Anthropogenic pressures on marine and terrestrial ecosystems have increased exponentially in the last century. Measuring and monitoring the resulting environmental changes is a challenging task, however, Earth Observation can provide a tool for constant, consistent and coherent observation.
Data from the Copernicus Sentinel missions, the Copernicus Marine Environment Monitoring Service (CMEMS), Copernicus Land Monitoring Service (CLMS) and the European Space Agency Climate Change Initiative (ESA CCI) are able to provide current and historic data at a range of temporal and spatial resolutions. These dataset are capable of fulfilling monitoring requirements but for non-specialists, extracting relevant information from the data is not always easy. It often requires knowledge of the most appropriate variables, the algorithms used to derive them and the data sources in addition to the technical challenges of downloading data and developing code to extract the required information.
To enable users who do not specialise in Earth Observation to benefit from these datasets, NEODAAS have developed a suite of ocean indicators, from key biogeochemical variables, representative of the status of the marine ecosystem. These indicators can be interrogated to inform regional analysis, add context to short-term trends and specific events, and highlight potential correlations between biogeochemical and physical variables.
The NEODAAS Satellite Indicators Suite is targeted to researchers planning to incorporate data from longer time series or wider spatial extents in their studies, supporting models and/or in situ measurements, to help optimise the impact of their work.
The NEODAAS Satellite Indicators Suite is currently composed of:
Silvia Pardo, Earth Observation Scientist at Plymouth Marine Laboratory and lead developer of the Satellite Indicator Suite, commented:
“Satellite-derived indicators are a powerful tool to monitor the health of ecosystems and track climate change impacts at different temporal and spatial scales. Working with researchers as part of NEODAAS, I've seen first-hand how useful these data can be to environmental researchers, many of which had not previously considered using satellite data”
- Time series – the average values of a variable for a region of interest, over a period of time. For variables that present a distinct seasonality, such as chlorophyll concentration, annual cycles can be extracted from the original signal.
- Anomalies – computed by subtracting a reference value from the observations. Climatologies provide a measure of the typical annual cycle and can be used to derive daily anomaly time series that reveal changes in the timing and amplitude of seasonal peaks.
- Trends – increases or decreases in a variable over a long period of time, accounting for the seasonal and interannual components of the signal.
More details about the Satellite Indicators Suite and marine case studies are available in the full report
If you are interested being provided with Satellite Indicators data then please contact us
to discuss submitting a custom data request
To demonstrate the suite, two case studies are presented using a version of the indicators suite applied to satellite-derived ocean indicators (NEODAAS Ocean Indicators Suite).
Using the NEODAAS Ocean Indicators Suite: Phytoplankton phenology in the Western English Channel
Phytoplankton, and chlorophyll concentration as their proxy, respond rapidly to changes in their physical environment. In the North Atlantic, these changes present a distinct seasonality and are mostly determined by light and nutrient availability. The following examples showcase chlorophyll concentration time series from late 1997 to the present day for different locations within the Western English Channel. In particular, data was extracted from the OC-CCI v4 dataset for two Western English Channel Observatory stations, E1 (open-shelf) and L4 (coastal), located in Plymouth Sound, and for a wider box located in the English Channel.
The time series in the image below provide a general view of the Western English Channel dynamics in the last 22 years. The cycle is dominated by the seasonal transition between mixing and stratification, with all three regions showcasing phytoplankton blooms in spring and autumn. The intensity of both blooms is broadly comparable at L4, while the autumn bloom tends to dominate at the open-shelf station E1. This can be connected to E1 developing the summer thermocline earlier than L4. L4 is influenced by river inputs, which can cause high nutrient events that compensate for the nutrient depletion after the spring bloom. Both stations can be subject to strong mixing due to tidal currents and weather conditions. The second half of the 20th century has seen an overall 0.32°C/decade increase in sea surface temperature in the Western English Channel, which can account for changes in the duration of the spring phytoplankton bloom.
Using the NEODAAS Ocean Indicators Suite: Arctic anomalies
Chlorophyll concentration is highly seasonal in the Arctic Ocean region due to a strong dependency on light and nutrient availability, which in turn are driven by seasonal sunlight and sea ice cover dynamics. The analysis of chlorophyll anomalies is critical in the context of Arctic amplification: negative anomalies are associated with a delay in ice breakup and, inversely, positive anomalies are detected in areas with early ice breakup events, although some studies have suggested increasing cloudiness over the region could dampen this effect.
The image shows the 2019 Arctic Sea annual chlorophyll anomaly with respect to the 1997-2019 climatology, both computed using the CMEMS 20-year reprocessed dataset based on the OC-CCI v4 release. Positive anomalies are shown in red, and negative anomalies are shown in blue.