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从2022年1月25日起，ECMWF 在全球范围内的大量预测数据将公开提供。这种向“开放数据”的转变是在大范围的预测图表被提供给任何对它们感兴趣的人之后发生的。
正在获得的数据基于一系列高分辨率预报(HRES-9公里水平分辨率)和总体预报(ENS-18公里水平分辨率)。它们的分辨率为0.4 x 0.4度。
虽然许多编程语言可以用来访问和可视化数据，ECMWF 已经准备了一套 Jupyter 笔记本，以帮助熟悉 Python 和 Jupyter 的用户发现开放的数据集。他们也可以使用我们的开源软件图书馆从我们的开放预报图表中复制图表。
在 ECMWF 网站上提供了一个关于哪些类型的数据可用的概述。更详细的说明如何访问数据也可以。该计划是在未来通过增加更多的数据来扩展开放数据。
这些数据可以通过 ECMWF 的 https 服务和微软 Azure 云服务获得。将来，它们也可能通过其他云供应商提供。
这些数据的使用受到欧洲知识共享管理委员会的 CC-4.0-BY 许可证和 ECMWF 使用条款的管理。这意味着这些数据可能会被重新分配，并在商业上使用，但要有适当的归属。
对于需要更高分辨率和更齐全ecmwf预报数据的可以私信小编（gavin7675），有相关公司提供合法付费渠道接口。具体如下：
From 25 January 2022, a wide range of ECMWF’s forecast data across the globe will be openly available. This move towards ‘open data’ comes after a large range of forecast charts were earlier made available to anybody interested in them.
The data that are becoming available are based on a range of high-resolution forecasts (HRES – 9 km horizontal resolution) and ensemble forecasts (ENS – 18 km horizontal resolution). They will be made accessible at a resolution of 0.4 x 0.4 degrees.
While many programming languages can be used to access and visualise the data, ECMWF has prepared a set of Jupyter notebooks to help users familiar with Python and Jupyter discover the open dataset. They can also reproduce the plots from our open forecast charts using our open-source software libraries.
An overview of what kinds of data are available is given on the ECMWF website. More detailed explanations of how to access the data are also available. The plan is to expand open data in the future by adding more data.
The data are available through ECMWF’s https service and via the Microsoft Azure cloud. In future, they may also be made available via other cloud providers.
Use of the data is governed by the Creative Commons CC-4.0-BY licence and the ECMWF Terms of Use. This means that the data may be redistributed and used commercially, subject to appropriate attribution.
Jupyter notebooks for reproducing open chart plots using open data can be accessed via the top right-hand menu of the available plots.
ECMWF looks forward to user feedback, which will help the open data provision to evolve.
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