Energetics of Madden-Julian oscillations in the National Center for Atmospheric Research Community Atmosphere Model version 3 (NCAR CAM3)

2006 ◽  
Vol 111 (D24) ◽  
Author(s):  
Mingquan Mu ◽  
Guang J. Zhang
Keyword(s):  
Research Community ◽  
Atmospheric Research ◽  
Model Version ◽  
Community Atmosphere Model ◽  
Atmosphere Model

scholarly journals Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations

2016 ◽  
Vol 121 (8) ◽  
pp. 4162-4176 ◽  
Author(s):  
Jennifer E. Kay ◽  
Line Bourdages ◽  
Nathaniel B. Miller ◽  
Ariel Morrison ◽  
Vineel Yettella ◽  
...  
Keyword(s):  
Model Version ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Lidar Observations

scholarly journals Direct comparisons of ice cloud macro- and microphysical properties simulated by the Community Atmosphere Model version 5 with HIPPO aircraft observations

2017 ◽  
Vol 17 (7) ◽  
pp. 4731-4749 ◽  
Author(s):  
Chenglai Wu ◽  
Xiaohong Liu ◽  
Minghui Diao ◽  
Kai Zhang ◽  
Andrew Gettelman ◽  
...  
Keyword(s):  
Nucleation And Growth ◽  
Ice Nucleation ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Model Version ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Ice Water

Abstract. In this study we evaluate cloud properties simulated by the Community Atmosphere Model version 5 (CAM5) using in situ measurements from the HIAPER Pole-to-Pole Observations (HIPPO) campaign for the period of 2009 to 2011. The modeled wind and temperature are nudged towards reanalysis. Model results collocated with HIPPO flight tracks are directly compared with the observations, and model sensitivities to the representations of ice nucleation and growth are also examined. Generally, CAM5 is able to capture specific cloud systems in terms of vertical configuration and horizontal extension. In total, the model reproduces 79.8 % of observed cloud occurrences inside model grid boxes and even higher (94.3 %) for ice clouds (T ≤ −40 °C). The missing cloud occurrences in the model are primarily ascribed to the fact that the model cannot account for the high spatial variability of observed relative humidity (RH). Furthermore, model RH biases are mostly attributed to the discrepancies in water vapor, rather than temperature. At the micro-scale of ice clouds, the model captures the observed increase of ice crystal mean sizes with temperature, albeit with smaller sizes than the observations. The model underestimates the observed ice number concentration (Ni) and ice water content (IWC) for ice crystals larger than 75 µm in diameter. Modeled IWC and Ni are more sensitive to the threshold diameter for autoconversion of cloud ice to snow (Dcs), while simulated ice crystal mean size is more sensitive to ice nucleation parameterizations than to Dcs. Our results highlight the need for further improvements to the sub-grid RH variability and ice nucleation and growth in the model.

scholarly journals Influence of Superparameterization and a Higher-Order Turbulence Closure on Rainfall Bias Over Amazonia in Community Atmosphere Model Version 5

2017 ◽  
Vol 122 (18) ◽  
pp. 9879-9902 ◽  
Author(s):  
Kai Zhang ◽  
Rong Fu ◽  
Muhammad J. Shaikh ◽  
Steven Ghan ◽  
Minghuai Wang ◽  
...  
Keyword(s):  
Higher Order ◽  
Turbulence Closure ◽  
Model Version ◽  
Community Atmosphere Model ◽  
Atmosphere Model
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