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The representation of the West African monsoon vertical cloud structure in the Met Office Unified Model: an evaluation with CloudSat
Author(s) -
Stein Thorwald H. M.,
Parker Douglas J.,
Hogan Robin J.,
Birch Cathryn E.,
Holloway Christopher E.,
Lister Grenville M. S.,
Marsham John H.,
Woolnough Steven J.
Publication year - 2015
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.2614
Subject(s) - parametrization (atmospheric modeling) , convection , precipitation , environmental science , cloud computing , cloud top , meteorology , cloud fraction , cloud cover , unified model , climatology , atmospheric sciences , geology , computer science , radiative transfer , geography , physics , quantum mechanics , operating system
Weather and climate model simulations of the West African Monsoon (WAM) have generally poor representation of the rainfall distribution and monsoon circulation because key processes, such as clouds and convection, are poorly characterized. The vertical distribution of cloud and precipitation during the WAM are evaluated in Met Office Unified Model simulations against CloudSat observations. Simulations were run at 40 and 12 km horizontal grid length using a convection parametrization scheme and at 12, 4, and 1.5 km grid length with the convection scheme effectively switched off, to study the impact of model resolution and convection parametrization scheme on the organisation of tropical convection. Radar reflectivity is forward‐modelled from the model cloud fields using the CloudSat simulator to present a like‐with‐like comparison with the CloudSat radar observations. The representation of cloud and precipitation at 12 km horizontal grid length improves dramatically when the convection parametrization is switched off, primarily because of a reduction in daytime (moist) convection. Further improvement is obtained when reducing model grid length to 4 or 1.5 km, especially in the representation of thin anvil and mid‐level cloud, but three issues remain in all model configurations. Firstly, all simulations underestimate the fraction of anvils with cloud‐top height above 12 km, which can be attributed to too low ice water contents in the model compared to satellite retrievals. Secondly, the model consistently detrains mid‐level cloud too close to the freezing level, compared to higher altitudes in CloudSat observations. Finally, there is too much low‐level cloud cover in all simulations and this bias was not improved when adjusting the rainfall parameters in the microphysics scheme. To improve model simulations of the WAM, more detailed and insitu observations of the dynamics and microphysics targeting these non‐precipitating cloud types are required.