|ABSTRACT||The motivation of this study is to investigate the intra-seasonal relationship between sea surface temperature and precipitation (SST-P) in the Anatolian Peninsula, which is a very unique region in terms of its regional climate system that is strongly affected by it's proximity large water bodies such as Mediterranean and Black Seas. Furthermore, this study aims to help understand the underlying mechanisms behind the complex interactions between atmosphere and ocean in the Mediterranean basin and specifically in the peninsula. The study presents a time-phase relationship analysis between SST and P, utilizing of a wide set of daily gridded observational precipitation products (i.e. TRMM, GPCP, E-OBS and ERA- Interim) as well as in-situ observations and satellite derived gridded SST datasets (AVHRR) to show the range of the uncertainty in the results. The results clearly show a significant and strong SST-P relationship at intra-seasonal time scales between the sea surface temperatures of the surrounded seas and precipitation over the peninsula, which varies seasonally and among the analyzed datasets. In general, the strongest SST-P relationship appears in the fall season, which is common across all of the analyzed datasets. In this case, the sub-basins of the peninsula exhibit a strong sensitivity to the SSTs of the eastern and central Mediterranean, as well as the Black Sea. The analysis also indicates a strong SST-P relationship with eastern Mediterranean, Levantine region and Black Sea in winter and spring, but with a slightly lower intensity. The evaluation of the results over the sea reveals that the strongest SST-P relationship appears in the western and central Mediterranean and Black Sea. The study is also extended with the analysis of the results of the newly developed regional climate modeling system (RegESM). In this case, the model output is analyzed with the same methodology that is used in the analysis of the observational datasets to find the same temporal and spatial SST-P correlation like observational datasets in the model results.
Acknowledgement: This study has been supported by a research grant (113Y108) provided by The Scientific and Technological Research Council of Turkey (TUBITAK). The computing resources used in this work to analyze the data were provided by the National Center for High Performance Computing of Turkey (UHEM) under grant number 500308201|