The Aerosol-Cloud Uncertainty REduction project (A-CURE)

A-CURE解决了大气科学中最具挑战性和持久性的问题之一-了解和量化人类活动引起的气溶胶颗粒变化如何影响气候。通过工业活动、运输和废物燃烧向大气层排放的气溶胶颗粒增加了地球反射的太阳辐射量，造成了冷却效应，部分抵消了温室气体的升温效应。所谓的气溶胶辐射强迫的大小在工业时期是高度不确定的。根据政府间气候变化专门委员会（IPCC）的最新评估，工业时期气溶胶排放造成的全球平均气候辐射强迫介于0和-2 W m-2之间，而二氧化碳排放造成的强迫为1.4 W m-2至2.2 W m-2。自1996年以来，这种巨大的不确定性一直存在于IPCC的所有评估中，极大地限制了我们对全球气候变化预测的信心。因此，气溶胶的不确定性限制了我们制定全球平均气温上升1.5或2 oC目标的能力。A-CURE旨在通过迄今为止最全面的气溶胶、云和大气辐射测量综合，结合分析全球模式不确定性的创新方法，减少气溶胶辐射强迫的不确定性。总体方法将是产生一套涵盖模型输入参数不确定性范围的大型模型模拟。先进的统计方法将用于生成基本上数以百万计的模型模拟，使模型的全部不确定性得以探索。然后，通过将模拟的气溶胶和云与广泛的大气测量进行比较，缩小这些模拟的范围。在A-CURE之后，区域和全球尺度气溶胶强迫的改进估计将使我们对历史气候，气候敏感性和气候预测的理解得到实质性改善。我们将使用改进的气候模式，缩小不确定性，以确定达到1.5或2 oC的全球平均温度上升的目标的影响。

A-CURE tackles one of the most challenging and persistent problems in atmospheric science - to understand and quantify how changes in aerosol particles caused by human activities affect climate. Emissions of aerosol particles to the atmosphere through industrial activity, transport and combustion of waste have increased the amount of solar radiation reflected by the Earth, which has caused a cooling effect that partly counteracts the warming effect of greenhouse gases. The magnitude of the so-called aerosol radiative forcing is highly uncertain over the industrial period. According to the latest intergovernmental panel (IPCC) assessment, the global mean radiative forcing of climate caused by aerosol emissions over the industrial period lies between 0 and -2 W m-2 compared to a much better understood and tighter constrained forcing of 1.4 W m-2 to 2.2 W m-2 due to CO2 emissions. This large uncertainty has persisted through all IPCC assessments since 1996 and significantly limits our confidence in global climate change projections. The aerosol uncertainty therefore limits our ability to define strategies for reaching a 1.5 or 2oC target for global mean temperature increase.A-CURE aims to reduce the uncertainty in aerosol radiative forcing through the most comprehensive ever synthesis of aerosol, cloud and atmospheric radiation measurements combined with innovative ways to analyse global model uncertainty. The overall approach will be to produce a large set of model simulations that spans the uncertainty range of the model input parameters. Advanced statistical methods will then be used to generate essentially millions of model simulations that enable the full uncertainty of the model to be explored. The spread of these simulations will then be narrowed by comparing the simulated aerosols and clouds against extensive atmospheric measurements. Following A-CURE, improved estimates of aerosol forcing on regional and global scales will enable substantial improvements in our understanding of historical climate, climate sensitivity and climate projections. We will use the improved climate model with narrowed uncertainty to determine the implications for reaching either a 1.5 or 2oC target for global mean temperature increase.