally small. The regionalisation preserves and sometimes increases the forecast skills of the global runs but results depend on lead time and ensemble generation. Moreover, regionalisation often improves the ensemble spread. Seasonal Eout skills are generally lower than for annual means. Skill scores are lowest during summer and persist longest in autumn. A large-scale westerly weather type with strong pressure gradients over Central Europe is identified as potential source of the skill for wind energy potentials, showing a similar forecast skill and a high correlation with Eout anomalies. These results are promising towards the establishment of a decadal prediction system for wind energy applications over Central Europe.

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Precipitation is expected to respond differently to various drivers of anthropogenic climate change. We present the first results from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where nine global climate models have perturbed CO2, CH4, black carbon, sulfate, and solar insolation. We divide the resulting changes to global mean and regional precipitation into fast responses that scale with changes in atmospheric absorption and slow responses scaling with surface temperature change. While the overall features are broadly similar between models, we find significant regional intermodel variability, especially over land. Black carbon stands out as a component that may cause significant model diversity in predicted precipitation change. Processes linked to atmospheric absorption are less consistently modeled than those linked to top-of-atmosphere radiative forcing. We identify a number of land regions where the model ensemble consistently predicts that fast precipitation responses to climate perturbations dominate over the slow, temperature-driven responses.

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We investigate how sea surface temperatures (SSTs) around Antarctica respond to the Southern An- nular Mode (SAM) on multiple timescales. To that end we examine the relationship between SAM and SST within unperturbed preindustrial control simulations of coupled general circulation models (GCMs) included in the Climate Modeling Intercomparison Project phase 5 (CMIP5). We develop a technique to extract the re- sponse of the Southern Ocean SST (55◦S−70◦S) to a hypothetical step increase in the SAM index. We demonstrate that in many GCMs, the expected SST step re- sponse function is nonmonotonic in time. Following a shift to a positive SAM anomaly, an initial cooling regime can transition into surface warming around Antarctica. However, there are large differences across the CMIP5 ensemble. In some models the step response function never changes sign and cooling persists, while in other GCMs the SST anomaly crosses over from negative to positive values only three years after a step increase in the SAM. This intermodel diversity can be related to differences in the models’ climatological thermal ocean stratification in the region of seasonal sea ice around Antarctica. Exploiting this relationship, we use obser- vational data for the time-mean meridional and vertical temperature gradients to constrain the real Southern Ocean response to SAM on fast and slow timescales.

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Parties to the United Nations Framework Convention on Climate Change (UNFCCC) have requested guidance on common greenhouse gas metrics in accounting for Nationally determined contributions (NDCs) to emission reductions1. Metric choice can affect the relative emphasis placed on reductions of ‘cumulative climate pollutants’ such as carbon dioxide versus ‘short-lived climate pollutants’ (SLCPs), including methane and black carbon2, 3, 4, 5, 6. Here we show that the widely used 100-year global warming potential (GWP100) effectively measures the relative impact of both cumulative pollutants and SLCPs on realized warming 20–40 years after the time of emission. If the overall goal of climate policy is to limit peak warming, GWP100 therefore overstates the importance of current SLCP emissions unless stringent and immediate reductions of all climate pollutants result in temperatures nearing their peak soon after mid-century7, 8, 9, 10, which may be necessary to limit warming to “well below 2 °C” (ref. 1). The GWP100 can be used to approximately equate a one-off pulse emission of a cumulative pollutant and an indefinitely sustained change in the rate of emission of an SLCP11, 12, 13. The climate implications of traditional CO2-equivalent targets are ambiguous unless contributions from cumulative pollutants and SLCPs are specified separately.