retrieval - Retrieval methods for hyperspectral cloud side observations

runmacs.spec.retrieval.cloudside.retrieval.append(self, obj)[source]

Set netCDF4 Variables and Dimensions as atttibutes

Parameters:
  • self – Object of which the attributes should be set
  • obj – netCDF4 Dataset to use
runmacs.spec.retrieval.cloudside.retrieval.eccentricity(day)[source]

Calculate the eccentricity correction factor \(E_0 = (\frac{r_0}{r})^2\) according to Iqbal, page 3. This factor, when multiplied with the irradiance, accounts for the annual variation of the sun-earth-distance.

Parameters:day – day since January 1 (0 … 365)
class runmacs.spec.retrieval.cloudside.retrieval.reffLUT(lut_file, **kwargs)[source]

Look-Up Table for effective radius retrieval

Parameters:
  • lut_file – File from which the Look-Up Table should be loaded
  • cut – set ?some? LUT entries to 0 (see calc_posteriors sourcecode)
  • quiet – If True, show less debug messages
find_nearest(data, metric=None)[source]

Replace the value of invalid ‘data’ cells (indicated by ‘np.nan’) by the value of the nearest valid data cell.

Parameters:
  • data – numpy array of any dimension
  • metric – Distance along each axis of data, can be float, int or sequence.
Returns:

a filled array.
iterate_file(obj, func)[source]

Iterate over members of netCDF4 file

class runmacs.spec.retrieval.cloudside.retrieval.reffRetrieval(lut_object, **kwargs)[source]

Effective radius retrieval

Parameters:lut_object – Look-Up Table to use (a reffLUT object)
calc_mom(pdfs=None, multipeak=None)[source]

Calculate moments of \(r_\textrm{eff}\) profiles.

Parameters:
  • pdfs – Can be output of calc_pdfs(), if None, output of last PDF computation will be used.
  • multipeak –

    If not None, multiple peak detection is performed. Currently the following modes are rupported:
calc_pdf(ch01s, ch02s, bscas, szas, grads=None, sigmas=None, deltas=None, eccen=None)[source]

Calculate \(r_\textrm{eff}\) radius probability distribution function(s).

Each parameter can be an arbitrary dimensional numpy array. These dimensions will be prepended to the output array.

Parameters:
  • ch01s – Radiance values of channel 1
  • ch02s – Radiance values of channel 2
  • bscas –
  • szas – Solar Zenith angle values
  • grads –
  • sigmas –
  • deltas –
  • eccen –
Returns:

\(r_\textrm{eff}\) PDF histogram according to LUT-interanl \(r_\textrm{eff}\) bins.