Aerosol‐cloud interactions (ACI) represent a significant source of forcing uncertainty in global climate models (GCMs). Estimates of radiative forcing due to ACI in Fifth Assessment Report range from ...−0.5 to −2.5 W m−2. A portion of this uncertainty is related to the first indirect, or Twomey, effect whereby aerosols act as nuclei for cloud droplets to condense upon. At constant liquid water content this increases the number of cloud droplets (Nd) and thus increases the cloud albedo. In this study we use remote‐sensing estimates of Nd within stratocumulus regions in combination with state‐of‐the‐art aerosol reanalysis from Modern‐Era Retrospective Analysis for Research and Applications version 2 (MERRA2) to diagnose how aerosols affect Nd. As in previous studies, Nd is related to sulfate mass through a power law relationship. The slope of the log‐log relationship between Nd and SO4 in maritime stratocumulus is found to be 0.31, which is similar to the range of 0.2–0.8 from previous in situ studies and remote‐sensing studies in the pristine Southern Ocean. Using preindustrial emissions models, the change in Nd between preindustrial and present day is estimated. Nd is inferred to have more than tripled in some regions. Cloud properties from Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate the radiative forcing due to this change in Nd. The Twomey effect operating in isolation is estimated to create a radiative forcing of −0.97 ± 0.23 W m−2 relative to the preindustrial era.
Key Points
Variability in MODIS Nd is well explained by MERRA aerosol mass concentration
AeroCom aerosol climatologies also appear to explain MODIS Nd
Doubling of Nd is inferred over heavily industrialized areas
Representing large-scale co-variability between variables related to aerosols, clouds and radiation is one of many aspects of agreement with observations desirable for a climate model. In this study ...such relations are investigated in terms of temporal correlations on monthly mean scale, to identify points of agreement and disagreement with observations. Ten regions with different meteorological characteristics and aerosol signatures are studied and correlation matrices for the selected regions offer an overview of model ability to represent present day climate variability. Global climate models with different levels of detail and sophistication in their representation of aerosols and clouds are compared with satellite observations and reanalysis assimilating meteorological fields as well as aerosol optical depth from observations. One example of how the correlation comparison can guide model evaluation and development is the often studied relation between cloud droplet number and water content. Reanalysis, with no parameterized aerosol–cloud coupling, shows weaker correlations than observations, indicating that microphysical couplings between cloud droplet number and water content are not negligible for the co-variations emerging on larger scale. These observed correlations are, however, not in agreement with those expected from dominance of the underlying microphysical aerosol–cloud couplings. For instance, negative correlations in subtropical stratocumulus regions show that suppression of precipitation and subsequent increase in water content due to aerosol is not a dominating process on this scale. Only in one of the studied models are cloud dynamics able to overcome the parameterized dependence of rain formation on droplet number concentration, and negative correlations in the stratocumulus regions are reproduced.
We study the relation between monthly mean albedo and cloud fraction over ocean, 60°S–60°N. Satellite observations indicate that these clouds all fall on the same near‐exponential curve, with a ...monotonic distribution over the ranges of cloud fractions and albedo. Using these observational data as a reference, we examine the degree to which 26 climate models capture this feature of the near‐global marine cloud population. Models show a general increase in albedo with increasing cloud fraction, but none of them display a relation that is as well defined as that characterizing the observations. Models typically display larger albedo variability at a given cloud fraction, larger sensitivity in albedo to changes in cloud fraction, and lower cloud fractions. Several models also show branched distributions, contrasting with the smooth observational relation. In the models the present‐day cloud scenes are more reflective than the preindustrial, demonstrating the simulated impact of anthropogenic aerosols on planetary albedo.
Key Points
Albedo and cloud fraction are extremely well correlated over global ocean
Models show too large spread in albedo for a given cloud fraction
Present‐day aerosols explain higher albedos for a given cloud fraction
The global aerosol extinction from the CALIOP space lidar was used to compute
aerosol optical depth (AOD) over a 9-year period (2007–2015) and
partitioned between the boundary layer (BL) and the free ...troposphere (FT)
using BL heights obtained from the ERA-Interim archive. The results show that
the vertical distribution of AOD does not follow the diurnal cycle of the BL
but remains similar between day and night highlighting the presence of a
residual layer during night. The BL and FT contribute 69 and 31 %,
respectively, to the global tropospheric AOD during daytime in line with
observations obtained in Aire sur l'Adour (France) using the Light Optical
Aerosol Counter (LOAC) instrument. The FT AOD contribution is larger in the
tropics than at mid-latitudes which indicates that convective transport
largely controls the vertical profile of aerosols. Over oceans, the FT AOD
contribution is mainly governed by long-range transport of aerosols from
emission sources located within neighboring continents. According to the
CALIOP aerosol classification, dust and smoke particles are the main aerosol
types transported into the FT. Overall, the study shows that the fraction of
AOD in the FT – and thus potentially located above low-level clouds – is
substantial and deserves more attention when evaluating the radiative effect
of aerosols in climate models. More generally, the results have implications
for processes determining the overall budgets, sources, sinks and transport
of aerosol particles and their description in atmospheric models.
Biomass burning plumes are frequently transported over the southeast Atlantic (SEA) stratocumulus deck during the southern African fire season (June–October). The plumes bring large amounts of ...absorbing aerosols and enhanced moisture, which can trigger a rich set of aerosol–cloud–radiation interactions with climatic consequences that are still poorly understood. We use large-eddy simulation (LES) to explore and disentangle the individual impacts of aerosols and moisture on the underlying stratocumulus clouds, the marine boundary layer (MBL) evolution, and the stratocumulus-to-cumulus transition (SCT) for three different meteorological situations over the southeast Atlantic during August 2017. For all three cases, our LES shows that the SCT is driven by increased sea surface temperatures and cloud-top entrainment as the air is advected towards the Equator. In the LES model, aerosol indirect effects, including impacts on drizzle production, have a small influence on the modeled cloud evolution and SCT, even when aerosol concentrations are lowered to background concentrations. In contrast, local semi-direct effects, i.e., aerosol absorption of solar radiation in the MBL, cause a reduction in cloud cover that can lead to a speed-up of the SCT, in particular during the daytime and during broken cloud conditions, especially in highly polluted situations. The largest impact on the radiative budget comes from aerosol impacts on cloud albedo: the plume with absorbing aerosols produces a total average 3 d of simulations. We find that the moisture accompanying the aerosol plume produces an additional cooling effect that is about as large as the total aerosol radiative effect. Overall, there is still a large uncertainty associated with the radiative and cloud evolution effects of biomass burning aerosols. A comparison between different models in a common framework, combined with constraints from in situ observations, could help to reduce the uncertainty.
Cloud droplet number concentration (CDNC) is the key state variable that moderates the relationship between aerosol and the radiative forcing arising from aerosol–cloud interactions. Uncertainty ...related to the effect of anthropogenic aerosol on cloud properties represents the largest uncertainty in total anthropogenic radiative forcing. Here we show that regionally averaged time series of the Moderate-Resolution Imaging Spectroradiometer (MODIS) observed CDNC of low, liquid-topped clouds is well predicted by the MERRA2 reanalysis near-surface sulfate mass concentration over decadal timescales. A multiple linear regression between MERRA2 reanalyses masses of sulfate (SO4), black carbon (BC), organic carbon (OC), sea salt (SS), and dust (DU) shows that CDNC across many different regimes can be reproduced by a simple power-law fit to near-surface SO4, with smaller contributions from BC, OC, SS, and DU. This confirms previous work using a less sophisticated retrieval of CDNC on monthly timescales. The analysis is supported by an examination of remotely sensed sulfur dioxide (SO2) over maritime volcanoes and the east coasts of North America and Asia, revealing that maritime CDNC responds to changes in SO2 as observed by the ozone monitoring instrument (OMI). This investigation of aerosol reanalysis and top-down remote-sensing observations reveals that emission controls in Asia and North America have decreased CDNC in their maritime outflow on a decadal timescale.
Uncertainty in cloud feedbacks in climate models is a major limitation in projections of future climate. Therefore, evaluation and improvement of cloud simulation are essential to ensure the accuracy ...of climate models. We analyse cloud biases and cloud change with respect to global mean near-surface temperature (GMST) in climate models relative to satellite observations and relate them to equilibrium climate sensitivity, transient climate response and cloud feedback. For this purpose, we develop a supervised deep convolutional artificial neural network for determination of cloud types from low-resolution (2.5∘×2.5∘) daily mean top-of-atmosphere shortwave and longwave radiation fields, corresponding to the World Meteorological Organization (WMO) cloud genera recorded by human observers in the Global Telecommunication System (GTS). We train this network on top-of-atmosphere radiation retrieved by the Clouds and the Earth’s Radiant Energy System (CERES) and GTS and apply it to the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5 and CMIP6) model output and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) and the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) reanalyses. We compare the cloud types between models and satellite observations. We link biases to climate sensitivity and identify a negative linear relationship between the root mean square error of cloud type occurrence derived from the neural network and model equilibrium climate sensitivity (ECS), transient climate response (TCR) and cloud feedback. This statistical relationship in the model ensemble favours models with higher ECS, TCR and cloud feedback. However, this relationship could be due to the relatively small size of the ensemble used or decoupling between present-day biases and future projected cloud change. Using the abrupt-4×CO2 CMIP5 and CMIP6 experiments, we show that models simulating decreasing stratiform and increasing cumuliform clouds tend to have higher ECS than models simulating increasing stratiform and decreasing cumuliform clouds, and this could also partially explain the association between the model cloud type occurrence error and model ECS.
Aerosol-cloud interactions are a major source of uncertainty in inferring the climate sensitivity from the observational record of temperature. The adjustment of clouds to aerosol is a poorly ...constrained aspect of these aerosol-cloud interactions. Here, we examine the response of midlatitude cyclone cloud properties to a change in cloud droplet number concentration (CDNC). Idealized experiments in high-resolution, convection-permitting global aquaplanet simulations with constant CDNC are compared to 13 years of remote-sensing observations. Observations and idealized aquaplanet simulations agree that increased warm conveyor belt (WCB) moisture flux into cyclones is consistent with higher cyclone liquid water path (CLWP). When CDNC is increased a larger LWP is needed to give the same rain rate. The LWP adjusts to allow the rain rate to be equal to the moisture flux into the cyclone along the WCB. This results in an increased CLWP for higher CDNC at a fixed WCB moisture flux in both observations and simulations. If observed cyclones in the top and bottom tercile of CDNC are contrasted it is found that they have not only higher CLWP but also cloud cover and albedo. The difference in cyclone albedo between the cyclones in the top and bottom third of CDNC is observed by CERES to be between 0.018 and 0.032, which is consistent with a 4.6-8.3 Wm(exp -2) in-cyclone enhancement in upwelling shortwave when scaled by annual-mean insolation. Based on a regression model to observed cyclone properties, roughly 60% of the observed variability in CLWP can be explained by CDNC and WCB moisture flux.
A detailed analysis of optical and microphysical properties of aerosol particles during the dry winter monsoon season above the northern Indian Ocean is presented. The Cloud Aerosol Radiative Forcing ...Experiment (CARDEX), conducted from 16 February to 30 March 2012 at the Maldives Climate Observatory on Hanimaadhoo island (MCOH) in the Republic of the Maldives, used autonomous unmanned aerial vehicles (AUAV) to perform vertical in situ measurements of particle number concentration, particle number size distribution as well as particle absorption coefficients. These measurements were used together with surface- based Mini Micro Pulse Lidar (MiniMPL) observations and aerosol in situ and off-line measurements to investigate the vertical distribution of aerosol particles.Air masses were mainly advected over the Indian subcontinent and the Arabian Peninsula. The mean surface aerosol number concentration was 1717 ± 604 cm−3 and the highest values were found in air masses from the Bay of Bengal and Indo-Gangetic Plain (2247 ± 370 cm−3). Investigations of the free tropospheric air showed that elevated aerosol layers with up to 3 times higher aerosol number concentrations than at the surface occurred mainly during periods with air masses originating from the Bay of Bengal and the Indo-Gangetic Plain. This feature is different compared to what was observed during the Indian Ocean Experiment (INDOEX) conducted in winter 1999, where aerosol number concentrations generally decreased with height. In contrast, lower particle absorption at the surface (σabs(520 nm) = 8.5 ± 4.2 Wm−1) was found during CARDEX compared to INDOEX 1999.Layers with source region specific single-scattering albedo (SSA) values were derived by combining vertical in situ particle absorption coefficients and scattering coefficients calculated with Mie theory. These SSA layers were utilized to calculate vertical particle absorption profiles from MiniMPL profiles. SSA surface values for 550 nm for dry conditions were found to be 0.94 ± 0.02 and 0.91 ± 0.02 for air masses from the Arabian Sea (and Middle East countries) and India (and Bay of Bengal), respectively. Lidar-derived particle absorption coefficient profiles showed both a similar magnitude and structure as the in situ profiles measured with the AUAV. However, primarily due to insufficient accuracy in the SSA estimates, the lidar-derived absorption coefficient profiles have large uncertainties and are generally weakly correlated to vertically in situ measured particle absorption coefficients.Furthermore, the mass absorption efficiency (MAE) for the northern Indian Ocean during the dry monsoon season was calculated to determine equivalent black carbon (EBC) concentrations from particle absorption coefficient measurements. A mean MAE of 11.6 and 6.9 m2 g−1 for 520 and 880 nm, respectively, was found, likely representing internally mixed BC containing particles. Lower MAE values for 880 and 520 nm were found for air masses originating from dust regions such as the Arabian Peninsula and western Asia (MAE(880 nm) = 5.6 m2 g−1, MAE(520 nm) = 9.5 m2 g−1) or from closer source regions as southern India (MAE(880 nm) = 4.3 m2 g−1, MAE(520 nm) = 7.3 m2 g−1).
The vertical distribution of aerosols plays an important role in determining the effective radiative forcing from aerosol–radiation and aerosol–cloud interactions. Here, a number of processes ...controlling the vertical distribution of aerosol in five subtropical marine stratocumulus regions in the climate model NorESM1-M are investigated, with a focus on the total aerosol extinction. A comparison with satellite lidar data (CALIOP, Cloud–Aerosol Lidar with Orthogonal Polarization) shows that the model underestimates aerosol extinction throughout the troposphere, especially elevated aerosol layers in the two regions where they are seen in observations. It is found that the shape of the vertical aerosol distribution is largely determined by the aerosol emission and removal processes in the model, primarily through the injection height, emitted particle size, and wet scavenging. In addition, the representation of vertical transport related to shallow convection and entrainment is found to be important, whereas alterations in aerosol optical properties and cloud microphysics parameterizations have smaller effects on the vertical aerosol extinction distribution. However, none of the alterations made are sufficient for reproducing the observed vertical distribution of aerosol extinction, neither in magnitude nor in shape. Interpolating the vertical levels of CALIOP to the corresponding model levels leads to better agreement in the boundary layer and highlights the importance of the vertical resolution.
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