scholarly journals Impacts of Aerosol Dry Deposition on Black Carbon Spatial Distributions and Radiative Effects in the Community Atmosphere Model CAM5

2018 ◽  
Vol 10 (5) ◽  
pp. 1150-1171 ◽  
Author(s):  
Mingxuan Wu ◽  
Xiaohong Liu ◽  
Leiming Zhang ◽  
Chenglai Wu ◽  
Zheng Lu ◽  
...  
2018 ◽  
Author(s):  
Hunter Brown ◽  
Xiaohong Liu ◽  
Yan Feng ◽  
Yiquan Jiang ◽  
Mingxuan Wu ◽  
...  

Abstract. A recent development in the representation of aerosols in climate models is the realization that some components of organic aerosol (OA), emitted from biomass and biofuel burning, can have a significant contribution to short-wave radiation absorption in the atmosphere. The absorbing fraction of OA is referred to as brown carbon (BrC). This study introduces one of the first implementations of BrC into the Community Atmosphere Model version 5 (CAM5), using a parameterization for BrC absorptivity described in Saleh et al. (2014). 9-year experiments are run (2003–2011) with prescribed emissions and sea surface temperatures to analyze the effect of BrC in the atmosphere. Model validation is conducted via model comparison to single-scatter albedo and aerosol optical depth from the Aerosol Robotic Network (AERONET). This comparison reveals a model underestimation of SSA in biomass burning regions for both default and BrC model runs, while a comparison between AERONET and model absorption Angstrom exponent shows a marked improvement with BrC implementation. Global annual average radiative effects are calculated due to aerosol-radiation interactions (REari; 0.13 ± 0.01 W m−2) and aerosol-cloud interactions (REaci; 0.01 ± 0.04 W m−2). REari is similar to other studies' estimations of BrC direct radiative effect, while REaci indicates a global reduction in low clouds due to the BrC semi-direct effect. The mechanisms for these physical changes are investigated and found to correspond with changes in global circulation patterns. Comparisons of BrC implementation approaches find that this implementation predicts a lower BrC REari in the Arctic regions than previous studies with CAM5. Implementation of BrC bleaching effect shows a significant reduction in REari (0.06 ± 0.008 W m−2). Also, variations in OA density can lead to differences in REari and REaci, indicating the importance of specifying this property when estimating the BrC radiative effects and when comparing similar studies.


2013 ◽  
Vol 118 (10) ◽  
pp. 4657-4669 ◽  
Author(s):  
Po-Lun Ma ◽  
Philip J. Rasch ◽  
Hailong Wang ◽  
Kai Zhang ◽  
Richard C. Easter ◽  
...  

2019 ◽  
Vol 32 (14) ◽  
pp. 4145-4165 ◽  
Author(s):  
Elizabeth Berry ◽  
Gerald G. Mace ◽  
Andrew Gettelman

Abstract The distribution of clouds and their radiative effects in the Community Atmosphere Model, version 5 (CAM5), are compared to A-Train satellite data in Southeast Asia during the summer monsoon. Cloud radiative kernels are created based on populations of observed and modeled clouds separately in order to compare the sensitivity of the TOA radiation to changes in cloud fraction. There is generally good agreement between the observation- and model-derived cloud radiative kernels for most cloud types, meaning that the clouds in the model are heating and cooling like clouds in nature. Cloud radiative effects are assessed by multiplying the cloud radiative kernel by the cloud fraction histogram. For ice clouds in particular, there is good agreement between the model and observations, with optically thin cirrus producing a moderate warming effect and cirrostratus producing a slight cooling effect, on average. Consistent with observations, the model also shows that the median value of the ice water path (IWP) distribution, rather than the mean, is a more representative measure of the ice clouds that are responsible for heating. In addition, in both observations and the model, it is cirrus clouds with an IWP of 20 g m−2 that have the largest warming effect in this region, given their radiative heating and frequency of occurrence.


2018 ◽  
Vol 18 (24) ◽  
pp. 17745-17768 ◽  
Author(s):  
Hunter Brown ◽  
Xiaohong Liu ◽  
Yan Feng ◽  
Yiquan Jiang ◽  
Mingxuan Wu ◽  
...  

Abstract. A recent development in the representation of aerosols in climate models is the realization that some components of organic aerosol (OA), emitted from biomass and biofuel burning, can have a significant contribution to shortwave radiation absorption in the atmosphere. The absorbing fraction of OA is referred to as brown carbon (BrC). This study introduces one of the first implementations of BrC into the Community Atmosphere Model version 5 (CAM5), using a parameterization for BrC absorptivity described in Saleh et al. (2014). Nine-year experiments are run (2003–2011) with prescribed emissions and sea surface temperatures to analyze the effect of BrC in the atmosphere. Model validation is conducted via model comparison to single-scatter albedo and aerosol optical depth from the Aerosol Robotic Network (AERONET). This comparison reveals a model underestimation of single scattering albedo (SSA) in biomass burning regions for both default and BrC model runs, while a comparison between AERONET and the model absorption Ångström exponent shows a marked improvement with BrC implementation. Global annual average radiative effects are calculated due to aerosol–radiation interaction (REari; 0.13±0.01 W m−2) and aerosol–cloud interaction (REaci; 0.01±0.04 W m−2). REari is similar to other studies' estimations of BrC direct radiative effect, while REaci indicates a global reduction in low clouds due to the BrC semi-direct effect. The mechanisms for these physical changes are investigated and found to correspond with changes in global circulation patterns. Comparisons of BrC implementation approaches find that this implementation predicts a lower BrC REari in the Arctic regions than previous studies with CAM5. Implementation of BrC bleaching effect shows a significant reduction in REari (0.06±0.008 W m−2). Also, variations in OA density can lead to differences in REari and REaci, indicating the importance of specifying this property when estimating the BrC radiative effects and when comparing similar studies.


2015 ◽  
Vol 15 (9) ◽  
pp. 12957-13000
Author(s):  
R. Zhang ◽  
H. Wang ◽  
D. A. Hegg ◽  
Y. Qian ◽  
S. J. Doherty ◽  
...  

Abstract. The Community Atmosphere Model (CAM5), equipped with a technique to tag black carbon (BC) emissions by source regions and types, has been employed to establish source-receptor relationships for atmospheric BC and its deposition to snow over Western North America. The CAM5 simulation was conducted with meteorological fields constrained by reanalysis for year 2013 when measurements of BC in both near-surface air and snow are available for model evaluation. We find that CAM5 has a significant low bias in predicted mixing ratios of BC in snow but only a small low bias in predicted atmospheric concentrations over the Northwest USA and West Canada. Even with a strong low bias in snow mixing ratios, radiative transfer calculations show that the BC-in-snow darkening effect is substantially larger than the BC dimming effect at the surface by atmospheric BC. Local sources contribute more to near-surface atmospheric BC and to deposition than distant sources, while the latter are more important in the middle and upper troposphere where wet removal is relatively weak. Fossil fuel (FF) is the dominant source type for total column BC burden over the two regions. FF is also the dominant local source type for BC column burden, deposition, and near-surface BC, while for all distant source regions combined the contribution of biomass/biofuel (BB) is larger than FF. An observationally based Positive Matrix Factorization (PMF) analysis of the snow-impurity chemistry is conducted to quantitatively evaluate the CAM5 BC source-type attribution. While CAM5 is qualitatively consistent with the PMF analysis with respect to partitioning of BC originating from BB and FF emissions, it significantly underestimates the relative contribution of BB. In addition to a possible low bias in BB emissions used in the simulation, the model is likely missing a significant source of snow darkening from local soil found in the observations.


2015 ◽  
Vol 15 (22) ◽  
pp. 12805-12822 ◽  
Author(s):  
R. Zhang ◽  
H. Wang ◽  
D. A. Hegg ◽  
Y. Qian ◽  
S. J. Doherty ◽  
...  

Abstract. The Community Atmosphere Model (CAM5), equipped with a technique to tag black carbon (BC) emissions by source regions and types, has been employed to establish source–receptor relationships for atmospheric BC and its deposition to snow over western North America. The CAM5 simulation was conducted with meteorological fields constrained by reanalysis for year 2013 when measurements of BC in both near-surface air and snow are available for model evaluation. We find that CAM5 has a significant low bias in predicted mixing ratios of BC in snow but only a small low bias in predicted atmospheric concentrations over northwestern USA and western Canada. Even with a strong low bias in snow mixing ratios, radiative transfer calculations show that the BC-in-snow darkening effect is substantially larger than the BC dimming effect at the surface by atmospheric BC. Local sources contribute more to near-surface atmospheric BC and to deposition than distant sources, while the latter are more important in the middle and upper troposphere where wet removal is relatively weak. Fossil fuel (FF) is the dominant source type for total column BC burden over the two regions. FF is also the dominant local source type for BC column burden, deposition, and near-surface BC, while for all distant source regions combined the contribution of biomass/biofuel (BB) is larger than FF. An observationally based positive matrix factorization (PMF) analysis of the snow-impurity chemistry is conducted to quantitatively evaluate the CAM5 BC source-type attribution. While CAM5 is qualitatively consistent with the PMF analysis with respect to partitioning of BC originating from BB and FF emissions, it significantly underestimates the relative contribution of BB. In addition to a possible low bias in BB emissions used in the simulation, the model is likely missing a significant source of snow darkening from local soil found in the observations.


2018 ◽  
Vol 10 (10) ◽  
pp. 2514-2526 ◽  
Author(s):  
Yuan Wang ◽  
Po‐Lun Ma ◽  
Jianfei Peng ◽  
Renyi Zhang ◽  
Jonathan H. Jiang ◽  
...  

2020 ◽  
Vol 33 (14) ◽  
pp. 6187-6203
Author(s):  
Elizabeth Berry ◽  
Gerald G. Mace ◽  
Andrew Gettelman

AbstractUsing information from the A-Train satellites, the properties and radiative effects of eastern Pacific Ocean boundary layer clouds are evaluated in the Community Atmosphere Model, version 5 (CAM5), from the summer of 2007 and 2008. The cloud microphysical properties are inferred using measurements from CloudSat and CALIPSO (CC) that are then used to calculate the broadband radiative flux profiles. Accounting appropriately for sampling differences between the measurements and the simulation, evidence of the “too few, too bright” low cloud bias is found in CAM5. Single-layer low clouds have a frequency of occurrence of 42% from CC, as compared with just 29% in CAM5, and the averaged cloud radiative kernel (CRK) for the model shows stronger cooling. For stratocumulus in particular, the cooling in the model CRK is larger by a factor of 2 relative to the observations, implying an overly sensitive tropical low cloud feedback. Differences in the day/night occurrence of stratocumulus help to explain some of the difference in the CRK. The cloud-type microphysics for liquid clouds is represented reasonably well by the model, with a tendency for smaller water paths and smaller effective radii. Overall, the occurrence and CRK have partially compensating errors such that the net cooling at the top of the atmosphere for eastern Pacific low clouds is −43 W m−2 in CAM5, as compared with −32 W m−2 from CC. The cooling effect in the model is accomplished by fewer low clouds with a narrower range of properties, as compared with more clouds with a broader range of properties in the observation-based dataset.


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