The factors governing daily near-surface air temperature variability over land

控制陆地近地表气温每日变化的因素

• 批准号: 1939988
• 负责人: Karen McKinnon
• 金额: $ 61.99万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1939988&HistoricalAwards=false
• 关键词: factors; governing; daily; near; surface

Hot and and cold extremes of surface air temperature have a clear association with atmospheric circulation patterns, for instance the coldest temperatures over the continental US are associated with the southward flow of air behind the polar front while summer heat waves are associated with stalled high pressure systems. But while the influence of atmospheric circulation is evident from weather maps, the underlying land surface can also affect the severity of hot and cold events. For instance the maximum surface air temperature during a heat wave could be lower due to evaporative cooling if the soil is wet, thus soil moisture could play an important role in limiting the magnitude of temperature fluctuations. Other surface properties including snow cover, reflectivity, and surface roughness are thought to influence surface air temperature variability, but the extent of the influence of these properties is difficult to quantify.This project examines the effects of atmospheric circulation and land surface properties on surface air temperature variability, seeking to determine 1) the fraction of temperature variability that can be explained by the large-scale atmospheric circulation alone, and how this varies as a function of location and season; 2) the key pathways through which the land surface can influence surface air temperature after controlling for the large-scale atmospheric circulation; and 3) the extent to which the land surface can modify the magnitude of extreme events, and may allow for subseasonal to seasonal predictability. The PIs use statistical methods to generate best-fit surface air temperature patterns based solely on the atmospheric circulation aloft, then compare the statistics of these circulation-derived temperature patterns to the actual temperature statistics to identify regions and seasons where differences in the two imply a strong role for surface properties. This observational analysis is followed by numerical experiments with a hierarchy of models to understand the physical mechanisms through which the land surface affects temperature variations. The model hierarchy includes the Community Atmosphere Model (CAM) coupled to the Simple Land Interface Model (SLIM), a land surface model configured to allows direct control of important land surface properties. Results of sensitivity studies carried out with CAM-SLIM and other model configurations are applied to the analysis of recent heat waves in North America, Europe, and Australia.Temperature extremes have numerous effects on human well being through impacts such as mortality, crop losses, and infrastructure failure. Better understanding of the role played by land surface properties in determining the severity of these extremes could prove useful in anticipating their occurrence, and the extent to which their frequency and intensity may be affected by climate change. The work will also benefit the broader scientific community through the development and dissemination of SLIM, which will be made available as part of a public release of the Community Earth System Model. The project also includes education and outreach through the Significant Opportunities in Atmospheric Research and Science (SOARS) program, and supports a graduate student and a postdoctoral research associate.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

地表气温的冷热极值与大气环流模式有着明显的联系，例如美国大陆上空的最冷温度与极地锋后的南向气流有关，而夏季热浪则与停滞的高压系统有关。 但是，虽然大气环流的影响在天气图上很明显，但下垫面也会影响冷热事件的严重程度。例如，如果土壤是湿的，则由于蒸发冷却，热浪期间的最高表面空气温度可能会较低，因此土壤湿度可以在限制温度波动的幅度方面发挥重要作用。 其他地表特性包括积雪、反射率和地表粗糙度被认为会影响地表气温变率，但这些特性的影响程度很难量化。本项目研究大气环流和地表特性对地表气温变率的影响，试图确定1）可以单独由大尺度大气环流解释的温度变化的比例，以及它如何作为位置和季节的函数而变化; 2）在控制大尺度大气环流后，陆地表面影响地表气温的主要途径; 3）陆地表面改变极端事件的程度，并可能允许亚季节到季节的可预测性。PI使用统计方法仅基于高空大气环流来生成最佳拟合的地面空气温度模式，然后将这些源自环流的温度模式的统计数据与实际温度统计数据进行比较，以确定两者差异对表面特性具有重要作用的区域和季节。 这种观测分析之后是一个层次模型的数值实验，以了解陆面影响温度变化的物理机制。 模型层次结构包括与简单陆地界面模型（SLIM）耦合的社区大气模型（CAM），简单陆地界面模型（SLIM）是一种陆地表面模型，配置为允许直接控制重要的陆地表面属性。 CAM-SLIM和其他模式配置进行的敏感性研究的结果被应用到最近在北美，欧洲和澳大利亚的热浪分析。极端温度对人类健康有许多影响，如死亡率，作物损失和基础设施故障。更好地了解陆地表面特性在确定这些极端事件的严重程度方面所起的作用，可能有助于预测其发生情况，以及其频率和强度受气候变化影响的程度。 这项工作还将通过SLIM的开发和传播使更广泛的科学界受益，SLIM将作为社区地球系统模型公开发布的一部分提供。 该项目还包括通过大气研究与科学重大机会（SOARS）计划进行教育和推广，并支持一名研究生和一名博士后研究助理。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Hot extremes have become drier in the United States Southwest

• DOI: 10.1038/s41558-021-01076-9
• 发表时间: 2021-06
• 期刊: Nature Climate Change
• 影响因子: 30.7
• 作者: K. McKinnon;A. Poppick;I. Simpson

Improvements in Wintertime Surface Temperature Variability in the Community Earth System Model Version 2 (CESM2) Related to the Representation of Snow Density

社区地球系统模型版本 2 (CESM2) 中与雪密度表示相关的冬季地表温度变化的改进

• DOI: 10.1029/2021ms002880
• 发表时间: 2022
• 期刊: Journal of Advances in Modeling Earth Systems
• 影响因子: 6.8
• 作者: Simpson, Isla R.;Lawrence, David M.;Swenson, Sean C.;Hannay, Cecile;McKinnon, Karen A.;Truesdale, John E.
• 通讯作者: Truesdale, John E.

Understanding responses of summer continental daily temperature variance to perturbations in the land surface evaporative resistance

了解夏季大陆日气温变化对地表蒸发阻力扰动的响应

• DOI: 10.1175/jcli-d-21-1011.1
• 发表时间: 2022
• 期刊: Journal of Climate
• 影响因子: 4.9
• 作者: Kong, Wenwen;McKinnon, Karen A.;Simpson, Isla R.;Laguë, Marysa M.
• 通讯作者: Laguë, Marysa M.

Circulation and Soil Moisture Contributions to Heatwaves in the United States

• DOI: 10.1175/jcli-d-21-0156.1
• 发表时间: 2022-12-15
• 期刊: JOURNAL OF CLIMATE
• 影响因子: 4.9
• 作者: Horowitz, Russell L.;McKinnon, Karen A.;Simpson, Isla R.
• 通讯作者: Simpson, Isla R.

How Unexpected Was the 2021 Pacific Northwest Heatwave?

• DOI: 10.1029/2022gl100380
• 发表时间: 2022-09-28
• 期刊: GEOPHYSICAL RESEARCH LETTERS
• 影响因子: 5.2
• 作者: McKinnon, Karen A.;Simpson, Isla R.
• 通讯作者: Simpson, Isla R.