Absorption‐Based Wavelength‐Resolved Hyperspectral Primary Productivity Algorithm for the Northern Gulf of Mexico

Abstract

The northern Gulf of Mexico (nGOM) is a region of high biological productivity largely influenced by the nutrient input from the Mississippi and Atchafalaya rivers. Prior studies utilizing bio‐optical algorithms to estimate primary production (PP) in this region have generally employed wavelength‐integrated models (WIM) involving attenuation of photosynthetically active radiation integrated over the 400–700 nm spectral range. Here, we describe a hyperspectral, wavelength‐resolved, absorption‐based PP model (WRM). This WRM is more computationally intensive than wavelength‐integrated approaches but provides more accurate representation of the subsurface light field. Additionally, the WRM more directly characterizes light absorption by phytoplankton in contrast to chlorophyll‐based models. To implement the algorithm, bio‐optical observations and photosynthesis‐irradiance (P‐E) measurements were acquired during five GulfCarbon cruises (January, April, July, November 2009, and March 2010). Hyperspectral downwelling irradiance was determined using a HyperPro optical profiler along with phytoplankton spectral absorption from filterpad absorption measurements. Results from the WRM produced consistently higher values of PP at depth than a conventional WIM, particularly in offshore waters. Water column‐integrated primary production (IPP) ranged between 0.09–1.66 mol C m ⁻²  d ⁻¹ (1.08–19.92 g C m ⁻²  d ⁻¹ ). This range is comparable to or higher than historical observations, and future work would benefit from further independent validation. A modified version of the WRM, the wavelength‐resolved model estimation, was also described, which utilizes P‐E parameters derived from regional empirical relations. This novel hyperspectral PP algorithm can be applied to hyperspectral ocean color satellite observations and is adaptable for use in other regions.