Articles | Volume 14, issue 12
Atmos. Meas. Tech., 14, 7749–7773, 2021
https://doi.org/10.5194/amt-14-7749-2021
Atmos. Meas. Tech., 14, 7749–7773, 2021
https://doi.org/10.5194/amt-14-7749-2021

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 et al.

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

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.