Abstract
Dynamic accurate predictions of Arctic sea ice, ocean, atmosphere, and ecosystem are necessary for safe and efficient Arctic maritime transportation; however a related technical roadmap has not yet been established. In this paper, we propose a management system for trans-Arctic maritime transportation supported by near real-time streaming data from air-space-ground-sea integrated monitoring networks and high spatio-temporal sea ice modeling. As the core algorithm of integrated monitoring networks, a long short-term memory (LSTM) neural network is embedded to improve Arctic sea ice mapping algorithms. Since the LSTM is localized in time and space, it can make full use of streaming data characteristics. The sea ice–related parameters from satellite remote sensing raw data are used as the input of the LSTM, while streaming data from shipborne radar networks and/or buoy measurements are used as training datasets to enhance the accuracy and resolution of environmental streaming data from outputs of LSTM. Due to large size of streaming data, the proposed management system of trans-Arctic shipping should be built on a cloud distribution platform using existing wireless communications networks among vessels and ports. Our management system will be used by the ongoing European Commission Horizon 2020 Programme “ePIcenter.”
Highlights
The dramatic shrinking and thinning of the summertime area of Arctic sea ice over the preceding 4 decades, especially in autumn and summer, accelerates deployments of large-scale trans-Arctic maritime transportation in the near future
Since the high reflective nature of snow/ice presents a good contrast with open water and other natural surface covers, streaming data from satellite remote sensing is a low-cost tool for monitoring changes of Arctic sea ice extent and thickness
Since the cost of airborne measurements are higher than buoy measurements or satellite remote sensing measurements, airborne measurements only work for several weeks a year, and it is only viewed as an auxiliary tool to support Arctic shipping
Summary
The dramatic shrinking and thinning of the summertime area of Arctic sea ice over the preceding 4 decades, especially in autumn and summer, accelerates deployments of large-scale trans-Arctic maritime transportation in the near future. Arctic shipping due to lower shipping costs, reduced carbon emissions, and shorter voyage times when Arctic routes are compared with the traditional Asia-Europe Suez Canal Route (Fu et al 2021). The core management system for the whole Arctic shipping to balance between risks and costs has not been effectively studied; only Zhang et al (2019) have given a framework for a big data–driven dynamic optimal trans-Arctic route (DOTAR) system. We overcome the disadvantages of the DOTAR system and establish a management system of environmental streaming data from a near real-time air-space-ground-sea integrated environmental monitoring network and high spatio-temporal sea ice modeling to support trans-Arctic maritime transportation. The management system can help to adjust and optimize shipping routes in near real time in order to maintain safe distances from large-size ice floes and to save time, fuel, and costs and to minimize risks. Our management system will be used by the ongoing European Commission Horizon 2020 Programme “Enhanced Physical Internet-Compatible EarthfrieNdly freight Transportation answer (ePIcenter)” as a core part of a trans-Arctic transportation system
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