Packed data is stored in a netCDF file using a smaller data type than the original data, for example, packing doubles into shorts. The netCDF library itself does not do packing and unpacking, but the Java-netCDF library will do automatic unpacking, see class VariableStandardized.

• For each variable with packed data, add two attributes called scale_factor and add_offset, such that

    unpacked_value = packed_value * scale_factor + add_offset
  

• The type of the stored variable is the type of the packed data type, typically byte, short, or int.
• The type of the scale_factor and add_offset attributes should be the type that you want the unpacked data to be, typically float or double.
• To compute the scale and offset for maximum precision packing of a set of numbers, use:

    add_offset = dataMin
    scale_factor = (dataMax - dataMin) / (2^n - 1)
  

  where n is the number of bits of the packed (integer) data type.

  Note: In an earlier version of this page, the scale_factor was incorrectly given as the reciprocal of the above formula.

• To avoid introducing a bias into the unpacked values due to truncation when packing, round to the nearest integer rather than just truncating towards zero:

    packed_value = nint((unpacked_value - add_offset) / scale_factor)
  

• The precision of the data will be 1.0 / scale_factor.
• Example, packing 32-bit floats into 16-bit shorts:

  variables:
    short data(z, y, x) ;
      data:scale_offset = 34.02f ;
      data:add_offset = 1.54f ;
  

2007 Unidata NetCDF Workshop for Developers and Data Providers > Best Practices