Changes in Atmospheric Constituents and in Radiative Forcing

This paper reviews the many developments in estimates of the direct and indirect global annual mean radiative forcing due to present-day concentra- tions of anthropogenic tropospheric aerosols since Inter- governmental Panel on Climate Change (1996). The range of estimates of the global mean direct radiative forcing due to six distinct aerosol types is presented. Addition- ally, the indirect effect is split into two components corresponding to the radiative forcing due to modifica- tion of the radiative properties of clouds (cloud albedo effect) and the effects of anthropogenic aerosols upon the lifetime of clouds (cloud lifetime effect). The radia- tive forcing for anthropogenic sulphate aerosol ranges from 20.26 to 20.82 W m 22 . For fossil fuel black carbon the radiative forcing ranges from 10.16 W m 22 for an external mixture to 10.42 W m 22 for where the black carbon is modeled as internally mixed with sulphate aerosol. For fossil fuel organic carbon the two estimates of the likely weakest limit of the direct radiative forcing are 20.02 and 20.04 W m 22 . For biomass-burning sources of black carbon and organic carbon the com-

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/1999RG000078

Estimates of the direct and indirect radiative forcing due to tropospheric aerosols: A review

The effect of anthropogenic aerosols on cloud droplet concentrations and radiative properties is the source of one of the largest uncertainties in the radiative forcing of climate over the industrial period. This uncertainty affects our ability to estimate how sensitive the climate is to greenhouse gas emissions. Here we perform a sensitivity analysis on a global model to quantify the uncertainty in cloud radiative forcing over the industrial period caused by uncertainties in aerosol emissions and processes. Our results show that 45 per cent of the variance of aerosol forcing since about 1750 arises from uncertainties in natural emissions of volcanic sulphur dioxide, marine dimethylsulphide, biogenic volatile organic carbon, biomass burning and sea spray. Only 34 per cent of the variance is associated with anthropogenic emissions. The results point to the importance of understanding pristine pre-industrial-like environments, with natural aerosols only, and suggest that improved measurements and evaluation of simulated aerosols in polluted present-day conditions will not necessarily result in commensurate reductions in the uncertainty of forcing estimates. The impact of aerosol changes on cloud albedo (called the aerosol first indirect forcing) 1 is estimated 2 to exert a global mean radiative forcing of climate over the industrial period between 20.4 W m 22 and 21.8 W m 22 . Other aerosol–cloud interaction effects, involving rapid adjustments, may be of comparable magnitude 3 but their radiative effects are even less well understood on a global scale 3,4 . The uncertainty in the aerosol forcing is much larger than the uncertainty in the well-constrained positive forcing of 1.7 6 0.2 W m 22 that is due to

/pdf/large-contribution-of-natural-aerosols-to-uncertainty-in-4mw8o6t16n.pdf

Large contribution of natural aerosols to uncertainty in indirect forcing

Landscape Ecology in Theory and Practice

Aerosols are a critical.factor in the atmospheric hydrological cycle and radiation budget. As a major agent for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosols have a major impact on the dynamics, microphysics, and electrification properties of continental mixed-phase convective clouds. In addition, high aerosol concentrations in urban environments could affect precipitation variability by providing a significant source of cloud condensation nuclei (CCN). Such pollution . effects on precipitation potentially have enormous climatic consequences both in terms of feedbacks involving the land surface via rainfall as well as the surface energy budget and changes in latent heat input to the atmosphere. Basically, aerosol concentrations can influence cloud droplet size distributions, the warm-rain process, the cold-rain process, cloud-top heights, the depth of the mixed-phase region, and the occurrence of lightning. Recently, many cloud resolution models (CRMs) have been used to examine the role of aerosols on mixed-phase convective clouds. These modeling studies have many differences in terms of model configuration (two- or three-dimensional), domain size, grid spacing (150-3000 m), microphysics (two-moment bulk, simple or sophisticated spectral-bin), turbulence (1st or 1.5 order turbulent kinetic energy (TKE)), radiation, lateral boundary conditions (i.e., closed, radiative open or cyclic), cases (isolated convection, tropical or midlatitude squall lines) and model integration time (e.g., 2.5 to 48 hours). Among these modeling studies, the most striking difference is that cumulative precipitation can either increase or decrease in response to higher concentrations of CCN. In this presentation, we review past efforts and summarize our current understanding of the effect of aerosols on convective precipitation processes. Specifically, this paper addresses the following topics: observational evidence of the effect of aerosols on precipitation processes, and results from (CRM) simulations. Note that this presentation is mainly based on a recent paper published in Geophy. Rev. (Tao et al. 2012).

/pdf/impact-of-aerosols-on-convective-clouds-and-precipitation-mgybjys25v.pdf

Impact of Aerosols on Convective Clouds and Precipitation

A new method for parametric uncertainty analysis of numerical geophysical models is presented. It approximates model response surfaces, which are functions of model input parameters, using orthogonal polynomials, whose weighting functions are the probabilistic density functions (PDFs) of the input uncertain parameters. This approach has been applied to the uncertainty analysis of an analytical model of the direct radiative forcing by anthropogenic sulfate aerosols which has nine uncertain parameters. This method is shown to generate PDFs of the radiative forcing which are very similar to the exact analytical PDF. Compared with the Monte Carlo method for this problem, the new method is a factor of 25 to 60 times faster, depending on the error tolerance, and exhibits an exponential decrease of error with increasing order of the approximation.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/97JD01654

An efficient method for parametric uncertainty analysis of numerical geophysical models

Uncertainty in the direct radiative forcing by anthropogenic sulfate aerosols is analyzed for four different aerosol model structures with 13 uncertain parameters using a second-order probabilistic collocation method. The resulting probability density functions agree well with those determined here by a computationally much more expensive 10,000-point Monte Carlo method. The structural difference, measured by the range of the mean responses in models with different approximations, is −0.28 to −1.3 W m−2, and the parametric uncertainty, induced by the uncertainties in the model parameters, is −0.1 to −4.2 W m−2, both with 95% confidence. This implies that refining uncertain input parameters may be more important than improving models in order to minimize the overall uncertainty in the direct radiative forcing by anthropogenic sulfate aerosols in these four models. The variance analysis indicates that the parametric uncertainty comes mainly from sulfate yield, sulfate lifetime, and ambient relative humidity. Variance contributions from aerosol size parameters are much smaller, and this finding agrees with the sensitivity analysis by Boucher and Anderson [1995]. Note that the conclusions reached here are dependent on the chosen model structures and parameter distributions. This study presents a computationally efficient framework for assessing uncertainty in aerosol radiative forcing which could be used to address an even wider range of structures and parameters in the future.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/97JD02809

Wenwei Pan

Papers

An efficient method for parametric uncertainty analysis of numerical geophysical models

Uncertainty analysis of direct radiative forcing by anthropogenic sulfate aerosols