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.

Abstract. In this study we use a new dust product developed using CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) observations and EAR-LINET (European Aerosol Research Lidar Network) measurements and methods to provide a 3-D multiyear analysis on the evolution of Saharan dust over North Africa and Europe. The product uses a CALIPSO L2 backscatter product corrected with a depolarization-based method to separate pure dust in external aerosol mixtures and a Saharan dust lidar ratio (LR) based on long-term EARLINET measurements to calculate the dust extinction profiles. The methodology is applied on a 9-year CALIPSO dataset (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) and the results are analyzed here to reveal for the first time the 3-D dust evolution and the seasonal patterns of dust over its transportation paths from the Sahara towards the Mediterranean and Continental Europe. During spring, the spatial distribution of dust shows a uniform pattern over the Sahara desert. The dust transport over the Mediterranean Sea results in mean dust optical depth (DOD) values up to 0.1. During summer, the dust activity is mostly shifted to the western part of the desert where mean DOD near the source is up to 0.6. Elevated dust plumes with mean extinction values between 10 and 75 Mm −1 are observed throughout the year at various heights between 2 and 6 km, extending up to latitudes of 40 • N. Dust advection is identified even at latitudes of about 60 • N, but this is due to rare events of episodic nature. Dust plumes of high DOD are also observed above the Balkans during the winter period and above northwest Europe during autumn at heights between 2 and 4 km, reaching mean extinction values up to 50 Mm −1 . The dataset is considered unique with respect to its potential applications, including the evaluation of dust transport models and the estimation of cloud condensation nuclei (CCN) and ice nuclei (IN) concentration profiles. Finally, the product can be used to study dust dynamics during transportation, since it is capable of revealing even fine dynamical features such as the particle uplifting and deposition on European mountainous ridges such as the Alps and Carpathian Mountains.

6The evaluation of key cloud properties such as cloud cover, vertical profile and optical depth as well as the analysis of their 7 intercorrelation lead to greater confidence in climate change projections. In addition, the use of collocated and instantaneous 8 data facilitates the links between observations and parameterizations of clouds in climate models. 9New space-borne multi-instruments observations collected with the A-train make simultaneous and independent 10 observations of the cloud cover and its three-dimensional structure at high spatial and temporal resolutions possible. The 11 CALIPSO cloud cover and vertical structure and the PARASOL visible directional reflectance, which is a surrogate for the

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.

Several studies have shown that most climate models underestimate cloud cover and overestimate cloud reflectivity, particularly for the tropical low‐level clouds. Here, we analyze the characteristics of low‐level tropical marine clouds simulated by six climate models, which provided COSP output within the CMIP6 project. CALIPSO lidar observations and PARASOL mono‐directional reflectance are used for model evaluation. It is found that the “too few, too bright” bias is still present for these models. The reflectance is particularly overestimated when cloud cover is low. Models do not simulate any optically thin clouds. They fail to reproduce the increasing cloud optical depth with increasing lower tropospheric stability as observed. These results suggest that most models do not sufficiently account for the effect of the small‐scale spatial heterogeneity in cloud properties or the variety of cloud types at the grid scale that is observed.

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 < 1.5) dominate the boundary layer over the trade wind regions. Optically thick 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

The cloud parameterizations of the LMDZ6A climate model (the atmospheric component of the IPSL-CM6 Earth system model) are entirely described, and the global cloud distribution and cloud radiative effects are evaluated against the CALIPSO-CloudSat and CERES observations. The cloud parameterizations in recent versions of LMDZ favor an object-oriented approach for convection, with two distinct parameterizations for shallow and deep convection and a coupling between convection and cloud description through the specification of the subgrid-scale distribution of water. Compared to the previous version of the model (LMDZ5A), LMDZ6A better represents the low-level cloud distribution in the tropical belt, and low-level cloud reflectance and cover are closer to the PARASOL and CALIPSO-GOCCP observations. Mid-level clouds, which were mostly missing in LMDZ5A, are now better represented globally. The distribution of cloud liquid and ice in mixed-phase clouds is also in better agreement with the observations. Among identified deficiencies, low-level cloud covers are too high in mid-latitude to high-latitude regions, and high-level cloud covers are biased low globally. However, the cloud global distribution is significantly improved, and progress has been made in the tuning of the model, resulting in a radiative balance in close agreement with the CERES observations. Improved tuning also revealed structural biases in LMDZ6A, which are currently being addressed through a series of new physical and radiative parameterizations for the next version of LMDZ.

Abstract. The CFMIP Diagnostic Codes Catalogue assembles cloud metrics, diagnostics and methodologies, together with programs to diagnose them from general circulation model (GCM) outputs written by various members of the CFMIP community. This aims to facilitate use of the diagnostics by the wider community studying climate and climate change. This paper describes the diagnostics and metrics which are currently in the catalogue, together with examples of their application to model evaluation studies and a summary of some of the insights these diagnostics have provided into the main shortcomings in current GCMs. Analysis of outputs from CFMIP and CMIP6 experiments will also be facilitated by the sharing of diagnostic codes via this catalogue.Any code which implements diagnostics relevant to analysing clouds -including cloud-circulation interactions and the contribution of clouds to estimates of climate sensitivity in models -and which is documented in peer-reviewed studies, can be included in the catalogue. We very much welcome additional contributions to further support community analysis of CMIP6 outputs.