11:00 AM - 11:15 AM
[ACG36-07] Accurate Detection of Marine Heatwaves using Sea Surface Temperature from Geostationary Meteorological Satellite Himawari Observations
Keywords:Marine heatwaves, Sea surface temperature, Himawari-8/9, NOAA OISST
Marine heatwaves (MHWs), a concept initially coined by Pearce et al. in 2011, are unusually warm oceanic events that have a significant impact on marine ecosystems. Hobday et al., based on the definition of atmospheric heatwaves, proposed a specific definition of MHWs in 2016. They used a relative threshold based on a fixed climatic baseline period with seasonal variability. According to this definition, MHWs are discrete prolonged anomalously warm water events.
In the context of global warming, the ocean has absorbed 93% of the heat, leading to a gradual increase in its heat capacity. Global warming has been triggering more frequent occurrences of MHWs, causing significant economic losses and ecological damage. MHWs have emerged as phenomena of significant ecological and economic consequence in the current landscape of climate research.
When studying MHWs using satellite imagery, the most extensively utilized dataset is the NOAA Optimum Interpolation Sea Surface Temperature (OISST) dataset. However, there are limitations to the NOAA OISST dataset. Therefore, this study utilizes Himawari SST data, which has superior temporal and spatial resolution. To directly evaluate the MHW results detected by these two satellite products, this study will conduct a comparative analysis. To comprehensively evaluate and validate the accuracy and reliability of these data sources, we also compared the MHW outcomes from both sources with mixed layer depth, which is a known driver of MHWs.
The results showed notable differences in the frequency and spatial distribution of MHWs when comparing the MHW spatial distribution maps derived from Himawari and NOAA OISST data. Specifically, during significant El Niño and La Niña events, Himawari data more accurately captured the changes in MHW events compared to NOAA OISST data.
Our analysis also revealed limitations in NOAA OISST's interpolation method, which could lead to misidentification of non-continuous high temperature records as continuous events, potentially overestimating the frequency of MHWs. Additionally, the study highlighted that the commonly used 30-year climate cycle may not accurately reflect recent climatic conditions, especially considering the last eight years as some of the warmest on record.
In the time series analysis, Himawari data clearly demonstrated a significant correlation between the decrease in mixed layer depth (MLD) and the occurrence of MHWs. This aligns with the theoretical expectation that shallower mixing layers are more conducive to the formation and maintenance of MHWs.
In the context of global warming, the ocean has absorbed 93% of the heat, leading to a gradual increase in its heat capacity. Global warming has been triggering more frequent occurrences of MHWs, causing significant economic losses and ecological damage. MHWs have emerged as phenomena of significant ecological and economic consequence in the current landscape of climate research.
When studying MHWs using satellite imagery, the most extensively utilized dataset is the NOAA Optimum Interpolation Sea Surface Temperature (OISST) dataset. However, there are limitations to the NOAA OISST dataset. Therefore, this study utilizes Himawari SST data, which has superior temporal and spatial resolution. To directly evaluate the MHW results detected by these two satellite products, this study will conduct a comparative analysis. To comprehensively evaluate and validate the accuracy and reliability of these data sources, we also compared the MHW outcomes from both sources with mixed layer depth, which is a known driver of MHWs.
The results showed notable differences in the frequency and spatial distribution of MHWs when comparing the MHW spatial distribution maps derived from Himawari and NOAA OISST data. Specifically, during significant El Niño and La Niña events, Himawari data more accurately captured the changes in MHW events compared to NOAA OISST data.
Our analysis also revealed limitations in NOAA OISST's interpolation method, which could lead to misidentification of non-continuous high temperature records as continuous events, potentially overestimating the frequency of MHWs. Additionally, the study highlighted that the commonly used 30-year climate cycle may not accurately reflect recent climatic conditions, especially considering the last eight years as some of the warmest on record.
In the time series analysis, Himawari data clearly demonstrated a significant correlation between the decrease in mixed layer depth (MLD) and the occurrence of MHWs. This aligns with the theoretical expectation that shallower mixing layers are more conducive to the formation and maintenance of MHWs.