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

Authors:

Chenglai Wu ^1,2, Xiaohong Liu ¹, Minghui Diao ³, Kai Zhang ⁴, Andrew Gettelman ⁵, Zheng Lu ¹, Joyce E. Penner ⁶, and
Zhaohui Lin ²

1 Department of Atmospheric Science, University of Wyoming, Laramie, Wyoming, USA
2 International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing, China
3 Department of Meteorology and Climate Science, San Jose State University, San Jose, California, USA
4 Pacific Northwest National Laboratory, Richland, Washington, USA
5 National Center for Atmospheric Research, Boulder, Colorado, USA
6 Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, Michigan, USA
Correspondence to: Xiaohong Liu (xliu6@uwyo.edu)
Received: 9 December 2016 – Discussion started: 16 January 2017
Revised: 17 March 2017 – Accepted: 20 March 2017 – Published: 11 April 2017

Abstract

In this study we evaluate cloud properties simulated by the Community Atmosphere Model version 5 (CAM5) using in situ measurements from the HIAPER Poleto-Pole Observations (HIPPO) campaign for the period of 2009 to 2011. The modeled wind and temperature are nudgedtowards reanalysis. Model results collocated with HIPPOflight tracks are directly compared with the observations, andmodel sensitivities to the representations of ice nucleationand growth are also examined. Generally, CAM5 is able tocapture specific cloud systems in terms of vertical configuration and horizontal extension. In total, the model reproduces79.8 % of observed cloud occurrences inside model gridboxes and even higher (94.3 %) for ice clouds (T ≤ ？40 ？C).The missing cloud occurrences in the model are primarilyascribed to the fact that the model cannot accountfor thehigh spatial variability of observed relative humidity (RH).

Furthermore, model RH biases are mostly attributed to thediscrepancies in water vapor, rather than temperature. At themicro-scale of ice clouds, the model captures the observedincrease of ice crystal mean sizes with temperature, albeitwith 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 μmin diameter. Modeled IWC and Ni are more sensitive to thethreshold diameter for autoconversion of cloud ice to snow(Dcs), while simulated ice crystal mean size is more sensitiveto ice nucleation parameterizations than to Dcs. Our resultshighlight the need for further improvements to the sub-gridRH variability and ice nucleation and growth in the model.

Citation:

Chenglai Wu , Xiaohong Liu, Minghui Diao, Kai Zhang, Andrew Gettelman, Zheng Lu, Joyce E. Penner,Zhaohui Lin,Direct comparisons of ice cloud macro- and microphysical properties simulated by the Community Atmosphere Model version 5 with HIPPO aircraft observations,Atmos. Chem. Phys., 17, 4731–4749, 2017 www.atmos-chem-phys.net/17/4731/2017/ doi:10.5194/acp-17-4731-2017

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