add PACE-OBIS notebook - #328
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Could probably skip all of cell[3] to save some STDOUT printing. That was just my testing of earthaccess.search_datasets(). cell[4] does the query we're interested in.
After reviewing cell[4] I recall this was a single time instance query. Is it possible to collect all time instances and generate an average? Then compare that to what we actually observe in OBIS (ie. the pyobis response). Then we can ask the question if the satellite observations match in-situ observations.
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Increasing the time span of the pace request can be quite computational and "bandwith" and heavy. While I agree that for a fair comparison we would need a larger time Windows, the comparison is already qualitative and I don't think it is worth adding that cost to the request.
With that said, we can try to fetch at least 1 year so we can have all seasons and increase the quality of the comparison. How does that sound?
PS: 1 year is ~23.76 G !
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Holy smokes! 24GB! Not worth it. This is a proof of concept. Let's keep it to that one time instance.
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It is still a lot, but I noticed that we have 1 dreegee and 4 km resolutions in the same response. We can filter for the 1 def only.
The question now is, if I understand it correctly, OBIS response is number of observations while PACE is Chlorophyll concentration. How do we compare those? My suggestion would be to normalize each one so both end up between 0-1 and plot the heatmap. Would that work?
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Yeah, we can normalize them to 0-1. We're just using chl-a as a proxy for surface phytoplankton concentration/abundance.
It is still a lot, but I noticed that we have 1 dreegee and 4 km resolutions in the same response. We can filter for the 1 def only.
Yeah! I haven't fully explored the earthaccess.search_data() response to see what all we can work with. I found the first chl-a dataset and ran with that. If there are other datasets that would be more useful/performant, lets use those.
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does this need a review? |
I want to get #333 finished first b/c that will change a bit how we publish notebooks. |
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I see. Okay. |
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@MathewBiddle it should be OK for a first pass. It would be nice to get someone that understands more about chlorophyll to comment here. I'm not really a phyto-person. |
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Thanks @ocefpaf ! I think normalizing from 0-1 isn't the right approach. I think leaving the units as they are and making the colormap on a log scale would be most effective. |
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jotting this down here. Might be useful at some point in the future https://fish-pace.github.io/point-collocation/1_pace_l3/ |
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I guess my mistake there was to use
Let me know your plans here. I can help with the code, but I'll need some help with the bio part for the text and the next steps. |
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That looks better. Not sure what I was hoping for from the FISH-PACE link. We should add some labels to the figures before we publish. |
I'll work on improving the text and labels tomorrow. |
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@MathewBiddle apologies for the delay. I was having trouble trying to come up with a narrative for this notebook. (Sometimes code is easier than writing text to humans). I think I got it though. Let me know what you think! |
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I don't think we need to normalize the data from 0-1. Leave the units as is.
Chlorophyll is used as a proxy measurement for phytoplankton in the water (think the more green the water, the more phytoplankton are present).
I think changing the last plot to
ax = gdfh3.plot(column="n", ax=ax0, legend=True, norm=colors.LogNorm())
gdfh3.plot(column="chlor", ax=ax1, legend=True, norm=colors.LogNorm())
would be fine.
I'll make some edits and send in the changes.
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I made some changes to the plots. I need to review the text as well. This is really close though. |
Working on those changes now... PR soon. |
Oh. You already made all the modifications in the last commit, right? |
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I did. I'll clean up the text now. |
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Okay, I edited the text and added some summary printout info about the OBIS data. I feel good about this now. Feel free to edit as you see fit. |
It is good on my end. Merge when ready! |
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Closes #317