| Popis: |
Phytoplankton occupy the oceans’ euphotic zone and are responsible for its primary production; thus, our ability to monitor their patterns of abundance and physiology is vital for tracking ocean health. Ocean colour sensors mounted on satellites can monitor the surface patterns of phytoplankton daily at global scales but cannot see into the subsurface. Autonomous robotic platforms, like Biogeochemical-Argo (BGC-Argo) profiling floats, do not have the coverage of satellites but can monitor the subsurface. Combining these methods can help track phytoplankton patterns throughout the euphotic zone. In this study, using a global array of BGC-Argo floats (76,043 profiles, spanning from 2010 to 2023), we revisit empirical relationships between the surface and column-integrated concentrations of chlorophyll-a (a proxy for phytoplankton abundance and physiology), originally developed using ship-based profiling data. We show that these relationships agree well with BGC-Argo float data. We then extend the relationships, removing the binary switch in parameters between mixed and stratified waters and trophic conditions such that the column-integrated chlorophyll-a concentration can be estimated as a continuous function of surface chlorophyll-a and a proxy for stratification (we use the optical mixed-layer depth, the mixed-layer depth multiplied by the diffuse attenuation coefficient, which is proportional to the ratio of the euphotic depth to the mixed layer depth when it approaches 1). The new model is shown to perform well in statistical tests (using separate training and independent validation data, with a correlation coefficient >0.73) and has fewer parameters than the earlier version. The model can be applied to satellite observations of surface chlorophyll-a and diffuse attenuation, together with fields of mixed-layer depth (e.g., from Argo), to track changes in column-integrated chlorophyll-a. Such fields may be useful for obtaining estimates of primary production, evaluating ecosystem models, and quantifying trophic energy transfer. The model may also be used to evaluate the influence of changing stratification patterns on phytoplankton abundance and physiology. |
