Comparing atmosphere-land surface feedbacks from models within the tropics (CALM)

对环境的人为改变，特别是对地表的改变，对所有生命赖以生存的降雨的分布(在时间和空间上)都产生了很大的影响。从全球大气组成的变化，通过温室气体和气溶胶的排放，到由于人口增长和生态足迹增加而导致的更局部的土地利用和土地覆盖(LULC)变化，人类活动对控制降雨的过程产生了相当大的影响。这对环境脆弱的区域特别重要，例如热带地区的许多区域。在这里，普遍的贫困、广泛的疾病负担和零星的政治不稳定导致对与气候有关的冲击和压力的复原力低，适应能力有限。CAMAL项目的主要目标是：(I)加深我们对第五次气候模型国际比较项目(CMIP5)最新气候模型模拟中热带降雨和地表之间的相互作用的理解；(Ii)这些相互作用与撒哈拉沙漠数千年前发生的气候突变或最近持续的萨赫勒干旱之间的关系。正如最近的气候灾害(如巴基斯坦的洪水、印度的热浪和中国的干旱)所表明的那样，社会特别容易受到与热带降雨有关的极端气候变化的影响。该项目的总体目标是更好地了解目前和未来的热带降雨可变性和相关的控制过程。特别是，最近的工作表明，对于任何可能的突然气候变化，大气-陆地表面反馈将变得越来越重要，因此该项目将重点放在已经发生这种变化的地点的这一过程的模型模拟上。这项研究涉及水循环驱动因素、水循环-人类界面、社会和不断变化的水循环以及陆地表面和次表层水之间的相互作用等相互关联的主题。土地利用(和相关的土地覆盖类型)正在迅速变化，随着越来越多的人口迁移到城市地区，大片土地被砍伐，农业集约化，地下水资源通过灌溉得到越来越多的利用。这些变化通过释放温室气体和气溶胶以及改变从地表到大气的质量和能量流动来影响气候。目前，温室气体和气溶胶浓度变化(由土地利用、土地利用的变化和土地利用变化引起)的气候影响是利用生物地球化学模型、大气成分变化的测量或通过建立由不同的未来社会经济变化驱动的温室气体排放情景来模拟过去和预测未来的。最近的一个项目CMIP5运行了许多最先进的气候模型，使用了各种现在和未来的温室气体排放情景，因此提供了前所未有的大量模拟模型数据。该项目旨在比较所有这些模型的数据，以及观测数据、卫星数据和混合观测卫星数据，以了解降雨和陆地表面之间的相互作用在模型和现实之间有何不同(或一致)。通过遵循基于过程的方法，该项目将使人们能够更好地了解当前和未来的降雨量与周围环境的关系。

Man-made transformations to the environment, and in particular the land surface, are having a large impact on the distribution (in both time and space) of rainfall, upon which all life is reliant. From global changes in the composition of the atmosphere, through the emission of greenhouse gases and aerosols, to more localised land use and land cover (LULC) changes due to an expanding population with an increasing ecological footprint, human activity has a considerable impact on the processes controlling rainfall. This is of particular importance for environmentally vulnerable regions such as many of those in the tropics. Here, widespread poverty, an extensive disease burden and pockets of political instability has resulted in a low resilience and limited adaptative capacity to climate related shocks and stresses. The CALM project has the overarching aims of: (i) furthering our understanding of how the interactions between tropical rainfall and the land surface are represented in the latest climate model simulations from the 5th Climate Modelling Intercomparison Project (CMIP5); and (ii) how these interactions relate to abrupt climate changes such as those which occurred over the Sahara thousands of years ago or, more recently, the prolonged Sahelian drought.As recent climate disasters (such as flooding in Pakistan, heat waves in India and droughts in China) demonstrate, society is particularly vulnerable to extremes related to tropical rainfall. The overall objective of this project is to better understand both present day and future tropical rainfall variability and associated controlling processes. In particular, recent work has suggested that the atmosphere-land surface feedback is going to be increasing important for any possible abrupt climate changes, thus this project will focus on model simulations of this process over a location where such changes have already taken place. The research addresses the interconnected themes of water cycle drivers, the water cycle-human interface, society and the changing water cycle, and interactions between water at the land surface and in the sub-surface. Land use (and related types of land cover) is rapidly changing, as an increasing population migrates to urban areas, large tracts of land are deforested, agriculture is intensified and increasing use is made of groundwater resources through irrigation. These changes influence the climate through the release of greenhouse gases and aerosols and by changing the flows of mass and energy from the surface to the atmosphere. Currently the climate influence of variations in concentrations of greenhouse gases and aerosols (induced by LULC change) is simulated for the past and projected into the future using bio-geochemical modelling, measurements of changes in atmospheric composition, or by building greenhouse gas emission scenarios driven by different future socio-economic changes. A recent project, CMIP5, has run a number of state-of-the-art climate models using various present-day and future emission scenarios of greenhouse gases, and therefore provides an unprecedented amount of simulated model data. This project aims to compare the data from all of these models, as well as observational, satellite-derived and blended observational-satellite data, to see how the interactions between rainfall and the land surface differs (or agrees) between the models and reality. By following a process-based methodology, which is already well established and widely used in other funded projects, the project will enable a better understanding of how present-day and future rainfall is associated with the surrounding environment.