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Global Surface Air Temperature (GloSAT)

Global Surface Air Temperature (GloSAT)
全球表面气温 (GloSAT)
批准号:
NE/S015566/1
负责人:
Kevin Cowtan
金额:
$32.01万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2019
资助国家:
英国
项目状态:
未结题
起止时间:
2019 至 --

项目摘要

项目成果

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中文摘要
翻译
地表温度是气候变化最长的仪器记录,也是《巴黎气候协议》中用来衡量气候变化的指标,该协议旨在防止对气候系统造成危险的人为干扰。该协议定义了将全球气温变化限制在比工业化前水平高1.5摄氏度或2摄氏度的雄心。政府间气候变化专门委员会(IPCC)使用1850-1900年的基线来定义“前工业化”,因为这是现有工具记录开始的时候。据估计,到目前为止,全球气温可能已经上升了0.0-0.2摄氏度,但由于缺乏数据,这一数字还不确定。然而,即使使用1850-1900年的基线,现有的温度数据集也不同意迄今为止的升温幅度,这种分歧意味着,仅由于观测到的地表温度变化的不确定性,满足《巴黎协定》目标的允许碳预算存在20%以上的不确定性。温度数据集之间的这些差异主要是由于两个结构上的不确定性:使用海洋表面温度而不是海洋,特别是冰盖区域的气温,以及数据覆盖范围和内插策略的差异。为了给决策者提供最好的信息,温度变化的记录必须尽可能准确、一致且尽可能长。现有的全球数据集开始于1850年或更晚,但我们将把这一记录再延长70年,追溯到18世纪末。目前关于这一时期的知识来自欧洲的仪器测量、古指标(树轮、珊瑚或冰芯)和气候模型。我们将极大地扩大这70年期间早期测量记录的空间覆盖范围,这对于了解自然气候变异性和气候对不同辐射强迫的响应非常重要。例如,较长的记录包括5次大火山喷发和额外的数十年气候振荡周期。这一新记录将使我们能够更好地理清人为和自然因素对气候系统的影响,并量化人类已经对地球温度产生的影响,从而对未来气候产生影响。一个主要的不一致是过去陆地上使用的气温,而海洋上使用的是SST。最近的进展意味着我们可以制作一个海洋气温记录,以构建第一个可以追溯到18世纪末的海洋、陆地和冰上的全球气温数据集。我们的数据集将独立于SST,SST是目前全球气温最不确定的组成部分。我们将改进陆地、海洋和冰冻圈的气温观测,使它们更加均匀,并将全球记录进一步向前延伸。这需要进行基础研究,以更好地了解历史观测的偏差和噪声特征,并开发新的误差模型。我们将采用复杂的统计技术,即使在观测数据有差距的情况下,也可以估计各地的气温。我们将通过新的航海日志和气象站数字化来扩展历史气候记录,重点放在早期数据、稀疏时段和地区以及陆地、海洋和冰之间的界面上。我们将在最近成功的公民科学活动的基础上,让公众参与数字化工作。我们将分析新的地表气温记录,以更好地了解自18世纪末以来气温的变化。这一较长的记录将使人们更好地了解自然气候变化,既有气候系统内部产生的变化,也有火山喷发和太阳变化等外部强迫因素造成的变化。这种对自然变异性的更好的理解将使我们能够更清楚地分离出人为气候变化的特征“指纹”,从而使我们能够更自信地检测到人类诱导的变化并将其归因于
英文摘要
Surface temperature is the longest instrumental record of climate change and the measure used in the Paris Climate Agreement that aims to 'prevent dangerous anthropogenic interference with the climate system'. The Agreement defines an ambition to limit global temperature change to 1.5C or 2C above pre-industrial levels. The Intergovernmental Panel on Climate Change (IPCC) used a baseline of 1850-1900 for its definition of 'pre-industrial' as this is when existing instrumental records begin. It has been estimated that global temperatures may have already increased by 0.0-0.2C by this time, but this is uncertain due to lack of data. However, even using the 1850-1900 baseline, existing temperature datasets disagree on the amount of warming to date and this disagreement implies more than 20% uncertainty in the allowed carbon budget to meet the goals of the Paris Agreement solely due to uncertainty in observed surface temperature change. These differences between temperature datasets arise mostly from two structural uncertainties: the use of sea surface temperatures (SST) rather than air temperatures over the oceans, especially ice-covered regions, and differences in data coverage and interpolation strategies. This project addresses both.To best inform decision-makers, records of temperature change must be as accurate, consistent, and long as possible. Existing global datasets start in 1850 or later, but we will extend the record a further 70 years back to the late 18th century. Current knowledge of this period comes from instrumental measurements in Europe, palaeo-proxies (tree-rings, corals or ice cores), and climate models. We will dramatically extend the spatial coverage of the early measured record in this 70-year period, which is important for understanding natural climate variability and the climate response to different radiative forcings. For example, the longer record includes the period of 5 large volcanic eruptions and extra cycles of multi-decadal climate oscillations. The new record will allow us to better disentangle the contributions of anthropogenic and natural factors on the climate system and quantify the effect humans have already had on Earth's temperature, and hence on future climate.A major inconsistency has been past use of air temperature over land but SST over oceans. Recent advances mean we can produce a marine air temperature record to construct the first global air temperature dataset over ocean, land and ice, stretching back to the late 18th century. Our dataset will be independent from SST, currently the most uncertain component of global temperature. We will improve land, marine and cryosphere air temperature observations to make them more homogeneous and extend the global record further back in time. This requires fundamental research to better understand the bias and noise characteristics of historical observations and develop new error models. We will adopt sophisticated statistical techniques to allow the estimation of air temperature everywhere, even when there are gaps in the observations. We will expand the historical climate record with new ship's logbook and weather station digitisations focused on early data, sparse periods and regions, and the interfaces between land, ocean and ice. We will engage the public in the digitisation effort building on recent successful citizen science initiatives.We will analyse the new surface air temperature record to better understand how temperatures have changed since the late 18th century. This longer record will give a better understanding of natural climate variations, both variability generated internally within the climate system and that due to external forcing factors such as volcanic eruptions and solar changes. This improved understanding of natural variability will enable us to more cleanly isolate the characteristic "fingerprints" of man-made climate change allowing us to more confidently detect and attribute human-induced changes
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A macromolecular structure building toolkit for machine learning and cloud applications
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  • 项目类别:
    Research Grant
  • 资助金额:
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  • 财政年份:
    2023
  • 负责人:
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Flexible-body refinement for Cryogenic Electron Microscopy Applications
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  • 项目类别:
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CCP4 Advanced integrated approaches to macromolecular structure determination
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  • 项目类别:
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  • 财政年份:
    2019
  • 负责人:
    Kevin Cowtan
  • 依托单位:
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  • 批准号:
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  • 项目类别:
    Research Grant
  • 资助金额:
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  • 财政年份:
    2019
  • 负责人:
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国内基金
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
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    2021
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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  • 负责人:
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  • 依托单位:
基于surface hopping方法探索有机半导体中激子解体机制
  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 负责人:
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  • 依托单位:
基于强自旋轨道耦合纳米线自旋量子比特的Surface code量子计算实验研究
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  • 项目类别:
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