Articles | Volume 9, issue 7
https://doi.org/10.5194/amt-9-2813-2016
https://doi.org/10.5194/amt-9-2813-2016
Research article
 | 
07 Jul 2016
Research article |  | 07 Jul 2016

Top-of-the-atmosphere shortwave flux estimation from satellite observations: an empirical neural network approach applied with data from the A-train constellation

Pawan Gupta, Joanna Joiner, Alexander Vasilkov, and Pawan K. Bhartia

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Download
Short summary
The A-train constellation of satellites provides a unique opportunity to analyze near-simultaneous data from several of these sensors. In this paper, retrievals of cloud/aerosols parameters and total column ozone (TCO) from the Aura Ozone Monitoring Instrument (OMI) have been used to develop a variety of neural networks that estimate TOA SWF globally over ocean and land using only OMI data as inputs. Application of our method to other ultraviolet sensors may provide unique estimates of TOA SWF.