Articles | Volume 15, issue 4
https://doi.org/10.5194/amt-15-927-2022
https://doi.org/10.5194/amt-15-927-2022
Research article
 | 
23 Feb 2022
Research article |  | 23 Feb 2022

Assessing synergistic radar and radiometer capability in retrieving ice cloud microphysics based on hybrid Bayesian algorithms

Yuli Liu and Gerald G. Mace

Viewed

Total article views: 1,531 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,029 438 64 1,531 41 48
  • HTML: 1,029
  • PDF: 438
  • XML: 64
  • Total: 1,531
  • BibTeX: 41
  • EndNote: 48
Views and downloads (calculated since 14 Jul 2021)
Cumulative views and downloads (calculated since 14 Jul 2021)

Viewed (geographical distribution)

Total article views: 1,531 (including HTML, PDF, and XML) Thereof 1,515 with geography defined and 16 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 25 Jun 2024
Download
Short summary
We propose a suite of Bayesian algorithms for synergistic radar and radiometer retrievals to evaluate the next-generation NASA Cloud, Convection and Precipitation (CCP) observing system. The algorithms address pixel-level retrievals using active-only, passive-only, and synergistic active–passive observations. Novel techniques in developing synergistic algorithms are presented. Quantitative assessments of the CCP observing system's capability in retrieving ice cloud microphysics are provided.