We present a novel method using satellite and biogeochemical Argo (BGC-Argo) data to retrieve the three-dimensional (3D) structure of chlorophyll a (Chla) in the northern Indian Ocean (NIO). The random forest (RF)-based method infers the vertical distribution of Chla using the near-surface and vertical features. The input variables can be divided into three categories: (1) near-surface features acquired by satellite products, (2) vertical physical properties obtained from temperature and salinity profiles collected by BGC-Argo floats, and (3) the temporal and spatial features, i.e., day of the year, longitude and latitude. The RF-Model is trained and evaluated using a large database including 9,738 profiles of Chla and temperature-salinity properties measured by BGC-Argo floats from 2011 to 2021, with synchronous satellite-derived products. The retrieved Chla values and the validation dataset (including 1,948 Chla profiles) agree fairly well, with R ² =0.962, root-mean-square error (RSME) = 0.012, and mean absolute percent difference (MAPD) = 11.31%. The vertical Chla profile in the NIO retrieved from the RF-Model is more accurate and robust, compared to the operational Chla profile datasets derived from the neural network and numerical modeling. A major application of the RF-retrieved Chla profiles is to obtain the 3D Chla structure with high vertical resolution. This will help to quantify phytoplankton productivity and carbon fluxes in the NIO more accurately. We expect that RF-Model can be used to develop long-time series products, to understand the variability of 3D Chla in future climate change scenarios.

In this study, we analyzed the effect of warming in ecological responses due to seasonal cycle and 2015/2016 El Niño event on the vertical distribution of phytoplankton within the entire euphotic zone (0–100 m) in the eastern Arabian Sea using BGC‐Argo data during 2015–2019. We found that phytoplankton in different layers had different responses to warming. Phytoplankton biomass (defined as the integrated chlorophyll a concentration in this paper) decreased in 0–50 m layer while it increased in 50–100 m layer during spring (March‐June) and 2015/2016 El Niño event. At the same time, the vertical expansion of warming (temperature >28 °C), together with nitrate and silicate co‐limitation, triggered the formation of subsurface chlorophyll maximum layer, which became thinner and deeper during these warming periods. Results from the generalized additive models showed that the monthly 28 °C isotherm can be used as a first approximation to separate vertical water column where warming had opposite signed effects. For a 0–50 m layer of poor nutrients due to the mixed layer shoaling and reduced atmospheric deposition, a negative effect of warming on phytoplankton was seen if the temperature was higher than 28 °C. But, for a 50–100 m layer of rich nutrients, a positive effect of warming on phytoplankton was seen if the temperature was within the range of 25.5–28.0 °C and the light was enhanced. These results shed light on the effect of global warming on subsurface phytoplankton and may help research of the same topic regarding future warming.

The Indian Ocean Dipole (IOD) and El Niño–Southern Oscillation (ENSO) are the primary climatic modes that profoundly impact physical and biological processes in the Northern Indian Ocean (NIO). IOD- and ENSO-related vertical phytoplankton anomalies, however, remain poorly understood. Using the three-dimensional Chlorophyll a concentration dataset generated by a machine learning model, this study examines IOD- and ENSO-linked vertical phytoplankton anomalies over the entire euphotic layer (0–100 m) in the NIO during 2000–2019. Results reveal that IOD and ENSO trigger significant opposite changes in phytoplankton at 0–50 m and 50–100 m. The effects of IOD and ENSO on the vertical structure of phytoplankton are generally asymmetric, with anomalies at 0–50 m being significantly larger than that at 50–100 m. During summer and fall, the significant vertical phytoplankton anomalies in the Central Arabian Sea (CAS), Southern Tip of India (STI), and the Eastern Equatorial Indian Ocean (EEIO), are primarily related to IOD forcing. IOD-linked negative (positive) phytoplankton anomalies at 0–50 m (50–100 m) are driven by the westward propagating downwelling Rossby waves. During winter and spring, due to the local wind anomalies and shallower thermocline, the Seychelles–Chagos Thermocline Ridge (SCTR) is the only region where ENSO exhibits greater positive effects on phytoplankton at 50–100 m than IOD. Different from IOD, the ENSO-related wind reversal impedes subsurface upwelling in the STI and EEIO, thereby constraining vertical biological activity. These findings could shed light on how phytoplankton will respond to changing ocean dynamics under global warming.

Submesoscale eddies strongly regulate upper-ocean physical–biological interactions, yet their ecological impacts remain poorly observed because conventional satellite measurements lack sufficient spatial resolution. Here, we combine Surface Water and Ocean Topography (SWOT) sea surface height observations with multi-resolution VIIRS ocean-colour data to investigate phytoplankton responses to a submesoscale eddy in the Agulhas Current system off South Africa. SWOT resolves a compact cyclonic eddy with a 15 cm sea surface height anomaly and a radius of only 15 km. In contrast, the eddy is almost completely absent from the conventional DUACS altimetry product. Near-simultaneous 750 m VIIRS observations reveal localized enhancements of chlorophyll a (Chla) and particulate organic carbon (POC) that coincide with the eddy. The 750 m observations also captured higher local extremes, with Chla exceeding 0.60 mg m⁻³ and POC exceeding 120 mg m⁻³. These biological features become progressively weaker in the 4 km and 9 km products, indicating that coarse-resolution observations may smooth fine-scale Chla and POC variability. Hydrographic observations reveal a cold-core structure and the upward displacement of dense subsurface water. These observations suggest that submesoscale upwelling and frontal convergence jointly promote localized Chla and POC enhancements. Our results reveal an association between submesoscale physical variability and localized biological variability. They highlight the potential of integrating SWOT with high-resolution ocean-colour observations to investigate fine-scale ecosystem dynamics and associated carbon variability.