Editing IPCC:AR6/SROCC/Chapter-6 (section)

=== 6.4.3 Risk Management and Adaptation, Monitoring and Early Warning Systems ===

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Risk management strategies to respond to MHWs include early warning systems as well as seasonal (weeks to several months) and multi-annual predictions systems. Since 1997, the National Oceanic and Atmospheric Administration’s (NOAA) Coral Reef Watch has used satellite SST data to provide near real-time warning of coral bleaching (Liu et al., 2014a <sup>[[#fn:r461|461]]</sup> ). These satellite-based products, along with NOAA Coral Reef Watch’s four month coral bleaching outlook based on operational climate forecast models (Liu et al., 2018 <sup>[[#fn:r462|462]]</sup> ), and coral disease outbreak risk (Heron et al., 2010 <sup>[[#fn:r463|463]]</sup> ) provide critical guidance to coral reef managers, scientists, and other stakeholders (Tommasi et al., 2017b <sup>[[#fn:r464|464]]</sup> ; Eakin et al., 2018 <sup>[[#fn:r465|465]]</sup> ). These products are also used to implement proactive bleaching response plans (Rosinski et al., 2017 <sup>[[#fn:r466|466]]</sup> ), brief stakeholders, and allocate monitoring resources in advance of bleaching events, such as the 2014–2017 global coral bleaching event (Eakin et al., 2017 <sup>[[#fn:r467|467]]</sup> ). For example, Thailand closed ten reefs for diving in advance of the bleaching peak in 2016, while Hawaii immediately began preparation of resources both to monitor the 2015 bleaching and to place specimens of rare corals in climate controlled, onshore nurseries in response to these forecast systems (Tommasi et al., 2017b <sup>[[#fn:r468|468]]</sup> ). New measurement techniques, such as Argo and deep Argo floats, may help to further develop prediction systems for subsurface MHWs, but such systems are not yet in place.

SST forecasts ranging from seasonal to decadal (5–10 years) have also been used or are planned to be used as early warning systems for multiple other ecosystems and fisheries in addition to coral reefs, including aquaculture, lobster, sardine, and tuna fisheries (Hobday et al., 2016b <sup>[[#fn:r469|469]]</sup> ; Payne et al., 2017 <sup>[[#fn:r470|470]]</sup> ; Tommasi et al., 2017b <sup>[[#fn:r471|471]]</sup> ). For example, seasonal forecasts of SST around Tasmania may help farm managers of salmon aquaculture to prepare and respond to upcoming MHWs by changing stocking densities, varying feed mixes, transferring fish to different locations in the farming region and implementing disease management (Spillman and Hobday, 2014 <sup>[[#fn:r472|472]]</sup> ; Hobday et al., 2016b <sup>[[#fn:r473|473]]</sup> ). Skilful multi-annual to decadal SST predictions may also inform and improve decisions about spatial and industrial planning, as well as the management of various extractive sectors such as the adjustments to quotas for internationally shared fish stocks (Tommasi et al., 2017a <sup>[[#fn:r474|474]]</sup> ). It has been shown that global climate forecasts have significant skill in predicting the occurrence of above average warm or cold SST events at decadal timescales in coastal areas (Tommasi et al., 2017a <sup>[[#fn:r475|475]]</sup> ), but barriers to their widespread usage in fishery and aquaculture industry still exist (Tommasi et al., 2017b <sup>[[#fn:r476|476]]</sup> ).

Even with a monitoring and prediction system in place, MHWs have developed without warning and had catastrophic effects (Payne et al., 2017 <sup>[[#fn:r477|477]]</sup> ). For example, governmental agencies, socioeconomic sectors, public health officials and citizens were not forewarned of the Coastal Peruvian 2017 MHW, despite a basin-wide monitoring system across the Pacific. The reason was partly due to a coastal El Niño definition problem and a new government (in Nicaragua) that may have hindered actions (Ramírez and Briones, 2017 <sup>[[#fn:r478|478]]</sup> ). Therefore, early warning systems should not only provide predictions of physical changes, but should also connect different institutions to assist decision makers in performing time-adaptive measures (Chang et al., 2013 <sup>[[#fn:r479|479]]</sup> ).

Monitoring and prediction systems are important and can be advanced by the use of common metrics to describe MHWs. So far, MHWs are often defined differently in the literature, and it is only recently that a categorising scheme (Categories I to IV; based on the degree to which temperatures exceed the local climatology), similar to what is used for hurricanes, has been developed (Hobday et al., 2018 <sup>[[#fn:r480|480]]</sup> ). Such a categorising scheme, can easily be applied to real data and predictions, and may facilitate comparison, public communication and familiarity with MHWs. Similar metrics (e.g., DHW) have been successfully developed and used to identify ocean regions where conditions conducive to coral bleaching are developing.

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