Weather forecasting has traditionally been done by physical models of the atmosphere, which are unstable to perturbations, and thus are inaccurate for large periods of time. Since machine learning techniques are more robust to perturbations, in this paper we explore their application to weather forecasting to potentially generate more accurate weather forecasts for large periods of time. The sc...

The results presented in this paper are part of a research project to investigate the possibilities to apply massively parallel architectures for numerical weather forecasting. Within numerical weather forecasting several numerical techniques are used to solve the model equations. This paper compares the performance of implementations on a MasPar system of two techniques, nite di erence and spe...

We analyze the impacts of adopting advanced weather forecasting systems at different levels of the decision-making hierarchy of the power grid. Using case studies, we show that state-of-the-art numerical weather prediction (NWP) models can provide high-precision forecasts and uncertainty information that can significantly enhance the performance of planning, scheduling, energy management, and f...

North part of Japan is one of the heaviest snowfall regions in winter. In a certain case, wet snow accretes to civil engineering structure such as power lines. There is a demand for the prediction that when the snow accretion will occur. General weather forecast is not enough resolution and meteorological variable for estimating snow accretion. By calculating weather condition on our own accoun...

A multiphysics and a stochastic kinetic-energy backscatter scheme are employed to represent model uncertainty in a mesoscale ensemble prediction system using the Weather Research and Forecasting model. Both model-error schemes lead to significant improvements over the control ensemble system that is simply a downscaled global ensemble forecast with the same physics for each ensemble member. The...

Forecasting space weather events presents the ultimate challenge to a space physics model. Not only should physical constraints be satisfied, but also practical issues such as timeliness, accuracy, and reliability must be adequately addressed. To address these needs, modern space weather forecasters and users rely on a great variety of space weather models, ranging from simple regressions and e...