The impacts of climate change on wildfires have been studied extensively. Along with declining emissions from fossil fuel combustion due to anthropogenic emission control, black carbon (BC) released from wildfires is expected to contribute a more significant portion to its atmospheric burden. However, from a global perspective, little is known about the BC burden and radiative forcing caused by wildfires. Here, we report the results from the long-term wildfire-induced BC concentration and direct radiative forcing (DRF) from 1981 to 2010 globally simulated by an Earth System Model using an updated wildfire BC emission inventory. We show that wildfire-induced BC concentration and DRF varied significantly spatially and temporarily, with the highest in sub-Saharan Africa, attributable to its highest level of wildfire BC emission worldwide. The temporal trends of near-surface air temperature, precipitation, and evapotranspiration and their association with wildfire-induced BC concentration are explored using the multidimensional ensemble empirical mode decomposition. A statistically significant relation between changes in climate parameters and wildfire-induced BC concentration was found for 53% of the land grid cells, explaining on average 33% of the concentration variations. The result suggests that the wildfire-induced BC DRF, with an increasing trend, would be an important contributor to climate change, especially in sub-Saharan Africa. Occurrences of wildfires in the Amazon Basin respond most strongly to climate change and play an increasingly important role in changing the global climate.

Dust transport and spatial distribution are poorly represented in current global climate models (GCMs) including the Community Atmosphere Model version 5 (CAM5). Particularly, models lack explicit representation of super-coarse dust, which may have important implications for dust radiative forcing and impacts on biogeochemistry. A nine-mode version of the modal aerosol model (MAM9) has been developed to address these issues. In this new aerosol scheme, four dust modes have been designed to treat dust particles of sizes up to 20 mu m. The MAM9-simulated results are compared with those from the default four-mode version of MAM (MAM4) and also with the in situ surface measurements of dust concentration and deposition flux, satellite-retrieved dust extinction profile, and in situ vertical measurements of dust concentrations from the NASA Atmosphere Tomography Mission (ATom). Overall, MAM9 improves the dust representation in remote regions while maintaining reasonably good results near the dust source regions. In addition, MAM9 reduces the fine dust burden and increases the coarse dust burden globally. The increased coarse dust burden has slightly increased the dust direct radiative effect by 0.01 W m(-2) while it enhanced dust indirect radiative effect by 0.36 W m(-2), globally.

Snow and ice albedo reduction due to deposition of absorbing particles (snow darkening effect [SDE]) warms the Earth system and is largely attributed to black carbon (BC) and dust. Absorbing organic aerosol (BrC) also contributes to SDE but has received less attention due to uncertainty and challenges in model representation. This work incorporates the SDE of absorbing organic aerosol (BrC) from biomass burning and biofuel sources into the Snow Ice and Aerosol Radiative (SNICAR) model within a variant of the Community Earth System Model. Additionally, 12 different emission regions of BrC and BC from biomass burning and biofuel sources are tagged to quantify the relative contribution to global and regional SDE. BrC global SDE (0.021-0.056 Wm(-2) over land area and 0.0061-0.016 Wm(-2) over global area) is larger than other model estimates, corresponding to 37%-98% of the SDE from BC. When compared to observations, BrC simulations have a range in median bias (-2.5% to +21%), with better agreement in the simulations that include BrC photochemical bleaching. The largest relative contributions to global BrC SDE are traced to Northern Asia (23%-31%), Southeast Asia (16%-21%), and South Africa (13%-17%). Transport from Southeast Asia contributes nearly half of the regional BrC SDE in Antarctica (0.084-0.3 Wm(-2)), which is the largest regional input to global BrC SDE. Lower latitude BrC SDE is correlated with snowmelt, in-snow BrC concentrations, and snow cover fraction, while polar BrC SDE is correlated with surface insolation and snowmelt. This indicates the importance of in-snow processes and snow feedbacks on modeled BrC SDE.

Biomass burning contributes considerably to black carbon (BC) emissions in South Asia, but such emissions have not been linked with the Green Revolution (GR) which has enabled substantial crop production growth in South Asian countries, India in particular. Here, we use an Earth system model to quantify climate change through the direct radiative forcing (DRF) by agriculture-emitted BC associated with the GR in India. We show that the BC DRF in India has increased significantly since the GR, especially during the post-GR period. The estimated BC DRF in India rose from +0.197 W/m(2) in 1961 to +0.805 W/m(2) in 2011; this represents a fourfold increase in DRF since the onset of the GR. The contribution of BC DRF by India's intensive agriculture to the global BC forcing also increased from 2.6% to 4.4% during the GR. Our results reveal that increasing BC emissions associated with the GR raises the importance of emission mitigation from agriculture source.

A version of the Community Earth System Model modified at the North Carolina State University (CESM-NCSU) is used to simulate the current and future atmosphere following the representative concentration partway scenarios for stabilization of radiative forcing at 4.5 W m(-2) (RCP4.5) and radiative forcing of 8.5 W m(-2) (RCP8.5). Part I describes the results from a comprehensive evaluation of current decadal simulations. Radiation and most meteorological variables are well simulated in CESM-NCSU. Cloud parameters are not as well simulated due in part to the tuning of model radiation and general biases in cloud variables common to all global chemistry-climate models. The concentrations of most inorganic aerosol species (i.e., SO42-, NH4+, and NO3-) are well simulated with normalized mean biases (NMBs) typically less than 20%. However, some notable exceptions are European NH4+, which is overpredicted by 33.0-42.2% due to high NH3 emissions and irreversible coarse mode condensation, and Cl-, that is negatively impacted by errors in emissions driven by wind speed and overpredicted HNO3. Carbonaceous aerosols are largely underpredicted following the RCP scenarios due to low emissions of black carbon, organic carbon, and anthropogenic volatile compounds in the RCP inventory and efficient wet removal. This results in underpredictions of PM2.5 and PM10 by 6.4-55.7%. The column mass abundances are reasonably well simulated. Larger biases occur in surface mixing ratios of trace gases in CESM-NCSU, likely due to numerical diffusion from the coarse grid spacing of the CESM-NCSU simulations or errors in the magnitudes and vertical structure of emissions. This is especially true for SO2 and NO2. The mixing ratio of O-3 is overpredicted by 38.9-76.0% due to the limitations in the O-3 deposition scheme used in CESM and insufficient titration resulted from large underpredictions in NO2. Despite these limitations, CESM-NCSU reproduces reasonably well the current atmosphere in terms of radiation, clouds, meteorology, trace gases, aerosols, and aerosol-cloud interactions, making it suitable for future climate simulations. (C) 2016 Elsevier Ltd. All rights reserved.