Ideas for new features and examples

Some of the ideas listed below are good candidates for individual or team projects or theses.

Physics:

• mixed-phase processes
• water isotopologues
• radiative transfer
• cloud biology: https://acp.copernicus.org/articles/20/1777/2020/acp-20-1777-2020.html
• breakup
• Ouzo (Ostwald ripening)
• kernel specification using Copulae
• turbulent kernels
• drop temperatures
• diffusion kinetics as in eq. 9 G&T'21: https://acp.copernicus.org/articles/21/4059/2021/
• add checks for mass conservation in dry radius discretisation (if we are discretising number distribution, in the example (or even within initialisation logic) we should be able to impose a threshold on the acceptable level of incurred mass difference (between the one obtainable via moments of dry volume and the analytical value stemming from lognormal distribution parameters))

Chemistry:

• support for >0D (not aware of any major reason it should not work!)
• reproduce 2D setup simulations from J&P (but also Schmeller & Geresdi '19)
• @njit for all methods
• numba.prange where possible
• better than Explicit Euler in oxidation
• take Henry coefficients and other constants from chempy?
• GPU support

New examples:

• sub-stepping issue described in appendix B of UWLCM paper: https://www.geosci-model-dev.net/12/2587/2019/#section9
• figures from "An elementary parcel model with explicit condensation and supersaturation" by Rogers (1975, https://doi.org/10.1080/00046973.1975.9648397)
• Fig 4a from Wang & Grabowski 2009 as parcel coalescence example (https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/asl.210)
• comparison against Bott's algorithm solution: https://www2.meteo.uni-bonn.de/forschung/gruppen/tgwww/people/abott/fortran/fortran_english.html
• external vs. internal mixing (needs adding hygroscopicity as attribute), example e.g. from Arabas & Pawlowska 2011 (GMD)
• new Hoppel gap examples, see MoAC wiki
• the stat-phys & F-P papers - see MoAC wiki
• Unterstrasser box and column examples
• Jensen & Nugent example
• 2nd kinematic framework from Szumowski's paper
• 2d spectral turbulence kinematic example from Pinsky et al. 2008
• fog case
• parcel output on metpy plots (CAPE?)
• lognormal shape preservation under collisions
• CCNC instrument
• Venus clouds
• cloud seeding example
• spurious supersaturation
• sol-gel transition
• oil in water
• plankton
• human speech droplets: http://dx.doi.org/10.1111/ina.12737
• https://www.nature.com/articles/s41598-021-89346-6
• co-condensation: https://www.nature.com/articles/ngeo1809

Unit test ideas

• two-sd ripening test case
• n=0 energy conservation test for parcel
• unit test checking precipitation from other than lowest grid cell
• 32-bit multiplicity overflows (see xfail in Berry smoke test)

Performance:

• employ MergeShuffle for parallel permutations (https://github.com/axel-bacher/mergeshuffle)
• lookup tables for speeding up physics
• moments, moments, moments
• use atomicAdd in Numba flag_precipitated
• introduce times_max? (one loop less on GPU)
• padding of arrays for ThrustRTC: idx size and relative storages sizes should be a multiple of 32 to ensure that all data of 1 super-droplets are in one GPU memory bank to avoid serialization
• rethink if gamma vector should not be of integer type
• gradually decrease the amount of shuffled numbers during adaptive coalescence substeps
• parallel random shuffling on CPU (np.random.rand() within numba.prange), hint: https://github.com/numba/numba/issues/2486#issuecomment-320089562

Non-physics new features/refactors:

• create pytest plugin for checking TODO annotations (currently almost the same code is in four repos: PySDM, PySDM-examples, PyMPDATA, PyMPDATA-examples); also obsolete dependency on ghapi; technical hints could be taken from https://github.com/nschloe/pytest-codeblocks
• serialization of Particles to enable simulation restarts
• logging layer (https://docs.python.org/3/library/logging.html)
• PM10, PM2.5 products
• mass-doubling spectral discretisation
• new GPU backend using CuPy (https://cupy.dev/)
• kernel density estimate for spectrum (sec. 5.1.4 in Shima et al. '09)
• 16-bit floating point option?
• common logic for cell-wise "foreach"

Visualisations, interactive notebooks, etc:

• enhance out-of-the box settings in Paraview (netCDF output)
• kernel plots
• droplets in space with vtk-js: https://kitware.github.io/vtk-js/examples/
• more controls in kinematic 2D GUI: spin-up, random seed, terminal velocity choice, kernel choice, backend choice, aerosol spectrum parameters, parallelisation controls, products, initialisation controls (constant multiplicity, ...)

New CI features (most also applies to PyMPDATA):

• pypi deployment (using twine)
• Apple M1 runs
• pytest-parallel: https://pypi.org/project/pytest-parallel/
• GPU-enabled runs: https://github.com/jfpanisset/cloud_gpu_build_agent
• parallel=False run on Github Actions
• pylint & mypy within CI script
• use pytest-check-links on GA for checking links in README and notebooks: https://github.com/jupyterlab/pytest-check-links
• assertions for execution times (e.g. for testing numba version bumps)

Packaging, dissemination, etc:

• conda package