On the relationships among cloud cover, mixed-phase partitioning, and planetary albedo in GCMs

In this study, it is shown that CMIP5 global climate models (GCMs) that convert supercooled water to ice at relatively warm temperatures tend to have a greater mean-state cloud fraction and more negative cloud feedback in the middle and high latitude Southern Hemisphere. We investigate possible reasons for these relationships by analyzing the mixed-phase parameterizations in 26 GCMs. The atmospheric temperature where ice and liquid are equally prevalent (T5050) is used to characterize the mixed-phase parameterization in each GCM. Liquid clouds have a higher albedo than ice clouds, so, all else being equal, models with more supercooled liquid water would also have a higher planetary albedo. The lower cloud fraction in these models compensates the higher cloud reflectivity and results in clouds that reflect shortwave radiation (SW) in reasonable agreement with observations, but gives clouds that are too bright and too few. The temperature at which supercooled liquid can remain unfrozen is strongly anti-correlated with cloud fraction in the climate mean state across the model ensemble, but we know of no robust physical mechanism to explain this behavior, especially because this anti-correlation extends through the subtropics. A set of perturbed physics simulations with the Community Atmospheric Model Version 4 (CAM4) shows that, if its temperature-dependent phase partitioning is varied and the critical relative humidity for cloud formation in each model run is also tuned to bring reflected SW into agreement with observations, then cloud fraction increases and liquid water path (LWP) decreases with T5050, as in the CMIP5 ensemble

Combined observational and modeling based study of the aerosol indirect effect

International audienceThe indirect effect of aerosols via liquid clouds is investigated by comparing aerosol and cloud characteristics from the Global Climate Model CAM-Oslo to those observed by the MODIS instrument onboard the TERRA and AQUA satellites http://modis.gsfc.nasa.gov). The comparison is carried out for 15 selected regions ranging from remote and clean to densely populated and polluted. For each region, the regression coefficient and correlation coefficient for the following parameters are calculated: Aerosol Optical Depth vs. Liquid Cloud Optical Thickness, Aerosol Optical Depth vs. Liquid Cloud Droplet Effective Radius and Aerosol Optical Depth vs. Cloud Liquid Water Path. Modeled and observed correlation coefficients and regression coefficients are then compared for a 3-year period starting in January 2001. Additionally, global maps for a number of aerosol and cloud parameters crucial for the understanding of the aerosol indirect effect are compared for the same period of time. Significant differences are found between MODIS and CAM-Oslo both in the regional and global comparison. However, both the model and the observations show a positive correlation between Aerosol Optical Depth and Cloud Optical Depth in practically all regions and for all seasons, in agreement with the current understanding of aerosol-cloud interactions. The correlation between Aerosol Optical Depth and Liquid Cloud Droplet Effective Radius is variable both in the model and the observations. However, the model reports the expected negative correlation more often than the MODIS data. Aerosol Optical Depth is overall positively correlated to Cloud Liquid Water Path both in the model and the observations, with a few regional exceptions

Cirrus Cloud Seeding has Potential to Cool Climate

Cirrus clouds, thin ice clouds in the upper troposphere, have a net warming effect on Earth s climate. Consequently, a reduction in cirrus cloud amount or optical thickness would cool the climate. Recent research indicates that by seeding cirrus clouds with particles that promote ice nucleation, their lifetimes and coverage could be reduced. We have tested this hypothesis in a global climate model with a state-of-the-art representation of cirrus clouds and find that cirrus cloud seeding has the potential to cancel the entire warming caused by human activity from pre-industrial times to present day. However, the desired effect is only obtained for seeding particle concentrations that lie within an optimal range. With lower than optimal particle concentrations, a seeding exercise would have no effect. Moreover, a higher than optimal concentration results in an over-seeding that could have the deleterious effect of prolonging cirrus lifetime and contributing to global warming

Modeling aerosol activation in a tropical, orographic, island setting: Sensitivity tests and comparison with observations

The aerosol, updraft and cloud droplet observations from the 2011 Dominica Experiment (DOMEX) field campaign provide an interesting opportunity to investigate the process of cloud droplet activation in a tropical, orographic, convective setting. This study involves adiabatic parcel model simulations with a state-of-the-art parameterization of droplet activation, which we run with aerosol size distributions and updraft velocities based on DOMEX data. We compare the cloud droplet concentrations predicted by the parameterization with the observations from DOMEX, and run various sensitivity tests to changes in model inputs on the order of their uncertainty, in order to gain insights into what factors are most important in determining the aerosol activation fraction in this setting. Our control simulations overestimated the observed droplet concentrations, especially for the days with strong trade winds, but in most cases these discrepancies could be eliminated by realistic changes in our assumptions. The remaining error could be the result of entrainment of sub-saturated air, precipitation, or advection of pre-existing clouds from upwind. We found strong sensitivities to the mean updraft velocity and to the size distribution and composition of particles in the Aitken mode, the smallest mode including particles below 100 nm. The Aitken mode accounted for 42% to 68% of the simulated droplet concentration in our control simulations, and simulations excluding the Aitken mode underestimated the observed droplet concentrations under realistic assumptions. Droplets from the Aitken mode dominated the changes in the simulated droplet concentrations in our sensitivity tests. The precision of our simulations, and our ability to constrain the role of the Aitken mode, were limited by our lack of knowledge of the composition and size distribution of Aitken mode particles, highlighting the importance of measuring these variables in field campaigns in similar settings

Total aerosol effect: forcing or radiative flux perturbation

Uncertainties in aerosol radiative forcings, especially those associated with clouds, contribute to a large extent to uncertainties in the total anthropogenic forcing. The interaction of aerosols with clouds and radiation introduces feedbacks which can affect the rate of precipitation formation. In former assessments of aerosol radiative forcings, these effects have not been quantified. Also, with global aerosol-climate models simulating interactively aerosols and cloud microphysical properties, a quantification of the aerosol forcings in the traditional way is difficult to define properly. Here we argue that fast feedbacks should be included because they act quickly compared with the time scale of global warming. We show that for different forcing agents (aerosols and greenhouse gases) the radiative forcings as traditionally defined agree rather well with estimates from a method, here referred to as radiative flux perturbations (RFP), that takes these fast feedbacks and interactions into account. Based on our results, we recommend RFP as a valid option to compare different forcing agents, and to compare the effects of particular forcing agents in different models

Global radiative effects of solid fuel cookstove aerosol emissions

We apply the NCAR CAM5-Chem global aerosol–climate model to quantify the net global radiative effects of black and organic carbon aerosols from global and Indian solid fuel cookstove emissions for the year 2010. Our updated assessment accounts for the direct radiative effects, changes to cloud albedo and lifetime (aerosol indirect effect, AIE), impacts on clouds via the vertical temperature profile (semi-direct effect, SDE), and changes in the surface albedo of snow and ice (surface albedo effect). In addition, we provide the first estimate of household solid fuel black carbon emission effects on ice clouds. Anthropogenic emissions are from the IIASA GAINS ECLIPSE V5a inventory. A global dataset of black carbon (BC) and organic aerosol (OA) measurements from surface sites and aerosol optical depth (AOD) from AERONET is used to evaluate the model skill. Compared with observations, the model successfully reproduces the spatial patterns of atmospheric BC and OA concentrations, and agrees with measurements to within a factor of 2. Globally, the simulated AOD agrees well with observations, with normalized mean bias close to zero. However, the model tends to underestimate AOD over India and China by ~ 19 % but overestimate it over Africa by ~ 25 %. Without BC serving as ice nuclei (IN), global and Indian solid fuel cookstove aerosol emissions have a net cooling impact on global climate of −141 ± 4 mW m−2 and −12 ± 4 mW m−2, respectively. The net radiative impacts are dominated by the AIE and SDE mechanisms, which originate from enhanced cloud condensation nuclei concentrations for the formation of liquid and mixed-phase clouds, and a suppression of convective transport of water vapor from the lower troposphere to the upper troposphere/lower stratosphere that in turn leads to reduced ice cloud formation. When BC is allowed to behave as a source of IN, the net global climate impacts of the global and Indian solid fuel cookstove emissions range from −260 to +135 mW m−2 and −33 to +24 mW m−2, with globally averaged values −51 ± 210 and 0.3 ± 29 mW m−2 respectively. The uncertainty range is calculated from sensitivity simulations that alter the maximum freezing efficiency of BC across a plausible range: 0.01, 0.05 and 0.1. BC–ice cloud interactions lead to substantial increases in high cloud (< 500 hPa) fractions. Thus, the net sign of the impacts of carbonaceous aerosols from solid fuel cookstoves on global climate (warming or cooling) remains ambiguous until improved constraints on BC interactions with mixed-phase and ice clouds are available

Radiative forcing of climate: the historical evolution of the radiative forcing concept, the forcing agents and their quantification, and applications

We describe the historical evolution of the conceptualization, formulation, quantification, application and utilization of “radiative forcing (RF, see e.g., IPCC, 1990)” of Earth’s climate. Basic theories of shortwave and long wave radiation were developed through the 19th and 20th centuries, and established the analytical framework for defining and quantifying the perturbations to the Earth’s radiative energy balance by natural and anthropogenic influences. The insight that the Earth’s climate could be radiatively forced by changes in carbon dioxide, first introduced in the 19th century, gained empirical support with sustained observations of the atmospheric concentrations of the gas beginning in 1957. Advances in laboratory and field measurements, theory, instrumentation, computational technology, data and analysis of well-mixed greenhouse gases and the global climate system through the 20th Century enabled the development and formalism of RF; this allowed RF to be related to changes in global-mean surface temperature with the aid of increasingly sophisticated models. This in turn led to RF becoming firmly established as a principal concept in climate science by 1990. The linkage with surface temperature has proven to be the most important application of the RF concept, enabling a simple metric to evaluate the relative climate impacts of different agents. The late 1970s and 1980s saw accelerated developments in quantification including the first assessment of the effect of the forcing due to doubling of carbon dioxide on climate (the “Charney” report, National Research Council, 1979). The concept was subsequently extended to a wide variety of agents beyond well-mixed greenhouse gases (WMGHGs: carbon dioxide, methane, nitrous oxide, and halocarbons) to short-lived species such as ozone. The WMO (1986) and IPCC (1990) international assessments began the important sequence of periodic evaluations and quantifications of the forcings by natural (solar irradiance changes and stratospheric aerosols resulting from volcanic eruptions) and a growing set of anthropogenic agents (WMGHGs, ozone, aerosols, land surface changes, contrails). From 1990s to the present, knowledge and scientific confidence in the radiative agents acting on the climate system has proliferated. The conceptual basis of RF has also evolved as both our understanding of the way radiative forcing drives climate change, and the diversity of the forcing mechanisms, have grown. This has led to the current situation where “Effective Radiative Forcing (ERF, e.g., IPCC, 2013)” is regarded as the preferred practical definition of radiative forcing in order to better capture the link between forcing and global-mean surface temperature change. The use of ERF, however, comes with its own attendant issues, including challenges in its diagnosis from climate models, its applications to small forcings, and blurring of the distinction between rapid climate adjustments (fast responses) and climate feedbacks; this will necessitate further elaboration of its utility in the future. Global climate model simulations of radiative perturbations by various agents have established how the forcings affect other climate variables besides temperature e.g., precipitation. The forcing-response linkage as simulated by models, including the diversity in the spatial distribution of forcings by the different agents, has provided a practical demonstration of the effectiveness of agents in perturbing the radiative energy balance and causing climate changes. The significant advances over the past half-century have established, with very high confidence, that the global-mean ERF due to human activity since preindustrial times is positive (the 2013 IPCC assessment gives a best estimate of 2.3 W m-2, with a range from 1.1 to 3.3 W m-2; 90% confidence interval). Further, except in the immediate aftermath of climatically-significant volcanic eruptions, the net anthropogenic forcing dominates over natural radiative forcing mechanisms. Nevertheless, the substantial remaining uncertainty in the net anthropogenic ERF leads to large uncertainties in estimates of climate sensitivity from observations and in predicting future climate impacts. The uncertainty in the ERF arises principally from the incorporation of the rapid climate adjustments in the formulation, the well-recognized difficulties in characterizing the preindustrial state of the atmosphere, and the incomplete knowledge of the interactions of aerosols with clouds. This uncertainty impairs the quantitative evaluation of climate adaptation and mitigation pathways in the future. A grand challenge in Earth System science lies in continuing to sustain the relatively simple essence of the radiative forcing concept in a form similar to that originally devised, and at the same time improving the quantification of the forcing. This, in turn, demands an accurate, yet increasingly complex and comprehensive, accounting of the relevant processes in the climate system

The Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6): simulation design and preliminary results

International audienceWe present a suite of new climate model experiment designs for the Geoengineering Model Intercompari-son Project (GeoMIP). This set of experiments, named Ge-oMIP6 (to be consistent with the Coupled Model Intercom-parison Project Phase 6), builds on the previous GeoMIP project simulations, and has been expanded to address several further important topics, including key uncertainties in extreme events, the use of geoengineering as part of a portfolio of responses to climate change, and the relatively new idea of cirrus cloud thinning to allow more longwave radiation to escape to space. We discuss experiment designs, as well as the rationale for those designs, showing preliminary results from individual models when available. We also introduce a new feature, called the GeoMIP Testbed, which provides a platform for simulations that will be performed with a few models and subsequently assessed to determine whether the proposed experiment designs will be adopted as core (Tier 1) GeoMIP experiments. This is meant to encourage various stakeholders to propose new targeted experiments that address their key open science questions, with the goal of making GeoMIP more relevant to a broader set of communities

Model intercomparison of indirect aerosol effects

Modeled differences in predicted effects are increasingly used to help quantify the uncertainty of these effects. Here, we examine modeled differences in the aerosol indirect effect in a series of experiments that help to quantify how and why model-predicted aerosol indirect forcing varies between models. The experiments start with an experiment in which aerosol concentrations, the parameterization of droplet concentrations and the autoconversion scheme are all specified and end with an experiment that examines the predicted aerosol indirect forcing when only aerosol sources are specified. Although there are large differences in the predicted liquid water path among the models, the predicted aerosol first indirect effect for the first experiment is rather similar, about −0.6Wm−2 to −0.7Wm−2. Changes to the autoconversion scheme can lead to large changes in the liquid water path of the models and to the response of the liquid water path to changes in aerosols. Adding an autoconversion scheme that depends on the droplet concentration caused a larger (negative) change in net outgoing shortwave radiation compared to the 1st indirect effect, and the increase varied from only 22% to more than a factor of three. The change in net shortwave forcing in the models due to varying the autoconversion scheme depends on the liquid water content of the clouds as well as their predicted droplet concentrations, and both increases and decreases in the net shortwave forcing can occur when autoconversion schemes are changed. The parameterization of cloud fraction within models is not sensitive to the aerosol concentration, and, therefore, the response of the modeled cloud fraction within the present models appears to be smaller than that which would be associated with model “noise”. The prediction of aerosol concentrations, given a fixed set of sources, leads to some of the largest differences in the predicted aerosol indirect radiative forcing among the models, with values of cloud forcing ranging from −0.3Wm−2 to −1.4Wm−2. Thus, this aspect of modeling requires significant improvement in order to improve the prediction of aerosol indirect effects

Energy Budget Constraints on the Time History of Aerosol Forcing and Climate Sensitivity

An observationally-constrained time series of historical aerosol effective radiative forcing (ERF) from 1750 to 2019 is developed in this paper. We find that the time history of aerosol ERFs diagnosed in CMIP6 models exhibits considerable variation and explore how the time history of aerosol forcing influences the probability distributions of present-day aerosol forcing and emergent metrics such as climate sensitivity. Using a simple energy balance model, trained on CMIP6 climate models and constrained by observed near-surface warming and ocean heat uptake, we derive estimates for the historical aerosol forcing. We find 2005-2014 mean aerosol ERF to be -1.1 (-1.8 to -0.5) W m-2 relative to 1750. Assuming recently published historical emissions from fossil fuel and industrial sectors and biomass burning emissions from SSP2-4.5, aerosol ERF in 2019 is -0.9 (-1.5 to -0.4) W m-2. There is a modest recovery in aerosol forcing (+0.025 W m-2 decade-1) between 1980 and 2014. This analysis also gives a 5-95% range of equilibrium climate sensitivity (ECS) of 1.8-5.1°C (best estimate 3.1°C) with a transient climate response (TCR) of 1.2-2.6°C (best estimate 1.8°C)