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相关概念视频

Global Climate Change01:50

Global Climate Change

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.
What is Climate?01:16

What is Climate?

Climate refers to the prevailing weather conditions in a specific area over an extended period. As the saying goes, “Climate is what you expect. Weather is what you get.” Climate is influenced by geographic factors, such as latitude, terrain, and proximity to bodies of water.
What is Weather?01:07

What is Weather?

Overview
Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
Precipitation Processes01:12

Precipitation Processes

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...
Graphs of Two-Variable Functions01:27

Graphs of Two-Variable Functions

A weather map provides a practical example of a function of two variables. Across a wide region such as the United States, temperatures vary from one location to another. Each location can be identified by two geographic coordinates: longitude and latitude. Since a single temperature value is assigned to each coordinate pair, the situation can be represented mathematically as a function with two inputs and one output.In mathematical notation, longitude and latitude can be labeled as x and y,...

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相关实验视频

Updated: Jul 12, 2026

Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

长期气候预测的双层方法

L Bengtsson, U Schlese, E Roeckner

    Science (New York, N.Y.)
    |August 20, 1993
    PubMed
    概括

    这项研究开发了一种用于长期全球气候预测的合海洋大气模型. 该模型准确地预测了从20世纪70年代到90年代的主要气候事件,显示了与观察结果的良好一致.

    科学领域:

    • 气候科学 气候科学
    • 大气科学 大气科学
    • 海洋学 海洋学 海洋学

    背景情况:

    • 准确的长期气候预测对于理解和减轻全球气候变化至关重要.
    • 现有的模型经常面临着在延长的交付时间内准确预测气候模式的挑战.

    研究的目的:

    • 开发和验证用于长期全球气候预测的新型建模方法.
    • 评估海洋与大气相结合模型在预测重大气候事件方面的能力.

    主要方法:

    • 利用一个用于热带太平洋海面温度 (SST) 预测的预测模型.
    • 采用大气一般循环模型,由预测的SST数据驱动.
    • 通过从1970年至1990年间的七个主要气候事件的后预测来验证模型的性能.

    主要成果:

    • 结合模型成功地预测了热带太平洋海面温度在长时间内.
    • 由SST预测驱动的大气模型模拟显示与观察到的全球气候模式有很好的一致性.
    • 七个主要气候事件的预测证明了该技术在全球各个地区的有效性.

    结论:

    • 结合海洋-大气模拟方法为长期全球气候预测提供了一种可靠的方法.

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    Watershed Planning within a Quantitative Scenario Analysis Framework
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    Watershed Planning within a Quantitative Scenario Analysis Framework

    Published on: July 24, 2016

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    Last Updated: Jul 12, 2026

    Using Generative Art to Convey Past and Future Climate Transitions
    06:10

    Using Generative Art to Convey Past and Future Climate Transitions

    Published on: March 31, 2023

    Watershed Planning within a Quantitative Scenario Analysis Framework
    12:44

    Watershed Planning within a Quantitative Scenario Analysis Framework

    Published on: July 24, 2016

  • 这种技术增强了我们预测气候变化及其影响的能力.
  • 这些发现支持在未来的气候预测和风险评估中使用这种合模型.