Podcast: From Early Warnings to Lasting Resilience: Strengthening Global Preparedness скачать в хорошем качестве

Podcast: From Early Warnings to Lasting Resilience: Strengthening Global Preparedness

Full title "From Early Warnings to Lasting Resilience: Strengthening Global Preparedness Through Science and Innovation" WMO Secretary-General Dr Celeste Saulo explores how the global public infrastructure coordinated by the World Meteorological Organization underpins weather, water and climate intelligence worldwide, enabling early warnings that protect lives, livelihoods and economic stability. This shared system, built on scientific data, observation networks, forecasting centres and international cooperation, supports timely warnings of extreme events, which increasingly affect both developed and developing countries. Drawing on examples from the Early Warnings for All initiative, the lecture shows how global systems translate into national and local capacity, particularly in least developed countries and small island developing states, where climate risks are most acute. The Secretary-General also highlights key initiatives, including the WMO Commons, SOFF and CREWS, that are strengthening shared capacity, sustaining essential global services and ensuring that early warning systems remain a trusted global public good in a changing climate. This event is part of the IIEA’s Development Matters Series which is kindly sponsored by Irish Aid. About the Speaker: Secretary-General Saulo was the first female and the first South American appointed as Secretary-General of the WMO and began her four-year term of office on 1 January 2024. Prior to this she served as the Director of the National Meteorological Service of Argentina and was the first Vice-President of the WMO. She graduated from the University of Buenos Aires in 1996 with a PhD and rose to a full professorship at that university where she became Director of the Department of Atmosphere and Ocean Sciences. Her scientific specialisations are in numerical weather prediction, data assimilation, short-to-medium range prediction and early warning systems.