1

Coupled Chemistry-Climate Effects from 2050 Projected Aviation Emissions Andrew Gettelman1, Chih-Chieh Chen1, Mark Z. Jacobson2, Mary A. Cameron2, Donald J. Wuebbles3, Arezoo Khodayari3,4 1National Center for Atmospheric Research, Boulder, CO, USA 5 2Stanford University, Palo Alto, CA, USA 3University of Illinois, Urbana, IL, USA 4now at California State University Los Angeles, CA, USA

Correspondence to: Andrew Gettelman (andrew@ucar.edu)

Abstract. Analyses of the climate effects of 2050 aviation emissions have been conducted with two coupled Chemistry Climate Models 10

(CCMs) including experiments with coupled ocean models. Results indicate that radiative forcing from projected aircraft emissions causes

statistically significant (at the 95% level) climate signals on regional and global surface temperature for 2050 conditions. Significant

signals emerge only after 20-50 years of simulation. The baseline 2050 aviation emissions scenario projects emissions ~5 times those in

2006. Simulations suggest a corresponding growth in the climate impact of aviation by 2050. Previous uncoupled experiments indicate

positive radiative forcing from contrails reaches +80mWm-2. Enhanced upper tropospheric and lower stratospheric ozone (O3) due to 15

aviation nitrogen oxide (NOx) emissions causes a radiative forcing of +60mWm-2. Changes in methane (CH4) lifetime induced by aviation

are estimated to cause -25mWm-2 of radiative forcing in 2050. Simulations indicate that moderate changes in water vapor emissions from

changes in combustion efficiency will not have significant forcing. Effects due to particles (black carbon and sulfur) included in these

calculations suggest an important role for black carbon (BC) in increasing contrail cirrus ice crystal number, leading to net warming.

Sulfur emissions brighten clouds and provide a net cooling, but this is dependent on uncertain background sulfur levels. Thus alternative 20

aviation fuels with reduced sulfur and BC may alter the future climate impact of aviation, but the magnitude is dependent on specific

processes represented and the background state. Many regions with high regional aviation forcing do not experience net surface

temperature changes because of advective rather than radiative driving of temperatures. Short-lived non-uniform aviation forcing will thus

affect climate differently than uniform forcing in the coupled climate system.

25

1. Introduction

Deleted: P

Deleted:

Deleted: Non-linear e30

Deleted: sign

Deleted: Regional perturbations due to contrail and particulate emissions may result in statistically significant regional surface temperature changes in coupled model simulations in areas near or adjacent to flight corridors, but significant signals only emerge after 35 20-50 years of simulation.

Deleted: Surface temperature signals are not significant globally even in long coupled simulations.

2

Aviation has several important impacts on climate (Wuebbles et al., 2007; and Lee et al, 2009, Brasseur et al., 2008 & 2015). Commercial

aircraft currently emit ~2% (Wuebbles et al., 2007) of global fossil-fuel related emissions of carbon dioxide (CO2). Aircraft also emit

water vapor (H2O), nitrogen oxides (NOx), various organic gases, sulfur dioxide (SO2), black carbon (BC) soot, other organic matter, and

particulate sulfate. These chemicals may alter upper level cloudiness, atmospheric composition, and climate in several different ways.

5

For low enough temperatures and high enough exhaust humidity, aircraft emissions create condensation trails, or contrails (Schmidt, 1941;

Appleman, 1953). If the ambient air is supersaturated with respect to ice, linear contrails may persist for minutes to several hours (Minnis

et al., 1998). The optical thickness of existing cirrus may be enhanced by the additional nuclei resulting from contrails that have aged due

to spreading, shearing, and sublimating (Minnis et al., 1998). Aircraft emission effects on ozone (O3) and methane (CH4) lifetimes may

also have radiative feedbacks on climate (Brasseur et al 2015). 10

Recent work summarized by Brasseur et al (2015) has shown significant effects from aviation aerosols due to (a) aerosol absorption,

termed ‘direct’ radiative effects and (b) modification of contrail and natural cloud microphysical properties by aerosols, or ‘indirect’

radiative effects. These effects may be as large or larger than the radiative effects of contrails themselves (Righi et al., 2013, Gettelman

and Chen, 2013, Zhou and Penner, 2014). Aviation soot aerosol may change their own properties as they age (Heymsfield et al 2010). 15

Soot inclusions within and between contrail and background cloud particles also create a cloud absorption effect by enhancing contrail

burnoff (Jacobson et al., 2013).

Many studies have explored the total non-CO2 (short lived) effects of aviation radaitive forcing. Lee et al. (2009) performed a review and

meta-analysis and estimated aviation radiative forcing (RF) of 59 to 110 mWm-2 for Ozone, -52 to -28mWm-2 for CH4, 37 to 55mWm-2 20

for linear contrails, -12 to -18 for SO4 (direct) and 9 to 13mWm-2 for BC (direct). The sign of the net NOx effect on ozone is still uncertain

(Pitari et al., 2016). . This is mainly because the positive RF associated with the short-term NOX-induced O3 production is offset by

negative RF associated with aviation NOX emissions, resulting in a relatively large uncertainty associated with the overall net NOX-induced

RF (Holmes et al., 2011). Different spatial and temporal scales associated with the positive and negative forcing is another reason for such

a large uncertainty (IPCC, 1999; Wuebbles et al., 2010). It is generally reported that the net effect is positive (IPCC, 1999; Holmes et al., 25

2011), although recently Pitari et al (2016) reported a small negative number (-6.7 Wm2-) for the net effect induced by aviation NOx.

Some of these differences in the sign of the net aviation-induced NOx effect are in part due to differences in model chemistry schemes

Deleted: ‘non-linear’

Formatted: NormalDeleted: It is noted that

Deleted: Pitari et al (2016) note that 30 Deleted: ,Deleted: but is a small negative number (-6.7 Wm-2)

Deleted: to some extent

Deleted: the

Deleted: s35 Deleted: .Deleted: ADeleted: ,Deleted: isDeleted: the 40

3

and the treatment of physical processes, including transport and other factors (IPCC 1999; Stevenson et al., 2004; Kohler et al., 2008;

Holmes et al., 2011; Olsen et al., 2013) and some due to considering a different suite of NOx induced effects.

This manuscript evaluates and assesses the radiative forcing, ozone perturbation and surface temperature changes from projected levels of

aviation emissions for 2050 in two advanced General Circulation Models (GCMs) with common scenarios for 2050 aviation emissions. 5

The study focuses on simulations with coupled ocean, land and ice models, similar to Huszcar et al (2013) and Olivié et al (2012). The

goal is to determine statistically significant signals for small perturbations in coupled simulations. This work is not designed to be a review

of the many aspects of the effects of aviation on climate and chemistry (e.g. recent review by Lee et al 2010), but rather a summary of two

comprehensive coupled climate models. Most previous studies have not been conducted with fully coupled “climate-response” models

with small aviation forcing. This is due to the complexity of models and to the high potential climate noise that makes it difficult to find 10

small signals from aviation (e.g. Forster et al 2016). Our results largely validate this problem, and show that aviation signals, even for

2050 climate are significant but hard to identify in comprehensive models.

Section 2 describes the models, methodology and scenarios. Section 3 describes the results, and section 4 discusses them with a focus on

comparing models. Section 5 provides conclusions and suggestions for future work. 15

2. Methodology

The climate-related effects described here include the radiative effects of contrails, the chemical effects of NOx on atmospheric

concentrations of ozone (O3) and methane (CH4), and the direct and indirect effects of atmospheric particles resulting from emissions of 20

BC, organic compounds, and sulfur species.

We use two different models with interactive chemistry and climate, described below.

2.1 AEDT Emissions/Scenario 25

Simulations are conducted using a common set of emissions scenarios. Emissions used in this study come from the Aviation Environmental

Design Tool (AEDT) emission inventory (Barrett et al., 2010; Olsen et al., 2012; Brasseur et al., 2015). The AEDT dataset is an hourly

Deleted:

Deleted: Chen and Gettelman (2016) recently performed 30 simulations with one of the models used here and found significant indirect effects of aviation aerosols, especially sulfate, and RF increases by a factor of 5-7 from 2006 to 2050.

Deleted: P

Deleted: (or non-linear)35

4

inventory of global aircraft emission mass of ten emission species over a 1° x 1° latitude-longitude mesh with a vertical spacing of 150 m

in the year of 2006. 2006 data are chorded (individual flight tracks), and 2050 data are scaled and gridded. For GATOR-GCMOM,

individual flight track 2050 aircraft emissions are obtained by extrapolating 2006 emissions in the same flight paths to 2050 by scaling

the current year 2006 flight data by the ratio of 2050 to 2006 emissions. Emission indices from Barrett et al., (2010) are used for different

species to determine particulate emissions. Both models use greenhouse gas concentrations in 2050 from the Representative Concentration 5

Pathway 4.5 scenario (RCP4.5).

Different scenarios are listed in Table 1. The Baseline scenario assumes no operational or technology improvements. Scenario 1 has

reduced fuel burn because of assumed technology improvements. Scenario 2 assumes the same fuel burn of Scenario 1 with an ‘Alternative

Fuel’ (Alt Fuel) that has no sulfur and 50% less BC (soot) emissions. Scenario 3 assumes Scenario 2 (reduced fuel burn with no sulfur 10

and 50% BC) with +5% higher aviation H2O emissions from the engine exhaust. These scenarios were implemented in CESM. GATOR-

GCMOM used 2050 baseline emissions, and a modified scenario 2 that assumes fuel burn of the Baseline scenario and an Alt Fuel version

that has no sulfur and 50% less BC. This scenario (run only by GATOR-GCMOM) is called ‘Scenario 2B’.

The baseline emissions scenario has a fuel burn in 2050 that is 5 times that of 2006 emissions. Over E. Asia, the 2050 emissions are nearly 15

8 times those of 2006. 2050 emissions changes are lower over the U.S. (2 times 2006) and Europe (4 times 2006). The reduced fuel burn

scenario (Scenarios 1 and 2) is only 3 times 2006 emissions, with 4 times 2006 Asia, and 2 times 2006 for the U.S. and Europe.

2.2 GATOR-GCMOM 20

GATOR-GCMOM (Gas, Aerosol, Transport, Radiation, General-Circulation, Mesoscale, and Ocean Model) is a one-way nested global-

through-urban atmosphere-ocean-land model [Jacobson et al., 2011, 2013]. Resolution is 4o (latitude) x 5o (longitude) horizontal resolution

with 68 vertical sigma-pressure layers from 0-60 km (0.219 hPa), including 15 layers from 0-1 km and 500-m resolution from 1-21 km.

The model is initialized January 1, 2050 with 1ox1o reanalysis meteorological fields and ocean surface temperatures from January 1, 2012 25

[GFS, 2013] and run forward with no data assimilation. A single temperature profile was used to uniformly scale the ocean temperature

relative to the surface, with temperatures at depth a constant ratio to the surface temperature. Thus the sub-surface ocean is not in balance

as the stratification does not reflect spatial variations.

Deleted: 1

5

GATOR-GCMOM explicitly treats both the microphysical and radiative effects of aerosols on clouds and precipitation (Jacobson, 2012).

Clouds, radiation and chemistry are coupled together, with feedbacks between them. GATOR-GCMOM treats the sub-grid evolution of

aircraft particle and gas exhaust, including sub-grid contrail formation from each individual flight (30 million annually) [Jacobson et al.,

2011, 2013; Whitt et al., 2010]. The sub-grid model (described in detail in Jacobson et al., [2011]) treats contrail formation and aerosol 5

evolution/coagulation, forming contrails within a plume, and evolving contrails and then merges them with the grid scale when the water

content falls below 10µg m-3. The SGS model has been evaluated against a detailed plume model by Jacobson [2010]. NOx emissions are

added to the grid scale, so non-linear plume effects of NOx are not treated. Evaluation of GATOR-GCMOM against chemistry and climate

observations (including BC aerosols) was conducted by Jacobson et al., [2011]. Non-aircraft anthropogenic emissions of NOx, SOx, NH3,

CO, NMVOCs, CH4, BC, OC for 2050 are derived from the Fifth Assessment Report (AR5) inventory for 2050 assuming the 10

Representative Concentration Pathway (RCP) 4.5 trajectory [Clarke et al., 2007]. In addition, for the long-lived greenhouse gases, CO2,

N2O, CFCs, and HFCs, the EDGAR 2010 inventory [European Commission, 2014] extrapolated to 2050 are used. Biomass-burning gas

and particle emissions are as in Jacobson [2012]. Natural emissions from lightning, soils, oceans, and vegetation are calculated as a

function of meteorology as in Jacobson and Streets [2009].

15

The following global simulations are run for GATOR-GCMOM:

1) 2050 climate, 2050 non-aircraft anthropogenic emissions, and 2050 chorded aircraft emissions.

2) Same as (1) but with 2006 chorded aircraft emissions (but 2050 climate and 2050 non-aircraft anthropogenic emissions).

3) Same as (1) but with no aircraft emissions. 20

4) Same as (1) but with no BC in aircraft emissions.

5) Same as (1) but with no SOx, NOx, CO, HC aircraft emissions.

6) Same as (1) but no contrail optical properties (contrail microphysics still occurred)

7) Same as (1) but with zero sulfur and 50% black carbon emissions (low-sulfur fuel scenario).

25

GATOR-GCMOM simulations have been run for six complete years we show the first 5 years for comparisons. Results are substantially

the same if year 6 is included. 20-year results for 2006 chorded emissions (with 2006 anthropogenic emissions and 2006 meteorology)

have been documented by Jacobson et al. [2013].

Formatted: Font:SymbolFormatted: Superscript

Deleted: The

Deleted: above 30

6

Due to the high internal variability of the coupled climate system, long simulations are needed to achieve equilibrium. The GATOR-

GCMOM simulations are transient simulations and are not in equilibrium. Long timescale feedbacks will not have fully adjusting to the

small aviation perturbation. This will limit interpretation of small surface temperature signals, but should not affect atmospheric responses

to aviation ozone and aerosols. We recognize there are limits to this method. We use longer CESM simulations (see below) to understand 5

the impact of these assumptions.

2.3 CESM

Community Earth System Model (CESM, Hurrell et al 2012) with version 5 of the Community Atmosphere Model (CAM5) (Neale et al., 10

2010) uses a full gas-phase chemical mechanisms including tropospheric and stratospheric chemistry with 133 species and 330

photochemical reactions (Lamarque et al., 2012). CESM includes a detailed treatment of cloud liquid and ice microphysics (Morrison

and Gettelman, 2008), including particle size distributions, a detailed mixed phase with a representation of water uptake onto ice (the

Bergeron–Findeisen process) and ice supersaturation (Gettelman et al., 2010). Heterogenous freezing on dust and homogenous freezing

are represented. Cloud microphysics is coupled to a consistent radiative treatment of ice clouds, and a 7-mode Modal Aerosol Model 15

(MAM7) (Liu et al., 2012) with particle effects on liquid and ice clouds (Liu et al., 2012).

Aviation emissions for water and other chemical species are put into CAM following Chen et al (2012) and using the AEDT emissions

inventories (as described below). The contrail parameterization of Chen et al., (2012) is able to produce a reasonable spatial and seasonal

distribution of contrails compared to observations (Chen et al., 2012). CESM contrails were evaluated against satellite contrail optical 20

depth measurements by Chen et al (2012). In addition, Chen et al (2012) illustrated that CESM produces a reasonable distribution of ice

supersaturation in the upper troposphere relative to satellite observations. CESM has been used to estimate the present day impact of

aviation emissions by Chen and Gettelman (2013). Gettelman and Chen (2013) estimated radiative effects of aviation aerosols. Chen and

Gettelman (2016) estimated aviation RF in specified dynamics simulations without chemistry.

25

2.3.1 CESM Specified Dynamics Simulations

Deleted: 2

Deleted: 2

7

To determine small radiative forcing perturbations, CAM specified dynamics (CAM-SD) simulations are used to eliminate meteorological

noise. CAM-SD simulations use fixed meteorology (imposed pressure, winds and atmospheric and sea surface temperatures). Water,

clouds, aerosols and chemical species are freely advected. The use of the SD model does not allow the feedback of aviation impacts or

chemistry on the background meteorology.

5

Two sets of SD simulations were performed. The first set of SD simulations for determining contrail and aerosol effects are 10 years long,

and use meteorology specified from a CESM coupled run. For future years, 4 sets of driving meteorology for each year (representing

evolving forcing) were derived by running CAM with SSTs from a coupled simulation with RCP4.5 or RCP8.5 forcing for that year. No

aviation emissions are included in the meteorology. Ensembles are created by applying a round off level temperature perturbation to the

initial conditions (Kay et al 2014). Then 4 pairs of simulations with and without aviation emissions are performed for each specified year 10

using that meteorological forcing. Each of the 4 simulation pairs uses different meteorology, to test the variability of the results with

respect to meteorology. The different years tested between 2006 and 2050 are: 2006, 2016, 2026, 2036 and 2050. For each of the 4

ensembles and each year (2006,2016,2026,2036,2050), we perform SD simulation pairs using RCP4.5 with different scenarios as outlined

below.

15

SD simulations examining NOx effects are 5 year simulations are performed for the year 2050. These are basically the same as the 2050

CESM SD simulations, but run with more comprehensive chemistry. RCP4.5 boundary conditions of non-aviation NOx and volatile

organic compounds (VOCs) were obtained from the IPCC RCP4.5 scenario for year 2050 (Van Vuuren et al., 2011). The monthly surface

concentrations of longer-lived species, e.g., CO2, CH4, chlorofluorocarbons (CFCs), and nitrous oxide (N2O), were specified as boundary

conditions based on the IPCC RCP4.5 scenario. Meteorological fields to drive the SD simulation are also taken from a coupled CESM 20

simulation for 2050.

The University of Illinois Urbana Champaign (UIUC) Radiaitve Transfer Model (RTM) was used offline to calculate the forcing associated

with aviation NOx-induced short-term O3, in CESM while contrail effects are calculated in-line. The UIUC RTM calculates the flux of

solar and terrestrial radiation across the tropopause (e.g., Jain et al., 2000; Naik et al., 2000; Youn et al., 2009; Patten et al., 2011). 25

Stratospheric adjustment is not used since the perturbations span the tropopause.

Deleted: with a unit

8

2.3.2 CESM Coupled Simulations

Coupled Simulations were also performed with CESM to explore potential surface temperature responses to aviation forcing. Coupled

simulations feature a free running atmosphere coupled to a full dynamic ocean and sea ice model with a land surface model. Feedbacks

between chemistry, clouds and meteorology occur. Simulations were performed for 50 years, starting from a spun up control run of CESM 5

for 2050 with RCP4.5. We only use the last 20 years for analysis, and allow 30 years for the model to adjust. These runs are closer to

equilibrium than the GATOR-GCMOM simulations.

In order to evaluate the effect of transients in the simulations we also perform shorter CESM coupled experiments. These transient CESM

simulations use the same ocean initial condition as GATOR-GCMOM: GFS reanalysis for SST for Jan 1, 2012. A single temperature 10

profile was used to uniformly scale the ocean temperature relative to the surface, following GATOR-GCMOM. Salinity was not changed

from the standard initial conditions in the RCP runs (the GATOR-GCMOM salinity was unstable in CESM). The biggest difference is

the uniform temperature profile scaling used in the ocean. This run is analyzed to show the effect of a non-equilibrium state on the results

from GATOR-GCMOM.

15

The 2050 AEDT gridded inventory (Barrett et al., 2010; Brasseur et al., 2015) for Scenario 1 assumes a combined aircraft technology and

operational improvement consistent with maintaining a 2 %/yr improvement in aviation system efficiency and a NOx-related technology

improvement consistent with published ICAO/CAEP scenarios to 2036 extended to 2050 based on NASA N+3 and N+4 targets of “better

than 75%” (Barrett et al 2010). The Baseline scenario does not include the operational or technology improvements that were included in

Scenario 1. 20

2.4 Simulation Summary

GATOR-GCMOM was run for five model years with and without aviation emissions for baseline and Scenario 2B in a fully coupled

configuration. Sensitivity tests were conducted as described in Section 2.1. CESM was run in both a specified dynamics (SD) mode, 25

without feedbacks between emissions, chemistry and meteorology, to determine radaitive forcing (Section 2.2.1) and in a fully coupled

mode to compare with GATOR-GCMOM (Section 2.2.2). CESM coupled experiments were run for 50 model years for longer-averaged

statistics. CESM was run with baseline emissions for 2050 and all three scenarios.

Deleted: 2

Deleted: 30

Deleted: 2.3 AEDT Emissions/Scenario ... [1]

Deleted: s

9

2.5 Statistical Significance

Statistical significance was assessed at individual points using a 2-sided Student’s t-test (e.g. Chervain and Schneider, 1976), estimating

the standard deviation of annual means from the simulations with one degree of freedom for each year. Statistically significant differences 5

are defined as those above 95% confidence. We also performed a paired sample t-test with autocorrelation on the difference of the annual

means and got essentially the same significance results (with a more formal treatment of autocorrelation). The significance in the maps

and zonal means is estimated using the False Discovery Rate (FDR) method to reduce spurious climate variability (Wilks 2016). The short

nature of the GATOR-GCMOM simulations (5 years) means that the standard deviations may be large (and the degrees of freedom small).

CESM simulations can be evaluated in a similar 5-year window, or with a longer 20-year window from the first 20 or last 20 years (31-10

50) of 50-year simulations to explicitly address the issue of short and transient simulations. Forster et al. (2016) indicate that radiative flux

differences derived from free-running fixed SST simulations should amount to at least 100 mW/m2 in order to reach sufficient statistical

significance levels. In case of nudged or specified dynamics simulations the threshold value may reduce to 10% (Forster et al., 2016, p.

13). As noted below, this is consistent with our results.

15

3. Results

First we present general results for fuel burn from the scenarios and illustrate the potential for contrail formation. We then examine the

model-derived radiative forcing from contrails and other aviation emissions, including the radiative effects of chemical perturbations and

the effects resulting from aircraft emissions of soot and sulfur. Next we examine the model-derived chemical effects on ozone and methane 20

from NOx emissions. Finally, we analyze the resulting temperature response from the aviation perturbations in 2050 based on coupled

simulations. Note that the effect of alternative fuel is Scenario 2B v. Baseline for GATOR-GCMOM and Scenario 2 v. Scenario 1 for

CESM.

3.1 Radiative Forcing in CESM 25

Deleted: 0

Deleted:

Deleted: “non-linear”

10

Radiative forcing for contrails and from aviation-related aerosols (both direct and indirect effects) were assessed in CESM. Top of

atmosphere net downward solar plus thermal-infrared irradiance changes (a surrogate for radiative forcing but not the same quantity) were

assessed in both CESM and GATOR-GCMOM. For clarity we focus on CESM radiative forcing.

Figure 1 (adapted from Chen and Gettelman 2016) shows the evolution of the radiative forcing over time in CESM for different scenarios 5

using SD simulations. The effects of water vapor only emissions (leading to contrail formation) are shown in Figure 1A, the effects of

H2O + BC + SO4 emissions in Figure 1B and the effects of BC+SO4 emissions only in Figure 1C, as the residual of panel B minus panel

A. Note that since H2O emissions for Scenario 1 and Scenario 2 are the same, their RF in Figure 1A is the same. Figure 1A shows clear

increases in contrail cirrus radiative forcing to 2050. While global emissions grow by a factor of 5, contrail cirrus RF may grow by a factor

of 7 (13 to 90 mWm-2). Note however that a warmer planet, using RCP4.5 meteorology (solid lines in Figure 1), lowers the resulting 10

aviation RF relative to what it would be using 2006 meteorology (dashed lines in Figure 1), due to a reduction in contrail formation

conditions at warmer temperatures (Chen and Gettelman, 2016). This assumes aircraft fly at the same pressure altitude in 2050 as today.

Global RF grows faster than the emissions because the regional pattern of emissions is changing. Emissions are rising faster in regions

like Asia, and in these regions the RF may increase more per unit emissions. The larger change in contrails may occur because there are 15

fewer contrails in 2006 (there is a saturation effect) and/or the chance of forming contrails at flight altitudes is higher (since aircraft are

always in the troposphere at low latitudes).

Figure 1C shows the impact of aerosols in CESM. In the scenarios with significant sulfur emissions (Baseline, red and Scenario 1, green)

there is significant decrease in TOA radiative forcing from aerosols (Figure 1C) that is anticipated to cause a near-surface cooling. Each 20

line represents an average of 4 simulations (spread shown as error bars with symbols at the ends in Figure 1A and 1B).

Eliminating sulfur in Scenario 2 (blue) and Scenario 3 (purple) eliminates the negative radiative forcing from the indirect effects of aerosols

(Figure 1C). The net forcing is then positive (Figure 1B) and similar to figure 1A. Scenario 3 has a small amount of additional water vapor

from aircraft. There is a small increase in contrail RF in 2050, on the order of 0-5% for a 5% increase in water vapor in Scenario 3, also 25

seen in Figure 1B. The effect is small since most of the water in the contrails comes from the ambient atmosphere, not the fuel. The

difference between scenario 2 and scenario 3 is not statistically significant.

Deleted: 2

Deleted: be more sensitive to perturbations30 Deleted: Sensitivity may be

Deleted: higher either

11

Additional radiative forcing components are listed in Table 2, reprinted from Brasseur et al (2015). In particular, we have added CAM5

values of radiative forcing for 2050 for short-term effects of ozone, methane and water vapor for Scenario 2 (alternative fuels). We have

also added available RF values for contrails and aerosols (Figure 1) from CESM-CAM5. Other values are as described in Brasseur et al

(2015). New values are in bold, and show small effects of alternative fuels on minor species radiative forcing. The 2006 value for O3 long

and short term (~+30 mWm-2) is larger than recent estimates by Pitari et al 2015 with 3 other models. The CH4 value of -12 mWm-2 is 5

very similar to that of Pitari et al (2015). The reduction in sulfur and black carbon for alternative fuels in Scenario 2 changes short-term

ozone RF by +12.0mWm-2(17%), long-term ozone RF by -0.8 mWm-2, methane by -2.2 mWm-2, and water vapor by -0.5mWm-2. The

short term ozone RF effect of the alternative fuel scenario (no BC and 50% S) is probably an ‘indirect effect’ on ozone that arises from

changes in UTLS temperature induced by BC reductions, but the result may not be significant given the small changes in ozone in Figures

3A and B. 10

3.2 2050 Aviation NOx-induced effects on Ozone

The impact of aviation NOx leads to a direct short term ozone production that produces a positive RF (Brasseur et al 2015). A subsequent

increase in OH then induces long-term reduction in methane (CH4) that results in a negative RF, and a long-term small decrease in ozone 15

generating negative RF (Wild et al., 2001). These effects are separated in Table 2, but combined in the figures. Some of the complexity

and differences in multi-model results are discussed further by Brasseur et al (2015).

3.2.1. Effects on ozone

20

Figure 2A and B illustrate the simulated relative changes in zonally-averaged O3 (in percent) due to aviation emissions for (A) GATOR-

GCMOM and (B) CESM. Note that CESM uses years 30-50 of a long coupled simulation while GATOR-GCMOM uses the first 5 years

of a 5-year simulation. Results for CESM at different averaging periods are in Figure 5, and are more similar between models. Statistical

significance of zonal mean changes is indicated by black dots, and uses a 2 sided t-test with the FDR approach as described above.

25

Ozone radiative forcing is especially sensitive to the predicted ozone distribution in the Upper Troposphere and Lower Stratosphere

(UTLS) (Lacis et al., 1990). GATOR-GCMOM (Figure 2A) projects a peak increase in ozone at cruise altitude between 45˚N and 90˚N

of ~60 ppb, or over 30%. Which is partially significant due to the short simulation. Effects at higher altitudes likely depend on perturbations

Formatted: Subscript

Formatted: SuperscriptFormatted: SubscriptFormatted: SuperscriptDeleted: 2Deleted: ,30 Deleted: 7

Deleted: These effects in CESM are minor

Deleted: .

Formatted: Subscript

Deleted: the supplement

Deleted: 35 Deleted: wDeleted: not

Deleted: statistically

12

to the temperature gradient altering transport. However, due to variability of the stratospheric circulation they are not significant. Effects

in CESM based on the first 5 years of a coupled simulation (Figure 5a) are similar in sign but only up to 20% (~20 to 30ppbv) and are

also significant. They occur at a lower altitude however in CESM.

The effects of non-linear plume chemistry may affect the ozone results, as discussed by Paoli et al., [2011], depending on the dilution 5

model assumed. Cameron et al, [2013] explicitly analyze this effect using a version of GATOR-GCMOM with a sub-grid scale plume

model, and found 30% decreased O3 production and a 10% change in NOx with a plume model.

3.2.2 Effects on ozone with CAM5 using fixed meteorology fields

10

CAM5 was also run with fixed meteorology fields for 2050 (based on meteorology from free running simulations). The NOx-induced

changes in tropospheric ozone are complicated by a short-term increase in O3 concentrations associated with a positive forcing, and a

long-term reduction of O3 concentrations tied to the aviation induced methane decrease. The long term-reduction is associated with

negative forcing (Stevenson et al., 2004). The short-term O3 forcing is one of the major contributors to the overall aviation forcing and

dominates the net O3 forcing (Lee et al., 2009). Since CH4 mixing ratios at the boundary layer are fixed, the calculated changes in O3 15

concentration are the short-term changes. This may have consequences for the results (Pitari et al 2016).

Radiative forcing effects from these aviation perturbations are illustrated in Table 2 for each of the scenarios in Table 1. Enhanced upper

tropospheric and lower stratospheric ozone (O3), termed “short-term O3 forcing”, due to nitrogen oxide (NOx) emissions contributes

~60mWm-2 of radiative forcing. Changes to the methane lifetime induced by aviation are estimated to induce a radiative forcing of -20

25mWm-2 in 2050.

3.2.3 Alternative fuel effects on ozone

Figure 3A and B show the effect of using an alternative fuel on ozone. Both CESM and GATOR-GCMOM indicate very small effects on 25

ozone by switching from traditional fuel to alternative fuel with reduced BC and no sulfur. Values are not significant, except for some

near surface values in the N. Hemisphere in CESM. The aviation NOx-induced effect on ozone in the presence of sulfur and BC appears

to be the same as for standard fuel.

Deleted: Significance is illustrated by the red dots in Figure 2 and other figures. 30 Deleted: Deleted: but also not significant as for GATOR-GCMOM

Formatted: Subscript

13

3.3 Temperature Effects

GATOR-GCMOM and CESM were run coupled to an active ocean to estimate the temperature and surface temperature response to

aviation emissions in 2050. The major motivation for running fully coupled climate simulations with GATOR-GCMOM and CESM is to 5

assess the effects of aviation radiative forcing due to chemistry, contrails and aerosols on surface climate.

3.3.1 Surface Temperature changes

Surface temperature changes are shown in Figure 4 for GATOR-GCMOM for the first 5 years for the effects of baseline emissions (Figure 10

4A) and the alternative fuel Scenario 2B (Figure 4B): none of these differences pass the significance test. Similar results are seen for

CESM simulations in the first 5 years (not shown). CESM is still adjusting to the forcing. CESM results over the years 31-50 for baseline

(Figure 4C) and the effects of an alternative fuel (Figure 4D) show more significant patterns in or adjacent to flight corridors. Jacobson et

al (2012) found with similar 20-year GATOR-GCMOM experiments 16% of the planet had 'significant' temperature changes (>95%

confidence level), including warming in the Arctic after a 20 year coupled experiment with present day aviation emission. In Figure 4 (and 15

in Jacobson et al 2010), regions of surface temperature change are not precisely co-located with the largest forcing, and are not significant

in 5 years of simulation using the FDR approach. For baseline emissions, net cooling from aviation sulfate in CESM causes significant

Northern Hemisphere mid-latitude cooling (Figure 4C), consistent with the effect of the net negative radiative forcing for the baseline

scenario in Figure 1b. Cooling occurs in the deep water formation region around Greenland, and in the sub-tropical N. Atlantic, south of

the N. Atlantic flight corridor. The removal of sulfur in the Alternative Fuel Scenario 2 causes a reversal of this pattern (significant 20

warming), associated with an increase in net radiative forcing (Figure 1B: scenario 1 to scenario 2) due to the dominance of contrails. See

section 3.4.3. Warming is significant in the N. Atlantic and N. Pacific, extending over Europe. But there is no significant warming over

the maximum forcing regions of Central Europe or Eastern N. America. The global temperature perturbations for the last 20 of 50 years

are ±0.1 Wm-2 (negative with aerosol effects, positive with only contrail effects), barely significant at the 95% level (not significant at the

99% level). 25

We have also examined CESM initialized with a similar ocean structure to GATOR-GCMOM. The ocean initial condition is a uniform

temperature scaling with depth. The CESM simulation with such ocean initial conditions is not in balance, and over the course of the 5

Deleted: 4

Deleted: 430

Deleted: very few

Deleted: aDeleted: in any coherent way

Deleted: that

Deleted: with 35

Deleted: significant

Formatted: Superscript

14

years analyzed is still adjusting. This simulation was conducted to better compare with GATOR-GCMOM, and uses the same baseline

emission scenario as GATOR-GCMOM. It highlights the transient nature of signals in the first 5 years of simulation. A case could be

made that it is sufficient to look at the perturbation to the transient response between the two simulations, but the transient and longer term

response seem different in CESM simulations because of the out of balance initial conditions from GATOR-GCMOM. Even after 50 years

with a small perturbation any the dis-equilibrium is smaller than the internal variability of the climate system (i.e., not significantly 5

different than zero change).

3.3.2 Vertical Temperature structure

Figure 2 illustrates the impact of baseline aviation emissions on zonal mean temperature in GATOR-GCMOM (Figure 2C) and CESM 10

(Figure 2D). Different time periods are shown: first 5 years for GATOR-GCMOM and years 31-50 for CESM. CESM is similar to

GATOR-GCMOM over the first 5 years (illustrated in Figure 5). Over the first 5 years there is warming in the tropics and warming at

flight levels, but cooling at higher altitudes and high latitudes. However, very little of this signal is significant given the variability in a 5

year simulation. For CESM some of the tropical warming and warming in the N. Hemisphere at flight altitudes is significant over the first

20 years of simulation (Figure 5) but this becomes a cooling over the last 20 years of a 50 year simulation due to the radiative cooling 15

from increased aviation sulfur (Gettelman and Chen 2013). Initially CESM also has a N. Hemisphere UTLS warming due to short lived

species and contrails (Figure 5), which as the SST cools over time due to aviation aerosols it becomes a cooling at the surface and in the

UTLS (Figure 2D). This is not significant in the global mean.

In GATOR-GCMOM, BC is a strong contributor to the UTLS warming, and the reduction of BC in the Alt fuel scenario (Figure 3C) 20

reduces warming relative to the baseline. The same is seen in CESM in the first 5 years of simulation (Figure 6). The UTLS warming due

to aviation BC (and cooling from its removal with alternative fuels) occurs due to two factors. First, there is enhanced BC absorption upon

coating by sulfate. Second, by enhanced BC absorption between contrail ice particles (Jacobson et al., 2013). Enhanced SW absorption

results from hygroscopic growth of BC-coated aerosol particles, and BC absorbs not only solar radiation going down but also reflected

upward radiation, increasing the effect over snow and ice covered surfaces. 25

Most of the UTLS warming in GATOR-GCMOM (Figure 2C) appears to be due to BC. This was verified by conducting a sensitivity test

with reduced BC only (not shown), which resulted in less tropospheric warming than the scenario shown. BC as pure aerosol warms the

Deleted: 4

Deleted: significant 30 Deleted: , as noted below

Deleted: , noted below

Deleted: To obtain the full effect of

Deleted: eDeleted: , it is necessary to treat the35 Deleted: at the relative humidity of the cloud rather than at the relative humidity of the clear sky

Deleted: . In addition, over snow-covered, ice-covered, and cloud surfaces,

Deleted: . As such, it impacts over reflective surfaces exceed those 40 over darker-surfaces.

Deleted: Contrails themselves contribute to upper-tropospheric warming at sub-polar latitudes, in part due to enhanced solar absorption due to their black carbon inclusions within contrail particles. Reducing BC (not shown) alone results in less upper 45 tropospheric warming compared with low-BC and low-sulfur fuel. The combination of aircraft SOx, NOx, CO, and HCs (and their effects on O3) has much less of an impact on temperatures than does BC alone.

Deleted: Thus m50 Deleted: .

15

air by direct absorption of solar radiation. When BC is emitted from aircraft however it is coated by organic material, sulfate, and water.

Coating increases BC absorption due to the optical focusing effect (Jacobson et al., 2013).

3.3.3 Alternative Fuel Effects

5

The reduction of BC in the alternative fuel scenario reduces the flight level warming in GATOR-GCMOM (Figure 3C) but increases it in

CESM (Figure 3D and Figure 6), though neither is significant over a 5-year period. Over the last 20 years of a 50-year simulation (Figure

3D), the reduction of Sulfur in CESM alternative fuel Scenario 2 results in a significant warming near the surface in the N. Hemisphere

as the cooling seen in Figure 2D is reversed when sulfur is removed in the alternative fuel scenario, as noted above. This is seen globally

in Figure 1, and in the vertical temperature structure of Figure 3. The evolution of the temperature structure in the Alt Fuel scenario for 10

CESM (Figure 6) highlights that the vertical structure of temperature changes quickly due to local radiative forcing, but then evolves in

response to surface temperature effects. The BC effect is a local warming at altitude, while the brightening of clouds due to aviation sulfur

affects the surface, which takes years to evolve. How this happens is best understood by looking in detail at the pattern of surface

temperature changes.

15

4. Discussion

The major mechanisms by which aviation affects temperature differ between the two models. For GATOR-GCMOM, absorption due to

aviation BC is important. For CESM, over land, contrail cirrus dominate the radiative forcing, while over oceans, this is negated by cooling

due to sulfate brightening of low level liquid clouds. However, the initial responses of the models over the first 5 years of simulation are 20

broadly similar. Below we attempt to understand and assess these differences.

4.1 Sulfur

Aviation sulfur affects climate in two ways. (1) Sulfate nucleates liquid cloud drops by deliquescence and activation of haze particles. (2) 25

Sulfuric acid in the hot exhaust will condense onto BC particles to enhance the number concentration of contrail particles. Nucleation, (1),

is unique to the co-emission of sulfur and BC (i.e., from aviation). Both models treat nucleation. Both models treat sulfur-BC mixtures,

but GATOR-GCMOM treats sulfur-BC mixtures explicitly whereas CESM assumes BC and sulfate are internally mixed in the exhaust.

Deleted: 4

Deleted: and 30

Deleted: contrail radiative forcing dominates and

Deleted: externally

Deleted: exhaus

Deleted: t

16

Note GATOR-GCMOM BC distributions were evaluated by Jacobson et al (2011) against observations. In addition, sulfate coating of BC

changes the absorption and ice nucleating properties of the BC aerosols in GATOR-GCMOM with both aviation and background emission.

Aircraft aerosol sulfate is a small fraction of total aircraft-emitted sulfur, as much of the sulfur in both models manifests as SO2, but that

small amount of sulfate is a relatively large fraction of total emitted aerosol mass.

5

CESM produces a large cooling due to sulfate that is reversed when it is removed in Scenario 2 (Figure 1 and Figure 3 v. Figure 4).

However, GATOR-GCMOM cools when Sulfate and BC are removed (Figure 3C v. Figure 4C). As noted in Section 3.3, the GATOR-

GCMOM results are due to BC changes (BC warms). GATOR-GCMOM does not simulate large aviation sulfate indirect impacts on

clouds. Possibly the main reason for the difference in sulfate cooling due to aviation in CESM (Figure 1) versus GATOR-GCMOM

(discussion in section 3.3.1) is that CESM predicts a much lower background (non-aviation) aerosol number concentration for particles 10

>100nm, only 6% that of GATOR-GCMOM, so changes in emissions due to aircraft, have a greater impact on cloud indirect effects in

CESM. CESM has larger (10%) perturbations to the number of Cloud Condensation Nuclei (CCN) in 2050 in N. Hemisphere mid-latitudes

due to aviation. The increase in activated aerosols for liquid cloud formation in the N. Atlantic flight corridor is +30%, significantly

increasing cloud drop number, and cloud liquid water. The maximum increase in drop number is in the sub-tropics where cooling is seen

in Figure 4C. Results are consistent with advection and subsiding motion from higher aircraft cruise altitudes down to liquid cloud levels. 15

These perturbations contribute to low-cloud brightening and cooling. Total Aerosol Optical Depth (AOD) levels (not shown) are much

closer between CESM and GATOR-GCMOM because of similar numbers of small particles <100nm. In GATOR-GCMOM the higher

background particle numbers and lower percent perturbation mean that aviation sulfur has less impact on clouds. However, previous work

from Righi et al (2013) treats aerosols similarly to CESM, and finds similar cooling effects to CESM. Righi et al. (2013) did not treat

cloud absorption effects of BC aerosols emitted by aircraft, and did not examine climate response, only radiative forcing. Kapadia et al 20

(2016) using a very different model and methodology also found aviation aerosols could impact liquid clouds below.

4.2 BC (Soot)

GATOR-GCMOM has a large impact from the effects of enhanced BC absorption at altitude, due to (a) direct effects of sulfur coated BC, 25

(b) cloud absorption effects of BC in contrail ice, (c) semi-direct effects, and (d) indirect effects on contrail ice number. GATOR-GCMOM

treats these effects, including the coating of BC particles by sulfate, ammonium, water, and other aerosol constituents, enhancing cloud

absorption effects of BC aerosols. At the high super-saturations seen in aircraft exhaust, all BC particles should activate to small liquid

Deleted: a small warming in

Deleted: 430

Deleted: The impact of sulfur aerosols indicates that significant changes to aviation sulfur emissions will have large effect on the climate response to aviation emissions.

Deleted: P35 Deleted: However,

Deleted: Deleted: Deleted: The impact of sulfur aerosols indicates that significant changes to aviation sulfur emissions will have large effect on the 40 climate response to aviation emissions.

Deleted: 1.

17

drops that eventually freeze to form ice crystals in the plume. These may then coalesce into larger drops. The BC inclusions result in a

significant absorption increase (Jacobson et al 2011; Jasobson et al 2012).

The CESM BC treatment is similar, with some important differences. The Modal Aerosol Model (MAM) in CESM does mix BC and

sulfate aerosol and simulate enhanced absorption due to internally mixed aerosol BC, but MAM in CESM does not treat enhanced 5

absorption by contrail particles containing BC. CESM does not treat enhanced absorption by aerosol BC between non-contrail cloud

particles at the relative humidity of the cloud or within cloud particles. CESM does not assume an initial particle number based on BC,

but rather an ‘aged’ or coagulated particle number based on coagulated particles (10 microns in size). The BC aerosol absorption

enhancement due to mixing of BC aerosol with sulfate is included in CESM, but there are significant differences in the treatment of

particle sizes and optical properties between the grid scale model of CESM and the plume model in GATOR-GCMOM. However, we do 10

see similar initial warming in CESM as in GATOR-GCMOM in the baseline scenario (Figure 2 and Figure 5) before effects of sulfur

cooling in CESM alter surface temperature.

To analyze the differences in BC treatment, CESM experiments were conducted to bring CESM assumptions closer to those of GATOR-

GCMOM. We tested any differences in the size distribution of BC between CESM and GATOR-GCMOM, altering CESM simulations to 15

reflect smaller BC size and higher numbers. CESM makes no distinction between background BC and aviation BC, and CESM assumes

0.1% efficiency of ice nucleation for all BC particles (Gettelman et al., 2010). The plume processing that occurs in GATOR-GCMOM

first allows for coagulation that reduces BC particle number significantly. Then, nearly 100% of the resulting BC particles can activate to

form contrail particles in the highly-supersaturated contrail plume that exists immediately behind an aircraft (Jacobson et al., 2011). To

bridge this difference CESM simulations were performed where the contrail ice particle number concentration was set to the aviation soot 20

number, both in a specified dynamics (to get radiative forcing) and coupled simulation. This results in much higher ice crystal numbers in

contrails in CESM, similar to what GATOR-GCMOM would produce in a contrail. In this test, the positive cloud forcing in SD simulations

from contrail cirrus in CESM increases by a factor of 4 and there is a net warming that is more similar to GATOR-GCMOM in magnitude.

The warming is large enough in this simulation to reduce contrail formation due to the warming (burnoff) as in GATOR-GCMOM.

25

Thus it appears that the BC soot aerosol particles emitted by aircraft increase the number of contrail ice crystals, increasing the optical

thickness, for a net warming (as the enhanced longwave absorption dominates over the enhanced shortwave reflectance). Previous studies

showed similar effects. For example, Wong et al. (2013) found using laboratory experiments and modeling studies that soot was internally

Deleted: From this analysis, it appears that the increased contrail number due 30 to BC aerosols and absorption creates a larger warming in GATOR-GCMOM. Similar effects can be produced in CESM with similar assumptions of higher contrail numbers from activation on BC and limited coagulation.

Deleted: , more 35 Deleted: Deleted: From this analysis, it appears that the increased contrail number due to BC aerosols and absorption creates a larger warming in GATOR-GCMOM. Similar effects can be produced in CESM with similar assumptions of higher contrail numbers from activation 40 on BC and limited coagulation.

Moved down [1]: Previous studies showed similar effects. For example, Wong et al. (2013) found using laboratory experiments and modeling studies that soot was internally mixed in contrail ice particles and Liou et al. (2013) found a resulting increase in cloud 45 heating rate due to these internal mixtures.

Deleted: Moved (insertion) [1]

18

mixed in contrail ice particles and Liou et al. (2013) found a resulting increase in cloud heating rate due to these internal mixtures. This

seems in contrast to significant cooling from soot effects on cirrus clouds noted by Zhou and Penner (2014).

4.3 Ozone

5

Both models show ozone concentration enhancement in the upper troposphere and lower stratosphere (9-12km) in the N. Hemisphere

(e.g., Figure 2A from GATOR-GCMOM) from the effects of aviation emissions. CESM effects are seen at lower altitudes (in the

troposphere, not in the lower stratosphere). CESM shows similar effects for simulations run as a CTM, without differences in meteorology

or temperature. Neither model shows significant effects from the alternative fuels scenario on the changes in ozone concentrations (Figure

3A and 3B). However, these effects are seen in the CESM uncoupled SD experiments with a lower noise threshold (Table 2). Ozone 10

changes are consistent with NOx and NOy changes in CESM. Increases in ozone concentrations are consistent with previous work

assessed in Brasseur et al (2015).

4.4 Surface Temperature

15

Both GATOR-GCMOM and CESM performed 2050 simulations of surface temperature changes. GATOR-GCMOM has a global mean

warming in the simulations relative to aerosol emissions, but it is not significant in a five-year simulation. In CESM, signals are not

significant after 5 years, only after 50 years. Most of the effect is in the atmosphere and the surface takes time to react. In general, surface

temperature effects of aviation emissions in 2050 are statistically significant only in regions of maximum emissions and forcing over

oceanic flight corridors, and barely significant globally. Similar results were found for present day emissions by Jacobson et al. (2012) 20

with 20-year GATOR-GCMOM experiments. The cooling from indirect effects of aviation sulfur in CESM results in a global average

mean temperature change of -0.11K after 50 years (Figure 4C), significantly different from zero at the 95% leevel. This means that the

short term aviation signal from contrails and aerosols, even at 5-8 times current levels in 2050, have a barely significant globally-averaged

surface temperature signal. The alternative fuel scenario (scenario 2, Figure 4D) is globally warmer (+0.2K) than the baseline scenario

(Figure 4C) in 2050 due to the large positive radiative forcing, and this is globally and regionally significant. 25

Regional patterns of temperature change in Figure 4 are correlated with short term aviation radiative forcing. For CESM simulations with

strong cooling from sulfate, there is cooling over the N. Atlantic, particularly in regions where deep water is forming in the ocean (Figure

Deleted:

Deleted: 30

Deleted: The effects of soot can significantly change the climate impact of aviation. To further constrain the BC soot effects for climate purposes, it would be necessary to characterize better the near term evolution of ice particles and try to constrain better the particle size distributions in contrails. Further analysis of existing 35 observations of such size distributions against the model size distributions could be conducted, but that for the moment is beyond the scope of this work.

Deleted: .1

Deleted: 240

Deleted: The positive radiative forcing in

Deleted: contributes to

Deleted: in either model

Deleted: barely

Deleted: in most regions and not45

Deleted: , but this is not

Deleted: does not

Deleted: broadly

19

4C). There is a reduction of this cooling (warming) if effect of sulfur is removed with an alternative fuel (Figure 4D). Note that the

warming and cooling in the coupled system occur not necessarily where the largest forcing is (over N. America and Europe), but where

the climate system is most sensitive to perturbations (the sea ice edge and the region of deep water formation). Similar findings for 20th

century emissions were noted by Shindel and Faluvegi (2012). Also, the climate system takes time to react to the forcing at the surface,

particularly over the ocean. 5

5. Conclusions

This study has analyzed the climate effects of 2050 aviation emissions using the same 2050 emissions scenarios with two very different

climate-chemistry modeling systems. The study highlights new work and particularly work with models coupled to an active ocean to 10

elucidate surface temperature responses. Small perturbations to the coupled climate system result in regionally significant responses that

are barely significant globally, but detectable after 50 years of simulation. Furthermore, we have attempted comparisons between two

coupled models (GATOR-GCMOM and CESM). Specific simulations have been performed to replicate one model with another for some

of the key uncertainties and processes, which we highlight below. Key conclusions concern aviation radiative forcing, the importance of

indirect effects of sulfur and BC emissions, and resulting temperature responses assessed with coupled simulations in this work. The two 15

models provide a consistent picture, when taken into context.

5.1 Radiative Forcing

Simulations indicate significant growth in the climate impact of aviation that occurs with projected increases in fuel use. Fuel use increases 20

by a factor of 3 to 5 relative to 2006, while radiative forcing from contrails increases 13 to 90 mWm-2 (7 times 2006 forcing). There are

also large Ozone radiative forcing responses in 2050. Short term O3 forcing is estimated at ~60mWm-2, and changes to the methane forcing

induced by aviation-caused methane lifetime changes are estimated at -25mWm-2 in 2050 (based on differences with and without aviation).

Ozone responses in 2050 to aviation emissions result from increases in ozone in flight corridors of 20-60ppb (10-30%). These effects from

aviation may be large (particularly in otherwise pristine regions), depending on the future background emissions. 25

5.2 Sulfur and BC Indirect Effects

Formatted: Superscript

Deleted:

Formatted: Font:BoldFormatted: Font:BoldDeleted: , Simulations indicate significant growth in the climate 30 impact of aviation that occurs with projected increases in fuel use. Fuel use increases by a factor of 3 to 5 relative to 2006, while radiative forcing from contrails increases 12 to 90 mWm-2 (7 times 2006 forcing). The baseline scenario (the high end of this range) assumes no technology improvement and is likely an unrealistic 35 upper bound. It is shown here for comparison purposes. Regional radiative forcing for 2050 is concentrated over regions of high emissions, either directly over high traffic land regions of Asia, N. America and W. Europe, or over oceanic flight corridors of the N. Pacific and N. Atlantic. Regional temperature change happens where 40 the climate system is most sensitive near regions of large forcing, but not always coincident with largest forcing.The diurnal timing of contrail effects of aviation may mean that there are some regional effects not treated here, though diurnal cycle effects (Chen and Gettelman, 2013) are smaller than uncertainties in the model 45 formulations or emissions. ... [2]Moved (insertion) [2]

20

Simulations in both model systems indicate that effects of aviation emissions, through interactions with aerosol particles, can be larger

than the effects of aviation CO2 or aviation H2O emissions that cause contrails (Figure 1). The main particle emissions affecting radiative

forcing are sulfate and BC soot.

Sulfur rapidly evolves in the atmosphere into sulfate aerosols that can interact with liquid clouds. The effect of this process will be net 5

cooling, but mostly over oceans. Because CESM predicts lower background aerosol concentrations of larger aerosol particles, changes in

emissions due to aircraft increase aerosol loadings by a larger fraction in CESM resulting in a greater impact on indirect effects in CESM.

As such, CESM predicts more cloud-enhanced cooling than GATOR-GCMOM of as much as -150 mWm-2 in CESM in 2050 (Figure 1C).

The physical mechanism in CESM is aerosol formation at flight altitudes, which advects in subsidence regions into the sub-tropics where

it can affect liquid clouds at low altitudes. This effect seems speculative, but has been seen significantly in other studies (Righi et al 2013, 10

Kapadia et al 2016) using different models and methods.

GATOR-GCMOM indicates that BC, coated by sulfate and efficiently activating to form contrail particles increases contrail absorption

(heating), while CESM does not simulate sulfate coating BC in contrail plumes to increase activation rates. However, there is still warming

at altitude in CESM either from BC or from contrails. When large BC numbers are assumed to efficiently create contrail particles in 15

CESM, there is better agreement in results between the two models. Thus, BC emissions appear in both models, if treated similarly, to

cause increases in contrail absorption (net heating).

As a result of these sulfur and BC effects, both model simulations indicate that the use of alternative fuels that substantially reduce sulfur

and BC emissions from aviation may significantly alter the future climate impact of aviation. The pathways indicated by the two modeling 20

systems are similar. These effects are large in both models examined, but depend on the nature of the processes represented (BC enhanced

absorption in GATOR-GCMOM) and the background state (lower sulfate in CESM). The magnitude of potential positive forcing from

BC effects still needs to be determined and better constrained. The BC and sulfur effects are uncertain, and further comparisons between

models and observations of contrail aerosols would be valuable and important to better constrain these effects. Specifically, to further

constrain the BC soot effects for climate purposes, it would be necessary to characterize better the near term evolution of ice particles and 25

try to constrain better the particle size distributions in contrails. Further analysis of existing observations of such size distributions against

the model size distributions could be conducted, but that for the moment is beyond the scope of this work.

Deleted: “non-linear”

Deleted: chiefly 30

Deleted: Deleted: is emitted primarily as a gas and subsequently

Deleted:

21

Indirect Sulfur and BC effects would be mitigated with alternative fuels. Reduced fuel burn (Scenario 1) reduces impacts across all

different aviation components. Alternative fuels with lower BC and no sulfur (Scenario 2 and 2B) significantly reduce indirect effects of

aerosol sulfur and BC while not affecting contrail formation very much. The result would shift the balance of aviation radiative forcing

effects but with reductions of positive forcing for BC reductions, and reduced negative forcing for sulfur reductions. There are still large

uncertainties in this finding that need to be better assessed by more fully analyzing how the models treat aviation BC soot and sulfate 5

aerosols.

5.3 Surface Temperature

The global surface temperature effects of aviation in 2050 are small, and barely significantly different than zero in CESM. Effects in the 10

Arctic seen in GATOR-GCMOM (Jacobson et al. 2013) are also seen in some CESM simulations over short periods of time, but not in

longer CESM coupled simulations. This means that some of the transient differences may be a product of the slightly different evolution

of feedbacks in the transient GATOR-GCMOM and CESM simulations. Effects in CESM are seen over longer periods (Figure 4C and

4D) in response to large 2050 aviation forcings. Arctic effects are seen in CESM only in simulations set up with an ocean state out of

balance. However, the effects of temperature were not examined with CESM with background aerosol levels similar to those in GATOR-15

GCMOM. Thus high latitude effects, particularly surface temperature responses, should be studied more, but will require long equilibrated

simulations with coupled models.

Regional radiative forcing for 2050 is concentrated over regions of high emissions, either directly over high traffic land regions of Asia,

N. America and W. Europe, or over oceanic flight corridors of the N. Pacific and N. Atlantic. But, regional radiative forcing does NOT 20

translate into regional surface temperature responses even when regional forcing reaches 2Wm-2. The heat budget of middle and high

latitudes is not controlled locally, but has a large transport component. Over regions of the largest positive aviation radiative forcing over

continents, temperature may be more due to advection than local radiative fluxes. Persistent short term regional forcing impacts the climate

system where the system is most sensitive (i.e., regions of the sea ice edge and deep water formation) rather than where forcing is largest.

The impact on the surface takes time to develop after radiative forcing is integrated for many years. Thus, short-lived and non-uniform 25

radiative forcing (e.g., from aviation aerosols and contrail effects) may have a climate response per unit of forcing very different from

long-lived and uniform forcing (such as from aviation CO2). Local effects on temperature may not be correlated with local radiative

forcing. Long coupled simulations are needed to be able to observe these effects, even for 2050 emissions whose forcing is several times

Deleted: The different non-linear effects indicate a very important role for the different emission scenarios. 30 Deleted: non-linear

Deleted:

Deleted: Ozone responses in 2050 to aviation emissions indicate increases in ozone in flight corridors of 20-60ppb. These effects from aviation may be large (particularly in otherwise pristine 35 regions), depending on the future background emissions. Short term O3 forcing is estimated at ~60mWm-2, and changes to the methane forcing induced by aviation-caused methane lifetime changes are estimated at -25mWm-2 in 2050 (based on differences with and without aviation).40 Formatted: Font:BoldDeleted: not

Deleted: Deleted: in almost all regions

Deleted: Deleted: R45

Deleted: oes

22

that of 2006. Further work with other coupled (climate-response) models would be valuable to evaluate or falsify the pathways and the

magnitude of the effects identified here in two models.

Acknowledgements 5

This work was made possible by the support of U.S. Federal Aviation Administration Aviation Climate Change Research Initiative

(ACCRI) grants to Stanford, NCAR and University of Illinois. Thanks to Andy Heymsfield and Rangasayi Halthore for comments, and

to Rangasayi Halthore for continued support and encouragement. NCAR is supported by the U.S. National Science Foundation.

10

References

Appleman, H., The formation of exhaust condensation trails by jet aircraft, B. Am. Meteor. Soc., 34, 14–20, 1953.

Barrett, S., M. Prather, J. Penner, H. Selkirk, S. Balasubramanian, A. Dopelheuer, G. Fleming, M. Gupta, R. Halthore, J. Hileman, M. 15

Jacobson, S. Kuhn, S. Lukachko, R. Miake-Lye, A. Petzold, C. Roof, M. Schaefer, U. Schumann, I. Waitz, and R. Wayson, Guidance

on the use of AEDT gridded aircraft emissions in atmospheric models, version 2.0, Tech. rep., Federal Aviation Administration, 2010.

Brasseur, G. P., ed, A Report on the Way Forward Based on the Review of Research Gaps and Priorities. Federal Aviation

Administration, 20

http://www.faa.gov/about/office_org/headquarters_offices/apl/research/science_integrated_modeling/accri/media/ACCRI_Report_final.

pdf, 2008.

Brasseur, Guy P., Mohan Gupta, Bruce E. Anderson, Sathya Balasubramanian, Steven Barrett, David Duda, Gregg Fleming, et al.

Impact of Aviation on Climate: FAA’s Aviation Climate Change Research Initiative (ACCRI) Phase II. Bulletin of the American 25

Meteorological Society, 2015. doi:10.1175/BAMS-D-13-00089.1.

Deleted: Thus non-linear effects of soot and sulfur from aviation will strongly 30 affect the overall climate impact of aviation in 2050. The pathways indicated by the two modeling systems are similar. These results strongly indicate that use of alternative fuels that significantly reduce sulfur and BC emissions from aviation will significantly alter the future climate impacts of aviation: sulfur is a strong cooling 35 effect through indirect effects on clouds, and soot heats the upper troposphere in the simulations with some net surface warming. Both these effects would be mitigated with alternative fuels. The effects are uncertain, and further comparisons between models and observations of contrail aerosols would be valuable and important to 40 better constrain these effects.

Moved up [2]: The diurnal timing of contrail effects of aviation may mean that there are some regional effects not treated here, though diurnal cycle effects (Chen and Gettelman, 2013) are smaller than uncertainties in the model formulations or emissions. 45 Deleted: Thus non-linear effects of soot and sulfur from aviation will strongly affect the overall climate impact of aviation in 2050. The pathways indicated by the two modeling systems are similar. These results strongly indicate that use of alternative fuels that significantly reduce sulfur and BC emissions from aviation will 50 significantly alter the future climate impacts of aviation: sulfur is a strong cooling effect through indirect effects on clouds, and soot heats the upper troposphere in the simulations with some net surface warming. Both these effects would be mitigated with alternative fuels. The effects are uncertain, and further comparisons between 55 models and observations of contrail aerosols would be valuable and important to better constrain these effects.

23

Cameron, Mary A., Mark Z. Jacobson, Alexander D. Naiman, and Sanjiva K. Lele. “Effects of Plume-Scale versus Grid-Scale

Treatment of Aircraft Exhaust Photochemistry.” Geophysical Research Letters 40, no. 21, 2013, doi:10.1002/2013GL057665.

Chen, C. C., A. Gettelman, C. Craig, P. Minnis, and D. P. Duda. Global contrail coverage simulated by CAM5 with the inventory of

2006 global aircraft emissions. J. Advances Modeling Earth Sys., 4 (M04003), 2012. 5

Chen, C.-C., and A. Gettelman. “Simulated 2050 Aviation Radiative Forcing from Contrails and Aerosols.” Atmos. Chem. Phys. 16, no.

11 (June 13, 2016): 7317–33. doi:10.5194/acp-16-7317-2016.

Chervin, R. M., and S. H. Schenider. “On Determining the Statistical Significance of Climate Experiments with General Circulation 10

Models.” Journal of the Atmospheric Sciences 33, no. 3 (March 1, 1976): 405–12. doi:10.1175/1520-

0469(1976)033<0405:ODTSSO>2.0.CO;2.

Clarke, L., J. Edmonds, H. Jacoby, H. Pitcher, J. Reilly, and R. Richels, Scenarios of Greenhouse Gas Emissions and Atmospheric

Concentrations, Sub-report 2.1A of Synthesis and Assessment Product 2.1 by the U.S. Climate Change Science Program and the 15

Subcommittee on Global Change Research, 154 pp., Department of Energy, Office of Biological & Environmental Research,

Washington, D. C., USA, 2007.

European Commission Joint Research Centre (JRC)/Netherlands Environmental Assessment Agency (PBL) (2014), Emission Database

for Global Atmospheric Research (EDGAR), http://edgar.jrc.ec.europa.eu/datasets_grid_list42FT2010.php#d, Accessed March 4, 2014. 20

Forster, Piers M., Thomas Richardson, Amanda C. Maycock, Christopher J. Smith, Bjorn H. Samset, Gunnar Myhre, Timothy Andrews,

Robert Pincus, and Michael Schulz. “Recommendations for Diagnosing Effective Radiative Forcing from Climate Models for CMIP6.”

Journal of Geophysical Research: Atmospheres, 2016, 2016JD025320. doi:10.1002/2016JD025320. 25

Gettelman, A., and C. Chen, The climate impact of aviation aerosols, Geophys. Res. Lett., 40, doi:10.1002/grl.50520, 2013.

24

Gettelman, A., X. Liu, S. J. Ghan, H. Morrison, S. Park, A. J. Conley, S. A. Klein, J. Boyle, D. L. Mitchell, and J.-L. F. Li., Global

simulations of ice nucleation and ice supersaturation with an improved cloud scheme in the community atmosphere model. J. Geophys.

Res., 115(D18216), 2010.

GFS (Global Forecast System) (2013), 1º x 1º reanalysis fields, http://nomads.ncdc.noaa.gov/data/gfs-avn-hi/, Accessed September 14, 5

2013.

Heymsfield, A. J., D. Baumgardner, P. DeMott, P. Forster, K. Gierens, and B. Kärcher. “Contrail Microphysics.” Bull. Amer. Met. Soc.

91: 465–72, 2010.

10

Hurrell, J. W., M. M. Holland, P. R. Gent, S. Ghan, J. E. Kay, P. J. Kushner, J-F. Lamarque, et al., The community earth system model:

A framework for collaborative research.Bull. Amer. Meteorol. Soc., 94, 1339-1360, 2013.

Holmes, C. D., Q. Tang, and M. J. Prather (2011), Uncertainties in climate assessment for the case of aviation NO, Proceedings of the

National Academy of Sciences, U.S.A., 108, 10 997–11 002, doi:10.1073/pnas.1101458108, 2011. 15

Huszar, P., H. Teyssèdre, M. Michou, A. Voldoire, D. J. L. Olivié, D. Saint-Martin, D. Cariolle, et al. “Modeling the Present and Future

Impact of Aviation on Climate: An AOGCM Approach with Online Coupled Chemistry.” Atmos. Chem. Phys. 13, no. 19 (October 11,

2013): 10027–48. doi:10.5194/acp-13-10027-2013.

20

IPCC, (1999), Aviation and the global atmosphere 1999, In: E Penner, J., Lister, D.H., Griggs, D.J., Dokken, D.J., McFarland, M.

(Eds.), Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK.

Jacobson, M. Z., J. T. Wilkerson, A. D. Naiman, and S. K. Lele, The effects of aircraft on climate and pollution. Part I: Numerical 25

methods for treating the subgrid evolution of discrete size- and composition-resolved contrails from all commercial flights worldwide. J.

Comp. Phys., 230, 5115-5132, doi:10.1016/j.jcp.2011.03.031, 2011,

Formatted: Font:10 pt, English (US)

Deleted:

25

Jacobson, M. Z., J. T. Wilkerson, A. D. Naiman, and S. K. Lele, The effects of aircraft on climate and pollution. Part II: 20-year impacts

of exhaust from all commercial aircraft worldwide treated individually at the subgrid scale. Faraday Discussions, 165, 369-382,

doi:10.1039/C3FD00034F, 2013.

Jacobson, M. Z., Development of mixed-phase clouds from multiple aerosol size distributions and the effect of the clouds on aerosol 5

removal. J. Geophys. Res., 108(D8), 4245, doi:10.1029/2002JD002691, 2003.

Jacobson, M. Z., and D. G. Streets, Influence of future anthropogenic emissions on climate, natural emissions, and air quality. J.

Geophys. Res., 114, D08118, doi:10.1029/2008JD011476, 2009.

10

Jacobson, M. Z., Short-term effects of controlling fossil-fuel soot, biofuel soot and gases, and methane on climate, Arctic ice, and air

pollution health, J. Geophys. Res. 115 (2010) D14209, doi:10.1029/2009JD013795.

Jacobson, M. Z., Investigating cloud absorption effects: Global absorption properties of black carbon, tar balls, and soil dust in clouds

and aerosols. J. Geophys. Res., 117, D06205, doi:10.1029/2011JD017218, 2012. 15

Jacobson, M. Z., J. T. Wilkerson, S. Balasubramanian, W. W. Cooper, Jr., and N. Mohleji, The effects of rerouting aircraft around the

Arctic Circle on Arctic and global climate. Climatic Change, 115, 709-724, doi:10.1007/s10584-012-0462-0, 2012.

Jain, A. K., B. P. Briegleb, K. Minschwaner, and D. J. Wuebbles, Radiative forcings and global warming potentials of 39 greenhouse 20

gases. J. Geophys. Res., 105, 20773–20790, doi:10.1029/2000JD900241, 2000.

Kapadia, Z. Z., D. V. Spracklen, S. R. Arnold, D. J. Borman, G. W. Mann, K. J. Pringle, S. A. Monks, et al. Impacts of Aviation Fuel Sulfur Content on Climate and Human Health. Atmos. Chem. Phys. 16, no. 16 (August 24, 2016): 10521–41. doi:10.5194/acp-16-10521-2016. 25 Kay, J. E., C. Deser, A. Phillips, A. Mai, C. Hannay, G. Strand, J. M. Arblaster, et al. “The Community Earth System Model (CESM) Large Ensemble Project: A Community Resource for Studying Climate Change in the Presence of Internal Climate Variability.” Bulletin of the American Meteorological Society, November 19, 2014. doi:10.1175/BAMS-D-13-00255.1. 30

Formatted: Font:10 pt

26

Kohler, M.O., Radel, G., Dessens, O., Shine, K.P., Rogers, H.L., Wild, O., Pyle, J.A., (2008), Impact of perturbations to nitrogen oxide emissions from global aviation, Journal of Geophysical Research, 113, D11305. doi:10.1029/2007JD009140.

Lacis, A. A., Wuebbles, D. J., & Logan, J. A. Radiative forcing of climate by changes in the vertical distribution of ozone. Journal of

Geophysical Research: Atmospheres, 95(D7), 9971-998, 1990. 5

Lamarque, J.-F., L. K. Emmons, P. G. Hess, , D. E. Kinnison, V. Tilmes, V. Vitt, V. Heald, E. A. Holland, P. H. Lauritzen, J. Neu, J. J.

Orlando, P. Rasch, and G. Tyndall, CAM-chem: description and evaluation of interactive atmospheric chemistry in Community Earth

System Model. Geosci. Model Dev., 5, 369 – 411, doi: 10.5194/gmd-5-369-2012, 2012.

10

Lee, D.S., D. W. Fahey, P. M. Forster, P. J. Newton, R. C. N. Wit, L. L. Lim, B. Owen, and R. Sausen. Aviation and global climate

change in the 21st century. Atmos. Env., 43:3520-3537, 2009.

Liou, K. N., Y. Takano, Q. Yue, and P. Yang, 2013: On the radiative forcing of contrail cirrus contaminated by black carbon, Geophys.

Res. Lett., 40, 1-7, doi:10.1002/grl.50110. 15

Liu, X., et al. Towards a minimal representation of aerosol direct and indirect effects: Model description and evaluation. Geosci. Model

Dev., 5:709-735, 2012.

Minnis, P., D. F. Young, D. P. Garber, L. Nguyen, W. L. J. Smith, and R. Palikonda, Transformation of contrails into cirrus during 20

SUCCESS. Geophys. Res. Lett., 25, 1157–1160, 1998.

Morrison, H., and A. Gettelman, A new two-moment bulk stratiform cloud microphysics scheme in the NCAR Community Atmosphere

Model (CAM3), Part I: Description and numerical tests. J. Clim., 21, 3642-3659, 2008.

25

Naik, V., A. K. Jain, K. O. Patten, and D. J. Wuebbles, Consistent sets of atmospheric lifetimes and radiative forcings on climate for

CFC replacements: HCFCs and HFCs, J.Geophys. Res., 105, 6903–6914, doi:10.1029/1999JD901128, 2000.

Formatted: Font:10 pt, English (US)

27

Neale, R. B., et al., Description of the NCAR Community Atmosphere Model (CAM5.0). Technical Report NCAR/TN-486+STR,

National Center for Atmospheric Research, Boulder, CO, USA, 2010.

Olivié, D. J. L., D. Cariolle, H. Teyssèdre, D. Salas, A. Voldoire, H. Clark, D. Saint-Martin, et al. “Modeling the Climate Impact of Road

Transport, Maritime Shipping and Aviation over the Period 1860–2100 with an AOGCM.” Atmos. Chem. Phys. 12, no. 3 (February 7, 5

2012): 1449–80. doi:10.5194/acp-12-1449-2012.

Olsen, S. C., D. J. Wuebbles, and B. Owen, Comparison of global 3-D aviation emissions datasets. Atmos. Chem. Phys., 13, 429 - 441,

doi: 10.5194/acp-13-429-2013, 2013.

10

Olsen, S. C., G. P. Brasseur, D. J. Wuebbles, S. R. H. Barrett, H. Dang, S. D. Eastham, M. Z. Jacobson, A. Khodayari, H. Selkirk, A.

Sokolov, N. Unger (2013), Comparison of model estimates of the effects of aviation emissions on atmospheric ozone and methane,

Geophysical Research Letters, 40, 6004–6009, doi: 10.1002/2013GL057660, 2013.

Paoli, R., D. Cariolle, and R. Sausen. “Review of Effective Emissions Modeling and Computation.” Geosci. Model Dev. 4, no. 3, 2011: 15

643–67. doi:10.5194/gmd-4-643-2011.

Patten, K. O., V. G. Khamaganov, V. L. Orkin, S. L. Baughcum, and D. J. Wuebbles, OH reaction rate constant, IR absorption spectrum,

ozone depletion potentials and global warming potentials of 2-bromo-3,3,3-trifluoropropene. J. Geophys. Res., 116, D24307, doi:

10.1029/2011JD016518, 2011. 20

Pitari, Giovanni, Daniela Iachetti, Glauco Di Genova, Natalia De Luca, Ole Amund Søvde, Øivind Hodnebrog, David S. Lee, and Ling

L. Lim. “Impact of Coupled NOx/Aerosol Aircraft Emissions on Ozone Photochemistry and Radiative Forcing.” Atmosphere 6, no. 6,

2015: 751–82. doi:10.3390/atmos6060751.

25

Pitari, Giovanni, Irene Cionni, Glauco Di Genova, Ole Amund Søvde, and Ling Lim. “Radiative Forcing from Aircraft Emissions of

NOx: Model Calculations with CH4 Surface Flux Boundary Condition.” Meteorologische Zeitschrift, 2016.

doi:10.1127/metz/2016/0776.

28

Righi, M., J. Hendricks, R. and Sausen, The global impact of the transport sectors on atmospheric aerosol: simulations for year 2000

emissions. Atmos. Chem. Phys., 13, 9939-9970, doi:10.5194/acp-13-9939-2013, 2013.

Schmidt, E., Die Entstehung von Eisnebel aus den Auspuffgasen von Flugmotoren. In: Verlag R. Oldenbourg, Schriften der Deutschen 5

Akademie der Luftfahrtforschung, 44, 1–15, 1941.

Shindell, Drew, and Greg Faluvegi. “Climate Response to Regional Radiative Forcing during the Twentieth Century.” Nature Geoscience

2, no. 4 (April 2009): 294–300. doi:10.1038/ngeo473. 10

Stevenson, D. S., R. M. Doherty, M. G. Sanderson, W. J. Collins, C. E. Johnson, and R. G. Derwent, Radiative forcing from aircraft

NOx emissions: Mechanisms and seasonal dependence. J. Geophys. Res., 109, D17, doi: 10.1029/2004JD004759, 2004.

Van Vuuren, D. P., J. Edmonds, M. Kainuma, K. Riahi, A. Thomson, K. Hibbard, G. C. Hurtt, T. Kram, V. Krey, J.-F. Lamarque, T.

Masui, M. Meinshausen, N. Nakicenovic, S. J. Smith, and S. K. Rose, The representative concentration pathways: an overview. Climatic 15

Change, 109, 5-31, doi: 10.1007/s10584-011-0148-z, 2011.

Whitt, D. B., J. T. Wilkerson, M. Z. Jacobson, A. D. Naiman, and S. K. Lele, Vertical mixing of commercial aviation emissions from

cruise altitude to the surface. J. Geophys. Res., 116, D14109, doi:1029/2010JD015532, 2011.

20

Wild, O., M.J. Prather, H. Akimoto, 2001: Indirect long-term global radiative cooling from NOx emissions, Geophys. Res. Lett., 28,

1719–1722.

Wilks, D. S. “‘The Stippling Shows Statistically Significant Grid Points’: How Research Results Are Routinely Overstated and Overinterpreted, and What to Do about It.” Bulletin of the American Meteorological Society 97, no. 12, 2016: 2263–73. 25 doi:10.1175/BAMS-D-15-00267.1.

Wong, H.-W. et al., 2013: Laboratory and modeling studies on the effects of water and soot emissions and ambient conditions on the

properties of contrail ice particles in the jet regime, Atmos. Chem. Phys., 13, 10049.

Formatted: Font:10 ptFormatted: Font:10 pt

29

Wuebbles, D. J., M. Gupta, and M. Ko, Evaluating the impacts of aviation on climate change. EOS, 88, 157-160., 2007.

Wuebbles, D., P. Forster, H. Rogers, and R. Herman (2010), Issues and uncertainties affecting metrics for aviation impacts on climate,

Bulletin of the American Meteorological Society, 91, 491–496. 5

Youn, D., Patten, K. O., Lin, J. T., and Wuebbles, D. J.: Explicit calculation of indirect global warming potentials for halons using

atmospheric models, Atmospheric Chemistry and Physics, 9, 8719–8733, doi:10.5194/acp-9-8719-2009, 2009.

Zhou, C., and J. E. Penner, Aircraft soot indirect effect on large-scale cirrus clouds: Is the indirect forcing by aircraft soot positive or 10

negative?, J. Geophys. Res. Atmos., 119, doi:10.1002/2014JD021914, 2014.

30

TABLES

Table 1: Description of Emissions Scenarios used in this work.

Scenario List

Baseline Baseline Fuel Burn (technology improvements not included)

Scenario 1 Reduced Fuel Burn (includes assumed technology improvements)

Scenario 2 ‘Alternative Fuel’; Reduced Fuel Burn, no Sulfur, 50% BC

Scenario 2B GATOR-GCMOM Baseline ‘Alt Fuel’ Scenario

Scenario 3 Scenario 2 with 5% increased H2O

5

Table 2 Comparison of aviation emissions component specific RF (mW/m2) for 2006 and 2050 baseline and alternative scenarios (From

Brasseur et al., 2015, Table 4) with new results from this study added in bold.

Scenario

Fuel

burn

(Tg)

NOx

(Tg

N)

O3-S CH4

Long

Term

O3

Water

Vapor

Contrai

ls

Aerosol

s

UIUC

CAM5*

UIUC

CAM5*

UIUC

CAM5

UIUC

CAM5

NCAR

CAM5

NCAR

CAM5

2006 -Base 188.1 0.812 36.5 -12.3 -4.5 -2.6 13 -38

2050-Base 902.8 3.950 143 -59.7 -20.3 -12.5 83 -160

2050-S1 514.4 1.570 70.5 -28.3 -9.4 -5.9 72 -107

2050-S2 514.4 1.570 58.5 -25.6 -8.8 -5.4 72 0

10

Deleted: 7

31

Figures

5

Figure 1: Radiative forcing in CESM from (A) H2O emissions alone (contrail cirrus), (B) H2O +BC + SO4 emissions and (C) The

residual effect of BC and SO4 estimated from (B) – (A). Solid lines are for the RCP 4.5 scenario with different meteorology each

year; dashed lines in panel (A) are using 2006 meteorology. Since scenario 1 and scenario 2 have the same H2O emissions, they

have the same RF in (A). The baseline aviation scenario is in red, scenario 1 is green, scenario 2 is blue and scenario 3 is purple. 10

32

Figure 2: Zonal mean change in (A,B) ozone and (C,D) temperature due to baseline 2050 aviation emissions (v. no aviation

emissions). Panels A,C for GATOR-GCMOM and B,D CESM. Black dots show regions of statistically significant perturbations

using the False Discovery Rate method as described in the text. Based on first 5 years of simulations for GATOR-GCMOM, and

years 31-50 for CESM. 5

Deleted: Red

33

Figure 3: Zonal mean change in (A,B) ozone and (C,D) temperature due to Alternative Fuel 2050 aviation emissions (v. 2050

aviation emissions). Panels A,C for GATOR-GCMOM and B,D CESM. Black dots show regions of statistically significant 5

(a) ∆O3 (%), 2050 AltFuel, GATOR-GCMOM

0

3

6

9

12

15

Hei

ght (

km)

(b) ∆O3 (%), 2050 AltFuel, CESM

-30 -20 -10 0 10 20 30

(c) ∆T (K), 2050 AltFuel, GATOR-GCMOM

-90 -60 -30 0 30 60 90latitude

0

3

6

9

12

15

Hei

ght (

km)

(d) ∆T (K), 2050 AltFuel, CESM

-90 -60 -30 0 30 60 90latitude

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Deleted: Red

34

perturbations using the FDR method as discussed in the text. Based on first 5 years of simulations for GATOR-GCMOM, and

years 31-50 for CESM.

35

Figure 4: Surface temperature changes in (A, B) GATOR_GCMOM and (C, D) 50 year CESM coupled simulations. A and C are

for baseline emissions (v. no emissions) and B and D are for an alternative fuel scenario. Black dots show regions of statistically

significant perturbations using the FDR approach as described in the text.

5

Deleted: Red

Deleted: . Red dots show regions of statistically significant perturbations.

36

Figure 5: CESM simulations for different time periods. Baseline – No Aviation. (A,B,C) dO3, (D,E,F) dTs. (A,D) First 5 years,

(B,E) First 20 years, (C,F) Years 31-50. Black dots show regions of statistically significant perturbations using the FDR method as

described in the text.

5

(a) ∆O3 (%), 2050 AltFuel, CESM (first 5 years)

15

12

9

6

3

0

Hei

ght (

km)

(b) ∆O3 (%), 2050 AltFuel, CESM (first 20 years) (c) ∆O

3 (%), 2050 AltFuel, CESM (last 20 years)

-30 -20 -10 0 10 20 30

(d) ∆T (K), 2050 AltFuel, CESM (first 5 years)

latitude

15

12

9

6

3

0

Hei

ght (

km)

(e) ∆T (K), 2050 AltFuel, CESM (first 20 years)

-90 -60 -30 0 30 60 90latitude

(f) ∆T (K), 2050 AltFuel, CESM (last 20 years)

-90 -60 -30 0 30 60 90latitude

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Deleted: Red

Deleted: .

37

Figure 6: CESM simulations for different time periods. AltFuel – Regular fuel (Scenario 2 – Scenario 1) (A,B,C) dO3, (D,E,F) dTs.

(A,D) First 5 years, (B,E) First 20 years, (C,F) Years 31-50. Black dots show regions of statistically significant perturbations using

the FDR approach as discussed in the text.

5

Deleted: Red

Deleted: .

Page 8: [1] Deleted andrewgettelman@gmail.com 5/31/17 10:29:00 AM 2.3 AEDT Emissions/Scenario

Simulations are conducted using a common set of emissions scenarios. Emissions used in this study come from the

Aviation Environmental Design Tool (AEDT) emission inventory (Barrett et al., 2010; Olsen et al., 2012; Brasseur et

al., 2015). The AEDT dataset is an hourly inventory of global aircraft emission mass of ten emission species over a

1° x 1° latitude-longitude mesh with a vertical spacing of 150 m in the year of 2006. 2006 data are chorded (individual

flight tracks), and 2050 data are scaled and gridded. For GATOR-GCMOM, individual flight track 2050 aircraft

emissions are obtained by extrapolating 2006 emissions in the same flight paths to 2050 by scaling the current year

2006 flight data by the ratio of 2050 to 2006 emissions. Emission indices from Barrett et al., (2010) are used for

different species to determine particulate emissions. Both models use greenhouse gas concentrations in 2050 from the

Representative Concentration Pathway 4.5 scenario (RCP4.5).

Different scenarios are listed in Table 1. The Baseline scenario assumes no operational or technology improvements.

Scenario 1 has reduced fuel burn because of assumed technology improvements. Scenario 2 assumes the same fuel

burn of Scenario 1 with an ‘Alternative Fuel’ (Alt Fuel) that has no sulfur and 50% less BC (soot) emissions. Scenario

3 assumes Scenario 2 (reduced fuel burn with no sulfur and 50% BC) with +5% higher aviation H2O emissions from

the engine exhaust. These scenarios were implemented in CESM. GATOR-GCMOM used 2050 baseline emissions,

and a modified scenario 2 that assumes fuel burn of the Baseline scenario and an Alt Fuel version that has no sulfur

and 50% less BC. This scenario (run only by GATOR-GCMOM) is called ‘Scenario 2B’.

The baseline emissions scenario has a fuel burn in 2050 that is 5 times that of 2006 emissions. Over E. Asia, the 2050

emissions are nearly 8 times those of 2006. 2050 emissions changes are lower over the U.S. (2 times 2006) and Europe

(4 times 2006). The reduced fuel burn scenario (Scenarios 1 and 2) is only 3 times 2006 emissions, with 4 times 2006

Asia, and 2 times 2006 for the U.S. and Europe.

Page 19: [2] Deleted andrewgettelman@gmail.com 7/10/17 12:03:00 PM , Simulations indicate significant growth in the climate impact of aviation that occurs with projected increases in fuel

use. Fuel use increases by a factor of 3 to 5 relative to 2006, while radiative forcing from contrails increases 12 to 90

mWm-2 (7 times 2006 forcing). The baseline scenario (the high end of this range) assumes no technology improvement

and is likely an unrealistic upper bound. It is shown here for comparison purposes. Regional radiative forcing for 2050

is concentrated over regions of high emissions, either directly over high traffic land regions of Asia, N. America and

W. Europe, or over oceanic flight corridors of the N. Pacific and N. Atlantic. Regional temperature change happens

where the climate system is most sensitive near regions of large forcing, but not always coincident with largest

forcing.The diurnal timing of contrail effects of aviation may mean that there are some regional effects not treated

here, though diurnal cycle effects (Chen and Gettelman, 2013) are smaller than uncertainties in the model formulations

or emissions.