Aerosol–cloud interactions are considered a key uncertainty in our understanding of climate change (Boucher et al., 2013). Knowledge of the global abundance of cloud condensation nuclei (CCN) is ...fundamental to determine the strength of the anthropogenic climate perturbation. Direct measurements are limited and sample only a very small fraction of the globe so that remote sensing from satellites and ground-based instruments is widely used as a proxy for cloud condensation nuclei (Nakajima et al., 2001; Andreae, 2009; Clarke and Kapustin, 2010; Boucher et al., 2013). However, the underlying assumptions cannot be robustly tested with the small number of measurements available so that no reliable global estimate of cloud condensation nuclei exists. This study overcomes this limitation using a self-consistent global model (ECHAM-HAM) of aerosol radiative properties and cloud condensation nuclei. An analysis of the correlation of simulated aerosol radiative properties and cloud condensation nuclei reveals that common assumptions about their relationships are violated for a significant fraction of the globe: 71 % of the area of the globe shows correlation coefficients between CCN0.2 % at cloud base and aerosol optical depth (AOD) below 0.5, i.e. AOD variability explains only 25 % of the CCN variance. This has significant implications for satellite based studies of aerosol–cloud interactions. The findings also suggest that vertically resolved remote-sensing techniques, such as satellite-based high spectral resolution lidars, have a large potential for global monitoring of cloud condensation nuclei.
Previous global satellite studies into the indirect aerosol effect have relied on determining the sensitivity of derived Cloud Droplet Number Concentration (Nd) to co‐located Aerosol Optical Depth ...(AOD). These studies generally find a positive Nd sensitivity to AOD changes over ocean, but some find a negative sensitivity over land, in contrast to that predicted by models and theory. Here we investigate the Ndsensitivity to AOD in different cloud regimes, determined using a k‐means clustering process on retrieved cloud properties. We find the strongest positive Nd sensitivity in the stratiform regimes over both land and ocean, providing the majority of the total sensitivity. The negative sensitivity previously observed over land is generated by the low cloud fraction regimes, suggesting that it is due to the difficulty of retrieving Nd at low cloud fractions. When considering a mean sensitivity, weighted by liquid cloud fraction to account for sampling biases, we find an increased sensitivity over land, in some regions becoming positive. This highlights the importance of regime based analysis when studying aerosol indirect effects.
Key Points
Sensitivity of cloud droplet number to aerosol optical depth differs by regime
The negative sensitivity observed over land is from low cloud fraction regimes
High cloud fraction regimes are the largest proportion of the total sensitivity
Abstract
Estimates of the anthropogenic effective radiative forcing (ERF) trend have increased by 50% since 2000 (from +0.4 W m
−2
decade
−1
in 2000–09 to +0.6 W m
−2
decade
−1
in 2010–19), the ...majority of which is driven by changes in the aerosol ERF trend, as a result of aerosol emissions reductions. Here we study the extent to which observations of the climate system agree with these ERF assumptions. We use a large ERF ensemble from the IPCC’s Sixth Assessment Report (AR6) to attribute the anthropogenic contributions to global mean surface temperature (GMST), top-of-atmosphere radiative flux, and we use aerosol optical depth observations. The GMST trend has increased from +0.18°C decade
−1
in 2000–09 to +0.35°C decade
−1
in 2010–19, coinciding with the anthropogenic warming trend rising from +0.19°C decade
−1
in 2000–09 to +0.24°C decade
−1
in 2010–19. This, as well as observed trends in top-of-atmosphere radiative fluxes and aerosol optical depths, supports the claim of an aerosol-induced temporary acceleration in the rate of warming. However, all three observation datasets additionally suggest that smaller aerosol ERF trend changes are compatible with observations since 2000, since radiative flux and GMST trends are significantly influenced by internal variability over this period. A
zero-trend-change
aerosol ERF scenario results in a much smaller anthropogenic warming acceleration since 2000 but is poorly represented in AR6’s ERF ensemble. Short-term ERF trends are difficult to verify using observations, so caution is required in predictions or policy judgments that depend on them, such as estimates of current anthropogenic warming trend, and the time remaining to, or the outstanding carbon budget consistent with, 1.5°C warming. Further systematic research focused on quantifying trends and early identification of acceleration or deceleration is required.
The impact of aerosols on ice- and mixed-phase processes in deep convective
clouds remains highly uncertain, and the wide range of interacting
microphysical processes is still poorly understood. To ...understand these
processes, we analyse diagnostic output of all individual microphysical
process rates for two bulk microphysics schemes in the Weather and Research
Forecasting model (WRF). We investigate the response of individual processes
to changes in aerosol conditions and the propagation of perturbations through
the microphysics all the way to the macrophysical development of the
convective clouds. We perform simulations for two different cases of
idealised supercells using two double-moment bulk microphysics
schemes and a bin microphysics scheme. The simulations cover a comprehensive
range of values for cloud droplet number concentration (CDNC) and cloud
condensation nuclei (CCN) concentration as a proxy for aerosol effects on
convective clouds. We have developed a new cloud tracking algorithm to
analyse the morphology and time evolution of individually tracked convective
cells in the simulations and their response to the aerosol perturbations. This analysis confirms an expected decrease in warm rain formation processes
due to autoconversion and accretion for more polluted conditions. There is no
evidence of a significant increase in the total amount of latent heat, as
changes to the individual components of the integrated latent heating in the
cloud compensate each other. The latent heating from freezing and riming
processes is shifted to a higher altitude in the cloud, but there is no
significant change to the integrated latent heat from freezing. Different
choices in the treatment of deposition and sublimation processes between the
microphysics schemes lead to strong differences including feedbacks onto
condensation and evaporation. These changes in the microphysical processes
explain some of the response in cloud mass and the altitude of the cloud
centre of gravity. However, there remain some contrasts in the development of
the bulk cloud parameters between the microphysics schemes and the two
simulated cases.
Uncertainty in the representation of biomass burning (BB) aerosol composition and optical properties in climate models contributes to a range in modeled aerosol effects on incoming solar radiation. ...Depending on the model, the top-of-the-atmosphere BB aerosol effect can range from cooling to warming. By relating aerosol absorption relative to extinction and carbonaceous aerosol composition from 12 observational datasets to nine state-of-the-art Earth system models/chemical transport models, we identify varying degrees of overestimation in BB aerosol absorptivity by these models. Modifications to BB aerosol refractive index, size, and mixing state improve the Community Atmosphere Model version 5 (CAM5) agreement with observations, leading to a global change in BB direct radiative effect of -0.07 W m
, and regional changes of -2 W m
(Africa) and -0.5 W m
(South America/Temperate). Our findings suggest that current modeled BB contributes less to warming than previously thought, largely due to treatments of aerosol mixing state.
The discontinuous spatio-temporal sampling of observations has an impact when using them to construct climatologies or evaluate models. Here we provide estimates of this so-called representation ...error for a range of timescales and length scales (semi-annually down to sub-daily, 300 to 50 km) and show that even after substantial averaging of data significant representation errors may remain, larger than typical measurement errors. Our study considers a variety of observations: ground-site or in situ remote sensing (PM2. 5, black carbon mass or number concentrations), satellite remote sensing with imagers or lidar (extinction). We show that observational coverage (a measure of how dense the spatio-temporal sampling of the observations is) is not an effective metric to limit representation errors. Different strategies to construct monthly gridded satellite L3 data are assessed and temporal averaging of spatially aggregated observations (super-observations) is found to be the best, although it still allows for significant representation errors. However, temporal collocation of data (possible when observations are compared to model data or other observations), combined with temporal averaging, can be very effective at reducing representation errors. We also show that ground-based and wide-swath imager satellite remote sensing data give rise to similar representation errors, although their observational sampling is different. Finally, emission sources and orography can lead to representation errors that are very hard to reduce, even with substantial temporal averaging.
The cloud droplet number concentration (Nd) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol‐cloud interactions. ...Current standard satellite retrievals do not operationally provide Nd, but it can be inferred from retrievals of cloud optical depth (τc) cloud droplet effective radius (re) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel‐level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. Nd uncertainty is dominated by errors in re, and therefore, improvements in re retrievals would greatly improve the quality of the Nd retrievals. Recommendations are made for how this might be achieved. Some existing Nd data sets are compared and discussed, and best practices for the use of Nd data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative Nd estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high‐quality ground‐based observations are examined.
Plain Language Summary
Clouds have a very large influence on weather and climate. It is thus a prime task for satellite‐ and ground‐based observations to measure clouds. For satellites and many other instruments this is done by remote sensing—radiation is measured, and knowledge about clouds is inferred. Liquid water clouds consist of numerous droplets of order of 10 μm in size. A key quantity that describes clouds is the number of droplets in a given volume or the droplet number concentration. However, satellite observations of droplet number concentration are only emerging, and the quality of these observations is poorly known. This review fulfills two tasks, namely, (1) to quantify how uncertain the current way to observe droplet number concentrations from satellite is and (2) to propose ways toward better approaches. It is concluded that the current way to obtain cloud droplet number concentration works for homogeneous stratus and stratocumulus clouds, with, however, a substantial error of around 50%. For cumulus clouds the observations are substantially worse. New avenues that are proposed for a better estimate of cloud droplet concentration exploit instruments that emit light (lidar) or microwaves (radar), and measure the reflected signal, or explore the polarization of light induced by clouds.
Key Points
Satellite cloud droplet concentration uncertainties of 78% for pixel‐level retrievals and 54% for 1 by 1 degree retrievals are estimated
The effective radius retrieval is the most important aspect for improvement, and more in situ evaluation is needed
Potential improvements using passive and active satellite, and ground‐based instruments are discussed
Current climate models cannot resolve individual convective clouds, and hence parameterizations are needed. The primary goal of convective parameterization is to represent the bulk impact of ...convection on the gridbox-scale variables. Spectral convective parameterizations also aim to represent the key features of the subgrid-scale convective cloud field such as cloud-top-height distribution and in-cloud vertical velocities in addition to precipitation rates. Ground-based radar retrievals of these quantities have been made available at Darwin, Australia, permitting direct comparisons of internal parameterization variables and providing new observational references for further model development.
A spectral convective parameterization the convective cloud field model (CCFM) is discussed, and its internal equation of motion is improved. Results from the ECHAM–HAM model in single-column mode using the CCFM and the bulk mass flux Tiedtke–Nordeng scheme are compared with the radar retrievals at Darwin. The CCFM is found to outperform the Tiedtke–Nordeng scheme for cloud-top-height and precipitation-rate distributions. Radar observations are further used to propose a modified CCFM configuration with an aerodynamic drag and reduced entrainment parameter, further improving both the convective cloud-top-height distribution (important for large-scale impact of convection) and the in-cloud vertical velocities (important for aerosol activation).
This study provides a new development in the CCFM, improving the representation of convective cloud spectrum characteristics observed in Darwin. This is a step toward an improved representation of convection and ultimately of aerosol effects on convection. It also shows how long-term radar observations of convective cloud properties can help constrain parameters of convective parameterization schemes.
The south-eastern Atlantic Ocean (SEA) is semi-permanently covered by one of
the most extensive stratocumulus cloud decks on the planet and experiences
about one-third of the global biomass burning ...emissions from the southern
Africa savannah region during the fire season. To get a better understanding
of the impact of these biomass burning aerosols on clouds and the radiation
balance over the SEA, the latest generation of the UK Earth System Model
(UKESM1) is employed. Measurements from the CLARIFY and ORACLES flight
campaigns are used to evaluate the model, demonstrating that the model has
good skill in reproducing the biomass burning plume. To investigate the
underlying mechanisms in detail, the effects of biomass burning aerosols on
the clouds are decomposed into radiative effects (via absorption and
scattering) and microphysical effects (via perturbation of cloud
condensation nuclei – CCN – and cloud microphysical processes).
July–August means are used to characterize aerosols, clouds, and the
radiation balance during the fire season. Results show that around 65 % of CCN
at 0.2 % supersaturation in the SEA can be attributed to biomass burning.
The absorption effect of biomass burning aerosols is the most significant on clouds and radiation. Near the continent, it increases the
supersaturation diagnosed by the activation scheme, while further from the
continent it reduces the altitude of the supersaturation. As a result, the
cloud droplet number concentration responds with a similar pattern to the
absorption effect of biomass burning aerosols. The microphysical effect,
however, decreases the supersaturation and increases the cloud droplet
concentration over the ocean, although this change is relatively small. The
liquid water path is also significantly increased over the SEA (mainly
caused by the absorption effect of biomass burning aerosols) when biomass
burning aerosols are above the stratocumulus cloud deck. The microphysical
pathways lead to a slight increase in the liquid water path over the ocean.
These changes in cloud properties indicate the significant role of biomass
burning aerosols for clouds in this region. Among the effects of biomass
burning aerosols on the radiation balance, the semi-direct radiative effects
(rapid adjustments induced by the radiative effects of biomass burning aerosols)
have a dominant cooling impact over the SEA, which offset the warming direct
radiative effect (radiative forcing from biomass burning aerosol–radiation
interactions) and lead to an overall net cooling radiative effect in the SEA.
However, the magnitude and the sign of the semi-direct effects are sensitive
to the relative location of biomass burning aerosols and clouds, reflecting
the critical task of the accurate modelling of the biomass burning plume and
clouds in this region.
An aerosol model (M7) designed to be coupled to general circulation models (GCM) and chemistry transport models (CTM) is described. In M7 the aerosol population is divided into two types of ...particles: mixed, or water‐soluble particles, and insoluble particles. The particles are represented by seven classes, using a “pseudomodal” approach. Four classes are for the mixed particles representing nucleation, Aitken, accumulation, and coarse mode, and three are for the insoluble (Aitken, accumulation, and coarse mode). The components considered are mineral dust, black carbon (BC) and primary organic carbon (OC), sulfate, and sea salt. The aerosol dynamic processes in M7 include nucleation, coagulation, and condensation of sulfuric acid. Mixed particles are formed from insoluble particles by coagulation and condensation. The integration scheme is computationally very efficient. The model has been tested against the analytical solution and a sectional model for the formation of SO4/BC mixed particles, evaluating the mixing by condensation and coagulation. Furthermore, M7 has been run in free tropospheric conditions and compared to aircraft observations. M7 has proven to be accurate and fast enough to be included in a GCM or CTM.
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