Toward Applicable Retrieval Models of Oceanic Particulate Organic Nitrogen Concentrations for Multiple Ocean Color Satellite Missions

Accurate satellite retrieval of oceanic particulate organic nitrogen (PON) concentrations could contribute to a better and more comprehensive understanding of global marine biogeochemical processes. However, no satisfactory satellite PON retrieval model could be found in the literature. In an attempt to develop applicable PON models, large diverse matchups of synchronous global oceanic in situ PON measurements and ocean color satellite data were used to develop PON retrieval models using the Gaussian process regression (GPR) method for SeaWiFS, Terra-Moderate Resolution Imaging Spectroradiometer (MODIS), MERIS, Aqua-MODIS, and SNPP-Visible Infrared Imaging Radiometer Suite (VIIRS), respectively. The GPR PON models were compared with polynomial PON models based on single bio-optical properties or band index, and further used to retrieve spatiotemporal variations of global oceanic PON concentrations. Combined with the satellite-derived particulate organic carbon (POC) products, the possibility of deriving the POC to nitrogen ratio (POC:PON) was further explored. Results showed that GPR PON models, with <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>, root mean square error (RMSE), and mean absolute percentage error (MAPE) ranging from 0.76 to 0.87, 0.15 to 0.18, and 9.19% to 12.59%, respectively, had a comparable performance for both Case-1 and Case-2 waters and outperformed the polynomial PON models. The global PON concentrations derived from different satellite missions were generally consistent, with their mean relative differences all less than 14.70% between Aqua-MODIS and the other four missions. The GPR-derived POC:PON was acceptable, with most relative errors within ±40% compared to in situ POC:PON. The applicable satellite PON retrieval models and the readily available satellite PON products should be helpful for studying oceanic PON dynamics and ecological processes in marine biogeochemical cycles.