Changes in sea ice conditions along the Arctic Northeast Passage from 1979 to 2012

    Changes in sea ice conditions along the Arctic Northeast Passage from 1979 to 2012 Ruibo Lei, Hongjie Xie, Jia Wang, Matti Lepp¨aranta, Ingibj¨org J´onsd´ottir, Zhanhai Zhang PII: DOI: Reference:

S0165-232X(15)00174-3 doi: 10.1016/j.coldregions.2015.08.004 COLTEC 2147

To appear in:

Cold Regions Science and Technology

Received date: Revised date: Accepted date:

27 January 2014 13 July 2015 8 August 2015

Please cite this article as: Lei, Ruibo, Xie, Hongjie, Wang, Jia, Lepp¨ aranta, Matti, J´onsd´ ottir, Ingibj¨ org, Zhang, Zhanhai, Changes in sea ice conditions along the Arctic Northeast Passage from 1979 to 2012, Cold Regions Science and Technology (2015), doi: 10.1016/j.coldregions.2015.08.004

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT Changes in sea ice conditions along the Arctic Northeast Passage from 1979 to 2012

Key Laboratory for Polar Science of the State Oceanic Administration, Polar Research Institute

SC R

a

IP

T

Ruibo Leia,*, Hongjie Xieb, Jia Wangc, Matti Leppärantad, Ingibjörg Jónsdóttire, Zhanhai Zhanga

of China, Shanghai, 200136, China b

Laboratory for Remote Sensing and Geoinformatics, University of Texas at San Antonio, Texas,

NOAA Great Lakes Environmental Research Laboratory, 4840 S. State Rd., Ann Arbor, MI

MA

c

NU

78249, USA

48108, USA

Department of Physics, University of Helsinki, P.O.Box 48, Helsinki, FI-00014, Finland

e

Institute of Earth Sciences, University of Iceland, Reykjavik, 101, Iceland

CE P

TE

D

d

* Corresponding author at: Key Laboratory for Polar Science of the State Oceanic Administration,

AC

Polar Research Institute of China, Shanghai 200136, China Fax: +86-21-58711663; Tel: +86-21-58714974. E-mail address: [email protected] (R. Lei).

1

ACCEPTED MANUSCRIPT ABSTRACT Sea ice conditions in the Arctic Northeast Passage (NEP) have changed dramatically in the last

IP

T

four decades, with important impacts on the environment and navigability. In the present study,

SC R

multisource remote sensing data for 1979–2012 were analyzed to quantify seasonal, interannual, and spatial changes in sea ice conditions along the NEP. Data for October–November showed that spatially averaged ice thickness in the NEP decreased from 1.2–1.3 m in 2003–2006 to 0.2–0.6 m

NU

in 2011–2012. From 1979 to 2012, the fastest decreasing trend in monthly ice concentration

MA

occurred in October (–1.76% per year, P<0.001), when the ice cover starts to increase. As a result of decreasing multiyear sea ice, thinning ice and delayed freeze-up, the spatially averaged length

D

of open period (ice concentration < 50%) increased from 84 days in the 1980s to 114 days in the

TE

2000s and reached 146 days in 2012. The Kara, Laptev, and East Siberian sectors were relatively

CE P

inaccessible, especially the sector of 90–110°E around the Vilkitsky Strait. However, because of the thinning sea ice prior to the melt season and the enhanced positive polarity of the summer

AC

Arctic Dipole Anomaly, these sectors have become more accessible in recent years. The summer sea ice along the high-latitude sea route (HSR) north of the eastern Arctic islands, with a route distance comparable to the NEP, has also decreased during the last decade with the ice-free period reaching 42 days in 2012. The HSR avoids shallow waters along the coast, improving access to the Arctic sea route for deeper-draft vessels.

Key words: Sea ice; Concentration; Thickness; Shipping; Northeast Passage; Arctic

2

ACCEPTED MANUSCRIPT 1. Introduction The extent and volume of Arctic sea ice has declined dramatically in recent decades. In

IP

T

September 2012, Arctic sea ice extent reached a record minimum since 1979, with a reduction of

SC R

45% compared with the 1979–2010 climatology. The percentage of multiyear sea ice in March decreased from 75% in the mid-1980s to 45% in 2011 (Maslanik et al., 2011). Sea ice extent in all seasons has declined across the entire Eurasian sector of the Arctic during the last two decades

NU

(Mahoney et al., 2008; Xia et al., 2014). Between the years 2003–2007 and 2010–2012, the fall

MA

Arctic sea ice volume decreased by 4291 km3 (Laxon et al., 2013). Anomalous Arctic sea level air pressure (SLP) has two leading patterns, the annular Arctic Oscillation (AO) and the meridional

D

Dipole Anomaly (DA) (Wang et al., 2009). Rigor et al. (2002) suggested that the thinning of

TE

Arctic sea ice could be partly attributed to the trend in the AO toward the high-index polarity

CE P

during the 1990s. Wang et al. (2009) highlighted that recent record lows of Arctic summer sea ice extent were triggered by the high-index polarity of the DA.

AC

The shrinking and thinning of Arctic sea ice allows greater accessibility for shipping. Numerical models indicate that sea ice limited the probability of an open-water vessel transit along the Northeast Passage (NEP) in September to about 40% or less in 1979–2005, but this probability has risen to 61–71% in 2006–2015, and is expected to reach 94–98% in 2040–2059 (Smith and Stephenson, 2013). The shipping distance between the Far East and Europe via the NEP is 30–40% shorter than the traditional Royal Road via the Suez Canal (Lasserre and Pelletier, 2011). Forty-six voyages carrying 1.26 million tons of cargo in 2012 alone clearly show the economic viability of the NEP (Stephenson et al., 2013). Until now, sea ice has been the greatest obstacle to use of the NEP by restricting the operational season (Rogers et al., 2013; Schøyen and 3

ACCEPTED MANUSCRIPT Bråthen, 2011), influencing the escort fee (Liu and Kronbak, 2010), and limiting the choice of vessel types (International Maritime Organization [IMO], 2002). Therefore, in the planning

IP

T

process it is very important for stakeholders, including ship owners, insurance agents, and

SC R

navigation authorities, to thoroughly understand the historical changes and the current state of sea ice along the NEP.

From a shipping perspective, the most important sea ice parameters are concentration,

NU

thickness, and type. Passive microwave satellite data can be used record changes in Arctic sea ice

MA

cover, because these data can provide consistent and up-to-date information on brightness temperature, which can be used to estimate sea ice extent (Fetterer and Knowles, 2004),

D

concentration (Markus and Cavalieri, 2000), type (Eastwood, 2012), and the melt season (Markus

TE

et al., 2009). Sea ice type can also be estimated by Ku-band backscatter measurements from the

CE P

SeaWinds instrument aboard the QuikSCAT satellite (Swan and Long, 2012). Measurements from spaceborne altimeters can be used to estimate sea ice thickness (Kwok and Cunningham, 2008;

AC

Laxon et al., 2013).

In this study, satellite products including those providing data on ice extent, concentration, thickness, type, and melt season, are combined to examine long-term, seasonal and spatial changes in sea ice conditions along the NEP from 1979 to 2012 from the perspectives of shipping.

2. Study region and data 2.1. CHINARE cruise and study regions The fifth Chinese National Arctic Research Expedition (CHINARE) was carried out aboard the icebreaker R/V Xuelong from July to September 2012. One objective of this expedition was to explore the navigability of the NEP. The R/V Xuelong departed from point A in the Chukchi Sea (68.0°N, 5°W, Fig.1) on 22 July 2012 and arrived at point B in the Norwegian Sea (75.1°N, 20°E) 4

ACCEPTED MANUSCRIPT on 2 August 2012. In this study, the sea route from A to B is defined as the standard NEP. On 24 August 2012, the R/V Xuelong reached Point C (80.1°N, 10.0°E) north of Svalbard

IP

T

and started traveling east. North of the Laptev Sea, she continued northward and reached the

SC R

northernmost point (E) on 30 August. Finally, she navigated to the north of Bering Strait (point D, 68.1°N, 10°W) by 8 September 2012. In this study we also define a High-Latitude Sea Route (HSR), which passes to the north of Svalbard, Franz Joseph Land, and the Severnaya Zemlya,

NU

New Siberian, and Wrangel Islands. The western section of the return track of the R/V Xuelong

MA

followed the HSR. In the Laptev and East Siberian Seas, the HSR stretches southward in line with the bathymetric setting of the Arctic sea ice edge (Nghiem et al., 2012). Adding the route from B

D

to C to the HSR and the route from A to D to the NEP, the lengths of the HSR and NEP are

TE

comparable at 2816 and 2822 nautical miles, respectively. However, the HSR avoids most of the

AC

CE P

shallow waters along the Eurasian coastal region, which is of benefit to deeper-draft vessels.

Fig. 1 SMMR–SSMIS-derived Arctic sea ice extent in September averaged from 1981 to 2010 and individually for the years 2007–2012, the tracks of the R/V Xuelong along the standard NEP (A to 5

ACCEPTED MANUSCRIPT B) and in the high latitudes (from C through F and E to D), and the HSR (from C through F to G). CS, ESS, LS, KS, and BS denote the Chukchi, East Siberian, Laptev, Kara, and Barents Seas,

IP

T

respectively.

SC R

2.2. Remote sensing data

Table 1 summarizes all remote sensing data used in this study. Along the NEP and HSR, test points are defined at every 0.25° of longitude, with distances ranging from 15 to 40 km depending

NU

on the latitude. In total, 661 and 721 test points are defined through the NEP and HSR,

MA

respectively. Remote sensing data derived from the four pixels surrounding the test points are bilinearly interpolated to the test points before any analysis, and on-land pixels are excluded from

D

the interpolation. The long-term trends in all satellite products are explored when data are

TE

available. Statistical significance is evaluated against the null hypothesis using t test statistics.

CE P

Time series of passive microwave data from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) for 1979–1986, Defense Meteorological Satellite Program (DMSP) Special

AC

Sensor Microwave/Imager, (SSM/I) for 1987–2007, and DMSP Special Sensor Microwave Imager Sounders (SSMIS) for 2008–present provide consistent information on sea ice concentration and extent (Fetterer and Knowles, 2004; Markus and Cavalieri, 2000). The data are provided every other day from 1979 to 1986 and daily for the subsequent years at a grid size of 25×25 km2. Sea ice concentration data retrieved using the National Aeronautics and Space Administration (NASA)-Team 2 algorithms (Markus and Cavalieri, 2000) from June to November, are used to

assess seasonal changes in ice conditions and the open period for sea routes. Three ice concentration thresholds of 75%, 50%, and 15% are used to define the open period. Most classification guidelines for icebreakers are scaled by ice thickness and type, for example, the 6

ACCEPTED MANUSCRIPT Polar Class (PC; International Association of Classification Societies [IACS], 2011). Most of the sea ice in the eastern Arctic Ocean is first-year ice in the recent years (Maslanik et al., 2011).

IP

T

Based on the general definitions of PC icebreakers (Table 2), we can relate the ice concentration

SC R

thresholds of 75%, 50%, and 15% to navigability for PC 4 icebreakers, PC 6 icebreakers (including R/V Xuelong), and open-water vessels, respectively. To explore spatial changes, open periods are estimated separately for every test point using these thresholds. In practice, a navigable

NU

sea route should be completely open. Therefore, the day that the entire sea route becomes open at

MA

all test points with no exceptions is also estimated.

Sea ice concentration derived from the Advanced Microwave Scanning Radiometer aboard

D

EOS (AMSR-E; launched in 2002), using the Arctic Radiation and Turbulence Interaction STudy

TE

(ARTIST) sea ice (ASI) algorithm offers spatial resolution a factor of four finer than the

CE P

SMMR–SSMIS data (6.25 × 6.25 km2). Therefore, the AMSR-E data has a relatively high ability to identify sea ice in the marginal ice zone (MIZ) and coastal zone (Spreen et al., 2008). However,

AC

the AMSR-E satellite stopped transmitting in October 2011, and consequently, the data cannot be used to determine the long-term changes. Here, we use the AMSR-E data from 2003 to 2010 to assess the open period of sea routes determined by the SSM/I–SSMIS data. Using SMMR–SSMIS brightness temperature data, Markus et al. (2009) defined four stages for an ice surface melt season: early melt, continuous melt, early freeze-up, and continuous freeze-up. We use the data for continuous melt and early freeze-up to determine long-term changes. The time between these two stages is defined as the inner length of the ice melt season (Stroeve et al., 2014). Sea ice thickness derived from the Ice, Cloud, and land Elevation Satellite (ICESat) was 7

ACCEPTED MANUSCRIPT available from 2003 to 2008 (Kwok and Cunningham, 2008). We use the data from release 428, which is a composite over the ICESat measurement period (Kwok et al., 2009). The duration of

IP

T

the measurements is about 35 days in October–November or February–March (Table 3). The

SC R

ICESat-retrieved ice thickness is available for 25-km segments. Its spatial resolution is also dependent on the zonal density of the satellite orbit. For the study area of 67–82°N, its spatial resolution is 30–50 km. There are no ICESat data for the 20–104°E sector along the NEP. Sea ice

NU

thickness data derived from CryoSat-2 are available from 2011 to the present, and are obtained by

MA

the CryoSat-2 level-2 processor (Hendricks et al., 2013) as monthly composites because of the 30-day subcycle of the satellite orbit pattern (Wingham et al., 2006). To compare CryoSat-2 data

D

with the ICESat product, we calculate two-month averages for October–November and

TE

February–March in 2011 and 2012 using the CryoSat-2 data. The spatial resolution of CryoSat-2

CE P

for our study area is 20–30 km. The two datasets are combined to detect the interannual variations in ice thickness from 2003 to 2012.

AC

Two products for sea ice type are used to extend the time series from 2003 to 2012. The first is obtained from the Norwegian Meteorological Service Ocean and Sea Ice Satellite Application Facility (OSI-SAF) system, available from 2005 to the present. Sea ice classes are assigned from atmospherically corrected SSM/I–SSMIS brightness temperatures and advanced scatterometer data products (Eastwood, 2012). The other is obtained from Ku-band backscatter measured by the SeaWinds instrument aboard QuikSCAT, available from 2003 to 2009 with a spatial resolution of 8–10 km (Swan and Long, 2012). Using these data, we calculate the percentage of multiyear ice along the NEP and HSR on 15 March, which is roughly when Arctic sea ice reaches its annual maximum extent. 8

ACCEPTED MANUSCRIPT

Overlap

Spatial

period

resolution

SMMR

1979–1986

concentration

SSM/I

1987–2007

SSMIS

2008–2012

AMSR-E

2003-2010

SMMR

1979–1986

SSM/I

1987–2007

SSMIS

2008–2012

Melt/freeze-up

SMMR

1979–1986

onset

SSM/I

1987–2007

SSMIS

2008–2011

Ice thickness

ICESat

CryoSat-2

6.25km

25km

25km

30–50km

2011–2012

20–30km

D

Ice thickness

2003–2008

TE

OSI-SAF

2005–2012

25km

Ice type

QuikSCAT

2003–2009

8–10 km

CE P

Cavalieri et al., 1996

http://www.iup.uni-bremen.d

Speen et al.,

e:8084/amsr/amsre.html

2008

ftp://sidads.colorado.edu/pub

Fetterer et al.,

/DATASETS/

2002

http://neptune.gsfc.nasa.gov/

Markus et al.,

csb/index.php?section=54

2009

http://icdc.zmaw.de/seaicethi

Kwok et al.,

ckness_satobs_arc.html?&L

2009

=1 http://www.meereisportal.de/

Hendricks et

de/datenportal/karten_und_d

al., 2013

atenarchiv/

Ice type

AC

ftp://sidads.colorado.edu/pub /DATASETS/

MA

Ice extent

25km

Reference

IP

Ice

Archive

SC R

Data source

NU

Product

T

Table 1 Descriptions of satellite remote sensing data used in the present study

http://osisaf.met.no/p/ice/#ed

Eastwood,

geAndType_details

2012

http://www.scp.byu.edu/data/

Swan and

Quikscat/iceage/Quikscat_M

Long, 2012

YFY.html#2003

Table 2 General description of Polar Class icebreakers (IACS, 2011)

Classification

Navigational conditions

PC 1

Year-round operation in all Arctic ice-covered waters

PC 2

PC 3

PC 4

PC 5

PC 6

PC 7

Year-round operation in moderate multiyear ice conditions Year-round operation in second-year ice which may include multiyear ice inclusions Year-round operation in thick first-year ice which may include old ice inclusions Year-round operation in medium first-year ice which may include old ice inclusions Summer/autumn operation in medium first-year ice which may include old ice inclusions Summer/autumn operation in thin first-year ice which may include old ice inclusions 9

Minimum level of icebreaking capability, m 3.0 2.4

1.8

1.3

1.0

0.7

0.5

ACCEPTED MANUSCRIPT

Table 3 Description of ICESat campaigns (Kwok et al., 2009) Period

notation(mmyy)

Days of operation

24 Sep. to 18 Nov.

55

FM04

17 Feb. to 21 Mar.

34

ON04

3 Oct. to 8 Nov.

FM05

17 Feb. to 24 Mar.

ON05

21 Oct to 24 Nov.

FM06

22 Feb. to 27 Mar.

ON06

25 Oct. to 27 Nov.

MA07

12 Mar. to 14 Apr.

17 Feb. to 21 Mar.

35 34 34 34 37 34

MA

2.3 Atmospheric circulation patterns

36

SC R

2 Oct. to 5 Nov.

FM08

37

NU

ON07

IP

ON03

T

Campaign

The monthly National Centers for Environmental Prediction–National Center for

D

Atmospheric Research (NCEP–NCAR) Reanalysis SLP data (Kistler et al., 2001) north of 70°N

TE

are used to derive the empirical orthogonal function (EOF) modes. The AO and DA correspond to

CE P

the first and second leading modes of the EOF (Wu et al., 2006). The empirical relationships between the lengths of the open period of sea routes and the seasonal average AO/DA indices are

AC

analyzed to determine the responses of sea ice to atmospheric circulation patterns.

3. Results

3.1. Sea ice concentration Eight to nine-year average sea ice concentrations and their anomalies relative to the average for 1979–2012 along the NEP and HSR are shown in Figs. 2 and 3, respectively. The boundaries of the Chukchi, East Siberian, Laptev, Kara, and Barents sectors along these sea routes are defined at approximately 179°E, 142°E, 103°E, and 67°E, respectively. Along the NEP, sea ice cover decreased significantly from the early 1980s to 2004–2012, almost disappearing throughout the entire NEP from early August to mid-October. Previous studies have shown that Arctic winter 10

ACCEPTED MANUSCRIPT retreat of sea ice has been most pronounced in the Barents Sea during the last three decades (Rodrigues, 2008) as a result of the increased advection of heat from the Atlantic Ocean (Årthun et

IP

T

al., 2012; Rogers et al., 2013). The near year-round opening of the Barents sector would not only

SC R

be beneficial to shipping, but also to offshore oil and gas drilling operations.

On average, the largest sea ice concentration appeared in the mid-East Siberian sector (150–170°E) and at the boundary between the Laptev and Kara sectors (90–110°E). Ocean

NU

bathymetry controls the distribution and mixing of warm and cold waters. At both sites, the deep

MA

Arctic basin extends to relatively low latitudes. Therefore sea ice extends quite a long way south during summer (Nghiem et al., 2012). In mid-September 2007, the Arctic sea ice edge reached

D

about 75°N near the Taimyr Peninsula, which is the northernmost point of the Eurasian mainland.

TE

The NEP was not completely ice free this year, although Arctic ice extent decreased to a record

CE P

low since 1979 (Fig. 1). Seasonally significant negative anomalies occurred from late September to late November when sea ice cover started to increase. The fastest decreasing trend of monthly

AC

averaged ice concentration occurred in October (−1.76% per year, P<0.001; Fig. 4). This resulted in the shifting of the end of the ice-free period from late September in the 1980s to late October after 2005 for most sectors, implying a later recovery of sea ice after the melt season.

11

MA

NU

SC R

IP

T

ACCEPTED MANUSCRIPT

Fig. 2 SMMR–SSMIS-derived multiyear average sea ice concentration along the NEP from 1 June

D

to 30 November (a–d) and the corresponding anomalies relative to the 1979–2012 average (e–h).

TE

As shown in Fig. 3, along the HSR ice-free events occurred only in the Chukchi and Barents

CE P

sectors from 1979 to 1996, while in 1997–2004 a short ice-free period was also observed in the eastern Laptev sector during September. Ice-free windows appeared in all sectors in 2005–2012,

AC

with an inconspicuous exception just north of Severnaya Zemlya Islands at about 100°E. This indicates that there has been a distinct sea ice loss along the HSR since 2005. Especially in the summer of 2012, the ice-free period for the entire HSR lasted 42 days, from 27 August to 8 October, making this summer the most accessible since 1979. The opening of the HSR in recent years can be considered as a significant extension of the NEP further northward from the coast. The fastest decreasing trend of the monthly averaged sea ice concentration occurred in September (−1.64% per year, P<0.001; Fig. 4) along the HSR, 1 month earlier than in the NEP. On average, the highest sea ice concentration was in sector 60–100°E, which made the HSR inaccessible for open-water vessels in most years. 12

ACCEPTED MANUSCRIPT In the sector 60–180°E along the NEP, the average sea ice concentration for July–October was 59% in the 1980s, about twice the average after 2000 (Fig. 4). Along the HSR, the

IP

T

corresponding ice concentration was 82% in the 1980s, about 1.4 times that after 2000. Using the

SC R

R/V Xuelong (PC 6) as an example, in summer she can navigate through waters covered by 30% first-year sea ice at a speed of about 12 knots. The speed decreases to about 7 knots for 60% first-year sea ice cover. This means that it would take the R/V Xuelong 15 days less to travel

NU

through NEP sector 60–180°E in the 2000s compared with the 1980s, even without considering

MA

the influence of the thinner sea ice. The average July–October sea ice concentrations in 2012 along the NEP and HSR sectors 60–180°E reached their recorded minima since 1979, with values

TE

AC

CE P

1979–2012 climatology.

D

of 13% and 32%, respectively. These values were about 31% and 43%, respectively, of the

Fig. 3 The same as Fig. 2, but for the HSR.

13

ACCEPTED MANUSCRIPT 0

40

60

80

100

Sea ice concentration /%

(a)

S =-0.31, R=0.62, P<0.001 S =-1.76, R=0.81, P<0.001

Sep.

S =-1.50, R=0.75, P<0.001

Aug.

S =-1.34, R=0.77, P<0.001

T

Oct.

Jul.

S =-1.01, R=0.72, P<0.001 S =-0.62, R=0.65, P<0.001

Jun. 1984

1989

1994

1999

(b)

Sep. Aug. Jul. Jun.

2009

1989

1994 Year

1999

2004

S =-0.14, R=0.47, P<0.01 S =-1.21, R=0.71, P<0.001 S =-1.64, R=0.69, P<0.001 S =-1.29, R=0.72, P<0.001 S =-0.55, R=0.62, P<0.001 S =-0.17, R=0.46, P<0.01

2009

MA

1984

NU

Month

Oct.

1979

2004

SC R

1979 Nov.

IP

Month

Nov.

20

Fig. 4 SMMR–SSMIS-derived monthly mean ice concentration from 60°E to 180°E along the

D

NEP (a) and the HSR (b). Also shown are the slope with unit of percent per year (S), correlation

TE

coefficient (R), and confidence level (P) of the linear trend in monthly ice concentration from

CE P

1979 to 2012.

3.2. Open period

AC

Open periods increased from 1979 to 2012 but with distinct year-to-year variability for both sea routes (Fig. 5). Along the NEP the open periods, averaged over all test points between 1979 and 2012 defined by ice concentration thresholds of 75%, 50%, and 15%, were 125, 104, and 81 days, respectively. Along the HSR, the corresponding values were 69, 47, and 30 days, respectively. Therefore, the open period was significantly longer in the NEP than in the HSR. Along the NEP, the open periods averaged from all test points defined by an ice concentration threshold of 50% were 84, 99, and 118 days during the 1980s, 1990s, and 2000s, respectively, while along the HSR, the corresponding values were 29, 41, and 61 days, respectively. This indicates a marked increase in the open period for both sea routes. The longest open period 14

ACCEPTED MANUSCRIPT averaged over all test points occurred in 2012, with values of 146 and 110 days for the NEP and HSR, respectively, using a 50% ice concentration threshold.

IP

T

Along the NEP, the Kara, Laptev, and East Siberian sectors were relatively inaccessible.

SC R

Their open periods were fairly similar prior to 2004, but the open period of the Kara sector has increased considerably since 2004. The open period averaged over the Kara test points was 63 days in 1979–2003 but increased to 121 days in 2004–2012, indicating that the Kara sector

NU

became more accessible than the Laptev and East Siberian sectors. Along the HSR, the Chukchi

MA

sector was mostly accessible, with an open period (114 days) comparable to the NEP (110 days). Therefore, the optimal sea route can extend to relatively high latitudes north of Wrangel Island to

D

avoid near-shore shallow waters and to ensure a consistently high level of accessibility. The HSR

TE

Kara sector was the most inaccessible. It was almost completely inaccessible prior to 2005, and

CE P

thereafter there was a very short open period (4–22 days). The HSR Barents sector was quite accessible. The open period averaged from test points in the sector was 60 days, but was still

AC

much shorter than the NEP Barents sector (169 days). Therefore, the sea route north of Franz Joseph Land and Svalbard was not optimal. A better route could be taken between the Severnaya Zemlya Islands and Franz Joseph Land, at relatively low latitudes in the Kara and Barents Seas, because the length of the ice-free season tends to increase considerably from the north to the south of Franz Joseph Land.

15

ACCEPTED MANUSCRIPT

130

100

100

70

70

40

40 1980

Longitude /E

1990

1995

2000

2005

2010

10

160

130

130

100

100

70

70

40

40

10

10

1980

1985 (c) <15%

1990

1995

2000

2005

2010

1980

190

160

160

130

130

100

100

70

70

40 10

1980

190

160

190

Longitude /E

1985 (b) <50%

160

40

1980

1985

1990

1995

2000

2005

2010

Year

1985 (e) <50%

10

1990

1995

2000

2005

140

2010

120 100

IP

10

180

T

130

1985 (f) <15%

NU

Longitude /E

160

190

(d) <75%

190

160

SC R

(a) <75%

190

1980

1985

1990

1990

1995

1995

2000

80 60 2005

40

2010

20 0 Open period /d

2000

2005

2010

Year

MA

Fig. 5 SMMR–SSMIS-derived open period defined by ice-concentration thresholds of 75%, 50%

D

and 15% along the NEP (a–c) and the HSR (d–f) from 1979 to 2012.

TE

Based on a 15% ice concentration threshold, an open period for the entire NEP (open at all test points with no exceptions) only occurred after 2009 (Fig. 6). The open days were discretely

CE P

distributed from September to early October, which implies that for an open-water vessel it is still hard to use this sea route unless course adjustments are made using real-time sea ice charting.

AC

Based on a 50% ice concentration threshold, the longest continuous open period for the entire NEP lasted about 43 days from September to early October in 2005 and 2009. The NEP was not open completely in the summers 2006 and 2007 because of localized blockages of sea ice. In 2012, the open period for the entire NEP defined by a 50% ice concentration was episodically interrupted from 23 August to 12 October. Except for those short interruptions, the NEP was open throughout this period. Therefore, PC 6 icebreakers can use the NEP for about 50 days if some small course adjustments can be made. Based on a 75% ice concentration threshold, the number of open days increased further and there were open days in all years since 2005. Continuous open periods longer than 40 days also appeared in the summers of 1995 and 2002 based on this 16

ACCEPTED MANUSCRIPT threshold. For the HSR, a completely open period was observed only in the 2012 summer even using a threshold of 75% ice concentration. The continuous open period lasted 47 days from 27

IP

T

August to 13 October 2012, comparable with the NEP. Using thresholds of 15% and 50%, the

2012 2009

2004

2004

1999

1999

1994

1994

1989

1989

1984

1984

(a)<15%

2012 2009

SC R

2012 2009

2004 1999 1994 1989

(b)<50%

NU

Year

continuous open period of the HSR was even longer than that of the NEP in the 2012 summer.

1984

(c)<75%

1979 1979 1979 1 Jun 1 Jul 31 Jul 29 Aug28 Sep 28 Oct27 Nov 1 Jun 1 Jul 31 Jul 29 Aug28 Sep 28 Oct27 Nov 1 Jun 1 Jul 31 Jul 29 Aug28 Sep 28 Oct27 Nov

2004

1999

1999

1994

1994

1989

1989

1984

1984

(d)<15%

Date 2012 2009 2004 1999 1994 1989

D

2004

MA

Date

2012 2009

TE

Year

Date

2012 2009

1984

(e)<50%

(f)<75%

1979 1979 1979 1 Jun 1 Jul 31 Jul 29 Aug28 Sep 28 Oct27 Nov 1 Jun 1 Jul 31 Jul 29 Aug28 Sep 28 Oct27 Nov 1 Jun 1 Jul 31 Jul 29 Aug28 Sep 28 Oct27 Nov

Date

Date

Date

CE P

Fig.6 SMMR–SSMIS-derived open days (blue) for the entire NEP (a–c) and the entire HSR (d–f)

AC

using ice concentration thresholds of 15%, 50% and 75%.

3.3. Melt season

The long-term average onset of ice surface melting along the NEP ranged from 19 March (Day of Year [DoY] 77) to 27 June (DoY 177), with an average onset day of 4 June (DoY 154) (Fig. 7). It was earliest in the Barents sector, with a spatial average on 26 April (DoY 115). Most parts of the Barents sector remained open water all year so the onset of melting and freeze-up cannot be defined. In the Chukchi sector, the average onset day was 5 June (DoY 155). The onset of melting was similar among the other sectors, averaging 12 June (DoY 162), 18 June (DoY 168), and 16 June (DoY 166) in the East Siberian, Laptev, and Kara sectors, respectively. The long-term trends are estimated only for the sectors east of 80°E, where no year-round open water is 17

ACCEPTED MANUSCRIPT identified. The average over all test points was −0.26 days per year from 1979 to 2011. Most test points (77%) show a trend to earlier onset of ice surface melting. However, only a quarter of these

IP

T

trends are statistically significant at the 0.05 level.

SC R

The dates of freeze-up along the NEP ranged from 6 September (DoY 248) to 31 January (DoY 395), with an average over all test points of 15 October (DoY 287). The Barents sector had much later freeze-up than the other sectors, with an average of 29 December (DoY 362). The

NU

spatially averaged freeze-up dates were 4 October (DoY 276), 27 September (DoY 269), 18

MA

September (DoY 260), and 4 October (DoY 276) for the Chukchi, East Siberian, Laptev, and Kara sectors, respectively. East of 80°E, most test points (98%) showed long-term trends to later dates

D

of freeze-up significant at the 0.05 level. This highlighted that delayed freeze-up was more

TE

significant than the earlier start of surface melt. The trend in freeze-up date averaged over all test

CE P

points was +1.37 days per year from 1979 to 2011. In general, the trend in surface melt onset is primarily a result of warming atmospheric temperature. In addition to atmospheric forcing,

AC

freeze-up onset is largely influenced by heat from the ocean mixed layer, which needs to be transferred to the atmosphere before freeze-up. Therefore, the ice albedo feedback amplifies the trend in freeze-up onset. Earlier surface melt onset might result in a later freeze-up. However, this connection was significant only in the Laptev and Kara sectors (Table 4), because in general, this causal link could be disturbed by atmospheric and oceanographic dynamics during the melt season. The length of the melt season averaged from the NEP test points was 133 days, with averages of 121, 107, 92, 109, and 246 days for the Chukchi, East Siberian, Laptev, Kara, and Barents sectors, respectively. These numbers were comparable with the open periods defined by the ice 18

ACCEPTED MANUSCRIPT concentration threshold of 75%. Compared with the onset of surface melting, the melt season was more dependent on freeze-up (Table 4). Most NEP test points (97%) showed a trend toward a

IP

T

longer melt season significant at the 0.05 level, even though the trends of the surface melt onset

SC R

were mostly ambiguous. The long-term trend in the length of the melt season averaged over the

AC

CE P

TE

D

MA

NU

NEP test points was +1.65 days per year.

Fig. 7 SMMR–SSMIS-derived onset of surface ice melt (a) and freeze-up (b), the length of the melt season (c), their long-term averages (d–f), and the slopes of the linear trend (g–i) from 1979 to 2011 for the NEP. Black marks (n.s.) denote the trend is insignificant at the 0.05 level.

Table 4. Statistical relationships between the melt season and open period for the NEP. Significance levels are P<0.001 (***), P<0.01 (**), and P<0.05 (*). n.s. denotes insignificant at the 0.05 level.

Melt onset vs. Melt season

Chukchi

East Siberian

Laptev

Kara

−0.64***

−0.53**

−0.83***

−0.84***

19

ACCEPTED MANUSCRIPT

season

0.89***

0.96***

0.94***

0.94***

n.s.

n.s.

−0.58***

−0.61***

0.72***

0.89***

0.86***

0.81***

Melt onset vs. Freeze-up Melt season vs. Open

IP

period (75%)

T

Freeze-up vs. Melt

SC R

In the HSR, the long-term averages for the onset of surface melt ranged from 11 May (DoY 130) to 5 July (DoY 185), with an overall average of 19 June (DoY 169) or about half a month

NU

later than for the NEP (Fig. 8). The largest difference between NEP and HSR occurred in the Barents sector, with a spatially averaged deviation of 49 days. The long-term trend in the onset of

MA

surface ice melting in the HSR averaged −0.38 days per year from 1979 to 2011. Most test points

D

(82%) showed a negative trend, but 78% of them were insignificant at the 0.05 level, comparable

TE

with the results for the NEP. The long-term average of the HSR freeze-up date ranged from 31

CE P

August (DoY 242) to 24 December (DoY 357), with an overall average of 27 September (DoY 269), about half a month earlier than for the NEP. The most distinct difference between the HSR freeze-up and the NEP freeze-up occurred in the Chukchi sector, where the spatially averaged

AC

freeze-up was on 26 October (DoY 298), 22 days later than freeze-up in the NEP. The long-term trend in freeze-up averaged over all HSR test points was +1.41 days per year from 1979 to 2011. Most trends (99%) were positive, and 82% were significant at the 0.05 level. Because of the later melt onset and earlier freeze-up, the melt season was 34 days shorter in the HSR than in the NEP, with the exception of one subsection in the Chukchi Sea. The average length of the melt season was 137, 90, 84, 66, and 127 days in the HSR Chukchi, East Siberian, Laptev, Kara, and Barents sectors, respectively. The long-term trend in the length of the HSR melt season averaged +1.79 days per year. All trends were positive, and 85% were significant at the 0.05 level. Similar to the NEP, the length of the melt season in the HSR was more dependent on the freeze-up than on the 20

ACCEPTED MANUSCRIPT

MA

NU

SC R

IP

T

onset of surface melting (Table 5).

D

Fig. 8 The same as Fig. 7, but for the HSR.

TE

Table 5. The same as Table 4, but for the HSR. Chukchi

Laptev

Kara

Barents

−0.63***

n.s.

−0.74***

−0.60***

−0.74***

0.94***

0.92***

0.94***

0.94***

0.92***

n.s.

n.s.

−0.48**

n.s.

−0.36*

0.73***

0.85***

0.84***

0.65***

0.70***

CE P

Melt onset vs. Melt

East Siberian

season

Freeze-up vs. Melt season

AC

Melt onset vs. Freeze-up

Melt season vs. Open period (75%)

3.4 Sea ice thickness Generally, the thickest sea ice in October–November along the NEP was found at ~ 110°E (western Laptev Sea). However, most of the sea ice thicker than 1.5 m disappeared gradually after 2005, and ice thicker than 1.3 m disappeared completely by 2012 (Fig. 9). The spatially averaged NEP ice thickness east of 104°E did not show any distinct change from 2003 to 2006. Because most parts of the NEP changed to open water in October–November 2007, the spatially averaged ice thickness decreased by about 1.0 m, from 1.2–1.3 m in 2003–2006 to 0.3 m in 2007. The mean 21

ACCEPTED MANUSCRIPT ice thickness was slightly higher (0.6 m) in 2011 but decreased again to 0.2 m in 2012. Comparisons of the October–November ice thickness distributions show that most of the sea ice

IP

T

thicker than 1.0 m in 2003 was replaced by ice thinner than 0.8 m in 2012 (Figs. 9d and 9e). The

SC R

increase in ice thickness from fall to late winter ranged from 0.5 m to 1.6 m. Regions with thin sea ice in fall tend to have large winter growth rates because of low insulation of the thin ice. Consequently, the February–March/March–April ice thickness was comparable in all years,

NU

ranging from 1.7 m to 2.1 m. Although the 2007 ICESat winter campaign was about 1 month later

MA

than in other years, no larger winter ice thickness was observed because most ice growth rates were very small after February in the NEP. 50

140 130 120 110

Ice thickness /cm

100 50

2004

2005

2006

300

350 Ice thickness /cm

180 170 160 150 140 130 120 110

2007

2011

2012

2004 (b)

Year

AC

2003 (a)

250

2005

Frequency /%

150

150

200

TE

160

CE P

Longitude /E

170

200

150

0 ON FM/MA Deviation -50 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Year (c)

Frequency /%

180

250

100

D

0

2006

2007

2008

2011

2012

Year

30.8

(d)

23.1 15.4 7.7 0 0 61.6

50

100

150

200

250

300 (e)

46.2 30.8 15.4 0 0

25

50

75

100

125

Ice thickness /cm

Fig. 9 Sea ice thicknesses (derived from ICESat between 2003 and 2008 and from CryoSat-2 between 2011 and 2012) along the NEP during October–November (ON) (a), and February–March/March–April (FM/MA) (b), the spatial averages and the deviations between them (c), and the frequency distributions of ice thickness in ON of 2003 (d) and 2012 (e).

22

150

ACCEPTED MANUSCRIPT Along the HSR, the spatially averaged sea ice thicknesses ranged from 0.4 to 1.9 m in October–November and from 1.3 m to 2.4 m in February–March/March–April in 2003-2012,

IP

T

respectively (Fig. 10). There was a distinct sea ice tongue reaching to relatively low latitudes in

SC R

the western Laptev Sea and north of Severnaya Zemlya Islands during 2007 summer (Fig. 1). Consequently, relatively thick ice was found at 100–110°E along the HSR in October–November. Because the fractions of open water and thin sea ice were increasing, the spatially averaged ice

NU

thickness in October–November decreased from 1.5–1.9 m prior to 2007 to 0.4–1.1 m in the

MA

succeeding years. The increased ice thickness from fall to late winter ranged from 0.1 m to 0.6 m in 2003–2012, much less than along the NEP, because of the larger initial ice thickness in fall

D

along the HSR. Different from the NEP, the sea ice thickness also decreased remarkably in

TE

February–March of 2012 compared to the previous years, as a result of the disappearance of ice

200

300

400

AC

Longitude /E

Ice thickness /cm 190 170 150 130 110 90 70 50 30 10 (a)2003 2004 2005 2006 2007 2011 2012 190 170 150 130 110 90 70 50 30 10 2004 2005 2006 2007 2008 2011 2012 (b) Year 300 200 100 0 -100 ON FM/MA Deviation 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 (c) Year

Longitude /E Ice thickness /cm

100

Frequency /% Frequency /% Frequency /% Frequency /%

0

CE P

thicker than 2 m for the entire sea route and the increase in open water north of Svalbard. 13.8 (d) 6.9 0 0 27.8

50

100 150 200 250 300 350 (e)

13.9 0 0 13.8

25

50

75

100 125 150 175 (f)

6.9 0 100 150 200 250 300 350 400 450 27.6 20.7 (g) 13.8 6.9 0 0 50 100 150 200 250 300

Sea ice thickness /cm

Fig. 10 Sea ice thicknesses (derived from ICESat between 2003 and 2008 and from CryoSat-2 between 2011 and 2012) along the HSR during October–November (ON) (a), and 23

ACCEPTED MANUSCRIPT February–March/March–April (FM/MA) (b), the spatial averages and the deviations between them (c), and the frequency distributions of ice thicknesses in ON/FM of 2003 (d/f) and 2012

IP

T

(e/g).

SC R

3.5 Ice type

The multiyear ice that reached the northern shores of the Severnaya Zemlya Islands, Franz Joseph Land, and Svalbard in March 2003 retreated gradually north thereafter (Fig. 11).

NU

Meanwhile, the multiyear ice that extended into the Laptev Sea and East Siberian Sea in March

MA

2003 and 2005 totally disappeared in March 2007 and 2009. On 15 March 2003, the percentage of multiyear ice along the NEP and HSR was 5% and 51% respectively. This percentage decreased to

D

1–2% and 3–4%, respectively, in 2006, and close to zero after 2007. The decrease in multiyear ice

TE

in winter significantly contributes to the increase in the summer opening period, because the

CE P

thicker multiyear ice is more likely to survive the melt season (Xie et al., 2013). The sea ice thickness in October–November 2005, averaging 1.4 m in the HSR, was obviously smaller than in

AC

the two previous years, averaging 1.7–1.9 m (Fig. 10), because of the loss of multiyear ice.

24

(b) 2005

(c) 2007

(d) 2009

SC R

NU

50

OSI-NEP QuikSCAT-NEP OSI-HSR QuikSCAT-HSR

(e)

40 30

MA

20 10

No data

Land

Open water NEP

First Multiyear -year ice ice HSR

0 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Year

D

Multiyear ice fraction /%

IP

(a) 2003

T

ACCEPTED MANUSCRIPT

TE

Fig. 11 Distribution of ice types on 15 March 2003 (a), 2005 (b), 2007 (c), and 2009 (d), and the percentage of multiyear sea ice along the NEP and HSR (e). The data shown in panels a–d are

CE P

derived from the QuikSCAT product, and those shown in panel e are derived from both the

AC

QuikSCAT and OSI-SAF products.

4. Discussion

4.1 Limitations of remote sensing data The major limitation of the SMMR–SSMIS data for Arctic sea ice charting is its coarse spatial resolution, which makes it difficult to solve mixed coastal pixels and to identify sea ice at the landfast ice or MIZ boundaries (Spreen et al., 2008). To assess the use of SMMR–SSMIS data to estimate the open period for the sea routes, we also evaluated the open period from 2003 to 2010 using the AMSR-E sea ice concentration data. A threshold of 50% ice concentration was selected. Visually, the NEP open periods derived from both datasets have similar spatial and 25

ACCEPTED MANUSCRIPT interannual changes (Figs.12a and 12b). The deviation between the two datasets ranged from −30 to +38 days (Fig. 12c), with a nearly unbiased normal distribution averaging 0.4±6.5 days (Fig.

IP

T

12e). Relatively large absolute bias occurred in the 90–120°E and 175–185°E sectors, with values

SC R

of 6.0±5.2 and 7.0±6.1 days, respectively (Fig. 12d). Both sectors are located near the coast and contain some narrow straits or offshore islands as shown in Fig.1. Moreover, there was a relatively large standard deviation (6.0 days) for the absolute bias in the Barents sector. This could be

NU

attributed to a large deviation between the two datasets in 2003, spatially averaging −16.3±6.6

MA

days. During most of the 2003 summer, the sea ice edge was located relatively far southward and reached the NEP Barents sector. The large deviation could be attributed to the different abilities of

D

these satellite sensors to observe MIZ conditions. Except for 2003, the deviation for this sector

TE

could be ignored because most test points had ice concentrations below 50% from June to

CE P

November. Very few (~10%) samples had a deviation (relative deviation) > 10 days (10%) (Fig. 12e). The deviation of open periods along the HSR determined by SMMR–SSMIS and AMSR-E

AC

data averaged 0.3±4.5 days, with 95% distributed in a bin of ±5 days (not shown here), which was better than the deviation along the NEP. This could be attributed to the fact that there are less test points along the HSR with mixed coast pixels or ice edge pixels. Using the NEP Laptev sector as an example from a climatological perspective, the long-term average and trend for the open period from 1979 to 2012 defined by 50% ice concentration using SMMR–SSMIS data were 70±32 days and +1.92 days per year (P<0.001), respectively. If the 2003–2010 AMSR-E data are used to replace the contemporaneous SMMR–SSMIS data, the long-term average and trend would change to 69±32 days and +1.89 days per year (P<0.001), respectively. The differences are only 1–2%. Therefore we argue that the SMMR–SSMIS data has 26

ACCEPTED MANUSCRIPT a comparable ability to determine the long-term behavior of sea ice as the AMSR-E data. However, the SMMR–SSMIS data do not meet the requirements for navigation purposes, especially for

IP

T

narrow waterways, such as the straits between the coast and islands. In such a situation, remote

50

100

20

-20

20

0

20

20

(a)

20 (c)

(b)

(d)

40

40

40

60

60

60

60

80

80

80

100

100

100

120

120

120

120

140

140

140

140

160

160

160

160

180

0304050607080910 Year

2.56.0

4.64.1

100

MA

180 0304050607080910 Year

80

D

180

NU

40

TE

Longitude (E)

Deviation (days)

150

4.33.9

50

Relative Deviation 0 20 40

40

Frequence (%)

Open period (days) 0

SC R

sensing data with a high spatial resolution (e.g., from synthetic aperture radar) are required.

(e)

30 20 10 0 -40

4.03.5

-20 0 20 Deviation (days)

40

180

0304050607080910 Year

7.87.4 -10 0 10 20 30 Absolute bias (days)

CE P

Fig. 12 Open period defined by an ice concentration threshold of 50% determined by SMMR–SSMIS data (a), AMSR-E data (b), and their deviation (c) along the NEP from 2003 to

AC

2010. The multiyear average (red line) and standard deviation (gray line) of the absolute biases are shown along with the dashed blue lines dividing the subsection along the NEP. Also shown are the spatial average and standard deviation of the subsections (d). The frequency distributions of deviation and the relative deviation of the open period (e).

Because of sea ice surface melt, spaceborne altimeter cannot accurately measure the ice freeboard, and ice thickness data are not available from ICESat or CryoSat during summer. This limits the accurate estimation of navigable periods using a threshold combining ice concentration and thickness. Furthermore, both the inter-sensor offset and the exact duration of the operation 27

ACCEPTED MANUSCRIPT period of ICESat and CryoSat campaigns could bias the comparison to a certain degree. As seen in Table 3, the 2004 and 2007 ICESat fall campaigns ran from early October to early November,

IP

T

comparable with the October measurements of CryoSat. The average NEP ice thicknesses derived

SC R

from the ICESat fall measurements in 2004 and 2007 and the CryoSat October measurements in 2011 and 2012 were 1.2, 0.3, 0.4, and 0.1 m, respectively. Likewise, the 2005 and 2006 ICESat fall campaigns ran from late October to late November, which was comparable with the

NU

November measurements of CryoSat. The average NEP ice thickness derived from the ICESat fall

MA

measurements in 2005 and 2006, and the CryoSat November measurements in 2011 and 2012 were 1.2, 1.3, 0.7, and 0.3 m, respectively. Therefore, after considering the exact duration of

D

satellite operations, the results still clearly support the distinct thinning of fall sea ice since 2007.

TE

Compared with moored and submarine upward-looking sonars, and aircraft-based electromagnetic

CE P

measurements, the biases of ICESat and CryoSat measurements ranged from −0.14 to 0.07 m (Kwok et al., 2009; Laxon et al., 2013). The thinning of sea ice after 2007 was at least 0.5 m,

AC

which overrides data errors and can be considered significant. The same as for ice thickness, there are no data on ice type available during the shipping season. However, the spring data can be used to infer that sea ice along both sea routes has been mostly first-year ice during the shipping season in recent years, except for some parts of the Chukchi and East Siberian sectors. In these sectors a few multiyear floes, advected from the western Arctic Ocean, may appear during early summer. Two datasets were also used to identify changes in sea ice type. QuikSCAT data were comparable to the OSI-SAF data for sea ice classification during overlapping years between 2005 and 2009 (Fig. 11e). This implies that inter-data deviation is negligible compared with the long-term change. 28

ACCEPTED MANUSCRIPT

4.2 Responses to atmospheric circulation

T

Pearson correlation analysis between the seasonal average AO/DA indices and the open

IP

period defined by a 50% ice concentration threshold (Tables 6 and 7) showed that the DA had a

SC R

more significant impact on the opening of both sea routes in the Chukchi, East Siberian, Laptev, and Kara sectors, especially for the summer indices. A high positive DA can load more sea ice

NU

from upstream into the Transpolar Drift Stream (TDS) (Nghiem et al., 2007; Wang et al., 2009). High positive summer DA results in extended opening of sea routes, because the advected sea ice

MA

is not replaced by new ice. In contrast, in winter these regions are cold and refreezing of open

D

water is possible. Consequently, a high positive winter DA does not result in an extended summer

TE

opening. In the Laptev sector, which is just upstream of the longitudinal center of the TDS, the impact of summer DA on the opening is more significant than in the other sectors. The summer

CE P

DA index showed a positive trend from 1979 to 2012, with a linear trend of 0.033 per year (P<0.001). Since 2007, the sustained high positive polarity of the summer DA partly contributed

AC

to longer opening of the sea routes. In the Laptev sector, the average open period (defined by 50% ice concentration) from 2007 to 2012 was 107 days and 80 days for the NEP and HSR, respectively. Both were much longer than the long-term average of 70 and 42 days, respectively, since 1979. In 2005, although the summer DA index was moderate (0.27), the monthly average DA index from March to November was 0.41, comparable to the average of 0.43 after 2007. Nearly one half of the multiyear sea ice in the eastern Arctic Ocean was depleted during 2005 (Nghiem et al., 2006). The annual minimum ice extent in the Arctic Russian sector was smaller in 2005 than in 2007 (Rodrigues, 2008). Therefore, the open period in the Laptev section in 2005 was comparable to that after 2007, with values of 103 days and 85 days for the NEP and HSR, 29

ACCEPTED MANUSCRIPT respectively. In the Barents sector, no significant relationship could be identified between the DA and the open period, because this sector is not upstream of the TDS.

IP

T

During a negative AO, an anticyclonic wind anomaly occurs that may result in increased

SC R

advection of multiyear ice from the western Arctic Ocean to the East Siberian Sea (Wu et al., 2006; Wang et al., 2009). In the melt season, the multiyear ice advected into this region may melt rapidly. Therefore, no significant relationship between the summer AO and the opening of sea routes could

NU

be identified. In contrast, multiyear ice in the ice growth season may survive longer. The

MA

relationships between winter/spring AO and the opening of the sea routes in the East Siberian Sea were significant at the 0.05 level. During a negative AO, an enhanced anticyclonic ice motion can

D

accelerate sea ice drifting north from the Kara Sea. Similar to the DA, the summer AO had a

CE P

TE

significant impact on the opening of this sector.

Table 6. Statistical relationship of seasonal average AO/DA indices and the open period defined by

AC

a 50% ice concentration threshold for the NEP. Significance levels are P<0.001 (***), P<0.01 (**), and P<0.05 (*). n.s. denotes insignificant at the 0.05 level, N/A denotes inapplicable. The subscripts w, sp, su, and a denote the winter (December–February), spring (March–May), summer (June–August), and autumn (September–November), respectively. Chukchi

East Siberian

Laptev

Kara

Barents

AO_w vs. Open period

n.s.

0.41*

n.s.

n.s.

n.s.

AO_sp vs. Open period

n.s.

0.49**

n.s.

n.s.

n.s.

AO_su vs.Open period

n.s.

n.s.

n.s.

-0.46**

n.s.

AO_a vs. Open period

n.s.

n.s.

n.s.

n.s.

n.s.

DA_w vs. Open period

n.s.

n.s.

n.s.

n.s.

n.s.

30

ACCEPTED MANUSCRIPT n.s.

0.49**

0.34*

n.s.

n.s.

DA_su vs.Open period

0.42*

0.49**

0.63***

0.63****

n.s.

DA_a vs. Open period

n.s.

0.49**

0.34*

n.s.

n.s.

T

DA_sp vs. Open period

Laptev

SC R

Kara

Barents

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

-0.39*

n.s.

MA

East

IP

Table 7. The same as Table 6, but for the HSR.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

n.s.

0.49**

n.s.

n.s.

n.s.

DA_su vs.Open period

0.41*

0.45**

0.61***

0.60*

n.s.

DA_a vs. Open period

n.s.

0.49**

n.s.

n.s.

n.s.

Chukchi

Siberian

n.s.

0.35*

AO_sp vs. Open period

n.s.

0.40*

AO_su vs.Open period

n.s.

AO_a vs. Open period

n.s.

CE P

TE

DA_sp vs. Open period

D

DA_w vs. Open period

NU

AO_w vs. Open period

AC

5 Conclusions

As a result of the dramatic decrease in the extent of multiyear sea ice in the Arctic Russian sector during the last three decades, especially in the 8 years after 2005, most very thick ice floes have disappeared from the NEP. The spatially averaged ice thickness in October–November decreased from 1.2–1.3 m prior to 2007 to 0.2–0.6 m in the succeeding years. The lengths of the open period and the melt season increased remarkably during the satellite era from 1979 to 2012 in all NEP sectors. The spatially averaged open period, defined by a 50% ice concentration threshold, increased from ~ 70 days in the early 1980s to ~ 140 days in the early 2010s, with an increasing trend of +2.1 days per year (P<0.01). The changes depended more strongly on changes

31

ACCEPTED MANUSCRIPT in the freeze-up in autumn than on the onset of ice surface melting in spring or early summer. The NEP Barents and Chukchi sectors were mostly accessible because they obtain more heat from the

IP

T

Atlantic and Pacific Oceans, respectively. During the last three decades, the most remarkable

SC R

Arctic winter ice retreat was observed in the Barents Sea, while the strongest summer retreat was observed in the Chukchi Sea. This further enhanced the accessibility of the NEP in these sectors in recent years. The NEP East Siberian, Laptev, and Kara sectors were relatively inaccessible,

NU

especially in the sector 90–110°E around the Vilkitsky Strait because of the northward extent of

MA

the Taimyr Peninsula and the southward stretch of the deep Arctic Basin. However, partly as a result of the thinning of sea ice prior to melting and enhanced positive polarity of summer DA,

D

these sectors have become more accessible. In contrast to the summer DA, the winter DA was not

TE

significantly correlated with the summer opening of the NEP, because the depleted sea ice can be

CE P

rapidly replaced by refreezing in winter. The statistical relationship between the AO and the opening of the NEP was relative weakly, because the forcing of the AO on the sea ice export from

AC

the Russian coast is not direct.

The summer opening of the HSR north of the islands of the eastern Arctic Ocean has also lengthened in recent years. The summer ice-free period reached 42 days in 2012. Using the HSR for shipping avoids the shallow waters along the coast and therefore benefits deeper-draft vessels. The lengthening of the HSR open period can be considered as an expansion of the NEP from the coast to higher latitudes. Compared to the NEP, the HSR Chukchi sector, which is just north of Wrangel Island, was more accessible. Therefore, here the HSR is the optimal route. The open period of the Barents sector was distinctly shorter in the HSR than in the NEP. Associated with the fact that the water along the NEP is relatively deep in the Barents Sea, the sea route north of 32

ACCEPTED MANUSCRIPT Svalbard and Franz Joseph Land does not need to be considered if the ship has no destinations in these islands.

IP

T

Although both the NEP and HSR have become more accessible in recent years, the spatial

SC R

distribution of sea ice has large year-to-year variability. Using the same threshold of ice concentration, the continuous period with the entire sea route open was much shorter than the open period averaged over all test points, because of localized blockages by sea ice. Therefore, the

NU

detailed sea route should be adjusted from the standard sea routes based on near real-time satellite

MA

observations.

TE

D

Acknowledgements

This work was financially supported by grants from the National Natural Science Foundation

CE P

of China (41476170), the Chinese Polar Environment Comprehensive Investigation and Assessment Programs (CHINARE2015-03-01/04-03/04-04), and Marine public industry research

AC

of China (201205007). This work has also been supported by the Nordic Center of Excellence Cryosphere-atmosphere interactions in a changing Arctic climate (CRAICC) and the NOAA Office of Arctic Research (This is GLERL Contribution No. 1755).

References Årthun, M., T. Eldevik, L. H. Smedsrud, Ø. Skagseth, R. B. Ingvaldsen, 2012: Quantifying the Influence of Atlantic Heat on Barents Sea Ice Variability and Retreat. J. Climate, 25, 4736–4743. Cavalieri, D. J., Parkinson, C. L., Gloersen, P., Zwally H., 1996. Updated yearly. Sea Ice 33

ACCEPTED MANUSCRIPT Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, gridded daily data. Boulder, Colorado USA: NASA DAAC at the National Snow and Ice

IP

T

Data Center.

SC R

Eastwood, S., 2012. OSI-SAF sea ice product manual, v3.8. EUMETSAT. Satellite Application Facility on Ocean and Sea Ice, available at http://osisaf.met.no/p/ice/. Fetterer, F., Knowles, K., Meier, W., Savoie, M., 2002. Updated daily. Sea Ice Index. Monthly

NU

extent. Boulder, Colorado USA: National Snow and Ice Data Center.

MA

Fetterer, F., Knowles, K., 2004. Sea ice index monitors polar ice extent. Eos Trans. AGU, 85(16): 163.

D

Hendricks, S., Ricker, R., Helm, V., 2013. AWI CryoSat-2 sea ice thickness data product, v1.0.

CE P

Available at

TE

Helmholtz Centre, Alfred Wegener Institute for Polar and Marine Research, Bremerhaven.

http://www.meereisportal.de/fileadmin/user_upload/Pictures/Meereisbeobachtung/cryoSat-2/

AC

AWI_CryoSat-2_Documentation_20130624.pdf. IACS, 2011. Requirements concerning polar class. International Association of Classification Societies, London. Available at http://www.iacs.org.uk/document/public/publications/unified_requirements/pdf/ur_i_pdf410. pdf. IMO, 2002. Guidelines for ships operating in Arctic ice-covered waters, MSC/Circ.1056-MEPC/Circ.394. International Maritime Organization, London. Available at http://www5.imo.org/SharePoint/blastDatArcticOceannly.asp/data_id=6629/1056-MEPC-Cir c399.pdf. 34

ACCEPTED MANUSCRIPT Kistler, R., et al., 2001. The NCEP-NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation. Bull. Am. Meteorol. Soc., 82, 247–268.

IP

T

Kwok, R., Cunningham, G.F., 2008. ICESat over Arctic sea ice: Estimation of snow depth and ice

SC R

thickness. J. Geophys. Res., 113, C08010, doi:10.1029/2008JC004753.

Kwok, R., Cunningham, G. F., Wensnahan, M., Rigor, I., Zwally, H. J., Yi, D., 2009. Thinning

C07005, doi:10.1029/2009JC005312.

NU

and volume loss of the Arctic Ocean sea ice cover: 2003–2008, J. Geophys. Res., 114,

MA

Lasserre, F., Pelletier, S., 2011. Polar super seaways? Maritime transport in the Arctic: An analysis of shipowners' intentions. J. Transp. Geogr. 19(6), 1465–1473,

D

10.1016/j.jtrangeo.2011.08.006.

TE

Laxon, S. W., Giles, K. A., Ridout, A. L., Wingham, D. J., Willatt, R., Cullen, R., Kwok, R.,

CE P

Schweiger, A., Zhang, J., Haas, C., Hendricks, S., Krishfield, R., Kurtz, N., Farrell, S., Davidson, M., 2013. CryoSat-2 estimates of Arctic sea ice thickness and volume. Geophys.

AC

Res. Lett. 40, 732–737, doi:10.1002/grl.50193, 2013. Liu, M., Kronbak, J., 2010. The potential economic viability of using the Northern Sea Route (NSR) as an alternative route between Asia and Europe. J. Transp. Geogr. 18(3), 434–444. Mahoney, A.R., Barry, R.G., Smolyanitsky, V., Fetterer, F., 2008. Observed sea ice extent in the Russian Arctic, 1933–2006. J. Geophys. Res. 113, C11005, doi:10.1029/2008JC004830. Markus, T., Cavalieri, D. J., 2000. An enhancement of the NASA team sea ice algorithm, IEEE Trans. Geosci. Rem. Sens., 38(3), 1387–1398. Markus, T., Stroeve, J.C., Miller, J., 2009. Recent changes in Arctic sea ice melt onset, freezeup, and melt season length, J. Geophys. Res., 114, C12024, doi:10.1029/2009JC005436. 35

ACCEPTED MANUSCRIPT Maslanik, J., Stroeve, J., Fowler, C., Emery, W., 2011. Distribution and trends in Arctic sea ice age through spring 2011. Geophys. Res. Lett. 38, L13502, doi:10.1029/2011GL047735.

IP

T

Nghiem, S. V., Chao, Y., Neumann, G., Li, P., Perovich, D.K., Street, T., Clemente-Colón, P.,

SC R

2006. Depletion of perennial sea ice in the East Arctic Ocean, Geophys. Res. Lett., 33, L17501, doi:10.1029/2006GL027198.

Nghiem, S.V., Clemente-Colónb, P., Rigorc, I.G., Halld, D.K., Neumanna, G., 2012. Seafloor

NU

control on sea ice. Deep Sea Research II, 77–80: 52–61.

MA

Nghiem, S. V., Rigor, I. G., Perovich, D. K., Clemente-Colon, P., Weatherly, J. W., Neumann, G., 2007. Rapid reduction of Arctic perennial sea ice. Geophys. Res. Lett. 34, L19504,

D

doi:10.1029/2007GL031138.

TE

Rigor, I. G., Wallace, J.M., Colony, R.L. 2002. Response of sea ice to the Arctic oscillation,

CE P

Journal of Climate 15, 2648–2663. Rodrigues, J., 2008. The rapid decline of the sea ice in the Russian Arctic. Cold Reg. Sci. Technol.

AC

54(2), 124-142.

Rogers, T.S., Walsh, J.E., Rupp, T.S., Brigham, L.W., Sfraga, M., 2013. Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice. Cryosphere. 7(1): 321–332. Schøyen, H., Bråthen, S., 2011. The Northern Sea Route versus the Suez Canal: Cases from bulk shipping. J. Transp. Geogr. 19(4), 977–983, 10.1016/j.jtrangeo.2011.03.003. Smith, L.C., Stephenson, S.R., 2013. New Trans-Arctic shipping routes navigable by midcentury. Proc. Natl. Acad. Sci. 110(13): 1191–1195. Spreen, G., L. Kaleschke, and G.Heygster(2008), Sea ice remote sensing using AMSR-E 89 GHz 36

ACCEPTED MANUSCRIPT channels J. Geophys. Res.,vol. 113, C02S03, doi:10.1029/2005JC003384.

IP

Sea Route. Polar Geogr. doi: 10.1080/1088937X.2013.845859.

T

Stephenson, S.R., Brigham, L.W., Smith, L.C., 2013. Marine accessibility along Russia's Northern

SC R

Stroeve, J. C., Markus, T., Boisvert, L., Miller, J., Barrett, A., 2014, Changes in Arctic melt season and implications for sea ice loss, Geophys. Res. Lett., 41, 1216–1225, doi:10.1002/2013GL058951.

MA

Geosci. Remote. 50(9), 3317–3326.

NU

Swan, A.M., Long, D.G., 2012. Multi-year Arctic sea ice classification using QuikSCAT. IEEE T.

Wang, J., Zhang, J., Watanabe, E., Mizobata, K., Ikeda, M., Walsh, J.E., Bai, X., Wu, B., 2009. Is

D

the Dipole Anomaly a major driver to record lows in the Arctic sea ice extent? Geophys. Res.

TE

Lett. 36, L05706, doi:10.1029/2008GL036706.

CE P

Wingham, D. J., Francis, C. R, Baker, S., et al., 2006. CryoSat: A mission to determine the fluctuations in Earth’s land and marine ice fields, Adv. Space Res., 37(4), 841–871.

AC

Wu, B., Wang, J., Walsh, J.E., 2006. Dipole Anomaly in the winter Arctic atmosphere and its association with Arctic sea ice motion, J. Clim. 19, 210– 225, doi:10.1175/JCLI3619.1. Xia, W., Xie, H., Ke, C., 2014. Assessing trend and variation of Arctic sea ice extent during 1979-2012 from a latitude perspective of ice edge. Polar Research. 33, 21249, doi: 10.3402/polar.v33.21249. Xie, H., Lei, R., Ke, C., Wang, H., Li, Z., Zhao, J., Ackley, S.F., 2013. Summer sea ice characteristics and morphology in the Pacific Arctic sector as observed during the CHINARE 2010 cruise. Cryosphere, 7(4), 1057–1072.

37

ACCEPTED MANUSCRIPT Highlights

AC

CE P

TE

D

MA

NU

SC R

IP

T

1 Due to multiyear ice shrinking, ice thinning and delayed freeze-up, the NEP opening increased. 2 The enhanced positive polarity of summer Arctic Dipole accelerated the opening of the NEP Laptev sector. 3 The opening of the high latitude sea route can be considered as the NEP expansion from Russian shelf.

38