Supporting Information for 1

Climatic responses to future trans-Arctic shipping 2

3

Scott R. Stephenson1, Wenshan Wang

2, Charles S. Zender

2, Hailong Wang

3, Steven J. Davis

2 4

and Philip J. Rasch3 5

6 1Department of Geography, University of Connecticut 7

215 Glenbrook Road 8

Storrs, CT 06269 9

10 2Department of Earth System Science, University of California, Irvine 11

Croul Hall 12

Irvine, CA 92697-3100 13

14 3Pacific Northwest National Laboratory 15

902 Battelle Boulevard 16

Richland, WA 17

18

19

Contents of this file 20

21

Text S1: Methods 22

Figures S1 to S6 23

Table S1 24

References 25 26 27

Text S1: Methods 28

Optimal least-cost shipping routes were calculated using the approach of Stephenson and Smith 29

(2015) and Smith and Stephenson (2013). Sea ice concentration and thickness output from 10 GCMs 30

(ACCESS1.0, ACCESS1.3, CCSM4, GFDL-CM3, HADGEM2-CC, IPSL-CM5A-LR, IPSL-CM5A-MR, 31

MIROC5, MIROC-ESM-CHEM, MPI-ESM-MR) were adapted for use with the Arctic Ice Regime 32

Shipping System (AIRSS) (Transport Canada, 1998), a widely-used maritime navigation framework that 33

characterizes the relative risk of different ice conditions. AIRSS defines the ability of a ship to enter a 34

particular ice regime according to the Ice Numeral (IN): 35

36 IN = (Ca * IMa) + (Cb * IMb) + … + (Cn * IMn) 37

38 where Ca/Cb is the concentration of ice type a/b and IMa/IMb is the Ice Multiplier (Transport Canada, 39

1998) of ice type a/b. The Ice Multiplier (non-zero integer ranging from -4 to 2) indicates the risk from a 40

given ice type to a given vessel class, where higher values denote lower risk. Ice type describes the 41

physical properties of ice and is closely related to ice age and thickness (Johnston and Timco, 2008; 42

Hunke and Bitz, 2009). Ice type was computed from GCM ice thickness as follows: “open water” (< 1 43

cm), “gray” (1-15 cm), “gray-white” (15-30 cm), “thin first-year first stage” (30-50 cm), “thin first-year 44

second stage” (50-70 cm), “medium first-year” (70-120 cm), “thick first-year” (first-year ice over 120 45

cm). Thickness ranges for older ice classes (> 120 cm) were calculated by linear interpolation of the 46

spatially-coincident relationship between ICESat freeboard ice thickness measurements (Kwok et al., 47

2007) and ice age grids derived from Lagrangian drift tracking (Maslanik et al., 2007; Stephenson et al., 48

2013). 49

Monthly Ice Numeral grids were created from 2005-2050 assuming a moderately ice-50

strengthened Polar Class 6 (PC6) vessel (nominally equivalent to AIRSS “Type A” class), capable of 51

“summer/autumn operation in medium first-year ice which may include old ice inclusions” (IMO, 2002). 52

Grid cells with a negative Ice Numeral were classified as inaccessible. Remaining grid cells were 53

converted to a vector line grid (20 km) with each segment coded with the travel time required to traverse 54

its length given its Ice Numeral (McCallum, 1996). Pairwise least-cost paths between European 55

(Rotterdam, Antwerp/Zeebrugge, Hamburg/Bremen/Bremerhaven, Felixstowe) and East Asian (Shanghai, 56

Hong Kong/Shenzhen/Guangzhou, Busan, Ningbo, Qingdao, Tianjin, Xiamen, Dalian, Tokyo/Yokohama, 57

Lianyungang, Ho Chi Minh, Yingkou, Kobe, Nagoya) ports were computed as the routes accumulating 58

the lowest travel time. 59

Figures 60

61 62

Figure S1: Differences in cloud fraction and cloud liquid water path (experiment minus LENS control) in 63 summer (MJJAS). Gray areas indicate one standard deviation of the 40-member LENS ensemble. 64 65 66

67 68 Figure S2: Seasonal average (2070-2099) difference in (a) cloud fraction and (b) cloud liquid path 69 (experiment minus LENS control). 70

71 72

73 74

Figure S3: Cloud radiative effects at the surface (experiment minus LENS control). Gray areas indicate 75 one standard deviation of the 40-member LENS ensemble. 76 77 78

79 80 Figure S4: Seasonal change in net cloud radiative effects at the surface (experiment minus LENS control); 81 5 ensemble members (thin lines) and ensemble average (thick line). 82 83 84

85 86 Figure S5: Sensible heat flux from the surface to the atmosphere (experiment minus LENS control). Gray 87 areas indicate one standard deviation of the 40-member LENS ensemble. 88 89 90 91

92 Figure S6: All-sky radiative fluxes at the surface (experiment minus LENS control). Gray areas indicate 93 one standard deviation of the 40-member LENS ensemble. 94 95 96 97 98 99

Table S1: Period-averaged difference in key climatic variables between experiment and LENS 100 control (* p < 0.05; ** p < 0.01) 101

2006-2099 2070-2099 2090-2099

Surface temperature (K) -0.37 -0.68* -0.94**

Sea ice extent (million km^2) 0.19 0.35* 0.49**

Cloud fraction 0.02** 0.03** 0.03**

Cloud liquid water path (g/m^2) 2.88** 4.23** 4.52**

Longwave radiation at surface (W/m^2) 2.83** 4.22** 4.32**

Shortwave radiation at surface (W/m^2) -4.43** -7.06** -8.31**

Net radiation at surface (W/m^2) -1.62 -2.84** -4.03*

Sensible heat flux (W/m^2) 0.38** 0.57** 0.41**

Longwave CRE at surface (W/m^2) 2.97** 4.36** 4.11**

Shortwave CRE at surface (W/m^2) -2.98 -4.10** -4.01

Net CRE at surface (W/m^2) -0.1 0.01 -0.39

102

103

References 104

1. Hunke, E.C. and C.M. Bitz (2009). Age characteristics in a multidecadal Arctic sea ice 105

simulation. Journal of Geophysical Research 114: C08013. 106

107

2. IMO (2002). Guidelines for ships operating in Arctic ice-covered waters. 108

109

3. Johnston, M.E. and G.W. Timco (2008). Understanding and identifying old ice in summer. 110

Canadian Hydraulics Centre, National Research Council Canada. Ottawa. 111

112

4. Kwok, R., G.F. Cunningham, H.J. Zwally and D. Yi (2007). Ice, Cloud, and land Elevation 113

Satellite (ICESat) over Arctic sea ice: retrieval of freeboard Journal of Geophysical Research 114

112: C12013. doi:10.1029/2006JC003978. 115

116

5. Maslanik, J.A., C. Fowler, J.C. Stroeve, S. Drobot, J. Zwally, D. Yi and W. Emery (2007). A 117

younger, thinner Arctic ice cover: increased potential for rapid, extensive sea-ice loss. 118

Geophysical Research Letters 34: L24501. doi:10.1029/2007GL032043. 119

120

6. McCallum, J. (1996). Safe speed in ice: an analysis of transit speed and ice decision numerals. 121

Ship Safety Northern, Transport Canada. Ottawa. 122

123

7. Smith, L.C. and S.R. Stephenson (2013). New Trans-Arctic shipping routes navigable by 124

midcentury. Proceedings of the National Academy of Sciences 110: 4871-4872. DOI: 125

10.1073/pnas.1214212110. 126

127

8. Stephenson, S.R. and L.C. Smith (2015). Influence of climate model variability on projected 128

Arctic shipping futures. Earth's Future 3: 331–343. DOI: 10.1002/2015EF000317. 129

130

9. Stephenson, S.R., L.C. Smith, L.W. Brigham and J.A. Agnew (2013). Projected 21st-century 131

changes to Arctic marine access. Climatic Change 118: 885-899. DOI: 10.1007/s10584-012-132

0685-0. 133

134

10. Transport Canada (1998). Arctic ice regime shipping system (AIRSS) standards. Ottawa. 135

136 137