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CalibrateEDMF.jl

Calibrate atmospheric turbulence and convection parameterizations using gradient-free ensemble Kalman methods.
https://github.com/CliMA/CalibrateEDMF.jl

Last synced: about 3 hours ago
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A package to calibrate atmospheric turbulence and convection parameterizations using gradient-free ensemble Kalman methods

README

        

## CalibrateEDMF.jl

A package to calibrate atmospheric turbulence and convection parameterizations using gradient-free ensemble Kalman methods.

The rationale behind the calibration framework implemented in this package is thoroughly described in our paper:

Lopez-Gomez, I., Christopoulos, C., Langeland Ervik, H. L., Dunbar, O. R. A., Cohen, Y., Schneider, T. (2022) **Training physics-based machine-learning parameterizations with gradient-free ensemble Kalman methods**, *Journal of Advances in Modeling Earth Systems*, 14(8), e2022MS003105. [doi](https://doi.org/10.1029/2022MS003105)

If you use this package for your own research, or find any of the ideas presented useful, please cite our work. The article also includes results for an extended eddy-diffusivity mass-flux (EDMF) closure of turbulence and convection trained using this package. The EDMF scheme is implemented in [TurbulenceConvection.jl](https://github.com/CliMA/TurbulenceConvection.jl), and described in the following papers:

Cohen, Y., Lopez-Gomez, I., Jaruga, A., He, J., Kaul, C., and Schneider, T. (2020) **Unified entrainment and detrainment closures for extended eddy-diffusivity mass-flux schemes.** *Journal of Advances in Modeling Earth Systems*, 12, e2020MS002162. [doi](https://doi.org/10.1029/2020MS002162)

Lopez-Gomez, I., Cohen, Y., He, J., Jaruga, A., Schneider, T. (2020) **A generalized mixing length closure for eddy-diffusivity mass-flux schemes of turbulence and convection.** *Journal of Advances in Modeling Earth Systems*, 12, e2020MS002161. [doi](https://doi.org/10.1029/2020MS002161)

For further details on how to use CalibrateEDMF, consult the [documentation](https://CliMA.github.io/CalibrateEDMF.jl/dev/).

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|---------------------:|:----------------------------------------------|
| **Documentation** | [![dev][docs-latest-img]][docs-latest-url] |
| **DOI** | [![DOI][zenodo-img]][zenodo-latest-url] |
| **Docs Build** | [![docs build][docs-bld-img]][docs-bld-url] |
| **GHA CI** | [![gha ci][gha-ci-img]][gha-ci-url] |
| **Code Coverage** | [![codecov][codecov-img]][codecov-url] |

[zenodo-img]: https://zenodo.org/badge/DOI/10.5281/zenodo.6382864.svg
[zenodo-latest-url]: https://doi.org/10.5281/zenodo.6382864

[docs-latest-img]: https://img.shields.io/badge/docs-latest-blue.svg
[docs-latest-url]: https://CliMA.github.io/CalibrateEDMF.jl/dev/

[docs-bld-img]: https://github.com/CliMA/CalibrateEDMF.jl/actions/workflows/docs.yml/badge.svg
[docs-bld-url]: https://github.com/CliMA/CalibrateEDMF.jl/actions/workflows/docs.yml

[gha-ci-img]: https://github.com/CliMA/CalibrateEDMF.jl/actions/workflows/ci.yml/badge.svg
[gha-ci-url]: https://github.com/CliMA/CalibrateEDMF.jl/actions/workflows/ci.yml

[codecov-img]: https://codecov.io/gh/CliMA/CalibrateEDMF.jl/branch/main/graph/badge.svg
[codecov-url]: https://codecov.io/gh/CliMA/CalibrateEDMF.jl

### Requirements

Julia version 1.5+

# Installation

To use latest version of this package, clone this repository

>> git clone https://github.com/CliMA/CalibrateEDMF.jl.git

To use the latest stable release, you can install the package on your Julia environment:

>> julia
>> julia> using Pkg; Pkg.add("CalibrateEDMF")

In order to use the package, compile the project first.

>> julia --project

>> julia> ]

>> pkg> instantiate

# Installation in dev mode (advanced)

Since both `TurbulenceConvection.jl` and `EnsembleKalmanProcesses.jl` are under rapid development, we may want to access a recent unpublished version of these packages when working with `CalibrateEDMF.jl`, or even use a version with local changes. If this is the case, clone the latest `EnsembleKalmanProcesses.jl` (resp. `EnsembleKalmanProcesses.jl`) version from GitHub (whichever you want to dev with),

>> git clone https://github.com/CliMA/EnsembleKalmanProcesses.jl.git

>> git clone https://github.com/CliMA/TurbulenceConvection.jl

and try the following,

>> julia --project

>> julia> ]

>> pkg> dev path/to/EnsembleKalmanProcesses.jl path/to/TurbulenceConvection.jl

>> pkg> instantiate

This will link CalibrateEDMF to your local version of `EnsembleKalmanProcesses.jl` (resp. `EnsembleKalmanProcesses.jl`), allowing rapid prototyping across packages.


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Committers metadata

Last synced: 24 days ago

Total Commits: 393
Total Committers: 8
Avg Commits per committer: 49.125
Development Distribution Score (DDS): 0.351

Commits in past year: 13
Committers in past year: 2
Avg Commits per committer in past year: 6.5
Development Distribution Score (DDS) in past year: 0.077

Name Email Commits
Ignacio Lopez Gomez i****o@c****u 255
Haakon Ludvig Langeland Ervik 4****e 38
costachris c****a@g****m 34
Charles Kawczynski k****s@g****m 31
CompatHelper Julia c****y@j****g 30
Anna Jaruga a****a@c****u 3
szy21 1****1 1
yairchn y****n@c****u 1

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Last synced: 1 day ago

Total issues: 6
Total pull requests: 126
Average time to close issues: about 1 month
Average time to close pull requests: 25 days
Total issue authors: 5
Total pull request authors: 4
Average comments per issue: 2.33
Average comments per pull request: 1.29
Merged pull request: 48
Bot issues: 0
Bot pull requests: 61

Past year issues: 2
Past year pull requests: 43
Past year average time to close issues: N/A
Past year average time to close pull requests: 2 months
Past year issue authors: 1
Past year pull request authors: 2
Past year average comments per issue: 1.5
Past year average comments per pull request: 0.42
Past year merged pull request: 10
Past year bot issues: 0
Past year bot pull requests: 29

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Package metadata

juliahub.com: CalibrateEDMF

A package to calibrate atmospheric turbulence and convection parameterizations using gradient-free ensemble Kalman methods

  • Homepage:
  • Status: removed
  • Documentation: https://docs.juliahub.com/CalibrateEDMF/YpPQU/
  • Licenses: Apache-2.0
  • Latest release: 0.7.0 (published over 1 year ago)
  • Last Synced: 2024-02-24T16:32:37.193Z (1 day ago)
  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Rankings:
    • Stargazers count: 29.752%
    • Average: 29.752%

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