Atmospheric extreme events cause severe damage to human societies and ecosystems.
The frequency and intensity of extremes and other associated events are continuously …

Climate variability and weather phenomena can cause extremes and pose significant risk to
society and ecosystems, making continued advances in our physical understanding of such …

The main challenges of the energy consumption forecasting problem are the concerns for
reliability, stability, efficiency and accuracy of the forecasting methods. The existing …

Recently, the use of machine learning in meteorology has increased greatly. While many
machine learning methods are not new, university classes on machine learning are largely …

Accuracy prediction of air quality is of crucial importance for people to take precautions and
improve environmental conditions. By introducing adjacency matrix in Long Short-Term …

Improvement of compressive strength prediction accuracy for concrete is crucial and is
considered a challenging task to reduce costly experiments and time. Particularly, the …

Reliable subseasonal forecasts of high summer temperatures would be very valuable for
society. Although state-of-the-art numerical weather prediction (NWP) models have become …

Previous studies have identified environmental characteristics that skillfully discriminate
between severe and significant-severe weather events, but they have largely been limited …

A primary goal of the National Oceanic and Atmospheric Administration Warn-on-Forecast
(WoF) project is to provide rapidly updating probabilistic guidance to human forecasters for …

In 2009, advancements in NWP and computing power inspired a vision to advance
hazardous weather warnings from a warn-on-detection to a warn-on-forecast paradigm. This …