GPS zenith delay sensitivity evaluated from high-resolution numerical weather prediction simulations of the 8–9 September 2002 flash flood over southeastern France

International audienceEstimations of zenith total delays (ZTD) were obtained during postprocessing of a high-resolution (2.4 km) nonhydrostatic atmospheric model (Méso-NH). These estimations were used to determine their sensitivity with respect to formulations of atmospheric refractivity, the approximation of zenith hydrostatic delays (ZHD) deduced from ground pressure, and the contributions of hydrometeors. The factor k for the conversion of zenith wet delay (ZWD) to integrated water vapor (IWV) was examined. Méso-NH is applied here to the extreme flash flood event of 8–9 September 2002 in southeastern France. The use of the hydrostatic formulation (to infer ZHD) leads to an overestimation of up to 18 mm with respect to the vertical integration of refractivity. Delay contributions of hydrometeors simulated by the high-resolution model reached more than 70 mm (%11 kg/m 2 IWV) in the heart of the convective cells in the case of the extreme flood event. The mean variations of IWV due to the use of different conversion factors (k used to transform ZWD to IWV) are evaluated to be less than 0.3 kg/m 2. This is less than the mean underestimation of IWV by 0.6 kg/m 2 relative to the GPS-like evaluation of IWV using the hydrostatic formulation and the ground temperature. In this study we also use GPS ZTD observations to validate three different numerical simulations of this extreme flood event. The simulation with the best fit to the GPS observations is also in best agreement with the surface rainfall measurements

DRIHM (2US): An e-Science environment for hydro-meteorological research on high impact weather events

From 1970 to 2012, about 9,000 high-impact weather events were reported globally, causing the loss of 1.94 million lives and damage of $2.4 trillion (U.S. dollars). The scientific community is called to action to improve the predictive ability of such events and communicate forecasts and associated risks both to affected populations and to those making decisions. At the heart of this challenge lies the ability to have easy access to hydrometeorological data and models and to facilitate the necessary collaboration between meteorologists, hydrologists, and computer science experts to achieve accelerated scientific advances. Two European Union (EU)-funded projects, Distributed Research Infrastructure for Hydro-Meteorology (DRIHM) and DRIHM to United States of America (DRIHM2US), sought to help address this challenge by developing a prototype e-science environment providing advanced end-to-end services (models, datasets, and postprocessing tools), with the aim of paving the way to a step change in how scientists can approach studying these events, with a special focus on flood events in complex topographic areas. This paper describes the motivation and philosophy behind this prototype e-science environment together with certain key components, focusing on hydrometeorological aspects that are then illustrated through actionable research for a critical flash flood event that occurred in October 2014 in Liguria, Italy

DRIHM (2US): An e-Science environment for hydro-meteorological research on high impact weather events

From 1970 to 2012, about 9,000 high-impact weather events were reported globally, causing the loss of 1.94 million lives and damage of $2.4 trillion (U.S. dollars). The scientific community is called to action to improve the predictive ability of such events and communicate forecasts and associated risks both to affected populations and to those making decisions. At the heart of this challenge lies the ability to have easy access to hydrometeorological data and models and to facilitate the necessary collaboration between meteorologists, hydrologists, and computer science experts to achieve accelerated scientific advances. Two European Union (EU)-funded projects, Distributed Research Infrastructure for Hydro-Meteorology (DRIHM) and DRIHM to United States of America (DRIHM2US), sought to help address this challenge by developing a prototype e-science environment providing advanced end-to-end services (models, datasets, and postprocessing tools), with the aim of paving the way to a step change in how scientists can approach studying these events, with a special focus on flood events in complex topographic areas. This paper describes the motivation and philosophy behind this prototype e-science environment together with certain key components, focusing on hydrometeorological aspects that are then illustrated through actionable research for a critical flash flood event that occurred in October 2014 in Liguria, Italy

On the Use of Transfer Entropy to Investigate the Time Horizon of Causal Influences between Signals

Understanding the details of the correlation between time series is an essential step on the route to assessing the causal relation between systems. Traditional statistical indicators, such as the Pearson correlation coefficient and the mutual information, have some significant limitations. More recently, transfer entropy has been proposed as a powerful tool to understand the flow of information between signals. In this paper, the comparative advantages of transfer entropy, for determining the time horizon of causal influence, are illustrated with the help of synthetic data. The technique has been specifically revised for the analysis of synchronization experiments. The investigation of experimental data from thermonuclear plasma diagnostics proves the potential and limitations of the developed approach

Maximum likelihood bolometric tomography for the determination of the uncertainties in the radiation emission on JET TOKAMAK

The total emission of radiation is a crucial quantity to calculate the power balances and to understand the physics of any Tokamak. Bolometric systems are the main tool to measure this important physical quantity through quite sophisticated tomographic inversion methods. On the Joint European Torus, the coverage of the bolometric diagnostic, due to the availability of basically only two projection angles, is quite limited, rendering the inversion a very ill-posed mathematical problem. A new approach, based on the maximum likelihood, has therefore been developed and implemented to alleviate one of the major weaknesses of traditional tomographic techniques: the difficulty to determine routinely the confidence intervals in the results. The method has been validated by numerical simulations with phantoms to assess the quality of the results and to optimise the configuration of the parameters for the main types of emissivity encountered experimentally. The typical levels of statistical errors, which may significantly influence the quality of the reconstructions, have been identified. The systematic tests with phantoms indicate that the errors in the reconstructions are quite limited and their effect on the total radiated power remains well below 10%. A comparison with other approaches to the inversion and to the regularization has also been performed