About

Prof. Julie K. Lundquist is the Bloomberg Distinguished Professor of Atmospheric Science and Wind Energy at Johns Hopkins University. She leads an interdisciplinary research group within the Department of Earth & Planetary Sciences and Mechanical Engineering, with a joint appointment at the National Renewable Energy Laboratory. Her research focuses on understanding the dynamics of the atmospheric boundary layer, emphasizing atmosphere-wind energy interactions through observational and computational approaches. Prof. Lundquist joined Johns Hopkins University in July 2024, also becoming a member of the Ralph O’Connor Sustainable Energy Institute and serving on its Leadership Council. Her academic background includes a Ph.D. in Astrophysics, Planetary, and Atmospheric Sciences from the University of Colorado Boulder, a Master's degree in the same field from the University of Colorado Boulder, and a B.A. in English and Physics from Trinity University. Her previous roles include professorship at the University of Colorado Boulder and a scientist position at Lawrence Livermore National Laboratory.

Research topics

• Environmental science
• Physics
• Engineering
• Meteorology
• Political Science
• Mechanics
• Marine engineering
• Geology
• Computer Science
• Geography
• Aerospace engineering
• Operating system
• Structural engineering
• Automotive engineering
• World Wide Web
• Aeronautics
• Mathematics
• Atmospheric sciences

Selected publications

• Assessing risks and opportunities for offshore wind energy under evolving tropical cyclone hazards

  Advances in wind engineering. · 2026-03-01

  articleOpen access

  This study presents a simulation-based framework for assessing offshore wind turbine failure risks and potential benefits from conceivable increased power generation during tropical cyclones. Using a future climate model based on projected sea surface temperatures (SSTs) of the Shared Socioeconomic Pathway 3 scenario (SSP3-7.0), the research examines the impact of changing tropical cyclone patterns on offshore wind power generation efficiency, safety, and reliability. Bias correction techniques are applied to global climate models (GCMs) to improve the accuracy of future climate projections, resulting in more robust and representative outcomes. Hazard curves for hurricane wind speeds indicate increased wind demand under the SSP3-7.0 scenario, particularly affecting Northeastern sites. In this study, the projected 50-year return-period wind speeds increase by 8 to 27% by 2060. Under the worst-case scenario in which the turbine loses yaw control and experiences a 65° yaw misalignment with respect to incoming wind, the probability of failure remains below 10% for IEC Typhoon Class (Class T) turbines with a reference wind speed of 57 m/s. Benefit analysis highlights potential increases in power generation at northern locations such as Massachusetts, New York and New Jersey, due to the greater frequency of weak tropical storms reaching northern regions. This study also evaluates hurricane-induced failure risks for offshore wind turbines by integrating site-specific hazard curves with structural fragility analysis. Results indicate that evaluating turbines designed for current climate conditions, particularly those based on IEC Class I (50 m/s survival wind speed) and Class T (57 m/s survival wind speed) specifications, using future hazard curves leads to more than an order-of-magnitude increase in annual failure probability, whereas designs that account for future climate conditions demonstrate substantially lower failure probabilities and improved structural reliability. At the time of manuscript preparation, several manufacturers produce turbines that exceed the IEC standard, with survival wind speeds of up to 80 m/s. The failure risk of these turbines is therefore expected to be lower than that evaluated in this study. • A simulation framework evaluates both risks and power gains from tropical cyclones. • Future SSTs under SSP3-7.0 increase hurricane hazard levels for 11 U.S. offshore wind energy sites. • Mid-Atlantic and northeastern offshore wind sites may require higher turbine survival capacities under future climate conditions. • Northern sites may gain power due to increased frequency of weaker storms. • Designing towers based on current climate conditions reduces tower reliability if future hurricane hazard under SSP3-7.0 pathway is realized.

  PublisherDOI

• Grand Challenges in Designing Resilient Wind Energy Systems in Areas Prone to Tropical Cyclones

  2026-02-11

  articleOpen access

  Abstract. Deployment of wind energy systems in cyclone-prone regions faces substantial challenges due to risks posed by tropical cyclones (TCs). These storms can generate extremely high winds and waves that have the potential to cause significant structural damage to turbines, disrupt energy production, and result in major financial losses. As such, it is important to better understand and quantify the risks associated with TCs and adapt design standards and operational guidelines to meet the increased reliability requirements for systems in these high-risk areas. Addressing these challenges requires significant advancements in modeling capabilities, the collection of high-quality data, and the integration of these resources to ensure that wind systems in cyclone-prone regions achieve a level of reliability comparable to systems in less hazardous environments (e.g., the North Sea). This article aims to shed light on the grand challenges in designing resilient wind energy systems in cyclone-prone regions by presenting the current state of research and engineering practices and identifying key research gaps; and to offer recommendations for future work, highlighting the need for enhanced modeling tools, data integration techniques, and more resilient design approaches.

  PublisherDOI

• The effects of wind farm wakes on freezing sea spray in the mid-Atlantic offshore wind energy areas

  Wind energy science · 2025-01-08 · 2 citations

  articleOpen access

  Abstract. The USA is expanding its wind energy fleet offshore where winds tend to be strong and consistent. In the mid-Atlantic, strong winds, which promote convective heat transfer and wind-generated sea spray, paired with cold temperatures can cause ice on equipment when plentiful moisture is available. Near-surface icing is induced by a moisture flux from sea spray, which poses a risk to vessels and crews. Ice accretion on turbine rotors and blades occurs from precipitation and in-cloud icing at temperatures below freezing. Ice accretion induces load and fatigue on mechanical parts, which reduces blade performance and power production. Thus, it is crucial to understand the icing hazard across the mid-Atlantic. We analyze Weather Research and Forecasting model numerical weather prediction simulations at a coarse temporal resolution over a 21-year period to assess freezing sea spray (FSS) events over the long-term record and at finer granularity over the 2019–2020 winter season to identify the post-construction turbine impacts. Over the 2019–2020 winter season, results suggest that sea-spray-induced icing can occur up to 67 h per month at 10 m at higher latitudes. Icing events during this season typically occur during cold air outbreaks (CAOs), which are the introduction of cold continental air over the warmer maritime surface. During the 2019–2020 winter season, CAOs lasted a total duration of 202 h. While not all freezing sea spray events occurred during CAOs over the 21-year period, all CAO events had FSS present. Further, we assess the turbine–atmosphere impacts of wind plant installation on icing using the fine-scale simulation dataset. Wakes from large wind plants reduce the wind speed, which mitigates the initiation of sea spray off white-capped waves. Conversely, the near-surface turbine-induced introduction of cold air in frequent wintertime unstable conditions enhances the risk for freezing. Overall, the turbine–atmosphere interaction causes a small reduction in FSS hours within the wind plant areas, with a reduction up to 15 h in January at the 10 and 20 m heights.

  PublisherOA PDFDOI

• Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California

  Wind energy science · 2025-07-02 · 3 citations

  articleOpen access

  Abstract. Mesoscale model predictions of wind, turbulence, and wind energy capacity factors are evaluated in the Altamont Pass Wind Resource Area of California (APWRA), where the diurnal regional sea breeze and associated terrain-driven speedup flows drive wind energy production during the summer months. Results from the Weather Research and Forecasting model version 4.4 using a novel three-dimensional planetary boundary layer (3D PBL) scheme, which treats both vertical and horizontal turbulent mixing, are compared to those using a well-established one-dimensional (1D) scheme that treats only vertical turbulent mixing. Each configuration is evaluated over a nearly 3-month-long period during the Hill Flow Study, and due to the recurring nature of the observed speedup flows, diurnal composite averaging is used to capture robust trends in model performance. Both model configurations showed similar overall skill. The general timing and direction of the speedup flows is captured, but their magnitude is overestimated within a typical wind turbine rotor layer. Both also fail to capture a persistent observed near-surface jet-like flow, likely due to the limited grid resolution that is typical of mesoscale models. However, the 3D PBL configuration shows several minor improvements over the 1D PBL configuration, including improved wind speed and turbulence kinetic energy profiles during the accelerating phase of the speedup events, as well as reduced positive wind speed bias at surface stations across the APWRA region. Using a mesoscale wind farm parameterization, modeled capacity factors are also compared to monthly data reported to the US Energy Information Administration (EIA) during the study period. Although the monthly trend in the data is captured, both model configurations overestimate capacity factors by roughly 7 %–11 %. Through model evaluation, this study provides confidence in the 3D PBL scheme for wind energy applications in complex terrain and provides guidance for future testing.

  PublisherOA PDFDOI

• A North Sea in situ evaluation of the Fitch Wind Farm Parametrization within the Mellor–Yamada–Nakanishi–Niino and 3D Planetary Boundary Layer schemes

  2025-02-26

  preprintOpen access

  Abstract. Wind resource assessments and wind power forecasts that account for wind farm wakes are sensitive to the choice of planetary boundary layer (PBL) scheme. This work compares the one-dimensional Mellor–Yamada–Nakanishi–Niino (MYNN) PBL scheme with a three-dimensional PBL (3DPBL) scheme, evaluating predictions made with both schemes against two sets of North Sea in situ observations of wind farm wakes. The optimal PBL scheme varies based on the observations (FINO1 tower vs. aircraft), the quantity of interest (wind speed vs. turbulence kinetic energy [TKE]), and the error metric (bias, centered root mean square error [cRMSE], and R2 vs. earth mover’s distance [EMD]). Whereas 3DPBL wind speeds outperform MYNN wind speeds with respect to the cRMSE at the FINO1 site within the turbine rotor layer, 3DPBL TKE bias underperforms MYNN TKE bias when compared to aircraft observations. Wind speeds in the aircraft region are ambiguous as to which PBL scheme is optimal. Aircraft MYNN wind speeds outperform 3DPBL wind speeds with respect to R2 and cRMSE but underperform with respect to bias and EMD. Tests to determine the optimal wind farm TKE factor reveal similar variability: The aircraft observations support a wind farm TKE factor of 1 for MYNN cases and a wind farm TKE factor of 0 or 0.25 for 3DPBL cases. In contrast, the optimal wind farm TKE factor based on FINO1 observations differs by metric. For FINO1 wind speeds, the cRMSE suggests that a wind farm TKE factor of 0 is most appropriate, whereas the bias and EMD support a wind farm TKE factor of 1.

  PublisherDOI

• Abstract 210: Ten‐Year Experience in the Endovascular Management of Spinal Vascular Malformations: Outcomes, Predictive Factors, and Lessons Learned from a Single Center

  Stroke Vascular and Interventional Neurology · 2025-11-01

  articleOpen access

  Background Spinal vascular malformations (SVMs) are rare and complex entities that pose considerable diagnostic and therapeutic challenges. Although infrequent, delayed diagnosis and treatment can result in irreversible neurological deficits. Objective To evaluate the clinical presentation, diagnostic strategies, treatment outcomes, and long‐term follow‐up of patients with SVMs managed at Instituto Médico ENERI over a 10‐year period, and to compare these findings with global data. Methods We retrospectively analyzed 38 patients with angiographically confirmed SVMs treated between 2015 and 2025. Lesions were classified according to Takai's system. All patients underwent endovascular embolization, and outcomes were assessed using imaging, symptom resolution, and Aminoff and Logue Scale (ALS) scores at follow‐up. Results The median age at diagnosis was 56 years. Paraparesis and paresthesia were the most common presenting symptoms, affecting 26 patients, while 4 presented with rupture. Lesion types included Type II glomus AVMs (n=9), Type I dural AVFs (n=11), and perimedullary AVFs (n=9). Complete angiographic occlusion was achieved in 96% of cases. Primary arterial feeders were lumbar (n=17), radiculomedullary (n=10), and intercostal arteries (n=25). Patients treated within 13 months of symptom onset demonstrated significantly better functional outcomes at follow‐up. Conclusion Endovascular embolization is an effective and durable treatment for SVMs, with high rates of complete occlusion and favorable neurological recovery, particularly when performed early. Our findings reinforce the importance of prompt diagnosis and timely intervention to optimize patient outcomes and align with international experience in the management of these complex lesions.

  PublisherDOI

• Simulated meteorological impacts of offshore wind turbines and sensitivity to the amount of added turbulence kinetic energy

  Wind energy science · 2025-07-10 · 3 citations

  articleOpen access

  Abstract. Offshore wind energy projects are currently in development off the east coast of the United States and may influence the local meteorology of the region. Wind power production and other commercial uses in this area are related to atmospheric conditions, and so it is important to understand how future wind plants may change the local meteorology. In the absence of measurements of potential wind plant impacts on meteorology, simulations offer the next-best possible insight into wake effects on boundary layer height, temperature, fluxes, and wind speeds. However, simulation tools that capture these effects offer multiple options for representing the amount of turbine-added turbulence that may impact assessments of micrometeorological effects. To explore this sensitivity, we compare 1 year of simulations from the Weather Research and Forecasting (WRF) model with and without wind plants incorporated, focusing on the lease area south of Massachusetts and Rhode Island. The simulations with wind plants are repeated to include both the maximum and minimum amounts of added turbulence to provide bounds on the potential impacts. We assess changes in wind speeds, 2 m temperature, surface heat flux, turbulence kinetic energy (TKE), and boundary layer height during different stability classifications and ambient wind speeds over the entire year and compare results for the degree of added turbulence in the wind plant simulations. Because the wake behavior may be a function of boundary layer stability, in this paper, we also present a machine learning algorithm to quantify the area and distance of the wake generated by the wind plant. This analysis enables us to identify the relationship between wake extent and boundary layer height. We find that hub-height wind speed is reduced within and downwind of the wind plant, with the strongest impacts occurring during stable conditions and faster wind speeds in region 3 of the turbine power curve, although impacts lessen as wind speeds increase past 15 m s−1. In contrast, wind speeds near the surface decrease when no turbine-added turbulence is included but can increase for stably stratified conditions when 100 % of possible TKE is included in the simulations. TKE increases at hub height in the simulations with added TKE for all stability classes, suggesting that atmospheric stability does not immediately modify the TKE generated by turbines. Negligible changes in hub-height TKE manifest in the simulations without the added TKE. At the surface, TKE increases in the simulations with maximum added turbulence only for unstable conditions. In the no-added-turbulence simulations, surface TKE decreases slightly in neutral and unstable simulations. Differences in 2 m temperatures and surface heat fluxes are small but vary considerably with atmospheric stability and the amount of added TKE. Boundary layer heights increase within the wind plant when turbine-added turbulence is included and decrease slightly downwind during stable conditions. In contrast, with no added turbulence, the boundary layer height is in general reduced in stable conditions with wind speeds less than 15 m s−1 and slightly increased in neutral conditions. Finally, shallower upwind boundary layer heights tend to correlate with larger wake areas and distances, though other factors likely also play a role in determining the extent of the wind plant wake. These simulation-based results provide a bound for micrometeorological impacts of wind plant wakes: simulations that couple the atmosphere to the ocean may reduce these impacts, and we await observational verification.

  PublisherOA PDFDOI

• Differences in cluster and internal wake effects from mesoscale and large-eddy simulations off the U.S. East Coast

  2025-08-29

  articleOpen access

  Abstract. Mesoscale simulations are increasingly used to estimate wake effects within and between large wind farms, despite limited validation for large-scale wake effects. This study evaluates the capabilities and limitations of mesoscale simulations in capturing wake-induced impacts on wind turbine power production through a direct comparison with large-domain large-eddy simulations (LES) for three planned offshore wind farms under realistic atmospheric conditions and a range of atmospheric stabilities. We assess mesoscale performance in replicating wake characteristics behind single and multiple turbine clusters and quantify the resulting variability in mean turbine power. Results show that mesoscale Weather Research and Forecasting simulations with the Fitch wind farm parameterization capture key features of the velocity deficit downstream of both single and multiple wind farms, with mean root-mean-square errors near 5 % and good agreement with stability-driven wake behavior. However, in these simulations, the mesoscale Fitch parameterization underestimates power losses from internal wake effects, particularly when turbines align with the prevailing wind direction or under stable stratification. In these conditions, individual wakes persist and dominate downstream power deficits. The coarse resolution of the mesoscale simulations limits their ability to resolve individual wind turbine wakes that drive power fluctuations within wind farms. Nonetheless, mesoscale simulations can yield accurate estimates of combined wake losses from internal and cluster effects across some wind direction sectors, where errors in wake representation may cancel out. These findings underscore the strengths of mesoscale simulations for capturing broader wake patterns, while highlighting their limitations for modeling turbine-level power losses. Future work should explore hybrid modeling approaches to capture both long-range cluster wake propagation and localized internal wake dynamics.

  PublisherOA PDFDOI

• Editorial for the collection “Preparatory Work for the American Wake Experiment (AWAKEN)”

  Journal of Renewable and Sustainable Energy · 2025-09-01

  article
  PublisherDOI

• Simulations suggest offshore wind farms modify low-level jets

  Wind energy science · 2025-01-14 · 13 citations

  articleOpen accessCorresponding

  Abstract. Offshore wind farms are scheduled to be constructed along the East Coast of the US in the coming years. Low-level jets (LLJs) – layers of relatively fast winds at low altitudes – also occur frequently in this region. Because LLJs provide considerable wind resources, it is important to understand how LLJs might change with turbine construction. LLJs also influence moisture and pollution transport; thus, the effects of wind farms on LLJs could also affect the region’s meteorology. In the absence of observations or significant wind farm construction as yet, we compare 1 year of simulations from the Weather Research and Forecasting (WRF) model with and without wind farms incorporated, focusing on locations chosen by their proximity to future wind development areas. We develop and present an algorithm to detect LLJs at each hour of the year at each of these locations. We validate the algorithm to the extent possible by comparing LLJs identified by lidar, constrained to the lowest 200 m, to WRF simulations of these very low LLJs (vLLJs). In the NOW-WAKES simulation data set, we find offshore LLJs in this region occur about 25 % of the time, most frequently at night, in the spring and summer months, in stably stratified conditions, and when a southwesterly wind is blowing. LLJ wind speed maxima range from 10 m s−1 to over 40 m s−1. The altitude of maximum wind speed, or the jet “nose”, is typically 300 m above the surface, above the height of most profiling lidars, although several hours of vLLJs occur in each month in the data set. The diurnal cycle for vLLJs is less pronounced than for all LLJs. Wind farms erode LLJs, as LLJs occur less frequently (19 %–20 % of hours) in the wind farm simulations than in the no-wind-farm (NWF) simulation (25 % of hours). When LLJs do occur in the simulation with wind farms, their noses are higher than in the NWF simulation: the LLJ nose has a mean altitude near 300 m for the NWF jets, but that nose height moves higher in the presence of wind farms, to a mean altitude near 400 m. Rotor region (30–250 m) wind veer is reduced across almost all months of the year in the wind farm simulations, while rotor region wind shear is similar in both simulations.

  PublisherOA PDFDOI

Recent grants

• CAREER: BREEZE: Boundary-layer REsearch and Education ZonE

  NSF · $549k · 2016–2023

• CNH-Ex: Legal, Economic, and Natural Science Analyses of Wind Plant Impacts and Interactions

  NSF · $249k · 2014–2018

• Microfronts 1995 and Cases 1999: Boundary Layer Influences on Fronts and Inertial Oscillations

  NSF · $348k · 1999–2004

• Collaborative Research: Perdigao--The Stable Boundary Layer over Complex Terrain

  NSF · $359k · 2016–2023

Frequent coauthors

• Joseph B. Olson

  NOAA Earth System Research Laboratory

  192 shared

• Yelena L. Pichugina

  NOAA Chemical Sciences Laboratory

  187 shared

• Robert M. Banta

  NOAA Chemical Sciences Laboratory

  186 shared

• L. Bianco

  170 shared

• Aditya Choukulkar

  168 shared

• Jaymes S. Kenyon

  Cooperative Institute for Research in Environmental Sciences

  156 shared

• Irina V. Djalalova

  Cooperative Institute for Research in Environmental Sciences

  145 shared

• Katherine McCaffrey

  Joint Research Centre

  133 shared

Awards & honors

• Bloomberg Distinguished Professor of Atmospheric Science and…