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Abstract Tropical gravity waves that are generated by convection are generally too small in scale and too high in frequency to be resolved in global climate models, yet their drag forces drive the important global‐scale quasi‐biennial oscillation (QBO) in the lower stratosphere, and models rely on parameterizations of gravity wave drag to simulate the QBO. We compare detailed properties of tropical parameterized gravity waves in the Whole Atmosphere Community Climate Model version 6 (WACCM6) with gravity waves observed by long‐duration superpressure balloons and also compare properties of parameterized convective latent heating with satellite data. Similarities and differences suggest that the WACCM6 parameterizations are excellent tools for representing tropical gravity waves, but the results also suggest detailed changes to the gravity wave parameterization tuning parameter assumptions that would bring the parameterized waves into much better agreement with observations. While WACCM6 currently includes only nonstationary gravity waves from convection, adding gravity waves generated by the steady component of the heating that are stationary relative to moving convective rain cells is likely to improve the simulation of the QBO in the model. The suggested changes have the potential to alleviate common biases in simulated QBO circulations in models.
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Recreating Observed Convection‐Generated Gravity Waves From Weather Radar Observations via a Neural Network and a Dynamical Atmospheric Model
Abstract Convection‐generated gravity waves (CGWs) transport momentum and energy, and this momentum is a dominant driver of global features of Earth's atmosphere's general circulation (e.g., the quasi‐biennial oscillation, the pole‐to‐pole mesospheric circulation). As CGWs are not generally resolved by global weather and climate models, their effects on the circulation need to be parameterized. However, quality observations of GWs are spatiotemporally sparse, limiting understanding and preventing constraints on parameterizations. Convection‐permitting or ‐resolving simulations do generate CGWs, but validation is not possible as these simulations cannot reproduce the CGW‐forcing convection at correct times, locations, and intensities. Here, realistic convective diabatic heating, learned from full‐physics convection‐permitting Weather Research and Forecasting simulations, is predicted from weather radar observations using neural networks and a previously developed look‐up table. These heating rates are then used to force an idealized GW‐resolving dynamical model. Simulated CGWs forced in this way closely resembled those observed by the Atmospheric InfraRed Sounder in the upper stratosphere. CGW drag in these validated simulations extends 100s of kilometers away from the convective sources, highlighting errors in current gravity wave drag parameterizations due to the use of the ubiquitous single‐column approximation. Such validatable simulations have significant potential to be used to further basic understanding of CGWs, improve their parameterizations physically, and provide more restrictive constraints on tuningwith confidence.
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- Award ID(s):
- 2005123
- PAR ID:
- 10500869
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Advances in Modeling Earth Systems
- Volume:
- 16
- Issue:
- 4
- ISSN:
- 1942-2466
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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