The potential links between climate change, weather patterns, migration and conflict have received growing attention from scientists, media and global institutions over the last decade. This report gives an overview of available humanitarian security databases and evaluates uncertainty issues around these data.
Despite the increasing role that climate change has played in global security analyses and conventions, research on these topics has not fully matured or reached consensus on the existence of causal relationships. As for drivers of conflicts, violence and migration multiple explanations are found in the literature.
To deepen scientific insights in these complex processes and to strengthen the knowledge–policy interface, PBL Netherlands Environmental Assessment Agency participates in the Planetary Security Initiative. The present report is part of this initiative.
Indicators on national scales
We explore a broad range of global databases containing human security indicators on country scale, varying from socio-economic indicators to climatic/weather indicators, and from indicators for food production to political indicators (corruption, governance, conflicts and violence).
The results reported here show the availability of a wealth of indicators and indicator frameworks, published by a great variety of organisations: national and international institutes, universities, think tanks and reinsurance companies. These indicators have multiple applications:
- monitor human security issues such as formulated in the Sustainable Development Goals,
- support research in the field of disaster risk reduction,
- support climate change adaptation research,
- identify hotspots of conflict and violence, this to prioritise humanitarian aid programs,
- feed statistical analyses and integrated assessment models that aim to analyse and predict impacts of climate change (poverty, water-related tensions, migration flows, conflicts).
An important question is the reliability of all these data. Reliability of data is important since poor numbers will be found in poor and fragile countries with low levels of statistical capacity. However, these countries might need humanitarian/financial aid the most.
To get a grip on reliability issues we identified a number of uncertainty sources and propose ways to check the quality of specific indicators, with special reference to individual countries. One suggestion is to incorporate the World Bank national-based statistical capacity indicator in statistical analyses.