Analysis of wave characteristics in the North Pacific Ocean based on the fusion of multi-source satellite altimetry

Author:

Gao Huijun,Liang Bingchen,Yang HongbinORCID,Shao ZhuxiaoORCID

Abstract

Regional analysis of wave characteristics is crucial for ocean engineering planning and marine disaster protection. However, current wave observation methods have limitations in capturing sufficient coverage and resolution of wave field data, specifically significant wave height (SWH). Thus, we fuse multi-source satellite altimeter data using four fusion methods to generate daily SWH fields with a spatial resolution of 0.125° × 0.125° over the North Pacific Ocean (NPO). The results show that the fused SWHs exhibit a consistent spatial distribution pattern similar to the product provided by Archiving, Validation, and Interpretation of Satellite Oceanographic Data. Considering the spatial and temporal variation characteristics of the along-track data, the inverse distance weighting-based spatiotemporal fusion (IDW-ST) method outperforms other fusion methods compared to buoy measurements. Building upon the IDW-ST method, we fuse multi-source satellite altimetry data from 2016 to 2020 and analyze the regional spatial patterns and variations of waves in the NPO. Waves in this region are primarily influenced by monsoons and significantly regulated by extreme weather systems, such as tropical cyclones (TCs). Seasonal variations in wave characteristics may be linked to the frequency and tracks of TCs, with distinctive local features observed in representative zones. For example, the probability distribution of SWHs in the NPO exhibits a trailing pattern with significant deviations from the main SWHs, particularly during winter. Additionally, a heavy-tailed distribution is observed in the central high-latitude zone, except during summer. These patterns indicate the frequency and severity of extreme wave events in these zones.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Postdoctoral Innovation Project of Shandong Province

Publisher

AIP Publishing

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