Numerical models that combine weather forecasting and atmospheric chemistry are here
referred to as chemical weather forecasting models. Eighteen operational chemical weather …

We developed a solar flare prediction model using a deep neural network (DNN) named
Deep Flare Net (DeFN). This model can calculate the probability of flares occurring in the …

Empirical rainfall thresholds are tools to forecast the possible occurrence of rainfall-induced
shallow landslides. Accurate prediction of landslide occurrence requires reliable thresholds …

This article describes a software suite that can be used for objective evaluation of tropical
cyclones (TCs) in gridded climate data. Using cyclone trajectories derived from 6-hourly …

Atmospheric rivers (ARs) are global phenomena that transport water vapor horizontally and
are associated with hydrological extremes. In this study, the Atmospheric River Skill …

A six‐year climatology of radiation fog has been compiled at two sites: the Research Centre
for the Lower Atmosphere (CIBA, Spain) and the Cabauw Experimental Site for Atmospheric …

Satellite-based rainfall estimates are a good and cost-effective alternative to low-density rain
gauges because they provide information for these areas. In this study, the accuracy of …

We developed an operational solar flare prediction model using deep neural networks,
named Deep Flare Net (DeFN). DeFN can issue probabilistic forecasts of solar flares in two …

Models in the North American Multi-Model Ensemble (NMME) predict sea surface
temperature (SST) trends in the central and eastern equatorial Pacific Ocean which are …

In recent years, it has been found that the Precipitable Water Vapor (PWV) time series
derived from ground-based GPS measurements can be used in to forecast precipitation in …