Vincent Eymet

Is Gliese 581d habitable? Some constraints from radiative-convective climate modeling

The recently discovered exoplanet Gl 581d is extremely close to the outer edge of its system’s habitable zone, which has led to much speculation on its possible climate. We have performed a range of simulations to assess whether, given simple combinations of chemically stable greenhouse gases, the planet could sustain liquid water on its surface. For best estimates of the surface gravity, surface albedo and cloud coverage, we find that less than 10 bars of CO2 is sufficient to maintain a global mean temperature above the melting point of water. Furthermore, even with the most conservative choices of these parameters, we calculate temperatures above the water melting point for CO2 partial pressures greater than about 40 bar. However, we note that as Gl 581d is probably in a tidally resonant orbit, further simulations in 3D are required to test whether such atmospheric conditions are stable against the collapse of CO2 on the surface.

A net-exchange Monte Carlo approach to radiation in optically thick systems

A Monte Carlo approach to radiative transfer in participating media is described and tested. It solves to a large extent the well known problem of Monte Carlo simulation of optically thick absorption configurations. The approach which is based on a net-exchange formulation and on adapted optical path sampling procedures is carefully designed to insure satisfactory convergence for all types of optical thicknesses. The need for such adapted algorithms is mainly related to the problem of gaseous line spectra representation in which extremely large ranges of optical thicknesses may be simultaneously encountered. The algorithm is tested against various band average computations for simple geometries using the Malkmus statistical narrow band model.

A boundary-based net-exchange Monte Carlo method for absorbing and scattering thick media

A boundary-based net-exchange Monte Carlo method was introduced (JQSRT 74 (2001) 563) that allows to bypass the difficulties encountered by standard Monte Carlo algorithms in the limit of optically thick absorption (and/or for quasi-isothermal configurations). With the present paper, this method is extended to scattering media. Developments are fully 3D, but illustrations are presented for plane parallel configuration. Compared to standard Monte Carlo algorithms, convergence qualities have been improved over a wide range of absorption and scattering optical thicknesses. The proposed algorithm still encounters a convergence difficulty in the case of optically thick, highly scattering media.

Long-wave radiative analysis of cloudy scattering atmospheres using a net exchange formulation

The Net Exchange Formulation (NEF) is an alternative to the usual radiative transfer equation. It was proposed in 1967 by Green [Q. J. R. Meteorol. Soc. 93 (1967) 371] for atmospheric sciences and by Hottel [H.C. Hottel, A.F. Sarofim. Radiative Transfer McGraw Hill, New York, 1967] for engineering sciences. Until now, the NEF has been used only in a very few cases for atmospheric studies. Recently we have developed a long-wave radiative code based on this formulation for a GCM of the Mars planet. Here, we will present results for the Earth atmosphere, obtained with a Monte Carlo Method based on the NEF. In this method, fluxes are not addressed any more. The basic variables are the net exchange rates (NER) between each pair of atmospheric layer (i, j), i.e. the radiative power emitted by i and absorbed by j minus the radiative power emitted by j and absorbed by i. The graphical representation of the NER matrix highlights the radiative exchanges that dominate the radiative budget of the atmosphere and allows one to have a very good insight of the radiative exchanges. Results will be presented for clear sky atmospheres with Mid-Latitude Summer and Sub-Arctic Winter temperature profiles, and for the same atmospheres with three different types of clouds. The effect of scattering on long-wave radiative exchanges will also be analysed.

Radiative, conductive and convective heat-transfers in a single Monte Carlo algorithm

It was recently shown that null-collision algorithms could lead to grid-free radiative- transfer Monte Carlo algorithms that immediately benefit of computer-graphics tools for an efficient handling of complex geometries [1, 2]. We here explore the idea of extending the approach to heat transfer problems combining radiation, conduction and convection. This is possible as soon as the model can be given the form of a second-kind Fredholm equation. In the following pages, we show that this is quite straightforward at the stationnary limit in the linear case. The oral presentation will provide corresponding simulation examples. Perspectives will then be drawn concerning the extension to non-stationnary cases and non-linear coupling.

Addressing nonlinearities in Monte Carlo

Monte Carlo is famous for accepting model extensions and model refinements up to infinite dimension. However, this powerful incremental design is based on a premise which has severely limited its application so far: a state-variable can only be recursively defined as a function of underlying state-variables if this function is linear. Here we show that this premise can be alleviated by projecting nonlinearities onto a polynomial basis and increasing the configuration space dimension. Considering phytoplankton growth in light-limited environments, radiative transfer in planetary atmospheres, electromagnetic scattering by particles, and concentrated solar power plant production, we prove the real-world usability of this advance in four test cases which were previously regarded as impracticable using Monte Carlo approaches. We also illustrate an outstanding feature of our method when applied to acute problems with interacting particles: handling rare events is now straightforward. Overall, our extension preserves the features that made the method popular: addressing nonlinearities does not compromise on model refinement or system complexity, and convergence rates remain independent of dimension.

Monte Carlo efficiency improvement by multiple sampling of conditioned integration variables

We present a technique that permits to increase the efficiency of multidimensional Monte Carlo algorithms when the sampling of the first, unconditioned random variable consumes much more computational time than the sampling of the remaining, conditioned random variables while its variability contributes only little to the total variance. This is in particular relevant for transport problems in complex and randomly distributed geometries. The proposed technique is based on an new Monte Carlo estimator in which the conditioned random variables are sampled more often than the unconditioned one. A significant contribution of the present Short Note is an automatic procedure for calculating the optimal number of samples of the conditioned random variable per sample of the unconditioned one. The technique is illustrated by a current research example where it permits to increase the efficiency by a factor 100. Increase of multidimensional Monte Carlo algorithms efficiency.Significant improvements when considering complex and randomly distributed geometries.Automatic procedure to determine the optimal number of samples.General concept easily applicable to several fields.

Net‐exchange analysis of the Earth greenhouse effect increase

In this paper, we propose an analysis of the greenhouse effect on the basis of a net‐exchange formulation for clear sky atmospheres. This formulation allows access to exchanges beetwen the differents elements of the atmosphere (gas layers, the ground and space). When the greenhouse gas concentration increases, we first use a simple configuration to analyse the variations of analytic monochromatic net exchange rates. The same type of analysis is then applied to the Earth atmosphere for a clear‐sky middle latitude summer configuration with an increase in water vapour of 20% at all altitudes.