Date of submission
Phase
Implementation
Countries
Objective
Sectors
Cross-sectoral enabler
Approach
Early Warning Systems Communication
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Date of submissionPhaseCompletedCountriesObjectiveSectorsCross-sectoral enablerContext
In Costa Rica, the role of forests in climate change adaptation and mitigation is widely acknowledged and various political and financial mechanisms have been developed to support ecosystems in facilitating adaptation processes and act as carbon sinks that directly contribute to mitigation. However, there is a lack of instruments to facilitate access to information for improving the decision-making process for climate change adaptation and mitigation when it comes to the management of forests and associated ecosystem services.
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Date of submissionPhaseCompletedCountriesObjectiveCross-sectoral enablerApproachThis Technology Transfer Advances Ghana's
- Nationally Determined Contribution to increase climate resilience and decrease vulnerability for agriculture and food security sector, by adopting disaster prevention actions such as early warning systems.
Context
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Date of submissionPhaseCompletedCountriesObjectiveCross-sectoral enablerApproachThis Technology Transfer Advances Thailand's
- Nationally Determined Contribution to
- Strengthen disaster risk reduction and reduce population’s vulnerability to climate risk and extreme weather events through enhanced awareness, coordination and adaptive capacity of local communities, especially in the disaster risk-prone areas
- Nationally Determined Contribution to
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Date of submissionPhaseCompletedCountriesObjectiveCross-sectoral enablerApproachThis Technology Transfer Advances The Dominican Republic's
- Nationally Determined Contribution to adopt Risk Management and Early Warning Systems as a strategic planning approach to climate change adaptation.
Context
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Objective
A climate change monitoring system integrates satellite observations, ground-based data and forecast models to monitor and forecast changes in the weather and climate. A historical record of spot measurements is built up over time, which provides the data to enable statistical analysis and the identification of mean values, trends and variations. The better the information available, the more the climate can be understood and the more accurately future conditions can be assessed, at the local, regional, national and global level.
