Coupled Model Biases in the Sea Surface Temperature (SST) Distribution of the Global Tropics and their Influence on Climate Change Projections

全球热带海面温度（SST）分布的耦合模型偏差及其对气候变化预测的影响

• 批准号: 1650037
• 负责人: Bradfield Lyon
• 金额: $ 73.88万
• 依托单位: University of Maine
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-15 至 2022-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1650037&HistoricalAwards=false
• 关键词: Coupled; Model; Biases; Sea; Surface

Through their influence on the distribution of tropical rainfall and the atmospheric teleconnections, spatial variations in tropical sea surface temperatures play a major role in shaping regional climates both within, and outside, the tropics. How current sea surface temperature patterns may change under increasing greenhouse gas warming has therefore important implications for regional climate projections around the globe. A fundamental challenge in making such projections, however, is that the latest generation of coupled climate struggles to capture important aspects of the observed distribution of sea surface temperatures, confounding the interpretation of regional climate projections made by such models. The overall goal of the project is to evaluate the influence of coupled model tropical SST biases on regional climate and climate change projections around the globe. Through the use of atmosphere-only model simulations with specified sea surface temperatures, this project will first investigate how systematic biases in coupled model simulations of tropical sea surface temperatures in the current climate impact regional climates around the globe. The PIs will compare the regional climate response to the biases in tropical sea surface temperatures with the regional climate projections made by various coupled climate models to assess to what extent the regional climate projection uncertainties can be directly attributed to the regional climate responses to these biases. To further substantiate the attribution by the atmosphere-only model, they will build a hybrid coupled model with prescribed oceanic fluxes in order to minimize the coupled model biases. The hybrid model will then be used to produce future climate scenarios under increasing greenhouse gas concentrations. The future regional climate projections made by the hybrid model will be evaluated against their counterparts produced by fully coupled models. These two sets of innovative numerical experiments would help to narrow down the regional climate projection uncertainties.In addition to building on our physical understanding of the climate system, key findings from this project will be highly relevant to organizations working on climate change impacts and adaptation. Several of the project collaborators are already engaged with organizations focused on climate change impacts on agriculture and food security. Elements of this project will also be used in the professional development of both current and pre-service high school science teachers across Maine through an established partnership with the University of Maine. Summer workshops run by project collaborators will be held with current earth science teachers to foster the use of project-related climate data in their classrooms. The PIs will do periodic follow-up meetings with these teachers to evaluate the overall effectiveness of the effort.

热带海表温度的空间变化通过其对热带降雨分布和大气遥相关的影响，在形成热带内外的区域气候方面发挥着重要作用。 因此，在温室气体变暖加剧的情况下，目前的海洋表面温度模式可能如何变化，对地球仪的区域气候预测具有重要意义。然而，进行这种预测的一个根本性挑战是，最新一代的耦合气候很难捕捉到观测到的海面温度分布的重要方面，从而混淆了这种模式对区域气候预测的解释。该项目的总体目标是评估耦合模式热带SST偏差对地球仪周围区域气候和气候变化预测的影响。通过使用具有特定海面温度的仅大气模式模拟，该项目将首先研究当前气候中热带海面温度耦合模式模拟的系统偏差如何影响地球仪周围的区域气候。研究项目将把热带海表温度偏差对区域气候的影响与各种耦合气候模式对区域气候的预测进行比较，以评估区域气候预测的不确定性在多大程度上可直接归因于这些偏差对区域气候的影响。 为了进一步证实大气模式的属性，他们将建立一个混合耦合模式，规定海洋通量，以尽量减少耦合模式的偏差。然后，混合模型将用于产生温室气体浓度增加情况下的未来气候情景。混合模式所作的未来区域气候预测将与完全耦合模式所作的预测进行比较。这两套创新的数值实验将有助于缩小区域气候预测的不确定性，除了建立在我们对气候系统的物理理解之外，该项目的关键发现将与从事气候变化影响和适应工作的组织高度相关。 一些项目合作者已经与关注气候变化对农业和粮食安全影响的组织合作。 通过与缅因州大学建立伙伴关系，该项目的内容还将用于缅因州现任和职前高中科学教师的专业发展。由项目合作者举办的暑期讲习班将与当前的地球科学教师一起举办，以促进在课堂上使用与项目相关的气候数据。PI将定期与这些教师进行后续会议，以评估工作的整体成效。

项目成果

Subseasonal convection variability over the Intra‐American Seas simulated by an AGCM and sensitivity to CMIP5 SST biases and projections

AGCM 模拟的美洲内海次季节对流变化以及对 CMIP5 海温偏差和预测的敏感性

• DOI: 10.1002/joc.6475
• 发表时间: 2020
• 期刊: International Journal of Climatology
• 作者: Vigaud, Nicolas;Lyon, Bradfield;Lee, Dong Eun
• 通讯作者: Lee, Dong Eun

Biases in CMIP5 Sea Surface Temperature and the Annual Cycle of East African Rainfall

• DOI: 10.1175/jcli-d-20-0092.1
• 发表时间: 2020-10
• 期刊: Journal of Climate
• 影响因子: 4.9
• 作者: B. Lyon

Dynamical and Thermodynamic Elements of Modeled Climate Change at the East African Margin of Convection

• DOI: 10.1002/2017gl075486
• 发表时间: 2018-01
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: A. Giannini;B. Lyon;R. Seager;N. Vigaud

Spatial Extents of Tropical Droughts During El Niño in Current and Future Climate in Observations, Reanalysis, and CMIP5 Models

观测、再分析和 CMIP5 模型中当前和未来气候中厄尔尼诺现象期间热带干旱的空间范围

• DOI: 10.1029/2021gl093701
• 发表时间: 2021
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Perez Arango, Juan D.;Lintner, Benjamin R.;Carvalho, Leila M. V.;Lyon, Bradfield
• 通讯作者: Lyon, Bradfield

Biases in sea surface temperature and the annual cycle of Greater Horn of Africa rainfall in CMIP6

CMIP6 中海面温度偏差和大非洲之角降雨年周期

• DOI: 10.1002/joc.7456
• 发表时间: 2021
• 期刊: International Journal of Climatology
• 作者: Lyon, Bradfield