使用3D神经网络准确的中距离全球天气预报
Kaifeng Bi1, Lingxi Xie1, Hengheng Zhang1
1Huawei Cloud, Shenzhen, China.
Nature
|July 5, 2023
概括
人工智能现在提供准确的中期全球天气预报. 作为人工智能模型的Pangu-Weather在准确性和速度上优于传统的数值天气预测系统.
科学领域:
- 天气学
- 人工智能
- 计算科学
背景情况:
- 数字天气预报 (NWP) 是准确天气预报的当前标准,但在计算上是密集的.
- 人工智能 (AI) 方法有望加速天气预报,但目前缺乏NWP的准确性.
- 准确的中期全球天气预报仍然是一个重大的科学和社会挑战.
研究的目的:
- 引入基于人工智能的方法,用于准确的中期全球天气预报.
- 展示深度学习模型的有效性与地球特定的天气预测先验.
- 使用层次时间聚合策略减少中期预测中的累积错误.
主要方法:
- 开发了Pangu-Weather,一个使用3D深度网络的深度学习模型.
- 实施了层次时间聚合策略,以减轻错误的累积.
- 在39年的全球天气数据中训练模型.
主要成果:
- 与欧洲中期天气预报中心 (ECMWF) 运营综合预报系统相比,Pangu-Weather取得了更好的确定性预报结果.
- 在所有测试变量中,人工智能模型在中期预测方面表现出强的表现.
- 在极端天气预报,集体预报和热带气旋跟踪方面,Pangu-Weather也表现出有效性.
结论:
- 基于人工智能的方法,特别是Pangu-Weather,可以实现高度准确的中期全球天气预报.
- 对于复杂的天气模式分析,具有地球特异性的深度网络和层次性的时间聚合是有效的.
- 这种人工智能方法提供了传统NWP系统的计算效率和准确性替代方案.
相关概念视频
01:07What is Weather?
18.4K
Overview
18.4K
01:26Errors in Global Positioning System
74
Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
74
01:03Prediction Intervals
2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.3K
01:20Maxwell-Boltzmann Distribution: Problem Solving
1.6K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.6K
01:50Global Climate Change
24.5K
Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
24.5K
01:12Precipitation Processes
492
The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
492