Reviewing the discoverability and accessibility to data and information products linked to Essential Climate Variables
Essential Climate Variables (ECVs) are geophysical records generated from systematic Earth Observations associated with climate variations, changes, and impacts. ECVs products support the data and information needs of international frameworks and policies such as the work of the United Nations Frame...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-02-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17538947.2019.1620882 |
| Summary: | Essential Climate Variables (ECVs) are geophysical records generated from systematic Earth Observations associated with climate variations, changes, and impacts. ECVs products support the data and information needs of international frameworks and policies such as the work of the United Nations Framework Convention on Climate Change (UNFCCC) and the Intergovernmental Panel on Climate Change (IPCC). We map the main networks and initiatives publishing ECVs, by presenting an overview of existing satellite-based ECVs, their general data creation characteristics, discoverability and accessibility methods from an end-user perspective. We investigate key initiatives providing or coordinating access to ECV data records, such as the Global Climate Observing System (GCOS), the Committee on Earth Observation Satellites (CEOS), the Coordination Group for Meteorological Satellites (CGMS), Joint Working Group on Climate (WGClimate), the Remote Sensing Systems (REMSS), and the European Space Agency Climate Change Initiative (ESA CCI). We find that ECV data discovery and access is difficult and time consuming due to the lack of common data and metadata catalogues. In addition, the selection of fit-for-purpose data records by end-users requires the implementation of interoperable standards and scalable data infrastructures to allow the generation of tailored applications and data-driven information products in support of decision-making processes. |
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| ISSN: | 1753-8947 1753-8955 |