Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Observational Learning01:12

Observational Learning

311
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
311
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

581
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
581
Deconvolution01:20

Deconvolution

251
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
251
Precipitation Processes01:12

Precipitation Processes

584
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...
584
Force Classification01:22

Force Classification

1.6K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.6K
Electrostatic Boundary Conditions01:16

Electrostatic Boundary Conditions

603
Consider an external electric field propagating through a homogeneous medium. When the electric field crosses the surface boundary of the medium, it undergoes a discontinuity. The electric field can be resolved into normal and tangential components. The amount by which the field changes at any boundary is given by the difference between the field components above and below the surface boundary.
The surface integral of an electric field is given by Gauss's law in integral form and is related to...
603

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Rossby wave-modulated orbital precipitation anomalies in the Asia-Pacific region.

Nature communications·2026
Same author

Oceanic mesoscale eddies enhance the Pacific Decadal Oscillation and its predictability.

Science advances·2026
Same author

Distinct impacts of tropical North Atlantic warming flavors on cross-basin tropical cyclone activity.

Science advances·2026
Same author

Tropical basin interactions reduce spring predictability barrier of ENSO in a deep learning model.

Science advances·2026
Same author

Upper-ocean stratification changes control ENSO amplitude shift under sustained global warming.

Nature communications·2026
Same author

Amazon deforestation weakens Atlantic Niño variability.

Nature communications·2026

相关实验视频

Updated: Sep 10, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

635

使用基于观察的深度学习来预测ENSO.

Yuchao Zhu1,2, Rong-Hua Zhang3, Fan Wang4,5

  • 1Key Laboratory of Ocean Observation and Forecasting & Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.

Nature communications
|August 19, 2025
PubMed
概括

使用人工神经网络 (ANN) 进行深度学习,可显著降低厄尔尼诺-南方振荡 (ENSO) 海面温度预测的不确定性54%. 该方法将气候模型模拟与观测数据相结合,以改善气候预测.

更多相关视频

Surface Mapping of Earth-like Exoplanets using Single Point Light Curves
06:48

Surface Mapping of Earth-like Exoplanets using Single Point Light Curves

Published on: May 10, 2020

3.6K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.1K

相关实验视频

Last Updated: Sep 10, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

635
Surface Mapping of Earth-like Exoplanets using Single Point Light Curves
06:48

Surface Mapping of Earth-like Exoplanets using Single Point Light Curves

Published on: May 10, 2020

3.6K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.1K

科学领域:

  • 气候科学 气候科学
  • 机器学习应用 机器学习应用
  • 海洋学 海洋学 海洋学

背景情况:

  • 厄尔尼诺-南方振荡 (ENSO) 显著影响全球气候模式.
  • 现有的气候模型在预测未来的ENSO海面温度 (SST) 变化方面表现出相当大的不确定性和模型间的差异.
  • 气候模型和ENSO物理学的观测之间的差异阻碍了准确的未来预测.

研究的目的:

  • 为了减少21世纪ENSO SST变化预测的不确定性.
  • 利用观测数据开发一种限制气候模型预测的方法.
  • 调查深度学习在改善气候模型准确性方面的作用.

主要方法:

  • 利用深度学习,特别是人工神经网络 (ANN),在气候模型模拟和观测数据上进行训练.
  • 采用可解释性分析来了解ANN如何捕捉ENSO物理.
  • 应用模型作为真相的方法来验证ANN生成的预测.
  • 基于ANN推断的ENSO对热带太平洋变暖的反应,基于未来的ENSO SST变化预测.

主要成果:

  • 在高排放场景下,深度学习将ENSO SST变化预测的不确定性降低了54%.
  • ANNs成功地复制了观察到的ENSO反应,确定了热带太平洋的关键变暖模式.
  • 该研究将预计的ENSO SST变化范围从0.59°C缩小到0.27°C.
  • 可解释性证实,复制观察到的ENSO物理是减少不确定性的关键.

结论:

  • 整合机器学习与观测数据提供了一个有希望的方法来减少气候预测中的不确定性.
  • 开发的深度学习方法为改进未来ENSO预测提供了强大的约束.
  • 对ENSO物理学的准确表示对于可靠的气候变化预测至关重要.