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

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.

Development and Evaluation of Chemistry-Aerosol-Climate Model CAM5-Chem-MAM7-MOSAIC: Global Atmospheric Distribution and Radiative Effects of Nitrate Aerosol.

An advanced aerosol treatment, with a focus on semivolatile nitrate formation, is introduced into the Community Atmosphere Model version 5 with interactive chemistry (CAM5-chem) by coupling the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) with the 7-mode Modal Aerosol Module (MAM7). An important feature of MOSAIC is dynamic partitioning of all condensable gases to the different fine and coarse mode aerosols, as governed by mode-resolved thermodynamics and heterogeneous chemical reactions. Applied in the free-running mode from 1995 to 2005 with prescribed historical climatological conditions, the model simulates global distributions of sulfate, nitrate, and ammonium in good agreement with observations and previous studies. Inclusion of nitrate resulted in ∼10% higher global average accumulation mode number concentrations, indicating enhanced growth of Aitken mode aerosols from nitrate formation. While the simulated accumulation mode nitrate burdens are high over the anthropogenic source regions, the sea-salt and dust modes respectively constitute about 74% and 17% of the annual global average nitrate burden. Regional clear-sky shortwave radiative cooling of up to -5 W m-2 due to nitrate is seen, with a much smaller global average cooling of -0.05 W m-2. Significant enhancements in regional cloud condensation nuclei (at 0.1% supersaturation) and cloud droplet number concentrations are also attributed to nitrate, causing an additional global average shortwave cooling of -0.8 W m-2. Taking into consideration of changes in both longwave and shortwave radiation under all-sky conditions, the net change in the top of the atmosphere radiative fluxes induced by including nitrate aerosol is -0.7 W m-2.

Observational constraint on cloud susceptibility weakened by aerosol retrieval limitations.

Aerosol-cloud interactions remain a major uncertainty in climate research. Studies have indicated that model estimates of cloud susceptibility to aerosols frequently exceed satellite estimates, motivating model reformulations to increase agreement. Here we show that conventional ways of using satellite information to estimate susceptibility can serve as only a weak constraint on models because the estimation is sensitive to errors in the retrieval procedures. Using instrument simulators to investigate differences between model and satellite estimates of susceptibilities, we find that low aerosol loading conditions are not well characterized by satellites, but model clouds are sensitive to aerosol perturbations in these conditions. We quantify the observational requirements needed to constrain models, and find that the nighttime lidar measurements of aerosols provide a better characterization of tenuous aerosols. We conclude that observational uncertainties and limitations need to be accounted for when assessing the role of aerosols in the climate system.

Dust-wind interactions can intensify aerosol pollution over eastern China.

Eastern China has experienced severe and persistent winter haze episodes in recent years due to intensification of aerosol pollution. In addition to anthropogenic emissions, the winter aerosol pollution over eastern China is associated with unusual meteorological conditions, including weaker wind speeds. Here we show, based on model simulations, that during years with decreased wind speed, large decreases in dust emissions (29%) moderate the wintertime land-sea surface air temperature difference and further decrease winds by -0.06 (±0.05) m s-1 averaged over eastern China. The dust-induced lower winds enhance stagnation of air and account for about 13% of increasing aerosol concentrations over eastern China. Although recent increases in anthropogenic emissions are the main factor causing haze over eastern China, we conclude that natural emissions also exert a significant influence on the increases in wintertime aerosol concentrations, with important implications that need to be taken into account by air quality studies.

Inter-comparisons of marine boundary layer cloud properties from the ARM CAP-MBL campaign and two MODIS cloud products.

From April 2009 to December 2010, the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an inter-comparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT) and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility (AMF) and two Moderate Resolution Spectroradiometer (MODIS) cloud products (GSFC-MODIS and CERES-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for inter-comparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R>0.95. despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER2.1) is significantly smaller than that based on the 3.7 µm band (CER3.7). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER3.7 and CER2.1 retrievals have a lower correlation (R~0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 µm.