Gravity waves (GWs) generated by tropical convection are important for the simulation of large‐scale atmospheric circulations, for example, the quasi‐biennial oscillation (QBO), and small‐scale phenomena like clear‐air turbulence. However, the simulation of these waves still poses a challenge due to the inaccurate representation of convection, and the high computational costs of global, cloud‐resolving models. Methods combining models with observations are needed to gain the necessary knowledge on GW generation, propagation, and dissipation so that we may encode this knowledge into fast parameterized physics for global weather and climate simulation or turbulence forecasting. We present a new method suitable for rapid simulation of realistic convective GWs. Here, we associate the profile of latent heating with two parameters: precipitation rate and cloud top height. Full‐physics cloud‐resolving WRF simulations are used to develop a lookup table for converting instantaneous radar precipitation rates and echo top measurements into a high‐resolution, time‐dependent latent heating field. The heating field from these simulations is then used to force an idealized dry version of the WRF model. We validate the method by comparing simulated precipitation rates and cloud tops with scanning radar observations and by comparing the GW field in the idealized simulations to satellite measurements. Our results suggest that including variable cloud top height in the derivation of the latent heating profiles leads to better representation of the GWs compared to using only the precipitation rate. The improvement is especially noticeable with respect to wave amplitudes. This improved representation also affects the forcing of GWs on large‐scale circulation.

中文翻译：

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利用雷达观测的降水率和回波顶部高度对热带大气重力波进行逼真的模拟

热带对流产生的重力波（GWs）对于模拟大规模大气环流非常重要，例如，准两年一次的振荡（QBO）和小规模的现象，如晴空湍流。但是，由于对流的表示不准确以及全局云解析模型的高计算成本，因此对这些波的模拟仍然构成挑战。需要将模型与观测结合起来的方法，以获取有关GW生成，传播和耗散的必要知识，以便我们可以将该知识编码为快速参数化的物理学，以进行全球天气和气候模拟或湍流预报。我们提出了一种新的方法，适用于对流GW的快速模拟。在这里，我们将潜热曲线与两个参数相关联：降水率和云顶高度。全物理场云解析WRF仿真用于开发查找表，以将瞬时雷达降水率和回波顶部测量值转换为高分辨率，与时间相关的潜在加热场。然后将这些模拟中的加热场用于强制实现WRF模型的理想干燥版本。我们通过将模拟降水率和云顶与扫描雷达观测值进行比较，并将理想化模拟中的GW场与卫星测量值进行比较，来验证该方法。我们的结果表明，与仅使用降水速率相比，在潜热廓线的推导中包括可变的云顶高度可以更好地表示GW。在波幅方面的改进尤其明显。