Constraining the influence of natural variability to improve estimates of global aerosol indirect effects in a nudged version of the Community Atmosphere Model 5

Kooperman, Gabriel J.; Pritchard, Michael S.; Ghan, Steven J.; Wang, Minghuai; Somerville, Richard C. J.; Russell, Lynn M.

doi:10.1029/2012jd018588

Cited by 124 publications

(179 citation statements)

References 82 publications

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“…Details of the nudging implementation are described in Zhang et al (2014). Nudging effectively constrains the large-scale circulation and suppresses the noise caused by natural variability, thus allowing for detection of changes in the simulated aerosol characteristics and their climate effects with substantially shorter simulations (see, e.g., Kooperman et al, 2012). …”

Section: Impact On Aerosol Climatology In Cam5mentioning

confidence: 99%

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

et al. 2016

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Abstract. This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities.In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography over land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing.The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2 • resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. In Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.

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Section: Impact On Aerosol Climatology In Cam5mentioning

confidence: 99%

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

et al. 2016

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“…Model simulations can also be sensitive to perturbations to initial conditions. To address this so-called "internal variability", caused by the internal processes of the model (Caya and Biner, 2004;Giorgi and Bi, 2000), ensemble simulations that increase the signal-to-noise ratio or nudging techniques that constrain large-scale climatology (e.g., Kanamaru and Kanamitsu, 2007;Kooperman et al, 2012;von Storch et al, 2000) can be performed.…”

Section: P-l Ma Et Al: Assessing the Cam5 Physics Suite In The Wrfmentioning

confidence: 99%

Assessing the CAM5 physics suite in the WRF-Chem model: implementation, resolution sensitivity, and a first evaluation for a regional case study

et al. 2014

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Abstract.A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 when the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem parameterizations.This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem, provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.

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“…It has also been used to help reduce the effect of natural variability thus making it easier to distinguish signal from noise [e.g., Lohmann and Hoose, 2009;Lohmann and Ferrachat, 2010;Kooperman et al, 2012]. For example, nudging has been shown to help effectively isolate the anthropogenic aerosol indirect effect with simulation lengths that are much shorter than what would otherwise be required for free-running simulations [Kooperman et al, 2012]. On the other hand, as nudging introduces an artificial forcing term to the prognostic equations of the model, it can significantly change the basic characteristics of the model climate, resulting in unintentional impacts on the simulated atmospheric physics and/or chemistry.…”

Section: Introductionmentioning

confidence: 99%

Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?

Lin

Wan

Zhang

et al. 2016

J Adv Model Earth Syst

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Efficient simulation strategies are crucial for the development and evaluation of high‐resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low‐level stratiform clouds (rhminl). Results suggest that the fidelity of the constrained simulations depends on the detailed implementation of nudging and the mechanism through which the perturbed parameter affects precipitation and cloud. The relative computational costs of nudged and free‐running simulations are determined by the magnitude of internal variability in the physical quantities of interest, as well as the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature, and/or wind nudging with a 6 h relaxation time scale leads to nonnegligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while 1 year free‐running simulations can satisfactorily capture the annual mean precipitation and cloud forcing sensitivities. In the case of a relatively weak perturbation in the large‐scale condensation scheme, results from 1 year free‐running simulations are strongly affected by natural noise, while nudging winds effectively reduces the noise, and reasonably reproduces the sensitivities. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.

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Constraining the influence of natural variability to improve estimates of global aerosol indirect effects in a nudged version of the Community Atmosphere Model 5

Cited by 124 publications

References 82 publications

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

Assessing the CAM5 physics suite in the WRF-Chem model: implementation, resolution sensitivity, and a first evaluation for a regional case study

Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?

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