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Planning and Collaborative Space for Science @ Scale Project
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Scenario #2: Calculating heat index from temperature and relative humidity #2

Open erogluorhan opened 3 years ago

erogluorhan commented 3 years ago

This scenario is based on NCL function heat_index_nws.

Development Steps:

  1. Implement heat_index_nws (in GeoCAT-comp directly): The function heat_index_nws seems to be a pure NCL function (i.e. does not contain Fortran implementation) so that we would need to implement it as pure python in GeoCAT-comp.

  2. Implement the scenario in Jupyter notebook that imports GeoCAT-comp's heat_index_nws implementations and handles whatever the scenario consists of as a workflow. @sethmcg please let us know if you have any thoughts/preferences on what this scenario should look like (e.g. what datafile we should use, algorithm flow, what plot type would best fit, etc.)

@jeffdlb and @NCAR/science-at-scale members, please let us know if you have any concerns/questions/corrections for these steps.

Estimated Deployment: March 31st, 2021

sethmcg commented 3 years ago

See issue 1 for example data suggestions. An analysis for this issue would be to calculate heat index for daily values, calculate the average number of days per year above some threshold like 100 or 105 F, and plot those as maps. Maybe also a timeseries plot for a few locations corresponding to big cities with the threshold value overlaid?