Coral reefs are extremely important ecosystems; although they cover less than 1% of the oceans, they are home to over 25% of all marine species. They protect coastlines from erosion, provide food, new drugs, income via tourism and many other services for over half a billion people worldwide. The single greatest threat to coral reefs worldwide is climate change. Extended periods of elevated temperature results in coral bleaching, which can lead to mortality. Satellite tools designed to monitor coral heat stress have become increasingly important for the management of coral reefs. To date, the only global near-real-time monitoring system for coral bleaching is produced by the National Oceanic and Atmospheric Administration (NOAA). This bleaching alert system is based on a gap-free sea surface temperature (SST) product, which is produced daily on a 0.05x0.05 degree (approx. 5x5km) pixel scale. A static climatology set in the mid-1980s is used to produce daily (positive only) SST anomalies. These anomalies are then summed over a 12 week running window, the resultant product is called Degree Heating Weeks (DHW). DHW≥4 degree weeks is considered to be sufficient heat stress to cause significant coral bleaching. The DHW metric does not consider measurement uncertainties and other possible sources of error including the mismatch between a surface measurement taken over a 5km pixel and a specific coral location at depth. Further, other drivers of coral bleaching, such as the role of light intensity, are also not considered, meaning that there are a range of error sources that are missing from the current bleaching alert system. Here we will show the initial attempts to apply a metrological framework (based on the FIDUCEO methodology) to the problem of coral bleaching. By creating a detailed uncertainty tree, which will include both measurement (SST) and model errors (including models of the biological process that drive the onset of coral bleaching), we can begin to create a complete, traceable uncertainty chain. Along with creating an uncertainty tree for the whole coral bleaching problem, we will also show the current state of knowledge regarding the different possible sources of error and what future studies may be needed to fill in any gaps. We will finally discuss the implications of creating an uncertainty model for corals on bleaching alert systems such as the one produced by NOAA’s Coral Reef Watch program.
Topic : Theme 1: Oceans and Hydrology.
Reference : T1-B16
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