Global Surface Air Temperature (GloSAT)
全球表面气温 (GloSAT)
基本信息
- 批准号:NE/S015698/1
- 负责人:
- 金额:$ 43.71万
- 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
- 起止时间:2019 至 无数据
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
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.
地表温度是气候变化最长的仪器记录,也是巴黎气候协定中使用的措施,旨在“防止危险的人为干扰气候系统”。该协定确定了将全球气温变化限制在工业化前水平以上1.5 ℃或2 ℃的目标。政府间气候变化专门委员会(IPCC)使用了1850-1900年的基线来定义“前工业化”,因为这是现有仪器记录开始的时间。据估计,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,这是不确定的。然而,即使使用1850-1900年的基线,现有的温度数据集对迄今为止的变暖量存在分歧,这种分歧意味着仅由于观测到的表面温度变化的不确定性,允许的碳预算超过20%的不确定性,以满足巴黎协定的目标。温度数据集之间的这些差异主要来自两个结构上的不确定性:使用海洋表面温度(SST)而不是海洋上空的气温,特别是冰层覆盖区域,以及数据覆盖范围和插值策略的差异。为了更好地为决策者提供信息,温度变化的记录必须尽可能准确、一致和长久。现有的全球数据集始于1850年或更晚,但我们将把记录再延长70年,追溯到世纪末。目前对这一时期的认识来自欧洲的仪器测量、古代用品(树木年轮、珊瑚或冰芯)和气候模型。我们将大幅扩展这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率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次大火山爆发和额外的数十年气候振荡周期。新的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贡献,并量化人类已经对地球温度的影响,从而对未来气候的影响。一个主要的不一致之处是过去在陆地上使用空气温度,但在海洋上使用SST。最近的进展意味着我们可以产生海洋空气温度记录,以构建第一个海洋,陆地和冰的全球空气温度数据集,可以追溯到18世纪世纪后期。我们的数据集将独立于SST,目前全球温度最不确定的组成部分。我们将改进陆地、海洋和冰冻圈气温观测,使其更加均匀,并将全球记录进一步追溯到过去。这需要基础研究来更好地理解历史观测的偏差和噪声特征,并开发新的误差模型。我们将采用先进的统计技术,即使在观测数据存在差距的情况下,也能估计各地的气温。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,重点关注早期数据,稀疏时期和地区,以及陆地,海洋和冰之间的界面。我们将在最近成功的公民科学倡议的基础上,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,包括气候系统内部产生的变化和火山爆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”,使我们能够更有信心地检测和归因于人为引起的变化。
项目成果
期刊论文数量(10)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Bias correcting climate model simulations using unpaired image-to-image translation networks
- DOI:10.1175/aies-d-22-0031.1
- 发表时间:2023-02
- 期刊:
- 影响因子:0
- 作者:D. J. Fulton;Ben J. Clarke;G. Hegerl
- 通讯作者:D. J. Fulton;Ben J. Clarke;G. Hegerl
West Antarctic Surface Climate Changes Since the Mid-20th Century Driven by Anthropogenic Forcing
20世纪中叶以来人为强迫驱动的南极西部表面气候变化
- DOI:10.1029/2022gl099543
- 发表时间:2022
- 期刊:
- 影响因子:5.2
- 作者:Dalaiden Q
- 通讯作者:Dalaiden Q
Assessing the impact of very large volcanic eruptions on the risk of extreme climate events
- DOI:10.1088/2752-5295/acee9f
- 发表时间:2023-08
- 期刊:
- 影响因子:0
- 作者:N. Freychet;A. Schurer;A. Ballinger;Laura Suarez‐Gutierrez;C. Timmreck
- 通讯作者:N. Freychet;A. Schurer;A. Ballinger;Laura Suarez‐Gutierrez;C. Timmreck
Climate Change Detection and Attribution using observed and simulated Tree-Ring Width
- DOI:10.5194/cp-2021-80
- 发表时间:2021-07
- 期刊:
- 影响因子:4.3
- 作者:J. Franke;M. Evans;A. Schurer;G. Hegerl
- 通讯作者:J. Franke;M. Evans;A. Schurer;G. Hegerl
Constraining human contributions to observed warming since the pre-industrial period
- DOI:10.1038/s41558-020-00965-9
- 发表时间:2021-01-18
- 期刊:
- 影响因子:30.7
- 作者:Gillett, Nathan P.;Kirchmeier-Young, Megan;Ziehn, Tilo
- 通讯作者:Ziehn, Tilo
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Gabriele Hegerl其他文献
Attributing cause and effect
归因于因果关系
- DOI:
10.1038/453296a - 发表时间:
2008-05-14 - 期刊:
- 影响因子:48.500
- 作者:
Francis Zwiers;Gabriele Hegerl - 通讯作者:
Gabriele Hegerl
The past as guide to the future
以过去指引未来
- DOI:
10.1038/33799 - 发表时间:
1998-04-01 - 期刊:
- 影响因子:48.500
- 作者:
Gabriele Hegerl - 通讯作者:
Gabriele Hegerl
Gabriele Hegerl的其他文献
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{{ truncateString('Gabriele Hegerl', 18)}}的其他基金
Securing Multidisciplinary UndeRstanding and Prediction of Hiatus and Surge events (SMURPHS)
确保对间断和激增事件的多学科理解和预测 (SMURPHS)
- 批准号:
NE/N006143/1 - 财政年份:2015
- 资助金额:
$ 43.71万 - 项目类别:
Research Grant
HydrOlogical cYcle Understanding vIa Process-bAsed GlObal Detection, Attribution and prediction (Horyuji PAGODA)
通过基于过程的全球检测、归因和预测了解水文循环(Horyuji PAGODA)
- 批准号:
NE/I006141/1 - 财政年份:2011
- 资助金额:
$ 43.71万 - 项目类别:
Research Grant
Attributing and predicting changes in the probability of climate extremes
归因和预测极端气候概率的变化
- 批准号:
NE/J005363/1 - 财政年份:2011
- 资助金额:
$ 43.71万 - 项目类别:
Research Grant
End-to-end Quantification of Uncertainty for Impacts Prediction (EQUIP)
影响预测不确定性的端到端量化 (EQUIP)
- 批准号:
NE/H003533/1 - 财政年份:2010
- 资助金额:
$ 43.71万 - 项目类别:
Research Grant
Causes of change in European mean and extreme climate over the past 500 years
过去500年欧洲平均和极端气候变化的原因
- 批准号:
NE/G019819/1 - 财政年份:2010
- 资助金额:
$ 43.71万 - 项目类别:
Research Grant
Detection and Attribution of Anthropogenic Changes in Climate Extremes and Variability
极端气候和变率的人为变化的检测和归因
- 批准号:
0634654 - 财政年份:2006
- 资助金额:
$ 43.71万 - 项目类别:
Standard Grant
Detection of Anthropogenic Changes in Climate Extremes
检测极端气候的人为变化
- 批准号:
0296007 - 财政年份:2001
- 资助金额:
$ 43.71万 - 项目类别:
Standard Grant
Detection of Anthropogenic Changes in Climate Extremes
检测极端气候的人为变化
- 批准号:
0002206 - 财政年份:2000
- 资助金额:
$ 43.71万 - 项目类别:
Standard Grant
Fingerprints of Anthropogenic and Natural Climate Variability
人为和自然气候变化的指纹
- 批准号:
0096017 - 财政年份:1999
- 资助金额:
$ 43.71万 - 项目类别:
Standard Grant
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