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… a single POD is run
… and create zonal means
…in directory name
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This pull request introduces 628 alerts when merging b41168c into 858303d - view on LGTM.com new alerts:
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Add atmos variables to the diag table Note that this currently generates variables required for the MJO_suite POD using GFDL standard output more variables may be required for the other PODs. It is also preferable to output in CMIP6 format
…iagnostics into feature/ETC-composites
…osites merged with develop branch
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This pull request introduces 628 alerts when merging 5cbaaf3 into 748d6da - view on LGTM.com new alerts:
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This pull request introduces 132 alerts when merging 5718729 into 748d6da - view on LGTM.com new alerts:
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This pull request introduces 107 alerts when merging 8697263 into 748d6da - view on LGTM.com new alerts:
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This pull request introduces 85 alerts when merging 6d5460c into 748d6da - view on LGTM.com new alerts:
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This pull request introduces 74 alerts when merging 7f9732c into 748d6da - view on LGTM.com new alerts:
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Hi @jeyavinoth, checking if you are still able to contribute to this PR? It looks like your code had some outstanding issues that must be addressed before it can be merged. |
@ahmedfiaz I haven't worked on this in a long while. Please follow up with @jfbooth (Jimmy Booth from CCNY) |
This is a preliminary version of the POD that tracks extra tropical cyclones and computes cyclone centered composites.
Summary:
The Extratropical cyclones are identified with the Modeling, Analysis and Prediction (MAP) Climatology of Midlatitude Storminess (MCMS) algorithm (Bauer et al. 2016) which uses 6-hourly gridded sea level pressure fields to locate storm centers and then track them through the cyclone lifetime. This algorithm has historically been used to create a database of cyclone locations using the ERA-Interim reanalysis (Dee et al. 2011). The MCMS algorithm is also applied to the model and re-analysis sea level pressure fields. We generate cyclone centered composites of cloud cover, as well as other atmospheric variables, over multiple instances of the same type of atmospheric phenomenon to compare the models with observations or reanalysis. The is a plan view as a passive instrument would observe. This method presents a great advantage for model evaluation as they allow multiple cases to be included and do not necessitate a match in time and space between the free running models and observations.