24,513 research outputs found

    Monitoring the Thermal Power of Nuclear Reactors with a Prototype Cubic Meter Antineutrino Detector

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    In this paper, we estimate how quickly and how precisely a reactor's operational status and thermal power can be monitored over hour to month time scales, using the antineutrino rate as measured by a cubic meter scale detector. Our results are obtained from a detector we have deployed and operated at 25 meter standoff from a reactor core. This prototype can detect a prompt reactor shutdown within five hours, and monitor relative thermal power to three percent within seven days. Monitoring of short-term power changes in this way may be useful in the context of International Atomic Energy Agency's (IAEA) Reactor Safeguards Regime, or other cooperative monitoring regimes.Comment: 10 pages, 9 figure

    The impact of stochastic physics on climate sensitivity in EC-Earth

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    Stochastic schemes, designed to represent unresolved sub-grid scale variability, are frequently used in short and medium-range weather forecasts, where they are found to improve several aspects of the model. In recent years, the impact of stochastic physics has also been found to be beneficial for the model's long term climate. In this paper, we demonstrate for the first time that the inclusion of a stochastic physics scheme can notably affect a model's projection of global warming, as well as its historical climatological global temperature. Specifically, we find that when including the 'stochastically perturbed parametrisation tendencies' scheme (SPPT) in the fully coupled climate model EC-Earth v3.1, the predicted level of global warming between 1850 and 2100 is reduced by 10% under an RCP8.5 forcing scenario. We link this reduction in climate sensitivity to a change in the cloud feedbacks with SPPT. In particular, the scheme appears to reduce the positive low cloud cover feedback, and increase the negative cloud optical feedback. A key role is played by a robust, rapid increase in cloud liquid water with SPPT, which we speculate is due to the scheme's non-linear interaction with condensation.Comment: Under review in Journal of Geophysical Research: Atmosphere

    Development and structure of karstification of the Dong Van Karst Plateau UNESCO Global Geopark, North Vietnam based on cave survey data

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    This paper presents a quantitative study of the relationship between the cave system and the tectonic and karst evolution of the Dong Van Karst Plateau based on analysis and statistics of geometric parameters and orientation of cave passages. The region is located in northern Vietnam and belongs to the extended part of the South China karst belt (Yunnan karst plateau), which is composed mainly of carbonate rocks. Cave classification based on cave conduits geometric parameters shows that caves developed mainly in the vadose zone (27 vadose branchwork caves, 10 mixed caves developed under the control of fault systems, and 12 water-table caves). The degree of correlation between cave levels and planation surfaces suggests that the development of horizontal cave passages is related to two levels of planation surfaces, including one at 1250–1450 masl (equivalent to cave level at 1350–1450 masl), and at 1000–1250 masl (corresponding to cave level at 1200–1250 masl). Additionally, cave passage orientation shows that the cave system formed and developed under the influence of tectonic activities in the Cenozoic. The dominant orientation trend is roughly in the East–West direction and occurred in the early phase (Eocene–Miocene). Next is a trend roughly North–South that occurred in the late phase (Pliocene–Quaternary). The last orientation trend follows the NW–SE direction due to the reactivation of paleo-fault systems in the same direction. Although there are limitations due to accessibility and the level of cave exploration, this research suggests that analysis and statistics of the geometric parameters and orientation of cave passages based on cave survey data can be one of the effective approaches used to identify the development and structure of karstification in the karst region

    ENSEMBLES: a new multi-model ensemble for seasonal-to-annual predictions: Skill and progress beyond DEMETER in forecasting tropical Pacific SSTs

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    A new 46-year hindcast dataset for seasonal-to-annual ensemble predictions has been created using a multi-model ensemble of 5 state-of-the-art coupled atmosphere-ocean circulation models. The multi-model outperforms any of the single-models in forecasting tropical Pacific SSTs because of reduced RMS errors and enhanced ensemble dispersion at all lead-times. Systematic errors are considerably reduced over the previous generation (DEMETER). Probabilistic skill scores show higher skill for the new multi-model ensemble than for DEMETER in the 4–6 month forecast range. However, substantially improved models would be required to achieve strongly statistical significant skill increases. The combination of ENSEMBLES and DEMETER into a grand multi-model ensemble does not improve the forecast skill further. Annual-range hindcasts show anomaly correlation skill of ∼0.5 up to 14 months ahead. A wide range of output from the multi-model simulations is becoming publicly available and the international community is invited to explore the full scientific potential of these data

    Oceanic stochastic parametrizations in a seasonal forecast system

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    We study the impact of three stochastic parametrizations in the ocean component of a coupled model, on forecast reliability over seasonal timescales. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the Stochastically Perturbed Parametrization Tendency (SPPT) scheme - which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely the western boundary currents and the Southern Ocean. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error. Whilst there are good grounds for implementing stochastic schemes in ocean models, our results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.Comment: 24 pages, 3 figure

    Oceanic stochastic parametrizations in a seasonal forecast system

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    We study the impact of three stochastic parametrizations in the ocean component of a coupled model, on forecast reliability over seasonal timescales. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the Stochastically Perturbed Parametrization Tendency (SPPT) scheme - which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely the western boundary currents and the Southern Ocean. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error. Whilst there are good grounds for implementing stochastic schemes in ocean models, our results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.Comment: 24 pages, 3 figure
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