DocumentCode :
3400252
Title :
Accuracy of physical, statistical and neural network based algorithms for the retrieval of atmospheric water by ground-based microwave radiometry
Author :
Basili, P. ; Ciotti, P. ; Fionda, E.
Author_Institution :
Ist. di Elettronica, Perugia Univ., Italy
Volume :
1
fYear :
1998
fDate :
6-10 Jul 1998
Firstpage :
418
Abstract :
This paper considers the estimation of atmospheric integrated precipitable water vapor and integrated liquid water content with reference to a dual-channel radiometer, including also the possible addition of a third higher frequency channel. The paper compares the performances of several retrieval algorithms applied to synthetic data of two Italian locations (Rome and Udine) on the basis of accuracy, robustness to measurement errors and applicability to sites having different climatologies from the training site
Keywords :
atmospheric humidity; atmospheric techniques; geophysical signal processing; geophysics computing; humidity measurement; neural nets; radiometry; remote sensing; EHF; SHF; atmosphere; dual-channel radiometer; ground-based microwave radiometry; humidity; integrated precipitable water vapor; liquid water content; measurement technique; meteorology; neural net; neural network; remote sensing; retrieval algorithm; statistical algorithm; water vapor; water vapour; Brightness temperature; Clouds; Frequency estimation; Information retrieval; Linear regression; Measurement errors; Microwave radiometry; Neural networks; Robustness; Temperature dependence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4403-0
Type :
conf
DOI :
10.1109/IGARSS.1998.702925
Filename :
702925
Link To Document :
بازگشت