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

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

doi:https://doi.org/10.5194/amt-14-7749-2021

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

Data sets

MLS/Aura L1 Radiances from Filter Banks for GHz V005 (https://disc.gsfc.nasa.gov/) R. Jarnot and V. Perun https://doi.org/10.5067/Aura/MLS/DATA2009

MLS/Aura Level 2 Water Vapor (H2O) Mixing Ratio V004 (https://disc.gsfc.nasa.gov/) A. Lambert, W. Read, and N. Livesey https://doi.org/10.5067/Aura/MLS/DATA2009

MODIS/Aqua Clouds 5-Min L2 Swath 1km and 5km (https://ladsweb.modaps.eosdis.nasa.gov/search/) S. Platnick, M. King, G. Wind, S. Ackerman, P. Menzel, and R. Frey https://doi.org/10.5067/MODIS/MYD06_L2.061

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.