Modeling pairwise dependencies in precipitation intensities

International audienceIn statistics, extreme events are classically defined as maxima over a block length (e.g. annual maxima of daily precipitation) or as exceedances above a given large threshold. These definitions allow the hydrologist and the flood planner to apply the univariate Extreme Value Theory (EVT) to their time series of interest. But these strategies have two main drawbacks. Firstly, working with maxima or exceedances implies that a lot of observations (those below the chosen threshold or the maximum) are completely disregarded. Secondly, this univariate modeling does not take into account the spatial dependence. Nearby weather stations are considered independent, although their recordings can show otherwise. To start addressing these two issues, we propose a new statistical bivariate model that takes advantages of the recent advances in multivariate EVT. Our model can be viewed as an extension of the non-homogeneous univariate mixture. The two strong points of this latter model are its capacity at modeling the entire range of precipitation (and not only the largest values) and the absence of an arbitrarily fixed large threshold to define exceedances. Here, we adapt this mixture and broaden it to the joint modeling of bivariate precipitation recordings. The performance and flexibility of this new model are illustrated on simulated and real precipitation data

Non-linear statistical downscaling of present and LGM precipitation and temperatures over Europe

International audienceLocal-scale climate information is increasingly needed for the study of past, present and future climate changes. In this study we develop a non-linear statistical downscaling method to generate local temperatures and precipitation values from large-scale variables of a Earth System Model of Intermediate Complexity (here CLIMBER). Our statistical downscaling scheme is based on the concept of Generalized Additive Models (GAMs), capturing non-linearities via non-parametric techniques. Our GAMs are calibrated on the present Western Europe climate. For this region, annual GAMs (i.e. models based on 12 monthly values per location) are fitted by combining two types of large-scale explanatory variables: geographical (e.g. topographical information) and physical (i.e. entirely simulated by the CLIMBER model). To evaluate the adequacy of the non-linear transfer functions fitted on the present Western European climate, they are applied to different spatial and temporal large-scale conditions. Local projections for present North America and Northern Europe climates are obtained and compared to local observations. This partially addresses the issue of spatial robustness of our transfer functions by answering the question "does our statistical model remain valid when applied to large-scale climate conditions from a region different from the one used for calibration?". To asses their temporal performances, local projections for the Last Glacial Maximum period are derived and compared to local reconstructions and General Circulation Model outputs. Our downscaling methodology performs adequately for the Western Europe climate. Concerning the spatial and temporal evaluations, it does not behave as well for Northern America and Northern Europe climates because the calibration domain may be too different from the targeted regions. The physical explanatory variables alone are not capable of downscaling realistic values. However, the inclusion of geographical-type variables – such as altitude, advective continentality and moutains effect on wind (W–slope) – as GAM explanatory variables clearly improves our local projections

Nonstationary probabilistic downscaling of extreme precipitation

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Orientation économique d'un programme d'amélioration génétique des porcs

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Multivariate stochastic bias corrections with optimal transport

Bias correction methods are used to calibrate climate model outputs with respect to observational records. The goal is to ensure that statistical features (such as means and variances) of climate simulations are coherent with observations. In this article, a multivariate stochastic bias correction method is developed based on optimal transport. Bias correction methods are usually defined as transfer functions between random variables. We show that such transfer functions induce a joint probability distribution between the biased random variable and its correction. The optimal transport theory allows us to construct a joint distribution that minimizes an energy spent in bias correction. This extends the classical univariate quantile mapping techniques in the multivariate case. We also propose a definition of non-stationary bias correction as a transfer of the model to the observational world, and we extend our method in this context. Those methodologies are first tested on an idealized chaotic system with three variables. In those controlled experiments, the correlations between variables appear almost perfectly corrected by our method, as opposed to a univariate correction. Our methodology is also tested on daily precipitation and temperatures over 12 locations in southern France. The correction of the inter-variable and inter-site structures of temperatures and precipitation appears in agreement with the multi-dimensional evolution of the model, hence satisfying our suggested definition of non-stationarity.</p

Projections of global changes in precipitation extremes from CMIP5 models

Precipitation extremes are expected to increase in a warming climate, thus it is essential to characterise their potential future changes. Here we evalu- ate eight high-resolution Global Climate Model simulations in the twenti- eth century and provide new evidence on projected global precipitation ex- tremes for the 21st century. A significant intensification of daily extremes for all seasons is projected for the mid and high latitudes of both hemispheres at the end of the present century. For the subtropics and tropics, the lack of reliable and consistent estimations found for both the historical and fu- ture simulations might be connected with model deficiencies in the repre- sentation of organised convective systems. Low inter-model variability and good agreement with high-resolution regional observations are found for the twentieth century winter over the Northern Hemisphere mid and high lat- itudes

Socioeconomic deprivation, urban-rural location and alcohol-related mortality in England and Wales

Background: Many causes of death are directly attributable to the toxic effects of alcohol and deaths from these causes are increasing in the United Kingdom. The aim of this study was to investigate variation in alcohol-related mortality in relation to socioeconomic deprivation, urban-rural location and age within a national context. Methods: An ecological study design was used with data from 8797 standard table wards in England and Wales. The methodology included using the Carstairs Index as a measure of socioeconomic deprivation at the small-area level and the national harmonised classification system for urban and rural areas in England and Wales. Alcohol-related mortality was defined using the National Statistics definition, devised for tracking national trends in alcohol-related deaths. Deaths from liver cirrhosis accounted for 85% of all deaths included in this definition. Deaths from 1999-2003 were examined and 2001 census ward population estimates were used as the denominators. Results: The analysis was based on 28,839 deaths. Alcohol-related mortality rates were higher in men and increased with increasing age, generally reaching peak levels in middle-aged adults. The 45-64 year age group contained a quarter of the total population but accounted for half of all alcohol-related deaths. There was a clear association between alcohol-related mortality and socioeconomic deprivation, with progressively higher rates in more deprived areas. The strength of the association varied with age. Greatest relative inequalities were seen amongst people aged 25-44 years, with relative risks of 4.73 (95% CI 4.00 to 5.59) and 4.24 (95% CI 3.50 to 5.13) for men and women respectively in the most relative to the least deprived quintiles. People living in urban areas experienced higher alcohol-related mortality relative to those living in rural areas, with differences remaining after adjustment for socioeconomic deprivation. Adjusted relative risks for urban relative to rural areas were 1.35 (95% CI 1.20 to 1.52) and 1.13 (95% CI 1.01 to 1.25) for men and women respectively. Conclusions: Large inequalities in alcohol-related mortality exist between sub-groups of the population in England and Wales. These should be considered when designing public health policies to reduce alcohol-related harm

DADA: data assimilation for the detection and attribution of weather and climate-related events

A new nudging method for data assimilation, delay‐coordinate nudging, is presented. Delay‐coordinate nudging makes explicit use of present and past observations in the formulation of the forcing driving the model evolution at each time step. Numerical experiments with a low‐order chaotic system show that the new method systematically outperforms standard nudging in different model and observational scenarios, also when using an unoptimized formulation of the delay‐nudging coefficients. A connection between the optimal delay and the dominant Lyapunov exponent of the dynamics is found based on heuristic arguments and is confirmed by the numerical results, providing a guideline for the practical implementation of the algorithm. Delay‐coordinate nudging preserves the easiness of implementation, the intuitive functioning and the reduced computational cost of the standard nudging, making it a potential alternative especially in the field of seasonal‐to‐decadal predictions with large Earth system models that limit the use of more sophisticated data assimilation procedures

Phlegmonous colitis: another source of sepsis in cirrhotic patients?

<p>Abstract</p> <p>Background</p> <p>The clinical relevance of phlegmonous colitis (PC), a rare autopsy finding in cirrhotic patients, is poorly documented. We postulated that PC might be a source of sepsis in patients with portal hypertensive colopathy (PHC).</p> <p>Case presentation</p> <p>We report three cirrhotic patients who were admitted with abdominal sepsis and who illustrate, to various degrees, the clinico-pathological sequence of colonic alterations associated with portal hypertension. Two cirrhotic patients with PHC developed gram-negative bacteraemia and quickly responded to intravenous antibiotics. Another cirrhotic patient underwent emergency colectomy for PC, and subsequently died from multiple organ failure. Histological alterations in the operative specimen included: a) mucosal ulcerations; b) disseminated micro-abscesses in the submucosa; and c) a severe vasculopathy leading to complete obliteration of submucosal blood vessels.</p> <p>Conclusions</p> <p>These data suggest that cirrhotic patients with PHC may progress towards PC, which, in turn, may be the cause for life-threatening sepsis.</p