A step-response approach for predicting and understanding non-linear precipitation changes
A step-response approach for predicting and understanding non-linear precipitation changes
复制标题
DOI：
10.1007/s00382-012-1571-1
复制
发表时间：
2012-10
期刊：
影响因子：
4.6
通讯作者：
P. Good;William Ingram;William Ingram;F. H. Lambert;J. Lowe;J. M. Gregory;J. M. Gregory;M. Webb;M. Ringer;P. Wu
中科院分区：
文献类型：
--
作者：
P. Good;William Ingram;William Ingram;F. H. Lambert;J. Lowe;J. M. Gregory;J. M. Gregory;M. Webb;M. Ringer;P. Wu
未来降水的变化是未来气候变化最重要和最不确定的可能影响之一。我们提出了一种基于理想co2阶跃变化环流模型（GCM）实验的新方法，并使用HadCM3 GCM进行了测试。该方法有两个目的：一是帮助理解GCM预估，二是建立和测试一个快速、简单的模式，用于各种强迫情景下的降水预估。总体而言，我们发现CO2step实验包含许多与瞬态预测相关的信息，但由于理想化的实验设计，这些信息更容易提取。我们发现，该GCM中全球平均降水在co2下降后的暂时加速不能简单地用co2和温度的线性响应来完全解释。一个更完整的解释可以用表示二氧化碳和温度效应之间相互作用的附加项来实现。这一阶段的能量收支分析主要由晴空长波辐射（CSOLR）和感热主导，但云和短波也有贡献。主要的CSOLR相互作用是由于co2的增加使平均排放水平上升到较冷的高度，这降低了OLR随变暖的增长率。这种行为可以用我们的简单模型再现。在区域尺度上，我们将我们的方法与线性“模式缩放”（通过全球平均温度变化缩放区域响应）进行比较。在我们的模型预测线性变化的地区，模式缩放同样有效。然而，在一些地区，发现与全球平均温度的线性标度有很大的偏差，我们的简单模式提供了更准确的预测。理想化的实验揭示了非线性行为的复杂模式。可能存在一系列不同于主导全球平均响应的控制物理机制，需要对个别区域和其他gcm进行重点调查。
Future changes in precipitation represent one of the most important and uncertain possible effects of future climate change. We demonstrate a new approach based on idealised CO2step-change general circulation model (GCM) experiments, and test it using the HadCM3 GCM. The approach has two purposes: to help understand GCM projections, and to build and test a fast simple model for precipitation projections under a wide range of forcing scenarios. Overall, we find that the CO2step experiments contain much information that is relevant to transient projections, but that is more easily extracted due to the idealised experimental design. We find that the temporary acceleration of global-mean precipitation in this GCM following CO2ramp-down cannot be fully explained simply using linear responses to CO2and temperature. A more complete explanation can be achieved with an additional term representing interaction between CO2and temperature effects. Energy budget analysis of this term is dominated by clear-sky outgoing long-wave radiation (CSOLR) and sensible heating, but cloud and short-wave terms also contribute. The dominant CSOLR interaction is attributable to increased CO2raising the mean emission level to colder altitudes, which reduces the rate of increase of OLR with warming. This behaviour can be reproduced by our simple model. On regional scales, we compare our approach with linear ‘pattern-scaling’ (scaling regional responses by global-mean temperature change). In regions where our model predicts linear change, pattern-scaling works equally well. In some regions, however, substantial deviations from linear scaling with global-mean temperature are found, and our simple model provides more accurate projections. The idealised experiments reveal a complex pattern of non-linear behaviour. There are likely to be a range of controlling physical mechanisms, different from those dominating the global-mean response, requiring focussed investigation for individual regions, and in other GCMs.