Entrapment: an important mechanism to explain the shortwave 3D radiative effect of clouds

Several mechanisms have previously been proposed to explain differences between the shortwave reflectance of realistic cloud scenes computed using the 1D independent column approximation (ICA) and 3D solutions of the radiative transfer equation. When the sun is low in the sky, interception of sunlight by cloud sides tends to increase reflectance relative to ICA estimates that neglect this effect. When the sun is high, 3D radiative transfer tends to make clouds less reflective, which we argue is explained by the mechanism of “entrapment” whereby horizontal transport of radiation beneath a cloud layer increases the chances, relative to the ICA, of light being absorbed by cloud or the surface. It is especially important for multilayered cloud scenes. We describe modifications to the previously described Speedy Algorithm for Radiative Transfer through Cloud Sides (SPARTACUS) to represent different entrapment assumptions, and test their impact on 65 contrasting scenes from a cloud-resolving model. When entrapment is represented explicitly via a calculation of the mean horizontal distance traveled by reflected light, SPARTACUS predicts a mean “3D radiative effect” (the difference in top-of-atmosphere irradiances between 3D and ICA calculations) of 8.1 W m−2 for overhead sun. This is within 2% of broadband Monte Carlo calculations on the same scenes. The importance of entrapment is highlighted by the finding that the extreme assumptions in SPARTACUS of “zero entrapment” and “maximum entrapment” lead to corresponding mean 3D radiative effects of 1.7 and 19.6 W m−2, respectively

Path-tracing Monte Carlo Library for 3D Radiative Transfer in Highly Resolved Cloudy Atmospheres

Interactions between clouds and radiation are at the root of many difficulties in numerically predicting future weather and climate and in retrieving the state of the atmosphere from remote sensing observations. The large range of issues related to these interactions, and in particular to three-dimensional interactions, motivated the development of accurate radiative tools able to compute all types of radiative metrics, from monochromatic, local and directional observables, to integrated energetic quantities. In the continuity of this community effort, we propose here an open-source library for general use in Monte Carlo algorithms. This library is devoted to the acceleration of path-tracing in complex data, typically high-resolution large-domain grounds and clouds. The main algorithmic advances embedded in the library are those related to the construction and traversal of hierarchical grids accelerating the tracing of paths through heterogeneous fields in null-collision (maximum cross-section) algorithms. We show that with these hierarchical grids, the computing time is only weakly sensitivive to the refinement of the volumetric data. The library is tested with a rendering algorithm that produces synthetic images of cloud radiances. Two other examples are given as illustrations, that are respectively used to analyse the transmission of solar radiation under a cloud together with its sensitivity to an optical parameter, and to assess a parametrization of 3D radiative effects of clouds.Comment: Submitted to JAMES, revised and submitted again (this is v2

The 3D radiative effects of boundary-layer clouds : from explicit simulation to parameterisation

Le rayonnement est un processus clé pour l'évolution de l'atmosphère. Les ondes électromagnétiques émises par les corps chauds comme le soleil interagissent avec de nombreuses composantes du Système Terre. Elles peuvent par exemple être diffusées et absorbées par de microscopiques gouttelettes d'eau en suspension dans les nuages. Aux échelles globales, ces processus radiatifs controlent les bilans d'énergie de la surface et de l'atmosphère. L'effet des cumulus — ces nuages de couche limite liquides, principalement non-précipitants, fractionnés — sur le rayonnement solaire est étudié depuis de nombreuses années. L'importance de ces effets pour les prévisions météorologiques et pour l'évolution du climat de la Terre a déjà été démontrée. Pourtant, notre compréhension de ces interactions complexes et multiéchelles reste limitée. Dans cette thèse, le lien entre les caractéristiques macrophysiques des nuages et leur impact sur le rayonnement solaire, et en particulier sur leurs ``effets 3D" (différence entre un calcul 3D et un calcul 1D dans lequel le transport horizontal est négligé), est étudié. Une paramétrisation existante des effets radiatifs 3D des nuages pour les modèles de grande échelle est analysée et évaluée contre des modèles de référence et des observations.A cette fin, des simulations haute résolution de quatre cas de convection de couche limite idéalisée sont réalisées à l'aide du modèle français Méso-NH, ainsi que des simulations perturbées permettant d'analyser l'impact de la résolution, de la taille du domaine, du schéma d'advection et des paramétrisations de la turbulence et de la microphysique sur les caractéristiques des populations nuageuses. Pour simuler à posteriori la propagation du rayonnement dans ces champs nuageux 3D, des outils Monte Carlo inspirés de la communauté de la synthèse d'image sont implémentés sous la forme d'un ensemble de modules génériques formant une bibliothèque libre ; ces modules sont ensuite utilisés pour implémenter des codes de Monte Carlo produisant un temps de calcul insensible à la complexité des scènes nuageuses.Le transfert radiatif 3D est résolu dans l'ensemble des champs nuageux simulés. Le lien entre les caractéristiques nuageuses analysées dans les différentes scènes et leurs effets radiatifs est analysé. Une attention particulière est portée sur les effets radiatifs 3D des nuages, par la réalisation de simulations Monte Carlo 3D et 1D (sous l'approximation de colonnes indépendantes), permettant d'isoler la contribution du transport horizontal sur les flux radiatifs à la surface et au sommet de l'atmosphère. Ces effets 3D sont quantifiés en fonction de l'angle solaire zénithal, et séparés en composantes directe et diffuse. Il apparait que les effets radiatifs 3D sont le résultat d'effets de signe opposé sur les flux direct et diffus, qui ne se compensent pas pour tous les angles solaires. La différence entre l'effet radiatif nuageux total (respectivement, direct) pour des calculs Monte Carlo 3D et 1D intégrés horizontalement et sur un cycle diurne atteint -13 W/m² (respectivement, -45 W/m²) pour des courses solaires correspondant aux hautes latitudes (les effets 3D refroidissent la surface).Radiation is a key process in the evolution of the atmosphere. Electromagnetic waves emitted by warm bodies like the sun interact with many components of the Earth system. For example, they can be scattered and absorbed by microscopic droplets in clouds. At global scales, these radiation processes drive the energy budgets of the surface and Earth. The impact of fractionated, mostly non-precipitating, liquid boundary-layer clouds (cumulus) on solar radiation has been studied for many years and is knowingly important for both Numerical Weather Predicitions and the evolution of the Earth's climate; yet our understanding of these complex, multi-scale interactions remains limited. In this thesis, the link between cloud macrophysic characteristics and their impact on solar radiation and in particular on their so-called 3D radiative effects (obtain from the difference between 3D and 1D computations where horizontal transport is neglected) is investigated. An existing parameterisation of 3D radiative effects of clouds for large-scale models is evaluated against reference models and observations. In order to do so, high-resolution simulations of four idealized convective boundary-layer cases are realized using the French Large-Eddy Model Méso-NH, along with perturbed simulations to assess the impact of resolution, domain size, advection scheme and parameterisations of turbulence and microphysics on cloud population characteristics. To simulate offline radiative transfer in these 3D cloudy fields, innovative Monte Carlo tools inspired from the community of computer graphics are implemented in the form of a collection of generic modules composing an open-source library, and used to build Monte Carlo codes that produce computing times that are insensitive to the complexity of the cloud scenes. 3D radiation is solved in all the simulated cloud fields, and the link between the characteristics of cloud populations from the various cases, and their radiative effect, is analysed. Special attention is dedicated to the 3D effects of clouds by performing 1D (under the independent column approximation) and 3D simulations by Monte Carlo, hence isolating the contribution of horizontal transport to the radiative fluxes at the surface and at the top of atmosphere. These 3D effects are quantified as a function of the solar zenith angle, and broken down into direct and diffuse components. It appears that the 3D bias on surface fluxes is the result of biases of opposite signs on direct and diffuse fluxes, that do not compensate each other at all solar angles. The difference between 1D and 3D total (respectively, direct) cloud radiative effect, integrated horizontally and over a diurnal cycle, can reach -13 W/m² (respectively, -45 W/m²) for sun paths corresponding to high latitudes (3D effects act to cool the surface)

Les effets radiatifs 3D des nuages de couche limite : de leur simulation explicite à leur paramétrisation

Radiation is a key process in the evolution of the atmosphere. Electromagnetic waves emitted by warm bodies like the sun interact with many components of the Earth system. For example, they can be scattered and absorbed by microscopic droplets in clouds. At global scales, these radiation processes drive the energy budgets of the surface and Earth. The impact of fractionated, mostly non-precipitating, liquid boundary-layer clouds (cumulus) on solar radiation has been studied for many years and is knowingly important for both Numerical Weather Predicitions and the evolution of the Earth's climate; yet our understanding of these complex, multi-scale interactions remains limited. In this thesis, the link between cloud macrophysic characteristics and their impact on solar radiation and in particular on their so-called 3D radiative effects (obtain from the difference between 3D and 1D computations where horizontal transport is neglected) is investigated. An existing parameterisation of 3D radiative effects of clouds for large-scale models is evaluated against reference models and observations. In order to do so, high-resolution simulations of four idealized convective boundary-layer cases are realized using the French Large-Eddy Model Méso-NH, along with perturbed simulations to assess the impact of resolution, domain size, advection scheme and parameterisations of turbulence and microphysics on cloud population characteristics. To simulate offline radiative transfer in these 3D cloudy fields, innovative Monte Carlo tools inspired from the community of computer graphics are implemented in the form of a collection of generic modules composing an open-source library, and used to build Monte Carlo codes that produce computing times that are insensitive to the complexity of the cloud scenes. 3D radiation is solved in all the simulated cloud fields, and the link between the characteristics of cloud populations from the various cases, and their radiative effect, is analysed. Special attention is dedicated to the 3D effects of clouds by performing 1D (under the independent column approximation) and 3D simulations by Monte Carlo, hence isolating the contribution of horizontal transport to the radiative fluxes at the surface and at the top of atmosphere. These 3D effects are quantified as a function of the solar zenith angle, and broken down into direct and diffuse components. It appears that the 3D bias on surface fluxes is the result of biases of opposite signs on direct and diffuse fluxes, that do not compensate each other at all solar angles. The difference between 1D and 3D total (respectively, direct) cloud radiative effect, integrated horizontally and over a diurnal cycle, can reach -13 W/m² (respectively, -45 W/m²) for sun paths corresponding to high latitudes (3D effects act to cool the surface).Le rayonnement est un processus clé pour l'évolution de l'atmosphère. Les ondes électromagnétiques émises par les corps chauds comme le soleil interagissent avec de nombreuses composantes du Système Terre. Elles peuvent par exemple être diffusées et absorbées par de microscopiques gouttelettes d'eau en suspension dans les nuages. Aux échelles globales, ces processus radiatifs controlent les bilans d'énergie de la surface et de l'atmosphère. L'effet des cumulus — ces nuages de couche limite liquides, principalement non-précipitants, fractionnés — sur le rayonnement solaire est étudié depuis de nombreuses années. L'importance de ces effets pour les prévisions météorologiques et pour l'évolution du climat de la Terre a déjà été démontrée. Pourtant, notre compréhension de ces interactions complexes et multiéchelles reste limitée. Dans cette thèse, le lien entre les caractéristiques macrophysiques des nuages et leur impact sur le rayonnement solaire, et en particulier sur leurs ``effets 3D" (différence entre un calcul 3D et un calcul 1D dans lequel le transport horizontal est négligé), est étudié. Une paramétrisation existante des effets radiatifs 3D des nuages pour les modèles de grande échelle est analysée et évaluée contre des modèles de référence et des observations.A cette fin, des simulations haute résolution de quatre cas de convection de couche limite idéalisée sont réalisées à l'aide du modèle français Méso-NH, ainsi que des simulations perturbées permettant d'analyser l'impact de la résolution, de la taille du domaine, du schéma d'advection et des paramétrisations de la turbulence et de la microphysique sur les caractéristiques des populations nuageuses. Pour simuler à posteriori la propagation du rayonnement dans ces champs nuageux 3D, des outils Monte Carlo inspirés de la communauté de la synthèse d'image sont implémentés sous la forme d'un ensemble de modules génériques formant une bibliothèque libre ; ces modules sont ensuite utilisés pour implémenter des codes de Monte Carlo produisant un temps de calcul insensible à la complexité des scènes nuageuses.Le transfert radiatif 3D est résolu dans l'ensemble des champs nuageux simulés. Le lien entre les caractéristiques nuageuses analysées dans les différentes scènes et leurs effets radiatifs est analysé. Une attention particulière est portée sur les effets radiatifs 3D des nuages, par la réalisation de simulations Monte Carlo 3D et 1D (sous l'approximation de colonnes indépendantes), permettant d'isoler la contribution du transport horizontal sur les flux radiatifs à la surface et au sommet de l'atmosphère. Ces effets 3D sont quantifiés en fonction de l'angle solaire zénithal, et séparés en composantes directe et diffuse. Il apparait que les effets radiatifs 3D sont le résultat d'effets de signe opposé sur les flux direct et diffus, qui ne se compensent pas pour tous les angles solaires. La différence entre l'effet radiatif nuageux total (respectivement, direct) pour des calculs Monte Carlo 3D et 1D intégrés horizontalement et sur un cycle diurne atteint -13 W/m² (respectivement, -45 W/m²) pour des courses solaires correspondant aux hautes latitudes (les effets 3D refroidissent la surface)

Evidence for the 3D radiative effects of boundary-layer clouds from observations of direct and diffuse surface solar fluxes

International audienceNumerical experiments have revealed the importance of horizontal transport of light in the presence of clouds (“3D effects”), with consequences for climate, weather, and solar resource availability predictions. Yet, analysis of 3D effects from observations remain sparse because of the difficulty to isolate the effect of horizontal transport in radiation measurements. In this study, we provide observational evidence for 3D effects based on the direct-diffuse partition of surface solar fluxes. It is compared to outputs from the ecRad radiative transfer scheme run on retrieved cloud profiles. The direct-beam calculation takes careful account of the field-of-view of the pyrheliometer to ensure consistency between observed and modeled direct fluxes. Only the solver that accounts for 3D effects is able to reproduce the observed mean direct-diffuse partition as a function of solar zenith angle and cloud cover, in particular at large solar zenith angles where cloud sides intercept most of the direct beam

Une représentation cohérente du recouvrement et de l'hétérogénéité verticale sous-maille des nuages

International audienceMany global climate models underestimate the cloud cover and overestimate the cloud albedo,especially for low-level clouds. We determine how a correct representation of the vertical struc-ture of clouds can fix part of this bias. We use the 1D McICA framework and focus on low-levelclouds. Using LES results as reference, we propose a method based on exponential-randomoverlap (ERO) that represents both the cloud overlap between layers and the subgrid cloudproperties over several vertical scales, with a single value of the overlap parameter. Startingfrom a coarse vertical grid, representative of atmospheric models, this algorithm is used to gen-erate the vertical profile of the cloud fraction with a finer vertical resolution, or to generate iton the coarse grid but with subgrid heterogeneity and cloud overlap that ensures a correct cloudcover. Doing so we find decorrelation lengths are dependent on the vertical resolution, except ifthe vertical subgrid heterogeneity and interlayer overlap are taken into account coherently. Weconfirm that the frequently used maximum-random overlap leads to a significant error by under-estimating the low-level cloud cover with a relative error of about 50%, that can lead to an errorof SW cloud albedo as big as 70%. Not taking into account the subgrid vertical heterogeneityof clouds can cause a relative error of 20% in brightness, assuming the cloud cover is correct.We also show that the decorrelation lengths used with exponential-random overlap are highlydependent on the vertical resolutions of models and observations, and we show how to addressthis difficulty

Une représentation cohérente du recouvrement et de l'hétérogénéité verticale sous-maille des nuages

International audienceMany global climate models underestimate the cloud cover and overestimate the cloud albedo,especially for low-level clouds. We determine how a correct representation of the vertical struc-ture of clouds can fix part of this bias. We use the 1D McICA framework and focus on low-levelclouds. Using LES results as reference, we propose a method based on exponential-randomoverlap (ERO) that represents both the cloud overlap between layers and the subgrid cloudproperties over several vertical scales, with a single value of the overlap parameter. Startingfrom a coarse vertical grid, representative of atmospheric models, this algorithm is used to gen-erate the vertical profile of the cloud fraction with a finer vertical resolution, or to generate iton the coarse grid but with subgrid heterogeneity and cloud overlap that ensures a correct cloudcover. Doing so we find decorrelation lengths are dependent on the vertical resolution, except ifthe vertical subgrid heterogeneity and interlayer overlap are taken into account coherently. Weconfirm that the frequently used maximum-random overlap leads to a significant error by under-estimating the low-level cloud cover with a relative error of about 50%, that can lead to an errorof SW cloud albedo as big as 70%. Not taking into account the subgrid vertical heterogeneityof clouds can cause a relative error of 20% in brightness, assuming the cloud cover is correct.We also show that the decorrelation lengths used with exponential-random overlap are highlydependent on the vertical resolutions of models and observations, and we show how to addressthis difficulty

A Consistent Representation of Cloud Overlap and Cloud Subgrid Vertical Heterogeneity

International audienceMany global climate models underestimate the cloud cover and overestimate the cloud albedo, especially for low-level clouds. We determine how a correct representation of the vertical structure of clouds can fix part of this bias. We use the 1D McICA framework and focus on low-level clouds. Using Large Eddy Simulations results as reference, we propose a method based on exponential-random overlap that represents the cloud overlap between layers and the subgrid cloud properties over several vertical scales, with a single value of the overlap parameter. Starting from a coarse vertical grid, representative of atmospheric models, this algorithm is used to generate the vertical profile of the cloud fraction with a finer vertical resolution, or to generate it on the coarse grid but with subgrid heterogeneity and cloud overlap that ensures a correct cloud cover. Doing so we find decorrelation lengths are dependent on the vertical resolution, except if the vertical subgrid heterogeneity and interlayer overlap are taken into account coherently. We confirm that the frequently used maximum-random overlap leads to a significant error by underestimating the low-level cloud cover with a relative error of about 50%, that can lead to an error of SW cloud albedo as big as 70%. Not taking into account the subgrid vertical heterogeneity of clouds can cause a relative error of 20% in brightness, assuming the cloud cover is correct

Une représentation cohérente du recouvrement et de l'hétérogénéité verticale sous-maille des nuages

International audienceMany global climate models underestimate the cloud cover and overestimate the cloud albedo,especially for low-level clouds. We determine how a correct representation of the vertical struc-ture of clouds can fix part of this bias. We use the 1D McICA framework and focus on low-levelclouds. Using LES results as reference, we propose a method based on exponential-randomoverlap (ERO) that represents both the cloud overlap between layers and the subgrid cloudproperties over several vertical scales, with a single value of the overlap parameter. Startingfrom a coarse vertical grid, representative of atmospheric models, this algorithm is used to gen-erate the vertical profile of the cloud fraction with a finer vertical resolution, or to generate iton the coarse grid but with subgrid heterogeneity and cloud overlap that ensures a correct cloudcover. Doing so we find decorrelation lengths are dependent on the vertical resolution, except ifthe vertical subgrid heterogeneity and interlayer overlap are taken into account coherently. Weconfirm that the frequently used maximum-random overlap leads to a significant error by under-estimating the low-level cloud cover with a relative error of about 50%, that can lead to an errorof SW cloud albedo as big as 70%. Not taking into account the subgrid vertical heterogeneityof clouds can cause a relative error of 20% in brightness, assuming the cloud cover is correct.We also show that the decorrelation lengths used with exponential-random overlap are highlydependent on the vertical resolutions of models and observations, and we show how to addressthis difficulty

Utilisation d'un code Monte-Carlo spectralement raffiné prenant en compte le recouvrement des nuages pour estimer le refroidissement de la Terre intégré sur une période climatique

The Earth’s radiative cooling is a key driver of climate and due to the complexity of the radia-tive transfer processes, current estimates of this cooling require the development and use of asuite of radiative transfer models of decreasing accuracy when moving from local, instantaneousestimates to estimates over the whole globe and for long periods (decades). Here we addresshow recent advances in non-linear Monte Carlo methods allow a paradigm shift by producing in a single step and at a very low computational cost a completely unbiased estimate of theEarth’s infrared cooling to space on a global scale and for years, while including the most re-fined spectroscopic models of molecular gas energy transitions. We also show it is possible totake exponential-random cloud overlap as well as the vertical subgrid heterogeneity of the cloudfraction into account directly during the Monte Carlo computations. The use of Monte-Carloallows to have access to some interesting diagnostics, as the emission height and the emissionagent. For illustration, we will show the emission altitudes of each atmospheric components andhow these altitudes shift when the greenhouse gas (CO2, H2O, etc.) concentration varies