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相关概念视频

What is Climate?01:16

What is Climate?

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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.
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Global Climate Change01:50

Global Climate Change

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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.
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What is Weather?01:07

What is Weather?

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Overview
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Precipitation Processes01:12

Precipitation Processes

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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...
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Prediction Intervals01:03

Prediction Intervals

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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. 
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Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

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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...
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Using Generative Art to Convey Past and Future Climate Transitions
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北大西洋的气候远比模型所暗示的更加可预测

D M Smith1, A A Scaife2,3, R Eade2

  • 1Met Office Hadley Centre, Exeter, UK. doug.smith@metoffice.gov.uk.

Nature
|July 31, 2020
PubMed
概括

气候模型低估了北大西洋冬季气候变化的可预测性. 一种新的后处理技术通过更好地估计北大西洋振荡信号来改善十年气候预测.

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科学领域:

  • 气候科学
  • 大气科学
  • 天气学

背景情况:

  • 量化气候信号和不确定性对于气候变化检测,归因,预测和预测至关重要.
  • 虽然大规模的温度信号显示出高度的模型间一致性,但大气循环动态和区域降水预测仍然存在高度不确定性.
  • 气候系统的混乱性可能意味着不可减少的信号不确定性,使气候预测的验证变得复杂.

研究的目的:

  • 评估过去60年的气候模型预测.
  • 研究北大西洋冬季气候十年变化的可预测性.
  • 解决当前气候模型中北大西洋振荡信号的低估问题.

主要方法:

  • 对60年的气候模型预测进行了回顾性分析.
  • 评估北大西洋振荡 (NAO) 的可预测信号.
  • 实施两阶段后处理技术:差异调整和组合成员选择.

主要成果:

  • 北大西洋冬季气候的十年变化是高度可预测的,尽管模型之间的分歧和原始模型输出预测很差.
  • 目前的气候模型低估了可预测的NAO信号,
  • 后处理技术显著改善了欧洲和北美冬季气候和大西洋多十年变化的十年预测.

结论:

  • 这项研究强调了当前气候模型中关于NAO的信号噪声比率的严重低估.
  • 开发的后处理方法提高了十年气候预测的准确性.
  • 纠正信号与噪声比的模型错误可以减少十年后区域气候变化预测的不确定性.