Update of upper level turbulence forecast by reducing unphysical components of topography in the numerical weather prediction model

Sang Hun Park, Jung Hoon Kim, Robert D. Sharman, Joseph B. Klemp

Research output: Contribution to journalArticle

5 Citations (Scopus)


On 2 November 2015, unrealistically large areas of light-or-stronger turbulence were predicted by the WRF-RAP (Weather Research and Forecast Rapid Refresh)-based operational turbulence forecast system over the western U.S. mountainous regions, which were not supported by available observations. These areas are reduced by applying additional terrain averaging, which damps out the unphysical components of small-scale (~2Δx) energy aloft induced by unfiltered topography in the initialization of the WRF model. First, a control simulation with the same design of the WRF-RAP model shows that the large-scale atmospheric conditions are well simulated but predict strong turbulence over the western mountainous region. Four experiments with different levels of additional terrain smoothing are applied in the initialization of the model integrations, which significantly reduce spurious mountain-wave-like features, leading to better turbulence forecasts more consistent with the observed data.

Original languageEnglish
Pages (from-to)7718-7724
Number of pages7
JournalGeophysical Research Letters
Issue number14
Publication statusPublished - 2016 Jul 28


All Science Journal Classification (ASJC) codes

  • Geophysics
  • Earth and Planetary Sciences(all)

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