By Topic

A multilayer perceptron approach for the retrieval of vertical temperature profiles from satellite radiation data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Shiguemori, E.H. ; Lab. for Comput. & Appl. Math., Nat. Inst. for Space Res., Sao Jose dos Campos, Brazil ; da Silva, J.D.S. ; Velho, H.Fd.C. ; Carvalho, J.C.

In this paper a multilayer perceptron neural network is used to retrieve vertical atmospheric temperature profiles from satellite radiation data. The training set consists of data provided by the direct model characterized by the radiative transfer equation (RTE) and by real radiation data from the NOAA-HIRS/2 (high resolution infrared radiation) sounder. The retrieved vertical temperature profiles are compared to radiosonde measured data. The neural network performance is compared to the results of the projects by J.C. Carvalho et al (1999) and by F.M. Ramos et al (1999) who used regularization techniques. Neural network approaches are especially advantageous due to the embed parallelism that may imply in faster vertical temperature profiles retrieving systems.

Published in:

Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on  (Volume:5 )

Date of Conference:

31 July-4 Aug. 2005