EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

A process-oriented approach for mining marine heatwaves with a time series of raster formatted products

Cunjin Xue1 and Changfeng Jing2
Cunjin Xue and Changfeng Jing
  • 1Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, P.R.ChinaChina (
  • 2Beijing University Civil Engineering & Architecture, School Geomatics & Urban Spatial Information,Beijing 100044,P.R.China

A marine heatwave (MHW) is defined as a coherent area of extreme warm sea surface temperature that persists for days to months, which has a property of evolution from production through development to death in space and time. MHWs usually relates to climatic extremes that can have devastating and long-term impacts on ecosystems, with subsequent socioeconomic consequences. Long term remote sensing products make it possible for mining successive MHWs at global scale. However, more literatures focus on a spatial distribution at a fixed time snapshot or a temporal statistic at a fixed grid cell of MWHs. As few considering the temporal evolution of MWHs, it is greater challenge to mining their dynamic changes of spatial structure. Thus, this manuscript proposes a process-oriented approach for identifying and tracking MWHs, named as PoAITM. The PoAITM considers a dynamic evolution of a MWH, which consists of three steps. The first step uses the threshold-based algorithm to identifying the time series of grid pixels which meets the MWH definition, called as MWH pixels; the second adopts the spatial proximities to connect the MWH pixels at the snapshots, and transforms them spatial objects, called as MWH objects; the third combines the dynamic characteristics and spatiotemporal topologies of MWH objects between the previous and next snapshots to identify and track them belonging to the same ones. The final extract MWH with a property from production through development to death is defined as a MWH process. Comparison with the prevail methods of tracking MHWs, The PoAITM has three advantages. Firstly, PoAITM combines the spatial distribution and temporal evolution of MWH to identify and track the MWH objects. The second considers not only the spatial structure of MWH at current snapshot, also the previous and next ones, to track the MWH process, which ensures the MWH completeness in a temporal domain. The third is the dynamic behaviors of MWH, e.g. developing, merging, splitting, are also found between the successive MWH objects. Finally, we address the global MWHs exploring from the sea surface temperature products during the period of January 1982 to December 2018. The results not only show well-known knowledge, but also some new findings about evolution characteristics of MWHs, which may provide new references for further study on global climate change.

How to cite: Xue, C. and Jing, C.: A process-oriented approach for mining marine heatwaves with a time series of raster formatted products, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2251,, 2020


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