An emerging paradigm: Process-based climate reconstructions
An emerging paradigm: Process-based climate reconstructions
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DOI：
10.22498/pages.18.2.87
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发表时间：
2010-08
期刊：
影响因子：
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通讯作者：
M. Hughes;J. Guiot;C. Ammann
中科院分区：
文献类型：
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作者：
M. Hughes;J. Guiot;C. Ammann
在过去的几十年里，在利用自然和人类档案重建过去气候方面取得了非凡的进展（Jones等人，2009; Wanner等人，2008年）。与此同时，我们对气候系统的理解加深了，这有力地推动了综合观测和模式分析的新方法的发展。为了继续这一进展，最好使用我们可以从自然档案中提取的所有气候信息。通常情况下，只使用那些记录的方面，这些记录有助于线性转换为常规气候量的估计值，例如平均季节温度或季节总降水量。然而，人们可以很容易地指出，自然档案中的强大气候信息不适合线性回归模型（例如，参见Kelly等人，1989年）。通过更多地使用基于过程的前向模型提供了一种前进的方式，这些模型捕捉了自然档案形成的环境控制的主要特征（图1）。每一个代用资料档案都是通过物理、化学和/或生物过程产生的气候记录。气候重建代表着试图扭转这一局面，以恢复气候信息。统计解决方案（最常见的回归）用于确定简单的，通常是线性的，在一个时期内的替代和仪器气候记录的关系。因此，这种方法减少了识别存储在自然档案中的本地代理记录的单个气候驱动因素的问题，该驱动因素被认为在任何时候都是主导的。最近的两篇文章（Guiot等人，2009; Hughes和Ammann，2009）讨论了使用现代理解的代理形成过程中的趋同趋势。他们指出了探索过去气候的重要新兴工具和能力，这些工具和能力可以帮助避免当前地理统计方法的局限性。Guiot等人（2009年）重点关注全新世和末次盛冰期，这两个时期跨越了强迫和气候系统状态的重大转变。Guiot等人（2000年）强调古植被记录，提出了从化石统计模型转向这种自然档案形成的正演模型反演（图1）。对于积累率相对较低的沉积物数据，目前的统计解决办法是利用空间数据校准代用数据与气候之间的关系，并将这种“空间-时间”关系应用于过去植被的信息，以便推断气候。这种方法假设产生自然档案的定律在整个空间和时间中保持不变（均变论原理）。然而，当大气CO2浓度等非气候因素在分析期间或相对于目前发生变化时，可能会违反这一假设。这是转向基于过程的模型的主要动机，以便根据一组现实的所有主要强迫变量（无论是否是气候变量）更好地捕捉植被变化。季风亚洲的变化，其中包括饥荒和印度内部的重大政治重组（Sinha等人，2007年），中国元朝的崩溃（Zhang et al，2008年）;以及柬埔寨吴哥窟的高棉文明（Buckley et al，2010年）。虽然气候和社会变化之间的关系是复杂的，不一定是决定性的，密切的时间关系之间的干旱和广泛的社会变化在季风亚洲当时强烈表明，季风干旱可能发挥了重要作用，在塑造这些社会变化。
The last few decades have seen extraordinary progress in the reconstruction of past climates using natural and human archives (Jones et al., 2009; Wanner et al., 2008). At the same time, our understanding of the climate system has deepened, strongly motivating development of new methods of integrating observations and model analyses. To continue this progress, it would be desirable to use all the climate information we can extract from natural archives. Frequently, only those aspects of the records are used that lend themselves to linear transformation into estimates of conventional climate quantities, such as mean seasonal temperatures or seasonal totals of precipitation. However, one can readily point to robust climatic information in natural archives that does not fit conveniently into a linear regression model (e.g., see Kelly et al., 1989). A way forward is offered by increased use of process-based forward models that capture the main features of the environmental control of the formation of natural archives (Fig. 1). Focus on process Each proxy archive represents a record of climate that was generated through physical, chemical and/or biological processes. Reconstructions of climate represent attempts to turn this around in order to get back to the climate information. Statistical solutions (most often regression) are used to identify simple, usually linear, relationships over a period covered by both proxy and instrumental climate records. This approach therefore reduces the problem to identifying a single climatic driver of the local proxy record stored in the natural archive, a driver that is assumed to be dominant at all times. Two recent articles (Guiot et al., 2009; Hughes and Ammann, 2009) discuss converging trends in the use of modern understanding of proxy-forming processes. They point to important emerging tools and capabilities in exploring climates of the past that could help avoid the limitations of current empirical-statistical methods. Guiot et al. (2009) focused on the Holocene and the Last Glacial Maximum, periods spanning major shifts in both forcing and the state of the climate system. Emphasizing paleovegetation records, Guiot et al. (2000) proposed a move from empirical-statistical models to the inversion of forward models of the formation of such natural archives (Fig. 1). For sediment data with relatively low accumulation rates, the current statistical solution is to use spatial data to calibrate a relationship between proxy and climate and to apply this “spacefor-time” relationship to information on past vegetation so that the climate can be inferred. This approach assumes that the laws producing the natural archive remained constant throughout space and time (uniformitarian principle). However, when non-climatic factors such as atmospheric CO2 concentration have changed during the period analyzed or with respect to the present, this assumption may have been violated. This is a major motivation for moving towards process-based models to better capture vegetation changes according to a realistic set of all major forcing variables, whether climatic or not. change across monsoon Asia, which included famines and significant political reorganization within India (Sinha et al., 2007), the collapse of the Yuan dynasty in China (Zhang et al, 2008); and the Khmer civilization of Angkor Wat fame in Cambodia (Buckley et al., 2010). Although the relationship between climate and societal change is complex and not necessarily deterministic, the close temporal association between droughts and widespread societal changes across monsoon Asia at that time strongly suggests that monsoon droughts may have played a major role in shaping these societal changes.