F. Delfrate et G. Schiavon, A COMBINED NATURAL ORTHOGONAL FUNCTIONS NEURAL-NETWORK TECHNIQUE FOR THE RADIOMETRIC ESTIMATION OF ATMOSPHERIC PROFILES, Radio science, 33(2), 1998, pp. 405-410
An inversion technique is presented for retrieving vertical profiles o
f atmospheric temperature and vapor from the brightness temperatures m
easured by a ground-based multichannel microwave radiometer and the su
rface measurements of temperature and relative humidity. It combines a
profile expansion over a complete set of natural orthogonal functions
with a neural network which performs the estimate of the coefficients
of the expansion itself. A simulation study has been carried out, and
the algorithm has been tested by comparing its retrievals with those
obtained by means of linear statistical inversion applied on the same
data sets. The analysis has been limited to the case of profiles with
clouds in order to test the ability of the neural network to face nonl
inear problems. The technique has proven to be flexible, showing a goo
d capability of exploiting information provided by other instruments,
such as a laser ceilometer. A fault tolerance evaluation has also been
considered, which showed interesting properties of robustness of the
algorithm.