The effect of 3D radiative transfer on climate

日常天气的常见经验表明，云层的存在或不存在对地表温度有深远的影响，因为云层阻挡了白天来自太阳的入射辐射，并捕获了夜间地表发射的热红外辐射。在更长的时间尺度上也是如此，因此，如果我们要预测下个世纪地表平均温度的变化，气候系统的计算机模型能够准确地表示云与辐射相互作用的方式是至关重要的。此外，云层会随着全球变暖而变化，这反过来又会影响它们与辐射的相互作用，而这种“反馈”是气候预测不确定性的最大原因之一。看一眼明亮的白色积云就会告诉你，太阳辐射可以从云层的一侧反射出来，所以如果了解到目前所有的气候模型都只允许辐射通过云顶和云底进入或离开，可能会令人惊讶。这种简化可能会导致模型中的云场只拦截现实中传入的太阳辐射的一半，这可能会导致地表温度的巨大误差，这可能会反馈到天气和气候。热红外辐射也存在很大的偏差。要准确计算辐射如何与复杂的云场相互作用，通常需要昂贵的蒙特卡罗计算，即模拟数百万个单独光子的路径。然而，PI最近设计了一种新的方法来计算通过大气的辐射传输，其中包括通过云端的辐射通量，但比蒙特卡洛快许多个数量级。因此，它适合在气候模式中实施。在该项目中，将全面开发新方法，并在英国气象局气候模型中实施，该模型在英国国内广泛使用，也是政府间气候变化专门委员会(IPCC)使用的模型之一。高分辨率卫星图像将被用来描述云的结构，为我们的方法提供必要的信息。我们将严格测试新方法，对照完整的蒙特卡罗计算，然后进行全局计算，以确定当前估计的云与辐射相互作用程度的误差大小。然后我们将进行气候模拟，以确定这对全球变暖的影响有多大。我们将探索我们的新方法的其他应用。例如，人们对飞机尾迹与太阳和红外辐射相互作用造成的气候影响感到关切，特别是考虑到预计未来十年航空旅行将迅速增加。在最近的一篇论文中，PI表明，由于忽略了进入和离开轨道一侧的辐射，目前关于辐射与轨道相互作用方式的计算存在很大误差。在这个项目中，我们将使用我们的新代码来更准确地计算轨迹对辐射的全球影响，这将是航空业和政策制定者感兴趣的。我们对气象局气候模型的更改将在未来用于气候和天气预报，并可用于NERC社区内的气候研究。

Common experience with the day-to-day weather reveals that the presence or absence of clouds has a profound impact on surface temperature, by the way clouds block the incoming radiation from the sun during the day and trap thermal infrared radiation emitted by the surface at night. This is no less true on much longer timescales, and so it is crucial if we are to predict changes to average surface temperatures over the next century that computer models of the climate system are able to accurately represent the way clouds interact with radiation. Moreover, clouds can change in response to global warming, which in turn affects their interaction with radiation, and this 'feedback' is one of the largest causes of uncertainty in climate predictions. A glance at a brilliant white cumulus cloud will tell you that solar radiation can be reflected off the side of the cloud, so it may be surprising to learn that all current climate models only allow radiation to enter or leave through the cloud top and base. This simplification can lead to a field of clouds in the model intercepting only half the incoming solar radiation as in reality, potentially resulting in large errors in surface temperature that could feed back on weather and climate. Substantial biases are also present for thermal infrared radiation. To calculate accurately how radiation interacts with a complex cloud field normally requires expensive 'Monte Carlo' calculations, where the path of millions of individual photons are simulated. However, the PI has recently devised a new method to calculate the transfer of radiation through the atmosphere that includes the flux of radiation through cloud sides, but is many orders of magnitude faster than Monte Carlo. Hence it is suitable for implementing within a climate model. In this project the new method will be developed fully and implemented in the Met Office climate model, which is widely used within the UK, as well as being one of the models used by the Intergovernmental Panel on Climate Change (IPCC). High resolution satellite images will be used to characterise the structure of clouds to provide the necessary information for our method. We will test the new method rigorously against full Monte Carlo calculations and then perform global calculations to determine the size of the error in current estimates of how much clouds interact with radiation. Then we will perform climate simulations to determine how much this affects global warming. We will explore other applications of our new method. For example, there is concern over the climate effect of aircraft contrails via their interaction with solar and infrared radiation, particularly given the rapid increase in air travel that is projected over the next decade. In a recent paper, the PI has shown that there are large errors in current calculations of the way radiation interacts with contrails because the radiation entering and leaving the side of the contrail is neglected. In this project we will use our new code to make much more accurate calculations of the global effect of contrails on radiation, which will be of interest to the airline industry and policy makers. Our changes to the Met Office climate model will be available for both climate and weather forecasting in the future, as well as being available for climate research within the NERC community.