Articles | Volume 9, issue 4
https://doi.org/10.5194/amt-9-1637-2016
https://doi.org/10.5194/amt-9-1637-2016
Research article
 | 
13 Apr 2016
Research article |  | 13 Apr 2016

An automatic precipitation-phase distinction algorithm for optical disdrometer data over the global ocean

Jörg Burdanowitz, Christian Klepp, and Stephan Bakan

Viewed

Total article views: 2,866 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,719 957 190 2,866 122 114
  • HTML: 1,719
  • PDF: 957
  • XML: 190
  • Total: 2,866
  • BibTeX: 122
  • EndNote: 114
Views and downloads (calculated since 21 Dec 2015)
Cumulative views and downloads (calculated since 21 Dec 2015)

Cited

Saved (preprint)

Latest update: 29 Jun 2024
Download
Short summary
We develop a new automatic algorithm to distinguish oceanic precipitation into rain, snow and mixed phase using optical disdrometers deployed on board research vessels. In combination, air temperature, relative humidity and the maximum precipitation particle diameter outperform human observer data and yield highest skill to predict the precipitation phase. This knowledge allows deriving accurate rain and snowfall rates with dense global ocean sampling, which enables satellite sensor validation.