Created: Dec. 6, 2023

Proposer: Matthias Schneider

Proposed Date: 2022-12-22

#199

Change Date: Dec. 6, 2023, 5:05 p.m.

Term: **fractional_kernel_of_mole_fraction_of_methane_in_air**

Unit: 1

Unit ref: UUUU

AMIP:

GRIB:

Change Date: Dec. 6, 2023, 5:07 p.m.

Term: **fractional_kernel_of_mole_fraction_of_methane_in_air**

Unit: 1

Unit ref: UUUU

AMIP:

GRIB:

The averaging kernel is a decisive component of a remote-sensing retrieval because it reveals how changes of the real atmospheric state affect the retrieved atmospheric state (Rodgers, 2000). The kernel is indispensable for data interpretation and data reuse. It is an {n x n} matrix where n is the number of atmospheric levels (the dimension of the atmospheric trace gas state vector). The elements of the kernel matrix are the ratios of the differentials: delta(x_retrieved)/delta(x_real)
Often the trace gas mole fractions are strongly varying with altitude. Then it is very useful to provide the fractional averaging kernels (e.g., Keppens et al., 2015). Because delta(x)/x =delta(ln(x)), the fractional averaging kernel is the same as the logarithmic scale averaging kernel.

Change Date: Jan. 29, 2024, 4:21 p.m.

Term: **remote_sensing_averaging_kernel_of_logarithm_of_mole_fraction_of_methane_in_air**

Unit: 1

Unit ref: UUUU

AMIP:

GRIB:

Logarithmic scale averaging kernels of the methane mole fractions obtained by a remote sensing observation (Rodgers, 2020). These kernels are also called fractional averaging kernels (Keppens et al., 2015) They represent the fractional changes of methane in the retrieved atmosphere relative to the fractional changes of methane in the true atmosphere.