ALBERT

Description: We apply the NCAR CAM5-Chem global aerosol-climate model to quantify the net global radiative effects of black and organic carbon aerosols from global and Indian solid fuel cookstove emissions for the year 2010. Our assessment accounts for the direct radiative effects, changes to cloud albedo and lifetime (aerosol indirect effect, AIE), impacts on clouds via the vertical temperature profile (semi-direct effect, SDE) and changes in the surface albedo of snow and ice (surface albedo effect). In addition, we provide the first estimate of household solid fuel black carbon emission effects on ice clouds. Anthropogenic emissions are from the IIASA GAINS ECLIPSE V5a inventory. A global dataset of black carbon (BC) and organic aerosol (OA) measurements from surface sites and aerosol optical depth (AOD) from AERONET is used to evaluate the model skill. Compared with observations, the model successfully reproduces the spatial patterns of atmospheric BC and OA concentrations, and agrees with measurements to within a factor of 2. Globally, the simulated AOD agrees well with observations, with a normalized mean bias close to zero. However, the model tends to underestimate AOD over India and China by  ∼  19 ± 4 % but overestimate it over Africa by  ∼  25 ± 11 % (± represents modeled temporal standard deviations for n = 5 run years). Without BC serving as ice nuclei (IN), global and Indian solid fuel cookstove aerosol emissions have net global cooling radiative effects of −141 ± 4 mW m−2 and −12 ± 4 mW m−2, respectively (± represents modeled temporal standard deviations for n = 5 run years). The net radiative impacts are dominated by the AIE and SDE mechanisms, which originate from enhanced cloud condensation nuclei concentrations for the formation of liquid and mixed-phase clouds, and a suppression of convective transport of water vapor from the lower troposphere to the upper troposphere/lower stratosphere that in turn leads to reduced ice cloud formation. When BC is allowed to behave as a source of IN, the net global radiative impacts of the global and Indian solid fuel cookstove emissions range from −275 to +154 mW m−2 and −33 to +24 mW m−2, with globally averaged values of −59 ± 215 and 0.3 ± 29 mW m−2, respectively. Here, the uncertainty range is based on sensitivity simulations that alter the maximum freezing efficiency of BC across a plausible range: 0.01, 0.05 and 0.1. BC–ice cloud interactions lead to substantial increases in high cloud (

Description: We apply the NCAR CAM5-Chem global aerosol–climate model to quantify the net global radiative effects of black and organic carbon aerosols from global and Indian solid fuel cookstove emissions for the year 2010. Our updated assessment accounts for the direct radiative effects, changes to cloud albedo and lifetime (aerosol indirect effect, AIE), impacts on clouds via the vertical temperature profile (semi-direct effect, SDE), and changes in the surface albedo of snow and ice (surface albedo effect). In addition, we provide the first estimate of household solid fuel black carbon emission effects on ice clouds. Anthropogenic emissions are from the IIASA GAINS ECLIPSE V5a inventory. A global dataset of black carbon (BC) and organic aerosol (OA) measurements from surface sites and aerosol optical depth (AOD) from AERONET is used to evaluate the model skill. Compared with observations, the model successfully reproduces the spatial patterns of atmospheric BC and OA concentrations, and agrees with measurements to within a factor of 2. Globally, the simulated AOD agrees well with observations, with normalized mean bias close to zero. However, the model tends to underestimate AOD over India and China by ~ 19 % but overestimate it over Africa by ~ 25 %. Without BC serving as ice nuclei (IN), global and Indian solid fuel cookstove aerosol emissions have a net cooling impact on global climate of −141 ± 4 mW m−2 and −12 ± 4 mW m−2, respectively. The net radiative impacts are dominated by the AIE and SDE mechanisms, which originate from enhanced cloud condensation nuclei concentrations for the formation of liquid and mixed-phase clouds, and a suppression of convective transport of water vapor from the lower troposphere to the upper troposphere/lower stratosphere that in turn leads to reduced ice cloud formation. When BC is allowed to behave as a source of IN, the net global climate impacts of the global and Indian solid fuel cookstove emissions range from −260 to +135 mW m−2 and −33 to +24 mW m−2, with globally averaged values −51 ± 210 and 0.3 ± 29 mW m−2 respectively. The uncertainty range is calculated from sensitivity simulations that alter the maximum freezing efficiency of BC across a plausible range: 0.01, 0.05 and 0.1. BC–ice cloud interactions lead to substantial increases in high cloud (

Description: Methane (CH4) is both a greenhouse gas and a precursor of tropospheric ozone, making it an important focus of chemistry–climate interactions. Methane has both anthropogenic and natural emission sources, and reaction with the atmosphere's principal oxidizing agent, the hydroxyl radical (OH), is the dominant tropospheric loss process of methane. The tight coupling between methane and OH abundances drives indirect linkages between methane and other short-lived air pollutants and prompts the use of interactive methane chemistry in global chemistry–climate modeling. In this study, an updated contemporary inventory of natural methane emissions and the soil sink is developed using an optimization procedure that applies published emissions data to the NASA GISS ModelE2-Yale Interactive terrestrial Biosphere (ModelE2-YIBs) global chemistry–climate model. Methane observations from the global surface air-sampling network of the Earth System Research Laboratory (ESRL) of the U.S. National Oceanic and Atmospheric Administration (NOAA) are used to guide refinement of the natural methane inventory. The optimization process indicates global annual wetland methane emissions of 140TgCH4y−1. The updated inventory includes total global annual methane emissions from natural sources of 181TgCH4y−1 and a global annual methane soil sink of 60TgCH4y−1. An interactive-methane simulation is run using ModelE2-YIBs, applying dynamic methane emissions and the updated natural methane emissions inventory that results from the optimization process. The simulated methane chemical lifetime of 10.4 ± 0.1 years corresponds well to observed lifetimes. The simulated year 2005 global-mean surface methane concentration is 1.1% higher than the observed value from the NOAA ESRL measurements. Comparison of the simulated atmospheric methane distribution with the NOAA ESRL surface observations at 50 measurement locations finds that the simulated annual methane mixing ratio is within 1 % (i.e., +1% to −1%) of the observed value at 76% of locations. Considering the 50 stations, the mean relative difference between the simulated and observed annual methane mixing ratio is a model overestimate of only 0.5%. Comparison of simulated annual column-averaged methane concentrations with SCIAMACHY satellite retrievals provides an independent post-optimization evaluation of modeled methane. The comparison finds a slight model underestimate in 95% of grid cells, suggesting that the applied methane source in the model is slightly underestimated or the model's methane sink strength is slightly too strong outside of the surface layer. Overall, the strong agreement between simulated and observed methane lifetimes and concentrations indicates that the ModelE2-YIBs chemistry–climate model is able to capture the principal processes that control atmospheric methane.

Description: Methane (CH4) is both a greenhouse gas and a precursor of tropospheric ozone, making it an important focus of chemistry–climate interactions. Methane has both anthropogenic and natural emission sources, and reaction with the atmosphere's principal oxidizing agent, the hydroxyl radical (OH), is the dominant tropospheric loss process of methane. The tight coupling between methane and OH abundances drives indirect linkages between methane and other short-lived air pollutants and prompts the use of interactive methane chemistry in global chemistry–climate modeling. In this study, an updated contemporary inventory of natural methane emissions and the soil sink is developed using an optimization procedure that applies published emissions data to the NASA GISS ModelE2-Yale Interactive terrestrial Biosphere (ModelE2-YIBs) global chemistry–climate model. Methane observations from the global surface air-sampling network of the Earth System Research Laboratory (ESRL) of the US National Oceanic and Atmospheric Administration (NOAA) are used to guide refinement of the natural methane inventory. The wetland methane flux is calculated as a best fit; thus, the accuracy of this derived flux assumes accurate simulation of methane chemical loss in the atmosphere and accurate prescription of the other methane fluxes (anthropogenic and natural). The optimization process indicates global annual wetland methane emissions of 140 Tg CH4 yr−1. The updated inventory includes total global annual methane emissions from natural sources of 181 Tg CH4 yr−1 and a global annual methane soil sink of 60 Tg CH4 yr−1. An interactive methane simulation is run using ModelE2-YIBs, applying dynamic methane emissions and the updated natural methane emissions inventory that results from the optimization process. The simulated methane chemical lifetime of 10.4±0.1 years corresponds well to observed lifetimes. The simulated year 2005 global-mean surface methane concentration is 1.1 % higher than the observed value from the NOAA ESRL measurements. Comparison of the simulated atmospheric methane distribution with the NOAA ESRL surface observations at 50 measurement locations finds that the simulated annual methane mixing ratio is within 1 % (i.e., +1 % to −1 %) of the observed value at 76 % of locations. Considering the 50 stations, the mean relative difference between the simulated and observed annual methane mixing ratio is a model overestimate of only 0.5 %. Comparison of simulated annual column-averaged methane concentrations with SCIAMACHY satellite retrievals provides an independent post-optimization evaluation of modeled methane. The comparison finds a slight model underestimate in 95 % of grid cells, suggesting that the applied methane source in the model is slightly underestimated or the model's methane sink strength is slightly too strong outside of the surface layer. Overall, the strong agreement between simulated and observed methane lifetimes and concentrations indicates that the ModelE2-YIBs chemistry–climate model is able to capture the principal processes that control atmospheric methane.