Articles | Volume 11, issue 10
https://doi.org/10.5194/wes-11-3919-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-3919-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
15 Oct 2026
Data description article |
| 15 Oct 2026
| 15 Oct 2026
The HRRR Meteorology, Energy, and Transmission (MET) Toolkit: advancing high-resolution atmospheric data for contiguous US energy applications
National Laboratory of the Rockies, Golden, CO, USA
Emina Maric
National Laboratory of the Rockies, Golden, CO, USA
Ulrike Egerer
National Laboratory of the Rockies, Golden, CO, USA
Grant Buster
National Laboratory of the Rockies, Golden, CO, USA
Luke Lavin
National Laboratory of the Rockies, Golden, CO, USA
Pavlo Pinchuk
National Laboratory of the Rockies, Golden, CO, USA
Brandon Benton
National Laboratory of the Rockies, Golden, CO, USA
David D. Turner
NOAA Global Systems Laboratory, Boulder, CO, USA
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Vincent Pronk, Nicola Bodini, Mike Optis, Julie K. Lundquist, Patrick Moriarty, Caroline Draxl, Avi Purkayastha, and Ethan Young
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Nicola Bodini, Weiming Hu, Mike Optis, Guido Cervone, and Stefano Alessandrini
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Andrea Burgos-Cuevas, David D. Turner, Jan H. Schween, Tobias Marke, Tobias Böck, and Ulrich Löhnert
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We developed a new method to estimate heat and moisture transport in the lower atmosphere using measurements from a single site. The method combines temperature, humidity, and wind observations and quantifies their uncertainty. Results show that strong transport events can be reliably detected, reducing the need for complex networks of instruments and providing a practical way to monitor important atmospheric processes.
Bianca Adler, Laura Bianco, David D. Turner, Joseph Olson, Xia Sun, Joshua Gebauer, Nicola Bodini, Stefano Letizia, and James M. Wilczak
Geosci. Model Dev., 19, 8627–8649, https://doi.org/10.5194/gmd-19-8627-2026, https://doi.org/10.5194/gmd-19-8627-2026, 2026
Short summary
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Accurate operational forecasts of temperature and wind in the coastal marine boundary layer are important for a wide range of applications. Leveraging data that were collected along the United States northeast coast during a multi-year period for the Third Wind Forecast Improvement project, we investigated the performance of the operational forecast model and identified systematic errors in wind and temperature forecasts that are now being addressed by the model developers.
Nicola Bodini, Grant Buster, and David D. Turner
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-680, https://doi.org/10.5194/essd-2026-680, 2026
Preprint under review for ESSD
Short summary
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Alaska's power systems depend on weather, yet weather stations there are few and far between. We turned seven years of hourly output from a national weather forecast model into an easy-to-use record of wind and temperature across Alaska, and checked it against measurements from more than 150 sites. The data generally match observations well, and are freely available to support energy planning, resilient power grids, and artificial intelligence research in this remote region.
Anders A. Jensen, David D. Turner, Jorge Guerra, Stanley G. Benjamin, Clark Evans, David J. Gagne, Justin R. Minder, and Joseph B. Olson
EGUsphere, https://doi.org/10.5194/egusphere-2026-4026, https://doi.org/10.5194/egusphere-2026-4026, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Clouds and precipitation are predicted by complex algorithms in weather models. In this study, parts of these algorithms were replaced by machine learning. This approach successfully added cloud details vital for cloud-radiation interactions and temperature forecasts, and replicated a model component while maintaining accurate total precipitation forecasts. Ultimately, weather models benefit from faster algorithms and the addition of physical details from machine learning.
Nicola Bodini, Patrick Moriarty, Regis Thedin, Paula Doubrawa, Cristina Archer, Myra Blaylock, Carlo Bottasso, Bruno Carmo, Lawrence Cheung, Camille Dubreuil, Rogier Floors, Thomas Herges, Daniel Houck, Ali Kanjari, Colleen M. Kaul, Christopher Kelley, Ru Li, Julie K. Lundquist, Desirae Major, Anh Kiet Nguyen, Mike Optis, Luan R. C. Parada, Alfredo Peña, Julian Quick, David Ricarte, William C. Radünz, Raj K. Rai, Oscar García-Santiago, Jonas Schulte, Knut S. Seim, M. Paul van der Laan, Kisorthman Vimalakanthan, and Adam Wise
Wind Energ. Sci., 11, 3107–3135, https://doi.org/10.5194/wes-11-3107-2026, https://doi.org/10.5194/wes-11-3107-2026, 2026
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Lindsay M. Sheridan, Raghavendra Krishnamurthy, Tien Manh Nguyen, Yi-Leng Chen, William I. Gustafson Jr., Ye Liu, Feng Hsiao, Rob K. Newsom, Preston Spicer, Evgueni Kassianov, Mikhail Pekour, Nicola Bodini, and Mark Severy
Wind Energ. Sci., 11, 2257–2285, https://doi.org/10.5194/wes-11-2257-2026, https://doi.org/10.5194/wes-11-2257-2026, 2026
Short summary
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Wind simulations can contain significant errors, which can lead to inaccurate estimates of wind energy generation. Using observations from a floating lidar off Hawai'i, we hypothesize and establish that distinct simulation datasets will exhibit diverse ranges of errors in this offshore environment. The most commonly used simulation dataset produces the largest wind speed biases due to underestimation of fast wind speeds and misrepresentation of how wind speed varies throughout the day and night.
Nicola Bodini, Joseph Olson, Brian Gaudet, Giacomo Valerio Iungo, Mojtaba Shams Solari, Sayahnya Roy, Julie K. Lundquist, Nathan Agarwal, Timothy A. Myers, Bianca Adler, Jeffrey D. Mirocha, Eric James, Laura Bianco, James M. Wilczak, and David D. Turner
Wind Energ. Sci., 11, 1949–1961, https://doi.org/10.5194/wes-11-1949-2026, https://doi.org/10.5194/wes-11-1949-2026, 2026
Short summary
Short summary
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Aliza Abraham, Nicola Bodini, Nicholas Hamilton, Brian Hirth, John Schroeder, and Patrick Moriarty
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Revised manuscript under review for WES
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Stefano Letizia, David D. Turner, Aliza Abraham, Luc Rochette, and Patrick J. Moriarty
Wind Energ. Sci., 11, 1653–1677, https://doi.org/10.5194/wes-11-1653-2026, https://doi.org/10.5194/wes-11-1653-2026, 2026
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David D. Turner, Bianca Adler, Laura Bianco, James M. Wilczak, Vincent Michaud-Belleau, and Luc Rochette
Atmos. Meas. Tech., 19, 1573–1586, https://doi.org/10.5194/amt-19-1573-2026, https://doi.org/10.5194/amt-19-1573-2026, 2026
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It is critical that a network of ground-based instruments that measure temperature and humidity profiles be well calibrated, so that differences between any two profiles can be attributed to atmospheric differences and not instrument calibration issues. This study evaluated the relative accuracy of 7 ground-based infrared spectrometers and their ability to measure these profiles, and found that the profile bias was much smaller than the uncertainty in the retrieved profiles themselves.
Nicola Bodini, Aliza Abraham, Paula Doubrawa, Stefano Letizia, Julie K. Lundquist, Patrick Moriarty, and Ryan Scott
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2026-33, https://doi.org/10.5194/wes-2026-33, 2026
Revised manuscript accepted for WES
Short summary
Short summary
Wind turbines create "wakes" of slowed air that reduce power for nearby turbines. To help improve wind energy models, we analyzed data from a large field experiment. We focused on a single day with changing weather patterns. We found that even simple terrain features interacted with the wind to create large variations in power output – up to 80 percent – across a wind farm. This detailed dataset provides a real-world case needed to validate and improve wind energy design tools.
Yelena Pichugina, Alan W. Brewer, Sunil Baidar, Robert Banta, Edward Strobach, Brandi McCarty, Brian Carroll, Nicola Bodini, Stefano Letizia, Richard Marchbanks, Michael Zucker, Maxwell Holloway, and Patrick Moriarty
Wind Energ. Sci., 11, 417–442, https://doi.org/10.5194/wes-11-417-2026, https://doi.org/10.5194/wes-11-417-2026, 2026
Short summary
Short summary
The truck-based Doppler lidar system was used during the American Wake Experiment (AWAKEN) to obtain the high-frequency, simultaneous measurements of the horizontal wind speed, direction, and vertical velocity from a moving platform. The paper presents the unique capability of the novel lidar system to characterize the temporal, vertical, and spatial variability in winds at various distances from operating turbines and obtain quantitative estimates of wind speed reduction in the waked flow.
Linus von Klitzing, David D. Turner, Diego Lange, and Volker Wulfmeyer
Atmos. Meas. Tech., 19, 359–370, https://doi.org/10.5194/amt-19-359-2026, https://doi.org/10.5194/amt-19-359-2026, 2026
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Many atmospheric science endeavors require temporally resolved profiles of temperature, humidity, and winds. Radiosondes are considered the gold standard for measuring these profiles, but the temporal resolution is frequently too coarse for many applications within the atmospheric boundary layer. This study proposes a new method using a normalized height grid in the temporal interpolation process that yields more accurate profiles in the convective boundary layer.
Calvin Coulbury, Ivy Tan, David Turner, and Chen Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2025-6553, https://doi.org/10.5194/egusphere-2025-6553, 2026
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Observations of low-level, single-layer clouds above the North Slope of Alaska, within the Arctic circle, are used to assess how cloud properties have changed from 2004 to 2023. Evidence is provided for a cooling influence of cloud property changes on Arctic amplified warming. Local temperature changes result in clouds becoming more opaque, driven by changes in cloud liquid water content. This work represents an avenue for the evaluation and improvement of model representations of Arctic clouds.
Jungmin Lee, Virendra P. Ghate, Arka Mitra, Lee M. Miller, Raghavendra Krishnamurthy, and Ulrike Egerer
Wind Energ. Sci., 10, 2755–2769, https://doi.org/10.5194/wes-10-2755-2025, https://doi.org/10.5194/wes-10-2755-2025, 2025
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This study evaluates how well the High-Resolution Rapid Refresh (HRRR) model represents wind and cloud patterns off coastal California near Morro Bay and Humboldt. Comparisons with buoy and satellite data show that the model captures overall cloudiness but underestimates cloud top height and misses daily variations. HRRR performs well under cloudy skies but shows larger errors under clear conditions.
Tessa E. Rosenberger, Thijs Heus, Girish N. Raghunathan, David D. Turner, Timothy J. Wagner, and Julia M. Simonson
Atmos. Meas. Tech., 18, 5129–5140, https://doi.org/10.5194/amt-18-5129-2025, https://doi.org/10.5194/amt-18-5129-2025, 2025
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Entrainment is key in understanding temperature and moisture changes within the boundary layer, but it is difficult to observe using ground-based observations. This work used simulations to verify an assumption that simplifies entrainment estimations from ground-based observational data, recognizing that entrainment is the combination of the transfer of heat and moisture from above the boundary layer into it and the change in concentration of heat and moisture as boundary layer depth changes.
Laura Bianco, Reagan Mendeke, Jakob Lindblom, Irina V. Djalalova, David D. Turner, and James M. Wilczak
Wind Energ. Sci., 10, 2117–2136, https://doi.org/10.5194/wes-10-2117-2025, https://doi.org/10.5194/wes-10-2117-2025, 2025
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Aliza Abraham, Matteo Puccioni, Arianna Jordan, Emina Maric, Nicola Bodini, Nicholas Hamilton, Stefano Letizia, Petra M. Klein, Elizabeth N. Smith, Sonia Wharton, Jonathan Gero, Jamey D. Jacob, Raghavendra Krishnamurthy, Rob K. Newsom, Mikhail Pekour, William Radünz, and Patrick Moriarty
Wind Energ. Sci., 10, 1681–1705, https://doi.org/10.5194/wes-10-1681-2025, https://doi.org/10.5194/wes-10-1681-2025, 2025
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This study is the first to use real-world atmospheric measurements to show that large wind plants can increase the height of the planetary boundary layer, the part of the atmosphere near the surface where life takes place. The planetary boundary layer height governs processes like pollutant transport and cloud formation and is a key parameter for modeling the atmosphere. The results of this study provide important insights into interactions between wind plants and their local environment.
Jonah K. Shaw, Dustin J. Swales, Sergio DeSouza-Machado, David D. Turner, Jennifer E. Kay, and David P. Schneider
Geosci. Model Dev., 18, 4935–4950, https://doi.org/10.5194/gmd-18-4935-2025, https://doi.org/10.5194/gmd-18-4935-2025, 2025
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Satellites have observed Earth's emissions of infrared radiation since the 1970s. Because infrared wavelengths interact with the atmosphere in distinct ways, these observations contain information about Earth and the atmosphere. We present a tool that runs within Earth system models and produces output that can be directly compared with satellite measurements of infrared radiation. We then use this tool for climate model evaluation, climate change detection, and satellite mission design.
Lindsay M. Sheridan, Jiali Wang, Caroline Draxl, Nicola Bodini, Caleb Phillips, Dmitry Duplyakin, Heidi Tinnesand, Raj K. Rai, Julia E. Flaherty, Larry K. Berg, Chunyong Jung, Ethan Young, and Rao Kotamarthi
Wind Energ. Sci., 10, 1551–1574, https://doi.org/10.5194/wes-10-1551-2025, https://doi.org/10.5194/wes-10-1551-2025, 2025
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Three recent wind resource datasets are assessed for their skills in representing annual average wind speeds and seasonal, diurnal, and interannual trends in the wind resource in coastal locations to support customers interested in small and midsize wind energy.
Vincent Michaud-Belleau, Michel Gaudreau, Jean Lacoursière, Éric Boisvert, Lalaina Ravelomanantsoa, David D. Turner, and Luc Rochette
Atmos. Meas. Tech., 18, 3585–3609, https://doi.org/10.5194/amt-18-3585-2025, https://doi.org/10.5194/amt-18-3585-2025, 2025
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The Atmospheric Sounder Spectrometer by Infrared Spectral Technology (ASSIST) is a commercially available ground-based infrared spectroradiometer. It is designed for automated and passive measurement of the thermal radiation emitted by the atmosphere, providing information about the vertical distribution of temperature and humidity, trace gases, clouds, and aerosols in the boundary layer. In this paper, we outline the key characteristics of the ASSIST hardware and signal processing algorithm that yields downwelling radiance spectra in near real-time.
David D. Turner, Maria P. Cadeddu, Julia M. Simonson, and Timothy J. Wagner
Atmos. Meas. Tech., 18, 3533–3546, https://doi.org/10.5194/amt-18-3533-2025, https://doi.org/10.5194/amt-18-3533-2025, 2025
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When deriving a geophysical variable from remote sensors, the uncertainty and information content are critical. The latter quantify specifies what fraction of a real perturbation would be observed in the derived variable. This paper outlines, for the first time, a methodology for propagating the information content from multiple remote sensors into a derived product using horizontal advection as an example.
Daphne Quint, Julie K. Lundquist, Nicola Bodini, and David Rosencrans
Wind Energ. Sci., 10, 1269–1301, https://doi.org/10.5194/wes-10-1269-2025, https://doi.org/10.5194/wes-10-1269-2025, 2025
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Offshore wind farms along the US East Coast can have limited effects on local weather. To study these effects, we include wind farms near Massachusetts and Rhode Island, and we test different amounts of turbulence in our model. We analyze changes in wind, temperature, and turbulence. Simulated effects on surface temperature and turbulence change depending on how much turbulence is added to the model. The extent of the wind farm wake depends on how deep the atmospheric boundary layer is.
Raghavendra Krishnamurthy, Rob K. Newsom, Colleen M. Kaul, Stefano Letizia, Mikhail Pekour, Nicholas Hamilton, Duli Chand, Donna Flynn, Nicola Bodini, and Patrick Moriarty
Wind Energ. Sci., 10, 361–380, https://doi.org/10.5194/wes-10-361-2025, https://doi.org/10.5194/wes-10-361-2025, 2025
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This study examines how atmospheric phenomena affect the recovery of wind farm wake – the disturbed air behind turbines. In regions like Oklahoma, where wind farms are often clustered, understanding wake recovery is crucial. We found that wind farms can alter phenomena like low-level jets, which are common in Oklahoma, by deflecting them above the wind farm. As a result, the impact of wakes can be observed up to 1–2 km above ground level.
David Rosencrans, Julie K. Lundquist, Mike Optis, and Nicola Bodini
Wind Energ. Sci., 10, 59–81, https://doi.org/10.5194/wes-10-59-2025, https://doi.org/10.5194/wes-10-59-2025, 2025
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The US offshore wind industry is growing rapidly. Expansion into cold climates will subject turbines and personnel to hazardous icing. We analyze the 21-year icing risk for US east coast wind areas based on numerical weather prediction simulations and further assess impacts from wind farm wakes over one winter season. Sea spray icing at 10 m can occur up to 67 h per month. However, turbine–atmosphere interactions reduce icing hours within wind plant areas.
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
Atmos. Meas. Tech., 17, 6603–6624, https://doi.org/10.5194/amt-17-6603-2024, https://doi.org/10.5194/amt-17-6603-2024, 2024
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Continuous profile observations of temperature and humidity in the lowest part of the atmosphere are essential for the evaluation of numerical weather prediction models and data assimilation for better weather forecasts. Such profiles can be retrieved from passive ground-based remote sensing instruments like infrared spectrometers and microwave radiometers. In this study, we describe three recent modifications to the retrieval framework TROPoe for improved temperature and humidity profiles.
Tessa E. Rosenberger, David D. Turner, Thijs Heus, Girish N. Raghunathan, Timothy J. Wagner, and Julia Simonson
Atmos. Meas. Tech., 17, 6595–6602, https://doi.org/10.5194/amt-17-6595-2024, https://doi.org/10.5194/amt-17-6595-2024, 2024
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This work used model output to show that considering the changes in boundary layer depth over time in the calculations of variables such as fluxes and variance yields more accurate results than cases where calculations were done at a constant height. This work was done to improve future observations of these variables at the top of the boundary layer.
Laura Bianco, Bianca Adler, Ludovic Bariteau, Irina V. Djalalova, Timothy Myers, Sergio Pezoa, David D. Turner, and James M. Wilczak
Atmos. Meas. Tech., 17, 3933–3948, https://doi.org/10.5194/amt-17-3933-2024, https://doi.org/10.5194/amt-17-3933-2024, 2024
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The Tropospheric Remotely Observed Profiling via Optimal Estimation physical retrieval is used to retrieve temperature and humidity profiles from various combinations of passive and active remote sensing instruments, surface platforms, and numerical weather prediction models. The retrieved profiles are assessed against collocated radiosonde in non-cloudy conditions to assess the sensitivity of the retrievals to different input combinations. Case studies with cloudy conditions are also inspected.
Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, and Walter Musial
Earth Syst. Sci. Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024, https://doi.org/10.5194/essd-16-1965-2024, 2024
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This article presents the 2023 National Offshore Wind data set (NOW-23), an updated resource for offshore wind information in the US. It replaces the Wind Integration National Dataset (WIND) Toolkit, offering improved accuracy through advanced weather prediction models. The data underwent regional tuning and validation and can be accessed at no cost.
Lindsay M. Sheridan, Raghavendra Krishnamurthy, William I. Gustafson Jr., Ye Liu, Brian J. Gaudet, Nicola Bodini, Rob K. Newsom, and Mikhail Pekour
Wind Energ. Sci., 9, 741–758, https://doi.org/10.5194/wes-9-741-2024, https://doi.org/10.5194/wes-9-741-2024, 2024
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In 2020, lidar-mounted buoys owned by the US Department of Energy (DOE) were deployed off the California coast in two wind energy lease areas and provided valuable year-long analyses of offshore low-level jet (LLJ) characteristics at heights relevant to wind turbines. In addition to the LLJ climatology, this work provides validation of LLJ representation in atmospheric models that are essential for assessing the potential energy yield of offshore wind farms.
David Rosencrans, Julie K. Lundquist, Mike Optis, Alex Rybchuk, Nicola Bodini, and Michael Rossol
Wind Energ. Sci., 9, 555–583, https://doi.org/10.5194/wes-9-555-2024, https://doi.org/10.5194/wes-9-555-2024, 2024
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The US offshore wind industry is developing rapidly. Using yearlong simulations of wind plants in the US mid-Atlantic, we assess the impacts of wind turbine wakes. While wakes are the strongest and longest during summertime stably stratified conditions, when New England grid demand peaks, they are predictable and thus manageable. Over a year, wakes reduce power output by over 35 %. Wakes in a wind plant contribute the most to that reduction, while wakes between wind plants play a secondary role.
Volker Wulfmeyer, Christoph Senff, Florian Späth, Andreas Behrendt, Diego Lange, Robert M. Banta, W. Alan Brewer, Andreas Wieser, and David D. Turner
Atmos. Meas. Tech., 17, 1175–1196, https://doi.org/10.5194/amt-17-1175-2024, https://doi.org/10.5194/amt-17-1175-2024, 2024
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A simultaneous deployment of Doppler, temperature, and water-vapor lidar systems is used to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of weather forecast and climate models.
Ulrike Egerer, Holger Siebert, Olaf Hellmuth, and Lise Lotte Sørensen
Atmos. Chem. Phys., 23, 15365–15373, https://doi.org/10.5194/acp-23-15365-2023, https://doi.org/10.5194/acp-23-15365-2023, 2023
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Low-level jets (LLJs) are strong winds near the surface and occur frequently in the Arctic in stable conditions. Using tethered-balloon profile measurements in Greenland, we analyze a multi-hour period with an LLJ that later weakens and finally collapses. Increased shear-induced turbulence at the LLJ bounds mostly does not reach the ground until the LLJ collapses. Our findings support the hypothesis that a passive tracer can be advected with an LLJ and mixed down when the LLJ collapses.
Sunil Baidar, Timothy J. Wagner, David D. Turner, and W. Alan Brewer
Atmos. Meas. Tech., 16, 3715–3726, https://doi.org/10.5194/amt-16-3715-2023, https://doi.org/10.5194/amt-16-3715-2023, 2023
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This paper provides a new method to retrieve wind profiles from coherent Doppler lidar (CDL) measurements. It takes advantage of layer-to-layer correlation in wind profiles to provide continuous profiles of up to 3 km by filling in the gaps where the CDL signal is too small to retrieve reliable results by itself. Comparison with the current method and collocated radiosonde wind measurements showed excellent agreement with no degradation in results where the current method gives valid results.
Ulrike Egerer, John J. Cassano, Matthew D. Shupe, Gijs de Boer, Dale Lawrence, Abhiram Doddi, Holger Siebert, Gina Jozef, Radiance Calmer, Jonathan Hamilton, Christian Pilz, and Michael Lonardi
Atmos. Meas. Tech., 16, 2297–2317, https://doi.org/10.5194/amt-16-2297-2023, https://doi.org/10.5194/amt-16-2297-2023, 2023
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This paper describes how measurements from a small uncrewed aircraft system can be used to estimate the vertical turbulent heat energy exchange between different layers in the atmosphere. This is particularly important for the atmosphere in the Arctic, as turbulent exchange in this region is often suppressed but is still important to understand how the atmosphere interacts with sea ice. We present three case studies from the MOSAiC field campaign in Arctic sea ice in 2020.
Nicola Bodini, Simon Castagneri, and Mike Optis
Wind Energ. Sci., 8, 607–620, https://doi.org/10.5194/wes-8-607-2023, https://doi.org/10.5194/wes-8-607-2023, 2023
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The National Renewable Energy Laboratory (NREL) has published updated maps of the wind resource along all US coasts. Given the upcoming offshore wind development, it is essential to quantify the uncertainty that comes with the modeled wind resource data set. The paper proposes a novel approach to quantify this numerical uncertainty by leveraging available observations along the US East Coast.
Maria P. Cadeddu, Virendra P. Ghate, David D. Turner, and Thomas E. Surleta
Atmos. Chem. Phys., 23, 3453–3470, https://doi.org/10.5194/acp-23-3453-2023, https://doi.org/10.5194/acp-23-3453-2023, 2023
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We analyze the variability in marine boundary layer moisture at the Eastern North Atlantic site on a monthly and daily temporal scale and examine its fundamental role in the control of boundary layer cloudiness and precipitation. The study also highlights the complex interaction between large-scale and local processes controlling the boundary layer moisture and the importance of the mesoscale spatial distribution of vapor to support convection and precipitation.
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
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Rapid changes in wind speed make the integration of wind energy produced during persistent orographic cold-air pools difficult to integrate into the electrical grid. By evaluating three 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-air pool event.
Gianluca Di Natale, David D. Turner, Giovanni Bianchini, Massimo Del Guasta, Luca Palchetti, Alessandro Bracci, Luca Baldini, Tiziano Maestri, William Cossich, Michele Martinazzo, and Luca Facheris
Atmos. Meas. Tech., 15, 7235–7258, https://doi.org/10.5194/amt-15-7235-2022, https://doi.org/10.5194/amt-15-7235-2022, 2022
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In this paper, we describe a new approach to test the consistency of the precipitating ice cloud optical and microphysical properties in Antarctica, Dome C, retrieved from hyperspectral measurements in the far-infrared, with the reflectivity detected by a co-located micro rain radar operating at 24 GHz. The retrieved ice crystal sizes were found in accordance with the direct measurements of an optical imager, also installed at Dome C, which can collect the falling ice particles.
William J. Shaw, Larry K. Berg, Mithu Debnath, Georgios Deskos, Caroline Draxl, Virendra P. Ghate, Charlotte B. Hasager, Rao Kotamarthi, Jeffrey D. Mirocha, Paytsar Muradyan, William J. Pringle, David D. Turner, and James M. Wilczak
Wind Energ. Sci., 7, 2307–2334, https://doi.org/10.5194/wes-7-2307-2022, https://doi.org/10.5194/wes-7-2307-2022, 2022
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This paper provides a review of prominent scientific challenges to characterizing the offshore wind resource using as examples phenomena that occur in the rapidly developing wind energy areas off the United States. The paper also describes the current state of modeling and observations in the marine atmospheric boundary layer and provides specific recommendations for filling key current knowledge gaps.
Alex Rybchuk, Timothy W. Juliano, Julie K. Lundquist, David Rosencrans, Nicola Bodini, and Mike Optis
Wind Energ. Sci., 7, 2085–2098, https://doi.org/10.5194/wes-7-2085-2022, https://doi.org/10.5194/wes-7-2085-2022, 2022
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Numerical weather prediction models are used to predict how wind turbines will interact with the atmosphere. Here, we characterize the uncertainty associated with the choice of turbulence parameterization on modeled wakes. We find that simulated wind speed deficits in turbine wakes can be significantly sensitive to the choice of turbulence parameterization. As such, predictions of future generated power are also sensitive to turbulence parameterization choice.
Heather Guy, David D. Turner, Von P. Walden, Ian M. Brooks, and Ryan R. Neely
Atmos. Meas. Tech., 15, 5095–5115, https://doi.org/10.5194/amt-15-5095-2022, https://doi.org/10.5194/amt-15-5095-2022, 2022
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Fog formation is highly sensitive to near-surface temperatures and humidity profiles. Passive remote sensing instruments can provide continuous measurements of the vertical temperature and humidity profiles and liquid water content, which can improve fog forecasts. Here we compare the performance of collocated infrared and microwave remote sensing instruments and demonstrate that the infrared instrument is especially sensitive to the onset of thin radiation fog.
James B. Duncan Jr., Laura Bianco, Bianca Adler, Tyler Bell, Irina V. Djalalova, Laura Riihimaki, Joseph Sedlar, Elizabeth N. Smith, David D. Turner, Timothy J. Wagner, and James M. Wilczak
Atmos. Meas. Tech., 15, 2479–2502, https://doi.org/10.5194/amt-15-2479-2022, https://doi.org/10.5194/amt-15-2479-2022, 2022
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In this study, several ground-based remote sensing instruments are used to estimate the height of the convective planetary boundary layer, and their performance is compared against independent boundary layer depth estimates obtained from radiosondes launched as part of the CHEESEHEAD19 field campaign. The impact of clouds (particularly boundary layer clouds) on the estimation of the boundary layer depth is also investigated.
Vincent Pronk, Nicola Bodini, Mike Optis, Julie K. Lundquist, Patrick Moriarty, Caroline Draxl, Avi Purkayastha, and Ethan Young
Wind Energ. Sci., 7, 487–504, https://doi.org/10.5194/wes-7-487-2022, https://doi.org/10.5194/wes-7-487-2022, 2022
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In this paper, we have assessed to which extent mesoscale numerical weather prediction models are more accurate than state-of-the-art reanalysis products in characterizing the wind resource at heights of interest for wind energy. The conclusions of our work will be of primary importance to the wind industry for recommending the best data sources for wind resource modeling.
Irina V. Djalalova, David D. Turner, Laura Bianco, James M. Wilczak, James Duncan, Bianca Adler, and Daniel Gottas
Atmos. Meas. Tech., 15, 521–537, https://doi.org/10.5194/amt-15-521-2022, https://doi.org/10.5194/amt-15-521-2022, 2022
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In this paper we investigate the synergy obtained by combining active (radio acoustic sounding system – RASS) and passive (microwave radiometer) remote sensing observations to obtain temperature vertical profiles through a radiative transfer model. Inclusion of the RASS observations leads to more accurate temperature profiles from the surface to 5 km above ground, well above the maximum height of the RASS observations themselves (2000 m), when compared to the microwave radiometer used alone.
Nicola Bodini, Weiming Hu, Mike Optis, Guido Cervone, and Stefano Alessandrini
Wind Energ. Sci., 6, 1363–1377, https://doi.org/10.5194/wes-6-1363-2021, https://doi.org/10.5194/wes-6-1363-2021, 2021
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We develop two machine-learning-based approaches to temporally extrapolate uncertainty in hub-height wind speed modeled by a numerical weather prediction model. We test our approaches in the California Outer Continental Shelf, where a significant offshore wind energy development is currently being planned, and we find that both provide accurate results.
Cited articles
Benjamin, S. G., James, E. P., Turner, D. D., Balmes, K. A., Sedlar, J., Lantz, K. O., Jensen, A. A., Riihimaki, L. D., and Augustine, J. A.: Excessive downward shortwave radiation in the HRRR and RAP weather models and testing strategies for improvements, Mon. Weather Rev., 153, 2279–2293, https://doi.org/10.1175/MWR-D-25-0094.1, 2025. a
Bianco, L., Djalalova, I. V., Wilczak, J. M., Olson, J. B., Kenyon, J. S., Choukulkar, A., Berg, L. K., Fernando, H. J. S., Grimit, E. P., Krishnamurthy, R., Lundquist, J. K., Muradyan, P., Pekour, M., Pichugina, Y., Stoelinga, M. T., and Turner, D. D.: Impact of model improvements on 80 m wind speeds during the second Wind Forecast Improvement Project (WFIP2), Geosci. Model Dev., 12, 4803–4821, https://doi.org/10.5194/gmd-12-4803-2019, 2019. a, b, c, d
Bianco, L., Mendeke, R., Lindblom, J., Djalalova, I. V., Turner, D. D., and Wilczak, J. M.: Evaluating the ability of the operational High Resolution Rapid Refresh model version 3 (HRRRv3) and version 4 (HRRRv4) to forecast wind ramp events in the US Great Plains, Wind Energ. Sci., 10, 2117–2136, https://doi.org/10.5194/wes-10-2117-2025, 2025. a
Bodini, N., Castagneri, S., and Optis, M.: Long-term uncertainty quantification in WRF-modeled offshore wind resource off the US Atlantic coast, Wind Energ. Sci., 8, 607–620, https://doi.org/10.5194/wes-8-607-2023, 2023. a
Bodini, N., Optis, M., Redfern, S., Rosencrans, D., Rybchuk, A., Lundquist, J. K., Pronk, V., Castagneri, S., Purkayastha, A., Draxl, C., Krishnamurthy, R., Young, E., Roberts, B., Rosenlieb, E., and Musial, W.: The 2023 National Offshore Wind data set (NOW-23), Earth Syst. Sci. Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024, 2024. a, b, c, d
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Buster, G., Pinchuk, P., Lavin, L., Benton, B., and Bodini, N.: Bias Correcting NOAA’s High-Resolution Rapid Refresh (HRRR) Wind Resource Data for Grid Integration Applications, Tech. Rep. NREL/PR-6A20-91749, National Renewable Energy Laboratory, https://doi.org/10.2172/2479268, 2024c. a
Cannon, A. J., Sobie, S. R., and Murdock, T. Q.: Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?, J. Climate, 28, 6938–6959, https://doi.org/10.1175/JCLI-D-14-00754.1, 2015. a, b
Carvalho, D., Rocha, A., Gómez-Gesteira, M., and Santos, C.: A sensitivity study of the WRF model in wind simulation for an area of high wind energy, Environ. Model. Softw., 33, 23–34, https://doi.org/10.1016/j.envsoft.2012.01.019, 2012. a, b
Cheynet, E., Diezel, J. M., Haakenstad, H., Breivik, Ø., Peña, A., and Reuder, J.: Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observations, Wind Energ. Sci., 10, 733–754, https://doi.org/10.5194/wes-10-733-2025, 2025. a
Collins, E., Lebo, Z. J., Cox, R., Hammer, C., Brothers, M., Geerts, B., Capella, R., and McCorkle, S.: Forecasting High Wind Events in the HRRR Model over Wyoming and Colorado. Part I: Evaluation of Wind Speeds and Gusts, Weather Forecast., 39, 705–723, https://doi.org/10.1175/WAF-D-23-0036.1, 2024. a, b
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Dörenkämper, M., Olsen, B. T., Witha, B., Hahmann, A. N., Davis, N. N., Barcons, J., Ezber, Y., García-Bustamante, E., González-Rouco, J. F., Navarro, J., Sastre-Marugán, M., Sīle, T., Trei, W., Žagar, M., Badger, J., Gottschall, J., Sanz Rodrigo, J., and Mann, J.: The Making of the New European Wind Atlas – Part 2: Production and evaluation, Geosci. Model Dev., 13, 5079–5102, https://doi.org/10.5194/gmd-13-5079-2020, 2020. a
Dowell, D. C., Alexander, C. R., James, E. P., Weygandt, S. S., Benjamin, S. G., Manikin, G. S., Blake, B. T., Brown, J. M., Olson, J. B., Hu, M., Smirnova, T. G., Ladwig, T., Kenyon, J. S., Ahmadov, R., Turner, D. D., Duda, J. D., and Alcott, T. I.: The High-Resolution Rapid Refresh (HRRR): An Hourly Updating Convection-Allowing Forecast Model. Part I: Motivation and System Description, Weather Forecast., 37, 1371–1395, https://doi.org/10.1175/WAF-D-21-0151.1, 2022. a, b
Draxl, C., Clifton, A., Hodge, B.-M., and McCaa, J.: The Wind Integration National Dataset (WIND) Toolkit, Appl. Energ., 151, 355–366, https://doi.org/10.1016/j.apenergy.2015.03.121, 2015. a, b, c
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Short summary
To plan a reliable United States power grid, engineers need continuous weather data. Because the previous standard record ended in 2013, we created a new, easy-to-use weather database by repackaging complex weather forecasting models onto the same historical grid. We compared our data against real-world observations nationwide, finding it is highly accurate. This provides a seamless, reliable new standard to help plan the future of our national energy system.
To plan a reliable United States power grid, engineers need continuous weather data. Because the...
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