Short Bio:

Jon Reisner received his Ph.D. in 1992 in atmospheric science from Iowa State University while on leave from NCAR, and became a Technical Staff Member in the Earth and Environmental Sciences (EES) division in 1995. Since that time Jon's principle task has involved the development and refinement of a numerical model, HIGRAD, capable of simulating extreme atmospheric events such as wildfires, hurricanes, and dispersion from explosive releases. The model development has required the parallel development of advanced numerical approaches capable of accurately simulating these extreme events. For example, as part of an ending LDRD project a first-of-a-kind fully implicit nonlinear solver has been developed and has been success-fully applied in simulating hurricanes. HIGRAD and FIRETEC won a R&D 100 award in 2003. Recently he became associate editor of the Monthly Weather Review.

Related Research Interests:

Jon is the primary developer of the LANL HIGRAD model that is being used by researchers at both LANL and other agencies throughout the world in simulations of first-of-a-kind complex fluid dynamical phenomena such as the crowning of wildfires. The following is a short list of some of the unique aspects of the HIGRAD model:

• HIGRAD is the first atmospheric science model to employ a nonlinear solver with this solver being first used in the simulations of hurricanes. The hurricane simulations documented the ability of the model to reduce overall numerical error by a factor of 100, as compared to current operational hurricane models, while still being able to predict a hurricane faster than real time.
• HIGRAD is the first atmospheric science model to be able to simulate liquid or solid phases in a "true" multiphase framework with these phases being able to be modeled in either a Lagragian (particle) or Eulerian framework. The multiphase model is currently being used in dust storm simulation on Mars, to advance our basic understanding of cloud physics, and in simulations of the dispersion of radioactive material from low-energy explosions.
• HIGRAD has been coupled to a NASA developed adaptive mesh refinement (AMR) solver, PARAMESH, to examine numerical errors associated with the movement in time of the adaptive meshes. This is the first coupling of an AMR solver to a nonlinear solver, e.g., all meshes levels and variables within the levels are inverted simultaneously, and illustrated the difficulty in achieving higher-order temporal accuracy within an AMR framework.

In addition to the development of advanced numerical methods, considerable effort has been spent with respect to developing parameterizations of physical processes that effectively minimize the influence of numerical errors. For example, a state-of-the-art differentiable cloud model has been developed with the past year. This model employs evaporation limiters based on a sophisticated probability density approach with these limiters preventing the fictitious evaporation of clouds due to numerical diffusion, while still allowing for evaporation due to parameterized turbulent diffusion.