IBM announced today that they will be introducing the world’s highest-resolution global weather forecasting model later in 2019--the IBM Global High-Resolution Atmospheric Forecasting System (GRAF). The model will be the first hourly-updating weather model that is able to predict something as small as a thunderstorm virtually anywhere on the planet.

IBM 今天宣布，他们将在2019年晚些时候引入世界上分辨率最高的全球天气预报模型—— IBM 全球高分辨率大气预报系统(GRAF)。 这个模型将是第一个每小时更新一次的天气模型，它能够预测地球上几乎任何地方的雷暴这样小的东西。

The current top global forecasting models, the European (ECMWF) model and the U.S. GFS model, subdivide the global atmosphere into grid boxes that average 9 kilometers and 13 kilometers on a side, respectively, then solve the mathematical equations of atmospheric flow to generate a forecast for each of those grid cells. The new GRAF model employs a variable-resolution grid, resembling a honeycomb, that can be configured with higher resolution over areas of particular interest (Figure 1). Over land areas, the GRAF grid elements will have average resolutions of 3 km, which is about 3 - 4 times greater than the European and GFS models.

目前最流行的全球气象预报模型，欧洲(ECMWF)模型和美国 GFS 模型，将全球大气细分为平均每侧9公里和13公里的网格盒，然后求解大气流动的数学方程，生成每个网格单元的预报。 新的 GRAF 模型使用了一个可变分辨率的网格，类似于蜂窝，可以在特定感兴趣的区域配置更高的分辨率(图1)。 在陆地上，GRAF 网格元素的平均分辨率为3公里，大约是欧洲和 GFS 模型的3-4倍。

Figure 1.  The framework on which GRAF is based enables forecasters to combine a global view of the atmosphere with a higher-resolution view of a particular region, such as North America, with lower resolution over the oceans. This image is from a previous model, MPAS, on which GRAF is based (see below). Image credit: UCAR.

图1 《全球行动计划》所依据的框架使预报员能够将全球大气层观点与北美等特定区域的高分辨率观点结合起来，同时降低对海洋的分辨率。 这张图片来自之前的模型 MPAS，GRAF 就是基于这个模型(见下文)。 图片来源: UCAR

GRAF achieves what has been something of a “holy grail” for global numerical weather forecasting--the ability to run at a resolution so fine that no approximations are needed to simulate how individual thunderstorms behave. Previous global models have always been forced to use what are called “convective parameterization” schemes to approximate what is going on with thunderstorms within each individual grid box, since numerous thunderstorms could be present within the box. These schemes can be a major source of error in weather forecasts. The new GRAF model does not need a convective parameterization scheme when running at 3 km resolution, since the model will permit the existence of individual thunderstorms. In many cases, this will allow the model to make more accurate forecasts in situations where thunderstorms are present.

Graf 实现了全球数值天气预报的某种"圣杯"的东西——能够以非常精细的分辨率运行，不需要近似来模拟单个雷暴的行为。 以前的全球模型总是被迫使用所谓的"对流参量化"方案来模拟在每个单独的网格中雷暴所发生的情况，因为网格中可能存在大量的雷暴。 这些方案可能是天气预报误差的主要来源。 新的 GRAF 模型在3公里的分辨率下运行时不需要对流 / 参量化方案，因为该模型将允许个别雷暴的存在。 在许多情况下，这将允许模型在雷暴存在的情况下做出更准确的预报。

In addition, GRAF runs hourly, compared to the 6-hourly runs available for the GFS model and the 12-hourly runs of the European model (though 6-hourly data from the model is available to some users for forecasts out to 90 hours in the future). NOAA’s High-Resolution Rapid Refresh (HRRR) model does run hourly at 3-kilometer resolution, but only covers the U.S. The new GRAF model will be like the HRRR model, but global in coverage.

此外，GRAF 每小时运行一次，而 GFS 模型每6小时运行一次，欧洲模型每12小时运行一次(尽管模型中每6小时的数据可供一些用户预测未来90小时)。 美国国家海洋和大气管理局(NOAA)的高分辨率快速刷新(HRRR)模型每小时运行一次，分辨率为3公里，但只覆盖美国。 新的 GRAF 模型将类似 HRRR 模型，但覆盖范围是全球性的。

Initially, the highest-resolution version of the GRAF model will run at least 12 hours into the future; a lower-resolution version now being tested extends out as far as 120 hours. Verification data to show the accuracy of the forecasts is not yet available, but we expect it to be later in 2019 once the model becomes operational. In particular, it will be very interesting to see how well the model does with rainfall forecasts for landfalling hurricanes. This is a critically important quantity to get right, as we saw with Hurricane Florence in 2018 and Hurricane Harvey in 2017.

最初，GRAF 模型的最高分辨率版本将在未来至少12小时内运行; 目前正在测试的低分辨率版本将延长至120小时。 目前尚无核实数据显示预测的准确性，但我们预计，一旦该模型投入使用，将在2019年晚些时候进行核实。 特别值得一提的是，这个模型在预测登陆飓风的降雨量方面的表现将会非常有趣。 正如我们在2018年的佛罗伦萨飓风和2017年的哈维飓风中看到的那样，这是一个至关重要的数值。

More specifically, GRAF will be composed of 84 nodes of the IBM Power Systems AC922 server and will use 3.5 petabytes of capacity from the IBM Elastic Storage Server to ensure data is available to keep the model fed. Elastic storage expands as needed to fulfill model demands, which reduces the total amount of storage needed over time.

更具体地说，GRAF 将由 IBM Power Systems AC922服务器的84个节点组成，并将使用 IBM Elastic Storage Server 的3.5 pb 容量来确保数据可用以保持模型的输入。 弹性存储可以根据需要扩展以满足模型需求，从而随着时间的推移减少所需的总存储量。

Unique data sources

独特的数据源

Every weather model requires weather observations to initialize the forecast, and GRAF uses the same system as the GFS to get the initial weather conditions. However, GRAF has the capability to crowdsource additional weather data by using pressure sensor readings sent from barometers found within smartphones, if people opt in to share that information. In addition, hundreds of thousands of pesonal weather stations, many operated by amateur weather enthusiasts, will also be able to contribute data to the model. These additional data sources will require some challenging quality assurance algorithms, and it will be very interesting to see by how much this crowd-sourced data improves forecasts.

每个天气模型都需要天气观测来初始化预报，GRAF 使用与 GFS 相同的系统来获得初始天气状况。 然而，如果人们选择分享这些信息，GRAF 可以通过使用智能手机中气压计发送的压力传感器读数来众包额外的天气数据。 此外，成千上万的夏季气象站(其中许多由业余气象爱好者操作)也将能够为模型提供数据。 这些额外的数据来源将需要一些具有挑战性的质量保证算法，而且这些众包数据在多大程度上改进了预测将是非常有趣的。

A collaboration between IBM and the National Center for Atmospheric Research

IBM 和美国国家大气研究中心的合作

This newest weather prediction system is made possible by The Weather Company’s open-source collaboration with the National Center for Atmospheric Research (NCAR). GRAF incorporates the latest-generation global weather model--the Model for Predictions Across Scales, or MPAS--which was developed by NCAR in conjunction with the Los Alamos National Laboratory. “This is a great example of how long-term basic research funded by the federal government has created an industry opportunity that is both good for the bottom line and protects lives and property,” said Antonio Busalacchi, president of the University Corporation for Atmospheric Research, which manages NCAR on behalf of the National Science Foundation.

这个最新的天气预报系统是由天气公司与美国国家大气研究中心(NCAR)的开源合作完成的。 Graf 整合了最新一代的全球天气模型——跨尺度预测模型，简称 MPAS ——该模型是由 NCAR 和洛斯阿拉莫斯国家实验室气象局共同开发的。 代表国家科学基金会管理 NCAR 的大学大气研究公司(University Corporation for Atmospheric Research)总裁安东尼奥•布萨拉奇(Antonio Busalacchi)表示:"这是一个很好的例子，说明联邦政府资助的长期基础研究如何创造了一个既有利于盈利，又能保护生命和财产的行业机会。"

In summary, the new GRAF model is a promising new addition to the weather forecasting business. What is especially cool is the potential for the model to utilize the power of the Internet to bring in additional high-resolution crowd-sourced data. Anybody with The Weather Channel or Weather Underground app on their smartphone will benefit from the improved forecasts and can help make these forecasts even better by choosing to opt in and share their personal weather station or smartphone weather data.

总而言之，新的 GRAF 模式对于天气预报来说是一个很有前途的新业务。 特别酷的是，该模型有可能利用互联网的力量，带来额外的高分辨率人群来源数据。 任何人只要在智能手机上安装了天气频道或者地下天气预报应用程序，就可以从改进的天气预报中受益，并且可以选择加入并分享他们的个人气象站或者智能手机天气数据，可以帮助做出更好的天气预报。

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