APA Reference

Pessanha Santos, N. , Moura, R., da Silva, C. S., Lamas, L., Lobo, V., & de Castro Neto, M. (2024). Long-term In Situ Eulerian Sea Surface Temperature Records along the Portuguese Coast. Data in Brief, 110287.
https://doi.org/10.1016/j.dib.2024.110287.

APA Reference

Silva, C. D. J. P. D. S. D. (2020). Análise da Variabilidade Espácio-Temporal da Temperatura da Superfície do Mar nas Águas Marinhas Portuguesas [Master dissertation]. Retrieved from https://comum.rcaap.pt/handle/10400.26/38070.

APA Reference

Silva, C, Lamas, L., Moura, R. (2020). Variabilidade da Temperatura da Superfície do Mar na Costa Portuguesa. 6.as Jornadas de Engenharia Hidrográfica/1.as Jornadas Luso-Espanholas de Hidrografia, 227-230. Retrieved from https://jornadas.hidrografico.pt/recursos/files/documentos/Livro_Atas_6JEH_2020.pdf.

Referência BibTeX

@masterthesis{jeronimo2021analise,
title={An{‘a}lise Comparativa entre diferentes fontes de dados oceanogr{‘a}ficos para a regi{~a}o da Macaron{‘e}sia},
author={Jer{‘o}nimo, Joana Alves de Melo},
year={2021}
}
@inproceedings{silva2020tsm,
title={Variabilidade da Temperatura da Superf{‘i}cie do Mar na Costa Portuguesa},
author={Silva, Catarina and Lamas, Luísa and Moura, Ricardo},
booktitle={6.as Jornadas de Engenharia Hidrográfica/1.as Jornadas Luso-Espanholas de Hidrografia},
pages={227–230}
year={2020}
}
@article{SANTOS2024110287,
title = {Long-term In Situ Eulerian Sea Surface Temperature Records along the Portuguese Coast},
journal = {Data in Brief},
pages = {110287},
year = {2024},
issn = {2352-3409},
doi = {https://doi.org/10.1016/j.dib.2024.110287},
url = {https://www.sciencedirect.com/science/article/pii/S2352340924002567},
author = {Nuno Pessanha Santos and Ricardo Moura and Catarina Santos {da Silva} and Luisa Lamas and Victor Lobo and Miguel de Castro Neto},
keywords = {Ocean surface temperature, Buoys, Temperature control, Temperature monitoring, Upwelling},
abstract = {Monitoring ocean surface temperature is critical to infer the variability of the upper layers of the ocean, from short temporal scales to climatic change scales. Analysis of the climatological trends and anomalies is fundamental to comprehend the long-term effects of climate change on marine ecosystems and coastal regions. The original data for the dataset presented was collected by the Portuguese Hydrographic Institute (Instituto Hidrográfico) using seven Ondograph and Meteo-oceanography buoys anchored offshore along the Portuguese coast to acquire ocean surface temperatures. The original raw data was pre-processed to provide averages over 3-hour periods and daily averages, and this cleaned data constitutes the provided dataset. The 3-hour temperature averages were obtained mainly between 2011 and 2015, and the daily temperature averages were obtained in intervals that vary with the considered buoy, having an average interval of 14 years per buoy. The data gathered provides a considerable temporal window, enabling the creation of data series and the implementation of data mining algorithms to develop decision support systems. Collecting data in situ makes it possible to validate simulated results obtained using approximation models. This allows for more accurate temperature readings and facilitates testing and correcting created models.}
}

Copiar BibTeX