Studies in the Climate Dynamics of Moist Process Variability and Change

潮湿过程变率和变化的气候动力学研究

• 批准号: 1936810
• 负责人: J David Neelin
• 金额: $ 111.26万
• 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: 2020-03-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1936810&HistoricalAwards=false
• 关键词: Studies; Climate; Dynamics; Moist; Process

Simulations of climate change show increases in the frequency of occurrence of extreme precipitation as temperature rises, in general agreement with observations. Increases in extremes are to be expected given that warmer air typically contains more moisture. But the moisture-temperature relationship does not by itself provide a theory to predict increases in the frequency and severity of extreme precipitation in a warming climate. Moreover, a satisfactory theoretical framework would address changes in the frequency of occurrence of precipitation events of all magnitudes, from weak to moderate to unprecedented.Work under this award seeks to develop such a theoretical framework by treating convective precipitation as a random process and applying the tools of statistical mechanics (the emphasis on convective precipitation is reasonable given that convective clouds are the source of most intense precipitation). The goal is to understand how the probability of occurrence of convective precipitation events of a given magnitude or intensity, referred to as the probability distribution, depends on temperature, moisture, and other environmental factors. Earlier work by the PI and others shows initiation and rapid intensification in convective precipitation as atmospheric moisture increases beyond a temperature-dependent threshold, a sort of threshold value of bulk column relative humidity. Research supported here extends earlier results by incorporating considerations of thermodynamic energy, atmospheric stability, and the probability distribution of the column moisture responsible for threshold behavior in precipitation. One novelty of the work is the use of collocated data from the Global Precipitation Mission and Radio Occultation receivers on the COSMIC and COSMIC-2 satellites to explore the high moisture/heavy precipitation regime. Additional work uses these ideas to develop representations of convective precipitation for use in models of the interaction of precipitation and atmospheric circulation. Results of the research are used to evaluate simulations from state-of-the-art climate models, attempting to connect extreme precipitation behaviors in present-day simulations to future increases. If robust connections can be found the present-day simulations can be evaluated against relevant observations, and the success of models in reproducing observed connections can be used as a benchmark to assess the validity of their simulations of the response to anthropogenic forcing.The project has societal relevance due to the connection between warming temperatures and increases in extreme event frequency and severity. Concerns over increasing damage from extreme precipitation have prompted considerable effort in generating and analyzing future climate simulations from global climate models and higher resolution regional models. But results of this "brute force" approach come with substantial uncertainty regarding the degree, geographical distribution, and other characteristics of the increases. A solid theoretical framework would thus be quite valuable in guiding the effort and interpreting its results. This project makes a direct connection between the development of new theory and its application to the analysis of climate model behaviors, thereby establishing an immediate connection to the larger enterprise of climate change impacts assessment. In addition, the project provides support and training for a graduate student, and results of the work are used to develop classroom teaching materials.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.

对气候变化的模拟显示，随着气温的上升，极端降水发生的频率增加，这与观测结果基本一致。 考虑到温暖的空气通常含有更多的水分，预计极端情况会增加。 但是，湿度-温度关系本身并不能提供一个理论来预测在气候变暖的情况下极端降水的频率和严重程度的增加。 此外，一个令人满意的理论框架将处理所有量级降水事件发生频率的变化，从弱到中等到前所未有。该奖项的工作旨在通过将对流降水视为随机过程并应用统计力学工具来发展这样一个理论框架（由于对流云是最强降水的来源，因此强调对流降水是合理的）。 目标是了解给定量级或强度的对流降水事件发生的概率（称为概率分布）如何取决于温度、湿度和其他环境因素。 PI和其他人的早期工作表明，当大气湿度增加超过与温度相关的阈值（一种体积柱相对湿度的阈值）时，对流降水开始并迅速加强。这里支持的研究扩展了早期的结果，结合考虑热力学能量，大气稳定性，和概率分布的柱水分负责阈值行为的降水。 这项工作的一个新奇是利用来自全球降水使命和COSMIC-2卫星上无线电掩星接收器的同位数据来探索高湿度/强降水状况。 额外的工作使用这些想法来开发对流降水的表示，用于降水和大气环流的相互作用的模型。研究结果用于评估最先进的气候模型的模拟，试图将当前模拟中的极端降水行为与未来的增加联系起来。 如果可以找到强有力的连接，目前的模拟可以评估相关的观测，和模型在再现观测到的连接的成功可以被用来作为基准，以评估其模拟的响应的有效性人为forcing.The项目的社会相关性，由于变暖的温度和极端事件的频率和严重程度的增加之间的连接。对极端降水造成的日益严重的破坏的担忧促使人们在全球气候模式和更高分辨率的区域模式中产生和分析未来气候模拟方面做出了相当大的努力。 但是，这种“蛮力”方法的结果在增加的程度、地理分布和其他特征方面具有很大的不确定性。 因此，一个坚实的理论框架对于指导这一努力和解释其结果是非常有价值的。 该项目将新理论的发展与其在气候模型行为分析中的应用直接联系起来，从而与气候变化影响评估的更大企业建立直接联系。 此外，该项目还为一名研究生提供支持和培训，并将工作成果用于开发课堂教学材料。该奖项反映了NSF的法定使命，并通过使用基金会的智力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

Tropical Thermodynamic–Convection Coupling in Observations and Reanalyses

观测和再分析中的热带热力学对流耦合

• DOI: 10.1175/jas-d-21-0256.1
• 发表时间: 2022
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: Wolding, Brandon;Powell, Scott W.;Ahmed, Fiaz;Dias, Juliana;Gehne, Maria;Kiladis, George;Neelin, J. David
• 通讯作者: Neelin, J. David

The ARM Data-Oriented Metrics and Diagnostics Package for Climate Models: A New Tool for Evaluating Climate Models with Field Data

ARM 面向数据的气候模型指标和诊断包：使用现场数据评估气候模型的新工具

• DOI: 10.1175/bams-d-19-0282.1
• 发表时间: 2020
• 期刊: Bulletin of the American Meteorological Society
• 影响因子: 8
• 作者: Zhang, C.;Xie, S.;Tao, C.;Tang, S.;Emmenegger, T.;Neelin, J. D.;Schiro, K. A.;Lin, W.;Shaheen, Z.
• 通讯作者: Shaheen, Z.

How Close Are Leading Tropical Tropospheric Temperature Perturbations to Those under Convective Quasi Equilibrium?

主要热带对流层温度扰动与对流准平衡状态下的温度扰动有多接近？

• DOI: 10.1175/jas-d-21-0315.1
• 发表时间: 2022
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: Li, Yi-Xian;Neelin, J. David;Kuo, Yi-Hung;Hsu, Huang-Hsiung;Yu, Jia-Yuh
• 通讯作者: Yu, Jia-Yuh

Extreme Tropical Precipitation Clusters Show Strong Increases in Frequency Under Global Warming in CMIP6 Models

• DOI: 10.1029/2021gl096037
• 发表时间: 2022-02-16
• 期刊: GEOPHYSICAL RESEARCH LETTERS
• 影响因子: 5.2
• 作者: Dulguerov, Leilani;Ahmed, Fiaz;Neelin, J. David
• 通讯作者: Neelin, J. David

Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): organization and experimental design

• DOI: 10.5194/gmd-14-4465-2021
• 发表时间: 2021-07
• 期刊: Geoscientific Model Development
• 影响因子: 5.1
• 作者: Y. Xue;T. Yao;A. Boone;I. Diallo;Ye Liu;X. Zeng;W. Lau;S. Sugimoto;Q. Tang;Xiaoduo Pan;P. J. Oevelen;D. Klocke;Myung‐Seo Koo;Zhaohui Lin;Y. Takaya;Tomonori Sato;C. Ardilouze;S. Saha;Mei Zhao;Xin‐Zhong Liang;F. Vitart;Xin Li;P. Zhao;D. Neelin;W. Guo;Miao Yu;Y. Qian;S. Shen;Yang Zhang;Kun Yang;R. Leung;Jing Yang;Yuan Qiu;M. Brunke;S. Chou;M. Ek;T. Fan;H. Guan;Hai Lin;S. Liang;S. Materia;Tetsu Nakamura;Xin Qi;Retish Senan;C. Shi;Hailan Wang;Helin Wei;S. Xie;Haoran Xu;Hongliang Zhang;Yanling Zhan;Weiping Li;Xueli Shi;P. Nobre;Yi Qin;J. Dozier;C. Ferguson;G. Balsamo;Q. Bao;Jinming Feng;Jinkyu Hong;Songyoul Hong;Huilin Huang;D. Ji;Zhenming Ji;Shi-chang Kang;Yanluan Lin;Weiguang Liu;R. Muncaster;Yan Pan;D. Peano;P. Rosnay;Hiroshi G. Takahashi;Jianping Tang;G. Wang;Shuyu Wang;Weicai Wang;Xu Zhou;Yuejian Zhu