Browse by PML Authors

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

Skakala, J, Bruggeman, J, Brewin, RJW, Ford, D and Ciavatta, S 2020 Improved representation of underwater light field and its impact on ecosystem dynamics: a study in the North Sea. Journal of Geophysical Research: Oceans. 1, pp. https://doi.org/10.1029/2020JC016122 (In Press)

Ciavatta, S, Kay, S, Brewin, RJW, Cox, R., Di Cicco, A, Nencioli, F, Polimene, L, Sammartino, M, Santoleri, R, Skakala, J and Tsapakis, M. 2019 Ecoregions in the Mediterranean Sea Through the Reanalysis of Phytoplankton Functional Types and Carbon Fluxes. Journal of Geophysical Research: Oceans, 124 (10). 6737-6759. https://doi.org/10.1029/2019JC015128

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

Skakala, J, Smyth, TJ, Torres, R, Buckingham, CE, Brearley, A, Hyder, P and Coward, AC 2019 SST dynamics at different scales: evaluating the oceanographic model resolution skill to represent SST processes in the Southern Ocean. Journal of Geophysical Research: Oceans. https://doi.org/10.1029/2018JC014791

Skakala, J and Bruun, JT 2018 A mechanism for Pacific interdecadal resonances. Journal of Geophysical Research-Oceans. https://doi.org/10.1029/2018JC013752

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