We review how machine learning has transformed our ability to model the Earth
system, and how we expect recent breakthroughs to benefit end-users in
Switzerland in the near future.

机器学习在模拟地球系统方面的应用及其对瑞士终端用户的未来帮助的评论。

下一代地球系统模型：可靠的混合模型用于天气和气候应用

Next-Generation Earth System Models: Towards Reliable Hybrid Models for  Weather and Climate Applications

Recent advances in Computer Vision and Deep Learning have enabled astonishing
results in a variety of fields and applications. Motivated by this success, the
SkyCam Dataset aims to enable image-based Deep Learning solutions for
short-term, precise prediction of solar radiation on a local level. For the
span of a year, three different cameras in three topographically different
locations in Switzerland are acquiring images of the sky every 10 seconds.
Thirteen high resolution images with different exposure times are captured and
used to create an additional HDR image. The images are paired with highly
precise irradiance values gathered from a high-accuracy pyranometer.

利用计算机视觉和深度学习的技术，通过 SkyCam 数据集对瑞士三个不同地形位置的天空进行短期精准预测，旨在实现基于图像的深度学习解决方案并精确预测太阳辐射。