Jupyter Notebook (Use Case 3) for the EOBS dataset - to be reviewed and optimised w/ eqc toolbox #161
Comments
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Hi @Figas23, It looks like you haven't been using the VM. More importantly, you're running an outdated version of the EQC software. The latest version now relies on earthkit-data, the official ECMWF library, whereas you're still using emohawk, which has been deprecated by ECMWF. When we migrated to the new VM a few months ago, we ensured that all existing notebooks were cached to use earthkit. I recommend either updating your environment and clearing the cache or switching to the VM. One of the VM's benefits is that it provides the correct environment, so you don't have to deal with your own installations. I plan to start working on this notebook later today or tomorrow. I immagine the data is not yet cached on the VM, so downloading everything could take some time. |
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Hello @malmans2 Thank you for the suggestions. I will follow them. |
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Hi @Figas23, I'm going through the code before I start working on it, and I noticed there's some interpolation of ERA5 data. Is that actually necessary? It seems like you’re only comparing time series and not calculating biases. Could we just cache the reduced ERA5 time series without interpolating? |
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Also, the notebook downloads era5 wind speed data, but those data are never used. |
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Hey @malmans2 We change our approach and we won't be using wind speed data in this notebook. You can remove those variables |
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What about the interpolation? I have a question about this plot: The title mentions 'Minimum precipitation,' but the code is actually using the mean precipitation. Is this the intended behavior? |
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One more questions. The maps compared are using different colorbars. |
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Hello @malmans2 Regarding the maps, yes, they are supposed to be using the same colorbar (this way is easier to compare for different seasons) |
OK, maybe the plot title is a little misleading as it's not obvious you are comparing the mean values, not the max/min values.
OK, I assume the same applies to the bins used to build the PDF? At the moment, your code uses different bins as it depends on the max/min values of each single plot. |
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Yes we still have to work on titles, descriptions and comments. Yes the same applies to the bins for the PDF |
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OK, I think I have everything I need. I still need a couple of info about the ERA5 processing though:
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Actually, another question. Some of the analyses use spatial weighted means, whereas others use regular means (e.g., the last section). Is this the intended behavior? I.e., do we need to cache both unweighted and weighted means? |
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Also, the section where the data is organised in periods uses data from 1951 to 2020, whereas the timeseries used after is from 1950 to 2020. Is this done on purpose? Should they use the same time periods? I.e., can we parametrise it instead of hardcoding it? |
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I have completed the first draft of the template. A few comments:
The notebook is already cached on the VM:
Let me know! |
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Hey @malmans2 Regarding your questions:
Meanwhile I took a look at the notebook and it looks great and all the analysis we wanted to do were there. Let me know. |
Why do you have this line in your code?
This is not implemented in your notebook yet, right? |
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Well @malmans2 our idea was to download all available timestamps and then resample by day in order to get sum of the precipitation for a given day. We do it using this code: ds_ERA5 = ds_ERA5['tp'].resample(time='1D').sum(dim='time') It is already implemented. Its just an interpolation so that the 2 datasets E-OBS and ERA5 have matching resolution: |
I see. Are you aware of this dataset? https://cds.climate.copernicus.eu/datasets/derived-era5-single-levels-daily-statistics
Yes, I’ve seen the interpolation, but my question is: can we avoid it? For example, where in your code do you need climatology maps? If there’s another reason for it, that’s fine, and I’ll try to optimise it. Otherwise, I think we can simply cache the spatially weighted means of ERA5 without interpolation. |
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ECMWF informed me that daily sums haven't been implemented yet, but they are working on it. In the meantime, let’s compute them ourselves. |
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Hi @Figas23, I've finalised the template. Here is a few comments:
Everything is already cached on the VM!
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Hi @Figas23, This issue has been inactive for a while. Do you need any further assistance, or should I go ahead and close it? |
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Hi there! Happy new year! OK, no problem. The reason I’m keen on closing issues is that we use GitHub issue stats to track progress and submit reports for our deliverables. Sometimes, issues become stale simply because evaluators don’t confirm they can be closed after the work is done. But we’ve successfully closed most issues so far, so we’re happy to leave this one open a bit longer. |
Notebook description
Insitu wind and precipitation completeness for climate monitoring
Use Case: Impact of climate change on precipitation over the Iberian Peninsula.
User Question: How consistent are the estimates of precipitation trends from E-OBS compared to those from reanalysis products?
Method: ERA5 and E-OBS daily precipitation sum (RR) from the latest available versions available, shall be used to calculate: (i) the probability density function of each alternative 30-year period (i.e., 1951-1980, 1961-1990, 1971-2000, 1981-2010, 1991-2020); (ii) the amount of days accounting for the tails of the distribution, i.e., annual count of days when RR >=10mm, (as defined by the WMO Expert Team on Climate Change Detection Indices, ETCCDI) and (iii) the corresponding maps. These maps will be compared to disclose if RR extremes are shifting in terms of mean and the distribution's tails. These results shall be compared in the two datasets.
Notebook link or upload
C3S2_D520.5.3.14b_Quality_Assessment_User_Questions_EOBS_UQ3_v1.6.zip
Anything else we need to know?
No response
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