QUEST Deglaciation: Climate and

在过去的两万年里，地球的气候已经从一个完整的冰河时代转变为一个温暖的时期。在冰河时期，欧洲和北美有大片的冰盖，海洋很冷，冬季有大面积的海冰，大陆很冷，通常很干燥，世界各地的森林大大减少，气候保持寒冷是因为二氧化碳和其他“温室气体”的浓度很低，空气中有大量的灰尘。最后一个冰河时代的气候也是不稳定的，不时会出现持续数十年至数百年的大幅降温和突然变暖;冰河时代之后的变暖突然被持续一千年的寒冷时期打断。从那时起，气候变得更加温暖和稳定，但气候、植被和大气层仍然发生了变化。例如，在工业革命开始的二氧化碳浓度急剧上升之前的大约8000年里，二氧化碳浓度缓慢上升。一些气候变化是戏剧性的，如撒哈拉沙漠的形成。这些事实已经得到了很好的证实，但要理解它们背后的机制仍然是对科学的挑战。气候变化的原因，以及工业化前温室气体和灰尘的变化（这反过来又影响气候），还没有得到充分的理解。唯一已知的外部原因是地球轨道的变化，它逐渐改变了在不同纬度和季节接收到的太阳能量的数量。地球显然以一种非常复杂的方式对这种变化做出反应，有时甚至是突然的。特别是大气层的变化，提供了一个线索，表明气候变化不仅仅是一个物理问题;它们还涉及“地球化学循环”的变化，即大气、海洋和陆地之间碳和其他元素的交换，这些交换受到生物体的调节。了解这些过程尤其重要，因为人类活动正在改变大气和气候，我们需要能够预测长期后果。“反向”预测是测试我们使用的模型的一种方法。该项目的目的是更全面地了解从最后一个冰河时代高峰期到近代这段时期是什么驱动了气候、大气成分和地球化学循环的变化。我们将联合收割机两种工作方式结合起来，这两种方式通常是分开的。一方面，我们将试图预测过去。我们将使用具有额外功能的计算机气候模型，包括可以预测湿地，沙漠和森林火灾变化的动态全球植被模型。这将使我们能够模拟影响气候的许多重要物质的陆地-大气交换，例如二氧化碳，甲烷，挥发性碳氢化合物，灰尘和烟灰。我们将使用这些模型的版本，这些模型非常有效，因为它们只模拟大规模模式。通过这种方式，我们可以比通常做更多和更长的模拟。另一方面，我们将利用现有的数据库和新的数据分析方法，对来自世界各地沉积物岩心的数据进行一次重要的综合，包括花粉计数（过去植被的一个指标）、木炭计数（过去火灾的一个指标）和碳同位素测量。这项工作将首次提供从最后一个冰河时代到近代地球陆地表面状况的连续图像。我们将评估气候模型的工作情况，并深入了解植被变化如何与气候和大气成分相互作用，通过将这种重建与我们的计算机生成的地球“虚拟历史”进行详细比较。

During the past twenty thousand years the Earth's climate has changed from a full ice age to a warm period. During ice ages there are large ice sheets in Europe and North America, the oceans are cold with large areas of sea-ice in winter, the continents are cold and generally dry, forests worldwide are much reduced, and the climate is kept cold by very low concentrations of carbon dioxide and other 'greenhouse gases' and by enormous amounts of dust in the air. The climate of the last ice age was also unstable, punctuated by large coolings and sudden warmings lasting tens to hundreds of years; and the warming after the ice age was suddenly interrupted by a cold period lasting a thousand years. The climate has been warmer and rather more stable since then, but there have still been changes in climate, vegetation and the atmosphere. For example, there was a slow rise in carbon dioxide concentration during some eight thousand years before the dramatic rise that began with the Industrial Revolution. Some climate changes were dramatic, like the formation of the Sahara desert. These facts are well established, but to understand the mechanisms behind them is still a challenge to science. The causes of changes in climate, and of pre-industrial changes in greenhouse gases and dust (which in turn affect the climate), are not fully understood. The only known external cause is the variation of the Earth's orbit, which gradually alters the amount of the Sun's energy received at different latitudes and seasons. The Earth apparently responds to this variation in a very complex way, and sometimes abruptly. The changes in the atmosphere, especially, give a clue that climate changes are not just a matter of physics; they also involve changes in 'biogeochemical cycles' / the exchanges of carbon and other elements between the atmosphere, ocean and land, which are regulated by living organisms. Understanding these processes is particularly important because human activities are now changing the atmosphere and climate, and we need to be able to predict the long-term consequences. Making predictions 'in reverse' is one way to test the models we use. The aim of this project is a fuller understanding of what has driven changes in climate, atmospheric composition and biogeochemical cycles during the period from the peak of the last ice age until recent times. We will combine two ways of working, which have usually been separate. On the one hand, we will try to predict the past. We will use computer climate models with extra features, including a dynamic global vegetation model that can predict changes in wetlands, deserts and forest fires. This will enable us to us simulate the land-atmosphere exchanges of many important substances that affect climate, such as carbon dioxide, methane, volatile hydrocarbons, dust and soot. We will use versions of these models which are very efficient because they only simulate large-scale patterns. In this way we can do many more and longer simulations than is usually done. On the other hand, we will use existing data bases and new data-analysis methods to make a major synthesis of the data from sediment cores around the world, including pollen counts (an indicator of past vegetation), charcoal counts (an indicator of past fires) and carbon isotope measurements. This work will provide, for the first time, a continuous picture of the state of the Earth's land surface from the last ice age up to recent times. We will assess how well the climate models are working, and get insights into how the vegetation changes are interacting with the climate and the composition of the atmosphere, by making a detailed comparison of this reconstruction with our computer-generated 'virtual history' of the Earth.