A path towards uncertainty assignment in an operational cloud-phase  algorithm from ARM vertically pointing active sensors

Riihimaki, Laura D.; Comstock, Jennifer M.; Anderson, Kevin K.; Holmes, Aimee; Luke, Edward

doi:10.5194/ascmo-2-49-2016

Articles | Volume 2, issue 1

https://doi.org/10.5194/ascmo-2-49-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/ascmo-2-49-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 2, issue 1

10 Jun 2016

| 10 Jun 2016

A path towards uncertainty assignment in an operational cloud-phase algorithm from ARM vertically pointing active sensors

Laura D. Riihimaki, Jennifer M. Comstock, Kevin K. Anderson, Aimee Holmes, and Edward Luke

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Cumulative views and downloads (calculated since 10 Jun 2016)

Month	HTML	PDF	XML	Total
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Jul 2016	14	2	1	17
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Latest update: 27 Feb 2026

Short summary

Between atmospheric temperatures of 0 and −38 °C, clouds contain ice crystals, super-cooled liquid droplets, or a mixture of both, impacting how they influence the atmospheric energy budget and challenging our ability to simulate climate change. Better cloud-phase measurements are needed to improve simulations. We demonstrate how a Bayesian method to identify cloud phase can improve on currently used methods by including information from multiple measurements and probability estimates.