Abstract
We describe an approach to produce short-term (1- to 3-day) forecasts of bio-optical properties by coupling moderate-resolution imaging spectroradiometer satellite (MODIS) ocean color imagery with a hydrodynamic model. The bio-optical property (chlorophyll in this case) is treated as a conservative tracer; the satellite distribution is advected forward in time using the current field from the hydrodynamic model. Uncertainties in both the satellite chlorophyll values and the currents from the circulation model impact the final forecast; we apply ensemble techniques to quantify the errors separately and in combination. For the ocean color imagery, we further apply ensemble techniques to partition the chlorophyll uncertainties into components due to atmospheric correction and bio-optical inversion, by applying noise to the near-infrared and visible band sets separately. The standard deviation for each ensemble suite provides an indication of uncertainty, or confidence in the satellite chlorophyll values and the hydrodynamic model current fields. By combining the two ensemble sets, we produce a final chlorophyll forecast field and associated uncertainty map that include both sets of uncertainties. We examine mean and individual forecast ensemble members (spread-skill statistics, RMS differences) to assess predictive value. This work represents a significant advancement in representing errors associated with satellite ocean color imagery and bio-optical forecasts.
Highlights
Satellite ocean color imagery can provide synoptic, surface estimates of water bio-optical properties, which are used in a wide variety of applications that are directly impacted by the penetration of light in the water column
Our objectives are: 1) to apply noise to satellite TOA radiances in an ensemble approach to quantify uncertainties in satellite-derived ocean color chlorophyll estimates; 2) to determine whether the ensembles are realistic; 3) to generate ensembles using different wavelength sets to partition the uncertainties into components due to atmospheric correction and bio-optical inversion; 4) to generate a separate ocean hydrodynamic ensemble set to quantify uncertainties in the model currents; and 5) to produce short-term chlorophyll forecasts and associated uncertainty maps using a hydrodynamic model simulation that incorporates both sets of uncertainties
The assumption here is that the ensemble set is realistic, that we are applying a reasonable amount of noise to the radiances, and that the noise encompasses natural variability
Summary
Satellite ocean color imagery can provide synoptic, surface estimates of water bio-optical properties, which are used in a wide variety of applications that are directly impacted by the penetration of light in the water column. The satellite measures spectral radiances reflected from the surface layer of the ocean, after transmission upward through the atmosphere. These measured top-of-the-atmosphere (TOA) radiances must undergo an atmospheric correction procedure to remove the light scattered into the viewing cone of the sensor by the atmosphere, in order to retrieve the desired water-leaving radiances (Lw).[1] The water-leaving radiance or remote sensing reflectance (Rrs), following conversion from radiance, is the important parameter related to the in-water bio-optical constituents.[2]
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