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Microburst Detection With the WRF Model: Effective Resolution and Forecasting Indices.
- Source :
- Journal of Geophysical Research. Atmospheres; 7/27/2020, Vol. 125 Issue 14, p1-13, 13p
- Publication Year :
- 2020
-
Abstract
- Microbursts are meteorological phenomena in the lower troposphere which can produce damaging surface winds and pose a severe risk to aircraft flying close to the ground. As these events usually span less than 4 km and 15 min, the spatiotemporal resolution is a challenge for numerical simulations. Although research of microburst using operative mesoscale models is scarce, the Weather Research and Forecasting (WRF) model has been used in the diagnosis of this phenomenon. In this paper, such model is used to simulate several microburst conducive days using two different boundary conditions. The energy spectra of the simulations are computed to evaluate the effective resolution of the model. The results are in line with previous studies and produce no notable differences among the boundary conditions. Nonetheless, the energy spectra show an overenergetic troposphere at microscale resolutions, rendering the effective resolution inadequate for microburst forecasting using the simulated physics variables. Thus, mesoscale indices are analyzed as a prognostic tool. The wind index, the wet microburst severity index and the microburst windspeed potential index do not show high forecasting performances, even though improving the results of climatology. Also, notable differences among the boundary conditions can be seen. The most consistent results are achieved by the wet microburst severity index. Key Points: The WRF model shows an unrealistic energy spectrum when microscale spatial resolutions are usedThe effective resolution of the simulations casts doubts over the ability to forecast microburstsWINDEX, WMSI, and MWPI microburst indices show better forecasting performance than climatology, despite being suboptimal in general terms [ABSTRACT FROM AUTHOR]
- Subjects :
- MICROBURSTS
METEOROLOGY
COMPUTER simulation
CLIMATOLOGY
CLIMATE change
Subjects
Details
- Language :
- English
- ISSN :
- 2169897X
- Volume :
- 125
- Issue :
- 14
- Database :
- Complementary Index
- Journal :
- Journal of Geophysical Research. Atmospheres
- Publication Type :
- Academic Journal
- Accession number :
- 144803902
- Full Text :
- https://doi.org/10.1029/2020JD032883