scholarly journals Assimilating high-resolution sea surface temperature data improves the ocean forecast potential in the Baltic Sea

Ocean Science ◽  
2018 ◽  
Vol 14 (3) ◽  
pp. 525-541 ◽  
Author(s):  
Ye Liu ◽  
Weiwei Fu

Abstract. We assess the impact of assimilating the satellite sea surface temperature (SST) data on the Baltic forecast, particularly on the forecast of ocean variables related to SST. For this purpose, a multivariable data assimilation (DA) system has been developed based on a Nordic version of the Nucleus for European Modelling of the Ocean (NEMO-Nordic). We use Kalman-type filtering to assimilate the observations in the coastal regions. Further, a low-rank approximation of the stationary background error covariance metrics is used at the analysis steps. High-resolution SST from the Ocean and Sea Ice Satellite Application Facility (OSISAF) is assimilated to verify the performance of the DA system. The assimilation run shows very stable improvements of the model simulation as compared with both independent and dependent observations. The SST prediction of NEMO-Nordic is significantly enhanced by the DA forecast. Temperatures are also closer to observations in the DA forecast than the model results in the water above 100 m in the Baltic Sea. In the deeper layers, salinity is also slightly improved. In addition, we find that sea level anomaly (SLA) is improved with the SST assimilation. Comparisons with independent tide gauge data show that the overall root mean square error (RMSE) is reduced by 1.8 % and the overall correlation coefficient is slightly increased. Moreover, the sea-ice concentration forecast is improved considerably in the Baltic Proper, the Gulf of Finland and the Bothnian Sea during the sea-ice formation period, respectively.

2018 ◽  
Author(s):  
Ye Liu ◽  
Weiwei Fu

Abstract. We assess the impact of assimilating the satellite sea surface temperature (SST) data on the Baltic forecast, practically on the forecast of ocean variables related to SST. For this purpose, a multivariable data assimilation (DA) system has been developed based on a Nordic version of the Nucleus for European Modelling of the Ocean (NEMO-Nordic). We use a localized Singular Evolutive Interpolated Kalman (SEIK) filter to characterize correlation scales in the coastal regions. High resolution SST from OSISAF is assimilated to verify the performance of DA system. The assimilation run shows very stable improvements on the model simulation as compared with both independent and dependent observations. The SST prediction of NEMO-Nordic is significantly enhanced by the DA system. Temperatures are also closer to observation in the DA system than the model results in the water above 100 m in the Baltic Sea. In the deeper layers, salinity is also slightly improved. Besides, we find that Sea level anomaly (SLA) is improved with the SST assimilation. Comparison with independent tide gauge data show that overall root mean square error (RMSE) is reduced by 1.8 % and overall correlation coefficient is increased by 0.4 %. Moreover, the sea ice concentration forecast is improved considerably in the Baltic proper, the Gulf of Finland and the Bothnian Sea, respectively.


2021 ◽  
Author(s):  
C. Dutheil ◽  
H. E. M. Meier ◽  
M. Gröger ◽  
F. Börgel

AbstractThe Baltic Sea is one of the fastest-warming semi-enclosed seas in the world over the last decades, yielding critical consequences on physical and biogeochemical conditions and on marine ecosystems. Although long-term trends in sea surface temperature (SST) have long been attributed to trends in air temperature, there are however, strong seasonal and sub-basin scale heterogeneities of similar magnitude than the average trend which are not fully explained. Here, using reconstructed atmospheric forcing fields for the period 1850–2008, oceanic climate simulations were performed and analyzed to identify areas of homogenous SST trends using spatial clustering. Our results show that the Baltic Sea can be divided into five different areas of homogeneous SST trends: the Bothnian Bay, the Bothnian Sea, the eastern and western Baltic proper, and the southwestern Baltic Sea. A classification tree and sensitivity experiments were carried out to analyze the main drivers behind the trends. While ice cover explains the seasonal north/south warming contrast, the changes in surface winds and air-sea temperature anomalies (along with changes in upwelling frequencies and heat fluxes) explain the SST trends differences between the sub-basins of the southern part of the Baltic Sea. To investigate future warming trends climate simulations were performed for the period 1976–2099 using two RCP scenarios. It was found that the seasonal north/south gradient of SST trends should be reduced in the future due to the vanishing of sea ice, while changes in the frequency of upwelling and heat fluxes explained the lower future east/west gradient of SST trend in fall. Finally, an ensemble of 48 climate change simulations has revealed that for a given RCP scenario the atmospheric forcing is the main source of uncertainty. Our results are useful to better understand the historical and future changes of SST in the Baltic Sea, but also in terms of marine ecosystem and public management, and could thus be used for planning sustainable coastal development.


2014 ◽  
Vol 129 ◽  
pp. 157-165 ◽  
Author(s):  
Igor Kozlov ◽  
Inga Dailidienė ◽  
Anton Korosov ◽  
Victor Klemas ◽  
Toma Mingėlaitė

AMBIO ◽  
2019 ◽  
Vol 48 (11) ◽  
pp. 1362-1376 ◽  
Author(s):  
H. E. Markus Meier ◽  
Christian Dieterich ◽  
Kari Eilola ◽  
Matthias Gröger ◽  
Anders Höglund ◽  
...  

Author(s):  
Christin Appelqvist ◽  
Jon N. Havenhand ◽  
Gunilla B. Toth

Shipworms (teredinids) are highly specialized marine bivalves that consume terrestrially derived wood. Changes in environmental variables may result in shipworms spreading into the Baltic Sea – which would have devastating consequences for maritime cultural heritage and submerged wooden structures. We investigated the distribution and abundance of the shipworms Teredo navalis and Psiloteredo megotara along the Swedish coast in 2006–2008, and compared our findings with data collected at partly the same locations in 1971–1973. Wooden test panels were submerged in near-surface waters at 18 harbours. The presence of shipworms was determined by X-ray radiography of each panel. Sea surface temperature and salinity data were analysed to investigate whether any changes in distribution were correlated to changes in environmental variables. We found that past and present distributions of T. navalis were similar – indicating that no range expansion of shipworms into the Baltic Sea has taken place the last 35 years. The abundance of T. navalis was similar between decades at all investigated sites except two (Arild and Barsebäckshamn), where abundances were higher in 2006–2008. The abundance of T. navalis varied along the coast and was positively correlated to mean sea surface salinity, but not to mean sea surface temperature (2006–2008 data). The distribution and abundance of P. megotara were similar during the two study periods with only single observations at a few sites. In conclusion, we found no evidence of range expansion of shipworms along the Swedish coast.


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