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

Atmospheric K-feldspar as a potential climate modulating agent through geologic time

Clouds and aerosols have a large, yet highly uncertain, effect on changes in Earth’s climate. A factor of particular note is the role played by ice-nucleating particles, which remains poorly understood. The mineral K-feldspar (Kfs) has recently been shown by a number of independent studies to nucleate ice in mixed-phase cloud conditions far more efficiently than other common minerals. Here, global atmospheric Kfs flux through geologic time is estimated; constrained by records of secular continental crust and biosphere evolution, plate tectonics, volcanism, glaciation, and attendant trends in land surface stability. The analysis reveals that Kfs flux today is at neither extreme of the range estimated across geological time. The present-day Kfs flux, however, is likely to be among the most spatially and temporally variable due to land surface change. The concept of an ice-nucleation efficiency factor that can be calculated from rocks, and also eolian sediments and soils, is proposed. This allows the impact of paleo-atmospheric dust to be estimated through the rock record alongside meteorological and atmospheric composition considerations. With the reasonable assumption that the ice-nucleating properties of Kfs are themselves independent of the background climate state, a better understanding of Kfs flux across a range of spatial and temporal scales will advance understanding of climate processes and interactions

Contributions of Mixed-Phase Clouds to Reduced Arctic Amplification

Earths Arctic is particularly sensitive to global warming. The climate record shows that Arctic changes in surface temperatures far exceed that of the global mean, a phenomenon referred to as Arctic amplification. Here, we show that warming of the Arctic atmosphere causes mixed-phase clouds in the region to contain less ice and more supercooled liquid, which in turn tends to increase their amount and thick- ness, thereby inducing a positive feedback mainly by increasing downward longwave (LW) radiation at the surface. The increased downward LW radiation decreases the positive lapse rate feedback in the Arctic, thus resulting in reduced Arctic amplification. The strength of this feedback depends on the initial mean-state supercooled liquid fraction (SLF) and the ice crystal effective radii. We also show that reduced precipitation rates can result from large mean-state ice effective radii being replaced by relatively more smaller liquid droplets in the cloud phase feedback, despite having high mean-state SLFs, demonstrating the importance of the representation of cloud microphysics in the Arctic

Intercomparison of the cloud water phase among global climate models

Mixed‐phase clouds (clouds that consist of both cloud droplets and ice crystals) are frequently present in the Earth's atmosphere and influence the Earth's energy budget through their radiative properties, which are highly dependent on the cloud water phase. In this study, the phase partitioning of cloud water is compared among six global climate models (GCMs) and with Cloud and Aerosol Lidar with Orthogonal Polarization retrievals. It is found that the GCMs predict vastly different distributions of cloud phase for a given temperature, and none of them are capable of reproducing the spatial distribution or magnitude of the observed phase partitioning. While some GCMs produced liquid water paths comparable to satellite observations, they all failed to preserve sufficient liquid water at mixed‐phase cloud temperatures. Our results suggest that validating GCMs using only the vertically integrated water contents could lead to amplified differences in cloud radiative feedback. The sensitivity of the simulated cloud phase in GCMs to the choice of heterogeneous ice nucleation parameterization is also investigated. The response to a change in ice nucleation is quite different for each GCM, and the implementation of the same ice nucleation parameterization in all models does not reduce the spread in simulated phase among GCMs. The results suggest that processes subsequent to ice nucleation are at least as important in determining phase and should be the focus of future studies aimed at understanding and reducing differences among the models. Key Points Phase partitioning of cloud water in GCMs is investigated Cloud water phase in GCMs is compared to satellite observations Ice nucleation parameterization influence on cloud water phase is investigatedPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106995/1/jgrd51239.pd

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

Econometric Measurement of Earth\u27s Transient Climate Sensitivity

How sensitive is Earth’s climate to a given increase in atmospheric greenhouse gas (GHG) concentrations? This long-standing and fundamental question in climate science was recently analyzed by dynamic panel data methods using extensive spatiotemporal data of global surface temperatures, solar radiation, and GHG concentrations over the last half century to 2010 (Storelvmo et al, 2016). These methods revealed that atmospheric aerosol effects masked approximately one-third of the continental warming due to increasing GHG concentrations over this period, thereby implying greater climate sensitivity to GHGs than previously thought. The present study provides asymptotic theory justifying the use of these methods when there are stochastic process trends in both the global forcing variables, such as GHGs, and station-level trend effects from such sources as local aerosol pollutants. These asymptotics validate con dence interval construction for econometric measures of Earth’s transient climate sensitivity. The methods are applied to observational data and to data generated from three leading global climate models (GCMs) that are sampled spatio-temporally in the same way as the empirical observations. The fi ndings indicate that estimates of transient climate sensitivity produced by these GCMs lie within empirically determined con dence limits but that the GCMs uniformly underestimate the effects of aerosol induced dimming. The analysis shows the potential of econometric methods to calibrate GCM performance against observational data and to reveal the respective sensitivity parameters (GHG and non-GHG related) governing GCM temperature trends

Modelled surface climate response to effusive Icelandic volcanic eruptions: sensitivity to season and size

Effusive, long-lasting volcanic eruptions impact climate through the emission of gases and the subsequent production of aerosols. Previous studies, both modelling and observational, have made efforts to quantify these impacts and untangle them from natural variability. However, due to the scarcity of large and well-observed effusive volcanic eruptions, our understanding remains patchy. Here, we use an Earth system model to systematically investigate the climate response to high-latitude, effusive volcanic eruptions, similar to the 2014–2015 Holuhraun eruption in Iceland, as a function of eruption season and size. The results show that the climate response is regional and strongly modulated by different seasons, exhibiting midlatitude cooling during summer and Arctic warming during winter. Furthermore, as eruptions increase in size in terms of sulfur dioxide emissions, the climate response becomes increasingly insensitive to variations in emission strength, levelling off for eruptions between 20 and 30 times the size of the 2014–2015 Holuhraun eruption. Volcanic eruptions are generally considered to lead to surface cooling, but our results indicate that this is an oversimplification, especially in the Arctic, where warming is found to be the dominant response during autumn and winter.publishedVersio