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The inherent optical properties (IOPs) of a water body can serve as robust proxies for many important ecological and biogeochemical processes that are of fundamental importance to the Earth system. IOPs can be derived from measurements of satellite ocean color, and many successful derivation methods now exist, and provide a powerful means of synoptically monitoring these processes and their response to a changing climate. However, in waters such as the coastal ocean and inland water bodies, accurate retrieval of IOPs is often hampered by factors including difficulties in removing the contributions of the atmosphere from the satellite signal, and poor performance of standard ocean color algorithms due to the complex relationships amongst the water constituents.

The objective of this project, therefore, is to develop an approach to derive accurate estimates of IOPs from top of atmosphere (TOA) satellite radiance, thereby bypassing the difficulties often associated with atmospheric correction procedures. This is of particular relevance to coastal and inland water bodies where retrieval of robust ocean color products is notoriously challenging, and is frequently hampered by difficulties in achieving accurate atmospheric correction. The approach may be used for all waters, but most importantly, offers a means to accurately estimate IOPs from ocean color in scenarios where it may otherwise not be possible.

The proposed objectives will be achieved using an approach already proven for both in situ hyperspectral and satellite multispectral measurements. Using a combination of existing satellite and aircraft hyperspectral ocean color measurements and a custom generated TOA synthetic dataset, we will perform rigorous statistical model evaluation, sensitivity analyses to investigate variable oceanic and atmospheric effects on model skill, and finally, will develop operational implementation strategies. These activities will allow the model to be fully developed for hyperspectral TOA applications and a determination of the best model type - regional, water type or global. The end product will be a set of methodologies to provide an accurate means of deriving hyperspectral IOPs in the most challenging scenarios and will represent a significant advance in our ability to fully exploit remote sensing of the planets most important and vulnerable water bodies. The proposed research directly addresses the requirements of the PACE mission to achieve accurate hyperspectral IOP estimates, and insight into the processes for which they are proxies, in critical coastal ocean and inland water bodies - areas particularly susceptible to the impacts of climate change and anthropogenic perturbation. This is entirely in keeping with the broader NASA Earth Science Research Program to acquire new insights into the Earth system.