Climate-Induced Variability of Sea Level in Stockholm: Influence of Air Temperature and Atmospheric Circulation

作     者：Deliang CHEN Anders OMSTEDT 

作者机构：Earth Sciences Centre Goteborg University Sweden Laboratory for Climate Studies/National Climate Center China Meteorological Administration Beijing 100081 

出 版 物：《Advances in Atmospheric Sciences》 (大气科学进展（英文版）)

年 卷 期：2005年第22卷第5期

页      面：655-664页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学] 

基　　金：This work was a part of the Swedish regional climate modeling program (SWECLIM)and Global Energy Water Cycle Experiment/The Baltic Sea Experiment (GEWEX/BALTEX) programmes has been funded by MISTRA and SMHI within the SWECLIM program and by Goteborg University the Swedish Research Council (Contract G 600-335/2001) It was also partly supported by two Swedish Sciences Council (NFR/VR) grants to Deliang Chen 

主　　题：sea level Baltic sea atmospheric circulation temperature Stockholm 

摘      要：This study is focused on climate-induced variation of sea level in Stockholm during 1873-1995. After the effect of the land uplift, is removed, the residual is characterized and related to large-scale temperature and atmospheric circulation. The residual shows an overall upward trend, although this result depends on the uplift rate used. However, the seasonal distribution of the trend is uneven. There are even two months （June and August） that show a negative trend. The significant trend in August may be linked to fresh water input that is controlled by precipitation. The influence of the atmospheric conditions on the sea level is mainly manifested through zonal winds, vorticity and temperature. While the wind is important in the period January-May, the vorticity plays a main role during June and December. A successful linear multiple-regression model linking the climatic variables （zonal winds, vorticity and mean air temperature during the previous two months） and the sea level is established for each month. An independent verification of the model shows that it has considerable skill in simulating the variability.