Scipy/Scipy: Scipy 0.18.1

Virtanen, Pauli; Gommers, Ralf; Oliphant, Travis E.; Cournapeau, David; Weckesser, Warren; Alexbrc,; Peterson, Pearu; Wnbell,; Mattknox_ca,; Walt, Stéfan van der; Laxalde, Denis; Brett, Matthew; Millman, Jarrod; Mayorov, Nikolay; Eric-Jones,; Kern, Robert C.; Moore, Eric J.; Gm, Pierre; Schofield, Ed; Leslie, Tim; Perktold, Josef; Cookedm,; Griffith, Blake; Nelson, A.; Eads, Damian; Vanderplas, Jake; Cj, Carey; Waite, Thomas A.; Wilson, Josh; Escalante, Abraham; Falck, Rob; Fullung,; Larson, Eric B.; Smith, Daniel B.; Harris, Charles B.; Archibald, Anne M.; Molden, Sturla; Cimrman, Robert; Henriksen, Ian; Hilboll, Andreas; Berkenkamp, Felix; Ye, Feng; Burns, C. B.; Taylor, Jonathan; Schnell, I.; Tsai, Richard; Nothman, Joel; Reimer, Joscha; Quintero, E. A.; Nowaczyk, Nikolai; Reddy, Tyler; Taylor, Julian; Prabhu,; Stevenson, Jacob D.; Seabold, Skipper; Hochberg, Tim; Pedregosa, Fabián; Teichmann, Martin; Bourquin, R.D.; McIntyre, Alan; Warde-Farley, David; Ingold, Gert‐Ludwig; Kroshko, Dmitrey; Varilly, Patrick; Gohlke, Christoph; Young, G.; Probst, Irvin; Nation, Paul; Fulton, Chad; Pérez, Fernando; Kulick, Jeffrey H.; Vankerschaver, Joris; Kerr, Chris; Mailhot, Fred; Nandana, Maniteja; Scopatz, Anthony; Vaught, Travis; Jtravs,; Foreest, Nicky D. van; Robitaille, Thomas; Lee, Antony; Venthur, Bastian; Boulogne, François; Brodtkorb, Per; Bunch, Pete; Wettinger, Raphael; Grigorievskiy, Alexander; Gaul, André; Silterra, Jacob; Chanley,; Weinbe,

doi:10.5281/zenodo.154391

Cited by 2 publications

(1 citation statement)

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“…The coding to the present study relies on the Python v2.7.13 packages xarray v0.9.1 written by Virtanen et al, 2016); here used for I/O tasks and statistical analyses. The Matplotlib v2.0.0 package written by Hunter (2007) (https://doi.org/10.5281/zenodo.248351, Droettboom et al, 2017), as well as the Basemap v1.0.7 toolkit (https://github.…”

Section: Applied Python Packagesmentioning

confidence: 99%

A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to-high latitudes

Brands

2022

Geosci. Model Dev.

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Abstract. Global climate models are a keystone of modern climate research. In most applications relevant for decision making, they are assumed to provide a plausible range of possible future climate states. However, these models have not been originally developed to reproduce the regional-scale climate, which is where information is needed in practice. To overcome this dilemma, two general efforts have been made since their introduction in the late 1960s. First, the models themselves have been steadily improved in terms of physical and chemical processes, parametrization schemes, resolution and implemented climate system components, giving rise to the term “Earth system model”. Second, the global models' output has been refined at the regional scale using limited area models or statistical methods in what is known as dynamical or statistical downscaling. For both approaches, however, it is difficult to correct errors resulting from a wrong representation of the large-scale circulation in the global model. Dynamical downscaling also has a high computational demand and thus cannot be applied to all available global models in practice. On this background, there is an ongoing debate in the downscaling community on whether to thrive away from the “model democracy” paradigm towards a careful selection strategy based on the global models' capacity to reproduce key aspects of the observed climate. The present study attempts to be useful for such a selection by providing a performance assessment of the historical global model experiments from CMIP5 and 6 based on recurring regional atmospheric circulation patterns, as defined by the Jenkinson–Collison approach. The latest model generation (CMIP6) is found to perform better on average, which can be partly explained by a moderately strong statistical relationship between performance and horizontal resolution in the atmosphere. A few models rank favourably over almost the entire Northern Hemisphere mid-to-high latitudes. Internal model variability only has a small influence on the model ranks. Reanalysis uncertainty is an issue in Greenland and the surrounding seas, the southwestern United States and the Gobi Desert but is otherwise generally negligible. Along the study, the prescribed and interactively simulated climate system components are identified for each applied coupled model configuration and a simple codification system is introduced to describe model complexity in this sense.

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Section: Applied Python Packagesmentioning

confidence: 99%

A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to-high latitudes

Brands

2022

Geosci. Model Dev.

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Respiratory syncytial virus co-opts host mitochondrial function to favour infectious virus production

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Ghildyal

et al. 2019

eLife

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Although respiratory syncytial virus (RSV) is responsible for more human deaths each year than influenza, its pathogenic mechanisms are poorly understood. Here high-resolution quantitative imaging, bioenergetics measurements and mitochondrial membrane potential- and redox-sensitive dyes are used to define RSV’s impact on host mitochondria for the first time, delineating RSV-induced microtubule/dynein-dependent mitochondrial perinuclear clustering, and translocation towards the microtubule-organizing centre. These changes are concomitant with impaired mitochondrial respiration, loss of mitochondrial membrane potential and increased production of mitochondrial reactive oxygen species (ROS). Strikingly, agents that target microtubule integrity the dynein motor protein, or inhibit mitochondrial ROS production strongly suppresses RSV virus production, including in a mouse model with concomitantly reduced virus-induced lung inflammation. The results establish RSV’s unique ability to co-opt host cell mitochondria to facilitate viral infection, revealing the RSV-mitochondrial interface for the first time as a viable target for therapeutic intervention.

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Scipy/Scipy: Scipy 0.18.1

Cited by 2 publications

References 0 publications

A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to-high latitudes

A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to-high latitudes

Respiratory syncytial virus co-opts host mitochondrial function to favour infectious virus production

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