Sustained global ocean observations are needed to recognise, understand, and manage changes in marine biodiversity, resources and habitats, and to implement wise conservation and sustainable development strategies. To meet this need, the Global Ocean Observing System (GOOS), a network of observing systems distributed around the world and coordinated by the Intergovernmental Oceanographic Commission (IOC) has proposed Essential Ocean Variables (EOVs) that are relevant to both the scientific and the broader community, including resource managers. Building a network that is truly global requires expanding participation beyond scientists from well-resourced countries to a far broader representation of the global community. New approaches are required to provide appropriate training, and resources and technology should follow to enable the application of this training to engage meaningfully in global observing networks and in the use of the data. Investments in technical capacity fulfil international reporting obligations under the UN Sustainable Development Goal 14A. Important opportunities are emerging now for countries to develop research partnerships with the IOC and GOOS to address these obligations. Implementing these partnerships requires new funding models and initiatives that support a sustained research capacity and marine technology transfer.
High quality data of surface radiation is a prerequisite for climate monitoring (Earth radiation budget) and solar energy applications. A very common method to derive solar surface irradiance is the Heliosat method, a one channel approach for the retrieval of the effective cloud albedo (CAL). This information is then used to derive the solar surface irradiance by application of a clear sky model. The results of this study are based on radiative transfer modelling, visual inspection of satellite images and evaluation of satellite based solar surface radiation with ground measurements. The respective results provide evidence that variations in Aerosol Optical depth induced by desert storms and biomass burning events lead to a significant increase of the effective cloud albedo, thus, that certain aerosol events are interpreted as clouds by the method. For the estimation of the solar surface radiation aerosol information is needed as input for the clear sky model. As the aerosol effect is partly considered by CAL, there is a need to modify external aerosol information for the use within the clear sky model, e.g., by truncation of high aerosol loads. Indeed, it has been shown that a modified version of the Monitoring Atmospheric Composition and Climate (MACC) aerosol information leads to better accuracy of the retrieved solar surface radiation than the original MACC data for the investigated 9 sites and time period (2006)(2007)(2008)(2009). Further, the assumption of a constant aerosol optical depth of 0.18 provides also better accuracies of the estimated solar surface radiation than the original MACC data for the investigated sites and period. It is concluded that this is partly due to the consideration of scattering aerosols by the effective cloud albedo.Atmosphere 2015, 6 864
<p>EUMETSAT provides user support and training for all users of the Copernicus Marine Data Stream (CMDS). The CMDS refers to all the level 1 and level 2 marine data from sensors on the Sentinel-3 and Jason-3 satellites, including ocean colour, sea surface temperature, and surface topography data. Details on the products and processing methodologies are available through handbooks, product notices, and a number of services including a help desk, and online forum. The training service aims to support all users wishing to explore potential applications of the CMDS. The service is primarily based around the delivery of two week, blended courses with both an online and classroom component.&#160; The online component is hosted on a Moodle platform and uses a variety of prepared resources including short articles, videos, software installation, and basic software tutorials; supported by discussion forums, to prepare participants for the classroom phase. The classroom phase is focused on practical work, with no lectures given. Participants are led through examples of workflows using SNAP and Jupyter Notebooks/Python, and are then given one-on-one/small group trainer support to work for 3 days on personal projects that they defined during the online phase. These projects yield a diverse range of synergistic use cases of ocean remote sensing data for societally relevant applications The training service has also run a variety of collaborative courses with community led initiatives, and proposes to develop online courses and resources in response to community needs. Feedback and requests from the ocean remote sensing community are welcomed.</p><p>&#160;</p>
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