Poster Presentation Australian Marine Sciences Association 2026 Conference

A New Classification Approach to Global Marine Heatwaves within a Spatiotemporal Framework (140107)

Yifei Yang 1 2 3 4 , Wenjin Sun 1 3 4 , Yongyan Pan 1 3 4 , Mingshen Xie 1 3 4 , Yindi Wang 1 3 4 , Lei Jiang 1 3 4 , Chunhui Li 1 3 4 , Xiao Hua Wang 2 , Changming Dong 1 3 4
  1. State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, China
  2. The Sino-Australian Research Consortium for Coastal Management, The University of New South Wales, Canberra, ACT, Australia
  3. International Geophysical Fluid Research Center, Nanjing, China
  4. School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, China

Most existing studies on marine heatwaves (MHWs) are conducted based on sea surface temperature (SST) time series at single points, which neglect the spatial characteristics of MHWs and limit further classification research on MHWs. This study uses the second version of the Optimal Interpolated Sea Surface Temperature analysis data (OISSTv2.0) to identify global MHWs within a spatiotemporal framework from 1982 to 2020, and proposes a new classification method for global MHWs based on four key parameters: occurrence area, cumulative intensity, duration, and intensity growth rate. Five dominant MHW types are identified: Normal (NL, 74.12%), High Rate (HR, 9.02%), High Duration (HD, 3.39%), High Area (HA, 3.16%), and High Duration-Area-Cumulative Intensity (HDAC, 3.46%). From 1982 to 2020, the intensity growth rate of HR- and HDAC-type MHWs shows a declining trend, whereas all other characteristic parameters increase over time except for the area of HR-type events. Spatially, regions featuring high cumulative intensity and intensity growth rate of NL-type MHWs, all metrics of HR-type MHWs, and rapid intensity growth of HDAC-type MHWs are mainly concentrated in dynamically active and climatically sensitive oceans. In addition, HD- and HA-type MHWs persist over the long term within the Arctic and Antarctic circles. Globally, MHW types are undergoing a significant reorganization. HDAC-type MHWs are gradually becoming the dominant type of MHW events, while the relative frequencies of the other four types show declining trends. Attribution analysis using Detection and Attribution Model Intercomparison Project (DAMIP) data shows that greenhouse gas and natural forcings are the primary drivers of the declining frequency of NL- and HR-type MHWs. In contrast, the synergistic effect of greenhouse gas and natural forcings drives the increasing frequency proportion of HDAC-type MHWs, with the combined contribution rate reaching 7.63% decade-1. This study expands the understanding of MHW characteristics and classification methods within a spatiotemporal framework, providing an important supplement and advancement to current research based on single-point MHW definitions. It contributes to a more comprehensive understanding of MHW-related hazards and the evolving trends.