Research on Digital Environment Services for Arctic Sea Route

doi:10.11871/jfdc.issn.2096-742X.2026.02.007

Abstract

Abstract:

[Background] Climate warming has led to a continuous reduction of Arctic sea ice, and has provided new routes for global transportation and international trade. Arctic navigation has shifted from the exploration stage to a period of development. During the low-ice season, melting, or freezing periods in the Arctic Ocean, the timely acquisition of environmental information on Arctic sea routes is crucial for ensuring safe navigation. [Objective] This paper aims to enhance the acquisition, service, and digital application capabilities of Arctic routes environmental information based on aerospace data, Artificial Intelligence (AI) based forecasting technologies, and a comprehensive navigability index. It seeks to develop a digital service system for Arctic route environmental conditions to support navigation safety and environmental governance in the Arctic. [Method] Focusing on the current accessibility of aerospace data, the study identifies essential environmental variables affecting Arctic sea routes. Based on traditional navigability indices, it incorporates additional environmental factors such as precipitation, air temperature, water vapor, sea surface temperature, and wave height to construct a comprehensive navigability assessment model. Furthermore, a route environmental information service system based on aerospace data is developed to provide multi-level support for Arctic emergency response, annual planning, and medium-to long-term strategic decision-making. The system has demonstrated practical effectiveness in supporting China’s exploratory Arctic voyages and extreme-environment Arctic expeditions. [Conclusion] By integrating essential environmental variables of Arctic sea routes, multi-source spatial data, sea ice forecasting technologies, and navigability assessment models, the system establishes a layered service strategy. It provides an essential digital tool for Arctic route environmental information services, navigation safety, and environmental governance.

Key words: Arctic sea route environment, essential variables, aerospace data and information, assessment on navigability of Shipping, AI-based sea ice forecasting

QIU Yubao, CUI Heng, JIN Zekai, LI Xiaoting, YU Shuwen. Research on Digital Environment Services for Arctic Sea Route[J]. Frontiers of Data and Computing, 2026, 8(2): 82-97, https://cstr.cn/32002.14.jfdc.CN10-1649/TP.2026.02.007.

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类别	关键变量	观测指标	主要作用	应用场景
冰况类	海冰类型	多年冰/一年冰	冰情/船冰级需求	航线规划
	海冰厚度	最大/平均厚度	影响航行	航行安全
	海冰密集度	覆盖率	影响航行	航行安全
	海冰漂移	速度/方向	流冰运动	航行安全
	浮冰/冰山	位置/范围	航道影响	航道安全
海况类	洋流	流速/流向	影响冰漂移/分布	航线安全
	温度	海表温度	影响结冰与消融	航行安全
	风场	海表风速/风向	影响冰漂移/气象条件	航行安全
	海浪	浪高/方向	影响冰漂移	航行安全
气象水文类	降水	雪深/雨量	气象条件	模型输入
	海雾	能见度（<1 km）	天气条件	航行安全
	水汽	水汽含量	水汽强度	模型输入
	风场	风速/风向	气象条件	模型输入
预报输入变量类	积雪	积雪覆盖度	影响陆-海相互作用	模型输入
预报输入变量类	云参数	云量/云底高度	影响辐射/气预测	模型输入