Improving S2S forecasts would significantly impact downstream applications such as streamflow forecasting, heatwave prediction, water resource management, and in-season climate-aware crop modeling on the sub-seasonal time scale. In this project, we propose to use a set of machine learning methods to...
Recent advances in machine learning (ML)-based weather prediction (MLWP) have been shown to provide greater accuracy and efficiency than NWP for non-probabilistic forecasts2,3,13,14,15,16,17,18. Rather than forecasting a single weather trajectory, or a distribution of trajectories, these methods...
MACHINE learningWEATHER forecastingDATA miningRANDOM forest algorithmsEMERGENCY managementAccurate weather forecasting is crucial for numerous sectors, including agriculture, disaster management, and daily life. This study leverages advanced data mining techniques to analyze and predict weather...
BEIJING, March 9 (Xinhua) -- A global team of researchers has made strides in refining weather forecasting methods using machine learning. Scientists have been looking for better ways to make weather forecasts more accurate. Despite the maturity of ensemble numerical weather prediction (NWP), the ...
MACHINE learningFORECASTINGSpace weather indices are used to drive forecasts of thermosphere density, which directly affects objects in low‐Earth orbit (LEO)... JD Daniell,PM Mehta - 《Space Weather the International Journal of Research & Applications》 被引量: 0发表: 2024年 Forecasting Excessive ...
Whether for leisure pursuits or outdoor business, reliable rain alerts can greatly impact people’s behavior and businesses’ ability to adapt to inclement weather. Weather forecasting is a highly variable practice though, subject to capricious forces that can change at a moment’s notice. Traditiona...
There are also reasons for caution. 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 r...
Deep learning is the primary technology behind driverless cars, face recognition, and voice control; it teaches computers to learn by example. This comes naturally to humans of course, as we learn from a young age how to classify tasks, recognize various patterns, and so on. Computers don’t...
Automatic weather stations are essential for fine-grained weather forecasting; they can be built almost anywhere around the world and are much cheaper than radars and satellites. However, these scattered stations only provide partial observations governe
Over the past few years, the rapid development of machine learning (ML) models for weather forecasting has led to state-of-the-art ML models that have superior performance compared to the European Centre for Medium-Range Weather Forecasts (ECMWF)’s high-resolution forecast (HRES), which is ...