Preprints
https://doi.org/10.5194/egusphere-2022-355
https://doi.org/10.5194/egusphere-2022-355
19 Jul 2022
 | 19 Jul 2022

Evaluation of a cloudy cold-air pool in the Columbia River Basin in different versions of the HRRR model

Bianca Adler, James M. Wilczak, Jaymes Kenyon, Laura Bianco, Irina V. Djalalova, Joseph B. Olson, and David D. Turner

Abstract. The accurate forecast of persistent orographic cold-air pools in numerical weather prediction models is essential for the optimal integration of wind energy into the electrical grid during these events. Model development efforts during the Second Wind Forecast Improvement Project (WFIP2) aimed to address the challenges also related to this. We evaluated three different versions of NOAA's High-Resolution Rapid Refresh model with two different horizontal grid spacings against in situ and remote sensing observations to investigate how developments in physical parameterizations and numerical methods targeted during WFIP2 impacted the simulation of a persistent cold-air pool in the Columbia River Basin. Differences between the different model versions were in particular visible in the simulated temperature and low-level cloud fields. The model developments led to an enhanced low-level cloud cover in the cold pool, resulting in better agreement with the observations. This removed a diurnal cycle in the near-surface temperature bias at stations throughout the basin by reducing a cold bias during the night and a warm bias during the day. However, low-level clouds did not clear sufficiently during daytime in the newest model version, which led to a warm bias near-the surface during the second night of the reforecasts and leaves room for further model developments. Besides the improvements during the persistent phase of the cold pool, the model developments also led to a better representation of its decay by slowing down its erosion.

Journal article(s) based on this preprint

26 Jan 2023
Evaluation of a cloudy cold-air pool in the Columbia River basin in different versions of the High-Resolution Rapid Refresh (HRRR) model
Bianca Adler, James M. Wilczak, Jaymes Kenyon, Laura Bianco, Irina V. Djalalova, Joseph B. Olson, and David D. Turner
Geosci. Model Dev., 16, 597–619, https://doi.org/10.5194/gmd-16-597-2023,https://doi.org/10.5194/gmd-16-597-2023, 2023
Short summary

Bianca Adler et al.

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Bianca Adler on behalf of the Authors (10 Dec 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (24 Dec 2022) by Chiel van Heerwaarden
RR by Anonymous Referee #1 (29 Dec 2022)
ED: Publish subject to technical corrections (01 Jan 2023) by Chiel van Heerwaarden
AR by Bianca Adler on behalf of the Authors (06 Jan 2023)  Manuscript 

Journal article(s) based on this preprint

26 Jan 2023
Evaluation of a cloudy cold-air pool in the Columbia River basin in different versions of the High-Resolution Rapid Refresh (HRRR) model
Bianca Adler, James M. Wilczak, Jaymes Kenyon, Laura Bianco, Irina V. Djalalova, Joseph B. Olson, and David D. Turner
Geosci. Model Dev., 16, 597–619, https://doi.org/10.5194/gmd-16-597-2023,https://doi.org/10.5194/gmd-16-597-2023, 2023
Short summary

Bianca Adler et al.

Bianca Adler et al.

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Short summary
Rapid changes in wind speed make the integration of wind energy produced during persistent orographic cold pools difficult to integrate into the electrical grid. By evaluating three different versions of NOAA’s High-Resolution-Rapid Refresh model, we demonstrate how model developments targeted during the Second Wind Forecast Improvement Project improve the forecast of a persistent cold pool event.