Assessment of satellite-based Net Primary Productivity models in different biogeochemical provinces over the northern Indian Ocean

The biological productivity in the oceanic ecosystem plays a vital role in the global carbon cycle and energy flow in the oceanic food chain. Therefore, proper monitoring of phytoplankton primary production in the ocean is essential to understand the role and responses of aquatic ecosystems to global climate change. Its quantification is also important for higher trophic-level studies and sustainable ecosystem management. The advent of satellite technology has provided an opportunity to retrieve Net Primary Productivity (NPP) at high spatial and temporal resolution. However, for efficient utilization of satellite NPP it is imperative to assess the models for their accuracy and variability. The present study described NPP estimated from MODIS-Aqua satellite data (2003-2021) using five models (VGPM, Eppley-VGPM, CbPM, CAFE, and SABPM) and their variability in the four biogeochemical provinces (ARAB, MONS, INDW and INDE) in the northern Indian Ocean. The temporal variability indicated all models exhibit seasonal variability in ARAB and INDW with two prominent peaks during peak southwest monsoon (June-August) and winter monsoon (December-January). However, there was significant difference in the magnitude. The seasonal peak was primarily due to increase in NPP due to summer upwelling and winter mixing. The spatially averaged diversity index indicated maximum variability in INDW (74.6-77.1%), followed by INDE (77.2-78.0%), ARAB (77.2-78.4%), and MONS (78.6-78.9%). The satellite retrieved NPP by various models showed maximum diversity in the region above 15 & DEG;N and west of 60 & DEG;E in AS and 20 & DEG;N and east 90 & DEG;E in the BoB indicating a significant influence of discharge from perennial rivers resulting in poor performance of the models in these regions. The variability of other models was then assessed with respect CbPM as the model was known to perform better. The Eppley-VGPM showed a maximum (55%) and SABPM showed a minimum (11%) Mean Absolute Percentage Difference with respect to CbPM. The long-term spatio-temporal and quantifiable variability between the NPP models, and biogeochemical provinces, indicated that the study provided useful information on the selection and utilization of an appropriate model for future sustainability and climate change studies.