Collaborative Research: Physics of and Climate Regulation by Convective Aggregation

大量深厚的、带雨的对流云团是热带天气的一个关键因素。大范围同时发生对流云的原因有时可以用外部因素来解释，如大陆加热或由海表面温度(SST)反差驱动的地面风辐合。但也许对流也可以自发聚集：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。在PIS和其他人对热带大气的理想化模拟中，已经发现了这种对流引起对流的自聚集。在这些模拟中，自聚集通常与温度有关，随着海温的增加而增加，并且随着对流聚集在非对流区晴朗干燥的天空。来自晴空区域的长波辐射导致的能量损失随后冷却了SST，从而减少了聚集，使海面恢复到原来的温度。这种恢复性反馈环路可以对热带地区的温度产生强大的影响，降低热带海温的可变性和由于温室气体浓度增加而导致的海温增加。自聚集作为热带恒温器的概念是有趣的，但到目前为止，这种效应主要是在理想化的模式中演示和研究的。这些模型中使用的简化包括有限的地理区域、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温度调节在现实世界中是否是一种稳健的效应。在这个方向的下一个合乎逻辑的步骤是在更复杂的模型中观察自聚集。在这个奖项下，首席调查人员(PI)在一个名为大气建模系统的全球云解析模型中检查自聚集的机制及其对热调节的效力。该模式由其中一个PI开发，可以模拟卫星图像中看到的对流聚集形式，包括飓风和大范围的马登-朱利安振荡。该模型允许进行实验，在这些实验中，被认为是聚集的各种机制被直接干预抑制。例如，云的长波辐射效应的重要性可以通过平均晴天和多云地区之间的辐射通量来评估，从而抑制作为聚集机制的长波辐射。该模型还包括云微物理的复杂表示，这使得能够测试聚集对特定云属性的敏感性。一个需要解决的问题是聚集对云顶附近冰晶辐射特性的敏感性。鉴于地球上大部分人口将受到自聚集恒温器的影响，这项工作具有社会和科学意义。更好地了解对流聚集也有助于预报热带天气，这项工作的结果可以为预报模式的发展提供信息。一个可能受益的领域是飓风预测，因为飓风是由热带云团形成的，而飓风起源的预测仍然是一个挑战。此外，该项目为两名研究生提供支持和培训，从而为这一研究领域的未来劳动力提供支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.