Combining Satellite Imagery and Numerical Modelling to Study the Occurrence of Warm Upwellings in the Southern Baltic Sea in Winter
Abstract
:1. Introduction
2. Materials and Methods
2.1. The Area of Interest
2.2. Satellite Data
2.3. The Model
2.3.1. The Model Output
2.3.2. Filtration and Assimilation of SST Satellite Data from AVHRR and MODIS Radiometers
- Cassim, parameter (0 to 1) defining the degree of assimilation;
- Rt, temporal range of assimilation;
- RZ, vertical range of assimilation;
- Δt, calculation step of the model;
- Ta, temperature calculated by the model after assimilation;
- Tm, temperature calculated by the model prior to assimilation;
- zi, depth of the ith layer.
2.4. Methods of Validation
3. Results
3.1. Model Validation
3.1.1. Validation with In Situ Measurements
3.1.2. Validation with Satellite SST Data
3.2. Frequency of Upwellings in the Southern Baltic Sea in January and February (2010–2017)
3.3. Winter Upwellings as Represented by the PM3D
3.3.1. Upwelling Event in February 2013
3.3.2. Upwelling Event in February 2011
3.3.3. Upwelling Event in January 2012
3.3.4. Upwelling Event in January 2016
3.3.5. Upwelling Event in February 2017
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Bowden, K.F. Physical Oceanography of Coastal Water; Ellis Harwood Ltd.: Chichester, UK, 1983; 302p. [Google Scholar]
- Krężel, A.; Ostrowski, M.; Szymelfenig, M. Sea surface temperature distribution during upwelling along the Polish Baltic coast. Oceanologia 2005, 47, 415–432. [Google Scholar]
- Myrberg, K.; Andrejev, O.; Lehmann, A. Dynamical features of successive upwelling in the Baltic Sea. Oceanologia 2010, 52, 77–99. [Google Scholar] [CrossRef] [Green Version]
- Bychkova, I.A.; Viktorov, S.V. Use of satellite data for identification and classification of upwelling in the Baltic Sea. Oceanology 1987, 27, 158–162. [Google Scholar]
- Jankowski, A. Variability of coastal water hydrodynamics in the Southern Baltic hindcast modelling of an upwelling event along the Polish coast. Oceanologia 2002, 44, 395–418. [Google Scholar]
- Lehmann, A.; Myrberg, K.; Höflich, K. A statistical approach to coastal upwelling in the Baltic Sea based on the analysis of satellite data for 1990–2009. Oceanologia 2012, 54, 369–393. [Google Scholar] [CrossRef] [Green Version]
- Gurova, E.; Lehmann, A.; Ivanov, A. Upwelling dynamics in the Baltic Sea studied by a combined SAR/infrared satellite data and circulation model analysis. Oceanologia 2013, 55, 687–707. [Google Scholar] [CrossRef] [Green Version]
- Siegel, M.; Gerth, M.; Neuman, T.; Doerfer, R. Case studies on phytoplankton blooms in coastal and open waters of the Baltic Sea using Coastal Zone Color Scanner data. Int. J. Remote Sens. 1999, 20, 1249–1264. [Google Scholar] [CrossRef]
- Kowalewski, M. The influence of Hel upwelling (Baltic Sea) on nutrient concentrations and primary production—The results of ecohydrodynamic model. Oceanologia 2005, 47, 567–590. [Google Scholar]
- Lehmann, A.; Myrberg, K. Upwelling in the Baltic Sea—A review. J. Mar. Syst. 2008, 74, 3–12. [Google Scholar] [CrossRef]
- Dabuleviciene, T.; Kozlov, I.E.; Vaiciute, D.; Dailidiene, I. Remote sensing of coastal upwelling in the south-eastern Baltic Sea: Statistical properties and implications for the coastal environment. Remote Sens. 2018, 10, 1752. [Google Scholar] [CrossRef] [Green Version]
- Leppäranta, M.; Myrberg, K. The Physical Oceanography of the Baltic Sea; Springer: Berlin/Heidelberg, Germany, 2009. [Google Scholar]
- Von Storch, H.; Omstedt, A. Introduction and summary. In Assessment of Climate Change for the Baltic Sea Basin; Regional Climate Studies; The BACC II Author Team, Ed.; Springer: Cham, Switzerland, 2008; pp. 1–34. [Google Scholar]
- Suursaar, U. Waves, currents and sea level variations along the Letipea–Sillamäe coastal section of the southern Gulf of Finland. Oceanologia 2010, 52, 391–416. [Google Scholar] [CrossRef] [Green Version]
- Horstmann, U. Distribution patterns of temperature and water colour in the Baltic Sea as recorded in satellite images: Indicators for phytoplankton growth. Ber. Inst. Meeresk. 1983, 1, 106. [Google Scholar]
- Gidhagen, L. Coastal upwelling in the Baltic Sea–satellite and in situ measurements of sea-surface temperatures indicating coastal upwelling. Estuar. Coast. Shelf Sci. 1987, 24, 449–462. [Google Scholar] [CrossRef]
- Bychkova, I.A.; Viktorov, S.V.; Shumakher, D.A. A relationship between the large-scale atmospheric circulation and the origin of coastal upwelling in the Baltic Sea. Meteorol. Gidrol. 1988, 10, 91–98. (In Russian) [Google Scholar]
- Kahru, M.; Håkansson, B.; Rud, O. Distributions of the sea-surface temperature fronts in the Baltic Sea as derived from satellite imagery. Cont. Shelf Res. 1995, 15, 663–679. [Google Scholar] [CrossRef]
- Uiboupin, R.; Laanemets, J. Upwelling characteristics derived from satellite sea surface temperature data in the Gulf of Finland, Baltic Sea. Boreal Environ. Res. 2009, 14, 297–304. [Google Scholar]
- Kozlov, I.E.; Kudryavtsev, V.N.; Johannessen, J.A.; Chapron, B.; Dailidienė, I.; Myasoedov, A.G. ASAR imaging for coastal upwelling in the Baltic Sea. Adv. Space Res. 2012, 50, 1125–1137. [Google Scholar] [CrossRef]
- Uiboupin, R.; Laanemets, J. Upwelling parameters from bias-corrected composite satellite SST maps in the Gulf of Finland (Baltic Sea). IEEE Geosci. Remote Sens. Lett. 2015, 12, 529–592. [Google Scholar] [CrossRef]
- Esiukova, E.E.; Chubarenko, I.P.; Stont, Z.I. Upwelling or differential cooling? Analysis of satellite SST images of the southeastern Baltic Sea. Water Resour. 2017, 44, 69–77. [Google Scholar] [CrossRef]
- Bednorz, E.; Czernecki, B.; Półrolniczak, M.; Tomczyk, A.M. Atmospheric forcing of upwelling along the southeastern Baltic coast. Baltica 2018, 31, 73–85. [Google Scholar] [CrossRef]
- Krechik, V.; Myslenkov, S.; Kapustina, M. New possibilities in the study of coastal upwellings in the Southeastern Baltic Sea with using thermistor chain. Geogr. Environ. Sustain. 2019, 12, 44–61. [Google Scholar] [CrossRef] [Green Version]
- Finkensieper, S.; Meirink, J.-F.; van Zadelhoff, G.-J.; Hanschmann, T.; Benas, N.; Stengel, M.; Fuchs, P.; Hollmann, R.; Werscheck, M. CLAAS-2: CM SAF Cloud Property dAtAset Using SEVIRI, 2nd ed.; Satellite Application Facility on Climate Monitoring: Offenbach am Main, Germany, 2016. [Google Scholar] [CrossRef]
- Lass, H.-U.; Schmidt, T.; Seifert, T. On the dynamics of upwelling observed at the Darss Sill. In Proceedings of the 19th Conference of Baltic Oceanographers, Sopot, Poland, 29 August–1 September 1994; pp. 247–260. [Google Scholar]
- Fennel, W.; Seifert, T. Kelvin wave controlled upwelling in the western Baltic. J. Mar. Syst. 1995, 6, 286–300. [Google Scholar] [CrossRef]
- Lehmann, A.; Krauss, W.; Hinrichsen, H.-H. Effects of remote and local atmospheric forcing on circulation and upwelling in the Baltic Sea. Tellus 2002, 54, 299–316. [Google Scholar] [CrossRef] [Green Version]
- Myrberg, K.; Andreyev, O. Main upwelling regions in the Baltic Sea—A statistical analysis based on three-dimensional modelling. Boreal Environ. Res. 2003, 8, 97–112. [Google Scholar]
- Golenko, N.N.; Golenko, M.N.; Shchuka, S.A. Observation and modeling of upwelling in the southeastern Baltic. Oceanology 2009, 49, 15–21. [Google Scholar] [CrossRef]
- Fennel, W.; Radtke, H.; Schmidt, M.; Neumann, T. Transient upwelling in the central Baltic Sea. Cont. Shelf Res. 2010, 30, 2015–2026. [Google Scholar] [CrossRef]
- Väli, G.; Zhurbas, V.; Lips, U.; Laanemets, J. Submesoscale structures related to upwelling events in the Gulf of Finland, Baltic Sea (numerical experiments). J. Mar. Syst. 2017, 171, 31–42. [Google Scholar] [CrossRef]
- Zhurbas, V.M.; Stipa, T.; Malkki, P.; Paka, V.T.; Kuzmina, N.P.; Sklyarov, E.V. Mesoscale variability of the upwelling in the southeastern Baltic Sea: IR images and numerical modeling. Oceanology 2004, 44, 619–628. [Google Scholar]
- Kowalewski, M.; Ostrowski, M. Coastal up- and downwelling in the southern Baltic. Oceanologia 2005, 47, 453–475. [Google Scholar]
- Svansson, A. Interaction between the coastal zone and the open sea. Merentutkimuslait. Julk. Havsforskningsinst. Skr. 1975, 24, 385–404. [Google Scholar]
- Pickart, R.S.; Moore, G.W.K.; Torres, D.J.; Fratantoni, P.S.; Goldsmith, R.A.; Yang, J. Upwelling on the continental slope of the Alaskan Beaufort Sea: Storms, ice, and oceanographic response. J. Geophys. Res. 2009, 114, C00A13. [Google Scholar] [CrossRef] [Green Version]
- Lind, S.; Ingvaldsen, R.B. Variability and impacts of Atlantic water entering the Barents Sea from the north. Deep Sea Res. I 2012, 62, 70–88. [Google Scholar] [CrossRef]
- Falk-Petersen, S.; Pavlov, V.; Berge, J.; Cottier, F.; Kovacs, K.M.; Lydersen, C. At the rainbow’s end: High productivity fueled by winter upwelling along an Arctic shelf. Polar Biol. 2015, 38, 5–11. [Google Scholar] [CrossRef] [Green Version]
- Randelhoff, A.; Sundfjord, A. Short commentary on marine productivity at Arctic shelf breaks: Upwelling, advection and vertical mixing. Ocean Sci. 2018, 14, 293–300. [Google Scholar] [CrossRef] [Green Version]
- Konik, M.; Kowalewski, M.; Bradtke, K.; Darecki, M. The operational method of filling information gaps in satellite imagery using numerical models. Int. J. Appl. Earth Obs. Geoinf. 2019, 75, 68–82. [Google Scholar] [CrossRef]
- Labrot, T.; Lavanant, L.; Whyte, K.; Atkinson, N.; Brunel, P. AAPP Documentation. Scientific Description, NWP SAF Satellite Application Facility for Numerical Weather Prediction. Document NWPSAF-MF-UD-001, Version 7.0, October 2011. Available online: https://nwpsaf.eu/site/download/documentation/aapp/NWPSAF-MF-UD-001_Science.pdf (accessed on 20 November 2019).
- Lavanant, L. MAIA AVHRR Cloud Mask and Classification, MAIA v3 Scientific and Validation Document, MeteoFrance, 07/11/2002. Ref: MF/DP/CMS/R&D/MAIA3. Available online: http://www.meteorologie.eu.org/ici/maia/maia3.pdf (accessed on 20 November 2019).
- Woźniak, B.; Krężel, A.; Darecki, M.; Woźniak, S.B.; Majchrowski, R.; Ostrowska, M.; Kozłowski, Ł.; Ficek, D.; Olszewski, J.; Dera, J. Algorithm for the remote sensing of the Baltic ecosystem (DESAMBEM), Part 1: Mathematical apparatus. Oceanologia 2008, 50, 451–508. [Google Scholar]
- Kowalewski, M.; Krężel, A. System of automatic registration and geometric correction of AVHRR data. Arch. Fotogram. Kartogr. Teledetek 2004, 13, 397–407. (In Polish) [Google Scholar]
- Blumberg, A.F.; Mellor, G.L. A description of a three-dimensional coastal ocean circulation model. In Three-Dimensional Coastal Ocean Models; Heaps, N.S., Ed.; American Geophysical Union: Washington, DC, USA, 1987; pp. 1–16. [Google Scholar]
- Kowalewski, M. A three-dimensional, hydrodynamic model of the Gulf of Gdańsk. Oceanol. Stud. 1997, 26, 77–98. [Google Scholar]
- Kowalewski, M. An operational hydrodynamic model of the Gulf of Gdańsk. In Research Works Based on the ICM’s UMPL Numerical Weather Prediction System Results; Wyd. ICM: Warsaw, Poland, 2002; pp. 109–119. [Google Scholar]
- Kowalewski, M. The flow of nitrogen into the euphotic zone of the Baltic Proper as a result of the vertical migration of phytoplankton: An analysis of the long-term observations and ecohydrodynamic model simulation. J. Mar. Syst. 2015, 145, 53–68. [Google Scholar] [CrossRef]
- Ołdakowski, B.; Kowalewski, M.; Jędrasik, J.; Szymelfenig, M. Ecohydrodynamic model of the Baltic Sea, Part I: Description of the ProDeMo model. Oceanologia 2005, 47, 477–516. [Google Scholar]
- Herman, A.; Jędrasik, J.; Kowalewski, M. Numerical modelling of thermodynamics and dynamics of sea ice in the Baltic Sea. Ocean Sci. 2011, 7, 257–276. [Google Scholar] [CrossRef]
- Kowalewski, M.; Kowalewska-Kalkowska, H. Performance of operationally calculated hydrodynamic forecasts during storm surges in the Pomeranian Bay and Szczecin Lagoon. Boreal Environ. Res. 2011, 16, 27–41. [Google Scholar]
- Woźniak, B.; Bradtke, K.; Darecki, M.; Dera, J.; Dzierzbicka, L.; Ficek, D.; Furmańczyk, K.; Kowalewski, M.; Krężel, A.; Majchrowski, R.; et al. SatBaltic—A Baltic environmental satellite remote sensing system—An ongoing project in Poland, Part 1: Assumptions, scope and operating range. Oceanologia 2011, 53, 897–924. [Google Scholar] [CrossRef] [Green Version]
- Woźniak, B.; Bradtke, K.; Darecki, M.; Dera, J.; Dudzińska-Nowak, J.; Dzierzbicka, L.; Ficek, D.; Furmańczyk, K.; Kowalewski, M.; Krężel, A.; et al. SatBaltic—A Baltic environmental satellite remote sensing system—An ongoing project in Poland, Part 2: Practica applicability and preliminary results. Oceanologia 2011, 53, 925–958. [Google Scholar] [CrossRef] [Green Version]
- Kowalewski, M.; Kowalewska-Kalkowska, H. Sensitivity of the Baltic Sea level prediction to spatial model resolution. J. Mar. Syst. 2017, 173, 101–113. [Google Scholar] [CrossRef]
- Jędrasik, J.; Kowalewski, M. Mean annual and seasonal circulation patterns and long-term variability of currents in the Baltic Sea. J. Mar. Syst. 2019, 193, 1–26. [Google Scholar] [CrossRef]
- Herman-Iżycki, L.; Jakubiak, B.; Nowiński, K.; Niezgódka, B. UMPL—Numerical weather prediction system for operational applications. In Research Works Based on the ICM’s UMPL Numerical Weather Prediction System Results; Wyd. ICM: Warsaw, Poland, 2002; pp. 14–27. [Google Scholar]
- Krężel, A.; Kozłowski, Ł.; Paszkuta, M. A simple model of light transmission through the atmosphere over the Baltic Sea utilising satellite data. Oceanologia 2008, 50, 125–146. [Google Scholar]
- Zujev, M.; Elken, J. Testing marine data assimilation in the Northeastern Baltic using satellite SST products from the Copernicus marine environment monitoring service. Proc. Est. Acad. Sci. 2018, 67, 217–230. [Google Scholar] [CrossRef]
- Cressman, G.P. An operational objective analysis system. Mon. Weather Rev. 1959, 87, 367–374. [Google Scholar] [CrossRef]
- Gandin, L.S. Objective Analysis of Meteorological Fields; Israel Program for Scientific Translation: Jerusalem, Israel, 1965; 242p. [Google Scholar]
- Evensen, G. Sequential data assimilation with a nonlinear quasigeastrophic model using Monte Carlo methods to forecast error statistics. J. Geoph. Res. 1994, 99, 10143–10162. [Google Scholar] [CrossRef]
- Evensen, G. The Ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dyn. 2003, 53, 343–367. [Google Scholar] [CrossRef]
- Pham, D.T.; Verron, J.; Gourdeau, L. Singular evolutive Kalman filters for data assimilation in oceanography. Comptes Rendus Acad. Sci. Paris Earth Planet. Sci. 1998, 326, 255–260. [Google Scholar]
- Parrish, D.; Derber, J. The National Meteorological Center’s spectral statistical interpolation analysis system. Mon. Weather Rev. 1992, 120, 17471763. [Google Scholar] [CrossRef]
- Sokolov, A.; Andrejev, O.; Wulff, F.; Rodriguez Medina, M. The data assimilation system for data analysis in the Baltic Sea. Syst. Ecol. Contrib. 1997, 3, 1–66. [Google Scholar]
- Zhuang, S.Y.; Fu, W.W.; She, J. A pre-operational three dimensional variational data assimilation system in the North/Baltic Sea. Ocean Sci. 2011, 7, 771–781. [Google Scholar] [CrossRef] [Green Version]
- Fu, W.; She, J.; Zhuang, S. Application of an ensemble optimal interpolation in a North/Baltic Sea model: Assimilating temperature and salinity profiles. Ocean Model. 2011, 40, 227–245. [Google Scholar] [CrossRef]
- Losa, S.N.; Danilov, S.; Schröter, J.; Nerger, L.; Maβmann, S.; Janssen, F. Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Inference about the data. J. Mar. Syst. 2012, 105, 152–162. [Google Scholar] [CrossRef] [Green Version]
- Axell, L.; Liu, Y. Application of 3-D ensemble variational data assimilation to a Baltic Sea reanalysis 1989–2013. Tellus A 2016, 68, 24220. [Google Scholar] [CrossRef] [Green Version]
- Nowicki, A.; Dzierzbicka-Głowacka, L.; Janecki, M.; Kałas, M. Assimilation of the satellite SST data in the 3D CEMBS model. Oceanologia 2015, 57, 17–24. [Google Scholar] [CrossRef] [Green Version]
No. | Abbreviation | Area |
---|---|---|
1 | CS | off the Curonian Spit |
2 | SP | off the Sambia Peninsula |
3 | VS | off the Vistula Spit |
4 | HP | off the Hel Peninsula |
5 | Ł | Polish coast off Łeba |
6 | K | Polish coast off Kołobrzeg |
7 | R | off the Island of Rügen |
8 | SWB | off southwestern Bornholm |
9 | NEB | off northeastern Bornholm |
10 | SS | off southern Skåne |
11 | ES | off eastern Skåne |
12 | B | off Blekinge |
Year | AVHRR | MODIS |
---|---|---|
2010 | 46 | 19 |
2011 | 145 | 8 |
2012 | 112 | 12 |
2013 | 9 | 3 |
2014 | 50 | 14 |
2015 | 45 | 16 |
2016 | 139 | 20 |
2017 | 126 | 18 |
Sum | 672 | 110 |
Station | Bias [°C] | RMSE [°C] | Correlation Coefficient | Number of Records | Observation Period |
---|---|---|---|---|---|
Kołobrzeg | −0.51 | 1.33 | 0.973 | 30238 | 2014–2017 |
Władysławowo | 0.00 | 1.44 | 0.969 | 30235 | 2014–2017 |
Lubiatowo | −0.44 | 0.57 | 0.993 | 2080 | 2015–2017 |
Oder Bank | −0.38 | 0.50 | 0.996 | 5885 | 2010–2017 |
Arkona | −0.16 | 0.63 | 0.994 | 8384 | 2010–2017 |
Kap Arkona | −0.52 | 1.17 | 0.978 | 29420 | 2010–2017 |
Tejn | −0.23 | 0.93 | 0.987 | 66307 | 2010–2017 |
Kungsholmsfort | −0.39 | 1.13 | 0.983 | 60165 | 2010–2017 |
SatBałtic | −0.09 | 0.47 | 0.997 | 2336 | 2013 |
PL-P1 | −0.18 | 0.69 | 0.994 | 111 | 2010–2017 |
BCS III-10 | 0.04 | 0.68 | 0.995 | 97 | 2010–2015 |
BY1 | 0.23 | 0.70 | 0.994 | 45 | 2010–2012 |
BY2 | −0.11 | 0.73 | 0.992 | 143 | 2010–2015 |
BY5 | 0.03 | 0.50 | 0.997 | 147 | 2010–2015 |
Area | Number of Cases Analysed | M(+), S(+) | M(+), S(−) | M(−), S(+) | M(−), S(−) | Consistent Situations | Inconsistent Situations | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
No. | % | No. | % | No. | % | No. | % | No. | % | No. | % | ||||
CS | 81 | 12 | 14.8 | 2 | 2.5 | 0 | 0.0 | 67 | 82.7 | 79 | 97.5 | 2 | 2.5 | ||
SP | 79 | 6 | 7.6 | 4 | 5.1 | 0 | 0.0 | 69 | 87.3 | 75 | 94.9 | 4 | 5.1 | ||
VS | 90 | 16 | 17.8 | 11 | 12.2 | 9 | 10.0 | 54 | 60.0 | 70 | 77.8 | 20 | 22.2 | ||
HP | 88 | 32 | 36.4 | 8 | 9.1 | 1 | 1.1 | 47 | 53.4 | 79 | 89.8 | 9 | 10.2 | ||
Ł | 82 | 1 | 1.2 | 0 | 0.0 | 4 | 4.9 | 77 | 93.9 | 78 | 95.1 | 4 | 4.9 | ||
K | 89 | 8 | 9.0 | 4 | 4.5 | 8 | 9.0 | 69 | 77.5 | 77 | 86.5 | 12 | 13.5 | ||
R | 104 | 25 | 24.0 | 5 | 4.8 | 4 | 3.8 | 70 | 67.3 | 95 | 91.3 | 9 | 8.7 | ||
SWB | 88 | 0 | 0.0 | 1 | 1.1 | 1 | 1.1 | 86 | 97.7 | 86 | 97.7 | 2 | 2.3 | ||
NEB | 91 | 2 | 2.2 | 9 | 9.9 | 5 | 5.5 | 75 | 82.4 | 77 | 84.6 | 14 | 15.4 | ||
SS | 102 | 1 | 1.0 | 0 | 0.0 | 1 | 1.0 | 100 | 98.0 | 101 | 99.0 | 1 | 1.0 | ||
ES | 103 | 24 | 23.3 | 7 | 6.8 | 3 | 2.9 | 69 | 67.0 | 93 | 90.3 | 10 | 9.7 | ||
B | 102 | 8 | 7.8 | 4 | 3.9 | 3 | 2.9 | 87 | 85.3 | 95 | 93.1 | 7 | 6.9 |
Area | Satellite SST Images | PM3D | |||||
---|---|---|---|---|---|---|---|
Available Dates 1 | % | Upwelling Events | Available Dates | Upwelling Events | |||
No. | % | No. | % | ||||
CS | 81 | 17.1 | 12 | 14.8 | 466 | 52 | 11.2 |
SP | 79 | 16.7 | 6 | 7.6 | 466 | 35 | 7.5 |
VS | 90 | 19.0 | 25 | 27.8 | 466 | 137 | 29.4 |
HP | 88 | 18.6 | 33 | 37.5 | 466 | 202 | 43.3 |
Ł | 82 | 17.3 | 5 | 6.1 | 466 | 4 | 0.9 |
K | 89 | 18.8 | 16 | 18.0 | 466 | 40 | 8.6 |
R | 104 | 21.9 | 29 | 27.9 | 466 | 114 | 24.5 |
SWB | 88 | 18.6 | 1 | 1.1 | 466 | 3 | 0.6 |
NEB | 91 | 19.2 | 7 | 7.7 | 466 | 43 | 9.2 |
SS | 102 | 21.5 | 2 | 2.0 | 466 | 2 | 0.4 |
ES | 103 | 21.7 | 27 | 26.2 | 466 | 79 | 17.0 |
B | 102 | 21.5 | 11 | 10.8 | 466 | 46 | 9.9 |
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Kowalewska-Kalkowska, H.; Kowalewski, M. Combining Satellite Imagery and Numerical Modelling to Study the Occurrence of Warm Upwellings in the Southern Baltic Sea in Winter. Remote Sens. 2019, 11, 2982. https://doi.org/10.3390/rs11242982
Kowalewska-Kalkowska H, Kowalewski M. Combining Satellite Imagery and Numerical Modelling to Study the Occurrence of Warm Upwellings in the Southern Baltic Sea in Winter. Remote Sensing. 2019; 11(24):2982. https://doi.org/10.3390/rs11242982
Chicago/Turabian StyleKowalewska-Kalkowska, Halina, and Marek Kowalewski. 2019. "Combining Satellite Imagery and Numerical Modelling to Study the Occurrence of Warm Upwellings in the Southern Baltic Sea in Winter" Remote Sensing 11, no. 24: 2982. https://doi.org/10.3390/rs11242982
APA StyleKowalewska-Kalkowska, H., & Kowalewski, M. (2019). Combining Satellite Imagery and Numerical Modelling to Study the Occurrence of Warm Upwellings in the Southern Baltic Sea in Winter. Remote Sensing, 11(24), 2982. https://doi.org/10.3390/rs11242982