2015
DOI: 10.5194/angeo-33-1155-2015
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Convective gravity wave propagation and breaking in the stratosphere: comparison between WRF model simulations and lidar data

Abstract: Abstract. In this work we perform numerical simulations of convective gravity waves (GWs), using the WRF (Weather Research and Forecasting) model. We first run an idealized, simplified and highly resolved simulation with model top at 80 km. Below 60 km of altitude, a vertical grid spacing smaller than 1 km is supposed to reliably resolve the effects of GW breaking. An eastward linear wind shear interacts with the GW field generated by a single convective thunderstorm. After 70 min of integration time, averagin… Show more

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Cited by 15 publications
(7 citation statements)
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“…The deviation between the logarithmic pressure height and the geometric height, which is strongly de-pendent on the temperature profile, is small for altitudes up to 110 km with about 5 km. The zonal-mean model temperature in the lowermost 10 km is nudged to 2000-2010 mean monthly mean ERA-Interim (Dee et al, 2011) zonal-mean temperature reanalysis data, which is necessary to correct the model climatology in the lower atmosphere, which is not included in the model. The lower boundary of the model at 1000 hPa is determined by 2000-2010 mean ERA-Interim monthly and zonal-mean temperature and geopotential reanalysis data as well as by the corresponding extracted SPWs with wavenumbers 1-3.…”
Section: Model Description and Experimentsmentioning
confidence: 99%
“…The deviation between the logarithmic pressure height and the geometric height, which is strongly de-pendent on the temperature profile, is small for altitudes up to 110 km with about 5 km. The zonal-mean model temperature in the lowermost 10 km is nudged to 2000-2010 mean monthly mean ERA-Interim (Dee et al, 2011) zonal-mean temperature reanalysis data, which is necessary to correct the model climatology in the lower atmosphere, which is not included in the model. The lower boundary of the model at 1000 hPa is determined by 2000-2010 mean ERA-Interim monthly and zonal-mean temperature and geopotential reanalysis data as well as by the corresponding extracted SPWs with wavenumbers 1-3.…”
Section: Model Description and Experimentsmentioning
confidence: 99%
“…At 110 km the deviation increases up to 5 km, whereas the highest logarithmic pressure level of about 160 km may correspond to a geometrical height between 300 and 400 km. In the lowermost 10 km, zonal mean temperatures are nudged to the 2000-2010 mean monthly mean ERA-Interim (Dee et al, 2011) zonal mean temperatures to correct the climatology of the troposphere, which is not included in the model in detail (Jacobi et al, 2015;Lilienthal et al, 2018). Furthermore, at 1000 hPa, which defines the lower boundary of the model, SPWs with wave numbers 1, 2 and 3 are forced, which are extracted from the 2000-2010 mean ERA-Interim monthly temperature and geopotential reanalysis data.…”
Section: Model Description and Setupmentioning
confidence: 99%
“…The ionization of the F region peak increased by 40% in comparison with the International Reference Ionosphere (IRI) model (Bilitza 2001). Ionospheric altitude oscillations at a few tens of minutes period Costantino et al 2015) were observed at different plasma frequencies (related to the electron density). The altitude variation of the F2 layer is generally decreasing during this time period as shown by the blue line (IRI model).…”
Section: Upward Propagation Of Convection Wavesmentioning
confidence: 92%
“…The conservative growth rate curve is also superimposed (green dashed line) with a constant density scale height of 7 km. Horizontal error bars indicate the uncertainty with respect to the temporal variability (Costantino et al 2015). This study quantifies the contribution of GWs from thunderstorms to the general circulation of the atmosphere which can be very strong in tropical configurations.…”
Section: Upward Propagation Of Convection Wavesmentioning
confidence: 99%