Observational Constraints Reduce Estimates of the Global Mean Climate Relevance of Black Carbon

Observational constraints reduce estimates of the global mean climate relevance of black carbon Gunnar Myhre ( [email protected] ) CICERO Center for International Climate Research - Oslo, 0318 Oslo https://orcid.org/0000-0002-4309- 476X Bjørn Samset CICERO Center for International Climate and Environmental Research in Oslo https://orcid.org/0000- 0001-8013-1833 Camilla Weum Stjern Center for International Climate and Environmental Research in Oslo Øivind Hodnebrog CICERO Center for International Climate Research https://orcid.org/0000-0001-5233-8992 Ryan Kramer NASA Christopher Smith University of Leeds https://orcid.org/0000-0003-0599-4633 Piers Forster University of Leeds https://orcid.org/0000-0002-6078-0171 Timothy Andrews Met Oce https://orcid.org/0000-0002-8248-8753 Olivier Boucher Institut Pierre-Simon Laplace, Sorbonne Université/CNRS G Faluvegi Columbia University, New York https://orcid.org/0000-0001-9011-3663 Drew Shindell Duke University https://orcid.org/0000-0003-1552-4715 Alf Kirkevåg Norwegian Meteorological Institute Trond Iversen Norwegian Meteorological Institute Dirk Olivie Norwegian Meteorological Institute Philip Stier University of Oxford https://orcid.org/0000-0002-1191-0128 Duncan Watson-Parris University of Oxford https://orcid.org/0000-0002-5312-4950 Article Keywords: black carbon (BC), climate effects, global warming Posted Date: July 29th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-691895/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License 1 Observational constraints reduce 2 estimates of the global mean climate 3 relevance of black carbon 4 5 Gunnar Myhre1*, Bjørn Samset1, Camilla Weum Stjern1, Øivind Hodnebrog1, Ryan Kramer2, 6 Chris Smith3.4, Timothy Andrews5, Olivier Boucher6, Greg Faluvegi7,8, Piers M. Forster3, 7 Trond Iversen9, Alf Kirkevåg9, Dirk Olivié9, Drew Shindell10, Philip Stier11, Duncan Watson- 8 Parris11 9 10 1CICERO Center for International Climate Research, Oslo, Norway 11 2NASA Goddard Space Flight Center, Earth Sciences Division, Greenbelt, MD, USA 12 3School of Earth and Environment, University of Leeds, Leeds, UK 13 4International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria 14 5Met Office Hadley Centre, Exeter, UK, 15 6Institut Pierre-Simon Laplace, Sorbonne Université/CNRS, Paris, France 16 7Center for Climate System Research, Columbia University, New York, NY, USA 17 8NASA Goddard Institute for Space Studies, New York, NY, USA 18 9Norwegian Meteorological Institute, Oslo, Norway 19 10Nicholas School of the Environment, Duke University, Durham, NC, USA 20 11Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK 21 22 *Corresponding author: [email protected] 23 24 25 How emissions of black carbon (BC) aerosols affect the climate is still uncertain, due to 26 incomplete knowledge of its sources, optical properties and atmospheric processes such as 27 transport, removal and impact on clouds. Here we constrain simulations from four climate 28 models with observations of atmospheric BC concentrations and absorption efficiency, and the 29 most recent emission inventories, to show that the current global mean surface temperature 30 change from anthropogenic BC emissions is likely to be weak at +0.03 ±0.02K. Atmospheric 31 rapid adjustment processes are found to reduce the top of atmosphere radiative imbalance 32 relative to instantaneous radiative forcing (direct aerosol effect) by almost 50% as a multi- 33 model mean. Furthermore, constraining the models to reproduce observational estimates of 34 the atmospheric vertical profile reduces BC effective radiative forcing to 0.08 W m-2, a value 35 more than 50% lower than in unconstrained simulations. Our results imply a need to revisit 36 commonly used climate metrics such as the global warming potential of BC. This value (for a 37 100-year time horizon) reduces from 680 when neglecting rapid adjustments and using an 38 unconstrained BC profile to our best estimate of 160 ±120. 39 1 40 Atmospheric black carbon (BC) aerosols, emitted from incomplete combustion of fossil fuel, 41 biofuel and biomass burning, can absorb incoming solar radiation 1-3, and is generally thought 42 to exert a positive net radiative forcing due to the direct interaction with sunlight. BC 43 shortwave absorption efficiency is highly dependent on the underlying albedo, and is 44 particularly strong over bright surfaces and above clouds 1. Estimates of the direct aerosol 45 effect of BC differ for a variety of reasons related to emissions, absorptive properties, 46 atmospheric abundance, interpretation of observations, and host climate models 2,4. The 47 atmospheric warming from BC alters clouds 5,6, but whether this enhances or counteracts the 48 direct influence on the radiation budget differs between various studies 7,8. The sign of the BC 49 influence on clouds is mainly dependent on whether BC is located above or below clouds 9-11, 50 while the strength of the impact depends on atmospheric conditions and cloud properties 11. 51 Available estimates of the BC induced cloud changes are mainly from models with spatial 52 resolutions ranging from hundreds of kilometers (global scale models) to tens of meters (large 53 eddy simulations) 7,10,12, and are partly based on satellite retrievals 13,14. While most model 54 studies assessing the temperature response from BC have been single-model simulations, two 55 multi-model studies exist 15,16. The direct absorption occurs almost entirely in the solar 56 spectrum but the consequences of the resulting atmospheric heating (e.g., in form of cloud 57 changes) also influences the thermal infrared radiation 17. BC is to a large extent co-emitted 58 with scattering aerosols, where the global overall aerosol cooling effect is stronger in 59 magnitude than the heating from BC 8,18. 60 Underestimation of absorption by BC in global models compared to observations has been 61 extensively discussed 2. The cause is associated with uncertainties in measurements 19 and in 62 model simulations of other aerosol types contributing to absorption, such as dust and 63 absorbing organic aerosols. Nevertheless, a crucial factor for the BC absorption is the mass 64 absorption coefficient, which is likely underestimated by about 25-50% in global climate 65 models 15 compared to regional measurements 20. Furthermore, emissions of BC vary among 66 available datasets 21 and a recent data set indicates higher emissions 22 than used in previous 67 multi-model exercises 8. Recent years, however, have seen a reduction of the BC emission 68 globally 23. Observations show that the concentration of BC in state-of-the-art global models 69 is smaller in the middle and upper troposphere than in the previous generation of global 70 aerosol models 24-26. It has also been shown that not accounting for the representativeness 71 error of observed BC concentrations or optical depths in constrained simulations could result 72 in an important positive bias in the forcing estimate 27. Overall, recent observational 73 constraints strongly indicate that the previous generation of global models on one hand 74 underestimate the climate effect of BC due to low mass absorption coefficient values and 75 emissions inventories, and on the other hand overestimate it by simulating too high BC 76 concentrations in the upper troposphere 28. 77 Effective radiative forcing (ERF), the top-of-atmosphere radiative perturbation due to the 78 instantaneous radiative perturbation (IRF) after subsequent rapid adjustments (short-term 79 atmospheric changes which are independent of surface temperature change) has been 2 80 evaluated to be the most appropriate way to compare various climate drivers in terms of their 81 surface temperature change 8,29,30. BC IRF is a measure of the direct aerosol effect. See Fig 1a 82 for an illustration of IRF, rapid adjustment, ERF and surface temperature change. A radiative 83 imbalance at the top of the atmosphere, quantified by the ERF, causes the climate system to 84 seek a new balance by increasing the global surface temperature, modified by climate 85 feedbacks. A positive value for ERF implies a net gain of energy throughout the climate system. 86 The full equilibrium climate response to an ERF is the difference between two equilibria with 87 and without the imposed ERF. 88 The importance of rapid adjustment for the total influence on the atmospheric energy budget 89 varies strongly among climate drivers, being highly important for absorbing components such 90 as BC 31-33. Smith, et al. 31 showed rapid adjustments to be strongly negative for BC, with cloud 91 changes as one of the main contributors. In this study we provide results from four climate 92 models with BC responses typical for the previous generation of global models. Several of 93 these are models already thoroughly analyzed in previous studies 15,31,34. We then compare 94 these results to new simulations where the vertical profile of BC has been constrained by 95 observations in the upper troposphere (see Methods). Additionally, we constrain the models 96 by observations of the mass absorption coefficient, and by using the most updated BC 97 emission data (see Methods). The scaling of the results by emissions and mass absorption 98 coefficient are applied since the original climate model simulations were performed without 99 the most recent progress in improved scientific knowledge of BC. Supplementary Table 1 100 shows a range of measurement of mass absorption coefficient. The representative observed 101 value of 10 m2 g-1 is higher than the multi-model mean of 7.3 m2 g-1. The main focus in this 102 study is on the radiative impact of BC, and on processes leading to ERF and surface 103 temperature changes due to BC. ERF is calculated from prescribed sea surface temperature 104 simulations and surface temperature changes from fully coupled atmosphere-ocean 105 simulations (see Methods).

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