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We have developed a hybrid deterministic/probabilistic methodology that uses a Bayesian Hierarchical Modeling (BHM) framework to forecast atmospheric turbulence in the upper-troposphere and lower-stratosphere for Air Force and Missile Defense applications. The approach incorporates three different modeling methods: 1) the Weather Research and Forecasting mesoscale model (WRF) provides numerical weather...
Forecasting atmospheric turbulence is notoriously challenging, given both (1) the enormous range of time and space scales involved, and (2) the nature of the individual processes that give rise to isolated turbulence patches and layers. Under the strongly stable conditions that characterize the stratosphere, isolated turbulence events are nearly always unresolved by traditional weather forecasting...
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