Page 6 - Disaster Management: The Standards Perspective

Preface – WMO

In recent decades, the increasing frequency and intensity
of natural hazards have highlighted the urgent need for
innovative solutions to mitigate their devastating impacts. As
the specialised UN agency for weather, climate, and water, the
World Meteorological Organization (WMO) recognizes the
challenges these phenomena present and the critical need
for timely and accurate information in disaster mitigation,
preparedness, management, response, and recovery. Artificial
Intelligence (AI) offers unprecedented opportunities to generate
and quality control date, enhance our predictive capabilities,
optimize resource allocation, and improve communication
during emergencies. It is my honour to co-present this report
which showcases the collaborative effort on standardization by the ITU/WMO/UNEP Focus
Group on AI for Natural Disaster Management (FG-AI4NDM). This report stands as a testament
to the power of international cooperation and the transformative potential of advanced
technologies in bolstering our resilience against natural hazards. AI can also speed up and
scale our efforts to achieve the 2030 Agenda for Sustainable Development and the Sustainable
Development Goals.

The work of FG-AI4NDM, which commenced in December 2020, explored the diverse
applications of AI and other emerging technologies throughout the disaster management cycle.
It demonstrates how AI can improve risk assessment, enable precise forecasting, facilitate real-
time monitoring, and support efficient recovery efforts. By harnessing AI, we can transform vast
amounts of meteorological and hydrological data into actionable insights, thereby enhancing
decision-making processes and ultimately saving lives and protecting livelihoods, including the
most vulnerable to climate change.

Each organization has contributed unique expertise: WMO its profound understanding of
meteorology, climatology, and hydrology, ITU its leadership in digital technologies and
standards; and UNEP its focus on environmental sustainability. Together, we have developed
a comprehensive framework for AI applications in disaster management, addressing key issues
such as data privacy, algorithmic biases, and the necessity for high-quality data. These activities
have not only fostered innovation but also built a global network of experts committed to
enhancing disaster resilience through AI.

Looking ahead, it is crucial that we continue to build on this foundation by promoting the
adoption of international standards for disaster management. The outcomes of FG-AI4NDM
are also anticipated to contribute to achieve the goals of the global Early Warnings for All
(EW4All) initiative and the WMO Working Group on Digital Transformation for Hydrology and
Water Resources, which aims to better manage water and climate related hazards and ensure
sustainable water management across all regions.

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