No abstract

-While shedding routes of Coxiella burnetii are identified, the characteristics of Coxiella shedding are still widely unknown, especially in dairy cattle. However, this information is crucial to assess the natural course of Coxiella burnetii infection within a herd and then to elaborate strategies to limit the risks of transmission between animals and to humans. The present study aimed at (i) describing the characteristics of Coxiella burnetii shedding by dairy cows (in milk, vaginal mucus, faeces) in five infected dairy herds, and at (ii) investigating the possible relationships between shedding patterns and serological responses. A total of 145 cows were included in a follow-up consisting of seven concomitant samplings of milk, vaginal mucus, faeces and blood (Day 0, D7, D14, D21, D28, D63, D90). Detection and quantification of Coxiella burnetii titres were performed in milk, vaginal mucus and faeces samples using real-time PCR assay, while antibodies against Coxiella were detected using an ELISA technique. For a given shedding route, and a given periodicity (weekly or monthly), cows were gathered into different shedding kinetic patterns according to the sequence of PCR responses. Distribution of estimated titres in Coxiella burnetii was described according to shedding kinetic patterns. Coxiella burnetii shedding was found scarcely and sporadically in faeces. Vaginal mucus shedding concerned almost 50% of the cows studied and was found intermittently or sporadically, depending on the periodicity considered. Almost 40% of cows were detected as milk shedders, with two predominant shedding patterns: persistent and sporadic, regardless of the sampling periodicity. Significantly higher estimated titres in Coxiella burnetii were observed in cows with persistent shedding patterns suggesting the existence of heavy shedder cows. These latter cows were mostly, persistently highly-seropositive, suggesting that repeated serological testings could be a reliable tool to screen heavy shedders, before using PCR assays. dairy cow / Coxiella burnetii / shedding / antibodies / kinetics

This study assesses the potential for a detection algorithm to identify discriminating analysis-based statistical predictors of a few relevant parameters that can be used to capture heavy precipitation events (HPEs), or, at least, their associated largescale circulation (LSC) patterns in a climate scenario. HPEs are defined from a sample combining 'large-scale' fields from the ECMWF ERA-40 reanalysis with local observations from the Météo-France rain-gauge network. In a first step, LSC patterns considered as significantly favouring HPE over southern France are identified and described with the greatest robustness possible. For that purpose, an objective automatic clustering of the unfiltered 500 hPa geopotential height field is performed. Four clusters are obtained. Among them, the most discriminating for heavy precipitation is characterised by a synoptic-scale deep upper-level low northwest of the area of interest, inducing a southerly flow over the western Mediterranean Sea and southern France. In a second step, other lower-scale parameters are used to refine the characteristics of the clusters. It has been found that the low-level moisture transport is a relevant low-level ingredient to regionally characterise heavy precipitation. Indeed, 'Cévennes' cases are related to more south to southeasterly flows over the Gulf of Lion, whereas 'Languedoc-Roussillon' events occurred preferentially within a more pronounced easterly wind component with two streams of low-level moisture transport. Moreover, in-depth examination of the low-level features reveals that HPEs tend to occur when the wind blows in a specific direction and for the greatest low-level moisture flux over the Gulf of Lion. Finally, the predictive skill of a detection tool for HPEs over southern France, with only synoptic-scale favourable parameters as predictors, is discussed. It is shown that this tool allows selection of HPE situations in more than 70% of cases.

Abstract. The ALADIN System is a numerical weather prediction (NWP) system developed by the international AL-ADIN consortium for operational weather forecasting and research purposes. It is based on a code that is shared with the global model IFS of the ECMWF and the ARPEGE model of Météo-France. Today, this system can be used to provide a multitude of high-resolution limited-area model (LAM) configurations. A few configurations are thoroughly validated and prepared to be used for the operational weather forecasting in the 16 partner institutes of this consortium. These configurations are called the ALADIN canonical model configurations (CMCs). There are currently three CMCs: the AL-ADIN baseline CMC, the AROME CMC and the ALARO CMC. Other configurations are possible for research, such as process studies and climate simulations.The purpose of this paper is (i) to define the ALADIN System in relation to the global counterparts IFS and ARPEGE, (ii) to explain the notion of the CMCs, (iii) to document their most recent versions, and (iv) to illustrate the process of the validation and the porting of these configurations to the operational forecast suites of the partner institutes of the AL-ADIN consortium. This paper is restricted to the forecast model only; data assimilation techniques and postprocessing techniques are part of the ALADIN System but they are not discussed here.

-Reliable detection of Coxiella burnetii shedders is a critical point for the control of the spread of this bacterium among animals and from animals to humans. Coxiella burnetii is shed by ruminants mainly by birth products (placenta, birth fluids), but may also be shed by vaginal mucus, milk, and faeces, urine and semen. However, the informative value of these types of samples to identify shedders under field conditions is unknown. Our aim was then to describe the responses obtained using a real-time PCR technique applied to milk, vaginal mucus and faeces samples taken from 242 dairy cows in commercial dairy herds known to be naturally infected with Coxiella burnetii, and to assess their putative associations. Positive results were found in all types of tested samples even in faeces. No predominant shedding route was identified. Among the shedder cows, 65.4% were detected as shedders by only one route. By contrast, cows with positive results for all three samples were scarce (less than 7%). Testing a cow based on only one type of biological sample may lead to misclassify it with regards to its shedding of Coxiella burnetii and thereby underestimate the risk of bacterial spread within a herd. dairy cows / Coxiella burnetii / shedding routes / real-time PCR / Q fever

No abstract

The Fronts and Atlantic Storm-Track Experiment (FASTEX) will address the life cycle of cyclones evolving over the North Atlantic Ocean in January and February 1997. The objectives of FASTEX are to improve the forecasts of endof-storm-track cyclogenesis (primarily in the eastern Atlantic but with applicability to the Pacific) in the range 24 to 72 h, to enable the testing of theoretical ideas on cyclone formation and development, and to document the vertical and the mesoscale structure of cloud systems in mature cyclones and their relation to the dynamics. The observing system includes ships that will remain in the vicinity of the main baroclinic zone in the central Atlantic Ocean, jet aircraft that will fly and drop sondes off the east coast of North America or over the central Atlantic Ocean, turboprop aircraft that will survey mature cyclones off Ireland with dropsondes, and airborne Doppler radars, including ASTRAIA/ELDORA. Radiosounding frequency around the North Atlantic basin will be increased, as well as the number of drifting buoys. These facilities will be activated during multiple-day intensive observing periods in order to observe the same meteorological systems at several stages of their life cycle. A central archive will be developed in quasi-real time in Toulouse, France, thus allowing data to be made widely available to the scientific community.

Météo-France has implemented a short-range ensemble prediction system known as Prévision d'Ensemble ARPEGE (PEARP). This system is a global ensemble performing forecasts up to 4.5 days. It uses the operational global numerical weather prediction model Action de Recherche Petite Echelle Grande Echelle (ARPEGE) and benefits from variable horizontal resolution, so that it is comparable to some limited-area mesoscale systems over France. Perturbations to the initial conditions are computed by combining an ensemble data assimilation system with singular vectors. Model uncertainties are represented through a 'multiphysics' approach with ten different physical parametrization sets. The article describes the set-up of the system and provides an assessment of the approaches used to represent initial conditions and model uncertainties. The positive impact of the variable horizontal resolution of PEARP is also illustrated. As a global ensemble forecast system (EFS), PEARP is also used to forecast cyclone tracks. It is shown that it has correctly predicted the landfall of hurricane Sandy. The performance of PEARP as run operationally with these features in 2014 is assessed objectively and compared with that of four operational global EFSs using classical probabilistic scores. This comparison is based on The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data. This is one of the first evaluations of EFSs for short-range forecasts. The reliability and global skill of the five EFSs are evaluated over a three-month period with scores computed against observations. PEARP shows skill comparable to or better than the other EFSs.