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 ...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.展开更多
文摘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.