Improving Estimates of Anthropogenic Aerosol Cooling and Climate Sensitivity

改进对人为气溶胶冷却和气候敏感性的估计

基本信息

  • 批准号:
    1622295
  • 负责人:
  • 金额:
    $ 44.82万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-11-01 至 2020-10-31
  • 项目状态:
    已结题

项目摘要

It is generally accepted that the warming effect of greenhouse gas increases over the 20th century was to some extent offset by cooling from aerosol pollution, and the extent of the cancellation is a central question in the detection and attribution of climate change. The observed temperature record could represent strong greenhouse warming masked by substantial aerosol cooling or weaker warming offset by less cooling. The two alternatives have very different consequences for future warming if greenhouse gases continue to accumulate while aerosols level off or decline.Earlier work by the PI and others has attempted to separate out the aerosol cooling (essentially a shading effect) using the fact that the surface temperature response to aerosols has a distinct spatial pattern, and sophisticated "optimal fingerprinting" techniques have been devised to identify that pattern in simulations of 20th century climate. Work in this project extends the methodology by combining surface temperature with other variables to help characterize the aerosol effect. Two variables that show promise in combination with temperature are precipitation and surface insolation (direct and indirect sunlight). The patterns are identified in climate model simulations using various 20th century climate forcing factors including all forcings combined, aerosols alone, and all forcings except aerosols. Additional work seeks to apply the method to observations, taking into account characteristics of observing networks including the geographic distribution of the stations and their periods of record.The work has broader impacts because better estimates of 20th century aerosol cooling will be helpful to derive observational constraints on climate sensitivity, which is the most important factor determining the severity of the long-term societal risk posed by global warming. Such guidance would directly benefit policy makers addressing climate change impacts, and would also be valuable for climate model development. The work also provides an assessment of the value of particular types of observations (for instance precipitation and insolation) for constraining aerosol cooling, and these estimates could be valuable for prioritizing investments in new observational infrastructure.
人们普遍认为,20世纪温室气体增加的变暖效应在一定程度上被气溶胶污染的降温所抵消,而这种抵消的程度是气候变化探测和归因中的一个核心问题。观测到的温度记录可能代表了被大量气溶胶冷却所掩盖的强烈温室变暖,或者是被较少的冷却所抵消的较弱的变暖。如果温室气体继续积累,而气溶胶趋于稳定或下降,这两种选择对未来的变暖将产生截然不同的后果。PI和其他人的早期工作试图分离出气溶胶冷却(本质上是一种遮阳效应),利用表面温度对气溶胶的响应具有明显的空间模式这一事实,并设计了复杂的“最佳指纹”技术来识别20世纪气候模拟中的这种模式。本项目的工作扩展了方法,将地表温度与其他变量相结合,以帮助表征气溶胶效应。降水和地表日晒(直接和间接阳光)是与温度相结合的两个变量。利用各种20世纪气候强迫因子,包括所有强迫组合、气溶胶单独和除气溶胶以外的所有强迫,在气候模式模拟中确定了这些模式。另外的工作是将该方法应用于观测,同时考虑到观测网的特点,包括台站的地理分布及其记录期间。这项工作具有更广泛的影响,因为对20世纪气溶胶冷却的更好估计将有助于得出气候敏感性的观测约束,而气候敏感性是决定全球变暖造成的长期社会风险严重程度的最重要因素。这种指导将直接有利于应对气候变化影响的政策制定者,对气候模型的开发也很有价值。这项工作还对特定类型的观测(例如降水和日照)在限制气溶胶冷却方面的价值进行了评估,这些估计对于优先投资新的观测基础设施可能很有价值。

项目成果

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Timothy Delsole其他文献

Timothy Delsole的其他文献

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{{ truncateString('Timothy Delsole', 18)}}的其他基金

Collaborative Research: Physics-Based Machine Learning for Sub-Seasonal Climate Forecasting
合作研究:基于物理的机器学习用于次季节气候预测
  • 批准号:
    1934529
  • 财政年份:
    2019
  • 资助金额:
    $ 44.82万
  • 项目类别:
    Continuing Grant
Advancing Sub-Seasonal Weather Predictability Through Machine Learning Techniques
通过机器学习技术提高次季节天气预报的可预测性
  • 批准号:
    1822221
  • 财政年份:
    2018
  • 资助金额:
    $ 44.82万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: Learning Relations between Extreme Weather Events and Planet-Wide Environmental Trends
EAGER:合作研究:学习极端天气事件与全球环境趋势之间的关系
  • 批准号:
    1451945
  • 财政年份:
    2014
  • 资助金额:
    $ 44.82万
  • 项目类别:
    Standard Grant

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