GRID product detail

Spatially enabling the Global Framework for Climate Services: Reviewing geospatial solutions to efficiently share and integrate climate data & information


Duration: September 2017 - on-going

In November 2016, the Paris Agreement entered into force calling Parties to strengthen their cooperation for enhancing adaptation and narrowing the gap between climate science and policy. Moreover, climate change has been identified as a central challenge for sustainable development by the United Nations 2030 Agenda for Sustainable Development. Data provide the basis for a reliable scientific understanding and knowledge as well as the foundation for services that are required to take informed decisions. In consequence, there is an increasing need for translating the massive amount of climate data and information that already exists into customized tools, products and services to monitor the range of climate change impacts and their evolution. It is crucial that these data and information should be made available not in the way that they are collected, but in the way that they are being used by the largest audience possible. Considering that climate data is part of the broader Earth observation and geospatial data domain, the aim of this paper is to review the state-of-the-art geospatial technologies that can support the delivery of efficient and effective climate services, and enhancing the value chain of climate data in support of the objectives of the Global Framework for Climate Services. The major benefit of spatially-enabling climate services is that it brings interoperability along the entire climate data value chain. It facilitates storing, visualizing, accessing, processing/analyzing, and integrating climate data and information and enables users to create value-added products and services.

Data credit(s): Gregory Giuliani (UNEP/DEWA/GRID-Geneva)

GRID unit: Environment Modelling and Geoprocessing

UNEP region: Global

UNEP priorities:  Climate Change, Environmental Governance

english version (2017, Size:0.64Mb)