Global Weather States and Their Properties from Passive and Active Satellite Cloud Retrievals

In this study, the authors apply a clustering algorithm to International Satellite Cloud Climatology Project (ISCCP) cloud optical thickness-cloud top pressure histograms in order to derive weather states (WSs) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global WSs are derived, a combination of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cloud structure retrievals is used to derive the vertical distribution of the cloud field within each WS. Finally, the dynamic environment and the radiative signature of the WSs are derived and their variability is examined. The cluster analysis produces a comprehensive description of global atmospheric conditions through the derivation of 11 WSs, each representing a distinct cloud structure characterized by the horizontal distribution of cloud optical depth and cloud top pressure. Matching those distinct WSs with cloud vertical profiles derived from CloudSat and CALIPSO retrievals shows that the ISCCP WSs exhibit unique distributions of vertical layering that correspond well to the horizontal structure of cloud properties. Matching the derived WSs with vertical velocity measurements shows a normal progression in dynamic regime when moving from the most convective to the least convective WS. Time trend analysis of the WSs shows a sharp increase of the fair-weather WS in the 1990s and a flattening of that increase in the 2000s. The fact that the fair-weather WS is the one with the lowest cloud radiative cooling capability implies that this behavior has contributed excess radiative warming to the global radiative budget during the 1990s

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

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.Les modèles climatiques ont beaucoup progressé pour représenter les nuages. Pourtant la réponse et la rétroaction nuageuse demeure très différente d'un modèle à l'autre, et reste la principale source d'incertitude pour la sensibilité climatique prédite par les modèles de climat, et limite la fiabilité sur les projections du changement climatique dû au forçage anthropique. Il est donc crucial d'améliorer la représentation des processus nuageux dans les modèles climatiques. L'évaluation des nuages nécessite des observations précises. Jusqu'à récemment, des observations de plusieurs aspects fondamentaux des nuages comme la distribution tridimensionnelle des nuages existaient uniquement très grossièrement et obtenus de manière très indirecte par les satellites de télédétection passive (i.e. CERES, ERBE, ScaRab, ISCCP) qui mesurent les flux radiatifs au sommet de l'atmosphère. Les observations A-Train constituent des outils exceptionnels pour caractériser les propriétés nuageuses. L'objet de cette thèse est de tirer profit des observations de l'A-train afin d'évaluer la description des nuages simulée par les modèles climatiques. Nous utilisons le radiomètre CERES pour estimer l'effet radiatif des nuages, les radiomètres PARASOL et MODIS qui mesurent la réflectance, analysée ici comme un proxy de l'épaisseur optique des nuages et le lidar CALIPSO qui fournit des informations précises sur la distribution verticale des nuages. Les données co-localisées et analysées statistiquement constituent une occasion exceptionnelle de contraindre simultanément les propriétés radiatives des nuages et leur distribution tridimensionnelle. Le modèle du climat évalué est le LMDZ ainsi qu'une nouvelle version du modèle en cours de développement, où des nouvelles paramétrisations du bloc couche-limite/convection/nuages est testée. La méthode de comparaison des sorties des modèles climatiques aux grandeurs observées utilise d'une part le simulateur COSP (CFMIP Observation Simulator Package) qui comprend SCOPS, le simulateur lidar et le simulateur PARASOL et d'autre part les jeux des données (CFMIP-OBS) construits pour être compatibles avec les simulateurs. Nous étudions les propriétés nuageuses dans les tropiques par régime de circulation, et en classant les nuages par régions. Une nouvelle méthode a été développée : les observations sont analysées à haute résolution (spatiale et temporelle) au lieu des moyennes mensuelles et saisonnières utilisées habituellement afin de se placer à une échelle aussi proche que possible de celle des processus nuageux. Cette analyse a permis de contraindre les paramétrisations développées pour représenter les nuages et révéler des biais dans les deux versions du LMDZ. Des compensations d'erreurs ont été identifiées (i) sur la distribution verticale des nuages : la couverture nuageuse des nuages hauts et surestimée alors que les nuages bas et moyens sont significativement sous-estimés, (ii) entre la couverture nuageuse et l'épaisseur optique : la couverture nuageuse totale est sous-estimée mais les nuages qui se forment ont une épaisseur optique très élevée ce qui aboutit à une simulation correcte des flux au sommet de l'atmosphère par le modèle

A process oriented characterization of tropical oceanic clouds for climate model evaluation, based on a statistical analysis of daytime A-train observations

International audienceThis paper aims at characterizing how different key cloud properties (cloud fraction, cloud vertical distribution, cloud reflectance, a surrogate of the cloud optical depth) vary as a function of the others over the tropical oceans. The correlations between the different cloud properties are built from 2 years of collocated A-train observations (CALIPSO-GOCCP and MODIS) at a scale close to cloud processes; it results in a characterization of the physical processes in tropical clouds, that can be used to better understand cloud behaviors, and constitute a powerful tool to develop and evaluate cloud parameterizations in climate models. First, we examine a case study of shallow cumulus cloud observed simultaneously by the two sensors (CALIPSO, MODIS), and develop a methodology that allows to build global scale statistics by keeping the separation between clear and cloudy areas at the pixel level (250, 330 m). Then we build statistical instantaneous relationships between the cloud cover, the cloud vertical distribution and the cloud reflectance. The vertical cloud distribution indicates that the optically thin clouds (optical thickness 3.4) are composed of high and mid-level clouds associated with deep convection along the ITCZ and SPCZ and over the warm pool, and by stratocumulus low level clouds located along the East coast of tropical oceans. The cloud properties are analyzed as a function of the large scale circulation regime. Optically thick high clouds are dominant in convective regions (CF > 80 %), while low level clouds with low optical thickness (< 3.5) are present in regimes of subsidence but in convective regimes as well, associated principally to low cloud fractions (CF < 50 %). A focus on low-level clouds allows us to quantify how the cloud optical depth increases with cloud top altitude and with cloud fraction

Evaluation de la description des nuages dans les modèles de climat à partir des observations satellitales de l'A-train

en français : Les modèles climatiques ont beaucoup progressé pour représenter les nuages. Pourtant la réponse et la rétroaction nuageuse demeure très différente d'un modèle à l'autre, et reste la principale source d'incertitude pour la sensibilité climatique prédite par les modèles de climat, et limite la fiabilité sur les projections du changement climatique dû au forçage anthropique. Il est donc crucial d'améliorer la représentation des processus nuageux dans les modèles climatiques. L'évaluation des nuages nécessite des observations précises. Jusqu'à récemment, des observations de plusieurs aspects fondamentaux des nuages comme la distribution tridimensionnelle des nuages existaient uniquement très grossièrement et obtenus de manière très indirecte par les satellites de télédétection passive (i.e. CERES, ERBE, ScaRab, ISCCP) qui mesurent les flux radiatifs au sommet de l'atmosphère. Les observations A-Train constituent des outils exceptionnels pour caractériser les propriétés nuageuses. L'objet de cette thèse est de tirer profit des observations de l'A-train afin d'évaluer la description des nuages simulée par les modèles climatiques. Nous utilisons le radiomètre CERES pour estimer l'effet radiatif des nuages, les radiomètres PARASOL et MODIS qui mesurent la réflectance, analysée ici comme un proxy de l'épaisseur optique des nuages et le lidar CALIPSO qui fournit des informations précises sur la distribution verticale des nuages. Les données co-localisées et analysées statistiquement constituent une occasion exceptionnelle de contraindre simultanément les propriétés radiatives des nuages et leur distribution tridimensionnelle. Le modèle du climat évalué est le LMDZ ainsi qu'une nouvelle version du modèle en cours de développement, où des nouvelles paramétrisations du bloc couche-limite/convection/nuages est testée. La méthode de comparaison des sorties des modèles climatiques aux grandeurs observées utilise d'une part le simulateur COSP (CFMIP Observation Simulator Package) qui comprend SCOPS, le simulateur lidar et le simulateur PARASOL et d'autre part les jeux des données (CFMIP-OBS) construits pour être compatibles avec les simulateurs. Nous étudions les propriétés nuageuses dans les tropiques par régime de circulation, et en classant les nuages par régions. Une nouvelle méthode a été développée : les observations sont analysées à haute résolution (spatiale et temporelle) au lieu des moyennes mensuelles et saisonnières utilisées habituellement afin de se placer à une échelle aussi proche que possible de celle des processus nuageux. Cette analyse a permis de contraindre les paramétrisations développées pour représenter les nuages et révéler des biais dans les deux versions du LMDZ. Des compensations d'erreurs ont été identifiées (i) sur la distribution verticale des nuages : la couverture nuageuse des nuages hauts et surestimée alors que les nuages bas et moyens sont significativement sous-estimés, (ii) entre la couverture nuageuse et l'épaisseur optique : la couverture nuageuse totale est sous-estimée mais les nuages qui se forment ont une épaisseur optique très élevée ce qui aboutit à une simulation correcte des flux au sommet de l'atmosphère par le modèle.en anglais : 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.PALAISEAU-Polytechnique (914772301) / SudocSudocFranceF

Midlatitude Cloud Shifts, Their Primary Link to the Hadley Cell, and Their Diverse Radiative Effects

We investigate the interannual relationship among clouds, their radiative effects, and two key indices of the atmospheric circulation: the latitudinal positions of the Hadley cell edge and the midlatitude jet. From reanalysis data and satellite observations, we find a clear and consistent relationship between the width of the Hadley cell and the high cloud field, statistically significant in nearly all regions and seasons. In contrast, shifts of the midlatitude jet correlate significantly with high cloud shifts only in the North Atlantic region during the winter season. While in that region and season poleward high cloud shifts are associated with shortwave radiative warming, over the Southern Oceans during all seasons they are associated with shortwave radiative cooling. Finally, a trend analysis reveals that poleward high cloud shifts observed over the 1983-2009 period are more likely related to Hadley cell expansion, rather than poleward shifts of the midlatitude jets

The analysis of a complex fire event using multispaceborne observations

This study documents a complex fire event that occurred on October 2016, in Middle East belligerent area. Two fire outbreaks were detected by different spacecraft monitoring instruments on board of TERRA, CALIPSO and AURA Earth Observation missions. Link with local weather conditions was examined using ERA Interim Reanalysis and CAMS datasets. The detection of the event by multiple sensors enabled a detailed characterization of fires and the comparison with different observational data

The analysis of a complex fire event using multispaceborne observations

This study documents a complex fire event that occurred on October 2016, in Middle East belligerent area. Two fire outbreaks were detected by different spacecraft monitoring instruments on board of TERRA, CALIPSO and AURA Earth Observation missions. Link with local weather conditions was examined using ERA Interim Reanalysis and CAMS datasets. The detection of the event by multiple sensors enabled a detailed characterization of fires and the comparison with different observational data

The Potential of GRASP/GARRLiC Retrievals for Dust Aerosol Model Evaluation: Case Study during the PreTECT Campaign

International audienceWe use the Generalized Retrieval of Aerosol Surface Properties algorithm (GRASP) to compare with dust concentration profiles derived from the NMME-DREAM model for a specific dust episode. The GRASP algorithm provides the possibility of deriving columnar and vertically-resolved aerosol properties from a combination of lidar and sun-photometer observations. Herein, we apply GRASP for analysis of a Saharan dust outburst observed during the “PREparatory: does dust TriboElectrification affect our ClimaTe” campaign (PreTECT) that took place at the North coast of Crete, at the Finokalia ACTRIS station. GRASP provides column-averaged and vertically resolved microphysical and optical properties of the particles. The retrieved dust concentration profiles are compared with modeled concentration profiles derived from the NMME-DREAM dust model. To strengthen the results, we use dust concentration profiles from the POlarization-LIdar PHOtometer Networking method (POLIPHON). A strong underestimation of the maximum dust concentration is observed from the NMME-DREAM model. The reported differences between the retrievals and the model indicate a high potential of the GRASP algorithm for future studies of dust model evaluation