Cloud System Resolving Modelling of the Tropical Atmosphere

热带地区通常被描述为地球气候系统的发动机室，为大气和海洋的全球循环提供动力。在低纬度地区，太阳光的吸收强烈地加热了陆地和海洋表面，产生对流，将能量从表面带到大气中。除了在沙漠上空，对流产生的深云将从海洋蒸发的水分输送到高层大气。当这些云下雨时，通过冷凝水释放的“潜热”产生进一步的加热，驱动热带天气系统并影响地球仪周围的风。但这种深对流云很少单独存在，它们几乎总是组织成各种结构，从飑线和云团到热带风暴、飓风和超级云团;对流在很宽的时间尺度上变化，从单个云元素（小时）的时间尺度，通过日常周期到过多的波，其周期范围高达季节内振荡，它可以在30-60天内传播到世界各地。因此，热带大气在一个巨大的空间和时间尺度范围内组织自己;对气候系统的影响与随机或无组织的湍流非常不同，因此，如果要准确地再现真实的世界，所有这些尺度都应该在计算机模型中表示。到目前为止，这些影响中的许多都必须通过一个称为参数化的过程以高度简化的方式表示。这试图在比模型中明确表示的尺度更小的尺度上模拟对流的影响。麻烦的是，在从几公里到几百公里的云系中，没有首选的尺度，这些尺度跨越了从“亚网格”（因此需要参数化）到模型所能解决的尺度的范围。即使有了现代超级计算机，在最新的气候模型中，从参数化到解析运动的转变也发生在100公里左右。所有在这个尺度下的真实的世界中出现的结构都被参数化了，所以在被解析的和被参数化的之间出现了一个完全人为的断裂。为了使问题复杂化，参数化假设无法解决的尺度上的组织对于确定对流的性质或其对大尺度流动的影响并不重要。但越来越多的证据表明，这在模型中产生了各种问题。几十年来人们一直致力于对流参数化的研究，但经过了这么多的时间和努力，仍然没有找到完全令人满意的解决方案，因此，我们提出了一种激进但完全合乎逻辑的方法来解决这个问题。现在可以在包含上述所有重要尺度的非常大的区域上运行明确解析对流系统的模型（至少低至1公里左右的尺度）。这种云系解析模型为理解对流如何真正起作用和组织自身，以及如何在气候模型中参数化它提供了一种新的工具。我们的建议将这些模型与来自卫星和地面的新数据联系起来，这将使我们对云和降雨系统的演变有一个前所未有的看法。我们将把这种独特的建模和观测相结合，来研究被认为是天气和气候中最基本的问题之一。这项工作的结果将为开发新一代更准确的大气模型提供信息，这些模型将在气候预测和天气预报中找到工作。

The tropics are often described as the engine room of the Earth's climate system, powering the global circulations of the atmosphere and oceans. Absorption of sunlight heats the land and ocean surfaces strongly at low latitudes, producing convection that carries the energy from the surface into the atmosphere. Except over the deserts, the convection generates deep clouds that transport moisture evaporated from the ocean into the upper atmosphere. When these clouds rain, the release of 'latent heat' by condensing water produces further heating that drives the weather systems of the tropics and influences the winds all around the globe. But such deep convective clouds rarely exist in isolation; they are almost always organised into structures ranging from squall lines and cloud clusters to tropical storms, hurricanes and super-clusters; and convection varies on a wide range of timescales from that of an individual cloud element (hours), through the daily cycle to a plethora of waves with periods ranging up to the intra-seasonal oscillation, which can propagate around the world in 30-60 days. The tropical atmosphere thus organises itself on a huge range of space and timescales; the effect on the climate system is very different from that of random, or disorganised turbulence so that all these scales should be represented in a computer model if it is to reproduce the real world accurately. Until now, many of these effects have had to be represented in a highly simplified way, through a process known as parametrization. This tries to mimic the effect of the convection on the scales smaller than those represented explicitly in the model. The trouble is that across the cloud system from a few to a few hundreds of kilometres there is no preferred scale, and these scales span the range from those that are 'sub-grid' and therefore need parametrization to those which are resolved by the model. Even with the availability of modern supercomputers, this transition from parametrization to resolved motion takes place at around 100km in the latest climate models. All of the structures that occur in the real world below this scale are parametrized, so a completely artificial break occurs between what is resolved and what is parametrized. To compound the problem, the parametrization assumes that organization on scales which cannot be resolved is not important for determining the properties of the convection or its influence on the large-scale flow. But there is mounting evidence that this creates all sorts of problems in the models. Several decades have been invested in developing convection parametrizations and even after all this time and effort no fully satisfactory solution has been found. We therefore propose to take a radical but entirely logical approach to this problem. It is now possible to run models that do resolve convective systems explicitly (at least down to scales of around 1km) over very large domains that encompass all of the important scales mentioned above. Such cloud system resolving models provide a new tool for understanding how convection really works and organises itself, and how it should be parametrized in climate models. Our proposal links these models with new data from satellites and from the surface that will give us an unprecedented view of the evolution of clouds and rain-producing systems. We will bring this unique combination of modelling and observations to bear on what is regarded as one of the most fundamental problems in weather and climate. The results of the work will inform the development of a new generation of more accurate atmospheric models that will find employment in both climate prediction and weather forecasting.