Abstract

Based on the SSM/I data from 1997 to 2016, the temporal and spatial variations of Arctic sea ice are studied from sea ice areas, sea ice margin zone and sea ice concentration. The results show that the sea ice areas for 20 years (1997–2016) are reduced at a speed of 0.0594 × 106 km2 per year, and the sea ice margin zone is reduced at a speed of 0.03 × 106 km2. From 1997 to 2006, the sea ice areas and margin zone show the same downward trend, which decreased by 0.062 × 106 km2 and 0.064 × 106 km2 per year, respectively. From 2007 to 2016, the sea ice areas and margin zone show an obvious fluctuation, which decreased by 0.027 × 106 km2 and 0.019 × 106 km2 per year, respectively. In the first ten years, the sea ice concentration (90–100%) is about 40%, and it is only about 20% in the second ten years, and the decrease is particularly obvious.

INTRODUCTION

Arctic sea ice is a key factor that affects the global climate system due to its high albedo, and it has been shrinking and thinning year to year in recent decades because of the effects of global warming (Clark et al. 1999; Miao et al. 2016; Wang et al. 2017). Accurately understanding and grasping the trend of Arctic sea ice change is a necessity for studying and understanding sea ice (Zhao et al. 2018). It is also of important significance for studying the influence and function of sea ice on the global climate system (Parkinson & Cavalieri 2008; Fan et al. 2017). Quantitative calculation of the variations of Arctic sea ice over many years can reflect the trend of Arctic sea ice variations to the greatest extent, and further determine whether Arctic sea ice has abnormal variations in some years, as well as discovering other useful information (Gascard et al. 2017).

The establishment of the Polar Research Association in 1920 marked the international joint stage of sea ice research and exploration. The study of sea ice can be roughly summed up in three stages. The first stage is the preliminary, understanding stage of sea ice detection. This stage mainly studies the physical properties of sea ice, the natural properties of sea ice, and the dynamics of sea ice. The second stage is mainly to summarize and improve the results of the first stage, and to study the characteristics of sea ice variations (Allison et al. 1989), the variations of sea ice extent (Massom et al. 1999), and the movement of sea ice. The third stage is the extension stage of sea ice research, which focuses on the quantitative simulation of sea ice variations on the basis of qualitative analysis (Li et al. 2014), so that we can comprehensively understand the relationship between sea ice and global change (Parizek & Alley 2004; Eldevik et al. 2014). Comiso (2002) studied the variations in Arctic multiyear ice, and they found that it decreased by about 9% every ten years. Later, research by Comiso et al. (2008) showed that the Arctic multiyear ice showed a trend of accelerating melting. Kwok & Cunningham (2010) studied the correlation of the multiyear ice between the Beaufort Sea and the Arctic. Xie et al. (2017) researched the spatial and temporal variability of sea ice deformation rates in the Arctic Ocean based on RADARSAT-1 data from November 1996 to April 2008.

Scholars have done a great deal of research on the Arctic sea ice variations. However, there are few studies on the spatial and temporal variations of Arctic sea ice in recent years in particular, and the trend of sea ice variations has been compared with the previous changes. This paper compares and analyzes the trend of Arctic sea ice variations for two ten-year periods (1997–2006 and 2007–2016), and then obtains a series of important conclusions and the trend characteristics of sea ice variations in the future.

DATA AND METHODS

Data

This paper mainly uses microwave radiometer SSM/I data (from 1 January 1997 to 31 December 2016). The selected data channels are the 19 GHz horizontal polarization channel and vertical polarization channel, the 37 GHz horizontal polarization channel and vertical polarization channel with F13 and F17 platforms. Over the 20-year period, there are two different kinds of platforms (F13 and F17). Therefore, it is necessary to study the different sensors’ data and normalize them to the same platform.

The overlap dates for the two kinds of data are from 30 September 2008 to 1 January 2009. Using these overlapping data sets, we can perform a regression treatment to calibrate the F13 and F17 platforms to the same platform. We do this using Equation (1):  
formula
(1)
where is the SSM/I brightness temperature data for the calibrated platform, and is the brightness temperature data for the F13 and F17 platforms, respectively; a (slope) and b (intercept) are regression parameters. Different platform data conversion parameters are shown in Table 1.
Table 1

Data transformation for different platform data

Data transformation Slope Intercept Correlation coefficient 
Transform SSM/I F11 and F13 19 GHz into SSM/I F8 19 GHz 1.008 −1.17 R > 0.99 
Transform SSM/I F17 19 GHz into SSM/I F8 19 GHz 1.0286 −3.0094 R > 0.99 
Data transformation Slope Intercept Correlation coefficient 
Transform SSM/I F11 and F13 19 GHz into SSM/I F8 19 GHz 1.008 −1.17 R > 0.99 
Transform SSM/I F17 19 GHz into SSM/I F8 19 GHz 1.0286 −3.0094 R > 0.99 

After all the data are normalized, we use the NASA TEAM algorithm to extract the 20-year sea ice information from SSM/I data.

NASA TEAM algorithm

At present, there are many algorithms for sea ice concentration inversion. There are several mature algorithms: NASA TEAM algorithm, bootstrap algorithm, ASI algorithm, and Lomax algorithm. Among them, bootstrap algorithm is based on the different characteristics of the sea ice emissivity in different frequency bands, so as to calculate the sea ice concentration (Comiso et al. 1997). ASI algorithm is close to the sea ice inversion algorithm based on 90 GHz band (Svendsen et al. 1987) on the basis of the improvement, compared with other algorithms using the 85 GHz band. The advantage of this algorithm is that it does not require additional data input, and can directly get the inversion results based on the brightness temperature data (Kaleschke et al. 2001). NASA TEAM algorithm uses the two polarizations (vertical V or horizontal H) of SSM/I: 19.4 GHz and 37 GHz. In this algorithm, the gradient ratio and the polarization ratio are introduced (Steffen & Schweiger 1991).

The definitions of and are as follows:  
formula
(2)
 
formula
(3)
First-year ice concentration CF and multiyear ice concentration CM are as follows:  
formula
(4)
 
formula
(5)
where , the overall sea ice concentration is as follows:  
formula
(6)
Through the above analysis of several algorithms, it is found that NASA TEAM algorithm uses the low frequency band data to conduct sea ice concentration inversion, which weakens the influence of atmospheric environment to a certain extent. NASA TEAM algorithm does not need external parameters, and to a certain extent, it ensures the accuracy of the inversion results. In this paper, NASA TEAM algorithm and SMM/I data are selected for sea ice concentration inversion.

RESULTS AND ANALYSIS

Arctic sea ice areas

Spatial variations

The average sea ice concentration is shown in Figure 1 based on SSM/I data (1997–2016). It can be seen from Figure 1 that there is a high sea ice concentration near the North Pole and rough circular distribution which gradually decreases from high latitudes to low latitudes. The following conclusions can be drawn by comprehensive analysis. (1) The annual sea water begins growing and expanding regions near the Bering Strait connecting with the North Pacific including the areas of the Chukchee Sea and the Beaufort Sea Area. (2) In the waters around Greenland and the waters of West Baffin Bay and Davis Strait, because of the large number of reefs in the region, the specific heat capacity of the land is far greater than that of the sea water in the summer, and the sea ice melts rapidly in the region during the summer, and the Arctic Northwest Passage is formed. (3) The sea ice on the east side of Greenland (the waters in Greenland Sea and Norskehavet) is mostly first-year ice with low concentration, which is also connected with open waters. It is vulnerable to the influence of the Atlantic warm current. Therefore, the waters are the initial areas for the annual sea ice melt onset. (4) The east side of the Bering Strait is adjacent to the Asian continent including the Laptev Sea, and in some years the region will be ice free in summer, which will lead to the Arctic Northeast Passage being unimpeded.

Figure 1

Arctic mean sea ice concentration (1997–2016).

Figure 1

Arctic mean sea ice concentration (1997–2016).

Temporal variations

The mean sea ice concentration for every year (from 1997 to 2016) is shown in Figure 2 based on the NASA TEAM algorithm, and the sea ice areas and trend lines of Arctic sea ice are shown in Figure 3 by statistics. It can be seen that the mean Arctic sea ice areas for every year from 1997 to 2006 are significantly higher than that from 1997 to 2016 and there is the smallest sea ice area in 2016. In addition to the increasing trend of individual years, there is a downward trend in 20 years, decreasing at a rate of 0.0594 × 106 km2 per year.

Figure 2

Mean sea ice concentration for every year from 1997 to 2016.

Figure 2

Mean sea ice concentration for every year from 1997 to 2016.

Figure 3

Variations of Arctic sea ice areas (1997–2016).

Figure 3

Variations of Arctic sea ice areas (1997–2016).

Comparative analysis of two serial ten-year sea ice areas

The Arctic sea ice areas and trend lines are shown in Figure 4 from 1997 to 2006, and the Arctic sea ice areas and trend lines are shown in Figure 5 from 2007 to 2016. Through comparison and analysis of Figures 35, it is known that R2 of the fitting equation of the whole changing trends is 0.8. Changes in sea ice areas have less fluctuation from 1997 to 2006, and the overall performance is a downward trend, and R2 of the fitting equation of the whole changing trends is 0.855. There is a downward trend from 2007 to 2016, but the ups and downs are large. It decreased at a rate of 0.03 × 106 km2 per year. R2 of the fitting equation is 0.126. There is a minimum in 2012, but the number of sea ice areas increased significantly in 2013 and 2014. The sea ice areas in 2016 show an obvious downward trend compared with 2015, and it is an extremely low value of sea ice areas in the recent 20 years. Compared with the first decade and the second decade, although the two decades all show a decreasing trend of sea ice areas, the fluctuation in the second decade is obviously larger than that in the first decade. Thus, this may be a trend of future Arctic sea ice, that is, overall decline, but the fluctuation trend is enhanced.

Figure 4

Variations of Arctic sea ice areas (1997–2006).

Figure 4

Variations of Arctic sea ice areas (1997–2006).

Figure 5

Variations of Arctic sea ice areas (2007–2016).

Figure 5

Variations of Arctic sea ice areas (2007–2016).

Arctic sea ice margin zone

The varying curve of Arctic sea ice margin zone is shown in Figure 6 based on SSM/I data from 1997 to 2016. We can see from Figure 6 that the Arctic sea ice margin zone has an overall downward trend at the speed of 0.03 × 106 km2 per year, while in 2007, 2012, and 2016 there is a smaller sea ice margin zone, and there is the smallest sea ice margin zone in 2016. We can see from Figure 3 that the biggest variations in the entire Arctic region are in the Beaufort Sea and waters near the Bering Strait adjacent to the American continent. The sea ice with high concentration turned into the sea ice with low concentration in the region for the years 1997–2016, and the Arctic sea ice margin zone is also down to close to 30%.

Figure 6

Variations of Arctic sea ice margin zone (1997–2016).

Figure 6

Variations of Arctic sea ice margin zone (1997–2016).

The variations of Arctic sea ice margin zone for the years 1997–2006 are shown in Figure 7, and the variations of Arctic sea ice margin zone for the years 2007–2016 are shown in Figure 8. For the first decade, the Arctic sea ice margin zone decreases by 0.06 × 106 km2 per year, and for the second decade, it decreases by 0.019 × 106 km2 per year. In comparison with the trend of the two decades, the fitting equation shows that the first decade has an obvious linear decreasing trend, and R2 is 0.9106, while the second decade shows a downward trend, but the fitting equation was not as good as that in the first decade, and R2 is 0.227 (The ups and downs of the second decade are more obvious.) By comparing and analyzing the sea ice areas and the sea ice margin zone, we can see that in the first decade both of them are at a speed of about 0.06 × 106 km2, and in the second decade the speed of sea ice area reduction is faster than the sea ice margin zone.

Figure 7

Variations of Arctic sea ice margin zone (1997–2006).

Figure 7

Variations of Arctic sea ice margin zone (1997–2006).

Figure 8

Variations of Arctic sea ice margin zone (2007–2016).

Figure 8

Variations of Arctic sea ice margin zone (2007–2016).

Arctic sea ice concentration

Sea ice area statistics of each concentration range are shown in Figure 9 in 1997–2016, 1997–2006, and 2007–2016. The Arctic mean sea ice concentrations (1997–2006 and 2007–2016) are shown in Figure 10. In 1997–2016, the sea ice concentration (90–100%) is about 40%, which is much higher than that of the total areas of all other types of sea ice, and the sea ice concentration (more than 80%) is more than 50%. In 2007–2016, the sea ice concentration (90–100%) is about 18%, and the sea ice concentration (80–90%) increases by about 10% from 21% (1997–2006), and the sea ice concentration (less than 50%) increases from 7.3% (1997–2006) to 8.9% (2007–2016), which has a small change. Thus, it can be concluded that the sea ice with the high concentration is decreasing obviously, the sea ice with less than 50% is not changed, and the sea ice with the concentration (80–90%) is increasing obviously. It can be seen from Figure 10 that the sea ice with the high concentration in the second decade is obviously lower than the first decade, of which the sea ice with the concentration (more than 90%) is less significant. From the distribution, the Laptev Sea bordering the Asian continent and the Beaufort Sea bordering North America decrease most significantly, and the sea ice concentration in the east side of the North Pole near the East Barents Sea is significantly lower than that of the west side of the North Pole. The regions with minimal sea ice concentration change are in the core regions of the Arctic Ocean near the Canadian Arctic archipelago on the west side of the Arctic point.

Figure 9

Sea ice area statistics of each concentration range.

Figure 9

Sea ice area statistics of each concentration range.

Figure 10

Arctic sea ice concentration 1997–2006 (left) and 2007–2016 (right).

Figure 10

Arctic sea ice concentration 1997–2006 (left) and 2007–2016 (right).

CONCLUSION

In this paper, the Arctic sea ice areas, margin zone, and concentration are studied. Among them, the sea ice areas are analyzed from two dimensions: temporal and spatial. The variations of sea ice concentration are compared between 1997–2006 and 2007–2016, and the following conclusions are drawn:

  1. On the whole, the concentration from high latitudes to low latitudes gradually decreases with the circular distribution. Among them, the sea ice concentration (90–100%) is greater, and most is near the North Pole and the Canadian Arctic archipelago. The sea ice distribution near the Barents Sea and the Svalbard archipelago changes greatly, and the area is about 40–70% for the sea ice concentration.

  2. In the past 20 years, the sea ice areas for the first decade (1997–2006) was obviously higher than the mean value of 20 years (1997–2016). In 2006, 2007, 2012, and 2016, there are fewer sea ice areas, of which, the year 2016 has the lowest. The sea ice areas for 20 years (1997–2016) are reduced at a speed of 0.0594 × 106 km2 per year, and the sea ice margin zone is reduced at a speed of 0.03 × 106 km2. The trend is basically the same, but the reduction of sea ice areas is slightly larger than the sea ice margin zone, which is related to the sharp decrease of high concentration sea ice in the past 20 years.

  3. Compared with the two decades from 1997 to 2006 and from 2007 to 2016, the change trend of the first decade is more stable, and the fluctuation of the second decade is more obvious. From 1997 to 2006, the sea ice areas and margin zone show a typical downward trend. The R2 of the fitting equation is about 0.9, which decreased by 0.062 × 106 km2 and 0.064 × 106 km2 per year, respectively. From 2007 to 2016, the sea ice areas and margin zone show an obvious fluctuation. The R2 of the fitting equation is obviously lower than the first decade, which decreased by 0.027 × 106 km2 and 0.019 × 106 km2 per year, respectively.

  4. In the first decade, the sea ice concentration between 90% and 100% is about 40%, and the sea ice concentration between 90% and 100% is only about 20% in the second decade, and the decrease is particularly obvious. In the first decade, sea ice concentration is less than 70% accounting for about 26%, and the sea ice concentration is less than 70% in the second decade accounting for about 34%, and the change was small. Usually, the sea ice with high concentration is mostly for multiyear ice, and the sea ice with low concentration is mostly for first-year ice. Through the above analysis, it can also be indirectly obtained that the Arctic multiyear ice has a significant decreasing trend.

ACKNOWLEDGEMENTS

This research was supported by National Natural Science Foundation of China (No. 41606209) and by Fujian Provincial Key Laboratory of Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, China (No. JYG1707), and by the Fundamental Research Funds for the Henan Provincial Colleges and Universities (No. 2015QNJH16). We thank the Chief Editor of the journal and the anonymous reviewers for their time and effort, which significantly improved the manuscript.

REFERENCES

REFERENCES
Clark
,
P. U.
,
Alley
,
R. B.
&
Pollard
,
D.
1999
Northern Hemisphere ice-sheet influences on global climate change
.
Science
286
(
5442
),
1104
1111
.
Comiso
,
J. C.
2002
A rapidly declining perennial sea ice cover in the Arctic
.
Geophysical Research Letters
29
(
20
),
17-1
17-4
.
Comiso
,
J. C.
,
Cavalieri
,
D. J.
,
Parkinson
,
C. L.
&
Gloersen
,
P.
1997
Passive microwave algorithms for sea ice concentration: a comparison of two techniques
.
Remote Sensing of Environment
60
(
3
),
357
384
.
Comiso
,
J. C.
,
Parkinson
,
C. L.
,
Gersten
,
R.
&
Stock
,
L.
2008
Accelerated decline in the Arctic sea ice cover
.
Geophysical Research Letters
35
(
1
),
L01703
.
Eldevik
,
T.
,
Risebrobakken
,
B.
,
Bjune
,
A. E.
,
Andersson
,
C.
,
Birks
,
H. J.
,
Dokken
,
T. M.
,
Drange
,
H.
,
Glessmer
,
M. S.
,
Li
,
G.
,
Nilsen
,
J. E.
,
Ottera
,
O. H.
,
Richter
,
K.
&
Skagseth
,
Q.
2014
A brief history of climate – the northern seas from the Last Glacial Maximum to global warming
.
Quaternary Science Reviews
106
(
1
),
225
246
.
Fan
,
X. Y.
,
Bi
,
H. B.
,
Wang
,
Y. H.
,
Fu
,
M.
,
Zhou
,
X.
,
Xu
,
X. L.
&
Huang
,
H. J.
2017
Increasing winter conductive heat transfer in the Arctic sea-ice-covered areas: 1979–2014
.
Journal of Ocean University of China
16
(
6
),
1061
1071
.
Gascard
,
J. C.
,
Riemann-Campe
,
K.
,
Gerdes
,
R.
,
Schyberg
,
H.
,
Randriamampianina
,
R.
,
Karcher
,
M.
,
Zhang
,
J. L.
&
Rafizadeh
,
M.
2017
Future sea ice conditions and weather forecasts in the Arctic: implications for Arctic shipping
.
AMBIO
46
(
SI
),
355
367
.
Kaleschke
,
L.
,
Liipkes
,
C.
,
Vihma
,
T.
,
Haarpaintner
,
J.
,
Bochert
,
A.
,
Hartmann
,
J.
&
Heygster
,
G.
2001
SSM/i sea ice remote sensing for mesoscale ocean-atmosphere interaction analysis
.
Canadian Journal of Remote Sensing
27
(
5
),
526
537
.
Kwok
,
R.
&
Cunningham
,
G. F.
2010
Contribution of melt in the Beaufort Sea to the decline in Arctic multiyear sea ice coverage: 1993–2009
.
Geophysical Research Letters
37
,
L20501
.
Li
,
L. H.
,
Miller
,
A. J.
,
McClean
,
J. L.
,
Eisenman
,
I.
&
Hendershott
,
M. C.
2014
Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: mean seasonal cycle
.
Ocean Modelling
84
,
51
66
.
Massom
,
R. A.
,
Comiso
,
J. C.
,
Worby
,
A. P.
,
Lytle
,
V. I.
&
Stock
,
L.
1999
Regional classes of sea ice cover in the East Antarctic Pack observed from satellite and in situ data during a winter time period
.
Remote Sensing of Environment
68
(
1
),
61
76
.
Miao
,
X.
,
Xie
,
H. J.
,
Ackley
,
S. F.
&
Zheng
,
S.
2016
Object-based Arctic sea ice ridge detection from high-spatial-resolution imagery
.
IEEE Geoscience and Remote Sensing Letters
13
(
6
),
787
791
.
Parizek
,
B. R.
&
Alley
,
R. B.
2004
Implications of increased Greenland surface melt under global-warming scenarios: ice-sheet simulations
.
Quaternary Science Reviews
23
(
9–10
),
1013
1027
.
Parkinson
,
C. L.
&
Cavalieri
,
D. J.
2008
Arctic sea ice variability and trends, 1979–2006
.
Journal of Geophysical Research: Oceans
113
(
C7
),
1
28
.
Svendsen
,
E.
,
Matzler
,
C.
&
Grenfell
,
T. C.
1987
A model for retrieving total sea ice concentration from a spaceborne dual-polarization passive microwave instrument operating near 90 GHz
.
International Journal of Remote Sensing
8
(
10
),
1479
1487
.
Wang
,
X. D.
,
Wu
,
Z. K.
,
Wang
,
C.
,
Li
,
X. W.
,
Li
,
X. G.
&
Qiu
,
Y. B.
2017
Reducing the impact of thin clouds on Arctic Ocean sea ice concentration from FengYun-3 MERSI data single cavity
.
IEEE Access
5
,
16341
16348
.
Xie
,
T.
,
Perrie
,
W.
,
Fang
,
H.
,
Zhao
,
L.
,
Yu
,
W. J.
&
He
,
Y. J.
2017
Spatial and temporal variability of sea ice deformation rates in the Arctic Ocean observed by RADARSAT-1
.
Science China-Earth Sciences
60
(
5
),
858
865
.
Zhao
,
J. P.
,
Barber
,
D.
&
Zhang
,
S. G.
2018
Record low sea-ice concentration in the central Arctic during summer 2010
.
Advances in Atmospheric Sciences
35
(
1
),
106
115
.