A diagnostic study of the variability of the Earth radiation energy budget using satellite observations and numerical simulations

即使规定了相同的辐射强迫，全球气候模式对年代际气候变化的预估也存在很大差异，这限制了这些预估为决策提供指导的有用性。由于缺乏对云和水蒸气等关键气候反馈因子的定量认识，存在较大的气候敏感性不确定性。观测项目的发展，如A-Train卫星，为从多个角度诊断大气顶部长波和短波辐射的变化以及相关的气候强迫和反馈提供了前所未有的机会。该研究计划解决了这些挑战和机遇，并致力于提高我们对地球辐射能量收支变异性的理解。**未来五年，我们将发展并应用分析和数值方法来了解A-Train卫星观测到的近十年来辐射预算的变化，在辐射变率和反馈强度方面验证最先进气候模式对气候变化的模拟，并结合历史辐射测量数据来改进模式集合气候预测。**长期目标是将卫星观测和气候模拟整合到麦吉尔大学的大气研究项目中。我们将努力在不同时空尺度上了解气候变率，特别是辐射领域的气候变率，了解辐射能量收支与气候系统其他物理成分之间的关系，并利用这些知识来改进气候预测。**该方案将对气候敏感性的不确定性提供强有力的观测约束，这是气候预测不确定性的主要来源。该项目还将有助于未来气候观测项目的发展。改善气候监测和预测将产生深远的全球和区域（加拿大）社会效益，例如为缓解和适应提供更好的指导。************************

There is a large discrepancy in the projection of decadal climate change among the global climate models even when identical radiative forcing is prescribed, which limits the usefulness of these projections as to providing guidance for policy-making. The large climate sensitivity uncertainty exists for lack of quantitative understanding of such key climate feedback factors as cloud and water vapor. The advancement of observing programs, such as the A-Train satellites, have provided unprecedented opportunities for diagnosing the variations of the top-of-the-atmosphere longwave and shortwave radiation and associated climate forcing and feedback from multiple angles. This research program addresses these challenges and opportunities and is dedicated to improving our understanding of the variability of the Earth radiation energy budget. ** In the next five years, we will develop and apply analytical and numerical methods to understand the variations in the radiation budget in the latest decade as observed by the A-Train satellites, validate the climate change simulations of the state-of-the-art climate models against the observations in terms of radiation variability and feedback strengths, and incorporate historical radiation measurements to improve model-ensemble climate projection.** The long-term objective is to integrate satellite observation and climate modeling into an atmospheric research program at McGill. We will endeavor to understand climate variability, especially that in the radiation fields, at different spatial and temporal scales, to understand the relation between the radiation energy budget and other physical components of the climate system, and to use this knowledge to improve climate prediction. ** This program will provide strong observational constraints on the uncertainty in climate sensitivity, a key source of uncertainty in climate prediction. This program will also aid the development of future climate observing programs. Improved climate monitoring and projection will have profound global and regional (Canada) societal benefits such as providing better guidance for mitigation and adaptation.************************