Impact of argopy#
Papers & proceedings mentioning argopy#
Bartlett, Jenna, “An investigation of geostationary satellite imagery to compare developing and non-developing African easterly waves” (2022). Thesis and Dissertations. 5600. https://scholarsjunction.msstate.edu/td/5600
Chafik, et.al, “The Faroe-Shetland Channel Jet: Structure, Variability, and Driving Mechanisms”, 2023, JGR Oceans, https://doi.org/10.1029/2022JC019083
Chevillard C, Juza M, Dıaz-Barroso L, Reyes E, Escudier R and Tintore J (2024) Capability of the Mediterranean Argo network to monitor sub-regional climate change indicators. Front. Mar. Sci. 11:1416486. https://doi.org/10.3389/fmars.2024.1416486
Dan E. Kelley, Jaimie Harbin, Clark Richards, “argoFloats: An R Package for Analyzing Argo Data”, 2021 Frontiers in Marine Science, https://doi.org/10.3389/fmars.2021.635922
de Solo, Sofia M., “What makes a hurricane fall apart? A multi-platform assessment of tropical cyclone weakening By” (2021). Thesis and Dissertations. 5274. https://scholarsjunction.msstate.edu/td/5274
Dunnington et al., (2021). argodata: An R interface to oceanographic data from the International Argo Program. Journal of Open Source Software, 6(68), 3659, https://doi.org/10.21105/joss.03659
Elipot S. , P Miron, M Curcic, K Santana, R Lumpkin (2024). Clouddrift: a Python package to accelerate the use of Lagrangian data for atmospheric, oceanic, and climate sciences. Journal of Open Source Software, 9(99), 6742, https://joss.theoj.org/papers/10.21105/joss.06742
Gonzalez A., “The Argo Online School: An e-learning tool to get started with Argo” (2023), The Journal of Open Source Education (Under review)
Huda, Md Nurul, “Machine Learning for Improvement of Ocean Data Resolution for Weather Forecasting and Climatological Research” (2023). Thesis and Dissertations, Virginia Tech, http://hdl.handle.net/10919/116504
Steinberg, J. M., Piecuch, C. G., Hamlington, B. D., Thompson, P. R., & Coats, S. (2024). Influence of deep-ocean warming on coastal sea-level decadal trends in the Gulf of Mexico. Journal of Geophysical Research: Oceans, 129, e2023JC019681. https://doi.org/10.1029/2023JC019681
Zhang, Y. (2023). Python Data Analysis Techniques in Administrative Information Integration Management System. In: Atiquzzaman, M., Yen, N.Y., Xu, Z. (eds) Proceedings of the 4th International Conference on Big Data Analytics for Cyber-Physical System in Smart City - Volume 2. BDCPS 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 168. Springer, Singapore. https://doi.org/10.1007/978-981-99-1157-8_35
Other interesting mentions#
Blog post & personal pages :
Kim Wood : https://kouya.has.arizona.edu/python/PythonResources.html
Zachary Labe : https://zacklabe.com/methods-and-open-software
WxGuy : https://wxguy.in/posts/list-of-python-packages-for-met-ocean-and-climate-science-applications
Samapriya Roy : https://samapriyaroy.medium.com/open-ocean-data-with-argofloats-tool-50efef6c4f05
Some academic python env :
Sydney univ academic conda env : http://climate-cms.wikis.unsw.edu.au/Conda
NCU (australian computing infra) PyAOS env : https://opus.nci.org.au/display/DAE/PyAOS+-++Python+for+Atmosphere+and+Ocean+Science
Stackoverflow : https://stackoverflow.com/search?q=argopy