Preprints
https://doi.org/10.5194/wes-2021-137
https://doi.org/10.5194/wes-2021-137
 
21 Dec 2021
21 Dec 2021
Status: a revised version of this preprint is currently under review for the journal WES.

Sensitivity analysis of mesoscale simulations to physics parameterizations: a case study of storm Ciara over the Belgian North Sea using WRF-ARW

Adithya Vemuri1, Sophia Buckingham1, Wim Munters1, Jan Helsen2, and Jeroen van Beeck1 Adithya Vemuri et al.
  • 1Department of Environmental and Applied Fluid Dynamics, von Karman Institute for Fluid Dynamics, Waterloosesteenweg 72, 1640 Sint-Genesius-Rode, Belgium
  • 2Department of Mechanical Engineering, Vrije Universiteit Brussel, Boulevard de la Plaine 2, 1050 Ixelles, Belgium

Abstract. The Weather, Research and Forecasting (WRF) model includes a multitude of physics parameterizations to account for atmospheric dynamics and interactions such as turbulent fluxes within the planetary boundary layer (PBL), long and short wave radiation, hydrometeor representation in microphysics, cloud ensemble representation in cumulus, amongst others. A sensitivity analysis is conducted in order to identify the optimal WRF-physics set-up and impact of temporal resolution of re-analysis dataset for the event of sudden changes in wind direction that can become challenging for reliable wind energy operations. In this context, Storm Ciara has been selected as a case study to investigate the influence of a broad combination of different interacting physics-schemes on quantities of interest that are relevant for energy yield assessment. Of particular relevance to fast transient weather events, two different temporal resolutions (1-hourly and 3-hourly) of the lateral boundary condition's re-analysis dataset, ERA5, are considered. Physics parameterizations considered in this study include: two PBL schemes (MYNN2.5 and scale-aware Shin Hong PBL), four cumulus schemes (Kain-Fritsch, Grell-Devenyi, and scale-aware Grell-Freitas and multi-scale Kain-Fritsch,) and three microphysics schemes (WSM5, Thompson and Morrison) coupled with two geospatial configurations for WRF simulation domains. The resulting WRF predictions are assessed by comparison to observational RADAR reflectivity data on precipitation. In addition, SCADA data on wind direction and wind speed from an offshore wind farm located in the Belgian North Sea is considered to assess modeling capabilities for local wind behavior at farm level. For precipitation, results are shown to be very sensitive to model setup, but no clear trends can be observed. For wind-related variables on the other hand, results show a definite improvement in accuracy when both scale-aware cumulus and PBL parameterizations are used in combination with 1-hourly temporal resolution reanalysis data and extended domain sizes.

Adithya Vemuri et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2021-137', Anonymous Referee #1, 27 Jan 2022
    • AC1: 'Reply on RC1', Adithya Vemuri, 24 Apr 2022
      • AC3: 'Reply on AC1', Adithya Vemuri, 07 Jul 2022
  • RC2: 'Comment on wes-2021-137', Anonymous Referee #2, 04 Feb 2022
    • AC2: 'Reply on RC2', Adithya Vemuri, 24 Apr 2022
      • AC4: 'Reply on AC2', Adithya Vemuri, 07 Jul 2022

Adithya Vemuri et al.

Adithya Vemuri et al.

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Short summary
The sensitivity of WRF mesoscale modelling framework in accurately representing and predicting wind farm level environmental variables for the extreme case of Storm Ciara over the Belgian North Sea is investigated in this study. The overall results indicate highly sensitivity simulation results, with supporting conclusions for scale-aware physics parameterizations to better reproduce wind-related variables and ensemble averaging as a promising approach for precipitation.