Evaluation of aerosol direct radiative forcing in MIRAGE

Ghan, Steven J.; Laulainen, N. S.; Easter, Richard C.; Wagener, R.; Nemesure, S.; Chapman, Elaine G.; Zhang, Yang; Leung, Ruby

doi:10.1029/2000jd900502

Cited by 194 publications

(159 citation statements)

References 61 publications

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“…The Maxwell-Garnett method assumes a random distribution of black carbon in spherical particles. Both of the volume and Maxwell-Garnett schemes call for the full Mie calculation only at the first time step (Ghan et al, 2001). However, the exact volume and exact MaxwellGarnett schemes call for the full Mie calculation at each time step.…”

Section: Experiments Designmentioning

confidence: 99%

Consistent response of Indian summer monsoon to Middle East dust in observations and simulations

Jin

Wei

et al. 2015

Atmos. Chem. Phys.

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Abstract. The response of the Indian summer monsoon (ISM) circulation and precipitation to Middle East dust aerosols on sub-seasonal timescales is studied using observations and the Weather Research and Forecasting model coupled with online chemistry (WRF-Chem). Satellite data show that the ISM rainfall in coastal southwest India, central and northern India, and Pakistan is closely associated with the Middle East dust aerosols. The physical mechanism behind this dust-ISM rainfall connection is examined through ensemble simulations with and without dust emissions. Each ensemble includes 16 members with various physical and chemical schemes to consider the model uncertainties in parameterizing short-wave radiation, the planetary boundary layer, and aerosol chemical mixing rules. Experiments show that dust aerosols increase rainfall by about 0.44 mm day −1 (∼ 10 % of the climatology) in coastal southwest India, central and northern India, and north Pakistan, a pattern consistent with the observed relationship. The ensemble mean rainfall response over India shows a much stronger spatial correlation with the observed rainfall response than any other ensemble members. The largest modeling uncertainties are from the boundary layer schemes, followed by short-wave radiation schemes. In WRF-Chem, the dust aerosol optical depth (AOD) over the Middle East shows the strongest correlation with the ISM rainfall response when dust AOD leads rainfall response by about 11 days. Further analyses show that increased ISM rainfall is related to enhanced southwesterly monsoon flow and moisture transport from the Arabian Sea to the Indian subcontinent, which are associated with the development of an anomalous low-pressure system over the Arabian Sea, the southern Arabian Peninsula, and the Iranian Plateau due to dust-induced heating in the troposphere. The dust-induced heating in the mid-upper troposphere is mainly located in the Iranian Plateau rather than the Tibetan Plateau. This study demonstrates a thermodynamic mechanism that links remote desert dust emissions in the Middle East to ISM circulation and precipitation variability on subseasonal timescales, which may have implications for ISM rainfall forecasts.

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Section: Experiments Designmentioning

confidence: 99%

Consistent response of Indian summer monsoon to Middle East dust in observations and simulations

Jin

Wei

et al. 2015

Atmos. Chem. Phys.

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“…Each chemical constituent of the aerosol is associated with a complex refraction index calculated by volume averaging for each size bin (or mode), and Mie theory is used to compute the extinction efficiency (Q e ) and the scattering efficiency (Q s ). To efficiently compute Q e and Q s , WRF-Chem uses a methodology described by Ghan et al (2001) that performs the full Mie calculations once first to obtain a table of seven sets of Chebyshev expansion coefficients, and later the full Mie calculations are skipped and Q e and Q s are calculated using bilinear interpolation over the Chebyshev coefficients stored in the table. A detailed description of the computation of aerosol optical properties in WRF-Chem can be found in Fast et al (2006) and Barnard et al (2010).…”

Section: Model Descriptionmentioning

confidence: 99%

Radiative impact of mineral dust on monsoon precipitation variability over West Africa

et al. 2011

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Abstract. The radiative forcing of dust and its impact on precipitation over the West Africa monsoon (WAM) region is simulated using a coupled meteorology and aerosol/chemistry model (WRF-Chem). During the monsoon season, dust is a dominant contributor to aerosol optical depth (AOD) over West Africa. In the control simulation, on 24-h domain average, dust has a cooling effect (−6.11 W m −2 ) at the surface, a warming effect (6.94 W m −2 ) in the atmosphere, and a relatively small TOA forcing (0.83 W m −2 ). Dust modifies the surface energy budget and atmospheric diabatic heating. As a result, atmospheric stability is increased in the daytime and reduced in the nighttime, leading to a reduction of late afternoon precipitation by up to 0.14 mm/h (25%) and an increase of nocturnal and early morning precipitation by up to 0.04 mm/h (45%) over the WAM region. Dust-induced reduction of diurnal precipitation variation improves the simulated diurnal cycle of precipitation when compared to measurements. However, daily precipitation is only changed by a relatively small amount (−0.17 mm/day or −4%). The dust-induced change of WAM precipitation is not sensitive to interannual monsoon variability. On the other hand, sensitivity simulations with weaker to stronger absorbing dust (in order to represent the uncertainty in dust solar absorptivity) show that, at the lower atmosphere, dust longwave warming effect in the nighttime surpasses its shortwave cooling effect in the daytime; this leads to a less stable atmosphere associated with more convective precipitation in the nighttime. As a result, the dust-induced change of daily WAM precipitation varies from a significant reduction of −0.52 mm/day (−12%, weaker absorbing dust) to a small increase of 0.03 mm/day (1%, stronger absorbing dust). This variation originates from the competition between dust impact on daytime and nightCorrespondence to: C. Zhao (chun.zhao@pnl.gov) time precipitation, which depends on dust shortwave absorption. Dust reduces the diurnal variation of precipitation regardless of its absorptivity, but more reduction is associated with stronger absorbing dust.

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“…Until recently, climate models used simple representations of aerosol, which were based mostly on just particle mass. But the recognition that simplification of physical processes limits model predictive capability has led to the development of more complex "second generation" aerosol microphysics schemes that are intended to enhance model realism and improve the reliability of predictions (Binkowski and Shankar, 1995;Jacobson, 1997;Whitby and McMurry, 1997;Ackermann et al, 1998;Ghan et al, 2001;Adams and Seinfeld, 2002;Lauer et al, 2005;Liu et al, 2005;Stier et al, 2005;Spracklen et al, 2005a;Debry et al, 2007;Spracklen et al, 2008). Model realism has undoubtedly improved, but the diversity in model aerosol radiative forcing estimates has remained high in successive IPCC assessments (Schimel et al, 1996;Penner et al, 2001;Forster et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Emulation of a complex global aerosol model to quantify sensitivity to uncertain parameters

et al. 2011

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Abstract. Sensitivity analysis of atmospheric models is necessary to identify the processes that lead to uncertainty in model predictions, to help understand model diversity through comparison of driving processes, and to prioritise research. Assessing the effect of parameter uncertainty in complex models is challenging and often limited by CPU constraints. Here we present a cost-effective application of variance-based sensitivity analysis to quantify the sensitivity of a 3-D global aerosol model to uncertain parameters. A Gaussian process emulator is used to estimate the model output across multi-dimensional parameter space, using information from a small number of model runs at points chosen using a Latin hypercube space-filling design. Gaussian process emulation is a Bayesian approach that uses information from the model runs along with some prior assumptions about the model behaviour to predict model output everywhere in the uncertainty space. We use the Gaussian process emulator to calculate the percentage of expected output variance explained by uncertainty in global aerosol model parameters and their interactions. To demonstrate the technique, we show examples of cloud condensation nuclei (CCN) sensitivity to 8 model parameters in polluted and remote marine environments as a function of altitude. In the polluted environment 95 % of the variance of CCN concentration is described by uncertainty in the 8 parameters (excluding their interaction effects) and is dominated by the uncertainty in the sulphur emissions, which explains 80 % of the variance. However, in the remote region parameter interaction effects become important, accounting for up to 40 % of the total variance. Some parameters are shown to have a negligible individual effect but a substantial interacCorrespondence to: L. A. Lee (l.a.lee@leeds.ac.uk) tion effect. Such sensitivities would not be detected in the commonly used single parameter perturbation experiments, which would therefore underpredict total uncertainty. Gaussian process emulation is shown to be an efficient and useful technique for quantifying parameter sensitivity in complex global atmospheric models.

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Evaluation of aerosol direct radiative forcing in MIRAGE

Cited by 194 publications

References 61 publications

Consistent response of Indian summer monsoon to Middle East dust in observations and simulations

Consistent response of Indian summer monsoon to Middle East dust in observations and simulations

Radiative impact of mineral dust on monsoon precipitation variability over West Africa

Emulation of a complex global aerosol model to quantify sensitivity to uncertain parameters

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