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: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 99, No. 6 ( 2018-06), p. 1155-1176
    Abstract: To advance the understanding of meteorological processes in offshore coastal regions, the spatial variability of wind profiles must be characterized and uncertainties (errors) in NWP model wind forecasts quantified. These gaps are especially critical for the new offshore wind energy industry, where wind profile measurements in the marine atmospheric layer spanned by wind turbine rotor blades, generally 50–200 m above mean sea level (MSL), have been largely unavailable. Here, high-quality wind profile measurements were available every 15 min from the National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL)’s high-resolution Doppler lidar (HRDL) during a monthlong research cruise in the Gulf of Maine for the 2004 New England Air Quality Study. These measurements were compared with retrospective NWP model wind forecasts over the area using two NOAA forecast-modeling systems [North American Mesoscale Forecast System (NAM) and Rapid Refresh (RAP)]. HRDL profile measurements quantified model errors, including their dependence on height above sea level, diurnal cycle, and forecast lead time. Typical model wind speed errors were ∼2.5 m s−1, and vector-wind errors were ∼4 m s−1. Short-term forecast errors were larger near the surface—30% larger below 100 m than above and largest for several hours after local midnight (biased low). Longer-term, 12-h forecasts had the largest errors after local sunset (biased high). At more than 3-h lead times, predictions from finer-resolution models exhibited larger errors. Horizontal variability of winds, measured as the ship traversed the Gulf of Maine, was significant and raised questions about whether modeled fields, which appeared smooth in comparison, were capturing this variability. If not, horizontal arrays of high-quality, vertical-profiling devices will be required for wind energy resource assessment offshore. Such measurement arrays are also needed to improve NWP models.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2018
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    In: Monthly Weather Review, American Meteorological Society, Vol. 145, No. 10 ( 2017-10), p. 4277-4301
    Abstract: Evaluation of model skill in predicting winds over the ocean was performed by comparing retrospective runs of numerical weather prediction (NWP) forecast models to shipborne Doppler lidar measurements in the Gulf of Maine, a potential region for U.S. coastal wind farm development. Deployed on board the NOAA R/V Ronald H. Brown during a 2004 field campaign, the high-resolution Doppler lidar (HRDL) provided accurate motion-compensated wind measurements from the water surface up through several hundred meters of the marine atmospheric boundary layer (MABL). The quality and resolution of the HRDL data allow detailed analysis of wind flow at heights within the rotor layer of modern wind turbines and data on other critical variables to be obtained, such as wind speed and direction shear, turbulence, low-level jet properties, ramp events, and many other wind-energy-relevant aspects of the flow. This study will focus on the quantitative validation of NWP models’ wind forecasts within the lower MABL by comparison with HRDL measurements. Validation of two modeling systems rerun in special configurations for these 2004 cases—the hourly updated Rapid Refresh (RAP) system and a special hourly updated version of the North American Mesoscale Forecast System [NAM Rapid Refresh (NAMRR)]—are presented. These models were run at both normal-resolution (RAP, 13 km; NAMRR, 12 km) and high-resolution versions: the NAMRR-CONUS-nest (4 km) and the High-Resolution Rapid Refresh (HRRR, 3 km). Each model was run twice: with (experimental runs) and without (control runs) assimilation of data from 11 wind profiling radars located along the U.S. East Coast. The impact of the additional assimilation of the 11 profilers was estimated by comparing HRDL data to modeled winds from both runs. The results obtained demonstrate the importance of high-resolution lidar measurements to validate NWP models and to better understand what atmospheric conditions may impact the accuracy of wind forecasts in th e marine atmospheric boundary layer. Results of this research will also provide a first guess as to the uncertainties of wind resource assessment using NWP models in one of the U.S. offshore areas projected for wind plant development.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    RVK:
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2017
    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 ...
  • 3
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 128, No. 12 ( 2023-06-27)
    Abstract: Temperature profiles retrieved from remotely sensed infrared radiances characterize the valley boundary layer over different snow covers The nocturnal inversion in a high‐altitude mountain valley is mixed out over low snow cover and persists when snow cover is high NOAA's operational weather prediction model struggles to correctly forecast the boundary layer especially when snow cover is high
    Type of Medium: Online Resource
    ISSN: 2169-897X , 2169-8996
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2023
    detail.hit.zdb_id: 710256-2
    detail.hit.zdb_id: 2016800-7
    detail.hit.zdb_id: 2969341-X
    SSG: 16,13
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 4
    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 ...
  • 5
    In: Wind Energy, Wiley, Vol. 22, No. 7 ( 2019-07), p. 932-944
    Abstract: During the first Wind Forecast Improvement Project (WFIP), new meteorological observations were collected from a large suite of instruments, including wind velocities measured on networks of tall towers provided by wind industry partners, wind speeds measured by cup anemometers mounted on the nacelles of wind turbines, and wind profiles by networks of Doppler sodars and radar wind profilers. Previous data denial studies found a significant improvement of up to 6% root mean squared error (RMSE) reduction for short‐term wind power forecasts due to the assimilation of all of these observations into the National Oceanic and Atmospheric Administration (NOAA) Rapid Refresh (RAP) forecast model using a 3D variational data assimilation scheme. As a follow‐on study, we now investigate the impacts of assimilating into the RAP model either the additional remote sensing observations (sodars and radar wind profilers) alone or assimilating the industry‐provided in situ observations (tall towers and nacelle anemometers) alone, in addition to routinely available standard meteorological data sets. The more numerous tall tower/nacelle observations provide a relatively large improvement through the first 3 to 4 hours of the forecasts, which diminishes to a negligible impact by forecast hour 6. In comparison, the sparser vertical profiling sodars/radars provide an initially smaller impact that decays at a much slower rate, with a positive impact present through the first 12 hours of the forecast. Large positive assimilation impacts for both sets of instruments are found during daytime hours, while small or even negative impacts are found during nighttime hours.
    Type of Medium: Online Resource
    ISSN: 1095-4244 , 1099-1824
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2024840-4
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 6
    In: Wind Energy, Wiley, Vol. 22, No. 9 ( 2019-09), p. 1165-1174
    Abstract: The first Wind Forecast Improvement Project (WFIP) was a DOE and NOAA‐funded 2‐year‐long observational, data assimilation, and modeling study with a 1‐year‐long field campaign aimed at demonstrating improvements in the accuracy of wind forecasts generated by the assimilation of additional observations for wind energy applications. In this paper, we present the results of applying a Ramp Tool and Metric (RT & M), developed during WFIP, to measure the skill of the 13‐km grid spacing National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL) Rapid Refresh (RAP) model at forecasting wind ramp events. To measure the impact on model skill generated by the additional observations, controlled data‐denial RAP simulations were run for six separate 7 to 12‐day periods (for a total of 55 days) over different seasons. The RT & M identifies ramp events in the time series of observed and forecast power, matches in time each forecast ramp event with the most appropriate observed ramp event, and computes the skill score of the forecast model penalizing both timing and amplitude errors. Because no unique definition of a ramp event exists (in terms of a single threshold of change in power over a single time duration), the RT & M computes integrated skill over a range of power change (Δp) and time period (Δt) values. A statistically significant improvement of the ramp event forecast skill is found through the assimilation of the special WFIP data in two different study areas, and variations in model skill between up‐ramp versus down‐ramp events are found.
    Type of Medium: Online Resource
    ISSN: 1095-4244 , 1099-1824
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2024840-4
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 7
    In: Weather and Forecasting, American Meteorological Society, Vol. 35, No. 6 ( 2020-12), p. 2407-2421
    Abstract: The second Wind Forecast Improvement Project (WFIP2) is a multiagency field campaign held in the Columbia Gorge area (October 2015–March 2017). The main goal of the project is to understand and improve the forecast skill of numerical weather prediction (NWP) models in complex terrain, particularly beneficial for the wind energy industry. This region is well known for its excellent wind resource. One of the biggest challenges for wind power production is the accurate forecasting of wind ramp events (large changes of generated power over short periods of time). Poor forecasting of the ramps requires large and sudden adjustments in conventional power generation, ultimately increasing the costs of power. A Ramp Tool and Metric (RT & M) was developed during the first WFIP experiment, held in the U.S. Great Plains (September 2011–August 2012). The RT & M was designed to explicitly measure the skill of NWP models at forecasting wind ramp events. Here we apply the RT & M to 80-m (turbine hub-height) wind speeds measured by 19 sodars and three lidars, and to forecasts from the High-Resolution Rapid Refresh (HRRR), 3-km, and from the High-Resolution Rapid Refresh Nest (HRRRNEST), 750-m horizontal grid spacing, models. The diurnal and seasonal distribution of ramp events are analyzed, finding a noticeable diurnal variability for spring and summer but less for fall and especially winter. Also, winter has fewer ramps compared to the other seasons. The model skill at forecasting ramp events, including the impact of the modification to the model physical parameterizations, was finally investigated.
    Type of Medium: Online Resource
    ISSN: 0882-8156 , 1520-0434
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 2025194-4
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 8
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 12, No. 11 ( 2019-11-21), p. 4803-4821
    Abstract: Abstract. During the second Wind Forecast Improvement Project (WFIP2; October 2015–March 2017, held in the Columbia River Gorge and Basin area of eastern Washington and Oregon states), several improvements to the parameterizations used in the High Resolution Rapid Refresh (HRRR – 3 km horizontal grid spacing) and the High Resolution Rapid Refresh Nest (HRRRNEST – 750 m horizontal grid spacing) numerical weather prediction (NWP) models were tested during four 6-week reforecast periods (one for each season). For these tests the models were run in control (CNT) and experimental (EXP) configurations, with the EXP configuration including all the improved parameterizations. The impacts of the experimental parameterizations on the forecast of 80 m wind speeds (wind turbine hub height) from the HRRR and HRRRNEST models are assessed, using observations collected by 19 sodars and three profiling lidars for comparison. Improvements due to the experimental physics (EXP vs. CNT runs) and those due to finer horizontal grid spacing (HRRRNEST vs. HRRR) and the combination of the two are compared, using standard bulk statistics such as mean absolute error (MAE) and mean bias error (bias). On average, the HRRR 80 m wind speed MAE is reduced by 3 %–4 % due to the experimental physics. The impact of the finer horizontal grid spacing in the CNT runs also shows a positive improvement of 5 % on MAE, which is particularly large at nighttime and during the morning transition. Lastly, the combined impact of the experimental physics and finer horizontal grid spacing produces larger improvements in the 80 m wind speed MAE, up to 7 %–8 %. The improvements are evaluated as a function of the model's initialization time, forecast horizon, time of the day, season of the year, site elevation, and meteorological phenomena. Causes of model weaknesses are identified. Finally, bias correction methods are applied to the 80 m wind speed model outputs to measure their impact on the improvements due to the removal of the systematic component of the errors.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2019
    detail.hit.zdb_id: 2456725-5
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 9
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 100, No. 9 ( 2019-09), p. 1687-1699
    Abstract: In 2015 the U.S. Department of Energy (DOE) initiated a 4-yr study, the Second Wind Forecast Improvement Project (WFIP2), to improve the representation of boundary layer physics and related processes in mesoscale models for better treatment of scales applicable to wind and wind power forecasts. This goal challenges numerical weather prediction (NWP) models in complex terrain in large part because of inherent assumptions underlying their boundary layer parameterizations. The WFIP2 effort involved the wind industry, universities, the National Oceanographic and Atmospheric Administration (NOAA), and the DOE’s national laboratories in an integrated observational and modeling study. Observations spanned 18 months to assure a full annual cycle of continuously recorded observations from remote sensing and in situ measurement systems. The study area comprised the Columbia basin of eastern Washington and Oregon, containing more than 6 GW of installed wind capacity. Nests of observational systems captured important atmospheric scales from mesoscale to NWP subgrid scale. Model improvements targeted NOAA’s High-Resolution Rapid Refresh (HRRR) model to facilitate transfer of improvements to National Weather Service (NWS) operational forecast models, and these modifications have already yielded quantitative improvements for the short-term operational forecasts. This paper describes the general WFIP2 scope and objectives, the particular scientific challenges of improving wind forecasts in complex terrain, early successes of the project, and an integrated approach to archiving observations and model output. It provides an introduction for a set of more detailed BAMS papers addressing WFIP2 observational science, modeling challenges and solutions, incorporation of forecasting uncertainty into decision support tools for the wind industry, and advances in coupling improved mesoscale models to microscale models that can represent interactions between wind plants and the atmosphere.
    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 ...
  • 10
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 16, No. 2 ( 2023-01-26), p. 597-619
    Abstract: 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 related to this. We evaluated three versions of the National Oceanic and Atmospheric Administration (NOAA) 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 amongst model versions were most apparent in simulated temperature and low-level cloud fields during the persistent phase of the cold-air pool. The model developments led to an enhanced low-level cloud cover, 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 leaves room for further model developments. The model developments also led to a better representation of the decay of the cold-air pool by slowing down its erosion.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
    detail.hit.zdb_id: 2456725-5
    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...