Extract latitude and longitude from rotated coordinate systemCopying netCDF coordinate systemGDAL for Python:...
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Extract latitude and longitude from rotated coordinate system
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I'm new to working with geographic data so please bear with me.
I have the following data:
bnds,projection_x_coordinate,projection_y_coordinate,realization,fog_area_fraction,lambert_azimuthal_equal_area,projection_y_coordinate_bnds,projection_x_coordinate_bnds,forecast_period,forecast_reference_time,time
0,-1158000.0,-1036000.0,12,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1036000.0,13,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1036000.0,14,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1034000.0,12,0.0,-2147483647,-1035000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
from which I would like to determine the appropriate lat/long coordinates. Note that the data is in the RotatedGeogCS format and I have x- and y-projections along with a data value for "Lambert Azimuthal Equal Area" projection.
Does anyone know how to convert from the given data to what I want? Is that even the appropriate question to ask here? The end goal is to present the fog_area_fraction data within the region it has been calculated for.
For those curious this data was extracted from the MOGREPS-UK dataset from AWS, processed using libraries for netCDF, xarray and Iris and then dumped to CSV.
Thanks
netcdf xarray
New contributor
add a comment |
I'm new to working with geographic data so please bear with me.
I have the following data:
bnds,projection_x_coordinate,projection_y_coordinate,realization,fog_area_fraction,lambert_azimuthal_equal_area,projection_y_coordinate_bnds,projection_x_coordinate_bnds,forecast_period,forecast_reference_time,time
0,-1158000.0,-1036000.0,12,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1036000.0,13,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1036000.0,14,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1034000.0,12,0.0,-2147483647,-1035000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
from which I would like to determine the appropriate lat/long coordinates. Note that the data is in the RotatedGeogCS format and I have x- and y-projections along with a data value for "Lambert Azimuthal Equal Area" projection.
Does anyone know how to convert from the given data to what I want? Is that even the appropriate question to ask here? The end goal is to present the fog_area_fraction data within the region it has been calculated for.
For those curious this data was extracted from the MOGREPS-UK dataset from AWS, processed using libraries for netCDF, xarray and Iris and then dumped to CSV.
Thanks
netcdf xarray
New contributor
add a comment |
I'm new to working with geographic data so please bear with me.
I have the following data:
bnds,projection_x_coordinate,projection_y_coordinate,realization,fog_area_fraction,lambert_azimuthal_equal_area,projection_y_coordinate_bnds,projection_x_coordinate_bnds,forecast_period,forecast_reference_time,time
0,-1158000.0,-1036000.0,12,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1036000.0,13,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1036000.0,14,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1034000.0,12,0.0,-2147483647,-1035000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
from which I would like to determine the appropriate lat/long coordinates. Note that the data is in the RotatedGeogCS format and I have x- and y-projections along with a data value for "Lambert Azimuthal Equal Area" projection.
Does anyone know how to convert from the given data to what I want? Is that even the appropriate question to ask here? The end goal is to present the fog_area_fraction data within the region it has been calculated for.
For those curious this data was extracted from the MOGREPS-UK dataset from AWS, processed using libraries for netCDF, xarray and Iris and then dumped to CSV.
Thanks
netcdf xarray
New contributor
I'm new to working with geographic data so please bear with me.
I have the following data:
bnds,projection_x_coordinate,projection_y_coordinate,realization,fog_area_fraction,lambert_azimuthal_equal_area,projection_y_coordinate_bnds,projection_x_coordinate_bnds,forecast_period,forecast_reference_time,time
0,-1158000.0,-1036000.0,12,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1036000.0,13,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1036000.0,14,0.0,-2147483647,-1037000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
0,-1158000.0,-1034000.0,12,0.0,-2147483647,-1035000.0,-1159000.0,1 days 06:00:00.000000000,2019-03-22 19:00:00,2019-03-24 01:00:00
from which I would like to determine the appropriate lat/long coordinates. Note that the data is in the RotatedGeogCS format and I have x- and y-projections along with a data value for "Lambert Azimuthal Equal Area" projection.
Does anyone know how to convert from the given data to what I want? Is that even the appropriate question to ask here? The end goal is to present the fog_area_fraction data within the region it has been calculated for.
For those curious this data was extracted from the MOGREPS-UK dataset from AWS, processed using libraries for netCDF, xarray and Iris and then dumped to CSV.
Thanks
netcdf xarray
netcdf xarray
New contributor
New contributor
New contributor
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aquaaqua
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