Timeline for I have a series of netcdf files of sst data. I want to compute sst gradient to locate the oceanic front
Current License: CC BY-SA 4.0
Post Revisions
10 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jan 18, 2020 at 10:17 | comment | added | hasna | the selected sst is taken as latitude below 40 degree and it is having shape of (72, 600, 4320). the sst_gradient is computed using np.gradient::sst_gradient= np.gradient(selected_sst.values,float(dy)*1e3,edge_order=2, axis=1). it is having a length of (72). | |
| Jan 17, 2020 at 7:01 | comment | added | kmuehlbauer |
You would need to add some information about the source data (shape, dimensions etc), How should we know otherwise why you are facing these problems. For xarray.Datasets the output of ds.info() would be nice, So the output of sst_selected.info() would be interesting, as well as information about sst_gradient.
|
|
| Jan 14, 2020 at 7:03 | answer | added | dl.meteo | timeline score: 0 | |
| Jan 13, 2020 at 12:35 | review | Close votes | |||
| Jan 17, 2020 at 0:00 | |||||
| S Jan 13, 2020 at 12:29 | history | edited | Cindy Meister | CC BY-SA 4.0 |
make question more readable
|
| S Jan 13, 2020 at 12:29 | history | suggested | Deepak Patankar | CC BY-SA 4.0 |
make question more readable
|
| Jan 13, 2020 at 11:46 | review | Suggested edits | |||
| S Jan 13, 2020 at 12:29 | |||||
| Jan 13, 2020 at 11:45 | review | First posts | |||
| Jan 13, 2020 at 11:55 | |||||
| S Jan 13, 2020 at 11:42 | review | Triage | |||
| Jan 13, 2020 at 12:33 | |||||
| S Jan 13, 2020 at 11:42 | history | asked | hasna | CC BY-SA 4.0 |