Observed and modeled patterns of covariability between low‐level cloudiness and the structure of the trade‐wind layer

• Published in: Journal of advances in modeling earth systems Vol. 7; no. 4; pp. 1741 - 1764
• Main Authors: Nuijens, Louise, Medeiros, Brian, Sandu, Irina, Ahlgrimm, Maike
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 01.12.2015; American Geophysical Union (AGU)
• Subjects: Boundary layer structure; Boundary layers; Climate; Climate models; Cloud cover; Cloudiness; Clouds; Condensation; Convection; Density stratification; GEOSCIENCES; Inversions; Lifting condensation level; Negative feedback; Relative humidity; shallow convection; Stratification; Surface wind; Trade; trade‐wind layer; Variability; Vertical motion; Wind; Winds; United States > US; Barbados
• ISSN: 1942-2466; 1942-2466
• DOI: 10.1002/2015MS000483

We present patterns of covariability between low‐level cloudiness and the trade‐wind boundary layer structure using long‐term measurements at a site representative of dynamical regimes with moderate subsidence or weak ascent. We compare these with ECMWF's Integrated Forecast System and 10 CMIP5 models. By using single‐time step output at a single location, we find that models can produce a fairly realistic trade‐wind layer structure in long‐term means, but with unrealistic variability at shorter‐time scales. The unrealistic variability in modeled cloudiness near the lifting condensation level (LCL) is due to stronger than observed relationships with mixed‐layer relative humidity (RH) and temperature stratification at the mixed‐layer top. Those relationships are weak in observations, or even of opposite sign, which can be explained by a negative feedback of convection on cloudiness. Cloudiness near cumulus tops at the trade‐wind inversion instead varies more pronouncedly in observations on monthly time scales, whereby larger cloudiness relates to larger surface winds and stronger trade‐wind inversions. However, these parameters appear to be a prerequisite, rather than strong controlling factors on cloudiness, because they do not explain submonthly variations in cloudiness. Models underestimate the strength of these relationships and diverge in particular in their responses to large‐scale vertical motion. No model stands out by reproducing the observed behavior in all respects. These findings suggest that climate models do not realistically represent the physical processes that underlie the coupling between trade‐wind clouds and their environments in present‐day climate, which is relevant for how we interpret modeled cloud feedbacks. Key Points: Models reveal unrealistic variability in cloudiness at short‐time scales Models overestimate variations in cloudiness near the LCL with RH and temperature lapse rates Models underestimate relationships that matter for cloudiness near the inversion on long‐time scales