Analyses of Global Climate Variability in Data and In Models

时空数据分析的新方法将应用于对流层和平流层的全球气候变率研究。这些方法包括：线性判别分析（LDA）、复合均差（CMD）投影、经验模态分解（EMD）和连续小波变换（CWT）。在对流层，更重要的是在地表，将研究十年时间尺度上的增温和降温模式，目的是将太阳变化引起的增温响应与温室气体引起的增温响应区分开来。将审查多个数据集，使用现场测量来确认全球再分析的结果。政府间气候变化专门委员会第四次评估（IPCC AR4）存储库的全球气候模式（GCM）输出将以与观测数据相同的方式进行分析，以确认其中一些耦合的大气-海洋模式能够正确地模拟对太阳周期强迫的响应，并利用这一结果来约束模拟的瞬态气候响应。在平流层，将提取厄尔尼诺-南方涛动（ENSO）、太阳周期和准两年一次涛动（QBO）对极地平流层的具有统计意义的扰动，以便了解这些“外部”扰动如何相互作用。LDA方法在提取这些扰动的空间模式并确定其统计显著性方面具有重要意义。CWT可以客观地研究太阳周期对QBO周期和振幅的年代际调制。气候对太阳周期强迫的响应机制将通过数据和模式分析得到阐明，对其他自然外部强迫的响应也将得到更好的量化。这些研究更广泛的影响在于它们在人为气候变化问题上的应用。预测气候变化的一个主要不确定性是地球气候敏感性的大小。参与IPCC AR4的耦合大气-海洋模式在其瞬态气候响应中跨越了很大的范围，但很少有独立的约束可以用来缩小不确定性。这种不确定性导致了对全球变暖的大范围预测。这项工作的结果可以作为一个独立的观测约束，用于校准gcm预测瞬态变暖的能力。

Novel methods of temporal and spatial data analysis will be applied to study global climate variability in the troposphere and the stratosphere. These methods include: Linear Discriminant Analysis (LDA), Composite Mean Difference (CMD) Projection, Empirical Mode Decomposition (EMD) and the Continuous Wavelet Transform (CWT). In the troposphere, and more importantly at the surface, patterns of warming and cooling on decadal time scales will be studied, with the intent to separate the warming response to solar variations from that due to greenhouse gases. Multiple datasets will be examined, with in situ measurements used to confirm results from global reanalyses. Global climate model (GCM) output from the Intergovernmental Panel on Climate Change Fourth Assessment (IPCC AR4) repository will be analyzed in the same way as the observed data, to confirm that some of these coupled atmosphere-ocean models are capable of correctly simulating the response to solar-cycle forcing and to use this result to constrain modeled transient climate responses. In the stratosphere, statistically significant perturbations to the polar stratosphere from the El Nino-southern Oscillation (ENSO), from the solar cycle and from the Quasi-Biennial Oscillation (QBO) will be extracted, in order to understand how these "external" perturbations interact with each other. The LDA method has proven to be important in extracting the spatial patterns of these perturbations and establishing their statistical significance. CWT can be used to objectively study the decadal modulation of the period and amplitude of the QBO, possibly by the solar cycle. The mechanisms responsible for the climate response to solar-cycle forcing are to be elucidated through data and model analyses, and the responses to other natural external forcings better quantified. Broader impacts of these studies are in their application to the problem of anthropogenic climate change. A major uncertainty in the prediction of climate change is the magnitude of Earth's climate sensitivity. The coupled atmosphere-ocean models participating in IPCC AR4 span a large range in their transient climate response, but there are very few independent constraints that can be used to narrow the uncertainty. This uncertainty has led to a large range of predicted global warming. The results from this work can be used as an independent observational constraint for the calibration of GCMs in their ability to predict transient warming.