CODEWITHSUNDEEP
python-3.xweatherpython-xarraymetpy
Matthew Brewer
Matthew Brewer

Reputation: 11

Metpy HRRR Cross Section

I am working on creating cross sections of HRRR model output, I have read in the grib files using xarray with pynio as the engine and then converted this files to netcdf so I can work with them on my windows machine, therefore I am wondering if this is causing these issues.

Here is a what my dataset looks like after reading in the netcdf with xarray: Imgur

After reading in the data I try to follow the Metpy cross section/ Xarray tutorials by parsing the data:

data = ds.metpy.parse_cf()

Which yields this new dataset:Imgur It created the crs coordinate so I assumed it worked somewhat correctly.

Following this I created a contour map of 700mb RH, winds, and elevation(different data set) where I parsed the RH from the data dataset and also pulled out the x and y

RH = data.metpy.parse_cf('RH_P0_L100_GLC0')
x, y = RH.metpy.coordinates('x', 'y')

This all worked and I could produce a nice looking plot no problem. So next I wanted to make a cross section. Following the example in the documentation:

start = (40.3847, -120.5676)
end = (39.2692, -122.3784)
cross = cross_section(data, start, end)

which gave these errors:Imgur

So then I instead tried using the RH variable from above since

RH.metpy.x

gave the x-dimension. But running

cross = cross_section(RH, start, end)

gave this error instead:Imgur

So I'm just wondering if I missed a step in parsing the original dataset or if the grib to netcdf conversion messed something up or if this is even possible using metpy?

In general I am just working towards creating a cross section like the one in the example: https://unidata.github.io/MetPy/latest/examples/cross_section.html#sphx-glr-examples-cross-section-py

As a bonus question would it be possible to fill terrain under the plots?

Upvotes: 1

Views: 1518

Answers (2)

S.Kociok
S.Kociok

Reputation: 169

I have nearly the same problem.

ValueError: Data missing required coordinate information. Verify that your data have been parsed by MetPy with proper x and y dimension coordinates and added crs coordinate of the correct projection for each variable.

if i try this:

cross = cross_section(data, start, end)

the xarray looks like this:

<xarray.Dataset>
Dimensions:           (bnds: 2, height: 61, height_2: 1, height_3: 60, height_4: 61, height_5: 1, lat: 101, lev: 1, lev_2: 1, lev_3: 1, lon: 121, time: 24)
Coordinates:
  * height            (height) float64 1.0 2.0 3.0 4.0 ... 58.0 59.0 60.0 61.0
  * height_3          (height_3) float64 1.0 2.0 3.0 4.0 ... 57.0 58.0 59.0 60.0
  * lev               (lev) float64 0.0
  * lev_2             (lev_2) float64 400.0
  * lev_3             (lev_3) float64 800.0
  * lon               (lon) float64 -30.0 -29.5 -29.0 -28.5 ... 29.0 29.5 30.0
  * lat               (lat) float64 -10.0 -9.5 -9.0 -8.5 ... 38.5 39.0 39.5 40.0
    crs               object Projection: latitude_longitude
  * height_2          (height_2) float64 10.0
  * time              (time) float64 2.017e+07 2.017e+07 ... 2.017e+07 2.017e+07
  * height_4          (height_4) float64 1.0 2.0 3.0 4.0 ... 58.0 59.0 60.0 61.0
  * height_5          (height_5) float64 2.0
Dimensions without coordinates: bnds
Data variables:
    height_bnds       (height, bnds) float64 ...
    height_3_bnds     (height_3, bnds) float64 ...
    lev_bnds          (lev, bnds) float64 ...
    lev_2_bnds        (lev_2, bnds) float64 ...
    lev_3_bnds        (lev_3, bnds) float64 ...
    z_ifc             (height, lat, lon) float32 ...
    topography_c      (lat, lon) float32 ...
    fis               (lat, lon) float32 ...
    con_gust          (time, height_2, lat, lon) float32 ...
    gust10            (time, height_2, lat, lon) float32 ...
    u                 (time, height_3, lat, lon) float32 ...

I mean there is a lat lon grid... is there a workaround to use the cross_section for a lat lon grid? or can i rename the lat lon to x and y?

Best

Upvotes: 0

Jon Thielen
Jon Thielen

Reputation: 489

Currently, MetPy's cross section interpolation relies on the x and y dimensions being present in the Dataset/DataArray as dimension coordinates (see the description in xarray's documentation here). In your dataset, the x and y dimensions of ygrid_0 and xgrid_0 are listed as dimensions without coordinates, hence the problem.

However, since this situation is commonly encountered in meteorological data files, MetPy's current implementation may be too stringent. I would suggest opening an issue on MetPy's issue tracker.

In regards to your bonus question, so long as you have terrain level data in the same vertical coordinate as your data, you can use the fill_between() method in matplotlib to fill in terrain under the plots.

Upvotes: 1

Related Questions