Conversion to time series format

For a lot of applications it is favorable to convert the image based format into a format which is optimized for fast time series retrieval. This is what we often need for e.g. validation studies. This can be done by stacking the images into a netCDF file and choosing the correct chunk sizes or a lot of other methods. We have chosen to do it in the following way:

  • Store the time series in netCDF4 in the Climate and Forecast convention Orthogonal multidimensional array representation

  • Store the time series in 5x5 degree cells. This means there will be 2448 cell files for global data and a file called, which contains the information about which grid point is stored in which file. This allows us to read a whole 5x5 degree area into memory and iterate over the time series quickly.


This conversion can be performed using the smos_repurpose command line program. An example would be:

smos_repurpose /smos_ic_img_data /timeseries/data 2011-01-01 2011-01-02 --parameters Soil_Moisture --bbox -11 34 43 71

Which would take Soil_Moisture values from SMOS IC images stored in /image_data from January 1st 2011 to January 2nd 2011 and store the values as time series in the folder /timeseries/data.

Keywords that can be used in smos_repurpose:

  • -h (–help) : Shows the help text for the reshuffle function
  • –parameters : Parameters to reshuffle into time series format. e.g. Soil_Moisture. If this is not specified, all parameters in the first detected image file will be reshuffled. Default: None.
  • –only_good : Read only 0-flagged (GOOD) observations (by Quality_Flag), if this is set to False, also 1-flagged (not recommended) ones will be read and reshuffled, 2-flagged (missing) values are always excluded. Excluded values are replaced by NaNs. Default: False.
  • –bbox : min_lon min_lat max_lon max_lat. Bounding Box (lower left and upper right corner) of subset area of global images to reshuffle (WGS84). Default: None.
  • –imgbuffer : The number of images that are read into memory before converting them into time series. Bigger numbers make the conversion faster but consume more memory. Default: 100.

Conversion to time series is performed by the repurpose package in the background. For custom settings or other options see the repurpose documentation .