particularly useful for extreme shallow water coverage and for measuring SST
close to coasts. These capabilities are currently used by a number of research
groups for coral reef applications, but are not yet available on an operational basis.
Observations of diurnal variation of SST are necessary to accurately monitor
thermal stress on coral (Maturi et al. 2008). Geostationary satellites, with repeat
acquisitions every *30 min, provide a measure of the diurnal variation more
effectively than SST products derived from polar-orbiters, which only observe a
location, at most, twice per day. For example, the current methodology applied
globally by NOAA CRW uses night-time only AVHRR (polar-orbiting) retrievals
to determine daily SST, and then calculates SST anomaly values to represent the
level of anomaly at the depth of corals during bleaching events (Skirving et al.
2006). Given that corals are sensitive to temperature extremes as well as thermal
exposure over time, a bleaching prediction technique based on full diurnal
observations of SST (Leichter et al. 2006) would be superior to techniques that are
updated just once daily (Maturi et al. 2008). The GHRSST is currently conducting
extensive research to ensure that SST diurnal variability is properly flagged within
observational data and developing methods to correct for bias in different satellite
datasets. NOAA is investing in blended SST products, which combine measurements from polar and geostationary satellites. It is of note that sub-surface variation of temperature needs be included in the interpretation and application of SST
products derived from full diurnal coverage.
There are also several developing products, based on satellite SST, that describe
various coral ecosystem parameters, currently being evaluated. For example,
NOAA CRW experimental products include descriptions of the return period for
bleaching-level stress, the duration of historical stress events, and recent short-term
trends in SST. A regional product describing the risk of coral disease outbreak
based on recent winter and summer temperatures is also available (Heron et al.
2010). ReefTemp produces experimental risk maps for research based on temperature conditions that are conducive to coral disease outbreaks (Maynard et al. 2010;
www.cmar.csiro.au/remotesensing/reeftemp/web/ReefTemp_Disease.htm).
Another NOAA CRW experimental product combines the effects of satellitederived temperature and solar radiation to provide an alternative predictor for coral
bleaching. The Light Stress Damage (LSD) algorithm has been developed by
specifically considering the photosystem of the coral symbiont (zooxanthellae) and
examining the physiological responses of the coral-algal symbiosis under varying
light and temperature conditions. While the existing CRW algorithms were
developed on observed coral response to temperature alone, the LSD algorithm has
been constructed using specially-designed physiological experiments to determine
the influence of temperature on light thresholds (Nim and Skirving 2010). Preliminary results have led to improved bleaching prediction using the LSD algorithm
over temperature-only products for the given test sites.
326
S. J. Weeks et al.
close to coasts. These capabilities are currently used by a number of research
groups for coral reef applications, but are not yet available on an operational basis.
Observations of diurnal variation of SST are necessary to accurately monitor
thermal stress on coral (Maturi et al. 2008). Geostationary satellites, with repeat
acquisitions every *30 min, provide a measure of the diurnal variation more
effectively than SST products derived from polar-orbiters, which only observe a
location, at most, twice per day. For example, the current methodology applied
globally by NOAA CRW uses night-time only AVHRR (polar-orbiting) retrievals
to determine daily SST, and then calculates SST anomaly values to represent the
level of anomaly at the depth of corals during bleaching events (Skirving et al.
2006). Given that corals are sensitive to temperature extremes as well as thermal
exposure over time, a bleaching prediction technique based on full diurnal
observations of SST (Leichter et al. 2006) would be superior to techniques that are
updated just once daily (Maturi et al. 2008). The GHRSST is currently conducting
extensive research to ensure that SST diurnal variability is properly flagged within
observational data and developing methods to correct for bias in different satellite
datasets. NOAA is investing in blended SST products, which combine measurements from polar and geostationary satellites. It is of note that sub-surface variation of temperature needs be included in the interpretation and application of SST
products derived from full diurnal coverage.
There are also several developing products, based on satellite SST, that describe
various coral ecosystem parameters, currently being evaluated. For example,
NOAA CRW experimental products include descriptions of the return period for
bleaching-level stress, the duration of historical stress events, and recent short-term
trends in SST. A regional product describing the risk of coral disease outbreak
based on recent winter and summer temperatures is also available (Heron et al.
2010). ReefTemp produces experimental risk maps for research based on temperature conditions that are conducive to coral disease outbreaks (Maynard et al. 2010;
www.cmar.csiro.au/remotesensing/reeftemp/web/ReefTemp_Disease.htm).
Another NOAA CRW experimental product combines the effects of satellitederived temperature and solar radiation to provide an alternative predictor for coral
bleaching. The Light Stress Damage (LSD) algorithm has been developed by
specifically considering the photosystem of the coral symbiont (zooxanthellae) and
examining the physiological responses of the coral-algal symbiosis under varying
light and temperature conditions. While the existing CRW algorithms were
developed on observed coral response to temperature alone, the LSD algorithm has
been constructed using specially-designed physiological experiments to determine
the influence of temperature on light thresholds (Nim and Skirving 2010). Preliminary results have led to improved bleaching prediction using the LSD algorithm
over temperature-only products for the given test sites.
326
S. J. Weeks et al.