Unlike numerical weather prediction models, forecast systems that use machine learning are not constrained by the physical laws that govern the atmosphere. So it’s possible that they could produce unrealistic results.
In a year overshadowed by the COVID-19 pandemic, 2021 nevertheless saw progress towards strengthening early warning services and building resilience to extreme weather and climate change impacts in some of the world’s most vulnerable countries.
Ahead of the Global Platform for Disaster Risk Reduction in Bali in late May, we bring you an example of how the World Food Programme works ahead of extreme weather events to save lives
This roadmap uses a series of progress models to measure Tunisia's Meteorological and Hydrological Service Providers’ capacities in several key areas: service delivery, observation and telecommunication, and modeling and forecasting.
A new report launched by the World Bank, the Government of Tunisia, and GFDRR examines ways to improve capabilities of Tunisia’s National Meteorological and Hydrological Services to support socio-economic development to save lives and livelihoods.
The Japan Meteorological Agency will start releasing forecast information about linear rainbands, called “senjo kosuitai,” from June that could give the public major flooding warnings. “Once linear rainbands occur, they will likely lead to a disaster."
Scientists at Northern Illinois University continue to hone extended-range weather forecasting, identifying patterns halfway around the globe that will heighten the probability weeks later for hail- and tornado-producing storms in the United States.
The first satellite-telemetered seismic station in Iloilo Province was inaugurated on 28 April 2022, as part of the Philippine Institute of Volcanology and Seismology's commitment to set up 115 seismic stations.
