PREDICTING THE CLIMATE OF THE COMING DECADE

预测未来十年的气候

• 批准号: NE/I020792/1
• 负责人: Ed Hawkins
• 金额: $ 57.7万
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI020792%2F1
• 关键词: PREDICTING; CLIMATE; COMING; DECADE

The Earth's climate is changing, and there is strong evidence that humans have caused most of the warming in the past 50 years. Until recently, much of the focus of climate science has been on making more detailed predictions of what might happen over the coming century, and especially on providing information to decision makers on likely impacts of a change in climate. This knowledge has motivated changes in policies to reduce greenhouse gas emissions, i.e. mitigation. However, some additional climate change is inevitable, which will require adaptation, regardless of the mitigation policies pursued. Predicting the climate of the next decade is essential because of the urgent need to adapt to a changing climate. For example, a prediction of low future rainfall in Africa would allow advance planning for potential droughts. A judgment on when to replace railway track might include the risks of a heatwave causing lines to buckle, as happened in the UK in August 2003. The diverse range of applications ensures that predicting the climate of the next decade is a fascinating and engaging challenge, with potentially enormous social and economic benefits. To ensure appropriate choices are made, decision makers need to trust the predictions made by climate scientists. But, according to a recent survey, 40% of the British public think the threat of climate change has been exaggerated. To convince a sceptical public and aid decision making, it is essential to build trust in the sophisticated climate models used to make predictions. Every day, similar supercomputer models are used to make weather forecasts which are later compared to what actually happened. This continual assessment allows the models to be improved, building trust in their predictions and ensuring forecasts are more accurate. This fellowship aims to help build the same trust in the models used to predict climate, especially for the coming decade. However, to make accurate climate predictions for the next decade, it is important to realise that the climate changes for two reasons: (i) factors such as greenhouse gases & solar output, and (ii) natural fluctuations. Such fluctuations can temporarily enhance or reduce any long-term trends, especially on regional scales, producing decades where temperatures are warming rapidly and decades when temperatures are stable or even cooling. For example, one third of future decades are predicted to show decreasing temperatures for the UK, i.e. we expect to see periods of cooling temperatures in a warming climate. Without accounting for these fluctuations, the forecasts would be inaccurate, reducing the trust in climate predictions, and so a new strategy is needed. This proposed research will design an improved system for making predictions by analysing the recent past, for example, by only using data available in 1990 to predict the subsequent decade. By improving predictions of the past we can build trust in predictions of the future. To predict these natural fluctuations, we first need to understand their causes. The answers mainly lie in the oceans, which change relatively slowly compared to the atmosphere. The oceans are the main source of natural decadal fluctuations, due to both their large heat capacity and slow changes in ocean circulation. Predicting how the oceans will change over the next decade is essential to predict climate. However, ocean predictions require ocean measurements, which are tricky and expensive to obtain, especially below the surface. It would be more cost effective to target particular locations, rather than the whole ocean. Another vital aspect of this fellowship is identifying sensitive regions of the oceans, and wider 'Earth system' components, such as sea-ice, where small uncertainties cause forecasts to be inaccurate. This research will improve the design of efficient monitoring systems to reduce uncertainty and ensure improved predictions of the climate of the coming decade.

地球的气候正在变化，有强有力的证据表明，在过去的50年里，人类造成了大部分的变暖。直到最近，气候科学的主要关注点一直是对下个世纪可能发生的事情做出更详细的预测，特别是向决策者提供有关气候变化可能影响的信息。这一知识推动了减少温室气体排放政策的变化，即缓解。然而，一些额外的气候变化是不可避免的，这将需要适应，无论采取何种缓解政策。预测未来十年的气候是至关重要的，因为迫切需要适应不断变化的气候。例如，对非洲未来降雨量较低的预测将允许提前规划潜在的干旱。关于何时更换铁轨的判断可能包括热浪导致铁路线弯曲的风险，就像2003年8月英国发生的那样。应用的多样性确保了预测未来十年的气候是一项引人入胜的挑战，具有潜在的巨大社会和经济效益。为了确保做出适当的选择，决策者需要相信气候科学家的预测。但是，根据最近的一项调查，40%的英国公众认为气候变化的威胁被夸大了。要说服持怀疑态度的公众并帮助决策，关键是要建立对用于预测的复杂气候模型的信任。每天，类似的超级计算机模型都被用来做出天气预报，然后与实际发生的情况进行比较。这种持续的评估使模型得以改进，建立了对其预测的信任，并确保预测更准确。这一奖学金旨在帮助建立对用于预测气候的模型的同样信任，特别是在未来十年。然而，要对未来十年做出准确的气候预测，重要的是要认识到气候变化有两个原因：(I)温室气体和太阳能输出等因素；(Ii)自然波动。这种波动可能会暂时增强或减少任何长期趋势，特别是在区域范围内，导致气温迅速变暖的几十年和温度稳定甚至冷却的几十年。例如，预计未来几十年的三分之一将显示英国气温下降，即我们预计在气候变暖的情况下会出现一段时间的降温。如果不考虑这些波动，预测将是不准确的，降低了人们对气候预测的信任，因此需要一种新的战略。这项拟议的研究将设计一种改进的系统，通过分析最近的过去来进行预测，例如，只使用1990年的数据来预测随后的十年。通过改进对过去的预测，我们可以建立对未来预测的信任。要预测这些自然波动，我们首先需要了解它们的原因。答案主要在于海洋，与大气相比，海洋的变化相对较慢。海洋是自然年代际波动的主要来源，因为海洋的热容量大，海洋环流变化缓慢。预测未来十年海洋将如何变化是预测气候的关键。然而，海洋预测需要海洋测量，而获取海洋测量既棘手又昂贵，尤其是在海平面以下。将目标对准特定的地点，而不是整个海洋，会更具成本效益。这项研究的另一个重要方面是确定海洋的敏感区域，以及更广泛的“地球系统”组成部分，如海冰，在这些区域，微小的不确定性会导致预测不准确。这项研究将改进高效监测系统的设计，以减少不确定性，并确保改进对未来十年气候的预测。

项目成果

An event-based approach to understanding decadal fluctuations in the Atlantic meridional overturning circulation

基于事件的方法来了解大西洋经向翻转环流的年代际波动

• DOI: 10.1007/s00382-014-2271-9
• 发表时间: 2014
• 期刊: Climate Dynamics
• 影响因子: 4.6
• 作者: Allison L

Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures

• DOI: 10.1002/2015gl064888
• 发表时间: 2015-08-16
• 期刊: GEOPHYSICAL RESEARCH LETTERS
• 影响因子: 5.2
• 作者: Cowtan, Kevin;Hausfather, Zeke;Way, Robert G.
• 通讯作者: Way, Robert G.

Decadal Climate Variability and Predictability: Challenges and Opportunities

• DOI: 10.1175/bams-d-16-0286.1
• 发表时间: 2018-03-01
• 期刊: BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
• 影响因子: 8
• 作者: Cassou, Christophe;Kushnir, Yochanan;Caltabiano, Nico
• 通讯作者: Caltabiano, Nico

Plant genetic resources and climate change

植物遗传资源与气候变化

• DOI: 10.1079/9781780641973.0190
• 发表时间: 2014
• 作者: Armstrong S

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

• DOI: 10.5194/esd-4-95-2013
• 发表时间: 2013-01-01
• 期刊: EARTH SYSTEM DYNAMICS
• 影响因子: 7.3
• 作者: Booth, B. B. B.;Bernie, D.;Sexton, D. M. H.
• 通讯作者: Sexton, D. M. H.