Mesoscale Atmospheric Processes Branch Seminar: Jon Reisner

Los Alamos National Laboratory


While the advection-condensation problem has received considerable attention in the stratus cloud modeling community, little attention has been placed with regard to the impact of this problem on other areas of cloud modeling. Simply put, the advection-condensation problem is due to the failure of Eulerian cloud models to resolve the sub-grid movement of cloud boundaries through a grid cell leading to spurious cooling at cloud edges. Likewise, inherent in any Eulerian advection scheme is the role that numerical errors play in distorting a simulated cloud field to such an extent that it eventually disappears and/or does not compare favorably with observations. In this talk, the large impact these numerical errors play with regard to preventing a hurricane model from producing the correct intensity for the right reason will be presented. Specifically, due to the generation of spurious evaporative cooling at simulated cloud edges, hurricane models must compensate for this cooling by increasing the modeled flux of moisture into the atmosphere and/or increasing surface friction---in order to reproduce the observed intensity. To reduce the impact of the spurious evaporation, an evaporative limiter can be incorporated into a Eulerian cloud model; however, though the limiter helps to mitigate the impact of spurious evaporation it cannot reduce advection errors. To address the deficiencies found in Eulerian hurricane models, the utilization of a Lagrangian cloud model to simulate hurricanes is proposed. While the Lagrangian approach suffers from its own deficiencies, i.e., sampling errors, the approach will be shown to produce smaller errors for hurricanes Guillermo and Rita than a typical Eulerian approach. Further, for sheared hurricanes such as Guillermo, a storm in which three-dimensional fields of latent heat have been obtained, the Lagrangian approach appears to be clearly superior to the Eulerian approach with regard to its ability to reproduce both the intensity and structure of the observed heating fields.