Wind conditions over the Baltic Sea – comparing reanalysis data sets with observations

2020 ◽  
Author(s):  
Christoffer Hallgren ◽  
Erik Sahlée ◽  
Stefan Ivanell ◽  
Heiner Körnich ◽  
Ville Vakkari
Keyword(s):  
Baltic Sea ◽  
Wind Power ◽  
Reanalysis Data ◽  
Data Sets ◽  
The Baltic Sea ◽  
Data Set ◽  
Low Level ◽  
Seasonal And Diurnal Variations ◽  
Low Level Jets ◽  
The Baltic

<p>The potential of increasing the amount of offshore wind energy production in the Baltic Sea has been of great interest for many countries and wind power companies for a long time. From a meteorological point of view, there are several special wind characteristics that are observed in this area that needs to be taken into consideration when planning for a wind farm. For example, as the Baltic Sea is a semi-enclosed basin surrounded by coastlines in all directions, phenomenon such as low-level jets occur frequently.</p><p>In order to create a climatology of the wind conditions over the Baltic Sea, with wind power applications in mind, four different state-of-the-art reanalysis data sets (MERRA2, ERA5, UERRA and NEWA) have been compared with measurements from LIDAR systems and high meteorological towers (Anholt, Finnish Utö, FINO2 and Östergarnsholm). The performance of the data sets has been analyzed in terms of stability and governing synoptic weather conditions as well as seasonal and diurnal variations. By selecting the most suitable reanalysis data set and using the observations to make corrections, a climatology for wind conditions over the Baltic Sea, focusing on the low-level jets, has then been constructed.</p>

scholarly journals Looking for an Offshore Low-Level Jet Champion among Recent Reanalyses: A Tight Race over the Baltic Sea

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3670
Author(s):  
Christoffer Hallgren ◽  
Johan Arnqvist ◽  
Stefan Ivanell ◽  
Heiner Körnich ◽  
Ville Vakkari ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Wind Farms ◽  
Resource Assessment ◽  
Offshore Wind ◽  
The Baltic Sea ◽  
Average Wind Speed ◽  
Low Level ◽  
Wide Range ◽  
Low Level Jets ◽  
The Baltic

With an increasing interest in offshore wind energy, focus has been directed towards large semi-enclosed basins such as the Baltic Sea as potential sites to set up wind turbines. The meteorology of this inland sea in particular is strongly affected by the surrounding land, creating mesoscale conditions that are important to take into consideration when planning for new wind farms. This paper presents a comparison between data from four state-of-the-art reanalyses (MERRA2, ERA5, UERRA, NEWA) and observations from LiDAR. The comparison is made for four sites in the Baltic Sea with wind profiles up to 300 m. The findings provide insight into the accuracy of reanalyses for wind resource assessment. In general, the reanalyses underestimate the average wind speed. The average shear is too low in NEWA, while ERA5 and UERRA predominantly overestimate the shear. MERRA2 suffers from insufficient vertical resolution, which limits its usefulness in evaluating the wind profile. It is also shown that low-level jets, a very frequent mesoscale phenomenon in the Baltic Sea during late spring, can appear in a wide range of wind speeds. The observed frequency of low-level jets is best captured by UERRA. In terms of general wind characteristics, ERA5, UERRA, and NEWA are similar, and the best choice depends on the application.

scholarly journals Comparisons of Satellite and Modeled Surface Temperature and Chlorophyll Concentrations in the Baltic Sea with In Situ Data

2021 ◽  
Vol 13 (15) ◽  
pp. 3049
Author(s):  
Malgorzata Stramska ◽  
Marta Konik ◽  
Paulina Aniskiewicz ◽  
Jaromir Jakacki ◽  
Miroslaw Darecki
Keyword(s):  
Baltic Sea ◽  
Satellite Data ◽  
In Situ Measurements ◽  
Data Sets ◽  
The Baltic Sea ◽  
Data Set ◽  
In Situ Data ◽  
The Baltic ◽  
Good Agreement

Among the most frequently used satellite data are surface chlorophyll concentration (Chl) and temperature (SST). These data can be degraded in some coastal areas, for example, in the Baltic Sea. Other popular sources of data are reanalysis models. Before satellite or model data can be used effectively, they should be extensively compared with in situ measurements. Herein, we present results of such comparisons. We used SST and Chl from model reanalysis and satellites, and in situ data measured at eight open Baltic Sea stations. The data cover time interval from 1 January 1998 to 31 December 2019, but some satellite data were not always available. Both the model and the satellite SST data had good agreement with in situ measurements. In contrast, satellite and model estimates of Chl concentrations presented large errors. Modeled Chl presented the lowest bias and the best correlation with in situ data from all Chl data sets evaluated. Chl estimates from a regionally tuned algorithm (SatBaltic) had smaller errors in comparison with other satellite data sets and good agreement with in situ data in summer. Statistics were not as good for the full data set. High uncertainties found in chlorophyll satellite algorithms for the Baltic Sea highlight the importance of continuous regional validation of such algorithms with in situ data.

scholarly journals A comparison between the ERA40 and the SMHI gridded meteorological databases as applied to Baltic Sea modelling

2005 ◽  
Vol 36 (4-5) ◽  
pp. 369-380 ◽  
Author(s):  
A. Omstedt ◽  
Y. Chen ◽  
K. Wesslander
Keyword(s):  
Baltic Sea ◽  
Time Resolution ◽  
Meteorological Data ◽  
Horizontal Resolution ◽  
Data Sets ◽  
The Baltic Sea ◽  
Data Set ◽  
Original Surface ◽  
Baltic Sea Region ◽  
The Baltic

Two gridded meteorological data sets for the Baltic Sea region, both having 1°×1° horizontal resolution, were compared and analysed for use in Baltic Sea modelling. The SMHI 1°×1° data set covers surface parameters with a three-hour time resolution over the 1970–2004 period. The ERA40 data cover analysed and modelled parameters for several atmospheric layers with a six-hour time resolution over the 1957–2002 period. Meteorological variables considered in this analysis were air temperature, wind speed, total cloud cover, relative humidity and precipitation. In considering Baltic Sea modelling, we examined maximum ice extent, water temperature, salinity and net precipitation calculations. The two data sets are largely similar and can both be used in Baltic Sea modelling. However, their horizontal resolution is too coarse for resolving marine conditions over the Baltic Sea. This implies, for example, that the ERA40 original surface winds are too low for some Baltic Sea regions. The ERA40 precipitation values are also too low compared with those of the SMHI and other available data.

scholarly journals Classification and properties of coastal wind profiles with negative gradients – an observational study

2022 ◽  
Author(s):  
Christoffer Hallgren ◽  
Johan Arnqvist ◽  
Erik Nilsson ◽  
Stefan Ivanell ◽  
Metodija Shapkalijevski ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Local Minimum ◽  
Stable Stratification ◽  
Offshore Wind ◽  
The Baltic Sea ◽  
Wind Maximum ◽  
Low Level ◽  
Low Level Jets ◽  
Wind Profiles ◽  
The Baltic

Abstract. Wind profiles with a negative gradient are frequently occurring over the Baltic Sea and are important to take into consideration for offshore wind power as they affect not only the power production, but also the loads on the structure and the behavior of the wake behind the turbine. In this study, we classified non-normal profiles as wind profiles having negative shear in at least one part of the profile between 28 and 300 m: low-level jets (with a local wind maximum in the profile), profiles with a local minimum, and negative profiles. Using observations spanning over 3 years, we show that the non-normal wind profiles are common over the Baltic Sea in late spring and summer, with a peak of 40 % relative occurrence in May. Negative profiles (in the 28–300 m layer) were mostly occurring during unstable conditions, in contrast to low-level jets that primarily occurred in stable stratification. There were indications that the the zone with strong shear during low-level jets could cause a relative suppression of the variance for large turbulent eddies compared to the peak of the velocity spectra, in the layer below the jet core. Swell conditions were found to be favourable for the occurrence of negative profiles and profiles with a local minimum, as the waves fed energy into the surface layer, resulting in an increase of the wind speed from below.

scholarly journals Mechanisms of variability in decadal sea-level trends in the Baltic Sea over the 20th century

2017 ◽  
Vol 8 (4) ◽  
pp. 1031-1046 ◽  
Author(s):  
Sitar Karabil ◽  
Eduardo Zorita ◽  
Birgit Hünicke
Keyword(s):  
Regression Model ◽  
Baltic Sea ◽  
Sea Level ◽  
Atmospheric Circulation ◽  
Data Sets ◽  
Climatic Data ◽  
The Baltic Sea ◽  
Underlying Factor ◽  
Coastal Sea ◽  
The Baltic

Abstract. Coastal sea-level trends in the Baltic Sea display decadal-scale variations around a long-term centennial trend. In this study, we analyse the spatial and temporal characteristics of the decadal trend variations and investigate the links between coastal sea-level trends and atmospheric forcing on a decadal timescale. For this analysis, we use monthly means of sea-level and climatic data sets. The sea-level data set is composed of long tide gauge records and gridded sea surface height (SSH) reconstructions. Climatic data sets are composed of sea-level pressure, air temperature, precipitation, evaporation, and climatic variability indices. The analysis indicates that atmospheric forcing is a driving factor of decadal sea-level trends. However, its effect is geographically heterogeneous. This impact is large in the northern and eastern regions of the Baltic Sea. In the southern Baltic Sea area, the impacts of atmospheric circulation on decadal sea-level trends are smaller. To identify the influence of the large-scale factors other than the effect of atmospheric circulation in the same season on Baltic Sea sea-level trends, we filter out the direct signature of atmospheric circulation for each season separately on the Baltic Sea level through a multivariate linear regression model and analyse the residuals of this regression model. These residuals hint at a common underlying factor that coherently drives the decadal sea-level trends in the whole Baltic Sea. We found that this underlying effect is partly a consequence of decadal precipitation trends in the Baltic Sea basin in the previous season. The investigation of the relation between the AMO index and sea-level trends implies that this detected underlying factor is not connected to oceanic forcing driven from the North Atlantic region.

Simulating extreme sea levels at the Baltic Sea coast from synthetic cyclones

2020 ◽  
Author(s):  
Jani Särkkä ◽  
Jani Räihä ◽  
Matti Kämäräinen ◽  
Kirsti Jylhä
Keyword(s):  
Baltic Sea ◽  
Sea Level ◽  
Water Volume ◽  
The Baltic Sea ◽  
Data Set ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Level Model ◽  
The Baltic ◽  
Sea Coast

<p>Coastal areas are under rapid changes. Management to face flooding hazards in changing climate is of great significance due to the major impact of flooding events in densely populated coastal regions, where also important and vulnerable infrastructure is located. The sea level of the Baltic Sea is affected by internal fluctuations caused by wind, air pressure and seiche oscillations, and by variations of the water volume due to the water exchange between the Baltic Sea and the North Sea through the Danish Straits. The highest sea level extremes are caused by cyclones moving over the region. The most vulnerable locations are at the ends of the bays. St. Petersburg, located at the eastern end of the Gulf of Finland, has experienced major sea floods in 1777, 1824 and 1924.</p><p>In order to study the effects of the depths and tracks of cyclones on the extreme sea levels, we have developed a method to generate cyclones for numerical sea level studies. A cyclone is modelled as a two-dimensional Gaussian function with adjustable horizontal size and depth. The cyclone moves through the Baltic Sea region with given direction and velocity. The output of this method is the gridded data set of mean sea level pressure and wind components which are used as an input for the sea level model. The internal variations of the Baltic Sea are calculated with a numerical barotropic sea level model, and the water volume variations are evaluated using a statistical sea level model based on wind speeds near the Danish Straits. The sea level model simulations allow us to study extremely rare but physically plausible sea level events that have not occurred during the observation period at the Baltic Sea coast. The simulation results are used to investigate extreme sea levels that could occur at selected sites at the Finnish coastline.</p>

The observation of seiches in the Baltic Sea using a multi data set of water levels

2000 ◽  
Vol 24 (1-2) ◽  
pp. 67-84 ◽  
Author(s):  
Margitta Metzner ◽  
Martin Gade ◽  
Ingo Hennings ◽  
Alexander B Rabinovich
Keyword(s):  
Baltic Sea ◽  
Water Levels ◽  
The Baltic Sea ◽  
Data Set ◽  
The Baltic

scholarly journals Baltic Offshore Wind Energy Development—Poland’s Public Policy Tools Analysis and the Geostrategic Implications

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4883
Author(s):  
Kamila Pronińska ◽  
Krzysztof Księżopolski
Keyword(s):  
Public Policy ◽  
Wind Energy ◽  
Baltic Sea ◽  
Wind Power ◽  
Offshore Wind ◽  
Policy Tools ◽  
Offshore Wind Energy ◽  
The Baltic Sea ◽  
Offshore Wind Power ◽  
The Baltic

A key question for European energy transition is which forms of renewable energy technologies will play a central role in this process. The recent dynamic growth in offshore wind power together with the vast wind energy potential of the European seas, including the Baltic Sea, make this technology an increasingly attractive and viable option. Considering the high installation and connection costs, government support is considered essential for the development of offshore wind power. The aim of this article is to analyze Poland’s public policy tools, which govern offshore wind farm development, and to present them from a wider geostrategic perspective. Authors identify, classify, and evaluate individual public policy tools with the use of multi-criteria and multi-dimensional methods while explaining their impact on offshore wind development in Poland. The analysis of the individual tools has shown that the currently applied tools give a high probability of achieving public policy objectives. The characteristics of the applied tools prove that vital decisions on offshore wind energy have been made concerning the need for decarbonization but also regarding wider geostrategic calculations. Given the changing security dynamics in the Baltic Sea region, we highlight potential geostrategic risks to the implementation of offshore wind projects.

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