ECMWF未来10年的机器学习计划研讨会

研讨会简介

机器学习能够从数据中学习复杂非线性的行为，这对数值天气预报和气候服务工作流程中的许多应用领域都非常有用。此次研讨会中，我将介绍ECMWF探索机器学习的最新动向，尤其是深度学习。我将介绍机器学习路线图，包括确定相应的挑战、提供潜在的解决方案，并定义步骤以引导相应的科学和技术项目，通过协调努力研究机器学习天气和气候预测。此路线图将有助于在未来几年充分利用机器学习进行天气和气候预测。

机器学习是ECMWF2021-30年间新战略中非常重要的部分。我们的目标是混合最佳的数据驱动方法和当前已有预报系统中物理理解，即耦合数据驱动和物理驱动方法，提供更好的天气和气候预测。

参加条件

此研讨会免费开放，无需注册。参与链接后面会发布在此研讨会页面。如果你想收到邮件提醒，请在2021年1月22日之前完善“Register your interest”表格。

时间：10:00 GMT | 26 January 2021

以下是通知原文

Seminar overview

Machine learning allows to learn complex, non-linear behaviour from data which is useful for many application areas across the workflow of numerical weather prediction and climate services. In this talk, I will provide an update on the activities at ECMWF to explore the potential of machine learning, and in particular deep learning. I will introduce the machine learning roadmap that identifies challenges, provides potential solutions, and defines steps to channel the many distributed science and technology projects that study machine learning for weather and climate prediction into a coordinated effort. The roadmap will help to make the most of machine learning for weather and climate predictions in the years to come.

Machine learning is an important part of ECMWF’s new Strategy 2021–30. The idea is to combine the best of what data-driven approaches can provide with the strengths and physical understanding encapsulated in our existing forecasting systems.

Attendance

This seminar is open to all and does not require pre-registration. The joining link will be published on this seminar web page. If you would like to receive an email to remind you about the seminar, please complete the "Register your interest" form before 22 January 2021.