Abstract
Natural modes of variability on many timescales influence aerosol particle distributions and cloud properties such that isolating statistically significant differences in cloud radiative forcing due to anthropogenic aerosol perturbations (indirect effects) typically requires integrating over long simulations. For state‐of‐the‐art global climate models (GCM), especially those in which embedded cloud‐resolving models replace conventional statistical parameterizations (i.e., multiscale modeling framework, MMF), the required long integrations can be prohibitively expensive. Here an alternative approach is explored, which implements Newtonian relaxation (nudging) to constrain simulations with both pre‐industrial and present‐day aerosol emissions toward identical meteorological conditions, thus reducing differences in natural variability and dampening feedback responses in order to isolate radiative forcing. Ten‐year GCM simulations with nudging provide a more stable estimate of the global‐annual mean net aerosol indirect radiative forcing than do conventional free‐running simulations. The estimates have mean values and 95% confidence intervals of −1.19 ± 0.02 W/m2 and −1.37 ± 0.13 W/m2for nudged and free‐running simulations, respectively. Nudging also substantially increases the fraction of the world's area in which a statistically significant aerosol indirect effect can be detected (66% and 28% of the Earth's surface for nudged and free‐running simulations, respectively). One‐year MMF simulations with and without nudging provide global‐annual mean net aerosol indirect radiative forcing estimates of −0.81 W/m2 and −0.82 W/m2, respectively. These results compare well with previous estimates from three‐year free‐running MMF simulations (−0.83 W/m2), which showed the aerosol‐cloud relationship to be in better agreement with observations and high‐resolution models than in the results obtained with conventional cloud parameterizations.
Highlights
The treatment of aerosol-cloud physics has undergone many notable updates in Community Atmosphere Model version 5 (CAM5) relative to its predecessor, including the addition of a three-mode twomoment aerosol module, a two-moment cloud microphysics scheme, deep convection with vertical entrainment and convective momentum transport, shallow convection based on moist turbulent processes, and radiative transfer calculations from the Rapid Radiative Transfer Model for global climate models (GCM) [Neale et al, 2010]
[18] The multiscale modeling framework (MMF) approach has been promoted by a National Science Foundation (NSF) Science and Technology Center called Center for Multiscale Modeling of Atmospheric Processes (CMMAP), which has recently collaborated with Pacific Northwest National Laboratory (PNNL) to implement a new version of the model, based on CAM5, to better represent the multiscale interactions between aerosol and clouds [Wang et al, 2011a]
Multiscale Aerosol Climate Model (MACM), the microphysics module for the cloud-resolving model (CRM) has been updated to include a two-moment microphysics scheme consistent with the scheme introduced in CAM5 [Morrison et al, 2005]
Summary
[2] The addition of anthropogenic aerosol particles to Earth’s atmosphere, through the burning of fossil fuels, industrial production, and land use changes, impacts the transmission of radiation by direct scattering and absorption, and by indirect modifications to cloud properties. [7] By design, this approach requires long simulation times to produce the full range of variability governed by natural processes in the climate system This is less a problem for conventionally parameterized climate models, which contain highly idealized cloud-aerosol physics in order to remain computationally affordable for long simulations. This provides the additional benefit of more closely approximating aerosol indirect effects as an instantaneous or pure forcing It removes some of the challenges associated with distinguishing radiative forcing from feedbacks in conventional simulations, which otherwise require new metrics that account for climate sensitivity and/or “fast-feedback” processes, including: quasi-forcing [Rotstayn and Penner, 2001], stratospheric adjustment [Forster et al, 1997], temperature-regressed radiative forcing [Forster and Taylor, 2006], and radiative flux perturbation [Lohmann et al, 2010], in order to accurately compare the impact of aerosol relative to that of other anthropogenic forcing agents.
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