Sensitivity of a two-dimensional convective model to turbulence parameterization

被引:0
|
作者
Nicolini, M [1 ]
Brizuela, MT [1 ]
机构
[1] Univ Buenos Aires, Dept Ciencias Atmosfera & Oceanos, Ctr Invest Mar & Atmosfera, CONICET, Buenos Aires, DF, Argentina
来源
ATMOSFERA | 2002年 / 15卷 / 04期
关键词
convection; turbulence parameterization; modeling;
D O I
暂无
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The sensitivity of a bidimensional cloud model with an upgraded turbulence parameterization is tested. This model, denoted as University of Buenos Aires model (UBA) has the ability to simulate a credible convective scenario in a real data case characterized by observed strong outflows. The main improvements have been made over the turbulence parameterization for the mixed phase microphysics using a first order turbulence closure. Four experiments were performed to accomplish this objective. Results show that the new turbulence parameterization affects the simulation of convection. The emphasis is in the representation of one of the significant features of the convective event used in this sensitivity test. Maximum surface wind speed corresponding to the strongest downdraft is better approached by the representation of a variable K-m. In order to find out whether the sensitivity of the UBA model to the turbulence parameterization is a peculiar characteristic of this model, the Advanced Regional Prediction System (ARPS) was also implemented to check results from the UBA model. ARPS model also shows sensitivity to the turbulence parameterization with a stronger impact. Compared with a 2-D experiments, the inclusion of the third dimension enhances the vertical motions but reduces the divergent outflows at the surface.. The UBA model performance proves to be higher than the ARPS 2-D version in terms of convective outflow strength near the surface in this simulated case, at Resistencia airport. This result is encouraging and justifies future validation of the UBA model in other downburst cases in order to asses its capability as a prognostic tool in airport forecast activities.
引用
收藏
页码:193 / 207
页数:15
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