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

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

doi:10.1002/2016gl069446

Cited by 16 publications

(10 citation statements)

References 24 publications

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“…New diagnostics or better subgrid-scale (SGS) turbulence parameterizations appropriate for stably stratified shear flow in the UTLS could be developed using observation campaigns and multinested high-resolution numerical simulations (e.g., Sharman and Lane 2016). 2) As turbulence forecasting depends highly upon underlying NWP model configurations, such as initial and boundary conditions, data assimilation, and physical parameterizations, the downstream impact to turbulence forecasts from changes to the underlying NWP must be identified and the G-GTG configuration modified for the best performance (e.g., Park et al 2016). 3) Obtaining more observational data, especially in poorly observed regions like the Southern Hemisphere, is necessary.…”

Section: Discussionmentioning

confidence: 99%

Improvements in Nonconvective Aviation Turbulence Prediction for the World Area Forecast System

Kim

Sharman

Strahan

et al. 2018

Bulletin of the American Meteorological Society

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For the next generation of the World Area Forecast System (WAFS), the global Graphical Turbulence Guidance (G-GTG) has been developed using global numerical weather prediction (NWP) model outputs as an input to compute a set of turbulence diagnostics, identifying strong spatial gradients of meteorological variables associated with clear-air turbulence (CAT) and mountain-wave turbulence (MWT). The G-GTG provides an atmospheric turbulence intensity metric of energy dissipation rate (EDR) to the 1/3 power (m2/3 s–1), which is the International Civil Aviation Organization (ICAO) standard for aircraft reporting. Deterministic CAT and MWT EDR forecasts are derived from ensembles of calibrated multiple CAT and MWT diagnostics, respectively, with the final forecast provided by the gridpoint-by-gridpoint maximum of the CAT and MWT ensemble means. In addition, a probabilistic EDR forecast is produced by the percentage agreement of the individual CAT and MWT diagnostics that exceed a certain EDR threshold for turbulence (i.e., multidiagnostic ensemble). Objective evaluations of the G-GTG against global in situ EDR measurement data show that both deterministic and probabilistic G-GTG significantly improve the current WAFS CAT product, mainly because the G-GTG takes into account turbulence from various sources related to CAT and MWT. The probabilistic G-GTG forecast is more reliable at predicting light-or-greater (EDR > 0.15)- than moderate-or-greater (EDR > 0.22)-level turbulence, although it suffers from overforecasting. This will be improved in the future when we use this methodology with NWP ensembles and more observation data will be available for calibration. We expect that the new G-GTG forecasts will be beneficial to aviation users globally.

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Section: Discussionmentioning

confidence: 99%

Improvements in Nonconvective Aviation Turbulence Prediction for the World Area Forecast System

Kim

Sharman

Strahan

et al. 2018

Bulletin of the American Meteorological Society

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“…Table 1 shows the detailed model settings for the current numerical simulation. This is similar to the National Oceanic and Atmospheric Administration (NOAA)'s operational NWP model of the high-resolution rapid refresh (HRRR) system version 4, because it has been tuned and updated to provide the best performance skills for mesoscale convective systems applicable for CIT, CAT, and MWT predictions [61][62][63][64]. Physics parameterizations used in the current simulation included the Thompson scheme [56] for microphysical processes, the Mellor-Yamada Nakanishi Niino (MYNN) planetary boundary layer (PBL) scheme [57], the rapid radiative transfer model for general circulation (RRTMG) long-and short-wave [58], and the unified Noah land-surface model [59].…”

Section: Experimental Designmentioning

confidence: 99%

Section: Experimental Designmentioning

confidence: 99%

“…Two turbulence diagnostics, the magnitude of vertical velocity (|w|) and |w| divided by the gradient Richardson number (Ri) (|w|/Ri), are computed using the 1 h model outputs. These two turbulence diagnostics are useful indicators for detecting the mesoscale forces like mountain wave activities for MWT [61][62][63][64]. These turbulence diagnostics were converted to the EDR scale using the LMT described in Section 3.1.…”

Section: Edr Converted From Nwp-based Turbulence Diagnosticsmentioning

confidence: 99%

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A Detection of Convectively Induced Turbulence Using in Situ Aircraft and Radar Spectral Width Data

et al. 2021

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A commercial aircraft, departing from Seoul to Jeju Island in South Korea, encountered a convectively induced turbulence (CIT) at about z = 2.2 km near Seoul on 28 October 2018. At this time, the observed radar reflectivity showed that the convective band with cloud tops of z = 6–7 km passed the CIT region with high values of spectral width (SW; larger than 4 m s–1). Using the 1 Hz wind data recorded by the aircraft, we estimated an objective intensity of the CIT as a cube root of eddy dissipation rate (EDR) based on the inertial range technique, which was about 0.33–0.37 m2/3 s-1. Radar-based EDR was also derived by lognormal mapping technique (LMT), showing that the EDR was about 0.3–0.35 m2/3 s-1 near the CIT location, which is consistent with in situ EDR. In addition, a feasibility of the CIT forecast was tested using the weather and research forecast (WRF) model with a 3 km horizontal grid spacing. The model accurately reproduced the convective band passing the CIT event with an hour delay, which allows the use of two methods to calculate EDR: The first is using both the sub-grid and resolved turbulent kinetic energy to infer the EDR; the second is using the LMT for converting absolute vertical velocity (and its combination with the Richardson number) to EDR-scale. As a result, we found that the model-based EDRs were about 0.3–0.4 m2/3 s-1 near the CIT event, which is consistent with the estimated EDRs from both aircraft and radar observations.

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“…Therefore, topography could significantly affect the behavior of winds to accelerate the wind speed or to change the wind direction. Such orographically strong wind and mountain waves can highly induce huge impacts on aviation operations (Clark et al, 2000;Chun, 2010, 2011;Kim et al, 2019;Park et al, 2016Park et al, , 2019, outdoor sport activities, and forest wildfires in a relatively drier environment under the fine weather conditions (Smith et al, 2018). Downslope windstorm can produce strong wind in the lee side and plays an essential role in creating and maintaining the wildfires near the northern California with the easterly winds across Sierra Nevada and the southern Cascade Mountains (Mass and Ovens, 2019).…”

Section: Introductionmentioning

confidence: 99%

Observational study for strong downslope wind event under fine weather condition during ICE-POP 2018

Tsai

Kim

Liou

et al. 2021

Preprint

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Abstract. A strong downslope wind event under fine weather condition on 13–15 February 2018 was examined by various observational and high resolution reanalysis datasets during the 2018 Winter Olympic and Paralympic games in Pyeongchang, Korea. High spatio-temporal resolution of wind information was obtained by Doppler lidars, automatic weather stations (AWS), wind profiler, and sounding observations under the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games (ICE-POP 2018). This study aimed to understand the possible generation mechanisms of localized strong wind event across high mountainous areas and in the lee side of mountains associated with the underlying large-scale pattern of a low-pressure system (LPS). The spatial distribution of linear trends for surface wind shows different patterns, exhibiting increased trend in the lee side and a persistent one in mountainous areas with the approaching LPS. Surface wind speed was intensified dramatically from ~3 to ~12 m s−1 (gust was stronger than 20 m s−1 above ground) at a surface station in the lee side (named as GWW). However, the mountainous station at DGW site appeared to have a persistently strong wind (~10 m s−1) during the research period. Budget analysis of horizontal momentum equation and local reanalysis data suggests that the pressure gradient force (PGF) derived by adiabatic warming along the downslope and subsequent hydraulic jump in the lee side of mountains was a main factor in the acceleration of the surface wind at the GWW site. Detailed analysis of the retrieved 3D winds reveals that the PGF also dominate at the DGW site, which causes the persistent strong wind that is related to the channeling effect across the valley areas in the mountain range. The observational evidence presented here shows that the different mechanisms in local areas under the same synoptic condition with LPS are important references in determining the strength and persistence of the orographic-induced strong winds under fine weather condition.

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

Cited by 16 publications

References 24 publications

Improvements in Nonconvective Aviation Turbulence Prediction for the World Area Forecast System

Improvements in Nonconvective Aviation Turbulence Prediction for the World Area Forecast System

A Detection of Convectively Induced Turbulence Using in Situ Aircraft and Radar Spectral Width Data

Observational study for strong downslope wind event under fine weather condition during ICE-POP 2018

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