Global Assessment Report Team GAR

1. Identifying new data needs and sources Linking DRR and Adaption: Disaster Inventories Data on impacts and vulnerability Global Assessment Report Team GAR United Nations International Strategy for Disaster Reduction UNISDR

2. HYOGO FRAMEWORK FOR ACTION • In January 2005, 168 Governments adopted a 10-year plan to make the world safer from natural hazards at the World Conference on Disaster Reduction, held in Kobe, Hyogo, Japan. • Its goal is to substantially reduce disaster losses in lives, and in the social, economic, and environmental assets of communities and countries. • The Hyogo Framework offers guiding principles summarized in 5 priorities for action

3. HFA 5 PRIORITIES FOR ACTION • Ensure that disaster risk reduction is a national and a local priority with a strong institutional basis for implementation. • Identify, assess and monitor disaster risks and enhance early warning. • Use knowledge, innovation and education to build a culture of safety and resilience at all levels. • Reduce the underlying risk factors. • Strengthen disaster preparedness for effective response at all levels.

4. HYOGO FRAMEWORK FOR ACTION A2 • Develop, update periodically and widely disseminate risk maps and related information to decision-makers, the general public and communities at risk • Develop systems of indicators of disaster risk and vulnerability at national and sub-national scales • Record, analyse, summarize and disseminate statistical information on disaster occurrence, impacts and losses, on a regular bases through international, regional, national and local mechanisms.

5. GEO/GEOSS goals GEOSS will yield a broad range of societal benefits, notably: • Reducing loss of life and property from natural and human-induced disasters • Understanding environmental factors affecting human health and well-being • Improving the management of energy resources • Understanding, assessing, predicting, mitigating, and adapting to climate variability and change • Improving water resource management through better understanding of the water cycle • Improving weather information, forecasting and warning • AND OTHERS....

6. Current data for monitoring disaster risk • Hyogo Framework for Action implementation • Monitoring of levels of risk to disasters • Monitoring levels of losses • Progress in measures to reduce risk • Global Assessment Report (Biennial) • Special Report of IPCC (SREX) • First IPCC review of what constitutes effective measures to reduce risk to extreme events

7. Typical contents of a Disaster database • Simple, low technology • Non expensive • High impact, ROI The actual screen for data capture. Customizable by users. Standard Effects (killed, injured, affected, etc.) Extension (Sectorial detail information)

8. What are National Disaster Inventories? • Disaster Inventories record and analyse the occurrence and effects of natural disasters • Disaggregated information is provided in tabular and graphical form (maps and charts) • Richer than global data: Events of all scales, more indicators, closer (local) level of observation

9. Temporal Analysis (Trends): distribution of losses over time Behaviour of disaster losses is key in understanding trends and essential for monitoring the effectiveness of DRR Seasonal distribution of floods in Mexico Number of reports of floods and people killed by epidemics in Orissa, India 11 years, showing a high correlation between floods and epidemics. Ovals show non-related epidemic events.

10. Spatial Analysis (patterns): distribution of losses over space The Municipalities located over the Andes mountain area are the most prone to landslide disasters Spatial distribution of landslides in Colombia

11. Usage of Disaster loss data in Risk Assessments. Typical analytical loss exceedance curve, Colombia The hybrid loss exceedance curve, Colombia

12. Impact and extent of (possibly) Climate Change related events Temporal distribution of Surge reports, PERU Mortality due to Surge , PERU Spatial distribution of Surge reports, PERU Damage to housing sector – due to Surge , PERU

13. Impact and extent of (possibly) Climate Change related events Frequency of extreme precipitation-related events , 8 South American countries Mortality due to extreme precipitation events

14. Usage of Historical Loss Data in DRRM • Modeling probable maximum losses up to a return period of approximately 30 – 50 years. • Provide historical vulnerability indexes/functions • Allow monitoring of DRR measures • Historical data can help validating Risk Assessments • Provide a dynamic vision of risk evolution over time • Provide evidence-based support to decision makers • Generate proxy indicators of Risk (for hard-to-model risks or when no data is available) • … • Climate Change Adaptation?

15. UN sponsored Disaster Inventories Asia/Pacific Sri Lanka, Indonesia, Iran, Maldives, Nepal, India (Tamil Nadu, Orissa, Andra Pradesh, Uttranchal, Delhi), Jordan, Syria, Vietnam, Laos*, Vanuatu*, Solomon*, SOPAC, East Timor, Philippines LAC Mexico, Costa Rica, El Salvador, Panama, Colombia, Ecuador, Peru, Bolivia, Venezuela, Argentina, Chile, Paraguay, Panama, Guatemala, Jamaica, Trinidad & Tobago, Guyana, Antigua Africa Egypt, Morocco, Yemen, Mozambique, Mali, Djibouti * Many other countries (USA, Australia, etc.) have independently build datasets. A total of about 60 datasets identified.

16. Potential Usage of Historical Loss Data in CC • Provide measures of historical/current impact ? • Historical data to be input layer for Impact Assessments • Permit finer grain impact analysis (compared to global datasets) • Validate hypothesis of realized change? • Allow monitoring of Climate Change impact ? • Frequency • Severity • Location • Other?

17. Global Assessment Report on Disaster Risk GAR United Nations International Strategy for Disaster Reduction UN-ISDR www.unisdr.org IEH International Environment House 7-9 Chemin de Balextert, 4th floor Julio Serje serje@un.org John Harding harding@un.org Justin Ginnetti ginnetti@un.org