Roesler, Collin: Bowdoin College (Project Lead)
Project Funding:
2014 - 2017
NRA: 2013 NASA: PACE Science Team
Funded by NASA
Abstract:
NASA’s fleet of ocean color satellites have provided an enduring times series of phytoplankton chlorophyll concentration of a quality sufficient for a climate data record. Following on from SeaWiFS and MODIS missions, the Pre-Aerosol, Cloud, ocean Ecosystem (PACE) mission is designed to fulfill the climate continuity requirements, with a launch readiness in the time frame of 7 years. Beyond the estimation of phytoplankton chlorophyll concentration, the goals of PACE are to provide climate- quality global ocean color measurements that are essential for understanding the carbon cycle and global ocean ecology and determining how the ocean’s role in global biogeochemical (carbon) cycling and ocean ecology both affects and is affected by climate change. Among the improvements for the ocean color specifications are increased spectral and spatial resolution.
One of the specific objectives of the PACE mission is the retrieval of the inherent optical properties (IOPs), absorption and backscattering, via ocean color inversion algorithms. The capability for retrieving spectral phytoplankton absorption coefficients is key to addressing questions of carbon cycling and ocean ecology as these coefficients provide not only an estimate of algal concentration (that can be linked by proxy to algal carbon) but also to algal composition via pigment-based taxonomic discrimination. Pigment- based taxonomic composition provides a key approach to defining phytoplankton functional types (PFTs) as many of the pigment-based lineages coincide with biogeochemical niches, calcifiers, silicifiers, nitrogen fixers, etc. One challenge for the PACE mission is to define robust protocols with quantified uncertainty terms for constructing validation data sets for phytoplankton absorption. While in situ optical technologies exist to measure hyperspectral absorption on the spatial and temporal scales approaching those required for satellite validation, extracting the signature associated solely with phytoplankton cannot currently be performed analytically and thus we rely on model estimates.

Measuring phytoplankton absorption requires collection of discrete water samples, collecting the particles on glass fiber filters to remove the optical contribution by colored dissolved organic matter (CDOM), and measuring the absorption spectrophotometrically before and after pigment extraction. The absorption by the phytoplankton pigments in vivo is calculated by difference. However, the filter pad contaminates the signal due to its strong scattering properties and additionally amplifies the optical pathlength of transmitted photons in the spectrophotometer. These two error sources are inadvertently combined into a single correction factor, beta, called the pathlength amplification factor. Many researchers over the years have investigated this factor using a variety of strategies and technologies and yet it remains the largest source of uncertainty in the quantification of phytoplankton absorption. Unfortunately, models for extracting the phytoplankton absorption from in situ observations of whole water or particulate absorption are based upon laboratory investigations in which beta was poorly constrained at worst, or at best for which the uncertainties were not quantified. Thus in order to address the need for ocean color validation of phytoplankton absorption coefficients, a unified approach linking the quantitative filter pad technique to continuous in situ absorption observations is required and is the primary focus of this proposal. The secondary focus of this proposal is to investigate whether multispectral chlorophyll fluorescence can provide a quantitative proxy for phytoplankton absorption at the excitation wavelengths. This approach would expand the opportunities for in situ phytoplankton absorption validation by making use of a simple, economical, easily deployed technology that does not require the same level of optical expertise as absorption technologies.
Cecile Rousseaux/Universities Space Research Association, Columbia Phytoplankton Composition Algorithms for PACE
We propose to develop an algorithm to derive phytoplankton composition using a radiation model that provides hyperspectral data similar to what we expect from the PACE mission. Because there has not been any previous global mission with similar capabilities, there is a need for assessing the best approaches and anticipate potential problems if we are to get the most information out of this mission. Here we propose to use the Ocean-Atmosphere Spectral Irradiance Model (OASIM) to derive the total water- leaving radiance of single and mixed phytoplankton functional groups. We will then use an extensive dataset to develop an algorithm or algorithms to derive phytoplankton composition from these hyperspectral data. We will test this algorithm against in situ data that were withheld from the algorithm development. Finally we will apply this algorithm to a state-of-the-art biogeochemical model (NASA Ocean Biogeochemical Model) that has been shown to represent reasonably well the global distribution of phytoplankton composition. Using this model, we will assess how well this newly developed algorithm does in representing the natural global distribution of phytoplankton groups. Comprehensive quantitative error and uncertainty analysis will be integral in each of the stages of the proposal. Additionally, we propose simulations to test different configurations of the sensor to understand the capabilities and limitations associated with engineering options. Although we acknowledge that there may be formidable challenges throughout these steps, we believe that we can learn some valuable information from these challenges.
More details may be found in the following project profile(s):
