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  • 1
    In: Monthly Weather Review, American Meteorological Society, Vol. 151, No. 12 ( 2023-12), p. 3063-3087
    Abstract: Doppler-lidar wind-profile measurements at three sites were used to evaluate NWP model errors from two versions of NOAA’s 3-km-grid HRRR model, to see whether updates in the latest version 4 reduced errors when compared against the original version 1. Nested (750-m grid) versions of each were also tested to see how grid spacing affected forecast skill. The measurements were part of the field phase of the Second Wind Forecasting Improvement Project (WFIP2), an 18-month deployment into central Oregon–Washington, a major wind-energy-producing region. This study focuses on errors in simulating marine intrusions, a summertime, 600–800-m-deep, regional sea-breeze flow found to generate large errors. HRRR errors proved to be complex and site dependent. The most prominent error resulted from a premature drop in modeled marine-intrusion wind speeds after local midnight, when lidar-measured winds of greater than 8 m s −1 persisted through the next morning. These large negative errors were offset at low levels by positive errors due to excessive mixing, complicating the interpretation of model “improvement,” such that the updates to the full-scale versions produced mixed results, sometimes enhancing but sometimes degrading model skill. Nesting consistently improved model performance, with version 1’s nest producing the smallest errors overall. HRRR’s ability to represent the stages of sea-breeze forcing was evaluated using radiation budget, surface-energy balance, and near-surface temperature measurements available during WFIP2. The significant site-to-site differences in model error and the complex nature of these errors mean that field-measurement campaigns having dense arrays of profiling sensors are necessary to properly diagnose and characterize model errors, as part of a systematic approach to NWP model improvement. Significance Statement Dramatic increases in NWP model skill will be required over the coming decades. This paper describes the role of major deployments of accurate profiling sensors in achieving that goal and presents an example from the Second Wind Forecast Improvement Program (WFIP2). Wind-profile data from scanning Doppler lidars were used to evaluate two versions of HRRR, the original and an updated version, and nested versions of each. This study focuses on the ability of updated HRRR versions to improve upon predicting a regional sea-breeze flow, which was found to generate large errors by the original HRRR. Updates to the full-scale HRRR versions produced mixed results, but the finer-mesh versions consistently reduced model errors.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2023
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    American Meteorological Society ; 2021
    In:  Monthly Weather Review Vol. 149, No. 2 ( 2021-02), p. 463-477
    In: Monthly Weather Review, American Meteorological Society, Vol. 149, No. 2 ( 2021-02), p. 463-477
    Abstract: The 2015 Plains Elevated Convection at Night (PECAN) field campaign provided a wealth of intensive observations for improving understanding of interplay between the Great Plains low-level jet (LLJ), mesoscale convective systems (MCSs), and other phenomena in the nocturnal boundary layer. This case study utilizes PECAN ground-based Doppler and water vapor lidar and airborne water vapor lidar observations for a detailed examination of water vapor transport in the Great Plains. The chosen case, 11 July 2015, featured a strong LLJ that helped sustain an MCS overnight. The lidars resolved boundary layer moisture being transported northward, leading to a large increase in water vapor in the lowest several hundred meters above the surface in northern Kansas. A branch of nocturnal convection initiated coincident with the observed maximum water vapor flux. Radiosondes confirmed an increase in convective potential within the LLJ layer. Moist static energy (MSE) growth was generated by increasing moisture in spite of a temperature decrease in the LLJ layer. This unique dataset is also used to evaluate the Rapid Refresh (RAP) analysis model performance, comparing model output against the continuous lidar profiles of water vapor and wind. While the RAP analysis captured the large-scale trends, errors in water vapor mixing ratio were found ranging from 0 to 2 g kg −1 at the ground-based lidar sites. Comparison with the airborne lidar throughout the PECAN domain yielded an RMSE of 1.14 g kg −1 in the planetary boundary layer. These errors mostly manifested as contiguous dry or wet regions spanning spatial scales on the order of ten to hundreds of kilometers.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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