Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth's ...radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable, and arguable lines of evidence, including modeling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes constrain the forcing from aerosol‐radiation interactions. A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol‐driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction is less clear, and the influence on mixed‐phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to a 68% confidence interval for the total aerosol effective radiative forcing of ‐1.6 to ‐0.6 W m−2, or ‐2.0 to ‐0.4 W m−2 with a 90% likelihood. Those intervals are of similar width to the last Intergovernmental Panel on Climate Change assessment but shifted toward more negative values. The uncertainty will narrow in the future by continuing to critically combine multiple lines of evidence, especially those addressing industrial‐era changes in aerosol sources and aerosol effects on liquid cloud amount and on ice clouds.
Plain Language Summary
Human activities emit into the atmosphere small liquid and solid particles called aerosols. Those aerosols change the energy budget of the Earth and trigger climate changes, by scattering and absorbing solar and terrestrial radiation and playing important roles in the formation of cloud droplets and ice crystals. But because aerosols are much more varied in their chemical composition and much more heterogeneous in their spatial and temporal distributions than greenhouse gases, their perturbation to the energy budget, called radiative forcing, is much more uncertain. This review uses traceable and arguable lines of evidence, supported by aerosol studies published over the past 40 years, to quantify that uncertainty. It finds that there are two chances out of three that aerosols from human activities have increased scattering and absorption of solar radiation by 14% to 29% and cloud droplet number concentration by 5 to 17% in the period 2005–2015 compared to the year 1850. Those increases exert a radiative forcing that offsets between a fifth and a half of the radiative forcing by greenhouse gases. The degree to which human activities affect natural aerosol levels, and the response of clouds, and especially ice clouds, to aerosol perturbations remain particularly uncertain.
Key Points
An assessment of multiple lines of evidence supported by a conceptual model provides ranges for aerosol radiative forcing of climate change
Aerosol effective radiative forcing is assessed to be between ‐1.6 and ‐0.6 W m−2 at the 16–84% confidence level
Although key uncertainties remain, new ways of using observations provide stronger constraints for models
Current climate models generally reflect too little solar radiation over the Southern Ocean, which may be the leading cause of the prevalent sea surface temperature biases in climate models. The ...authors study the role of clouds on the radiation biases in atmosphere-only simulations of the Cloud Feedback Model Intercomparison Project phase 2 (CFMIP2), as clouds have a leading role in controlling the solar radiation absorbed at those latitudes. The authors composite daily data around cyclone centers in the latitude band between 40° and 70°S during the summer. They use cloud property estimates from satellite to classify clouds into different regimes, which allow them to relate the cloud regimes and their associated radiative biases to the meteorological conditions in which they occur. The cloud regimes are defined using cloud properties retrieved using passive sensors and may suffer from the errors associated with this type of retrievals. The authors use information from theCloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)lidar to investigate in more detail the properties of the “midlevel” cloud regime. Most of the model biases occur in the cold-air side of the cyclone composite, and the cyclone composite accounts formost of the climatological error in that latitudinal band. The midlevel regime is the main contributor to reflected shortwave radiation biases.CALIPSOdata show that the midlevel cloud regime is dominated by two main cloud types: cloud with tops actually at midlevel and low-level cloud. Improving the simulation of these cloud types should help reduce the biases in the simulation of the solar radiation budget in the Southern Ocean in climate models.
Previous generations of climate models have been shown to under‐estimate the occurrence of tropical low‐level clouds and to over‐estimate their radiative effects. This study analyzes outputs from ...multiple climate models participating in the Fifth phase of the Coupled Model Intercomparison Project (CMIP5) using the Cloud Feedback Model Intercomparison Project Observations Simulator Package (COSP), and compares them with different satellite data sets. Those include CALIPSO lidar observations, PARASOL mono‐directional reflectances and CERES radiative fluxes at the top of the atmosphere. We show that current state‐of‐the‐art climate models predict overly bright low‐clouds, even for a correct low‐cloud cover. The impact of these biases on the Earth' radiation budget, however, is reduced by compensating errors. Those include the tendency of models to under‐estimate the low‐cloud cover and to over‐estimate the occurrence of mid‐ and high‐clouds above low‐clouds. Finally, we show that models poorly represent the dependence of the vertical structure of low‐clouds on large‐scale environmental conditions. The implications of this ‘too few, too bright low‐cloud problem’ for climate sensitivity and model development are discussed.
Key Points
Low clouds too optically thick; particularly shallow cumulus clouds
Compensating errors: underestimate low‐cloud & overestimate high‐cloud fraction
Relative frequency of stratocumulus & shallow cumulus clouds not captured well
Rising propensity of precipitation extremes and concomitant decline of summer-monsoon rains are amongst the most distinctive hydroclimatic signals that have emerged over South Asia since 1950s. A ...clear understanding of the underlying causes driving these monsoon hydroclimatic signals has remained elusive. Using a state-of-the-art global climate model with high-resolution zooming over South Asia, we demonstrate that a juxtaposition of regional land-use changes, anthropogenic-aerosol forcing and the rapid warming signal of the equatorial Indian Ocean is crucial to produce the observed monsoon weakening in recent decades. Our findings also show that this monsoonal weakening significantly enhances occurrence of localized intense precipitation events, as compared to the global-warming response. A 21st century climate projection using the same high-resolution model indicates persistent decrease of monsoonal rains and prolongation of soil drying. Critical value-additions from this study include (1) realistic simulation of the mean and long-term historical trends in the Indian monsoon rainfall (2) robust attributions of changes in moderate and heavy precipitation events over Central India (3) a 21st century projection of drying trend of the South Asian monsoon. The present findings have profound bearing on the regional water-security, which is already under severe hydrological-stress.
New space‐borne active sensors make it possible to observe the three‐dimensional structure of clouds. Here we use CALIPSO lidar observations together with a lidar simulator to evaluate the cloudiness ...simulated by a climate model: modeled atmospheric profiles are converted to an ensemble of subgrid‐scale attenuated backscatter lidar signals from which a cloud fraction is derived. Except in regions of persistent thick upper‐level clouds, the cloud fraction diagnosed through this procedure is close to that actually predicted by the model. A fractional cloudiness is diagnosed consistently from CALIPSO data at a spatio‐temporal resolution comparable to that of the model. The comparison of the model's cloudiness with CALIPSO data reveals discrepancies more pronounced than in previous model evaluations based on passive observations. This suggests that space‐borne lidar observations constitute a powerful tool for the evaluation of clouds in large‐scale models, including marine boundary‐layer clouds
Clouds are sensitive to changes in both the large-scale circulation and the thermodynamic structure of the atmosphere. In the tropics, temperature changes that occur on seasonal to decadal time ...scales are often associated with circulation changes. Therefore, it is difficult to determine the part of cloud variations that results from a change in the dynamics from the part that may result from the temperature change itself. This study proposes a simple framework to unravel the dynamic and non-dynamic (referred to as thermodynamic) components of the cloud response to climate variations. It is used to analyze the contrasted response, to a prescribed ocean warming, of the tropically-averaged cloud radiative forcing (CRF) simulated by the ECMWF, LMD and UKMO climate models. In each model, the dynamic component largely dominates the CRF response at the regional scale, but this is the thermodynamic component that explains most of the average CRF response to the imposed perturbation. It is shown that this component strongly depends on the behaviour of the low-level clouds that occur in regions of moderate subsidence (e.g. in the trade wind regions). These clouds exhibit a moderate sensitivity to temperature changes, but this is mostly their huge statistical weight that explains their large influence on the tropical radiation budget. Several propositions are made for assessing the sensitivity of clouds to changes in temperature and in large-scale motions using satellite observations and meteorological analyses on the one hand, and mesoscale models on the other hand.
The evaluation of key cloud properties such as cloud cover, vertical profile and optical depth as well as the analysis of their intercorrelation lead to greater confidence in climate change ...projections. In addition, the comparison between observations and parameterizations of clouds in climate models is improved by using collocated and instantaneous data of cloud properties. Simultaneous and independent observations of the cloud cover and its three-dimensional structure at high spatial and temporal resolutions are made possible by the new space-borne multi-instruments observations collected with the A-train. The cloud cover and its vertical structure observed by CALIPSO and the visible directional reflectance (a surrogate for the cloud optical depth) observed by PARASOL, are used to evaluate the representation of cloudiness in two versions of the atmospheric component of the IPSL-CM5 climate model (LMDZ5). A model-to-satellite approach, applying the CFMIP Observation Simulation Package (COSP), is used to allow a quantitative comparison between model results and observations. The representation of clouds in the two model versions is first evaluated using monthly mean data. This classical approach reveals biases of different magnitudes in the two model versions. These biases consist of (1) an underestimation of cloud cover associated to an overestimation of cloud optical depth, (2) an underestimation of low- and mid-level tropical clouds and (3) an overestimation of high clouds. The difference in the magnitude of these biases between the two model versions clearly highlights the improvement of the amount of boundary layer clouds, the improvement of the properties of high-level clouds, and the improvement of the simulated mid-level clouds in the tropics in LMDZ5B compared to LMDZ5A, due to the new convective, boundary layer, and cloud parametrizations implemented in LMDZ5B. The correlation between instantaneous cloud properties allows for a process-oriented evaluation of tropical oceanic clouds. This process-oriented evaluation shows that the cloud population characterized by intermediate values of cloud cover and cloud reflectance can be split in two groups of clouds when using monthly mean values of cloud cover and cloud reflectance: one group with low to intermediate values of the cloud cover, and one group with cloud cover close to one. The precise determination of cloud height allows us to focus on specific types of clouds (i.e. boundary layer clouds, high clouds, low-level clouds with no clouds above). For low-level clouds over the tropical oceans, the relationship between instantaneous values of the cloud cover and of the cloud reflectance reveals a major bias in the simulated liquid water content for both model versions. The origin of this bias is identified and possible improvements, such as considering the sub-grid heterogeneity of cloud properties, are investigated using sensitivity experiments. In summary, the analysis of the relationship between different instantaneous and collocated variables allows for process-oriented evaluations. These evaluations may in turn help to improve model parameterizations, and may also help to bridge the gap between model evaluation and model development.
COSP Bodas-Salcedo, A.; Webb, M. J.; Bony, S. ...
Bulletin of the American Meteorological Society,
08/2011, Letnik:
92, Številka:
8
Journal Article
Recenzirano
Odprti dostop
Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) ...Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibility of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. In this article we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.
Byline: G. Krinner (1), O. Magand (1), I. Simmonds (2), C. Genthon (1), J. -L. Dufresne (3) The aim of this work is to assess potential future Antarctic surface mass balance changes, the underlying ...mechanisms, and the impact of these changes on global sea level. To this end, this paper presents simulations of the Antarctic climate for the end of the twentieth and twenty-first centuries. The simulations were carried out with a stretched-grid atmospheric general circulation model, allowing for high horizontal resolution (60 km) over Antarctica. It is found that the simulated present-day surface mass balance is skilful on continental scales. Errors on regional scales are moderate when observed sea surface conditions are used; more significant regional biases appear when sea surface conditions from a coupled model run are prescribed. The simulated Antarctic surface mass balance increases by 32 mm water equivalent per year in the next century, corresponding to a sea level decrease of 1.2 mm year.sup.-1 by the end of the twenty-first century. This surface mass balance increase is largely due to precipitation changes, while changes in snow melt and turbulent latent surface fluxes are weak. The temperature increase leads to an increased moisture transport towards the interior of the continent because of the higher moisture holding capacity of warmer air, but changes in atmospheric dynamics, in particular off the Antarctic coast, regionally modulate this signal. Author Affiliation: (1) LGGE, CNRS/UJF Grenoble, BP 96, 38402, St Martin d'Heres Cedex, France (2) School of Earth Sciences, University of Melbourne, Parkville, Victoria , 3052, Australia (3) LMD/IPSL, CNRS/Universite Paris 6, Boite 99, 75252, Paris Cedex 05, France Article History: Registration Date: 06/07/2006 Received Date: 28/09/2005 Accepted Date: 03/07/2006 Online Date: 09/08/2006
This article presents the GCM‐Oriented Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP) designed to evaluate the cloudiness simulated by general ...circulation models (GCMs). For this purpose, Cloud‐Aerosol Lidar with Orthogonal Polarization L1 data are processed following the same steps as in a lidar simulator used to diagnose the model cloud cover that CALIPSO would observe from space if the satellite was flying above an atmosphere similar to that predicted by the GCM. Instantaneous profiles of the lidar scattering ratio (SR) are first computed at the highest horizontal resolution of the data but at the vertical resolution typical of current GCMs, and then cloud diagnostics are inferred from these profiles: vertical distribution of cloud fraction, horizontal distribution of low, middle, high, and total cloud fractions, instantaneous SR profiles, and SR histograms as a function of height. Results are presented for different seasons (January–March 2007–2008 and June–August 2006–2008), and their sensitivity to parameters of the lidar simulator is investigated. It is shown that the choice of the vertical resolution and of the SR threshold value used for cloud detection can modify the cloud fraction by up to 0.20, particularly in the shallow cumulus regions. The tropical marine low‐level cloud fraction is larger during nighttime (by up to 0.15) than during daytime. The histograms of SR characterize the cloud types encountered in different regions. The GOCCP high‐level cloud amount is similar to that from the TIROS Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). The low‐level and middle‐level cloud fractions are larger than those derived from passive remote sensing (International Satellite Cloud Climatology Project, Moderate‐Resolution Imaging Spectroradiometer–Cloud and Earth Radiant Energy System Polarization and Directionality of Earth Reflectances, TOVS Path B, AIRS–Laboratoire de Météorologie Dynamique) because the latter only provide information on the uppermost cloud layer.
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