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

全球气候模式对十年气候变化的预测存在很大的差异，即使在规定相同的辐射强迫时，这限制了这些预测在为决策提供指导方面的有用性。由于缺乏对云和水汽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。A-Train卫星等观测计划的进步为从多个角度诊断大气层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预算变化的理解。在接下来的五年里，我们将开发和应用分析和数值方法来了解A-Train卫星观测到的最近十年辐射预算的变化，验证最先进气候模型的气候变化模拟。辐射变率和反馈强度方面的观测结果，并结合历史辐射测量值来改善模型集合气候预测。长期目标是将卫星观测和气候建模纳入麦吉尔大学的大气研究计划。我们将奋进了解气候变率，特别是在辐射场，在不同的空间和时间尺度，了解辐射能量收支和气候系统的其他物理组成部分之间的关系，并利用这些知识来改善气候预测。这一计划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一个关键来源。该计划还将有助于未来气候观测计划的发展。改进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，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.