scholarly journals Revisiting Trans-Arctic Maritime Navigability in 2011–2016 from the Perspective of Sea Ice Thickness

2021 ◽  
Vol 13 (14) ◽  
pp. 2766
Author(s):  
Xiangying Zhou ◽  
Chao Min ◽  
Yijun Yang ◽  
Jack C. Landy ◽  
Longjiang Mu ◽  
...  

Arctic navigation has become operational in recent decades with the decline in summer sea ice. To assess the navigability of trans-Arctic passages, combined model and satellite sea ice thickness (CMST) data covering both freezing seasons and melting seasons are integrated with the Arctic Transportation Accessibility Model (ATAM). The trans-Arctic navigation window and transit time are thereby obtained daily from modeled sea ice fields constrained by satellite observations. Our results indicate that the poorest navigability conditions for the maritime Arctic occurred in 2013 and 2014, particularly in the Northwest Passage (NWP) with sea ice blockage. The NWP has generally exhibited less favorable navigation conditions and shorter navigable windows than the Northern Sea Route (NSR). For instance, in 2013, Open Water (OW) vessels that can only safely resist ice with a thickness under 15 cm had navigation windows of 47 days along the NSR (45% shorter than the 2011–2016 mean) and only 13 days along the NWP (80% shorter than the 2011–2016 mean). The longest navigation windows were in 2011 and 2015, with lengths of 103 and 107 days, respectively. The minimum transit time occurred in 2012, when more northward routes were accessible, especially in the Laptev Sea and East Siberian Sea with the sea ice edge retreated. The longest navigation windows for Polar Class 6 (PC6) vessels with a resistance to ice thickness up to 120 cm reached more than 200 days. PC6 vessels cost less transit time and exhibit less fluctuation in their navigation windows compared with OW vessels because of their ice-breaking capability. Finally, we found that restricted navigation along the NSR in 2013 and 2014 was related to the shorter periods of navigable days in the East Siberian Sea and Vilkitskogo Strait, with local blockages of thick ice having a disproportionate impact on the total transit. Shorter than usual navigable windows in the Canadian Arctic Archipelago and Beaufort Sea shortened the windows for entire routes of the NWP in 2013 and 2014.

2021 ◽  
Vol 15 (12) ◽  
pp. 5473-5482
Author(s):  
Jinlei Chen ◽  
Shichang Kang ◽  
Wentao Du ◽  
Junming Guo ◽  
Min Xu ◽  
...  

Abstract. The retreat of sea ice has been found to be very significant in the Arctic under global warming. It is projected to continue and will have great impacts on navigation. Perspectives on the changes in sea ice and navigability are crucial to the circulation pattern and future of the Arctic. In this investigation, the decadal changes in sea ice parameters were evaluated by the multi-model from the Coupled Model Inter-comparison Project Phase 6, and Arctic navigability was assessed under two shared socioeconomic pathways (SSPs) and two vessel classes with the Arctic transportation accessibility model. The sea ice extent shows a high possibility of decreasing along SSP5-8.5 under current emissions and climate change. The decadal rate of decreasing sea ice extent will increase in March but decrease in September until 2060, when the oldest ice will have completely disappeared and the sea ice will reach an irreversible tipping point. Sea ice thickness is expected to decrease and transit in certain parts, declining by −0.22 m per decade after September 2060. Both the sea ice concentration and volume will thoroughly decline at decreasing decadal rates, with a greater decrease in volume in March than in September. Open water ships will be able to cross the Northern Sea Route and Northwest Passage between August and October during the period from 2045 to 2055, with a maximum navigable percentage in September. The time for Polar Class 6 (PC6) ships will shift to October–December during the period from 2021 to 2030, with a maximum navigable percentage in October. In addition, the central passage will be open for PC6 ships between September and October during 2021–2030.


2021 ◽  
Author(s):  
Jinlei Chen ◽  
Shichang Kang ◽  
Wentao Du ◽  
Junming Guo ◽  
Min Xu ◽  
...  

Abstract. The retreat of sea ice is very significant in the Arctic under global warming. It is projected to continue and have great impacts on navigation. In this investigation, decadal changes in sea ice parameters were evaluated by multimodel from the Coupled Model Intercomparison Project Phase 6, and Arctic navigability was assessed under two shared socioeconomic pathways (SSPs) and two vessel classes within the Arctic transportation accessibility model. The sea ice extent is expected to decrease along the SSP5-8.5 scenario with a high possibility under current emissions and climate change. The decadal decreasing rate will increase in March but decrease in September until 2060 when the oldest ice completely disappears and sea ice changes reach an irreversible tipping point. The sea ice thickness will decrease and transit in parts of the Arctic and will decline overall by −0.22 m per decade after September 2060. Both the sea ice concentration and volume will thoroughly decline with decreasing decadal rates, while the decrease in volume will be higher in March than in September. Open water ships will be able to cross the Northeast Passage and Northwest Passage in August–October 2045–2055, with a maximum navigable area in September. The opportunistic crossing time for polar class 6 (PC6) ships will advance to October–December in 2021–2030, while the maximum navigable area will be seen in October. In addition, the Central Passage will also open for PC6 ships during September–October in 2021–2030.


2018 ◽  
Author(s):  
Byoung Woong An ◽  
Sang Min Lee ◽  
Pil-Hun Chang ◽  
KiRyong Kang ◽  
Yoon Jae Kim

Abstract. Ensemble sea ice forecasts of the Arctic Ocean conducted with the Korea Meteorological Administration's coupled global seasonal forecast system (GloSea5) is verified. To investigate the temporal and spatial characteristics of the seasonal projection of Arctic sea ice extent and thickness, a set of ensemble potential predictability is assessed. It shows significance for all lead months except anomalous around East Siberian Sea, Chukchi Sea and Beaufort Sea during summer months. However, during the radipdly thawing and freezing season, initial states lose its predictability and increase uncertainties in the prediction. The probability skill metrics show the summer sea ice prediction which strongly depends on the sea ice thickness interacting with the accuracy of the snow depth. We found the forecast skill is determined primarily by the timing of sea ice drift (i.e., Beaufort Gyre and Transpolar drift) and sea ice formation by freshwater flux in the East Siberian Sea. Therefore, capturing the sea ice thickness state effectively is the key process for skillful estimation of Arctic sea ice. In spite of the uncertainties in atmospheric conditions, this system provides skillful Arctic seasonal sea ice extent predictions up to six months.


2021 ◽  
Author(s):  
Isolde Glissenaar ◽  
Jack Landy ◽  
Alek Petty ◽  
Nathan Kurtz ◽  
Julienne Stroeve

<p>The ice cover of the Arctic Ocean is increasingly becoming dominated by seasonal sea ice. It is important to focus on the processing of altimetry ice thickness data in thinner seasonal ice regions to understand seasonal sea ice behaviour better. This study focusses on Baffin Bay as a region of interest to study seasonal ice behaviour.</p><p>We aim to reconcile the spring sea ice thickness derived from multiple satellite altimetry sensors and sea ice charts in Baffin Bay and produce a robust long-term record (2003-2020) for analysing trends in sea ice thickness. We investigate the impact of choosing different snow depth products (the Warren climatology, a passive microwave snow depth product and modelled snow depth from reanalysis data) and snow redistribution methods (a sigmoidal function and an empirical piecewise function) to retrieve sea ice thickness from satellite altimetry sea ice freeboard data.</p><p>The choice of snow depth product and redistribution method results in an uncertainty envelope around the March mean sea ice thickness in Baffin Bay of 10%. Moreover, the sea ice thickness trend ranges from -15 cm/dec to 20 cm/dec depending on the applied snow depth product and redistribution method. Previous studies have shown a possible long-term asymmetrical trend in sea ice thinning in Baffin Bay. The present study shows that whether a significant long-term asymmetrical trend was found depends on the choice of snow depth product and redistribution method. The satellite altimetry sea ice thickness results with different snow depth products and snow redistribution methods show that different processing techniques can lead to different results and can influence conclusions on total and spatial sea ice thickness trends. Further processing work on the historic radar altimetry record is needed to create reliable sea ice thickness products in the marginal ice zone.</p>


2016 ◽  
Author(s):  
R. L. Tilling ◽  
A. Ridout ◽  
A. Shepherd

Abstract. Timely observations of sea ice thickness help us to understand Arctic climate, and can support maritime activities in the Polar Regions. Although it is possible to calculate Arctic sea ice thickness using measurements acquired by CryoSat-2, the latency of the final release dataset is typically one month, due to the time required to determine precise satellite orbits. We use a new fast delivery CryoSat-2 dataset based on preliminary orbits to compute Arctic sea ice thickness in near real time (NRT), and analyse this data for one sea ice growth season from October 2014 to April 2015. We show that this NRT sea ice thickness product is of comparable accuracy to that produced using the final release CryoSat-2 data, with an average thickness difference of 5 cm, demonstrating that the satellite orbit is not a critical factor in determining sea ice freeboard. In addition, the CryoSat-2 fast delivery product also provides measurements of Arctic sea ice thickness within three days of acquisition by the satellite, and a measurement is delivered, on average, within 10, 7 and 6 km of each location in the Arctic every 2, 14 and 28 days respectively. The CryoSat-2 NRT sea ice thickness dataset provides an additional constraint for seasonal predictions of Arctic climate change, and will allow industries such as tourism and transport to navigate the polar oceans with safety and care.


2020 ◽  
Vol 14 (7) ◽  
pp. 2189-2203
Author(s):  
H. Jakob Belter ◽  
Thomas Krumpen ◽  
Stefan Hendricks ◽  
Jens Hoelemann ◽  
Markus A. Janout ◽  
...  

Abstract. The gridded sea ice thickness (SIT) climate data record (CDR) produced by the European Space Agency (ESA) Sea Ice Climate Change Initiative Phase 2 (CCI-2) is the longest available, Arctic-wide SIT record covering the period from 2002 to 2017. SIT data are based on radar altimetry measurements of sea ice freeboard from the Environmental Satellite (ENVISAT) and CryoSat-2 (CS2). The CCI-2 SIT has previously been validated with in situ observations from drilling, airborne remote sensing, electromagnetic (EM) measurements and upward-looking sonars (ULSs) from multiple ice-covered regions of the Arctic. Here we present the Laptev Sea CCI-2 SIT record from 2002 to 2017 and use newly acquired ULS and upward-looking acoustic Doppler current profiler (ADCP) sea ice draft (VAL) data for validation of the gridded CCI-2 and additional satellite SIT products. The ULS and ADCP time series provide the first long-term satellite SIT validation data set from this important source region of sea ice in the Transpolar Drift. The comparison of VAL sea ice draft data with gridded monthly mean and orbit trajectory CCI-2 data, as well as merged CryoSat-2–SMOS (CS2SMOS) sea ice draft, shows that the agreement between the satellite and VAL draft data strongly depends on the thickness of the sampled ice. Rather than providing mean sea ice draft, the considered satellite products provide modal sea ice draft in the Laptev Sea. Ice drafts thinner than 0.7 m are overestimated, while drafts thicker than approximately 1.3 m are increasingly underestimated by all satellite products investigated for this study. The tendency of the satellite SIT products to better agree with modal sea ice draft and underestimate thicker ice needs to be considered for all past and future investigations into SIT changes in this important region. The performance of the CCI-2 SIT CDR is considered stable over time; however, observed trends in gridded CCI-2 SIT are strongly influenced by the uncertainties of ENVISAT and CS2 and the comparably short investigation period.


2021 ◽  
Author(s):  
Alek Petty ◽  
Nicole Keeney ◽  
Alex Cabaj ◽  
Paul Kushner ◽  
Nathan Kurtz ◽  
...  

<div> <div> <div> <div> <p>National Aeronautics and Space Administration's (NASA's) Ice, Cloud, and land Elevation Satellite‐ 2 (ICESat‐2) mission was launched in September 2018 and is now providing routine, very high‐resolution estimates of surface height/type (the ATL07 product) and freeboard (the ATL10 product) across the Arctic and Southern Oceans. In recent work we used snow depth and density estimates from the NASA Eulerian Snow on Sea Ice Model (NESOSIM) together with ATL10 freeboard data to estimate sea ice thickness across the entire Arctic Ocean. Here we provide an overview of updates made to both the underlying ATL10 freeboard product and the NESOSIM model, and the subsequent impacts on our estimates of sea ice thickness including updated comparisons to the original ICESat mission and ESA’s CryoSat-2. Finally we compare our Arctic ice thickness estimates from the 2018-2019 and 2019-2020 winters and discuss possible causes of these differences based on an analysis of atmospheric data (ERA5), ice drift (NSIDC) and ice type (OSI SAF).</p> </div> </div> </div> </div>


Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7011
Author(s):  
Feng Xiao ◽  
Fei Li ◽  
Shengkai Zhang ◽  
Jiaxing Li ◽  
Tong Geng ◽  
...  

Satellite altimeters can be used to derive long-term and large-scale sea ice thickness changes. Sea ice thickness retrieval is based on measurements of freeboard, and the conversion of freeboard to thickness requires knowledge of the snow depth and snow, sea ice, and sea water densities. However, these parameters are difficult to be observed concurrently with altimeter measurements. The uncertainties in these parameters inevitably cause uncertainties in sea ice thickness estimations. This paper introduces a new method based on least squares adjustment (LSA) to estimate Arctic sea ice thickness with CryoSat-2 measurements. A model between the sea ice freeboard and thickness is established within a 5 km × 5 km grid, and the model coefficients and sea ice thickness are calculated using the LSA method. Based on the newly developed method, we are able to derive estimates of the Arctic sea ice thickness for 2010 through 2019 using CryoSat-2 altimetry data. Spatial and temporal variations of the Arctic sea ice thickness are analyzed, and comparisons between sea ice thickness estimates using the LSA method and three CryoSat-2 sea ice thickness products (Alfred Wegener Institute (AWI), Centre for Polar Observation and Modelling (CPOM), and NASA Goddard Space Flight Centre (GSFC)) are performed for the 2018–2019 Arctic sea ice growth season. The overall differences of sea ice thickness estimated in this study between AWI, CPOM, and GSFC are 0.025 ± 0.640 m, 0.143 ± 0.640 m, and −0.274 ± 0.628 m, respectively. Large differences between the LSA and three products tend to appear in areas covered with thin ice due to the limited accuracy of CryoSat-2 over thin ice. Spatiotemporally coincident Operation IceBridge (OIB) thickness values are also used for validation. Good agreement with a difference of 0.065 ± 0.187 m is found between our estimates and the OIB results.


Sign in / Sign up

Export Citation Format

Share Document