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Casey J. Wall, Dennis L. Hartmann, and Po-Lun Ma

Abstract

Instantaneous, coincident, footprint-level satellite observations of cloud properties and radiation taken during austral summer over the Southern Ocean are used to study relationships between clouds and large-scale meteorology. Cloud properties are very sensitive to the strength of vertical motion in the midtroposphere, and low-cloud properties are sensitive to estimated inversion strength, low-level temperature advection, and sea surface temperature. These relationships are quantified. An index for the meteorological anomalies associated with midlatitude cyclones is presented, and it is used to reveal the sensitivity of clouds to the meteorology within the warm and cold sectors of cyclones.

The observed relationships between clouds and meteorology are compared to those in the Community Atmosphere Model, version 5 (CAM5), using satellite simulators. Low clouds simulated by CAM5 are too few, are too bright, and contain too much ice. In the cold sector of cyclones, the low clouds are also too sensitive to variations in the meteorology. When CAM5 is coupled with an updated boundary layer parameterization known as Cloud Layers Unified by Binormals (CLUBB), bias in the ice content of low clouds is dramatically reduced. More generally, this study demonstrates that examining the instantaneous time scale is a powerful approach to understanding the physical processes that control clouds and how they are represented in climate models. Such an evaluation goes beyond the cloud climatology and exposes model bias under various meteorological conditions.

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Po-Lun Ma, Kai Zhang, Jainn Jong Shi, Toshihisa Matsui, and Albert Arking

Abstract

Episodic events of both Saharan dust outbreaks and African easterly waves (AEWs) are observed to move westward over the eastern tropical Atlantic Ocean. The relationship between the warm, dry, and dusty Saharan air layer on the nearby storms has been the subject of considerable debate. In this study, the Weather Research and Forecasting model is used to investigate the radiative effect of dust on the development of AEWs during August and September, the months of maximum tropical cyclone activity, in years 2003–07. The simulations show that dust radiative forcing enhances the convective instability of the environment. As a result, most AEWs intensify in the presence of a dust layer. The Lorenz energy cycle analysis reveals that the dust radiative forcing enhances the condensational heating, which elevates the zonal and eddy available potential energy. In turn, available potential energy is effectively converted to eddy kinetic energy, in which local convective overturning plays the primary role. The magnitude of the intensification effect depends on the initial environmental conditions, including moisture, baroclinity, and the depth of the boundary layer. The authors conclude that dust radiative forcing, albeit small, serves as a catalyst to promote local convection that facilitates AEW development.

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Hailong Wang, Casey D. Burleyson, Po-Lun Ma, Jerome D. Fast, and Philip J. Rasch

Abstract

Long-term Atmospheric Radiation Measurement (ARM) datasets collected at the three tropical western Pacific (TWP) sites are used to evaluate the ability of the Community Atmosphere Model (CAM5) to simulate the various types of clouds, their seasonal and diurnal variations, and their impact on surface radiation. A number of CAM5 simulations are conducted at various horizontal grid spacing (around 2°, 1°, 0.5°, and 0.25°) with meteorological constraints from analysis or reanalysis. Model biases in the seasonal cycle of cloudiness are found to be weakly dependent on model resolution. Positive biases (up to 20%) in the annual mean total cloud fraction appear mostly in stratiform ice clouds. Higher-resolution simulations do reduce the positive bias in ice clouds, but they inadvertently increase the negative biases in convective clouds and low-level liquid clouds, leading to a positive bias in annual mean shortwave fluxes at the sites, as high as 65 W m−2 in the 0.25° simulation. Such resolution-dependent biases in clouds can adversely lead to biases in ambient thermodynamic properties and, in turn, produce feedback onto clouds. Both the model and observations show distinct diurnal cycles in total, stratiform, and convective cloud fractions; however, they are out of phase by 12 h and the biases vary by site. The results suggest that biases in deep convection affect the vertical distribution and diurnal cycle of stratiform clouds through the transport of vapor and/or the detrainment of liquid and ice. The approach used here can be easily adapted for the evaluation of new parameterizations being developed for CAM5 or other global or regional models.

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Hua Song, Zhibo Zhang, Po-Lun Ma, Steven J. Ghan, and Minghuai Wang

Abstract

This paper presents a satellite-observation-based evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmosphere Model, version 5 (CAM5), simulations, one with the standard parameterization schemes (CAM5–Base) and the other with the Cloud Layers Unified by Binormals scheme (CAM5–CLUBB). When comparing the direct model outputs, the authors find that CAM5–CLUBB produces more MBL clouds, a smoother transition from stratocumulus to cumulus, and a tighter correlation between in-cloud water and cloud fraction than CAM5–Base. In the model-to-observation comparison using the COSP satellite simulators, the authors find that both simulations capture the main features and spatial patterns of the observed cloud fraction from MODIS and shortwave cloud radiative forcing (SWCF) from CERES. However, CAM5–CLUBB suffers more than CAM5–Base from a problem that can be best summarized as “undetectable” clouds (i.e., a significant fraction of simulated MBL clouds are thinner than the MODIS detection threshold). This issue leads to a smaller COSP–MODIS cloud fraction and a weaker SWCF in CAM5–CLUBB than the observations and also CAM5–Base in the tropical descending regions. Finally, the authors compare modeled radar reflectivity with CloudSat observations and find that both simulations, especially CAM5–CLUBB, suffer from an excessive drizzle problem. Further analysis reveals that the subgrid precipitation enhancement factors in CAM5–CLUBB are unrealistically large, which makes MBL clouds precipitate too excessively, and in turn results in too many undetectable thin clouds.

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