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python-3.xnetcdfcoordinate-transformationpython-xarraynetcdf4

Using xarray to change coordinate system in order to Slice operation

I am new here. first on all, I am very thankful for your time and consideration. I have 2 questions regarding to managing 2 different netcdf files in python. I searched a lot but unfortunately I couldn't find a solution.

1- I have a netcdf file which has coordinates like below:

time     datetime64[ns] 2016-08-16T22:00:00
* y        (y) int32 220000  ...  620000
* x        (x) int32 20000  ...  720000
 lat      (y, x) float64 dask.array<shape=(401, 701), 
 lon      (y, x) float64 dask.array<shape=(401, 701),

I need to change coords to lon/lat in order that I can slice an area based on specific lon/lat coords (by using xarray). But I don't know how to change x and y to lon lat. here my code:

import xarray as xr
import matplotlib.pyplot as plt
p = "R_201608.nc"
ds = xr.open_mfdataset(p)
q=ds.RR.sel(time='2016-08-16T21:00:00')

2- Similar to 1, I have another netcdf file which has coordinates like below:

   * X           (X) float32 557600.0 .. 579400.0
   * Y           (Y) float32 5190600 ... 5205400.0
   * time        (time) datetime64[ns] 2007-01I

How can I convert x and y to lon/lat system in order that I can plot it in lon/lat system?

Edit related to @Ryan : 1- Yes. this file demonestrates rainfall over a large area. I want to cut it into smaller area -similar area of file related to q2- and compare them uusing bias, RMSE, etc. here is full information related to this file:

 <xarray.Dataset>
  Dimensions:                  (time: 2976, x: 701, y: 401)
  Coordinates:
  * time             (time) datetime64[ns] 2016-08-31T23:45:00
  * y          (y) int32 220000 221000  ... 619000 620000
  * x          (x) int32 20000 21000  ... 719000 720000
  lat        (y, x) float64 dask.array<shape=(401, 701),chunksize=(401, 701)>
  lon        (y, x) float64 dask.array<shape=(401, 701), chunksize=(401, 701)

 Data variables:
    RR       (time, y, x) float32 dask.array<shape=(2976, 401, 701),    chunksize=(2976, 401, 701)>
    lambert_conformal_conic  int32 ...

    Conventions:  CF-1.5

edit related to @Ryan :2- And here it is the full information about the second file (Smaller area):

   <xarray.DataArray 'Precip' (time: 8928, Y: 75, X: 110)>
   dask.array<shape=(8928, 75, 110), dtype=float32, chunksize=(288, 75, 110)>
   Coordinates:

      sensor_height_precip  float32 1.5
      sensor_height_P       float32 1.5
      * X                     (X) float32 557600.0 557800.0 ... 579200.0 579400.0
      * Y                     (Y) float32 5190600.0 5190800.0 ... 5205400.0
      * time                  (time) datetime64[ns]  2007-01-31T23:55:00
   Attributes:
      grid_mapping:         UTM33N
      ancillary_variables:  QFlag_Precip QGrid_Precip
      long_name:            Precipitation Amount
      standard_name:        precipitation_amount
      cell_methods:         time:sum
      units:                mm
Solution

  • In problem 1), it is not possible to convert lon and lat to dimension coordinates, because they are two-dimensional (both have dimension x, y). Dimension coordinates, used for slicing, can only be one-dimensional. If you can be more specific about what you want to do after slicing, we can provide more suggestions about how to proceed. Do you want to select a particular latitude / longitude range and then calculate some statistics (e.g. mean / variance)?

    In problem 2) it looks like you have a map projection. Without more information about the projection, it is impossible to convert to lat / lon coordinates or plot on a map. Is there more information contained in your dataset about the map projection used? Can you post the full output of print(ds)?