parts.retrieval.a_priori

The retrieval.a_priori sub-module provides modular data provider object that can be used to build a priori data providers.

class parts.retrieval.a_priori.APrioriProviderBase(name, covariance)

Bases: parts.data_provider.DataProviderBase

class parts.retrieval.a_priori.AltitudeMask(lower_limit, upper_limit)

Bases: object

The altitude mask replaces values at grid points outside of the given altitude interval with another value.

class parts.retrieval.a_priori.And(*args)

Bases: object

Creates a combined mask by applying logical and to a list of single masks.

class parts.retrieval.a_priori.DataProviderAPriori(name, covariance)

Bases: parts.retrieval.a_priori.APrioriProviderBase

A priori provider that propagates an atmospheric quantity name as a priori mean profile from the data provider.

class parts.retrieval.a_priori.FixedAPriori(name, xa, covariance, mask=None, mask_value=1e-12)

Bases: parts.retrieval.a_priori.APrioriProviderBase

Returns an a priori profile that does not depend on the atmospheric state.

class parts.retrieval.a_priori.FunctionalAPriori(name, variable, f, covariance, mask=None, mask_value=1e-12)

Bases: parts.retrieval.a_priori.APrioriProviderBase

Returns an a priori profile that does not depend on the atmospheric state.

class parts.retrieval.a_priori.ReducedVerticalGrid(a_priori, grid, quantity='pressure', covariance=None)

Bases: parts.retrieval.a_priori.APrioriProviderBase

class parts.retrieval.a_priori.SensorNoiseAPriori(sensors)

Bases: parts.data_provider.DataProviderBase

Measurement error due to sensor noise.

The SensorNoiseAPriori class constructs a combined observation error covariance matrix from the noise characteristics of a list of sensors.

The noise of particular sensors can be amplified by adding the scaling factor to the noise_scaling attribute of the class.

Attributes:

noise_scaling(dict): Dictionary mapping sensor names to

noise scaling factors.

class parts.retrieval.a_priori.SpatialCorrelation(covariance, correlation_length, correlation_type='exp', cutoff=0.01)

Bases: object

Adds spatial correlation to a given covariance matrix.

class parts.retrieval.a_priori.TemperatureMask(lower_limit, upper_limit)

Bases: object

The temperature mask replaces values at grid points outside of the given temperature interval with another value.

class parts.retrieval.a_priori.Thikhonov(scaling=1.0, diagonal=0.0, mask=None, mask_value=1000000000000.0, z_scaling=True)

Bases: object

Thikhonov regularization using second order finite differences.

class parts.retrieval.a_priori.TropopauseMask

Bases: object

Returns a mask that is true only below the approximate height of the troposphere. The troposphere is detected as the first grid point where the lapse rate is negative and the temperature below 220.