Faust

De cada obra s'ha digitalitzat un programa sencer. De la resta s'han digitalitzat les parts que són diferents.Direcció de Paul Ethuin ; direcció d'escena Diego MonjoEmpresa: Juan A. Pamia

The VALUE perfect predictor experiment: evaluation of temporal variability

Temporal variability is an important feature of climate, comprising systematic vari-ations such as the annual cycle, as well as residual temporal variations such asshort-term variations, spells and variability from interannual to long-term trends.The EU-COST Action VALUE developed a comprehensive framework to evaluatedownscaling methods. Here we present the evaluation of the perfect predictorexperiment for temporal variability. Overall, the behaviour of the differentapproaches turned out to be as expected from their structure and implementation.The chosen regional climate model adds value to reanalysis data for most consid-ered aspects, for all seasons and for both temperature and precipitation. Bias cor-rection methods do not directly modify temporal variability apart from the annualcycle. However, wet day corrections substantially improve transition probabilitiesand spell length distributions, whereas interannual variability is in some cases dete-riorated by quantile mapping. The performance of perfect prognosis (PP) statisticaldownscaling methods varies strongly from aspect to aspect and method to method,and depends strongly on the predictor choice. Unconditional weather generatorstend to perform well for the aspects they have been calibrated for, but underrepre-sent long spells and interannual variability. Long-term temperature trends of thedriving model are essentially unchanged by bias correction methods. If precipita-tion trends are not well simulated by the driving model, bias correction furtherdeteriorates these trends. The performance of PP methods to simulate trendsdepends strongly on the chosen predictors.VALUE has been funded as EU COST Action ES1102

Analysis of pulse propagation in a bottom limited sound channel with a surface duct

An acoustic data set, that was collected in a bottom limited sound channel with a surface duct, has been modeled using broadband ray , normal mode , fast-field, and parabolic approximation techniques. Surface ducted propagation was compared to propagation when no surface duct is present. The surface duct was found to generate a series of modes each in a distinctive state. This series of modal states was shown to represent a resonance between the highly dispersive (SRBR) and less dispersive (RBR) propagation regimes. At a range of 42 kilometers 6 surface ducted arrivals are evident in the data set and are predicted by all models except ray theory. The six arrivals are found to be made up of energy from three different paths and propagation types. Faster precursors are purely diffracted energy, while slower precursors have RBR and SRBR contributions. Ray theory successfully predicts the RBR and SRBR contributions, but not the diffracted energy. Videos of the evolution of the broadband signal show that the precursors are generated at discrete ranges where RBR and SRBR phase fronts interact near the surface. Energy leaking from these precursors is proposed to leak into slower modal states such that the exchange of energy in and out of the duct is accomplished in a range independent environment without mode coupling or energy transfer between modes. Oceanic variability in the Florida straits is proposed to vary precursor amplitude not by changing the retention strength of the duct, but by changing the character of the leakage mechanism to the channel below