2519 - Estimate near-surface chlorophyll-a concentration for monitoring harmful algal blooms (HABs)

Estimate near-surface chlorophyll-a concentration for monitoring harmful algal blooms (HABs)

Concepts

  • [TA13-6-1] Monitor the marine ecosystem
    Oceanic waters cover approximately 70% of the Earth´s surface and play a key role in regulating Earth temperature and climate, support important marine ecosystems and provide food and transport. Ocean waters occupy large areas and involve highly dynamic processes with different temporal and spatial scales. In-situ measurements taken by ships and buoys can provide accurate information but only at specific locations, being limited to understand large-scale processes. To characterise the heterogeneity and dynamics of ocean waters, it would be required to perform exhaustive field campaigns with associated high costs and infrastructure challenges. EO is an efficient tool to monitor ocean waters and to complement ocean in-situ monitoring programmes as it can provide cost-effective information over vast areas at continuous temporal and spatial scales. Since the first EO satellite specifically designed to study the oceans (SeaSat) has been launch in the 1970s, many sensors and platforms have been developed. This variety of sensors have provided measurements of a broad range of ocean physical and biological variables to the present day. For example, satellite observations in the visible and near-infrared bands have provided information about ocean colour that can be used to estimate chlorophyll-a concentration for monitoring water quality, productivity and algal blooms. Thermal infrared (TIR) sensors have provided data of Sea Surface Temperature (SST) that is of importance for the study of currents and ocean warming. Microwave radiometers have registered sea surface salinity (SSS), critical to determine the global water balance, understanding ocean currents and estimating evaporation rates. EO can also provide information about physical ocean features such as surface elevation and ocean currents, sea surface winds, ocean waves, vessels and pollutants such as oil spills. The versatility of EO data have been proved in a broad range of applications, including the monitoring of water quality, climate change effects, hurricane tracking and prediction, monitor maritime traffic and pollution, harmful algal blooms and fisheries management. In recent years, the Copernicus programme has launched a series of satellite missions for water and land monitoring that guarantee the provision of long-term observations giving continuity to previous satellite missions. Within the Copernicus programme, especially the Sentinel-3 mission will have relevance for ocean observations. Currently, two satellites Sentinel-3A and Sentinel-3B, launched respectively in 2016 and 2018, are providing near-real-time data on the state of the ocean surface, including sea surface temperature, marine ecosystems, water quality and pollution monitoring. New hyperspectral missions such as the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) developed by NASA, are currently under development. In the near future, they will complement the existing satellite missions and will register data in a high number of spectral bands. This information will be essential in diverse applications such as aquatic ecology and biochemistry. Ocean EO is still an evolving field that will need skilled professionals that exploit the data from the new and upcoming missions for the advancement of ocean knowledge and monitoring.
  • [IP3-1-1-4] Water quality variables
    Water quality variables can be derived from Earth observation (EO) data to provide essential ocean variables. They include Sea-surface temperature (SST), Sea-surface salinity (SSS) and Air-Sea Fluxes. SST controls the atmospheric response to the ocean at both weather and climate time scales. The spatial patterns of SST reveal the structure of the underlying ocean dynamics, such as, ocean fronts, eddies, coastal upwelling and exchanges between the coastal shelf and open ocean. SSS observations contribute to monitoring the global water cycle (evaporation, precipitation and glacier and river runoff). Water quality variables can be derived from EO data by using ocean colour products from optical sensors and relating them to ground truth information from in situ sensor networks.