Open weather and climate science in the digital era

The need for open science has been recognized by the communities of meteorology and climate science. While these domains are mature in terms of applying digital technologies, the implementation of open science methodologies is less advanced. In a session on “Weather and Climate Science in the Digital Era” at the 14th IEEE International eScience Conference domain specialists and data and computer scientists discussed the road towards open weather and climate science. Roughly 80 % of the studies presented in the conference session showed the added value of open data and software. These studies included open datasets from disparate sources in their analyses or developed tools and approaches that were made openly available to the research community. Furthermore, shared software is a prerequisite for the studies which presented systems like a model coupling framework or digital collaboration platform. Although these studies showed that sharing code and data is important, the consensus among the participants was that this is not sufficient to achieve open weather and climate science and that there are important issues to address. At the level of technology, the application of the findable, accessible, interoperable, and reusable (FAIR) principles to many datasets used in weathe

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

Previsão de produção fotovoltaica : o ponto de partida para a integração de uma fonte de energia variável no tempo

CIES2020 - XVII Congresso Ibérico e XIII Congresso Ibero-americano de Energia SolarRESUMO: Previsões de produção são consideradas como uma das ferramentas mais custo-eficaz para integrar capacidades elevadas de tecnologia fotovoltaica (FV) em sistemas elétricos. Este trabalho procura discutir de forma breve a maturação desta área de investigação e a aparente falta de divulgação de trabalhos que abordem o uso final das previsões e o valor técnico-económico associado. São identificadas diversas aplicações, discutindo em maior detalhe duas delas: a operação de redes elétricas (p.e. com um caso de estudo a demonstrar uma valorização de até 1.42 €/MWhproduzido para um dado sistema elétrico com 18% de penetração FV) e a participação de centrais FV em mercado (p.e. com um caso de estudo a estimar uma valorização de até 3.8 €/MWhproduzido para uma central FV a operar no mercado ibérico do dia seguinte).ABSTRACT: Generation forecasts are considered as one of the most cost-effective tools to integrate high levels of photovoltaic (PV) capacity in power systems. This work aims to briefly discuss the maturation of this research field and the apparent lack of outreach for works that address the end-use of solar forecasts and the associated technical-economic gains. Several applications are identified, with two of them being discussed in more detail: the operation of power systems (e.g. with one case-study estimating a valorization up to 1.42 €/MWhgenerated for a given power system with 18% PV penetration) and the participation of PV power plants in energy markets (e.g. with a case-study suggesting a valorization up to 3.8 €/MWhgenerated for a PV plant operating in the day-ahead Iberian market).info:eu-repo/semantics/publishedVersio

Are South African linefishes recovering and what makes them prone to overexploitation?

Managing coastal fisheries is challenging as the status of many fish stocks caught in these fisheries remains unknown. In the South African linefishery, regular comprehensive assessments of the status of most linefish stocks are unattainable owing to a scarcity of reliable long-term data. Length-based analysis remains the only option to determine stock status in the form of spawning potential ratio (SPR), as life-history information and representative length samples are available for many linefish species. Although per-recruit models are susceptible to bias due to violation of the steady-state assumption, the SPR has been shown to be robust for long-lived species under reasonably consistent fishing mortality. In this study we used observer-collected length-frequency data from two time periods 20 years apart (1988–1990 and 2008–2010), before and after management regulations were implemented, in combination with life-history information, to estimate the SPRs for 17 linefish species. We then correlated the recent stock-status estimates to species-specific life-history traits to identify length-based indicators of susceptibility to exploitation. Most species showed improvements in SPR between the periods, caused mainly by decreases in fishing mortality (F) and also increases in length-at-first-capture (Lc). The ratio between Lc and asymptotic length (Lc/L∞), and the ratio between Lc and optimum length (Lc/Lopt), had significant relationships with SPR. We suggest that length-based indicators could be used to classify risk to overfishing in data-poor fisheries for medium- to long-lived species when time-series data are not attainable, but where representative size samples and adequate life-history information exist. Keywords: assessment methods, data-limited fishery, fisheries management, length-based indicators, life-history traits, per-recruit model, spawning potential rati

Software tools for the evaluation of clinical signs and symptoms in the medical management of acute radiation syndrome-a five-year experience.

A suite of software tools has been developed for dose estimation (BAT, WinFRAT) and prediction of acute health effects (WinFRAT, H-Module) using clinical symptoms and/or changes in blood cell counts. We constructed a database of 191 ARS cases using the METREPOL (n = 167) and the SEARCH-database (n = 24). The cases ranged from unexposed (RC0), to mild (RC1), moderate (RC2), severe (RC3), and lethal ARS (RC4). From 2015-2019, radiobiology students and participants of two NATO meetings predicted clinical outcomes (RC, H-ARS, and hospitalization) based on clinical symptoms. We evaluated the prediction outcomes using the same input datasets with a total of 32 teams and 94 participants. We found that: (1) unexposed (RC0) and mildly exposed individuals (RC1) could not be discriminated; (2) the severity of RC2 and RC3 were systematically overestimated, but almost all lethal cases (RC4) were correctly predicted; (3) introducing a prior education component for non-physicians significantly increased the correct predictions of RC, ARS, and hospitalization by around 10% (p<0.005) with a threefold reduction in variance and a halving of the evaluation time per case; (4) correct outcome prediction was independent of the software tools used; and (5) comparing the dose estimates generated by the teams with H-ARS severity reflected known limitations of dose alone as a surrogate for H-ARS severity. We found inexperienced personnel can use software tools to make accurate diagnostic and treatment recommendations with up to 98% accuracy. Educational training improved the quality of decision making and enabled participants lacking a medical background to perform comparably to experts

Uncertainty Forecasting in a Nutshell

It is in the nature of chaotic atmospheric processes that weather forecasts will never be perfectly accurate. This natural fact poses challenges not only for private life, public safety, and traffic but also for electrical power systems with high shares of weather-dependent wind and solar power production. To facilitate a secure and economic grid and market integration of renewable energy sources (RES), grid operators and electricity traders must know how much power RES within their systems will produce over the next hours and days. This is why RES forecast models have grown over the past decade to become indispensable tools for many stakeholders in the energy economy. Driven by increased grid stability requirements and market forces, forecast systems have become tailored to the end user's application and already perform reliably over long periods. Apart from a residually moderate forecast error, there are single extreme-error events that greatly affect grid operators