Mean Wind Research Articles

Spatiotemporal Variation and Influencing Factors of Atmospheric Aerosol in the Middle Region of the Yarlung Zangbo River Basin from 2000 to 2020

Based on the aerosol optical depth （AOD） of the MODIS MCD19A2 dataset from 2000 to 2020, combined with meteorological data, land use/land cover data, and socio-economic data, the spatiotemporal distribution of AOD in the middle region of the Yarlung Zangbo River Basin was analyzed using STL and Theil-Sen Median trend estimation and the influence of natural and anthropogenic factors on AOD was revealed using GeoDetector, XGBoost model and SHAP analysis. The results showed that the spatial heterogeneity of AOD in the middle region of the Yarlung Zangbo River Basin was obvious, which was mainly controlled by topography, with high AOD value concentrated in the valley with the altitude lower than 4 300 m. Owing to the precipitation and surface wind speed, the seasonal difference of AOD was obvious, with the highest in winter. From 2000 to 2020, AOD in the middle region of the Yarlung Zangbo River Basin showed an increasing trend, with the annual average AOD rising from 0.008 to 0.012. This increase was especially strong in the valley area, where the AOD was significantly impacted by enhanced anthropogenic activities and the abundance of sand sources of exposed riverbed. Among the factors influencing AOD in the middle region of the Yarlung Zangbo River Basin, the changes in mean annual temperature, mean wind speed, population density, and GDP were positively correlated with the changes in AOD, whereas the changes in precipitation were negatively correlated. In particular, the increase in temperature was the factor that contributed predominantly （61.1%） to the recent changes in AOD.

Storage capacity estimates and site conditions of potential locations for offshore-wind powered carbon dioxide removal and carbon sequestration in ocean basalt

Negative emission technologies (NETs) are considered essential to keep global warming below 2 °C. Situating wind-powered carbon dioxide removal (CDR) devices offshore and injecting carbon dioxide (CO2) into deep-water sub-seafloor basalt aquifers has the potential to offer large CO2 removal capacity. It also avoids land and water-use competition and provides additional low-risk protections against post-injection leakage compared to terrestrial CO2 storage. This paper seeks to identify locations where offshore wind and potential basalt storage locations exist within close proximity to one another around the globe. A global mean wind power density map at 150 m height was computed using 30 years (1986–2016) of ERA5 hourly wind speed reanalysis data. Offshore regions with mean wind speed greater than 8 m/s were identified. Offshore regions with basalt aquifers along seismic or aseismic ridges which provide potential CO2 storage sites were identified and selected based on sediment thickness, age, and distance from plate boundaries. Four scenarios were constructed to capture a range of constraints with implications for technical, economic and regulatory difficulties. For each scenario, eligible regions for CO2 injection were filled by regularly spaced grid points and the distance to the nearest eligible wind resource was calculated for each point to identify the most promising configurations. Total available storage capacity within reach of wind resources was estimated to be between 4,300Gt and 196,000Gt depending on both uncertainties in porosity and other imposed constraints; even the most conservative estimates represent enormous capacity compared to global targets for negative emissions technologies. Typically, the best areas were found close to the poles due to the greater prevalence of good wind resources in those areas. Site-specific properties such as water depth and distance from shore are computed for the identified locations in order to characterize the conditions in which such locations are typically found.

Assessment of Wind Energy in the Ali Al-Gharbi Region

Assessment of wind resources is an important issue in the wind industry. This study aims to assess wind energy in southern Iraq, especially in the Ali Al-Gharbi region. It includes field data for the wind speed at two altitudes (30 and 50m) in 2017, using the Weibull Distribution, wind power density and wind energy density equations. The probability density distribution of mean wind speed and daily, monthly, and seasonal wind speeds were calculated. The monthly mean wind power density and wind energy density at heights (30 and 50m) were estimated. The suitable wind turbine in this study area was the Unison U50. The capacity factor was assessed. The results showed a northwesterly prevailing wind speed direction in the study area. Mean wind speed increases during day hours and decreases during night hours throughout the four seasons. The highest monthly mean wind speed is in May and June. The highest seasonal mean wind speed is in spring and summer, while the lowest is in winter and autumn. The highest monthly mean of wind power density and wind energy density were in June, while the lowest values were in February. The highest monthly values of wind power, wind energy, and capacity factor were (5851.11kW, 4212802.15kW.h, 78%) respectively, while the lowest monthly values were (1080.43kW, 777913.34kW.h, 14%), respectively.

Understanding the impact of data gaps on long-term offshore wind resource estimates

Abstract. In the context of a wind farm project, the wind resource is assessed to predict the power output and the optimal positioning of wind turbines. This requires taking wind measurements on the site of interest and extrapolating these to the long term using so-called “measure, correlate, and predict” (MCP) methods. Sensor, power supply, and software failures are common phenomena. These disruptions cause gaps in the measured data, which can especially be long in offshore measurement campaigns due to harsh weather conditions causing system failures and preventing servicing and redeployment. The present study investigates the effect of measurement data gaps on long-term offshore wind estimates by analyzing the bias they introduce in the parameters commonly used for wind resource assessment. Furthermore, it aims to show how filling the gaps can mitigate their effect. To achieve this, we perform investigations for three offshore sites in Europe with 2 years of concurrent measurements. We use reanalysis data and various MCP methods to fill gaps in the measured data and extrapolate these data to the long term. Current standards demand high data availability (80 % or 90 %) for wind measurement campaigns, so we expect that the effect of missing data on the uncertainty in long-term extrapolations is of the same order of magnitude as other uncertainty components such as the measurement uncertainty or the inter-annual variability. Nevertheless, our results show that the effects of gaps are considerably smaller than the other uncertainty components. For instance, gaps of 180 d cause an average deviation of the long-term mean wind speed of less than 0.04 m s−1 and a 95th percentile deviation of less than 0.075 m s−1 for all tested sites. Due to the low impact of gaps, gap filling does not have the potential to significantly reduce the uncertainty in the long-term extrapolation.

Evolution of the subtropical surface wind in the north-east Atlantic under climate change

The climate of western Europe and northwest Africa strongly depends on the Azores anticyclone strength, location, and shape and, locally, also on the characteristics of the Iberia and Sahara summer thermal lows. EC-EARTH3 global simulations are here used to assess the predicted behaviour of these two relevant surface pressure systems and associated surface wind, by the end of XXI century (2071–2100), considering two climate change scenarios. Additionally, a high-resolution Weather Research and Forecasting (WRF) simulation centred on Madeira Island is used to assess the influence of climate change on the surface wind at smaller scales, in a region well known for its perturbed flows. Results indicate a general mean wind speed decrease over a sector of the North-Atlantic, associated with a flatter Azores anticyclone. However, the predicted intensification of the Iberia and Sahara thermal lows imposes an increasing surface wind speed near west Iberia and northwest Africa, in summer. Southwest of Iberia, Madeira Island is also predicted to experience a summer intensification of its tip-jets. The projected changes in low-level wind speed and variability will impact on different sectors of activity, either directly as are the cases of aeronautical operation and offshore renewable energy, or indirectly through changes in the ocean circulation.

Buffeting induced fatigue damage assessment of long-span bridge decks under uncertain turbulence conditions

Fatigue in wind-sensitive structures is influenced by the mean wind speed and the turbulence characteristics. This study investigates the importance of uncertainty in the turbulence characteristics of buffeting-induced fatigue damage of flexible wind-sensitive structures, focusing on long-span bridges. We address the importance of the variability of uncertainty in the wind field by using a probabilistic wind field model, including uncertain turbulence parameters for calculating the accumulated fatigue damage throughout the structure’s design life. However, it has been demonstrated that a high computational load accompanies this approach. A new method is proposed that significantly reduces the computational effort through surrogate modelling. This is achieved through a sequentially updating Gaussian Process surrogate modelling approach, which integrates new simulation points into the training dataset and reduces the number of buffeting calculations required for the surrogate to converge to the true solution, thereby reducing the computational cost by almost 95%. The efficiency of the algorithm is demonstrated by using it to compute the fatigue damage accumulation through the design life for a long-span bridge girder, resulting in the increase of damage by several orders of magnitude in comparison to the conventional method of treating the turbulence parameters as deterministic and uncorrelated.

A multi-site passive approach to studying the emissions and evolution of smoke from prescribed fires

Abstract. We conducted a 2-year study utilizing a network of fixed sites with sampling throughout an extended prescribed burning period to characterize the emissions and evolution of smoke from silvicultural prescribed burning at a military base in the southeastern USA. The measurement approach and an assessment of the instrument performance are described. Smoke sources, including those within and off the base, are identified, and plume ages are determined to quantify emissions and study the evolution of smoke PM2.5 (particulate matter with aerodynamic diameters 2.5 µm or smaller) mass, black carbon (BC), and brown carbon (BrC). Over the 2021 and 2022 prescribed burning seasons (nominally January to May), we identified 64 smoke events based on high levels of PM2.5 mass, BC, BrC, and carbon monoxide (CO), of which 61 were linked to a specific burning area. Smoke transport times were estimated in two ways: using the mean wind speed and the distance between the fire and the measurement site, and from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) back-trajectories. PM2.5 emission ratios based on ΔPM2.5 mass / ΔCO for fresh smoke (age ≤ 1 h) ranged between 0.04 and 0.18 µg m−3 ppb−1 with a mean of 0.117 µg m−3 ppb−1 (median of 0.121 µg m−3 ppb−1). Both the mean emission ratio and the variability were similar to findings from other prescribed fire studies but were lower than those from wildfires. The mean emission ratios of BC and BrC were 0.014 µg m−3 ppb−1 and 0.442 Mm−1 ppb−1, respectively. Ozone enhancements (ΔO3) were always observed in plumes detected in the afternoon. ΔPM2.5 mass / ΔCO was observed to increase with plume age in all of the ozone-enhanced plumes, suggesting photochemical secondary aerosol formation. In contrast, ΔBrC/ΔCO was not found to vary with plume ages less than 8 h during photochemically active periods.

Reconstruction of unstable atmospheric surface layer streamwise turbulence based on multi-layer perceptron neural network architecture

The accurate simulation of sand-laden turbulence under different stratification stabilities remains a critical challenge in turbulence research. This study presents an innovative approach to reconstructing streamwise turbulence in an unstable atmospheric surface layer (ASL) using a multi-layer perceptron (MLP) neural network architecture. Leveraging high-resolution measurements of three-dimensional wind velocity and temperature from multiple observational sites, the study develops prediction models for streamwise wind velocity at varying heights in the unstable ASL. The predictive model integrates large-scale motions (LSMs) generated by the MLP, small-scale motions (SSMs) derived from the Kaimal spectrum, and mean wind velocity, providing a comprehensive representation of turbulence. The impact of sand content and stratification stability on model performance is analyzed, with discussion highlighting the model's strengths and limitations under weak instability conditions. Validation is conducted through cross-site comparison, statistical analysis, and power spectrum assessment, demonstrating the model's ability to capture the temporal and spectral characteristics of wind velocity in sand-laden, unstable ASL conditions. The study also reveals that, under weak instability, shear forces dominate the formation of coherent structures, while buoyancy effects enhance vertical mixing as instability increases. Compared to existing models, the proposed prediction model is applicable over a broader range of conditions, offering a valuable data source for the study of atmospheric sand-laden turbulence and serving as a reference for practical sand control projects.

Stronger Westerly Wind Bursts in a Warming Climate: The Effects of the Pacific Warming Pattern, the Madden–Julian Oscillation, and Tropical Cyclones

Abstract Westerly wind bursts (WWBs) in the western–central equatorial Pacific are critical in El Niño–Southern Oscillation (ENSO) dynamics. Understanding how they may change with global warming has important implications for future projections of El Niño. In this study, we investigate how the enhanced eastern equatorial Pacific warming pattern, emerging in future climate projections, can influence WWB characteristics in an atmospheric general circulation model, CAM6. Changes in three main factors affecting WWBs—El Niño-conditions mean westerly wind stress anomalies, the Madden–Julian oscillation (MJO), and tropical cyclones (TCs)—are analyzed. We find that during El Niño onset (December–April), the WWB wind stress intensity remains largely unchanged but WWBs shift westward by about 20° of longitude. In contrast, during El Niño development (May–November), the WWB intensity increases by 41% or 79% in two warming scenarios considered [shared socioeconomic pathways (SSP5-8.5) and SSP2-4.5, respectively], which is mainly caused by a higher frequency of TC occurrence in the central tropical Pacific within 15°N/S. Further, we find that westerly wind speed anomalies associated with El Niño and the MJO also increase during El Niño development. However, as trade winds weaken in the central-eastern equatorial Pacific, the mean strength of the resulting westerly wind stress anomalies does not change much, and no significant eastward shift of WWBs is observed. Thus, our atmospheric model simulations suggest a strong TC-driven increase in WWB wind stress anomalies during El Niño development and hence a more important role of TCs in WWB generation, which in a coupled system could lead to stronger ENSO events, enhanced TC–ENSO coupling, and even greater intensification of WWBs.

A straightforward method for estimating evolutionary power spectral density of non-stationary typhoon wind speed

PurposeA precise estimation of the evolutionary power spectral density (EPSD) of typhoon wind speed is a difficult and significant undertaking in the analysis of turbulence effects on large-expansive structures. A majority of the prevailing EPSD estimation techniques rely on complex signal processing methodologies, such as wavelet decomposition, Hilbert–Huang transformation and time-varying autoregressive moving average (ARMA) model. However, these approaches often pose challenges in terms of comprehensibility and practical implementation for engineers. In light of this issue, the present study introduces a straightforward and effective EPSD estimation method tailored specifically for typhoon wind speed, aiming to facilitate its understanding and application in engineering contexts.Design/methodology/approachFirstly, the mathematical model of a uniformly modulated non-stationary process is employed to represent the typhoon wind speed. Secondly, the reverse arrangement test serves as an auxiliary tool in conjunction with wavelet transform or empirical mode decomposition, aiding in the determination of the optimal slowly varying mean wind speed. Thirdly, Kernel regression technique is utilized to discern the time-dependent standard deviation of wind speed fluctuations. Finally, the power spectral density (PSD) of wind speed residuals is computed to facilitate the estimation of the EPSD.FindingsFirstly, the reverse arrangement test-assisted approach enables the determination of an optimal time-dependent mean from the candidate results obtained through discrete wavelet transform (DWT) and empirical mode decomposition (EMD). Secondly, the application of the Kernel regression technique facilitates accurate identification of the time-dependent variance from the fluctuating wind speed data. Thirdly, due to the influence of the extreme weather, the Gaussianity of the reduced turbulent fluctuations in typhoon wind is easily disturbed, resulting in the obvious non-Gaussian features.Originality/valueThis paper employs the mathematical model of uniformly modulated non-stationary process to characterize typhoon wind speeds and then proposes a straightforward and efficient method for estimating the EPSD of typhoon wind. The accuracy and efficacy of the presented estimation method are verified using the field-measured wind speed data from Typhoon Rammasun. The proposed EPSD estimation method for typhoon wind exhibits suitability for engineering applications owing to its simplicity and computational efficiency.

Wingsail performance in unsteady atmospheric surface layer winds

The performance of wind propulsion systems is evaluated in unsteady inhomogeneous winds with tools that are routinely used to predict the performance of wind turbines and which give access to the unsteady aerodynamic forces acting on the wingsail. A rigid wingsail exposed to a realistic atmospheric surface layer wind is used as a testbed. For this case, we show that standard deviations of the aerodynamic driving force are larger than 15%–20% of the mean values when the true wind velocity is larger than the ship speed. We also show that the mean aerodynamic driving forces computed by averaging the unsteady driving forces are only slightly smaller than the ones computed on the mean wind despite the strongly nonlinear dependence of the unsteady forces on the wind velocity and direction.

PIV study on characteristics of pedestrian-level fluctuating wind speeds around square buildings with different heights

Flow fields around four square-section buildings with different heights in boundary layer flow (BLF) were captured by PIV tests to investigate the influence of an increase in building height on fluctuating wind speed fields and pedestrian-level peak wind speed around buildings. Flow visualization results indicate that upstream stagnation levels significantly increase with increasing building height, along with higher wind speeds in approaching BLF, causing stronger front downwash flows and upwash flows behind higher buildings. Variation in flow structures with building height significantly change pedestrian-level wind speed fields, including (1) causing a significant increase in mean wind speed on the sides of buildings, although their influence on turbulent kinetic energies (TKE) in the region is not obvious; (2) causing an increase in mean wind speeds and especially TKE downstream of buildings; Accordingly, high peak pedestrian-level winds for higher buildings occur not only in windy regions beside buildings but also in generally considered low-speed wake regions. This suggests that measurement of only mean pedestrian-level wind around buildings, especially super high-rise buildings, may not be adequate and might underestimate the influence of pedestrian-level winds on pedestrians. In addition, by zoning according to different fluctuating wind characteristics around buildings, peak pedestrian-level wind speed can be estimated by gust factor with better accuracy. Meanwhile, the influence of building height can be easily reflected by constant coefficients.

Wind-wave characteristics in the coastal area between Damietta and Port Said, Egypt

This study attempts to investigate the wind-wave characteristics in the region between Damietta and Port Said from 2011 to 2020 using the ERA5 data set for the considered area. Fourteen stations were used for data collection to represent the study area. The ERA5 data were compared with measured wave data from a directional wave buoy from February 1999 to February 2000. The following error statistics were obtained: bias = - 0.014 m and RMSE = 0.3 m. The ERA5 data were then used to create seasonal maps to simulate wind speed and direction, significant wave height (Hs), wave direction, and wave period. Results showed that the annual average Hs was 0.42 m, and the annual mean wind speed was 5.13 m/s. According to the Mann-Kendall test, the average Hs exhibited increasing trends of 0.0014 m/year and 0.0024 m/year with 70–80 % significance levels, respectively, in winter and autumn. In the spring, the Hs trend was 0.0013 m/year with an 80–90 % significance. During summer, this trend decreased to −0.00037 m/year, with a 70–80 % significance level. The average wind speed had increasing trends in winter, spring, and autumn of 0.009 m/s/year and 0.016 m/s/year with a 70–80 % level of significance and 0.0026 m/s/year with 80–90 % significance level, respectively. Meanwhile, the summer average wind speed showed a weak, insignificant trend of increase of as low as 0.0001 m/s/year. The study recommends using simulated wave characteristics to fill the gap in wave data along the Southeastern Mediterranean coast and using the southeast zone of the study area for economic activities.

Flow observations using nacelle lidars: A study on the University of Stavanger campus

Abstract This study deals with wind measurements on the campus of the University of Stavanger, using two continuous-wave nacelle lidars and a vertical continuous-wave profiler. Wind data is further acquired by 2-D sonic anemometers fixed to the lidars. The emphasis of the analysis is on the data gathered by the nacelle lidars. The horizontal wind speeds reconstructed from the radial velocities are compared to the recordings of the sonic anemometers and analysed in terms of mean wind profiles over the extent of the scanning circle. Standard logarithmic and power laws are fitted to the profiles to estimate site-specific parameters such as wind shear exponent and surface roughness. Turbulence characteristics in the mean wind direction, such as spectra and variances, are estimated and compared to those from the sonic anemometer. The study demonstrates the overall potential of remote sensing for wind monitoring in an urban environment. The wind velocities acquired in the individual measurement points along the nacelle lidars’ scanning circles are found to capture the flow in the monitored regions around the buildings in a realistic way. Together with the information from the vertically pointing wind profiler, the measurement data represents a valuable source for validation of related numerical models for flow in an urban area.

Accuracy assessment of offshore wind measurements partially compensated by MCP method considering data availability

Abstract In Japan, most offshore promotion areas for bottom-fixed wind turbines are in near-shore areas, where offshore wind speeds are not uniform. The dual-scanning LiDAR system (DSL), which is a remote-sensing technology, is widely used to measure the mean wind speed, wind direction, and turbulence for resource and site assessments. However, the availability of DSL data tends to be lower than the key performance indicators proposed in the Carbon Trust in Offshore Wind Accelerator project owing to the characteristics of DSL. Missing observed data can be predicted using the measure–correlate–predict (MCP) method, and the uncertainty of the MCP method can be examined using a prediction function. However, a method to evaluate the accuracy of the final dataset comprising observed data and data predicted by the MCP method is yet to be devised. In this study, a set of formulas is proposed to evaluate the accuracy of indices, such as the coefficient of determination, slope, and offset of linear regression, for a partially complemented dataset using the MCP method. The proposed formulas are validated against on-site measurements.

Assessment of offshore wind conditions in coastal areas of Japan using single scanning Doppler LiDAR

Abstract In this study, offshore wind conditions in coastal areas of Japan measured by single scanning Doppler lidar is investigated. The effects of measurement range as well as rainfall and snowfall on data availability of the Doppler scanning lidar are examined. Data filtering criteria are then proposed and verified by data thinning to meet both accuracy and post-processed data availability requirements for offshore wind measurements at multiple altitudes. Finally, one-year offshore wind measurement with three different elevation angles is conducted using a single Doppler scanning lidar to investigate wind conditions in the coastal region of Northern Japan. It is found that the accuracy of 15-second average wind speed measurements by PPI (Plan Position Indicator) scan depends on the sector size. An accurate 10-minute mean wind is measured when the sector size is larger than 39 degrees and proportion of valid data acquisition is more than 10% of the time duration. The vertical and horizontal distributions of offshore wind speed in different wind directions are also analyzed and the effects of onshore topography on offshore wind conditions are clarified.

Collocating wind data: A case study on the verification of the CERRA dataset

Abstract Wind resource assessment often relies on reanalysis data or meso-scale models due to the challenges and costs associated with on-site measurement campaigns, especially in offshore locations. While these datasets offer extensive spatial coverage, they often provide the desired parameters on a coarse grid only. The spatial averaging over the grid and the low frequency of the outputs hinders the model’s ability to capture the short-term wind speed variability and events with a time scale of a few minutes to a few dozen of minutes. In this paper we investigate the temporal scales of the wind events resolved by the Copernicus European Regional Re-Analysis (CERRA) dataset, ERA5, and an in-house regional down-scaling of ERA5 using the WRF model by comparing them against measurements. We propose a method to collocate the two sources of wind data (measured and modeled), focusing on the verification of CERRA with respect to first and second-order statistics in the North Sea. The results highlight the superiority of CERRA compared to ERA5 in estimating the wind speed distribution, improving the 95th percentile error from -0.85 to -0.19 ms−1 and the average bias from -0.286 to -0.004 m s−1 across all locations. The wind speed change over one hour is underestimated by both CERRA and ERA5 when collocated with 10-minute measurements at the full hour. However, hourly averaged measurements align well with CERRA’s wind speed variation predictions, while an averaging window of 3.5 hours is needed to align with ERA5’s hourly wind speed changes. The results showed that the synthetic wind speeds exhibit optimal correlation with the measurements when the measurements are averaged over 4.5 to 7 hours, depending on the modeled dataset. This time scale corresponds to a length scale of 160-250 km, assuming a mean wind speed of 10 m s−1, which falls within the meso-scale range. The study contributes to the understanding of model validation in offshore wind energy studies, with the potential to enhance wind resource assessment calculations and improve the results of long-term extrapolations.

Fatigue Damage and Reliability Assessment of Wind Turbine Structure During Service Utilizing Real-Time Monitoring Data

Under the action of wind load, a wind turbine tower will produce alternating stress, which leads to fatigue failure. According to the mean wind speed at the wind turbine impeller collected from the SCADA system, the mean wind speed of the simulation point is calculated by using the wind speed exponential model formula. Davenport spectra are used to simulate the pulsating wind speed time series. The wind spectrum is obtained using the harmonic superposition method. Subsequently, the wind speed time series and wind load time series at the simulation point are calculated. Structural modeling of a 5 MW wind turbine tower is performed in ABAQUS 2021. The modal shape and natural frequency are obtained by modal analysis to verify the rationality of the model. Subsequently, wind loads are applied to the model, and structural stress time history is obtained by transient modal dynamics analysis. The stress time history of the maximum stress area of the tower structure is extracted, and the rain flow counting method is applied to it to obtain the stress spectrum. The Weibull distribution of the stress spectrum is fitted, the mean and variance of the total damage in one day are calculated, and the fatigue reliability analysis of the maximum stress area of the tower structure is carried out. And the nonlinear fatigue cumulative damage analysis of the region is carried out. This work has implications for fatigue reliability studies for approximate operating conditions.

Converging profile relationships for offshore wind speed and turbulence intensity

Abstract. This paper reduces uncertainty in the quantification of offshore wind speed and turbulence intensity. A range of industry standard relationships, including those from International Electrotechnical Commission (IEC) and International Organization for Standardization (ISO), are compared with an extensive set of met mast data collected offshore northwestern Europe over recent decades. Analysis initially focused on over 1000 independent storm peak events identified within the 10 min mean wind speed data. Time series and coherent vertical profiles were subjected to detailed scrutiny and analysis, considering wind speeds at various averaging periods, turbulence intensity and gust factors. Most peak events were associated with neutral atmospheric conditions, so they were well represented by the ISO Frøya profile, with a shear close to the IEC power law exponent of α= 0.11. A new pragmatic approximation of atmospheric stability in terms of relative shear is outlined, bringing together key elements of the IEC and ISO standards. New empirical relationships to quantify offshore wind ambient turbulence intensity are described. A simple generalised form of gust factor relationship is adopted, with a coefficient that varies with averaging period. Distinct recommendations are made for estimating peak 10 min mean winds from peaks in 1 or 3 h mean winds. Finally, a simplified workflow for the estimation of extreme offshore winds is used to show how IEC and ISO relationships can be effectively combined.

Novel Technique to Close Stellate Corneal Lacerations.

The study was performed to evaluate and optimize a novel technique to close stellate corneal lacerations in a wet laboratory environment. Twenty-one ex vivo porcine eyes with standardized, experimentally created stellate corneal lacerations were assigned to one of three surgical repair techniques. In Group 1 (n = 9), lacerations were closed with simple interrupted sutures only. In Group 2 (n = 7), a large-radius central purse string was used in addition to simple interrupted sutures. In Group 3 (n = 5), a small-radius central purse string was used in addition to simple interrupted sutures. Wound stability was assessed by determining the intraocular pressure (IOP) at which wound leak occurred. Group 3 eyes demonstrated a mean wound leak IOP of 56.1 mm Hg (range 32-90.3) compared with groups 1 and 2, which demonstrated mean wound leak IOPs of 6.4 mm Hg (range 1.9-19) and 13.3 mm Hg (range 2.8-31), respectively. These differences were highly statistically significant (P<0.002 and P<0.015, respectively, compared with Group 3). The use of a small-radius internal purse-string suture, when combined with simple interrupted sutures, produced a highly effective watertight closure in experimentally created stellate corneal lacerations, significantly outperforming approaches using only interrupted sutures or a large-radius purse string. The use of a small-radius purse-string suture should be considered for clinical use in the repair of stellate corneal lacerations.