Resolving satellite-in situ mismatches in Net Primary Production using high-frequency in situ bio-optical observations in the subpolar Northwest Atlantic
Kitty Kam, Emmanuel Devred, Stephanie Clay, Mohammad M. Amirian, Andrew Irwin + 3 more
TLDR
Satellite models significantly overestimate Net Primary Production (NPP) in the subpolar Northwest Atlantic, requiring better regional calibration.
Key contributions
- Compared global (VGPM) and regionally tuned (BIO) satellite NPP models against high-frequency in situ data.
- Satellite models overestimated depth-integrated NPP by 2.5 to 4 times in the subpolar Northwest Atlantic.
- VGPM's global parameters and simplified depth assumption caused unrealistic vertical NPP and missed a major bloom.
- BIO model's remaining discrepancies were primarily due to P-I parameter assignment, despite tuned Chl-a.
Why it matters
Accurate NPP estimates are vital for understanding the global carbon sink, especially in high-latitude regions. This study reveals significant satellite-derived NPP mismatches, offering insights to improve regional model calibration and data sources for more reliable carbon cycle assessments.
Original Abstract
Net primary productivity (NPP) forms the basis of biological carbon pump, but its estimates in high-latitude regions remain highly uncertain despite its disproportional importance for the global carbon sink. Optical satellites are limited by cloud cover, low irradiance, and shallow light penetration, with uncertainties further exacerbated by the lack of in situ validations and regional model tuning for NPP measurements. This study compared two satellite-based models, a global (VGPM) and a regionally tuned (BIO) NPP model, with a time series of in situ NPP. Using a high-frequency, depth-resolved moored profiler in the subpolar Northwest Atlantic (56°N) in 2016, in situ NPP was estimated by daily bio-optical profiles and prior measurement of photosynthesis-irradiance (P-I) parameters. Our findings indicated that satellite-derived estimates of depth-integrated NPP were overestimated by a factor of 2.5 to 4. However, the reasons for the discrepancies varied between the VGPM and BIO model. VGPM used global photosynthetic parameters with a simplified depth assumption, leading to an unrealistic vertical structure for depth-integrated NPP, despite its surface values were lower than in situ estimates. A major phytoplankton bloom in June-July was missed by VGPM, likely due to the use of non-regionally calibrated OCI Chl-a, which led to an underestimation of biomass. In contrast, the BIO model used regionally tuned POLY4 Chl-a products, and the differences in the assignment of P-I parameters accounted for the remaining discrepancies. This study showed the possibility to reach good agreement between satellite and in situ NPPs if the challenge of P-I assignment can be overcome. We recommend further studies to investigate discrepancies of NPP estimates in high-latitude regions, focusing on data sources and model choices, as well as improving regional model calibration to enhance NPP accuracy.
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