scholarly journals Variability of the Stratospheric Quasi-Biennial Oscillation and Its Wave Forcing Simulated in the Beijing Climate Center Atmospheric General Circulation Model

2019 ◽  
Vol 77 (1) ◽  
pp. 149-165 ◽  
Author(s):  
Yixiong Lu ◽  
Tongwen Wu ◽  
Weihua Jie ◽  
Adam A. Scaife ◽  
Martin B. Andrews ◽  
...  

Abstract It is well known that the stratospheric quasi-biennial oscillation (QBO) is forced by equatorial waves with different horizontal/vertical scales, including Kelvin waves, mixed Rossby–gravity (MRG) waves, inertial gravity waves (GWs), and mesoscale GWs, but the relative contribution of each wave is currently not very clear. Proper representation of these waves is critical to the simulation of the QBO in general circulation models (GCMs). In this study, the vertical resolution in the Beijing Climate Center Atmospheric General Circulation Model (BCC-AGCM) is increased to better represent large-scale waves, and a mesoscale GW parameterization scheme, which is coupled to the convective sources, is implemented to provide unresolved wave forcing of the QBO. Results show that BCC-AGCM can spontaneously generate the QBO with realistic periods, amplitudes, and asymmetric features between westerly and easterly phases. There are significant spatiotemporal variations of parameterized convective GWs, largely contributing to a great degree of variability in the simulated QBO. In the eastward wind shear of the QBO at 20 hPa, forcing provided by resolved waves is 0.1–0.2 m s−1 day−1 and forcing provided by parameterized GWs is ~0.15 m s−1 day−1. On the other hand, westward forcings by resolved waves and parameterized GWs are ~0.1 and 0.4–0.5 m s−1 day−1, respectively. It is inferred that the eastward forcing of the QBO is provided by both Kelvin waves and mesoscale convective GWs, whereas the westward forcing is largely provided by mesoscale GWs. MRG waves barely contribute to the formation of the QBO in the model.

2005 ◽  
Vol 18 (17) ◽  
pp. 3527-3535 ◽  
Author(s):  
C. A. Severijns ◽  
W. Hazeleger

Abstract An efficient method to optimize the parameter values of the subgrid parameterizations of an atmospheric general circulation model is described. The method is based on the downhill simplex minimization of a cost function computed from the difference between simulated and observed fields. It is used to find optimal values of the radiation and cloud-related parameters. The model error is reduced significantly within a limited number of iterations (about 250) of short integrations (5 yr). The method appears to be robust and finds the global minimum of the cost function. The radiation budget of the model improves considerably without violating the already well simulated general circulation. Different aspects of the general circulation, such as the Hadley and Walker cells improve, although they are not incorporated into the cost function. It is concluded that the method can be used to efficiently determine optimal parameters for general circulation models even when the model behavior has a strong nonlinear dependence on these parameters.


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