Pre process - xiyutailang1101/Freeze-thaw_SMAP_ASCAT GitHub Wiki

Pre_process of ASCAT and SMAP data (Point)

1. Read_radar.radar_read_main()

Save SMAP L1C product corresponds to each station, as SMAP_XXX_X_YYYYmmdd.h5, XXX: site id, X: orbit, find this in spt_rs_read.py

2. Read_radar.read_tb2txt()

Read data from processed SMAP L1C product for a period, and saved in .txt file, as tb_XXX_X_YYYY, the attributes depends on keyword attribute_name.

3. Read_radar.getascat()

Read data from ASCAT data corresponds tp each station, as ascat_YYYYmmdd_XXX.npy, XXX: site id.

     Current save path is "result_05_01/tp_site_ascat/"

4. spt_quick.ascat_point_plot()

Read data from processed ASCAT data for a time period, as ascat_sXXX_YYYY.npy

Process of ASCAT and SMAP data (Alaska)

1. Read_radar.read_ascat_alaska()

Read ascat 12.5 km backscatter for the region of Alaska, as ascat_YYYY_alaska.npy

2. spt_quick.ascat_area_plot2()

Resample the daily Alaska backscatter into fixed grid system Output includes:

• resampled backscatter

• resampled incidence angle

• resampled and angular-normalized backscatter

• mask of resampled backscatter

  2.2. data_process.ascat_alaska_onset()

  calculate the onset using ASCAT observations of AK, save in forms of 3-d array
  

3. test_def.read_alaska()

Read SMAP L1C into txt files, txt_xyzYYYY.mm.dd.npy

4. spt_quick.smap_area_plot()

Resample the daily Alaska to the fixed grid system, so you do something like::

#  An EASE grid 2.0 system, with 36 km, North pole projection. Given a grid system based on coordinate X and Y  
   From the grid. X or Y is one by N array.
#  Resampled daily SMAP observation to location (X, Y) with a distance of 27 km
#  Assign the resampled value to where they located in EASE grid 2.0 system. The location index is ~ease_lon.mask

-https://github.com/xiyutailang1101/Freeze-thaw_SMAP_ASCAT/blob/master/spt_quick.py::