GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 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
    BibTip Others were also interested in ...
  • 2
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 100, No. 9 ( 2019-09), p. 1701-1723
    Abstract: The Second Wind Forecast Improvement Project (WFIP2) is a U.S. Department of Energy (DOE)- and National Oceanic and Atmospheric Administration (NOAA)-funded program, with private-sector and university partners, which aims to improve the accuracy of numerical weather prediction (NWP) model forecasts of wind speed in complex terrain for wind energy applications. A core component of WFIP2 was an 18-month field campaign that took place in the U.S. Pacific Northwest between October 2015 and March 2017. A large suite of instrumentation was deployed in a series of telescoping arrays, ranging from 500 km across to a densely instrumented 2 km × 2 km area similar in size to a high-resolution NWP model grid cell. Observations from these instruments are being used to improve our understanding of the meteorological phenomena that affect wind energy production in complex terrain and to evaluate and improve model physical parameterization schemes. We present several brief case studies using these observations to describe phenomena that are routinely difficult to forecast, including wintertime cold pools, diurnally driven gap flows, and mountain waves/wakes. Observing system and data product improvements developed during WFIP2 are also described.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2019
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    Online Resource
    Online Resource
    American Meteorological Society ; 2013
    In:  Journal of Applied Meteorology and Climatology Vol. 52, No. 8 ( 2013-08), p. 1753-1763
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 52, No. 8 ( 2013-08), p. 1753-1763
    Abstract: One challenge with wind-power forecasts is the accurate prediction of rapid changes in wind speed (ramps). To evaluate the Weather Research and Forecasting (WRF) model's ability to predict such events, model simulations, conducted over an area of complex terrain in May 2011, are used. The sensitivity of the model's performance to the choice among three planetary boundary layer (PBL) schemes [Mellor–Yamada–Janjić (MYJ), University of Washington (UW), and Yonsei University (YSU)] is investigated. The simulated near-hub-height winds (62 m), vertical wind speed profiles, and ramps are evaluated against measurements obtained from tower-mounted anemometers, a Doppler sodar, and a radar wind profiler deployed during the Columbia Basin Wind Energy Study (CBWES). The predicted winds at near–hub height have nonnegligible biases in monthly mean under stable conditions. Under stable conditions, the simulation with the UW scheme better predicts upward ramps and the MYJ scheme is the most successful in simulating downward ramps. Under unstable conditions, simulations using the YSU and UW schemes show good performance in predicting upward ramps and downward ramps, with the YSU scheme being slightly better at predicting ramps with durations longer than 1 h. The largest differences in mean wind speed profiles among simulations using the three PBL schemes occur during upward ramps under stable conditions, which were frequently associated with low-level jets. The UW scheme has the best overall performance in ramp prediction over the CBWES site when evaluated using prediction accuracy and capture-rate statistics, but no single PBL parameterization is clearly superior to the others when all atmospheric conditions are considered.
    Type of Medium: Online Resource
    ISSN: 1558-8424 , 1558-8432
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2013
    detail.hit.zdb_id: 2227779-1
    detail.hit.zdb_id: 2227759-6
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...