Physical simulation of atmospheric microbursts

Ferrero, E.; Mortarini, Luca; Manfrin, M.; Solari, M.; Forza, R.

doi:10.1002/2013jd021243

Cited by 3 publications

(2 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Atlas et al () use Doppler radar observations to conclude the concurrence with Srivastava's models and that a narrow distribution of hail meteor sizes produces stronger high‐reflectivity microbursts. Ferrero et al () perform laboratory simulations of microbursts to conclude that the fluid column height and density do not produce remarkable differences to the microburst, although high flow rotation can prevent the event, in contrast to former results. Pryor () produces the Microburst Windspeed Potential Index as a nowcasting algorithm.…”

Section: State Of the Artmentioning

confidence: 99%

Simulation of Atmospheric Microbursts Using a Numerical Mesoscale Model at High Spatiotemporal Resolution

et al. 2020

View full text Add to dashboard Cite

Atmospheric microbursts are low‐level meteorological events that can produce significant damage on the surface and pose a major risk to aircraft flying close to the ground. Studies and ad hoc numerical models have been developed to understand the origin and dynamics of the microburst; nevertheless, there are few researches of the phenomenon using global and mesoscale models. This is mainly due to the limitations in resolution, as microbursts normally span for less than 4 km and 20 min. In this paper, the Weather Research and Forecasting model is used at resolutions of 400 m and 3 min to test if it can properly capture the variables and dynamics of high‐reflectivity microbursts. Several microphysics and planetary boundary layer parametrizations are tested to find the best model configuration for the simulation of this kind of episodes. General conditions are evaluated by using thermodynamic diagrams. Surface and vertical wind speed, reflectivity, precipitation, and other variables for each simulated event are compared with observations, and the model's sensitivity to the variables is assessed. The dynamics and evolution of the microburst is evaluated using different plots of a chosen event. The results show that the model is able to reproduce high‐reflectivity microbursts in accordance with observations, although there is a tendency to underestimate the intensity of variables, most markedly on the wind vertical velocity. Regarding the microphysics schemes, the Morrison parametrization performs better than the WRF single‐moment 6‐class scheme. No major differences are found between the Mellor‐Yamada‐Janjic and the Mellor‐Yamada‐Nakanishi‐Niino planetary boundary layer parametrizations.

show abstract

Section: State Of the Artmentioning

confidence: 99%

Simulation of Atmospheric Microbursts Using a Numerical Mesoscale Model at High Spatiotemporal Resolution

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Enhanced physical understanding of the microburst phenomenon has been provided by highresolution simulations (e.g., Proctor 1988, Orf et al 1996, Orf and Anderson 1999, Nicholls et al 1993, and laboratory studies (e.g., Ferrero et al 2014). Because of its importance to aviation, LLWS is routinely forecasted using the vector wind difference of wind between 2000 ft AGL (619.5 m) and the surface (e.g., NOAA NWS Instruction 10-813, 2016), although these forecasts are mainly driven by resolvable non-convective sources, e.g., frontal passages, lowlevel jets, lee side mountain effects, sea breeze fronts, etc.…”

Section: Integrated Systems A) Numerical Guidance Systems For Aviationmentioning

confidence: 99%

A Review of High Impact Weather for Aviation Meteorology

Gültepe

Sharman

Williams

et al. 2019

Pure Appl. Geophys.

205

121

View full text Add to dashboard Cite

This review paper summarizes current knowledge available for aviation operations related to meteorology and provides suggestions for necessary improvements in the measurement and prediction of weather-related parameters, new physical methods for numerical weather predictions (NWP), and next-generation integrated systems. Severe weather can disrupt aviation operations on the ground or in-flight. The most important parameters related to aviation meteorology are wind and turbulence, fog visibility (Vis) and ceiling, rain and snow amount and rates, icing, ice microphysical parameters, convection and precipitation intensity, microbursts, hail, and lightning. Measurements of these parameters are also functions of sensor response times and measurement thresholds in extreme weather conditions. In addition to these, airport environments can play an important role leading to intensification of extreme weather conditions or high impact weather events, e.g., anthropogenic ice fog. To observe meteorological parameters, new remote sensing platforms, namely wind LIDAR, sodars, radars, and geostationary satellites, and in-situ observations at the surface and in the cloud, as well as aircraft and Unmanned Aerial Vehicles (UAV) mounted sensors, are becoming more common. Because of prediction issues at smaller time and space scales (e.g., <1 km), meteorological forecasts from NWP models need to be continuously improved. Aviation weather forecasts also need to be developed to provide information that represents both deterministic and statistical approaches. In this review, we present available resources and issues for aviation meteorology and evaluate them for required improvements related to measurements, nowcasting, forecasting, and climate change, and emphasize future challenges.

show abstract