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how are you doing?

I have been working on this for quite a while now, but I am not able to proceed any further. I was given .nc Files with Cloud Based Altitudes (CBA are measurements to indicate the height of clods for a particular area).

For now I am not even able to extract Data for a single Coordinate. This Data contains the area shown in this picture, from the top left to the bottom right:

Area contained in Data

Here is a screenshot of the data I am working with:

enter image description here

Sorry that I can not provide more Data than that, but I don't want to get in trouble.

The cba value is the information I want to extract. So let's say I have a set of coordinates (longitude/latitude) of an area I am interested in, how would I be able to get the appropriate cba values?

I don't need a specific solution, but a direction so I can continue on my own.

For additional information this is how the .cba and .cba.values look:

enter image description here

I have been working with data like that before, but not this nested, so I have absolutely no idea how I can even approach that. Is there a module/package in python which would allow me to easily handle this, so when I put in coordinates for an area it would directly give me the corresponding cba-values?

I hope that is enough information to go on and you can help me, I would really appreciate it.

Regards

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The package you are using (xarray) is already perfectly suited for this task.

dObj is an xarray.Dataset object, each contained variable (such as dObj['cba']) is an xarray.DataArray object.

You can access the data at a given set of coordinates like this:

lat = ...
lon = ...
dObj['cbd'].sel(y=lat, x=lon, method='nearest')

method='nearest' is needed as your coordinate array is unlikely to contain the requested floating point values exactly.

If you instead want to select a range of latitudes and longitudes you can do that as follows:

lat_min, lat_max = (...)
lon_min, lon_max = (...)
dObj['cbd'].sel(y=slice(lat_min, lat_max), x=slice(lon_min, lon_max))

For more information about dealing with xarray objects, have a look at the very comprehensive documentation: http://xarray.pydata.org/en/stable/index.html

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5 Comments

Holy shit, thank you SOOOOOO MUCH. This is EXACTLY what I needed. Oh man I have been working with python for quite a while now, but there is so much I don't yet know and understand. Thank you again.
Hey Jhansen, I have a follow up question. Is it possible to find out which coordinates have been selected when using this function -> dObj['cbd'].sel(y=lat, x=lon, method='nearest') I would like to check some things and need to know how far they are apart and which coordinates have been used.
@Medhusalem Sure, once you have selected the subset you can simply access the .coords attribute of the DataArray to check the x and y coordinate arrays: dObj['cbd'].sel(..).coords.
Ah thank you very much for the answer, I have just figure out that this approach "dObj['cbd'].sel(y=lat, x=lon, method='nearest')" will not really work out for me. Since y and x coordinates are some weird UTM Format. What I really need are the informations contained in the variables longitude and latitude but since they are 2Dimensional, when I use: dObj['cbd'].sel(latitude=lat, longitude=lon, method='nearest') I get an error ValueError: dimensions or multi-index levels ['latitude', 'longitude'] do not exist. It is really starting to get frustrating...
Yes, if you want to select by latitude and longitude but your data is in a different projection then you either have to convert your lat and lon values into the data CRS before using .sel(), or reproject the entire dataset into EPSG:4326 (i.e. lat-lon coordinates)

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