Recent findings on the effects ofaerosols on the climate
Bjørn H. Samset
Research Director, CICERO Center for International Climate Researchb.h.samset@cicero.oslo.no

Conclusions• Anthropogenic aerosols currently mask at least 0.5°C of global warming• Aerosol climate impacts (temperature, precipitation and extremes) are regionallyheterogeneous, and follow different patterns than those from greenhouse gases – and fromemissions emission patterns• Sulfate aerosols (from SO2 emissions) are the main temperature driver– …with aerosol-cloud interactions representing a major source of uncertainty• Black carbon (BC) has a lower climate impact (and radiative forcing) than previously thought– …with emission estimates representing a major source of uncertainty• Organic carbon (OC) emissions are moderately cooling– …with emission estimates and brown carbon (BrC) representing major sources ofuncertainty• Aerosols (very likely) affect precipitation, globally (ITCZ, surface cooling, atmosphericstability) and regionally (monsoon patterns, mediterranean and South African drying)• Present and future air quality measures will affect the climate, but it’s far from clear just how
and how much
2

The climate impact of aerosols (here: BC)
Breaking it down:
Em × LT × MAC × RFE = RF
AAOD × RFE = RF
RF → dT, dPEm
LTMAC
RFE

==
==Emissions
Lifetime / residence time
Mass absorption coefficient
Radiative forcing efficiency

AAOD= Aerosol abosrption optical depth

RF= Radiative forcing

dTdP= Surface temperature change= Precipitation change
Hoesly et al. 2018 / Myhre et al. 2013 / Stjern et al. 2017 /IPCC AR5 WG13

Samset et al., 2018, GRLSamset, 2018, ScienceBaker et al., 2015, ACP

The climate impact of present dayemissions of anthropogenic aerosols

4

Stjern et al., 2016, ACPSamset et al., 2018, GRLAerosol impacts follow a different pattern toGHG, due – partly – to long range transport

5Sulfate• Emissions: Relatively well characterized• Climate impact: Uncertain, due to aerosol-cloud-interactions• Several groups working to unify model estimates withobservational estimates

Gryspeerdt et al. 2018 PNAS

McCoy et al. 2017 JGRAMalavelle et al. 2017 Nature6

Organic aerosol

Zhang et al. 2017 NGeo

• Broad term (primary organic aerosols, secondary organics, broad rangeof sources, chemistry and transport, lack of observations…)• Thorough multi-model inter- and observational comparison:
Tsigaridis et al. 2014 ACP• Recent topic: Brown Carbon
Prevalent, also in uppertroposphere:• However, BrC only weakly modifies global negative RF from OA in moststudies. SOA scattering dominates POA, due to altitude. (Lund et al. 2018, ACPD)
7

The climate impact of aerosols (here: BC)
Breaking it down:
Em × LT × MAC × RFE = RF
AAOD × RFE = RF
RF → dT, dP
EmLTMAC
RFE====Emissions
Lifetime / residence time
Mass absorption coefficient
Radiative forcing efficiency

AAOD= Aerosol abosrption optical depth

RF= Radiative forcing

dTdP= Surface temperature change= Precipitation change
Hoesly et al. 2018 / Myhre et al. 2013 / Stjern et al. 2017 /IPCC AR5 WG1

8Emissions keep increasing

Em × LT × MAC × RFE = RF → dT, dP

SPEW (Bond et al., 2007), J08 (Junker and Liousse, 2008), ACCMIP and MACCity for the Atmospheric Chemistry and Climate Model Intercomparison Project (Lamarque et al., 2010; Granier et al., 2011),
CMIP6 (Coupled Model Intercomparison Project Phase 6) (Hoesly et al., 2017), PKU-BC (Wang et al., 2014), K17 for (Klimont et al, 2017), GFED2 (Global Fire Emissions Database version 2) (van der Werfet al., 2006), GFED3 (van der Werf et al., 2006), GFED4 (Randerson et al., 2015), GICC (Le progamme Gestion et Impacts du Changement climatique) (Mieville et al., 2010) and RETRO (REanalysis of theTROpospheric chemical composition over the past 40 years) (Schultz et al., 2008). For the PKU-BC inventory, annual BC emissions and uncertainties are shown as median values (red line) and interquartile ranges (shaded area) from a Monte Carlo simulation.

Many thanks to prof. Rong Wang for this compilation.
NB: Cohen and Wang 2014, Kalman filter estimate, 17.8 ± 5.6 Tg/yr,
9Forcing efficiency:

Em × LT × MAC × RFE = RF → dT, dP(D)RF is not temperature

Temperatur change [K]Cloud fraction change [%]ERF = direct RF + rapid adjustments

Time [hours]

Time [hours]

10Temperature response…
…seems moderateEm × LT × MAC × RFE = RF → dT, dP+ Baker 2015, ACP

11

Precipitation impact?
Rapid adjustments and weak temperature
response make BC mess up global modelling!

Em × LT × MAC × RFE = RF → dT, dP
Samset 2018, npj Clim. Atm. Sci.

Samset and Myhre 2015, JGRA

+ Stjern 2017, JGRA

Mediterranean: See Tao et al. 2018, ACPD
Regional response: See Liu 2018, JCLIM
Samset 2016 Baker 2015
GRLACP

12

Krishnan et al. 2016 Clim. Dyn.

Hodnebrog et al. 2016 NComm• ITCZ shift• Asian Monsoon slowdown• Southern African andMediterranean drying•…

Tang et al. 2018 ACPD

Regional effects of anthropogenic aerosols

13Conclusions• Anthropogenic aerosols currently mask at least 0.5°C of global warming• Aerosol climate impacts (temperature, precipitation and extremes) are regionallyheterogeneous, and follow different patterns than those from greenhouse gases – and fromemissions emission patterns• Sulfate aerosols (from SO2 emissions) are the main temperature driver– …with aerosol-cloud interactions representing a major source of uncertainty• Black carbon (BC) has a lower climate impact (and radiative forcing) than previously thought– …with emission estimates representing a major source of uncertainty• Organic carbon (OC) emissions are moderately cooling– …with emission estimates and brown carbon (BrC) representing major sources ofuncertainty• Aerosols (very likely) affect precipitation, globally (ITCZ, surface cooling, atmosphericstability) and regionally (monsoon patterns, mediterranean and South African drying)• Present and future air quality measures will affect the climate, but it’s far from clear just how
and how much14

cicero_klima
cicero.oslo.no
cicerosenterforklimaforskning

MISR

OMI

MODIS Terra MODIS Aqua

Aerosol optical depth

Something funny…

16