Biological and Environmental Research - Earth and Environmental System Sciences
Earth and Environmental System Modeling

The Behavior of Trade-Wind Cloudiness in Observations and Models: The major cloud components and their variability

TitleThe Behavior of Trade-Wind Cloudiness in Observations and Models: The major cloud components and their variability
Publication TypeJournal Article
Year of Publication2015
AuthorsNuijens, Louise, Medeiros Brian, Sandu Irina, and Ahlgrimm Maike
JournalJournal of Advances in Modeling Earth Systems
Volume7
Number2
Pages600-616
Abstract / Summary

Guided by ground‐based radar and lidar profiling at the Barbados Cloud Observatory (BCO), this study evaluates trade‐wind cloudiness in ECMWF's Integrated Forecast System (IFS) and nine CMIP5 models using their single‐timestep output at selected grid points. The observed profile of cloudiness is relatively evenly distributed between two important height levels: the lifting condensation level (LCL) and the tops of the deepest cumuli near the trade‐wind inversion (2–3 km). Cloudiness at the LCL dominates the total cloud cover, but is relatively invariant. Variance in cloudiness instead peaks at the inversion. The IFS reproduces the depth of the cloud field and its variability, but underestimates cloudiness at the LCL and the inversion. A few CMIP5 models produce a single stratocumulus‐like layer near the LCL, but more than half of the CMIP5 models reproduce the observed cloud layer depth in long‐term mean profiles. At single‐time steps, however, half of the models do not produce cloudiness near cloud tops along with the (almost ever‐present) cloudiness near the LCL. In seven models, cloudiness is zero at both levels 10 to 65% of the time, compared to 3% in the observations. Models therefore tend to overestimate variance in cloudiness near the LCL. This variance is associated with longer time scales than in observations, which suggests that modeled cloudiness is too sensitive to large‐scale processes. To conclude, many models do not appear to capture the processes that underlie changes in cloudiness, which is relevant for cloud feedbacks and climate prediction.

URLhttps://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2014MS000390
DOI10.1002/2014MS000390
Journal: Journal of Advances in Modeling Earth Systems
Year of Publication: 2015
Volume: 7
Number: 2
Pages: 600-616
Publication Date: 04/2015

Guided by ground‐based radar and lidar profiling at the Barbados Cloud Observatory (BCO), this study evaluates trade‐wind cloudiness in ECMWF's Integrated Forecast System (IFS) and nine CMIP5 models using their single‐timestep output at selected grid points. The observed profile of cloudiness is relatively evenly distributed between two important height levels: the lifting condensation level (LCL) and the tops of the deepest cumuli near the trade‐wind inversion (2–3 km). Cloudiness at the LCL dominates the total cloud cover, but is relatively invariant. Variance in cloudiness instead peaks at the inversion. The IFS reproduces the depth of the cloud field and its variability, but underestimates cloudiness at the LCL and the inversion. A few CMIP5 models produce a single stratocumulus‐like layer near the LCL, but more than half of the CMIP5 models reproduce the observed cloud layer depth in long‐term mean profiles. At single‐time steps, however, half of the models do not produce cloudiness near cloud tops along with the (almost ever‐present) cloudiness near the LCL. In seven models, cloudiness is zero at both levels 10 to 65% of the time, compared to 3% in the observations. Models therefore tend to overestimate variance in cloudiness near the LCL. This variance is associated with longer time scales than in observations, which suggests that modeled cloudiness is too sensitive to large‐scale processes. To conclude, many models do not appear to capture the processes that underlie changes in cloudiness, which is relevant for cloud feedbacks and climate prediction.

DOI: 10.1002/2014MS000390
Citation:
Nuijens, L, B Medeiros, I Sandu, and M Ahlgrimm.  2015.  "The Behavior of Trade-Wind Cloudiness in Observations and Models: The major cloud components and their variability."  Journal of Advances in Modeling Earth Systems 7(2): 600-616.  https://doi.org/10.1002/2014MS000390.