FlowSieve: A Coarse-Graining Utility for Geophysical Flows on the Sphere
Description
The core features of `FlowSieve` are:
1) computes coarse-grained scalar and vector fields for arbitrary filter scales, in both Cartesian and spherical coordinates,
2) built-in diagnostics for oceanographic settings, including kinetic energy (KE), KE cascades, vorticity, divergence, etc.,
3) built-in post-processing tools compute region averages for an arbitrary number of custom user-specified regions [ avoiding storage concerns when handling large datasets ], and
4) includes Helmholtz-decomposition scripts to allow careful coarse-graining on the sphere [ i.e. to maintain commutativity with derivatives ].
`FlowSieve` is written in C++, with some user-friendly Python scripts included.
Input and output files are netCDF.
`FlowSieve` is designed with heavy parallelization in mind, as well as several context-based optimizations, in order to facilitate processing high-resolution datasets.
In particular, MPI is used to divide time and depth [ with minimal communication costs, since coarse-graining is applied at each time and depth independently ], while OpenMP is used to parallelize latitude and longitude loops, taking advantage of shared memory to reduce communication overhead.
Files
FlowSieve.zip
Files
(4.0 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:db60b1396313d542017327fb57c29a6f
|
4.0 MB | Preview Download |
Additional details
Related works
- Is continued by
- Software: https://github.com/husseinaluie/FlowSieve (URL)
- Is supplemented by
- Software documentation: https://flowsieve.readthedocs.io/en/latest/ (URL)
References
- Aluie, H. (2019). Convolutions on the sphere: commutation with differential operators. GEM - International Journal on Geomathematics, 10(1), 9. , 9. https://doi.org/10.1007/s13137- 019- 0123- 9
- Aluie, H., Hecht, M., & Vallis, G. K. (2018). Mapping the Energy Cascade in the North Atlantic Ocean: The Coarse-graining Approach. Journal of Physical Oceanography, 48, 225–244. https://doi.org/10.1175/JPO-D-17-0100.1
- Balwada, D., Xie, J.-H., Marino, R., & Feraco, F. (2022). Direct observational evidence of an oceanic dual kinetic energy cascade and its seasonality. http://arxiv.org/abs/2202.08637
- Frisch, U. (1995). Turbulence: The Legacy of A.N. Kolmogorov. Cambridge University Press. https://doi.org/10.1017/CBO9781139170666
- Grooms, I., Loose, N., Abernathey, R., Steinberg, J. M., Bachman, S. D., Marques, G., Guillaumin, A. P., & Yankovsky, E. (2021). Diffusion-Based Smoothers for Spatial Filtering of Gridded Geophysical Data. Journal of Advances in Modeling Earth Systems, 13(9), 1–24. https://doi.org/10.1029/2021MS002552
- Loose, N., Abernathey, R., Grooms, I., Busecke, J., Guillaumin, A., Yankovsky, E., Marques, G., Steinberg, J., Ross, A. S., Khatri, H., Bachman, S., Zanna, L., & Martin, P. (2022). GCM-filters: A python package for diffusion-based spatial filtering of gridded data. Journal of Open Source Software, 7(70), 3947. https://doi.org/10.21105/joss.03947
- Storer, B. A., Buzzicotti, M., Khatri, H., Griffies, S. M., & Aluie, H. (2022). Global energy spectrum of the general oceanic circulation. Nature Communications, 13(1), 5314. https://doi.org/10.1038/s41467- 022- 33031- 3 DRAF