ECMWF Launches First Operational AI Weather Model ECMWF has been developing the Artificial Intelligence Forecasting System (AIFS) to run side by side with its traditional physics-based Integrated ...

Much of the heavy rains that hit the Philippines during the Amihan northeast monsoon season between November and March are ...

Abstract: Traffic flow forecasting is essential for managing congestion, improving safety, and optimizing various transportation systems. However, it remains a prevailing challenge due to the ...

The neural network gives a highly detailed forecast for the Barents and Kara Seas more than 50 times faster than resource-intensive physical models ...

An AI system developed at NYU Abu Dhabi can predict solar wind conditions four days ahead by analyzing detailed images of the Sun. The improved accuracy may help shield satellites, power grids, and ...

Google DeepMind and Google Research today announced WeatherNext 2 as its “most advanced and efficient forecasting model.” Notably, it’s helping power forecasts in Google’s consumer apps, including ...

This project uses spatio-temporal graph neural networks to perform weather forecasting on ERA5 reanalysis data. The model treats the global weather system as a graph where each grid point is a node ...

ABSTRACT: This study evaluates the performance of a feed-forward Artificial Neural Network (ANN) model in simulating historical monthly rainfall in Togo (1981-1985, 1986-1990, 1991-1996, and 1996-2000 ...

1 Department of Physics and Chemistry, Ecole Normale Supérieure of Atakpamé, Atakpamé, Togo. 2 Laboratory of Solar Energy, University of Lomé, Lomé, Togo. 3 Laboratory of Applied Hydrology, National ...

UPS Inc. has outsourced its proprietary weather-forecasting operations, along with moves to offload some tech support and investment office functions, as the company seeks to cut costs and streamline ...

According to Google DeepMind, their experimental deep neural network model leverages decades of historical data and nearly 5,000 observed cyclones to predict a broad range of global weather conditions ...