SLAC-SD. Relevance of sea and land surface-atmosphere-climate interactions within the framework of statistical downscaling for Europe and the Mediterranean area.

陆地-大气和海洋-大气的相互作用在全球气候中具有相当重要的意义。当前气候研究中的主要挑战是海面和陆地过程对气候变异性和变化以及对极端事件的影响。在这方面，重要的是评估海洋和陆地表面影响大气过程和气候的动态和物理机制。到目前为止，大多数研究都集中在数值模式研究上，以解决大气和气候对海洋和陆地表面缓慢变化状态的响应。然而，目前的地球系统模型(ESM)分辨率较低，物理参数仍然相对简单，只能提供有限的局部到区域尺度的信息。因此，重要的是将大尺度模式输出缩小到较小的尺度，以便提供精细的气候变化信息。在这个项目中，目的是在统计缩小尺度的框架内明确地引入海面和陆面特征作为预测因子。在这方面，必须在观测数据集中以及在环境监测系统中分析这些变量。利用多元统计分析方法，研究了观测资料与ESM资料之间的土壤湿度(SM)和海表面温度(SSTs)的一般表示以及SM/SST-大气-气候之间的特殊相互作用。随后的分析致力于可转移性和在未来气候变化假设下观察到的预测者-预测者之间关系的修改。这将使人们更好地了解所涉及的过程，并通过纳入SM和/或SST作为额外的预测指标，评估改进统计缩小尺度模型的潜力。分析将集中在欧洲/地中海地区的温度和降水。这一领域的选择使得有可能捕捉到潜在的气候变化引起的海、陆表面-大气-气候相互作用的空间变化。除了平均值，还将讨论温度和降水的变异性和极端情况。最后，该项目旨在增进对观测和模式数据中陆地和海洋表面--大气--气候相互作用的了解，评价和改进统计缩小尺度技术的性能，从而减少区域和地方尺度气候变化预测的不确定性。

Land-atmosphere and ocean-atmosphere interactions are of considerable importance in the global climate. Major challenges in current climate research are the impact of sea surface and land processes on climate variability and change as well as on extreme events. Within this context it is important to assess the dynamic and physical mechanisms by which the sea and land surfaces influence atmospheric processes and climate. Up to now most studies concentrated on numerical model studies to address the atmospheric and climatic response to slowly varying states of the ocean and land surfaces. However, with the coarse resolution and still relatively simple physical parameterizations, current Earth System Models (ESMs) can only provide limited information on local to regional scales. Thus, it is important to downscale the large-scale model output to smaller scales in order to provide fine-scale climate change information. In this project the aim is to explicitly introduce sea surface and land surface characteristics as predictors in the framework of statistical downscaling. In this context it is essential to analyse these variables in the observational data sets as well as in the ESMs. Using multivariate statistical analysis, the general representation of Soil Moisture (SM) and Sea Surface Temperatures (SSTs) and the specific SM/SST-atmosphere-climate interactions in and between the observations and the ESM data are investigated. Subsequent analyses are devoted to the transferability and to the modifications of the observed predictor-predictand relationships under the assumption of future climate change. This will lead to a better understanding of the processes involved and to an assessment of the potential for improvement of statistical downscaling models through the inclusion of SM and/or SSTs as additional predictors. Analyses will concentrate on temperature and precipitation in the European/ Mediterranean area. The selection of this domain makes it possible to capture potential climate change induced spatial shifts of sea and land surface-atmosphere-climate interactions. Besides mean values, temperature and precipitation variability and extremes will be addressed. Finally, the project aims to contribute to an enhanced understanding of land and sea surface-atmosphere-climate interactions in observations and model data, to evaluate and improve the performance of statistical downscaling techniques and thus to reduce uncertainties of climate change projections on regional to local scales.