greetings

[Tamirat B. JImma]

Hello ESA pyCPT community! This is Tamirat from Ethiopia.

[Tamiru Kebede]

Hi

I am happy to join this group

[Benjamin Kwenda]

Hie to you all. I am Benjamin from Zimbabwe

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Benjamin M Kwenda

Agriculture Meteorologist

Long Range Forecasting

Meteorological Services Department

Belvedere, Harare

(+263) 773504696

Skype: bkwenda_1

Scientists of today think deeply instead of clearly. One must be sane to think clearly, but one can think deeply and be quite insane!!!!- Nikola Tesla

[Godwin Ayesiga]

Hi Tamirat,

Thank you for this initiative.

Regards,

Godwin

On Sat, Oct 8, 2022 at 10:45 AM Tamirat B. JImma <atomic...@gmail.com> wrote:

Hello ESA pyCPT community! This is Tamirat from Ethiopia.

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[Tamirat Bekele]

Hi Godwin,

No problem at all.

Regards,

Tamirat
from my phone

[Celio Matuele]

Great idea guys. 

I am Celio.

Lets connect trough the group.

Asante sana.

A sábado, 8/10/2022, 12:45, Tamirat B. JImma <atomic...@gmail.com> escreveu:

Hello ESA pyCPT community! This is Tamirat from Ethiopia.

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[Jonas Zucule]

Hi to you alll;

I'm Jonas Zucule (JZ), thank you for having this forum, now on, we are connected.

Regards

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                  Do not judge people about what they do

                   but from their heart and attitude.

                                             JZ            

                                             

On Sat, Oct 8, 2022 at 11:45 AM Tamirat B. JImma <atomic...@gmail.com> wrote:

Hello ESA pyCPT community! This is Tamirat from Ethiopia.

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[Celio Matuele]

Hello Tamirat.

I was wondering if it is possible to extract/save probabilistic forecast information to plot our own maps as we usually do with the ordinary CPT as below.

Best regards.

On Sat, Oct 8, 2022 at 11:45 AM Tamirat B. JImma <atomic...@gmail.com> wrote:

Hello ESA pyCPT community! This is Tamirat from Ethiopia.

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[Tamirat Bekele]

Hi Celio,

Sure, it is possible to do that. Please take a look at the following snippet of code; it is part of the notebook I shared during the training:

figInstance, axisInstance = ce.view_probabilistic(pr_fcst.where(pr_fcst > prob_missing_value_flag).rename({'C':'M'}).isel(T=-1) / 100)

axisInstance.add_feature(countryShape)
axisInstance.add_feature(regionShape)

#apply the mask here
axisInstance.contourf(lons,lats, np.where(mask,0,np.nan), cmap='Greys')

figName = MOS + '_ensemble_probabilisticForecast.png'
plt.savefig(Path.home() / "Desktop" / caseDir / domainFolder / "figures" / figName, bbox_inches='tight')

The first line gets the figure and axis instance from the 'cpt extra' module 'view' function; thus, you can apply your country and county shapefiles on this axis (i.e., axisInstance). You can also apply the 'mask' on this axis and hide other regions outside your country's boundary (or any region defined by your custom shapefile). Finally, you can save the figure using the matplotlib (which is imported as 'plt' here) 'savefig' function as indicated in the above code. I hope this helps.

Happy forecasting!

best,

--

Tamirat B. Jimma

Addis Ababa University,
Institute of Geophysics, Space Science and Astronomy (IGSSA)
King George VI St. P.O.Box 1176
Addis Ababa, Ethiopia.

Cell: +251911152860
Skype: tamirat.bekele

[Celio Matuele]

Hi Tamirat.

Thank you very much for replying to my email!

I am not happy with the answer because I am wondering about how to extract/save the data file (maybe file.txt, file.nc., file.tsv, whatever)

which produces the probabilistic forecast figure (PNG).

Best regards,

Celio.

[Jemal Ahmed]

Hi Celio, 

You can save the data in NetCDF format using a line of xarray code. You can also check in the recently shared notebook. 

nextgen_skill.to_netcdf(outputDir /  (MOS +  '_'  + target  + '_nextgen_skill.nc'))
pr_fcst.to_netcdf(outputDir /  (MOS +  '_'  + target +  '_ensemble_probabilisticForecast.nc'))

det_fcst.to_netcdf(outputDir /  (MOS +  '_'  + target + '_ensemble_DeterministicForecast.nc'))

I hope it helps.

Best,

Jemal

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