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.