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Search Results: 1 - 10 of 397453 matches for " J. -F. Paquet "
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Introducing a rainfall compound distribution model based on weather patterns sub-sampling
F. Garavaglia,J. Gailhard,E. Paquet,M. Lang
Hydrology and Earth System Sciences Discussions , 2010,
Abstract: This paper presents a new probabilistic model for daily rainfall, using sub-sampling based on meteorological circulation. We classified eight typical but contrasted synoptic situations (weather patterns) for France and surrounding areas, using a "bottom-up" approach, i.e. from the shape of the rain field to the synoptic situations described by geopotential fields. These weather patterns (WP) provide a discriminating variable that is consistent with French climatology, and allows seasonal rainfall records to be split into more homogeneous sub-samples. An exponential POT model is used to fit the distribution of each sub-sample. The distribution of the multi-exponential weather patterns (MEWP) is then defined as the composition, for a given season, of all WP sub-sample marginal distributions, weighted by the relative frequency of occurrence of each WP. The MEWP distribution appears able to fit various shapes of distributions using a simple and robust approach for asymptotic behaviour. It is a new contribution to the ongoing debate on the probabilistic tools used to study the asymptotic behaviour of extreme rainfall from observed records. The paper is illustrated throughout with the example of the Lyon (France) rainfall record for the period 1953–2005.
Reliability and robustness of rainfall compound distribution model based on weather pattern sub-sampling
F. Garavaglia,M. Lang,E. Paquet,J. Gailhard
Hydrology and Earth System Sciences Discussions , 2010, DOI: 10.5194/hessd-7-6757-2010
Abstract: Design floods for EDF (électricité de France, French electricity company) dam spillways are now computed using a probabilistic method named SCHADEX (Climatic-Hydrological Simulation of Extreme Floods) based on an extreme rainfall model named the MEWP (Multi Exponential Weather Pattern) distribution. This probabilistic model provides estimates of extreme rainfall quantiles using a mixture of exponential distributions. Each exponential distribution applies to a specific sub-sample of rainfall observations, corresponding to one of eight typical atmospheric circulation patterns that are relevant for France and the surrounding area. The aim of this paper is to validate the MEWP model by assessing its reliability and robustness with rainfall data from France, Spain and Switzerland. Data include 37 long series for the period 1904–2003, and a regional data set of 478 rain gauges for the period 1954–2005. Two complementary properties are investigated: (i) the reliability of estimates, i.e. the agreement between the estimated probabilities of exceedance and the actual exceedances observed on the dataset; (ii) the robustness of extreme quantiles and associated confidence intervals, assessed using various sub-samples of the long data series. New specific criteria are proposed to quantify reliability and robustness.The MEWP model is compared to standard models (seasonalised Generalised Extreme Value and Generalised Pareto distributions). In order to evaluate the suitability of the exponential model used for each weather pattern (WP), a general case of the MEWP distribution, using Generalized Pareto distributions for each WP, is also considered. Concerning the considered dataset, the exponential hypothesis of asymptotic behaviour of each seasonal and weather pattern rainfall records, appears to be reasonable. The results highlight: (i) the interest of WP sub-sampling that lead to significant improvement in reliability models performances; (ii) the low level of robustness of the models based on at-site estimation of shape parameter; (iii) the MEWP distribution proved to be robust and reliable, demonstrating the interest of the proposed approach.
Introducing a rainfall compound distribution model based on weather patterns sub-sampling
F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Gar on,P. Bernardara
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2010,
Abstract: This paper presents a probabilistic model for daily rainfall, using sub-sampling based on meteorological circulation. We classified eight typical but contrasted synoptic situations (weather patterns) for France and surrounding areas, using a "bottom-up" approach, i.e. from the shape of the rain field to the synoptic situations described by geopotential fields. These weather patterns (WP) provide a discriminating variable that is consistent with French climatology, and allows seasonal rainfall records to be split into more homogeneous sub-samples, in term of meteorological genesis. First results show how the combination of seasonal and WP sub-sampling strongly influences the identification of the asymptotic behaviour of rainfall probabilistic models. Furthermore, with this level of stratification, an asymptotic exponential behaviour of each sub-sample appears as a reasonable hypothesis. This first part is illustrated with two daily rainfall records from SE of France. The distribution of the multi-exponential weather patterns (MEWP) is then defined as the composition, for a given season, of all WP sub-sample marginal distributions, weighted by the relative frequency of occurrence of each WP. This model is finally compared to Exponential and Generalized Pareto distributions, showing good features in terms of robustness and accuracy. These final statistical results are computed from a wide dataset of 478 rainfall chronicles spread on the southern half of France. All these data cover the 1953–2005 period.
Statistical analysis of error propagation from radar rainfall to hydrological models
P. Brigode, Z. Mi ovi , P. Bernardara, E. Paquet, F. Garavaglia, J. Gailhard,P. Ribstein
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2013, DOI: 10.5194/hess-17-1455-2013
Abstract: Classifications of atmospheric weather patterns (WPs) are widely used for the description of the climate of a given region and are employed for many applications, such as weather forecasting, downscaling of global circulation model outputs and reconstruction of past climates. WP classifications were recently used to improve the statistical characterisation of heavy rainfall. In this context, bottom-up approaches, combining spatial distribution of heavy rainfall observations and geopotential height fields have been used to define WP classifications relevant for heavy rainfall statistical analysis. The definition of WPs at the synoptic scale creates an interesting variable which could be used as a link between the global scale of climate signals and the local scale of precipitation station measurements. We introduce here a new WP classification centred on the British Columbia (BC) coastal region (Canada) and based on a bottom-up approach. Five contrasted WPs composed this classification, four rainy WPs and one non-rainy WP, the anticyclonic pattern. The four rainy WPs are mainly observed in the winter months (October to March), which is the period of heavy precipitation events in coastal BC and is thus consistent with the local climatology. The combination of this WP classification with the seasonal description of rainfall is shown to be useful for splitting observed precipitation series into more homogeneous sub-samples (i.e. sub-samples constituted by days having similar atmospheric circulation patterns) and thus identifying, for each station, the synoptic situations that generate the highest hazard in terms of heavy rainfall events. El Ni o-Southern Oscillations (ENSO) significantly influence the frequency of occurrence of two coastal BC WPs. Within each WP, ENSO seem to influence only the frequency of rainy events and not the magnitudes of heavy rainfall events. Consequently, heavy rainfall estimations do not show significant evolution of heavy rainfall behaviour between Ni o and Ni a winters. However, the WP approach captures the variability of the probability of occurrences of synoptic situations generating heavy rainfall depending on ENSO and opening interesting perspectives for the analysis of heavy rainfall distribution in a non-stationary context.
Reliability and robustness of rainfall compound distribution model based on weather pattern sub-sampling
F. Garavaglia, M. Lang, E. Paquet, J. Gailhard, R. Gar on,B. Renard
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2011,
Abstract: A new probabilistic model for daily rainfall, named MEWP (Multi Exponential Weather Pattern) distribution, has been introduced in Garavaglia et al. (2010). This model provides estimates of extreme rainfall quantiles using a mixture of exponential distributions. Each exponential distribution applies to a specific sub-sample of rainfall observations, corresponding to one of eight typical atmospheric circulation patterns that are relevant for France and the surrounding area. The aim of this paper is to validate the MEWP model by assessing its reliability and robustness with rainfall data from France, Spain and Switzerland. Data include 37 long series for the period 1904–2003, and a regional data set of 478 rain gauges for the period 1954–2005. Two complementary properties are investigated: (i) the reliability of estimates, i.e. the agreement between the estimated probabilities of exceedance and the actual exceedances observed on the dataset; (ii) the robustness of extreme quantiles and associated confidence intervals, assessed using various sub-samples of the long data series. New specific criteria are proposed to quantify reliability and robustness. The MEWP model is compared to standard models (seasonalised Generalised Extreme Value and Generalised Pareto distributions). In order to evaluate the suitability of the exponential model used for each weather pattern (WP), a general case of the MEWP distribution, using Generalized Pareto distributions for each WP, is also considered. Concerning the considered dataset, the exponential hypothesis of asymptotic behaviour of each seasonal and weather pattern rainfall records, appears to be reasonable. The results highlight : (i) the interest of WP sub-sampling that lead to significant improvement in reliability models performances; (ii) the low level of robustness of the models based on at-site estimation of shape parameter; (iii) the MEWP distribution proved to be robust and reliable, demonstrating the interest of the proposed approach.
Thermal photon radiation in high multiplicity p+Pb collisions at the Large Hadron Collider
C. Shen,J. -F. Paquet,G. S. Denicol,S. Jeon,C. Gale
Physics , 2015,
Abstract: The collective behaviour of hadronic particles has been observed in high multiplicity proton-lead collisions at the Large Hadron Collider (LHC), as well as in deuteron-gold collisions at the Relativistic Heavy-Ion Collider (RHIC). In this work we present the first calculation, in the hydrodynamic framework, of thermal photon radiation from such small collision systems. Owing to their compact size, these systems can reach temperatures comparable to those in central nucleus-nucleus collisions. The thermal photons can thus shine over the prompt background, and increase the low $p_T$ direct photon spectrum by a factor of 2-3 in 0-1% p+Pb collisions at 5.02 TeV. This thermal photon enhancement can therefore serve as a clean signature of the existence of a hot quark-gluon plasma during the evolution of these small collision systems, as well as validate hydrodynamic behavior in small systems.
The importance of the bulk viscosity of QCD in ultrarelativistic heavy-ion collisions
S. Ryu,J. -F. Paquet,C. Shen,G. S. Denicol,B. Schenke,S. Jeon,C. Gale
Physics , 2015, DOI: 10.1103/PhysRevLett.115.132301
Abstract: We investigate the consequences of a nonzero bulk viscosity coefficient on the transverse momentum spectra, azimuthal momentum anisotropy, and multiplicity of charged hadrons produced in heavy ion collisions at LHC energies. The agreement between a realistic 3D hybrid simulation and the experimentally measured data considerably improves with the addition of a bulk viscosity coefficient for strongly interacting matter. This paves the way for an eventual quantitative determination of several QCD transport coefficients from the experimental heavy ion and hadron-nucleus collision programs.
Effect of initial-state nucleon-nucleon correlations on collective flow in ultra-central heavy-ion collisions
G. S. Denicol,C. Gale,S. Jeon,J. -F. Paquet,B. Schenke
Physics , 2014,
Abstract: We investigate the effect of nucleon-nucleon correlations on the initial condition of ultra-central heavy ion collisions at LHC energies. We calculate the eccentricities of the MC-Glauber and IP-Glasma models in the 0--1% centrality class and show that they are considerably affected by the inclusion of such type of correlations. For an IP-Glasma initial condition, we further demonstrate that this effect survives the fluid-dynamical evolution of the system and can be observed in its final state azimuthal momentum anisotropy.
Extracting the bulk viscosity of the quark-gluon plasma
J. -B. Rose,J. -F. Paquet,G. S. Denicol,M. Luzum,B. Schenke,S. Jeon,C. Gale
Physics , 2014, DOI: 10.1016/j.nuclphysa.2014.09.044
Abstract: We investigate the implications of a nonzero bulk viscosity coefficient on the azimuthal momentum anisotropy of ultracentral relativistic heavy ion collisions at the Large Hadron Collider. We find that, with IP-Glasma initial conditions, a finite bulk viscosity coefficient leads to a better description of the flow harmonics in ultracentral collisions. We then extract optimal values of bulk and shear viscosity coefficients that provide the best agreement with flow harmonic coefficients data in this centrality class.
Parkin Is Protective against Proteotoxic Stress in a Transgenic Zebrafish Model
Mareike E. Fett,Anna Pilsl,Dominik Paquet,Frauke van Bebber,Christian Haass,J?rg Tatzelt,Bettina Schmid,Konstanze F. Winklhofer
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0011783
Abstract: Mutations in the gene encoding the E3 ubiquitin ligase parkin (PARK2) are responsible for the majority of autosomal recessive parkinsonism. Similarly to other knockout mouse models of PD-associated genes, parkin knockout mice do not show a substantial neuropathological or behavioral phenotype, while loss of parkin in Drosophila melanogaster leads to a severe phenotype, including reduced lifespan, apoptotic flight muscle degeneration and male sterility. In order to study the function of parkin in more detail and to address possible differences in its role in different species, we chose Danio rerio as a different vertebrate model system.
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