Skip to Main content Skip to Navigation
Theses

EVALUATION DE LA DESCRIPTION DES NUAGES DANS LES MODÈLES DE CLIMAT À PARTIR DES OBSERVATIONS SATELLITALES DE L'A-TRAIN

Abstract : Climate models have progressed a lot in the representation of clouds. Nevertheless the cloud response and the cloud feedback remain very different from one model to another, and they still constitute a major limitation to the reliability of climate change projections due to anthropogenic forcing. It is therefore imperative to improve the representation of cloud processes in models. The evaluation of clouds description requires accurate observations. Until recently, observations of several fundamental aspects of the cloudiness as the three-dimensional distribution of the cloud cover existed only very roughly and has been largely indirect, based on passive remote sensing satellites (e.g. CERES, ERBE, ScaRab, ISCCP) which measure the TOA radiative fluxes. The A-train observations constitute exceptional tools to characterize the cloud properties. The goal of this thesis is to use the A-train observations to better assess the cloud description simulated by GCMs. We use the radiometer CERES to estimate the radiative effect of clouds, the radiometers MODIS and PARASOL that measure reflectance values which are analysed as a proxy of the clouds optical thickness, and the lidar CALIPSO that provides accurate information on the vertical distribution of clouds. The data are colocalised and analysed statistically and they constitute a unique opportunity to constrain simultaneously the radiative properties of clouds with their three-dimensional distribution. The LMDZ model is evaluated and a new version of the model under development, where new parameterisations of the block boundary layer/convection/clouds is also tested. The method for comparing the model's outputs with the observations uses on the one hand the COSP simulator (CFMIP Observation Simulator Package) which includes SCOPS, the lidar simulator and PARASOL simulator and on the other hand the CFMIP-OBS observational dataset, built to be compatible with the simulators. The analysis is done in classifying clouds in function of the circulation regime in the tropics, and according to geographical areas. A new method has been developed to analyse observations: those are examined statistically at high resolution (both in space and time), instead of monthly and seasonal means usually used, to focus on a scale as close as possible to the cloud processes one. This analysis has allowed constraining the parameterisations developed to represent the clouds and revealing the biases in the two versions of LMDZ. Errors' compensations were identified (i) on the cloud vertical distribution: the high cloud cover is overestimated whereas low and mid level clouds are significantly underestimated, (ii) between the cloud cover and the optical depth: overall the global cloud cover is underestimated but the clouds that form have a too high optical depth which results in a correct simulation of the TOA fluxes by the model.
Keywords : clouds nuages A-Train GCM
Complete list of metadatas

Cited literature [92 references]  Display  Hide  Download

https://pastel.archives-ouvertes.fr/pastel-00556418
Contributor : Dimitra Konsta <>
Submitted on : Sunday, January 16, 2011 - 11:06:06 AM
Last modification on : Tuesday, September 22, 2020 - 3:50:17 AM
Long-term archiving on: : Sunday, April 17, 2011 - 2:36:28 AM

Identifiers

  • HAL Id : pastel-00556418, version 1

Citation

Dimitra Konsta. EVALUATION DE LA DESCRIPTION DES NUAGES DANS LES MODÈLES DE CLIMAT À PARTIR DES OBSERVATIONS SATELLITALES DE L'A-TRAIN. Climatologie. Ecole Polytechnique X, 2010. Français. ⟨pastel-00556418⟩

Share

Metrics

Record views

794

Files downloads

1995