Theoretical and Computational Fluid Dynamics

, Volume 28, Issue 1, pp 107–128 | Cite as

Simulation of tropical-cyclone-like vortices in shallow-water ICON-hex using goal-oriented r-adaptivity

  • Werner Bauer
  • Martin Baumann
  • Leonhard Scheck
  • Almut Gassmann
  • Vincent Heuveline
  • Sarah C. Jones
Original Article

Abstract

We demonstrate how efficient r-adapted grids for the prediction of tropical cyclone (TC) tracks can be constructed with the help of goal-oriented error estimates. The binary interaction of TCs in a barotropic model is used as a test case. We perform a linear sensitivity analysis for this problem to evaluate the contribution of each grid cell to an error measure correlated with the cyclone positions. This information allows us to estimate the local grid resolution required to minimize the TC position error. An algorithm involving the solution of a Poisson problem is employed to compute how grid points should be moved such that the desired local resolution is achieved. A hexagonal shallow-water version of the next-generation numerical weather prediction and climate model ICON is used to perform model runs on these adapted grids. The results show that for adequately chosen grid adaptation parameters, the accuracy of the track prediction can be maintained even when a coarser grid is used in regions for which the estimated error contribution is low. Accurate track predictions are obtained only when a grid with high resolution consisting of cells with nearly constant size and regular shape covers the part of the domain where the estimated error contribution is large. The number of grid points required to achieve a certain accuracy in the track prediction can be decreased substantially with our approach.

Keywords

Binary tropical cyclone interaction Goal-oriented r-adaptivity A posteriori error estimation Geophysical shallow-water equations Hexagonal C-grid model 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Werner Bauer
    • 1
    • 5
  • Martin Baumann
    • 2
  • Leonhard Scheck
    • 3
  • Almut Gassmann
    • 4
  • Vincent Heuveline
    • 2
  • Sarah C. Jones
    • 3
    • 6
  1. 1.Max Planck Institute for MeteorologyHamburgGermany
  2. 2.Engineering Mathematics and Computing LabKarlsruhe Institute of TechnologyKarlsruheGermany
  3. 3.Institute for Meteorology and Climate ResearchKarlsruhe Institute of TechnologyKarlsruheGermany
  4. 4.Leibniz-Institute of Atmospheric PhysicsUniversity of RostockKühlungsbornGermany
  5. 5.KlimaCampusUniversity of HamburgHamburgGermany
  6. 6.Deutscher WetterdienstOffenbachGermany

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