Spectrally-resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and inter-annual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes current status and future prospects in the field of ocean colour focussing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focussing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean are described and finally a summary of future perspectives is provided.

Climate change is expected to elicit widespread alterations to nutrient and light supply, which interact to influence phytoplankton growth and their seasonal cycles. Using 25 years of satellite chlorophyll a data, we show that large regions of the Southern Ocean express significant multi-decadal trends in phenological indices that are typically larger (<50 days decade^–1) than previously reported in modelling studies (<10 days decade^–1). Although regionally dependent, there is an overall tendency for phytoplankton blooms to increase in amplitude, decline in seasonality, initiate later, terminate earlier and have shorter durations, except in the ice, which initiate earlier and have longer durations. Investigating relationships with prominent climate drivers highlights regional sensitivities and complexities of multiple interacting aspects of a changing climate. Seasonal adjustments of this magnitude at the base of the food web can de-synchronize energy transfer to higher trophic levels, threatening ecosystem services and impacting global climate by altering natural CO₂ uptake.

The aquaculture industry of southern Africa faces environmental threats from harmful algal blooms (HABs), which have the potential to cause devastating economic losses (Pitcher et al., 2019). Satellite earth observation offers a systematic and cost effective method for operational monitoring of HABs over large areas. Whilst the chlorophyll-a concentration ([Chl-a]) product, often used as a proxy for phytoplankton biomass, can be used to indicate high biomass blooms (elevated biomass against a background signal of 5–10 mgChl m⁻³), there is a clear need for value-added products that not only alert on bloom presence, but also on the bloom type and persistence. This study demonstrates the identification of different phytoplankton communities that can feasibly be identified in bloom concentrations from space, relevant to the aquaculture industry of South Africa. In terms of water-leaving reflectance, 76 % of the variance in the red and NIR spectral region is significantly positively correlated to phytoplankton abundance, [Chl-a], and the maximum line height (MLH) (defined as the height of the maximum reflectance peak above a baseline between 665 and 753 nm). The MLH is related to dominant phytoplankton types derived from phytoplankton count data, in order to identify thresholds which represent blooms that pose a high hypoxia and/or toxicity risk; whilst 0.0016 < MLH < 0.003 represent low to moderate concern mixed assemblage blooms, MLH > 0.003 has a strong likelihood of indicating high biomass dinoflagellate or Pseudo-nitzschia blooms. These techniques are routinely used by the aquaculture industry in South Africa for decision support and risk mitigation. The high biomass nature of the South African regional waters provide strong assemblage-related spectral variability, which can be exploited with the spectral bands of OLCI and MERIS. Application to these sensors not only ensures future monitoring capability, but also allows the creation of a historical risk climatology that can guide the site selection of industries sensitive to the presence of HABs, such as aquaculture facilities and desalination plants.

The Southern Ocean (SO) is highly sensitive to climate change. Therefore, an accurate estimate of phytoplankton biomass is key to being able to predict the climate trajectory of the 21st century. In this study, MODerate resolution Imaging Spectroradiometer (MODIS), on board EOS Aqua spacecraft, Level 2 (nominal 1 km × 1 km resolution) chlorophyll-a (C ${}^{Sat}$ ) and Particulate Organic Carbon (POC ${}^{sat}$ ) products are evaluated by comparison with an in situ dataset from 11 research cruises (2008–2017) to the SO, across multiple seasons, which includes measurements of POC and chlorophyll-a (C ${}^{insitu}$ ) from both High Performance Liquid Chromatography (C ${}^{HPLC}$ ) and fluorometry (C ${}^{Fluo}$ ). Contrary to a number of previous studies, results highlighted good performance of the algorithm in the SO when comparing estimations with HPLC measurements. Using a time window of ±12 h and a mean satellite chlorophyll from a 5 × 5 pixel box centered on the in situ location, the median C ${}^{Sat}$ :C ${}^{insitu}$ ratios were 0.89 (N = 46) and 0.49 (N = 73) for C ${}^{HPLC}$ and C ${}^{Fluo}$ respectively. Differences between C ${}^{HPLC}$ and C ${}^{Fluo}$ were associated with the presence of diatoms containing chlorophyll-c pigments, which induced an overestimation of chlorophyll-a when measured fluorometrically due to a potential overlap of the chlorophyll-a and chlorophyll-c emission spectra. An underestimation of ∼0.13 mg m ${}^{-3}$ was observed for the global POC algorithm. This error was likely due to an overestimate of in situ POC ${}^{insitu}$ measurements from the impact of dissolved organic carbon not accounted for in the blank correction. These results highlight the important implications of different in situ methodologies when validating ocean colour products.