|Atmospheric mesoscale conditions during the Boothbay meteotsunami: a numerical sensitivity study using a high-resolution mesoscale model|Horvath, K.; Vilibic, I. (2015). Atmospheric mesoscale conditions during the Boothbay meteotsunami: a numerical sensitivity study using a high-resolution mesoscale model, in: Vilibic, I. et al. (Ed.) Meteorological tsunamis: The U.S. East Coast and other coastal regions. pp. 55-74. hdl.handle.net/10.1007/978-3-319-12712-5_4
In: Vilibic, I. et al. (Ed.) (2015). Meteorological tsunamis: The U.S. East Coast and other coastal regions. Previously published in Natural Hazards, Volume 74, Issue 1, 2014. Springer: Cham. ISBN 978-3-319-12711-8. 303 pp. dx.doi.org/10.1007/978-3-319-12712-5, more
Mesoscale atmospheric model Sensitivity study Boothbay meteotsunami
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The article aims to test the sensitivity of high-resolution mesoscale atmospheric model to fairly reproduce atmospheric processes that were present during the Boothbay Harbor meteotsunami on 28 October 2008. The simulations were performed by the Weather and Research Forecasting (WRF) model at 1-km horizontal grid spacing by varying initial conditions (ICs) and lateral boundary conditions (LBCs), nesting strategy, simulation lead time and microphysics and convective parameterizations. It seems that the simulations that used higher-resolution IC and LBC were more successful in reproduction of precipitation zone and surface pressure oscillations caused by internal gravity waves observed during the event. The results were very sensitive to the simulation lead time and to the choice of convective parameterization, while the choice of microphysics parameterization and the type of nesting strategy (one-way or two-way) was less important for reproducibility of the event. The success of the WRF model appears limited to very short-range forecasting, most advanced parameterizations, and very high-resolution grid spacing; therefore, the applicability of present atmospheric mesoscale models to future operational meteotsunami warning systems still has a lot of room for improvements.