Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.climate | aerosol−cloud effects | general circulation models | radiative forcing | satellite observations Clouds play a key role in Earth's radiation budget, and aerosols serve as the seeds upon which cloud droplets form. Anthropogenic activity has led to an increase in aerosol particle concentrations globally and an increase in those particles that act as cloud condensation nuclei (CCN) and ice nucleating particles (INP). The effect of an increase in aerosols on cloud optical properties, and associated radiative forcing, is the most uncertain component of historical radiative forcing of Earth's climate caused by greenhouse gases (GHGs) and aerosols. The Intergovernmental Panel on Climate Change (IPCC) AR5 assessment of climate forcing factors (Fig. S1) ascribes "high" confidence to the estimate of direct aerosol radiative forcing (mean

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“…Ghan et al (59) estimate the structural uncertainty in representations like Eq. 5 using a suite of atmospheric models.…”

Section: Connecting Process-scale Models To Climate Modelsmentioning

confidence: 99%

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

Seinfeld

Bretherton

Carslaw

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…Further, that uncertainties due to the choice of microphysics scheme dominate any aerosol response within a given scheme has implications for global modelling studies of aerosol indirect effects (e.g. Zhang et al, 2016;Ghan et al, 2016). Once again, this highlights the continuing need of our community for tight observational constraints on cloud and precipitation processes and their response to aerosol, as well as for ongoing parameterisation development to allow these processes to be accurately represented in large domain (or global), long-term simulations.…”

Section: Congo-morr Congo-thom Super-morr Super-thom Rico-morr Rico-thommentioning

confidence: 99%

“…Indeed, bulk schemes remain as standard in global models, and successful studies of aerosol indirect effects in global models have been performed using bulk microphysics (e.g. Zhang et al, 2016;Ghan et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Uncertainty from the choice of microphysics scheme in convection-permitting models significantly exceeds aerosol effects

White

Gryspeerdt²,

Stier

et al. 2017

Atmos. Chem. Phys.

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Abstract. This study investigates the hydrometeor development and response to cloud droplet number concentration (CDNC) perturbations in convection-permitting model configurations. We present results from a real-data simulation of deep convection in the Congo basin, an idealised supercell case, and a warm-rain large-eddy simulation (LES). In each case we compare two frequently used double-moment bulk microphysics schemes and investigate the response to CDNC perturbations. We find that the variability among the two schemes, including the response to aerosol, differs widely between these cases. In all cases, differences in the simulated cloud morphology and precipitation are found to be significantly greater between the microphysics schemes than due to CDNC perturbations within each scheme. Further, we show that the response of the hydrometeors to CDNC perturbations differs strongly not only between microphysics schemes, but the inter-scheme variability also differs between cases of convection. Sensitivity tests show that the representation of autoconversion is the dominant factor that drives differences in rain production between the microphysics schemes in the idealised precipitating shallow cumulus case and in a subregion of the Congo basin simulations dominated by liquidphase processes. In this region, rain mass is also shown to be relatively insensitive to the radiative effects of an overlying layer of ice-phase cloud. The conversion of cloud ice to snow is the process responsible for differences in cold cloud bias between the schemes in the Congo. In the idealised supercell case, thermodynamic impacts on the storm system using different microphysics parameterisations can equal those due to aerosol effects. These results highlight the large uncertainty in cloud and precipitation responses to aerosol in convectionpermitting simulations and have important implications not only for process studies of aerosol-convection interaction, but also for global modelling studies of aerosol indirect effects. These results indicate the continuing need for tighter observational constraints of cloud processes and response to aerosol in a range of meteorological regimes.

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“…S POP has been shown to strongly correlate with cloud water response to aerosol perturbations in global climate models Ghan et al, 2016). Terai et al (2012Terai et al ( , 2015 further extended the definition of precipitation susceptibility:…”

Section: Introductionmentioning

confidence: 99%

Estimating precipitation susceptibility in warm marine clouds using multi-sensor aerosol and cloud products from A-Train satellites

et al. 2018

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Abstract. Precipitation susceptibility to aerosol perturbation plays a key role in understanding aerosol-cloud interactions and constraining aerosol indirect effects. However, large discrepancies exist in the previous satellite estimates of precipitation susceptibility. In this paper, multi-sensor aerosol and cloud products, including those from the CloudAerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) from June 2006 to April 2011 are analyzed to estimate precipitation frequency susceptibility S POP , precipitation intensity susceptibility S I , and precipitation rate susceptibility S R in warm marine clouds. We find that S POP strongly depends on atmospheric stability, with larger values under more stable environments. Our results show that precipitation susceptibility for drizzle (with a −15 dBZ rainfall threshold) is significantly different than that for rain (with a 0 dBZ rainfall threshold). Onset of drizzle is not as readily suppressed in warm clouds as rainfall while precipitation intensity susceptibility is generally smaller for rain than for drizzle. We find that S POP derived with respect to aerosol index (AI) is about one-third of S POP derived with respect to cloud droplet number concentration (CDNC). Overall, S POP demonstrates relatively robust features throughout independent liquid water path (LWP) products and diverse rain products. In contrast, the behaviors of S I and S R are subject to LWP or rain products used to derive them. Recommendations are further made for how to better use these metrics to quantify aerosolcloud-precipitation interactions in observations and models.

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Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability

Cited by 149 publications

References 85 publications

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

Uncertainty from the choice of microphysics scheme in convection-permitting models significantly exceeds aerosol effects

Estimating precipitation susceptibility in warm marine clouds using multi-sensor aerosol and cloud products from A-Train satellites

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