Assessing the skill of a high-resolution marine biophysical model using geostatistical analysis of mesoscale ocean chlorophyll variability from field observations and remote sensing

• Published in: Frontiers in Marine Science
• Other Authors: Eveleth, Rachel (author), Glover, David M. (author), Long, Matthew C. (author), Lima, Ivan D. (author), Chase, Alison P. (author), Doney, Scott C. (author)
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2021
• Subjects: North Atlantic
• Online Access: https://doi.org/10.3389/fmars.2021.612764

High-resolution ocean biophysical models are now routinely being conducted at basin and global-scale, opening opportunities to deepen our understanding of the mechanistic coupling of physical and biological processes at the mesoscale. Prior to using these models to test scientific questions, we need to assess their skill. While progress has been made in validating the mean field, little work has been done to evaluate skill of the simulated mesoscale variability. Here we use geostatistical 2-D variograms to quantify the magnitude and spatial scale of chlorophyll a patchiness in a 1/10th-degree eddyresolving coupled Community Earth System Model simulation. We compare results from satellite remote sensing and ship underway observations in the North Atlantic Ocean, where there is a large seasonal phytoplankton bloom. The coefficients of variation, i.e., the arithmetic standard deviation divided by the mean, from the two observational data sets are approximately invariant across a large range of mean chlorophyll a values from oligotrophic and winter to subpolar bloom conditions. This relationship between the chlorophyll a mesoscale variability and the mean field appears to reflect an emergent property of marine biophysics, and the high-resolution simulation does poorly in capturing this skill metric, with the model underestimating observed variability under low chlorophyll a conditions such as in the subtropics.