Collaborative Research: Physics of and Climate Regulation by Convective Aggregation

合作研究：对流聚集的物理学和气候调节

• 批准号: 1906768
• 负责人: Kerry Emanuel
• 金额: $ 56.28万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1906768&HistoricalAwards=false
• 关键词: Collaborative; Research; Physics; Climate; Regulation

Large aggregations of deep, rain-bearing convective clouds are a key element of the weather in the tropics. The simultaneous occurrence of convective clouds over a large region can sometimes be explained in terms of external factors, such as continental heating or surface wind convergence driven by sea surface temperature (SST) contrasts. But perhaps convection can also aggregate spontaneously: not because external factors favor it, but because convection itself creates favorable conditions for additional convection. Such self-aggregation, in which convection begets convection, has been found in idealized simulations of the tropical atmosphere by the PIs and others.In these simulations self-aggregation is typically temperature dependent, increasing with SSTs, and as convection aggregates skies clear and dry in the non-convecting areas. The loss of energy to space by longwave radiation from the clear-sky regions subsequently cools the SSTs, which reduces aggregation and restores the sea surface to its original temperature. This restorative feedback loop could exert a powerful influence on the temperature of the tropics, acting to reduce both the variability of tropical SSTs and the increase in SSTs due to increasing greenhouse gas concentrations.The notion of self-aggregation as a tropical thermostat is intriguing, but so far the effect has been demonstrated and studied primarily in idealized models. Simplifications used in these models include limited geographical domain, uniform SSTs, and periodic lateral boundaries. More work is thus needed to determine if thermal regulation through self-aggregation is a robust effect in the real world. A logical next step in this direction is to look at self-aggregation in more sophisticated models.Under this award the Principal Investigators (PIs) examine the mechanisms of self-aggregation, and its potency for thermal regulation, in a global cloud resolving model called the System for Atmospheric Modeling. The model, developed by one of the PIs, can simulate the forms of convective aggregation seen in satellite images, including hurricanes and the large-scale Madden-Julian Oscillation. The model allows experiments in which various mechanisms thought to be responsible for aggregation are suppressed by direct intervention. For instance the importance of cloud longwave radiative effects can be assessed by averaging the radiative flux between clear and cloudy areas, thereby suppressing longwave radiation as a mechanism for aggregation. The model also includes a sophisticated representation of cloud microphysics, which enables tests of the sensitivity of aggregation to specific cloud properties. One issue to be addressed is the sensitivity of aggregation to the radiative properties of ice crystals near the tops of the clouds.The work is of societal as well as scientific interest given the large and populous portion of the earth that would be affected by the self-aggregation thermostat. A better understanding of convective aggregation could also be beneficial for predicting tropical weather, and results of this work could inform the development of forecast models. One area that could benefit is hurricane prediction, as hurricanes form from tropical cloud clusters, and the prediction of hurricane genesis remains a challenge. In addition, the project provides support and training for two graduate students, thereby providing for the future workforce in this research area.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.

深雨的对流云的大量聚集是热带天气的关键要素。有时可以用外部因素来解释对流云的同时出现对流云，例如大陆加热或由海面温度（SST）对比驱动的表面风收敛。但是，也许对流也可以自发地汇总：不是因为外部因素有利于它，而是因为对流本身为额外的对流创造了有利的条件。这种自我聚集在对流的对流中已经在PIS和其他的对热带气氛的理想化模拟中发现。这些模拟通常取决于温度，随着SST的增加，并且随着对流聚合的天空在非探视区域中清除而干燥。长波辐射从透明的区域降低了空间的能量损失，随后冷却了SST，从而降低了聚集并将海面恢复到其原始温度。这种恢复性反馈回路可能会对热带温度产生强大的影响，从而降低热带SST的变异性和由于温室气体浓度的增加而引起的SST的增加，自我凝聚的概念是热带温度恒温器的概念，但到目前为止，迄今为止，效果已经证明和研究了理想的模型。这些模型中使用的简化包括有限的地理领域，统一的SST和周期性的横向边界。因此，需要更多的工作来确定通过自我聚集的热调节是否是现实世界中的强大效果。朝这个方向迈出的逻辑下一步是在更复杂的模型中查看自我聚集。在该奖项中，主要研究人员（PIS）在一个全球云解决模型中，研究了自我聚集的机制及其热调节的效力，称为大气建模的系统。由其中一个PI开发的模型可以模拟卫星图像中看到的对流聚集形式，包括飓风和大规模的Madden-Julian振荡。该模型允许进行实验，其中各种被认为负责聚集的机制会被直接干预抑制。例如，可以通过平均透明区域和多云区域之间的辐射通量来评估云长波辐射效应的重要性，从而抑制长波辐射作为聚集机制。该模型还包括云微物理学的复杂表示，该表示可以测试聚集对特定云特性的敏感性。要解决的一个问题是聚集对云层顶部附近冰晶的辐射特性的敏感性。鉴于地球上大部分且人口众多的部分将受到自我凝集恒温器的影响，这项工作是社会和科学兴趣。对对流聚集的更好理解也可能有益于预测热带天气，这项工作的结果可能会为预测模型的发展提供信息。可能受益的一个领域是飓风预测，因为热带云集群形成飓风，对飓风创世纪的预测仍然是一个挑战。此外，该项目为两名研究生提供了支持和培训，从而为该研究领域提供了未来的劳动力。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估审查标准来评估的。

项目成果

Tropical Cyclone Seeds, Transition Probabilities, and Genesis

• DOI: 10.1175/jcli-d-21-0922.1
• 发表时间: 2022-06-01
• 期刊: JOURNAL OF CLIMATE
• 影响因子: 4.9
• 作者: Emanuel, Kerry

Slow Modes of the Equatorial Waveguide

• DOI: 10.1175/jas-d-19-0281.1
• 发表时间: 2020-02
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: K. Emanuel

Evolution of Convective Energy and Inhibition before Instances of Large CAPE

大 CAPE 之前的对流能量和抑制的演化

• DOI: 10.1175/mwr-d-21-0302.1
• 发表时间: 2023
• 期刊: Monthly Weather Review
• 影响因子: 3.2
• 作者: Tuckman, Philip;Agard, Vince;Emanuel, Kerry
• 通讯作者: Emanuel, Kerry

A Weak Temperature Gradient Framework to Quantify the Causes of Potential Intensity Variability in the Tropics

用于量化热带地区潜在强度变异原因的弱温度梯度框架

• DOI: 10.1175/jcli-d-21-0139.1
• 发表时间: 2021
• 期刊: Journal of Climate
• 影响因子: 4.9
• 作者: Rousseau-Rizzi, Raphaël;Emanuel, Kerry
• 通讯作者: Emanuel, Kerry