Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: J. Navarro x
  • Monthly Weather Review x
  • All content x
Clear All Modify Search
Erika L. Navarro and Gregory J. Hakim


A significant challenge for tropical cyclone ensemble data assimilation is that storm-scale observations tend to make analyses that are more asymmetric than the prior forecasts. Compromised structure and intensity, such as an increase of amplitude across the azimuthal Fourier spectrum, are a routine property of ensemble-based analyses, even with accurate position observations and frequent assimilation. Storm dynamics in subsequent forecasts evolve these states toward axisymmetry, creating difficulty in distinguishing between model-induced and actual storm asymmetries for predictability studies and forecasting. To address this issue, a novel algorithm using a storm-centered approach is proposed. The method is designed for use with existing ensemble filters with little or no modification, facilitating its adoption and maintenance. The algorithm consists of 1) an analysis of the environment using conventional coordinates, 2) a storm-centered analysis using storm-relative coordinates, and 3) a merged analysis that combines the large-scale and storm-scale fields together at an updated storm location. This algorithm is evaluated in two sets of observing system simulation experiments (OSSEs): first, no-cycling tests of the update step for idealized three-dimensional storms in radiative–convective equilibrium; second, full cycling tests of data assimilation applied to a shallow-water model for a field of interacting vortices. Results are compared against a control experiment based on a conventional ensemble Kalman filter (EnKF) scheme as well as an alternative EnKF scheme proposed by Lawson and Hansen. The storm-relative method yields vortices that are more symmetric and exhibit finer inner-core structure than either approach, with errors reduced by an order of magnitude over a control case with prior spread consistent with the National Hurricane Center (NHC)’s mean 5-yr forecast track error at 12 h. Azimuthal Fourier error spectra exhibit much-reduced noise associated with data assimilation as compared to both the control and the Lawson and Hansen approach. An assessment of free-surface height tendency of model forecasts after the merge step reveals a balanced trend between the storm-centered and conventional approaches, with storm-centered values more closely resembling the reference state.

Full access
Pedro A. Jiménez, Jimy Dudhia, J. Fidel González-Rouco, Jorge Navarro, Juan P. Montávez, and Elena García-Bustamante


This study summarizes the revision performed on the surface layer formulation of the Weather Research and Forecasting (WRF) model. A first set of modifications are introduced to provide more suitable similarity functions to simulate the surface layer evolution under strong stable/unstable conditions. A second set of changes are incorporated to reduce or suppress the limits that are imposed on certain variables in order to avoid undesired effects (e.g., a lower limit in u *). The changes introduced lead to a more consistent surface layer formulation that covers the full range of atmospheric stabilities. The turbulent fluxes are more (less) efficient during the day (night) in the revised scheme and produce a sharper afternoon transition that shows the largest impacts in the planetary boundary layer meteorological variables. The most important impacts in the near-surface diagnostic variables are analyzed and compared with observations from a mesoscale network.

Full access