Because of these influences, simulation of the QBO in global climate and long-range weather prediction models has become a higher priority in recent years. Methods used to generate a QBO in global climate and weather models inevitably involve the application of gravity wave drag parameterizations, which approximate convectively-generated gravity wave wind tendencies to apply them in prognostic momentum equations solved by the model. The most advanced parameterization methods link the properties of the parameterized waves to parameterized convective precipitation or latent heating in the model. One such parameterization employed in the National Center for Atmospheric Research (NCAR) climate models is the Beres scheme, which is linked to the Zhang-McFarlane (ZM) convective parameterization. There are many uncertainties in these parameterized gravity wave schemes, and there are only very limited observational constraints on the gravity waves. Our work seeks to validate and improve the parameterized gravity wave drag and the representation of the QBO in the NCAR models.
We use two approaches, one using satellite observations of convective rain (TRMM) coupled to the Beres scheme, and the other using a specialized version of the climate model in which the winds and temperatures have been nudged toward observed fields. Differences reveal the effect of realistic convective wave sources compared to sources that are based on the ZM convective parameterization. Properties of the gravity waves in both approaches are also validated by comparison to waves observed during the PreConcordiasi super-pressure balloon field campaign. The results suggest possible changes to Beres scheme parameter settings for climate simulations. We also examine interannual and intraseasonal variations in gravity waves over the entire 16-year TRMM satellite record.
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