swirlspy.sat.h8 package

Himawari-8 data loader.

swirlspy.sat.h8.read_h8_data(data_dir: str, base_time: pandas._libs.tslibs.timestamps.Timestamp, area: Tuple[float, float, float, float], grid_size: Tuple[float, float], nn_dir: str = None, mode: swirlspy.sat.h8._read_h8.Mode = <Mode.Blended: 3>) → xarray.core.dataarray.DataArray

Parse Himawari-8 data files to reflectivity. (filename in format HS_H08_{date}_{time}_B{channel:02}_FLDK_R{rsol:02}_S{seg:02}10.DAT). Returns an xarray.DataArray.

Parameters:
  • data_dir (str) – Directory path which is containing required H8 data. **H8 file name format: HS_H08_{date}_{time}_B{channel:02}_FLDK_R{rsol:02}_S{seg:02}10.DAT **Files must be included channel 3 (resolution = 5); 4, 5, 8, 10, 13, 15 (resolution = 20)
  • base_time (pandas.Timestamp) – Date time of required data.
  • area ((float, float, float, float)) – Interested area in WGS-84 (latitude_from, latitude_to, longitude_from, longitude_to).
  • grid_size ((float, float)) – Latitude and longitude step size between each point (latitude_step, longitude_step).
  • nn_dir (str, optional) – If nn_dir is not None, it will use as the directory of neural network weight files (day.net, transform_tabDAY.txt, night.net, transform_tabNIGHT.txt). Otherwise default weight files will be used. Default : None
  • mode (swirlspy.sat.H8_ReaderMode, optional) – Reader mode is used. Default : Blended
Returns:

Parsed data with coordinate in (‘time’, ‘y’, ‘x’) in WGS-84.

Return type:

xarray.DataArray

swirlspy.sat.h8.H8_ReaderMode

alias of swirlspy.sat.h8._read_h8.Mode