References
Chambers, F., John M. CRC Press Boca Raton. (2016). Extending
r. CRC Press, Taylor & Francis Group. https://www.routledge.com/Extending-R/Chambers/p/book/9781498775717
Chen, J., Dai, A., Zhang, Y., & Rasmussen, K. L. (2020). Changes in
convective available potential energy and convective inhibition under
global warming. Journal of Climate, 33(6), 2025–2050.
https://doi.org/10.1175/JCLI-D-19-0461.1
Chirila, D. B., & Lohmann, G. (2014). Introduction to modern
fortran for the earth system sciences. Springer Berlin Heidelberg.
https://doi.org/10.1007/978-3-642-37009-0
Draelos, R. (2019). Convolution vs. Cross-correlation. In Glass
Box. https://glassboxmedicine.com/2019/07/26/convolution-vs-cross-correlation/
Eddelbuettel, D., Francois, R., Allaire, J., Ushey, K., Kou, Q.,
Russell, N., Ucar, I., Bates, D., & Chambers, J. (2024). Rcpp:
Seamless r and c++ integration. https://www.rcpp.org
Fischer, B., Smith, M., & Pau, G. (2023). rhdf5: R interface to
HDF5. https://doi.org/10.18129/B9.bioc.rhdf5
Gerber, F., Moesinger, K., & Furrer, R. (2018). dotCall64: An R package providing an
efficient interface to compiled C, C++, and
Fortran code supporting long vectors. SoftwareX,
7, 217–221. https://doi.org/10.1016/j.softx.2018.06.002
Gerber, F., & Mösinger, K. (2023). dotCall64: Enhanced foreign
function interface supporting long vectors. https://git.math.uzh.ch/reinhard.furrer/dotCall64
Hijmans, R. J. (2024). Terra: Spatial data analysis. https://rspatial.org/
Masuda, Y. (2020). Modern fortran tutorial. Introduction. https://masuday.github.io/fortran_tutorial/introduction.html
Mersmann, O. (2024). Microbenchmark: Accurate timing functions.
https://github.com/joshuaulrich/microbenchmark/
Metcalf, M., Reid, J., & Cohen, M. (2018). Modern Fortran
Explained: Incorporating Fortran 2018. Oxford University
Press. https://doi.org/10.1093/oso/9780198811893.001.0001
Pebesma, E. (2018). Simple Features for R:
Standardized Support for Spatial Vector Data. The R
Journal, 10(1), 439–446. https://doi.org/10.32614/RJ-2018-009
Pebesma, E. (2024a). Sf: Simple features for r. https://r-spatial.github.io/sf/
Pebesma, E. (2024b). Stars: Spatiotemporal arrays, raster and vector
data cubes. https://r-spatial.github.io/stars/
Pebesma, E., & Bivand, R. (2023). Spatial
Data Science: With applications in R. Chapman and
Hall/CRC. https://doi.org/10.1201/9780429459016
Pierce, D. (2023). ncdf4: Interface to unidata netCDF (version 4 or
earlier) format data files. https://cirrus.ucsd.edu/~pierce/ncdf/
R Core Team. (2023). R: A language and environment for statistical
computing. R Foundation for Statistical Computing. https://www.R-project.org/
Seelig, T., Deneke, H., Quaas, J., & Tesche, M. (2021). Life Cycle of Shallow Marine Cumulus Clouds From
Geostationary Satellite Observations. Journal of Geophysical
Research: Atmospheres, 126(22). https://doi.org/10.1029/2021JD035577
Stull, R. (2016). Practical meteorology: An algebra-based survey of
atmospheric science. AVP International, University of British
Columbia. https://www.eoas.ubc.ca/books/Practical_Meteorology/
Urbanek, S. (2024). rJava: Low-level r to java interface. http://www.rforge.net/rJava/
Ushey, K., Allaire, J., & Tang, Y. (2024). Reticulate: Interface
to python. https://rstudio.github.io/reticulate/
Wang, C. (2019). Kernel learning for visual perception. https://doi.org/10.32657/10220/47835
Warren, M. A., Quartly, G. D., Shutler, J. D., Miller, P. I., &
Yoshikawa, Y. (2016). Estimation of ocean surface currents from maximum
cross correlation applied to GOCI geostationary satellite remote sensing
data over the tsushima (korea) straits. Journal of Geophysical
Research: Oceans, 121(9), 6993–7009. https://doi.org/https://doi.org/10.1002/2016JC011814
Wickham, H. (2015). Advanced r. CRC Press. https://www.oreilly.com/library/view/advanced-r/9781466586963/
Wickham, H. (2016). ggplot2: Elegant graphics for data
analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org
Wickham, H. (2023). Tidyverse: Easily install and load the
tidyverse. https://tidyverse.tidyverse.org
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D.,
François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M.,
Pedersen, T. L., Miller, E., Bache, S. M., Müller, K., Ooms, J.,
Robinson, D., Seidel, D. P., Spinu, V., … Yutani, H. (2019). Welcome to
the tidyverse. Journal of Open Source
Software, 4(43), 1686. https://doi.org/10.21105/joss.01686
Wickham, H., & Bryan, J. (2023). R packages: Organize, test,
document, and share your code. O’Reilly.
Wickham, H., Çetinkaya-Rundel, M., & Grolemund, G. (2023). R for
data science import, tidy, transform, visualize, and model data
(2nd edition). O’Reilly Media.
Wickham, H., Chang, W., Henry, L., Pedersen, T. L., Takahashi, K.,
Wilke, C., Woo, K., Yutani, H., Dunnington, D., & van den Brand, T.
(2024). ggplot2: Create elegant data visualisations using the
grammar of graphics. https://ggplot2.tidyverse.org
Wilkinson, M. D., Dumontier, M., Aalbersberg, Ij. J., Appleton, G.,
Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L.
B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M.,
Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., … Mons, B.
(2016). The FAIR Guiding Principles for scientific
data management and stewardship. Scientific Data,
3(1), 160018. https://doi.org/10.1038/sdata.2016.18
Willert, C. E., & Gharib, M. (1991). Digital
particle image velocimetry. Experiments in Fluids,
10(4), 181–193. https://doi.org/10.1007/BF00190388