One of the central goals of using satellite ocean color remote sensing is to detect and identify different phytoplankton groups (size classes) and describe their variability continuously and synoptically for various applications including marine ecosystem dynamics, carbon and biogeochemical cycles, and related fields in oceanography. Taking the advantage of phytoplankton communities having distinct optical properties, this study presents a new model to explicitly detect and differentiate between three phytoplankton size-classes namely, picophytoplankton, nanophytoplankton, and microphytoplankton, based on distinct differences in the optical signatures of these phytoplankton groups in a wide variety of coastal and oceanic waters. The model is based on the assumption that there is a significant relationship between chlorophyll-. a concentration, and total as well as the size-fractioned absorption coefficients of phytoplankton. The new model is validated using three different in-situ datasets collected from a wide variety of locations in the global and regional oceans (including turbid coastal and eutrophic waters) and its results are further compared with those of the existing two- and three-component models. The new model performs better than other models in terms of yielding more accurate estimates of the total and size-dependent phytoplankton absorption coefficients across the entire visible wavelengths. Since satellite observation of 'ocean color' as detected by a remote sensor provides an estimate of the chlorophyll-. a concentration, commonly used as an index of phytoplankton biomass, the new model is also applied to regional and global images of seasonal climatology over a decade of satellite ocean color observations provided by the MODIS-Aqua sensor. When applied to the MODIS-Aqua images of the Arabian Sea dominated by spatially intense algal blooms, the present model is generally excellent at predicting and describing the spatial distribution of these phytoplankton groups within cyclonic eddies and adjacent regions in the Arabian Sea. Conversely, size-fractioned phytoplankton absorption coefficients derived from global images of seasonal climatology are found to vary depending on the season and ocean basin. These global images imply that when phytoplankton abundance increases, larger size-classes are added incrementally to a background of smaller cells. Further examination of these data showed that picophytoplankton population is generally low, although dominating a major part of the surface ocean during summer and winter. Nanophytoplankton and microphytoplankton populations are high in surface waters of the North and South Atlantic, North and South Pacific Oceans, Arabian Sea, and equatorial region, showing an increasing trend in summer and a decreasing trend in winter in each hemisphere. These results suggest that the new model is an important tool which will inspire further research to investigate different phytoplankton size classes and their variability on regional and global scales. © 2014 Elsevier Inc.