Cross Sections in MetPy
(with xarray...and xkcd)
Unidata Summer Internship 2018
Jon Thielen (with Ryan May and John Leeman)
Working on MetPy
- Started contributing in Nov 17'
- Applied in Jan 18'
- Started internship in May
Initial Plans
Another Plan: Cross Sections...
...with xarray!
import xarray as xr
data = xr.open_dataset('irma_gfs_example.nc')
print(data)
<xarray.Dataset>
Dimensions: (isobaric1: 21, isobaric3: 31, latitude: 81, longitude: 131, time1: 9)
Coordinates:
* time1 (time1) datetime64[ns] 2017-09-05T12:00:00 ...
reftime datetime64[ns] ...
* latitude (latitude) float32 50.0 49.5 49.0 ...
* isobaric3 (isobaric3) float64 100.0 200.0 ...
* isobaric1 (isobaric1) float64 1e+04 1.5e+04 ...
* longitude (longitude) float32 250.0 250.5 ...
Data variables:
Vertical_velocity_pressure_isobaric (time1, isobaric1, latitude, longitude) float32 ...
Relative_humidity_isobaric (time1, isobaric3, latitude, longitude) float32 ...
Temperature_isobaric (time1, isobaric3, latitude, longitude) float32 ...
u-component_of_wind_isobaric (time1, isobaric3, latitude, longitude) float32 ...
v-component_of_wind_isobaric (time1, isobaric3, latitude, longitude) float32 ...
Geopotential_height_isobaric (time1, isobaric3, latitude, longitude) float32 ...
LatLon_361X720-0p25S-180p00E int32 ...
Attributes:
Originating_or_generating_Center: ...
Originating_or_generating_Subcenter: ...
GRIB_table_version: ...
Type_of_generating_process: ...
Analysis_or_forecast_generating_process_identifier_defined_by_originating...
Conventions: ...
history: ...
featureType: ...
History: ...
geospatial_lat_min: ...
geospatial_lat_max: ...
geospatial_lon_min: ...
geospatial_lon_max: ...
heights = data['Geopotential_height_isobaric']
heights.sel(time1='2017-09-06T00:00Z',
isobaric3=50000.)
<xarray.DataArray 'Geopotential_height_isobaric' (latitude: 81, longitude: 131)>
array([[5880.9595, 5878.8394, 5876.5195, ..., 5807.9194, 5809.3594, 5810.679 ],
[5884.5596, 5882.3994, 5879.9194, ..., 5821.2393, 5822.7593, 5824.119 ],
[5888.4395, 5885.7993, 5883.2393, ..., 5833.3193, 5834.8794, 5836.2793],
...,
[5871.679 , 5871.719 , 5871.5996, ..., 5894.8394, 5894.5596, 5894.5195],
[5871.2393, 5871.159 , 5871.159 , ..., 5892.8794, 5893.159 , 5893.159 ],
[5870.5195, 5871.119 , 5870.7993, ..., 5891.119 , 5891.7993, 5891.8794]],
dtype=float32)
Coordinates:
time1 datetime64[ns] 2017-09-06
reftime datetime64[ns] ...
* latitude (latitude) float32 50.0 49.5 49.0 48.5 48.0 47.5 47.0 46.5 ...
isobaric3 float64 5e+04
* longitude (longitude) float32 250.0 250.5 251.0 251.5 252.0 252.5 253.0 ...
Attributes:
long_name: Geopotential height @ Isobaric surface
units: gpm
Grib_Variable_Id: VAR_0-3-5_L100
Grib2_Parameter: [0 3 5]
Grib2_Parameter_Discipline: Meteorological products
Grib2_Parameter_Category: Mass
Grib2_Parameter_Name: Geopotential height
Grib2_Level_Type: 100
Grib2_Level_Desc: Isobaric surface
Grib2_Generating_Process_Type: Forecast
grid_mapping: LatLon_361X720-0p25S-180p00E
data['Temperature_isobaric'].mean(
('time1', 'latitude', 'longitude'))
<xarray.DataArray 'Temperature_isobaric' (isobaric3: 31)>
array([259.4611 , 255.66313, 248.79195, 240.33334, 235.54622, 231.1286 ,
223.24205, 218.46536, 213.04253, 208.66364, 204.48088, 209.77391,
219.08775, 229.3075 , 238.7891 , 247.04654, 253.94908, 259.74255,
264.77377, 269.32214, 273.50998, 277.24646, 280.57074, 283.58157,
286.40454, 289.0842 , 291.59814, 292.82648, 294.26868, 295.83304,
297.45053], dtype=float32)
Coordinates:
reftime datetime64[ns] ...
* isobaric3 (isobaric3) float64 100.0 200.0 300.0 500.0 700.0 1e+03 2e+03 ...
(data['Temperature_isobaric'] -
data['Temperature_isobaric'].mean(
('time1', 'latitude', 'longitude')))
<xarray.DataArray 'Temperature_isobaric' (time1: 9, isobaric3: 31, latitude: 81, longitude: 131)>
array([[[[ -1.46109 , ..., -1.161102],
...,
[ 1.738922, ..., -1.161102]],
...,
[[ -7.250519, ..., -10.750519],
...,
[ 1.749481, ..., 1.849457]]],
...,
[[[ -1.661102, ..., -2.861084],
...,
[ 3.03891 , ..., -0.261078]],
...,
[[ -4.150543, ..., -10.450531],
...,
[ 1.949463, ..., 1.949463]]]], dtype=float32)
Coordinates:
* time1 (time1) datetime64[ns] 2017-09-05T12:00:00 ...
reftime datetime64[ns] 2017-09-05T12:00:00
* latitude (latitude) float32 50.0 49.5 49.0 48.5 48.0 47.5 47.0 46.5 ...
* isobaric3 (isobaric3) float64 100.0 200.0 300.0 500.0 700.0 1e+03 2e+03 ...
* longitude (longitude) float32 250.0 250.5 251.0 251.5 252.0 252.5 253.0 ...
Units
Meteorological Calculations
But what about cross sections?
With that out of the way...
Cross sections!
Live Demo Time!
