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!