Publications associées à Atmosphère de Jupiter

Atmospheric isoprene measurements reveal larger-than-expected Southern Ocean emissions

Isoprene is a key trace component of the atmosphere emitted by vegetation and other organisms. It is highly reactive and can impact atmospheric composition and climate by affecting the greenhouse gases ozone and methane and secondary organic aerosol format ...

Nature Research2024

A Downscaling Intercomparison Study: The Representation of Slope- and Ridge-Scale Processes in Models of Different Complexity

Varun Sharma, Franziska Gerber, Albertus Christiaan Kruyt, Dylan Stewart Reynolds

Spatially distributed meteorological information at the slope scale is relevant for many processes in complex terrain, yet information at this sub-km spatial resolution is difficult to obtain. While downscaling to kilometer resolutions is well described in ...

FRONTIERS MEDIA SA2022

The Alfvenic nature of chromospheric swirls

Aleksi Antoine Bossart, Andrea Francesco Battaglia

Context. Observations show that small-scale vortical plasma motions are ubiquitous in the quiet solar atmosphere. They have received increasing attention in recent years because they are a viable candidate mechanism for the heating of the outer solar atmos ...

EDP SCIENCES S A2021

How eigenmode self-interaction affects zonal flows and convergence of tokamak core turbulence with toroidal system size

Stephan Brunner, Justin Richard Ball, Gabriele Merlo, Ajay Chandrarajan Jayalekshmi, Julien Stanislas Pierre Dominski

Self-interaction is the process by which a microinstability eigenmode that is extended along the direction parallel to the magnetic field interacts non-linearly with itself. This effect is particularly significant in gyrokinetic simulations accounting for ...

Cambridge University Press2020

Three-dimensional radiative transfer effects on airborne and ground-based trace gas remote sensing

Alexis Berne, Dominik Brunner, Thomas Wagner

Air mass factors (AMFs) are used in passive trace gas remote sensing for converting slant column densities (SCDs) to vertical column densities (VCDs). AMFs are traditionally computed with 1D radiative transfer models assuming horizontally homogeneous condi ...

2020

Improved Near-Surface Continental Climate in IPSL-CM6A-LR by Combined Evolutions of Atmospheric and Land Surface Physics

Etienne Gabriel Henri Vignon

This work is motivated by the identification of the land-atmosphere interactions as one of the key sources of uncertainty in climate change simulations. It documents new developments in related processes, namely, boundary layer/convection/clouds parameteri ...

2020

The Pristine survey IX. CFHT ESPaDOnS spectroscopic analysis of 115 bright metal-poor candidate stars

Pascale Jablonka, Carmela Lardo

A chemo-dynamical analysis of 115 metal-poor candidate stars selected from the narrow band Pristine photometric survey is presented based on CFHT high-resolution ESPaDOnS spectroscopy, We have discovered 28 new bright (V < 15) stars with I Fe/H]

OXFORD UNIV PRESS2020

Meteorological Aspects of Self-Initiated Upward Lightning at the Santis Tower (Switzerland)

Marcos Rubinstein, Antonio Sunjerga, Farhad Rachidi-Haeri, Mohammad Azadifar, Amirhossein Mostajabi, Nikola Besic, Jacopo Grazioli, Urs Martin Germann

Interest in exploring the meteorological conditions favoring upward lightning from tall man-made structures has grown in recent years, largely due to the worldwide expansion of wind energy. To this end, instrumented towers existing around the world are the ...

2019

Tracing the formation of the Milky Way through ultra metal-poor stars

Pascale Jablonka, Nicolas Lawrence Etienne Longeard

We use Gaia DR2 astrometric and photometric data, published radial velocities and MESA models to infer distances, orbits, surface gravities, and effective temperatures for all ultra metal-poor stars ([Fe/H] < -4.0 dex) available in the literature. Assuming ...

OXFORD UNIV PRESS2019

Reconstruction of Cloud Vertical Structure With a Generative Adversarial Network

Jussi Sakari Leinonen

We demonstrate the feasibility of solving atmospheric remote sensing problems with machine learning using conditional generative adversarial networks (CGANs), implemented using convolutional neural networks. We apply the CGAN to generating two-dimensional ...

AMER GEOPHYSICAL UNION2019