Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes

A transition to renewable energy is needed to mitigate climate change. In Europe, this transition has been led by wind energy, which is one of the fastest growing energy sources. However, energy demand and production are sensitive to meteorological conditions and atmospheric variability at multiple time scales. To accomplish the required balance between these two variables, critical conditions of high demand and low wind energy supply must be considered in the design of energy systems. We describe a methodology for modeling joint distributions of meteorological variables without making any assumptions about their marginal distributions. In this context, Gaussian copulas are used to model the correlated nature of cold and weak-wind events. The marginal distributions are modeled with logistic regressions defining two sets of binary variables as predictors: four large-scale weather regimes and the months of the extended winter season. By applying this framework to ERA5 data, we can compute the joint probabilities of co-occurrence of cold and weak-wind events on a high-resolution grid (0.25 deg). Our results show that a) weather regimes must be considered when modeling cold and weak-wind events, b) it is essential to account for the correlations between these events when modeling their joint distribution, c) we need to analyze each month separately, and d) the highest estimated number of days with compound events are associated with the negative phase of the North Atlantic Oscillation (3 days on average over Finland, Ireland, and Lithuania in January, and France and Luxembourg in February) and the Scandinavian Blocking pattern (3 days on average over Ireland in January and Denmark in February). This information could be relevant for application in sub-seasonal to seasonal forecasts of such events

Bias Correction of Operational Storm Surge Forecasts Using Neural Networks

Storm surges can give rise to extreme floods in coastal areas. The Norwegian Meteorological Institute produces 120-hour regional operational storm surge forecasts along the coast of Norway based on the Regional Ocean Modeling System (ROMS), using a model setup called Nordic4-SS. Despite advances in the development of models and computational capabilities, forecast errors remain large enough to impact response measures and issued alerts, in particular, during the strongest events. Reducing these errors will positively impact the efficiency of the warning systems while minimizing efforts and resources spent on mitigation. Here, we investigate how forecasts can be improved with residual learning, i.e., training data-driven models to predict the residuals in forecasts from Nordic4-SS. A simple error mapping technique and a more sophisticated Neural Network (NN) method are tested. Using the NN residual correction method, the Root Mean Square Error in the Oslo Fjord is reduced by 36% for lead times of one hour and 9% for 24 hours. Therefore, the residual NN method is a promising direction for correcting storm surge forecasts, especially on short timescales. Moreover, it is well adapted to being deployed operationally, as i) the correction is applied on top of the existing model and requires no changes to it, ii) all predictors used for NN inference are already available operationally, iii) prediction by the NNs is very fast, typically a few seconds per station, and iv) the NN correction can be provided to a human expert who may inspect it, compare it with the model output, and see how much correction is brought by the NN, allowing to capitalize on human expertise as a quality validation of the NN output. While no changes to the hydrodynamic model are necessary to calibrate the neural networks, they are specific to a given model and must be recalibrated when the numerical models are updated

Identification of a Sorbicillinoid-Producing Aspergillus Strain with Antimicrobial Activity Against Staphylococcus aureus: a New Polyextremophilic Marine Fungus from Barents Sea

The exploration of poorly studied areas of Earth can highly increase the possibility to discover novel bioactive compounds. In this study, the cultivable fraction of fungi and bacteria from Barents Sea sediments has been studied to mine new bioactive molecules with antibacterial activity against a panel of human pathogens. We isolated diverse strains of psychrophilic and halophilic bacteria and fungi from a collection of nine samples from sea sediment. Following a full bioassay-guided approach, we isolated a new promising polyextremophilic marine fungus strain 8Na, identified as Aspergillusprotuberus MUT 3638, possessing the potential to produce antimicrobial agents. This fungus, isolated from cold seawater, was able to grow in a wide range of salinity, pH and temperatures. The growth conditions were optimised and scaled to fermentation, and its produced extract was subjected to chemical analysis. The active component was identified as bisvertinolone, a member of sorbicillonoid family that was found to display significant activity against Staphylococcus aureus with a minimum inhibitory concentration (MIC) of 30 μg/mL. © 2018, Springer Science+Business Media, LLC, part of Springer Nature

A dataset of direct observations of sea ice drift and waves in ice

Variability in sea ice conditions, combined with strong couplings to the atmosphere and the ocean, lead to a broad range of complex sea ice dynamics. More in-situ measurements are needed to better identify the phenomena and mechanisms that govern sea ice growth, drift, and breakup. To this end, we have gathered a dataset of in-situ observations of sea ice drift and waves in ice. A total of 15 deployments were performed over a period of 5 years in both the Arctic and Antarctic, involving 72 instruments. These provide both GPS drift tracks, and measurements of waves in ice. The data can, in turn, be used for tuning sea ice drift models, investigating waves damping by sea ice, and helping calibrate other sea ice measurement techniques, such as satellite based observations

Joint modeling of low temperature and low wind speed events over Europe conditioned on winter weather regimes

A transition to renewable energy is needed to mitigate climate change. This transition has been led by wind energy, and it is expected to continue to be the largest source of renewable energy through to 2030 (Sawyer et al., 2017). Both energy demand and production are sensitive to meteorological conditions and atmospheric variability at multiple time scales. To accomplish the required balance between these two variables, critical conditions of high demand and low wind energy supply must be considered in the design of energy systems. The aim of this thesis is twofold. Firstly, investigate the impacts of large-scale weather regimes on cold and weak-wind events during the extended boreal winter season (NDJFM). Secondly, to establish a methodology for modeling the joint distributions without making any assumptions about the marginal distributions. The analysis of 38 years of hourly high-resolution ERA5 reanalysis data proves that weather regimes are important predictors for both low temperature and low wind speed events over Europe. Blocking conditions, such as those observed during the negative phase of the North Atlantic Oscillation and the Scandinavian Blocking, are associated with cold and weak wind events. Compound events are observed more than 10% of the days overlarge geographical areas during blocking conditions. Nevertheless, high probabilities are also observed during AR, and to some extent, during the positive phase of the North Atlantic Oscillation. Dependency between cold events and weak wind events is proved to be statistically significant. The correlations between the events are higher when computed for each month separately compared to the entire winter season,revealing a strong seasonality. The highest correlations values are associated with the negative phase of the North Atlantic Oscillation, ρ=0.84, but values as high as 0.7 are registered for all the regimes. A methodology for modeling the bivariate joint distributions of low temperature and low-wind speed events is described. In this context, the concept of Gaussian copulas is used to mathematically model the correlated nature among them. The marginal distributions are modeled with logistic regressions defining two sets of binary variables for the weather regimes and months predictors

Identification Of A Sorbicillinoid-Producing Aspergillus Strain With Antimicrobial Activity Against Staphylococcus Aureus: A New Polyextremophilic Marine Fungus From Barents Sea

The exploration of poorly studied areas of Earth can highly increase the possibility to discover novel bioactive compounds. In this study, the cultivable fraction of fungi and bacteria from Barents Sea sediments has been studied to mine new bioactive molecules with antibacterial activity against a panel of human pathogens. We isolated diverse strains of psychrophilic and halophilic bacteria and fungi from a collection of nine samples from sea sediment. Following a full bioassay-guided approach, we isolated a new promising polyextremophilic marine fungus strain 8Na, identified as Aspergillusprotuberus MUT 3638, possessing the potential to produce antimicrobial agents. This fungus, isolated from cold seawater, was able to grow in a wide range of salinity, pH and temperatures. The growth conditions were optimised and scaled to fermentation, and its produced extract was subjected to chemical analysis. The active component was identified as bisvertinolone, a member of sorbicillonoid family that was found to display significant activity against Staphylococcus aureus with a minimum inhibitory concentration (MIC) of 30 μg/mL

Femmes de cinéma

Ce numéro, consacré aux femmes dans le cinéma latino-américain, propose des panoramas sur toute l’Amérique latine (la place des femmes dans la production, dans la réalisation), des articles sur les pionnières du cinéma, sur des réalisatrices contemporaines, des études plus détaillées sur des aspects cinématographiques de réalisatrices latino-américaines (comme par exemple Lucrecia Martel). Afin de rendre hommage aux réalisatrices latino-américaines, la revue a souhaité leur donner la parole en leur posant 3 questions à propos de leur conception de la création cinématographique. Leurs réponses ouvriront ce numéro. Enfin, une rubrique « reseñas » propose des comptes-rendus de livres récemment publiés à propos du cinéma latino-américain