Minghuai Wang

Inclusion of Ice Microphysics in the NCAR Community Atmospheric Model Version 3 (CAM3)

Abstract A prognostic equation for ice crystal number concentration together with an ice nucleation scheme are implemented in the National Center for Atmospheric Research (NCAR) Community Atmospheric Model version 3 (CAM3) with the aim of studying the indirect effect of aerosols on cold clouds. The effective radius of ice crystals, which is used in the radiation and gravitational settlement calculations, is now calculated from model-predicted mass and number of ice crystals rather than diagnosed as a function of temperature. A water vapor deposition scheme is added to replace the condensation and evaporation (C–E) in the standard CAM3 for ice clouds. The repartitioning of total water into liquid and ice in mixed-phase clouds as a function of temperature is removed, and ice supersaturation is allowed. The predicted ice water content in the modified CAM3 is in better agreement with the Aura Microwave Limb Sounder (MLS) data than that in the standard CAM3. The cirrus cloud fraction near the tropical tropopau...

Satellite methods underestimate indirect climate forcing by aerosols

Satellite-based estimates of the aerosol indirect effect (AIE) are consistently smaller than the estimates from global aerosol models, and, partly as a result of these differences, the assessment of this climate forcing includes large uncertainties. Satellite estimates typically use the present-day (PD) relationship between observed cloud drop number concentrations (Nc) and aerosol optical depths (AODs) to determine the preindustrial (PI) values of Nc. These values are then used to determine the PD and PI cloud albedos and, thus, the effect of anthropogenic aerosols on top of the atmosphere radiative fluxes. Here, we use a model with realistic aerosol and cloud processes to show that empirical relationships for ln(Nc) versus ln(AOD) derived from PD results do not represent the atmospheric perturbation caused by the addition of anthropogenic aerosols to the preindustrial atmosphere. As a result, the model estimates based on satellite methods of the AIE are between a factor of 3 to more than a factor of 6 smaller than model estimates based on actual PD and PI values for Nc. Using ln(Nc) versus ln(AI) (Aerosol Index, or the optical depth times angstrom exponent) to estimate preindustrial values for Nc provides estimates for Nc and forcing that are closer to the values predicted by the model. Nevertheless, the AIE using ln(Nc) versus ln(AI) may be substantially incorrect on a regional basis and may underestimate or overestimate the global average forcing by 25 to 35%.

Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model

Significance Increasing levels of air pollutants in Asia have recently drawn considerable attention, but the effects of Asian pollution outflows on regional climate and global atmospheric circulation remain to be quantified. Using a multiscale global aerosol–climate model (GCM), we demonstrate long-range transport of the Asian pollution, large resulting variations in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths; enhanced shortwave and longwave cloud radiative forcings; and increased precipitation and poleward heat transport. Our work provides, for the first time to the authors’ knowledge, a global multiscale perspective of the climatic effects of pollution outflows from Asia. The results reveal that the multiscale modeling framework is essential in simulating the aerosol invigoration effect of deep convective cloud systems by a GCM. Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the effects of anthropogenic aerosols on the Pacific storm track, using a multiscale global aerosol–climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and preindustrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and longwave cloud radiative forcing at the top of atmosphere are changed by −2.5 and +1.3 W m−2, respectively, by emission changes from preindustrial to present day, and an increased cloud top height indicates invigorated midlatitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides, for the first time to the authors’ knowledge, a global perspective of the effects of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multiscale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on a global scale.

Enhanced haze pollution by black carbon in megacities in China

Aerosol-planetary boundary layer (PBL) interactions have been found to enhance air pollution in megacities in China. We show that black carbon (BC) aerosols play the key role in modifying the PBL meteorology and hence enhancing the haze pollution. With model simulations and data analysis from various field observations in December 2013, we demonstrate that BC induces heating in the PBL, particularly in the upper PBL, and the resulting decreased surface heat flux substantially depresses the development of PBL and consequently enhances the occurrences of extreme haze pollution episodes. We define this process as the “dome effect” of BC and suggest an urgent need for reducing BC emissions as an efficient way to mitigate the extreme haze pollution in megacities of China.

PDF Parameterization of Boundary Layer Clouds in Models with Horizontal Grid Spacings from 2 to 16 km

Many present-day numerical weather prediction (NWP) models are run at resolutions that permit deep convection. In these models, however, the boundary layer turbulence and boundary layer cloud features are still grossly underresolved. Underresolution is also present in climate models that use a multiscale modeling framework (MMF), in which a convection-permitting model is run in each grid column of a global general circulation model. To better represent boundary layer clouds and turbulence in convection-permitting models, a parameterization was developed that models the joint probability density function (PDF) of vertical velocity, heat, and moisture. Although PDF-based parameterizations are more complex and computationally expensive than many other parameterizations, in principle PDF parameterizations have several advantages. For instance, they ensure consistency of liquid (cloud) water and cloud fraction; they avoid using separate parameterizations for different cloud types such as cumulus and stratocumulus; and they have an appropriate formulation in the ‘‘terra incognita’’ in which updrafts are marginally resolved. In this paper, an implementation of a PDF parameterization is tested to see whether it improves the simulations of a state-of-the-art convection-permitting model. The PDF parameterization used is the Cloud LayersUnifiedBy Binormals (CLUBB)parameterization.The host cloud-resolving model usedis theSystem forAtmosphericModeling(SAM).SAMisrunbothwithandwithoutCLUBBimplementedinit.Simulations of two shallowcumulus(Cu)cases andtwo shallowstratocumulus(Sc)casesarerun ina 3D configurationat 2-, 4-, and 16-km horizontal grid spacings. Including CLUBB in the simulations improves some of the simulated fields—such as vertical velocity variance, horizontal wind fields, cloud water content, and drizzle water content—especially in the two Cu cases. Implementing CLUBB in SAM improves the simulations slightly at 2-km horizontal grid spacing, significantlyat4-kmgridspacing,andgreatlyat 16-kmgridspacing.Furthermore,thesimulationsthatinclude CLUBB exhibit a reduced sensitivity to horizontal grid spacing.

Coupled IMPACT aerosol and NCAR CAM3 model: Evaluation of predicted aerosol number and size distribution

Received 20 May 2008; revised 4 September 2008; accepted 9 January 2009; published 21 March 2009. [1] Simulated aerosol fields from a coupled aerosol/atmospheric circulation model that includes prediction of both sulfate aerosol size and number are evaluated. Sensitivity tests are used to evaluate uncertainties due to the inclusion of primary emitted particulate sulfate as a means of representing nucleation of particles in subgrid-scale plumes, the use of two boundary layer aerosol nucleation mechanisms, and a three-mode sulfate aerosol representation. Simulated annual and global aerosol budgets are comparable to other model studies with the exception of carbonaceous aerosols and fine mode dust, where smaller mass concentrations are simulated. The model underestimates the accumulation mode aerosol number in the marine boundary layer over middle and low latitudes, which is consistent with an underestimate of fine mode sea salt mass in these locations. Primary emitted particulate sulfate contributes significantly to aerosol number at sites located in the boundary layer over Europe, but the absence of constraints on the number of such particles from either observations or fine-resolution models makes this treatment undesirable. Boundary layer nucleation mechanisms improve the comparison of simulated aerosol number concentrations with observations in the marine boundary layer, suggesting that a treatment of boundary layer nucleation is needed in global aerosol models, although more studies are needed to quantify how different nucleation mechanisms and condensable gases other than sulfuric acid affect aerosol number. The three-mode representation of sulfate aerosol simulates the observed increase in accumulation mode number concentration with altitude in the upper troposphere and improves the simulated Aitken mode aerosol number concentration there. This indicates the importance of a separate representation of freshly nucleated particles when nucleation is an important source of particle number concentrations.

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

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 worlds area in which a statistically significant aerosol indirect effect can be detected (66% and 28% of the Earths 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.

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

A large number of processes are involved in the chain from emissions of aerosol precursor gases and primary particles to impacts on cloud radiative forcing. Those processes are manifest in a number of relationships that can be expressed as factors dlnX/dlnY driving aerosol effects on cloud radiative forcing. These factors include the relationships between cloud condensation nuclei (CCN) concentration and emissions, droplet number and CCN concentration, cloud fraction and droplet number, cloud optical depth and droplet number, and cloud radiative forcing and cloud optical depth. The relationship between cloud optical depth and droplet number can be further decomposed into the sum of two terms involving the relationship of droplet effective radius and cloud liquid water path with droplet number. These relationships can be constrained using observations of recent spatial and temporal variability of these quantities. However, we are most interested in the radiative forcing since the preindustrial era. Because few relevant measurements are available from that era, relationships from recent variability have been assumed to be applicable to the preindustrial to present-day change. Our analysis of Aerosol Comparisons between Observations and Models (AeroCom) model simulations suggests that estimates of relationships from recent variability are poor constraints on relationships from anthropogenic change for some terms, with even the sign of some relationships differing in many regions. Proxies connecting recent spatial/temporal variability to anthropogenic change, or sustained measurements in regions where emissions have changed, are needed to constrain estimates of anthropogenic aerosol impacts on cloud radiative forcing.

How does increasing horizontal resolution in a global climate model improve the simulation of aerosol-cloud interactions?

The Community Atmosphere Model Version 5 is run at horizontal grid spacing of 2, 1, 0.5, and 0.25°, with the meteorology nudged toward the Year Of Tropical Convection analysis, and cloud simulators and the collocated A-Train satellite observations are used to explore the resolution dependence of aerosol-cloud interactions. The higher-resolution model produces results that agree better with observations, showing an increase of susceptibility of cloud droplet size, indicating a stronger first aerosol indirect forcing (AIF), and a decrease of susceptibility of precipitation probability, suggesting a weaker second AIF. The resolution sensitivities of AIF are attributed to those of droplet nucleation and precipitation parameterizations. The annual average AIF in the Northern Hemisphere midlatitudes (where most anthropogenic emissions occur) in the 0.25° model is reduced by about 1 W m−2 (−30%) compared to the 2° model, leading to a 0.26 W m−2 reduction (−15%) in the global annual average AIF.

Parametric sensitivity analysis of precipitation at global and local scales in the Community Atmosphere Model CAM5

We investigate the sensitivity of precipitation characteristics (mean, extreme, and diurnal cycle) to a set of uncertain parameters that influence the qualitative and quantitative behavior of cloud and aerosol processes in the Community Atmosphere Model (CAM5). We adopt both the Latin hypercube and Quasi-Monte Carlo sampling approaches to effectively explore the high-dimensional parameter space and then conduct two large sets of simulations. One set consists of 1100 simulations (cloud ensemble) perturbing 22 parameters related to cloud physics and convection, and the other set consists of 256 simulations (aerosol ensemble) focusing on 16 parameters related to aerosols and cloud microphysics. In the cloud ensemble, six parameters having the greatest influences on the global mean precipitation are identified, three of which (related to the deep convection scheme) are the primary contributors to the total variance of the phase and amplitude of the precipitation diurnal cycle over land. The extreme precipitation characteristics are sensitive to a fewer number of parameters. Precipitation does not always respond monotonically to parameter change. The influence of individual parameters does not depend on the sampling approaches or concomitant parameters selected. Generally, the Generalized Linear Model is able to explain more of the parametric sensitivity of global precipitation than local or regional features. The total explained variance for precipitation is primarily due to contributions from the individual parameters (75–90% in total). The total variance shows a significant seasonal variability in midlatitude continental regions, but very small in tropical continental regions.