Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 12
Articles | Volume 14, issue 12
https://doi.org/10.5194/amt-14-7749-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-7749-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 12
Research article
 | 
09 Dec 2021
Research article |  | 09 Dec 2021

Improved cloud detection for the Aura Microwave Limb Sounder (MLS): training an artificial neural network on colocated MLS and Aqua MODIS data

Frank Werner, Nathaniel J. Livesey, Michael J. Schwartz, William G. Read, Michelle L. Santee, and Galina Wind

Viewed

Total article views: 2,114 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,498 554 62 2,114 49 80
  • HTML: 1,498
  • PDF: 554
  • XML: 62
  • Total: 2,114
  • BibTeX: 49
  • EndNote: 80
Views and downloads (calculated since 25 May 2021)
Cumulative views and downloads (calculated since 25 May 2021)

Viewed (geographical distribution)

Total article views: 2,114 (including HTML, PDF, and XML) Thereof 2,033 with geography defined and 81 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Nov 2024
Download
Short summary
In this study we present an improved cloud detection scheme for the Microwave Limb Sounder, which is based on a feedforward artificial neural network. This new algorithm is shown not only to reliably detect high and mid-level convection containing even small amounts of cloud water but also to distinguish between high-reaching and mid-level to low convection.
Read more