I have been using the python package xgrads to parse and read a descriptor file with a suffix .ctl which describes a raw binary 3D dataset, provided by GrADS (Grid Analysis and Display System), a widely used software for easy access, manipulation, and visualization of earth science data. I have been using the following code to read the binary data into a xarray.Dataset.
from xgrads import open_CtlDataset
dset = open_CtlDataset('./ur2m_eta40km_2001011312.ctl')
# print all the info in ctl file
print(dset)
<xarray.Dataset>
Dimensions: (time: 553, lat: 36, lon: 30)
Coordinates:
* time (time) datetime64[ns] 2001-01-13T12:00:00 ... 2001-05-31T12:00:00
* lat (lat) float32 -21.2 -20.8 -20.4 -20.0 -19.6 ... -8.4 -8.0 -7.6 -7.2
* lon (lon) float32 -47.8 -47.4 -47.0 -46.6 ... -37.4 -37.0 -36.6 -36.2
Data variables:
ur2m (time, lat, lon) float32 dask.array<chunksize=(1, 36, 30), meta=np.ndarray>
Attributes:
comment: Relative Humidity 2m
storage: 99
title: File
undef: 1e+20
pdef: None
This .ctl file comprises forecast results of humidity, estimated over a predefined area at each 6 hours, from 2001-01-13 12:00:00 hs to 2001-05-31 12:00:00 hs. Plotting the results for the first time step (2001-01-13T12:00:00) I got this:
ds['ur2m'][0,...].plot()
I would like to know if it is possible to create tabular data from this xarray.Dataset and export it as a single .csv or .txt file, following the data structure below:
long lat ur2m time variable datetime
-47.8 -21.2 0 1 ur2m 2001-01-13 12:00:00
-47.4 -21.2 0 1 ur2m 2001-01-13 12:00:00
-47.0 -21.2 0 1 ur2m 2001-01-13 12:00:00
-46.6 -21.2 0 1 ur2m 2001-01-13 12:00:00
... ... ... ... <NA> ... <NA>
-37.4 -7.2 0 553 ur2m 2001-05-31 12:00:00
-37.0 -7.2 0 553 ur2m 2001-05-31 12:00:00
-36.6 -7.2 0 553 ur2m 2001-05-31 12:00:00
-36.2 -7.2 0 553 ur2m 2001-05-31 12:00:00
The original data are available here
