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Ciavatta, S, Lazzari, P, Álvarez, E, Bertino, L, Bolding, K, Bruggeman, J, Capet, A, Cossarini, G, Daryabor, F, Nerger, L, Popov, M, Skákala, J, Spada, S, Teruzzi, A, Wakamatsu, T, Yumruktepe, VC and Brasseur, P 2024 Control of simulated ocean ecosystem indicators by biogeochemical observations. Progress in Oceanography. 103384. https://doi.org/10.1016/j.pocean.2024.103384 (In Press)
Banerjee, DS and Skákala, J 2024 Improved understanding of eutrophication trends, indicators and problem areas using machine learning. Improved understanding of eutrophication trends, indicators and problem areas using machine learning. https://doi.org/10.22541/essoar.171405637.76928549/v1
Skákala, J, Ford, D, Fowler, A, Lea, D, Martin, M and Ciavatta, S 2024 How uncertain and observable are marine ecosystem indicators in shelf seas?. Progress in Oceanography, 224. 103249. https://doi.org/10.1016/j.pocean.2024.103249
Higgs, I, Skákala, J, Bannister, R, Carrassi, A and Ciavatta, Stefano 2024 Investigating ecosystem connections in the shelf sea environment using complex networks. Biogeosciences, 21 (3). 731-746. https://doi.org/10.5194/bg-21-731-2024
Bruggeman, J, Bolding, K, Nerger, L, Teruzzi, A, Spada, S, Skákala, J and Ciavatta, S 2024 EAT v0.9.6: a 1D testbed for physical-biogeochemical data assimilation in natural waters. https://doi.org/10.5194/gmd-2023-238 (In Press)
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Skákala, J, Awty-Carroll, K, Menon, PP, Wang, K and Lessin, G 2023 Future digital twins: emulating a highly complex marine biogeochemical model with machine learning to predict hypoxia. Frontiers in Marine Science, 10. https://doi.org/10.3389/fmars.2023.1058837
Ford, DA, Grossberg, S, Rinaldi, G, Menon, PP, Palmer, MR, Skákala, J, Smyth, TJ, Williams, CAJ, Lorenzo Lopez, A and Ciavatta, S 2022 A solution for autonomous, adaptive monitoring of coastal ocean ecosystems: Integrating ocean robots and operational forecasts. Frontiers in Marine Science, 9. https://doi.org/10.3389/fmars.2022.1067174
Fowler, AM, Skákala, J and Ford, D 2022 Validating and improving the uncertainty assumptions for the assimilation of ocean‐colour‐derived chlorophyll a$$ a $$ into a marine biogeochemistry model of the Northwest European Shelf Seas. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.4408
Skákala, J, Bruggeman, J, Ford, D, Wakelin, S, Akpınar, A, Hull, T, Kaiser, J, Loveday, BR, O’Dea, E, Williams, CAJ and Ciavatta, S 2022 The impact of ocean biogeochemistry on physics and its consequences for modelling shelf seas. Ocean Modelling, 172. 101976. https://doi.org/10.1016/j.ocemod.2022.101976
Skákala, J, Ford, D, Bruggeman, J, Hull, T, Kaiser, J, King, RR, Loveday, BR, Palmer, MR, Smyth, TJ, Williams, CAJ and Ciavatta, S 2021 Towards a multi‐platform assimilative system for North Sea biogeochemistry. Journal of Geophysical Research: Oceans. https://doi.org/10.1029/2020JC016649
Skákala, J and Lazzari, P 2021 Low complexity model to study scale dependence of phytoplankton dynamics in the tropical Pacific. Physical Review E, 103 (1). 22, pp. https://doi.org/10.1103/PhysRevE.103.012401
Groom, SB, Sathyendranath, S, Ban, Y, Bernard, S, Brewin, RJW, Brotas, V, Brockmann, C, Chauhan, P, Choi, J-K, Chuprin, A, Ciavatta, S, Cipollini, P, Donlon, CJ, Franz, BA, He, X, Hirata, T, Jackson, T, Kampel, M, Krasemann, H, Lavender, SJ, Pardo-Martinez, S, Melin, F, Platt, T, Santoleri, R, Skákala, J, Schaeffer, B, Smith, M, Steinmetz, F, Valente, A and Wang, M 2019 Satellite Ocean Colour: Current Status and Future Perspective. Frontiers in Marine Science, 6. https://doi.org/10.3389/fmars.2019.00485
Skákala, J, Ford, D, Brewin, RJW, McEwan, R, Kay, S, Taylor, BH, de Mora, L and Ciavatta, S 2018 The Assimilation of Phytoplankton Functional Types for Operational Forecasting in the Northwest European Shelf. Journal of Geophysical Research-Oceans. https://doi.org/10.1029/2018JC014153
Ciavatta, S, Brewin, RJW, Skákala, J, Polimene, L, Artioli, Y, Allen, JI and de Mora, L 2018 Assimilation of ocean-colour plankton functional types to improve marine ecosystem simulations. Journal of Geophysical Research-Oceans. https://doi.org/10.1002/2017JC013490
Skákala, J, Cazenave, PW, Smyth, TJ and Torres, R 2016 Using multifractals to evaluate oceanographic model skill. Journal of Geophysical Research: Oceans. https://doi.org/10.1002/2016JC011741
Skákala, J and Smyth, TJ 2016 Simple heterogeneity parametrization for sea surface temperature and chlorophyll. Journal of Marine Systems, 158. 52-58. https://doi.org/10.1016/j.jmarsys.2016.01.010
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Skákala, J and Smyth, TJ 2015 Complex coastal oceanographic fields can be described by universal multifractals. Journal of Geophysical Research: Oceans, 120 (9). 6253-6265. https://doi.org/10.1002/2015JC011111