Vertical dependence of black carbon, sulphate and biomass burning aerosol radiative forcing

2011 ◽  
Vol 38 (24) ◽  
pp. n/a-n/a ◽  
Author(s):  
Bjørn H. Samset ◽  
Gunnar Myhre
Keyword(s):  
Black Carbon ◽  
Biomass Burning ◽  
Radiative Forcing ◽  
Aerosol Radiative Forcing ◽  
Biomass Burning Aerosol ◽  
Aerosol Radiative

Aerosol radiative forcing due to enhanced black carbon at an urban site in India

2002 ◽  
Vol 29 (18) ◽  
pp. 27-1-27-4 ◽  
Author(s):  
S. Suresh Babu ◽  
S. K. Satheesh ◽  
K. Krishna Moorthy
Keyword(s):  
Black Carbon ◽  
Radiative Forcing ◽  
Urban Site ◽  
Aerosol Radiative Forcing ◽  
Aerosol Radiative

Improved estimates of future fire emissions under CMIP6 scenarios and implications for aerosol radiative forcing

2021 ◽  
Author(s):  
Matthew Kasoar ◽  
Douglas Hamilton ◽  
Daniela Dalmonech ◽  
Stijn Hantson ◽  
Gitta Lasslop ◽  
...  
Keyword(s):  
Machine Learning ◽  
Biomass Burning ◽  
Radiative Forcing ◽  
Learning Methods ◽  
Aerosol Radiative Forcing ◽  
Fire Emissions ◽  
Machine Learning Methods ◽  
The Tropics ◽  
In Fire ◽  
Aerosol Radiative

<p>The CMIP6 Shared Socioeconomic Pathway (SSP) scenarios include projections of future changes in anthropogenic biomass-burning.  Globally, they assume a decrease in total fire emissions over the next century under all scenarios.  However, fire regimes and emissions are expected to additionally change with future climate, and the methodology used to project fire emissions in the SSP scenarios is opaque.</p><p>We aim to provide a more traceable estimate of future fire emissions under CMIP6 scenarios and evaluate the impacts for aerosol radiative forcing.  We utilise interactive wildfire emissions from four independent land-surface models (CLM5, JSBACH3.2, LPJ-GUESS, and ISBA-CTRIP) used within CMIP6 ESMs, and two different machine-learning methods (a random forest, and a generalised additive model) trained on historical data, to predict year 2100 biomass-burning aerosol emissions consistent with the CMIP6-modelled climate for three different scenarios: SSP126, SSP370, and SSP585.  This multi-method approach provides future fire emissions integrating information from observations, projections of climate, socioeconomic parameters and changes in vegetation distribution and fuel loads.</p><p>Our analysis shows a robust increase in fire emissions for large areas of the extra-tropics until the end of this century for all methods.  Although this pattern was present to an extent in the original SSP projections, both the interactive fire models and machine-learning methods predict substantially higher increases in extra-tropical emissions in 2100 than the corresponding SSP datasets.  Within the tropics the signal is mixed. Increases in emissions are largely driven by the temperature changes, while in some tropical areas reductions in fire emissions are driven by human factors and changes in precipitation, with the largest reductions in Africa. The machine-learning methods show a stronger reduction in the tropics than the interactive fire models, however overall there is strong agreement between both the models and the machine-learning methods.</p><p>We then use additional nudged atmospheric simulations with two state-of-the-art composition-climate models, UKESM1 and CESM2, to diagnose the impact of these updated fire emissions on aerosol burden and radiative forcing, compared with the original SSP prescribed emissions.  We provide estimates of future fire radiative forcing, compared to modern-day, under these CMIP6 scenarios which span both the severity of climate change in 2100, and the rate of reduction of other aerosol species.</p>

scholarly journals Role of black carbon mass size distribution in the direct aerosol radiative forcing

2019 ◽  
Vol 19 (20) ◽  
pp. 13175-13188 ◽  
Author(s):  
Gang Zhao ◽  
Jiangchuan Tao ◽  
Ye Kuang ◽  
Chuanyang Shen ◽  
Yingli Yu ◽  
...  
Keyword(s):  
Size Distribution ◽  
Black Carbon ◽  
Radiative Forcing ◽  
Climate Models ◽  
Radiative Effects ◽  
Aerosol Radiative Forcing ◽  
Mass Size Distribution ◽  
Mass Size ◽  
Mixing States ◽  
Aerosol Radiative

Abstract. Large uncertainties exist when estimating radiative effects of ambient black carbon (BC) aerosol. Previous studies about the BC aerosol radiative forcing mainly focus on the BC aerosols' mass concentrations and mixing states, while the effects of BC mass size distribution (BCMSD) were not well considered. In this paper, we developed a method of measuring the BCMSD by using a differential mobility analyzer in tandem with an Aethalometer. A comprehensive method of multiple charging corrections was proposed and implemented in measuring the BCMSD. Good agreement was obtained between the BC mass concentration integrated from this system and that measured in the bulk phase, demonstrating the reliability of our proposed method. Characteristics of the BCMSD and corresponding radiative effects were studied based on a field measurement campaign conducted in the North China Plain by using our own measurement system. Results showed that the BCMSD had two modes and the mean peak diameters of the modes were 150 and 503 nm. The BCMSD of the coarser mode varied significantly under different pollution conditions with peak diameter varying between 430 and 580 nm, which gave rise to significant variation in aerosol bulk optical properties. The direct aerosol radiative forcing was estimated to vary by 8.45 % for different measured BCMSDs of the coarser mode, which shared the same magnitude with the variation associated with assuming different aerosol mixing states (10.5 %). Our study reveals that the BCMSD as well as its mixing state in estimating the direct aerosol radiative forcing matters. Knowledge of the BCMSD should be fully considered in climate models.

scholarly journals Wet removal of black carbon in Asian outflow: Aerosol Radiative Forcing in East Asia (A-FORCE) aircraft campaign

2012 ◽  
Vol 117 (D3) ◽  
pp. n/a-n/a ◽  
Author(s):  
N. Oshima ◽  
Y. Kondo ◽  
N. Moteki ◽  
N. Takegawa ◽  
M. Koike ◽  
...  
Keyword(s):  
East Asia ◽  
Black Carbon ◽  
Radiative Forcing ◽  
Aerosol Radiative Forcing ◽  
Aerosol Radiative ◽  
Wet Removal

Constraining direct aerosol radiative forcing using remote sensing and in-situ constraints

2020 ◽  
Author(s):  
Lucia Timea Deaconu ◽  
Duncan Watson-Parris ◽  
Philip Stier ◽  
Lindsay Lee
Keyword(s):  
Remote Sensing ◽  
Black Carbon ◽  
Optical Depth ◽  
Radiative Forcing ◽  
Removal Rates ◽  
Aerosol Radiative Forcing ◽  
Aerosol Absorption ◽  
Direct Radiative Forcing ◽  
Aerosol Radiative

<p>Absorbing aerosols affect the climate system (radiative forcing, cloud formation, precipitation and more) by strongly absorbing solar radiation, particularly at ultraviolet and visible wavelengths. The environmental impacts of an absorbing aerosol layer are influenced by its single scattering albedo (SSA), the albedo of the underlying surface, and also by the atmospheric residence time and column concentration of the aerosols.</p><p>Black-carbon (BC), the collective term used for strongly absorbing, carbonaceous aerosols, emitted by incomplete combustion of fossil fuel, biofuel and biomass, is a significant contributor to atmospheric absorption and probably a main-driver in inter-model differences and large uncertainties in estimating the aerosol radiative forcing due to aerosol-radiation interaction (RFari). Estimates of BC direct radiative forcing suggest a positive effect of +0.71 Wm<sup>-2</sup> (Bond and Bergstrom (2006)) with large uncertainties [+0.08, +1.27] Wm<sup>-2</sup>. These uncertainties result from poor estimates of BC atmospheric burden (emissions and removal rates) and its radiative properties. The uncertainty in the burden is due to the uncertainty in emissions (7.5 [2, 29] Tg yr<sup>-1</sup>) and lifetime (removal rates). In comparison with the available observations, global climate models (GCMs) tend to under-predict absorption near source (e.g. at AERONET stations), and over-predict concentrations in remote regions (e.g. as measured by aircraft campaigns). This may be due to GCM’s weak emissions at the source, but longer lifetime of aerosols in the atmosphere.</p><p>This study aims to address the parametric uncertainty of GCMs and constrain the direct radiative forcing using a perturbed parameter ensemble (PPE) and a collection of observations, from remote sensing to in-situ measurements. Total atmospheric aerosol extinction is quantified using satellite observations that provide aerosol optical depth (AOD), while the SSA is constrained by the use of high-temporal resolution aerosol absorption optical depth (AAOD) measured with AERONET sun-photometers (for near-source columnar information of aerosol absorption) and airborne black-carbon in-situ measurements collected and synthesised in the Global Aerosol Synthesis and Science Project (GASSP) (for properties of long-range transported aerosols). Measurements from the airborne campaigns ATOM and HIPPO are valuable for constraining aerosol absorption in remote areas, while CLARIFY and ORACLES, that were employed over Southeast Atlantic, are considered in our study for near source observations of biomass burning aerosols transported over the bright surface of stratocumulus clouds.</p><p>Using the PPE to explore the uncertainties in the aerosol absorption as well as the dominant emission and removal processes, and by comparing with a variety of observations we have confidence to better constrain the aerosol direct radiative forcing.</p>

scholarly journals Quantifying uncertainty from aerosol and atmospheric parameters and their impact on climate sensitivity

2018 ◽  
Vol 18 (23) ◽  
pp. 17529-17543 ◽  
Author(s):  
Christopher G. Fletcher ◽  
Ben Kravitz ◽  
Bakr Badawy
Keyword(s):  
Black Carbon ◽  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Deep Convection ◽  
Cloud Amount ◽  
Skill Score ◽  
Model Parameters ◽  
Atmospheric Parameters ◽  
Aerosol Radiative Forcing ◽  
Aerosol Radiative

Abstract. Climate sensitivity in Earth system models (ESMs) is an emergent property that is affected by structural (missing or inaccurate model physics) and parametric (variations in model parameters) uncertainty. This work provides the first quantitative assessment of the role of compensation between uncertainties in aerosol forcing and atmospheric parameters, and their impact on the climate sensitivity of the Community Atmosphere Model, Version 4 (CAM4). Running the model with prescribed ocean and ice conditions, we perturb four parameters related to sulfate and black carbon aerosol radiative forcing and distribution, as well as five atmospheric parameters related to clouds, convection, and radiative flux. In this experimental setup where aerosols do not affect the properties of clouds, the atmospheric parameters explain the majority of variance in climate sensitivity, with two parameters being the most important: one controlling low cloud amount, and one controlling the timescale for deep convection. Although the aerosol parameters strongly affect aerosol optical depth, their impacts on climate sensitivity are substantially weaker than the impacts of the atmospheric parameters, but this result may depend on whether aerosol–cloud interactions are simulated. Based on comparisons to inter-model spread of other ESMs, we conclude that structural uncertainties in this configuration of CAM4 likely contribute 3 times more to uncertainty in climate sensitivity than parametric uncertainties. We provide several parameter sets that could provide plausible (measured by a skill score) configurations of CAM4, but with different sulfate aerosol radiative forcing, black carbon radiative forcing, and climate sensitivity.

scholarly journals Quantifying uncertainty from aerosol and atmospheric parameters and their impact on climate sensitivity

2018 ◽  
Author(s):  
Christopher G. Fletcher ◽  
Ben Kravitz ◽  
Bakr Badawy
Keyword(s):  
Black Carbon ◽  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Deep Convection ◽  
Cloud Amount ◽  
Model Parameters ◽  
Atmospheric Parameters ◽  
Aerosol Radiative Forcing ◽  
Aerosol Parameters ◽  
Aerosol Radiative

Abstract. Climate sensitivity in Earth System Models (ESMs) is an emergent property that is affected by structural (missing or inaccurate model physics) and parametric (variations in model parameters) uncertainty. This work provides the first quantitative assessment of the role of compensation between uncertainties in aerosol forcing and atmospheric parameters, and their impact on the climate sensitivity of the Community Atmosphere Model, Version 4 (CAM4). Running the model with prescribed ocean and ice conditions, we perturb four parameters related to sulfate and black carbon aerosol radiative forcing and distribution, as well as five atmospheric parameters related to clouds, convection, and radiative flux. The atmospheric parameters explain more than 85 \\% of the variance in climate sensitivity for the ranges of parameters explored here, with two parameters being the most important: one controlling low cloud amount, and one controlling the timescale for deep convection. Although the aerosol parameters strongly affect aerosol optical depth, the effects of these aerosol parameters on climate sensitivity are substantially weaker than the effects of the atmospheric parameters. Based on comparisons to inter-model spread of other ESMs, we conclude that structural uncertainties in this configuration of CAM4 likely contribute three times more to uncertainty in climate sensitivity than parametric uncertainty. We provide several parameter sets that could provide plausible (measured by a skill score) configurations of CAM4, but with different sulfate aerosol radiative forcing, black carbon radiative forcing, and climate sensitivity.

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