Convective-Scale Impacts of Deforestation on Amazonian Rainfall

亚马逊雨林占世界上所有现存热带雨林的40%，但自20世纪60年代以来，森林砍伐迅速，到2050年，巴西亚马逊雨林将被砍伐多达40%。土地利用变化是气候变化的一个重要人为驱动因素。我们知道，森林砍伐通常会使大气变得更温暖、更干燥，但这些变化将如何影响降雨则更为复杂。气候模型大多预测，森林砍伐会减少降雨量，但在不同的研究中，降雨量从0%到60%不等。气候模型使用的栅格为10到100公里，比典型的云要大得多。虽然云的性质可以从网格框中的条件估计，但计算降雨量是非常不确定的，特别是在热带地区。一种解决方案是运行一个网格框小得多的模型，但专注于一个小区域，这样在亚马逊地区发现的云和详细的森林砍伐模式就可以明确地表示出来。这些研究表明，地表模式改变了当地的天气模式，增加了森林被砍伐地区的降雨量，这与气候模型相矛盾。然而，由于这些研究集中在较小的区域，我们不知道这些局部影响是否对整个亚马逊的水循环很重要。该项目将结合这两种方法，利用现有的增强计算能力，首次模拟整个亚马逊盆地，同时也明确地表示云。这是一个至关重要的改进，因为过去的研究表明，对云的解析会导致模型行为的完全改变，极大地改善了热带降雨的表现方式，包括对当地人口影响最大的洪水和干旱等极端气候。我们将使用这些模拟来研究日益增加的森林砍伐将如何影响亚马逊地区的降雨，以及这些变化与由二氧化碳水平增加引起的全球气候变化造成的变化相比如何。该项目特别令人兴奋，因为它将提供对森林砍伐如何影响降雨的全面了解，模拟区域气候和当地天气模式的变化，这些变化直接影响到人们。热带降雨是气候模拟研究的一个关键领域，因为尽管它是最终用户最重要的气候参数，但它也是最不确定的。例如，降雨驱动农业和水力发电等许多经济部门，虽然砍伐森林被用来为农业清理土地，但降雨量的减少可能会降低每公顷的产量，从而抵消增加农业面积所带来的任何经济收益。森林砍伐的模式也会影响降雨的地点，这可以帮助规划者找到减轻对剩余森林的一些负面影响的方法。该项目将通过研讨会与该地区的利益相关者合作，以有针对性的方式提高我们对物理的理解，以应对与许多人直接相关的全球挑战。

The Amazon rainforest contains 40% of all remaining tropical rainforest in the world, but has seen rapid deforestation since the 1960s, and as much as 40% of the Brazilian Amazon could be deforested by 2050. Land-use change is an important man-made driver of climate change. We know that deforestation will generally make the atmosphere both warmer and drier, but how these changes will affect rainfall is more complex. Climate models mostly predict that deforestation will reduce rainfall, but the amount varies from 0 to 60% across different studies. Climate models use grid boxes of 10s to 100s km, which are much larger than a typical cloud. While cloud properties can be estimated from the conditions in the grid box, calculating the amount of rainfall is very uncertain, especially in the tropics. One solution is to run a model with much smaller grid boxes, but focusing on a small region, so that clouds and the detailed deforestation patterns found in the Amazon can be represented explicitly. These studies show that the surface patterns alter local weather patterns, increasing rainfall over the deforested patches, which contradicts climate models. However, because these studies focus on smaller regions, we do not know if these local effects are important for the water cycle of the entire Amazon.This project will combine both approaches, using the increased computing power now available to simulate, for the first time, the entire Amazon basin while also explicitly representing clouds. This is a crucial improvement, because past studies have shown that resolving clouds leads to a complete change in model behaviour, greatly improving how tropical rainfall is represented, including climate extremes like flooding and droughts which have the most impact on local populations. We will use these simulations to investigate how increasing deforestation will affect rainfall over the Amazon, and how these changes compare to those caused by global climate change driven by increasing carbon dioxide levels. The project is particularly exciting because it will provide a comprehensive understanding of how deforestation affects rainfall, simulating both changes in regional climate and the local weather patterns within it which directly affect people. Tropical rainfall is a key area of research in climate modelling, because although it is the most important climatic parameter to end users, it is also the most uncertain. For example rainfall drives a number of economic sectors such as agriculture and hydroelectric power, and while deforestation is used to clear land for agriculture, reductions in rainfall could reduce the yield per hectare, negating any economic gain from increasing the agricultural area. Patterns of deforestation can also affect where it rains, which could help planners identify ways to mitigate some of the negative effects on the remaining forest. This project will engage with stakeholders in the region through workshops to improve our physical understanding in a targeted way to address global challenges which have direct relevance to many people.