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Highlighting the key role of statistics in managing climate change-related disaster risks

Statistics play a crucial role in dealing with disasters, from preparation to recovery and reporting. The need for timely and accurate data is especially significant in light of the increasing frequency and severity of climate change-related extreme weather events.

However, the data needed for effective disaster risk reduction is not always readily available when needed. It is therefore important to strengthen the role of official statistics as they provide key data relevant to all phases of disaster risk management.

“It is not enough to sit and watch as scientific predictions about climate change come true. Data are fundamental to deciding how to react to large global scale problems. The effort we are doing here to improve data has never been more important.” said Gavin Schmidt, Director of NASA Goddard Institute for Space Studies, addressing more than 100 statisticians, scientists, and climate change and disaster risk experts in Rome at the UNECE Expert Forum on Climate Change, hosted by FAO on 3-5 October 2017.

The experts gathered in Rome to agree on how to bring together the right people to improve the evidence-base of climate policy making and disaster risk reduction. This is necessary to enable a well-designed response to the changes in climate and disaster events that we are increasingly experiencing.

It was also an opportunity to review statistical approaches to disaster risk reduction from a number of countries. These highlighted ways to use official statistics in disaster risk management and examples of producing a set of climate change indicators, as endorsed by the Conference of European Statisticians in June this year.

UNECE is developing recommendations on the role of national statistical offices in disaster risk management with a network of experts, in addition to practical guidance on  data needs linked to disaster risk reduction. The draft guidelines will be shared with countries by the end of 2018.

The guidance is expected to help all countries to monitor and report on progress in achieving the goals of the Sendai Framework for Disaster Risk Reduction and the goals of the 2030 Agenda for Sustainable Development that relate to climate change, extreme events and disasters.

The role of statistics in disaster risk management

When preparing for disasters and assessing risks, statistics are useful for analyzing existing risks, informing the public about future risks, and planning actions to prevent disasters. For instance, statistical data are important for identifying high-risk areas or conditions, and for planning appropriate ways to provide early warning to people and prevent serious damage to infrastructure, buildings and transportation.

Phases of disaster risk management

During a disaster, emergency response and recovery teams use statistics to get data on population and information on infrastructure and services located in the area.

After the disaster, statistics help to mitigate the impact of the disaster and estimate the damage, losses, and disruption to functions and services caused by the event.

Statistics are particularly useful for disaster risk analysis when linked to the geographical location as it enables detailed local and regional analysis. To react to this need, statistical offices are increasingly working together with geospatial experts.

Most statistical offices have not been directly involved in collecting and providing data specifically for disaster risk management. This is because not all statistical offices are fully aware of the exact data needs or have the capability to produce data to meet the specific needs.

Some statistical offices, however, are leading the way forward. For instance, the National Institute of Statistics and Geography in Mexico set up a Collaborative Disaster Relief Site (SICADE) with up-to-date information about the earthquakes that took place on 7 and 19 September 2017. Examples such as this could prove valuable for statistical offices in regions prone to climate-change related extreme weather events as they look to strengthen the role of statistics in all phases of disaster risk management. 

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