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A Comparison of Model and Observed Turbulent Kinetic Energy Within Coastal Barrier Jets Forced By Landfall Cyclones

Abstract

The Rapid Refresh (RR) is a 1-h data assimilation system at 13-km grid spacing, which provides mesoscale guidance for short-range forecasts. Among the many significant weather phenomena, the RUC is relied upon for the prediction of turbulence and high speed wind events by the marine and aviation industries. The Rapid Refresh (RR) forecast model component uses a version of the Advanced Research Weather Research and Forecast (WRF-ARW) model. The implementation of a High Resolution Rapid Refresh (HRRR) version of the WRF-ARW for the Alaska Region with 3-km grid spacing is currently being explored. As part of the development and testing of the RR/HRRR, new planetary boundary layer (PBL) schemes are being developed and compared to current operational schemes. This work focuses on WRF-ARW performance in simulating low-level coastal jets with moderate turbulence, which can have practical importance to offshore wind energy applications. This study evaluates the performance of the WRF-ARW and investigates the model errors along the complex coastal orography of Alaska, with focus on the spatial and temporal structure of a coastal barrier jet and the turbulent kinetic energy (TKE) within the jet. High-resolution model simulations (near-LES scale) are compared with HRRR-like (3-km) grid spacing, as well as measurements by the Wyoming King-air research aircraft during the Southeastern Alaskan Regional Jets (SARJET) field experiment. Large-eddy mixing from Kelvin-Helmholtz waves in the high-resolution simulations are compared to the parameterized mixing in the 1-dimensions PBL schemes. Also, the advection of TKE within the WRF-ARW is implemented and compared to the default (non-TKE advection) configuration.

Article / Publication Data
Active/Online
YES
Available Metadata
Fiscal Year
Published On
January 01, 2011
Submitted On
March 15, 2021
Event

This publication was presented at the following:

Title
24th Conference on Weather and Forecasting/20th Conference on Numerical Weather Prediction
Sponsor
American Meteorological Society

Author

Authors who have authored or contributed to this publication.