Document Type
Article
Publication Date
10-16-2015
Publication Title
Geophysical Research Letters
Abstract
High-resolution ground-based measurements are used to assess the realism of fine-scale numerical simulations of shallow cumulus cloud fields. The overlap statistics of cumuli as produced by large-eddy simulations (LES) are confronted with Cloudnet data sets at the Jülich Observatory for Cloud Evolution. The Cloudnet pixel is small enough to detect cumuliform cloud overlap. Cloud fraction masks are derived for five different cases, using gridded time-height data sets at various temporal and vertical resolutions. The overlap ratio (R), i.e., the ratio between cloud fraction by volume and by area, is studied as a function of the vertical resolution. Good agreement is found between R derived from observations and simulations. An inverse linear function is found to best describe the observed overlap behavior, confirming previous LES results. Simulated and observed decorrelation lengths are smaller (∼300 m) than previously reported (>1 km). A similar diurnal variation in the overlap efficiency is found in observations and simulations.
Repository Citation
Corbetta, G.; Orlandi, E.; Heus, Thijs; Neggers, Roel; and Crewell, S., "Overlap Statistics of Shallow Boundary Layer Clouds: Comparing Ground-Based Observations with Large-Eddy Simulations" (2015). Physics Faculty Publications. 224.
https://engagedscholarship.csuohio.edu/sciphysics_facpub/224
DOI
10.1002/2015GL065140
Version
Publisher's PDF
Publisher's Statement
Open Access
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Volume
42
Issue
19
Comments
This research has been jointly financed by the Federal Ministry of Education and Research (BMBF) within the programme High Definition Clouds and Precipitation for advancing Climate Predic tion (HD(CP)2) under grant HD(CP)2 01LK1209A and ITARS(www.itars.net), European Union Seventh Framework Programme FP7: People, and ITN Marie SklodowskaCurie Actions Programme under grant agreement 289923.