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

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

doi:https://doi.org/10.5194/amt-9-2813-2016

Articles | Volume 9, issue 7

https://doi.org/10.5194/amt-9-2813-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Ten years of Ozone Monitoring Instrument (OMI) observations...

https://doi.org/10.5194/amt-9-2813-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 7

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

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Final revised paper (published on 07 Jul 2016)
Supplement to the final revised paper
Preprint (discussion started on 01 Feb 2016)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of Gupta et al.', Anonymous Referee #2, 17 Mar 2016
- AC1: 'Response to Anonymous Referee #2', Pawan Gupta, 03 May 2016
RC2: 'Top-of-the-atmosphere shortwave flux estimation from UV satellite observations: An empirical approach using data from the A-train constellation', Anonymous Referee #1, 29 Mar 2016
- AC2: 'Response to Anonymous Referee #1', Pawan Gupta, 03 May 2016

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.