The Effects of Numerical Dissipation on Hurricane Rapid Intensification with Observational Heating

Abstract

Abstract The computational fluid dynamics of hurricane rapid intensification (RI) is examined through idealized simulations using two codes: a community-based, finite-difference/split-explicit model (WRF) and a spectral-element/semi-implicit model (NUMA). The focus of the analysis is on the effects of implicit numerical dissipation (IND) in the energetics of the vortex response to heating, which embodies the fundamental dynamics in the hurricane RI process. The heating considered here is derived from observations: four-dimensional, fully nonlinear, latent heating/cooling rates calculated from airborne Doppler radar measurements collected in a hurricane undergoing RI. The results continue to show significant IND in WRF relative to NUMA with a reduction in various intensity metrics: (1) time-integrated, mean kinetic energy values in WRF are ∼20% lower than NUMA and (2) peak, localized wind speeds in WRF are ∼12m/s lower than NUMA. Values of the eddy diffusivity in WRF need to be reduced by ∼50% from those in NUMA to produce a similar intensity time series. Kinetic energy budgets demonstrate that the pressure contribution is the main factor in the model differences with WRF producing smaller energy input to the vortex by ∼23%, on average. The low-order spatial discretization of the pressure gradient in WRF is implicated in the IND. In addition, the eddy transport term is found to have a largely positive impact on the vortex intensification with a mean contribution of ∼20%. Overall, these results have important implications for the research and operational forecasting communities that use WRF and WRF-like numerical models. Plain Language Summary The intensity of a hurricane is primarily a balance between energy production and dissipation from various physical processes. Numerical models calculate this energy balance by solving complicated equations that attempt to capture these physical processes. Previous research has shown that the methods used to solve these equations can introduce additional dissipation into the system that affects the prediction of the storm intensity. In this paper, we examine this “numerical dissipation” idea more closely by conducting carefully designed comparisons between the community numerical model (WRF) and an advanced, research model (NUMA). Using observational estimates of heating in clouds, which feed the production of energy, we find that the WRF model produces significantly more numerical dissipation relative to NUMA that results in a reduced intensity of the storm. Our analysis indicates that the reason for the anomalous numerical dissipation in WRF is due to how the pressure gradient is computed. These results can have potentially important consequences for operational forecasts, especially the rapid intensification process. For example, the under-prediction or low bias of rapid intensification forecasts may be partly due to excessive numerical dissipation.