Gust Speed Research Articles

The Effectiveness and Limitations of Fuel Modeling Using the Fire and Fuels Extension to the Forest Vegetation Simulator

Fuel treatment effectiveness is often evaluated with fire behavior modeling systems that use fuel models to generate fire behavior outputs. How surface fuels are assigned, either using one of the 53 stylized fuel models or developing custom fuel models, can affect predicted fire behavior. We collected surface and canopy fuels data before and 1, 2, 5, and 8 years after prescribed fire treatments across 10 National Forests in California. Two new methods of assigning fuel models within the Fire and Fuels Extension to the Forest Vegetation Simulator were evaluated. Field-based values for dead and downed fuel loading were used to create custom fuel models or to assign stylized fuel models. Fire was simulated with two wind scenarios (maximum 1-minute speed and maximum momentary gust speed) to assess the effect of the fuel model method on potential fire behavior. Surface flame lengths and fire type produced from custom fuel models followed the fluctuations and variability of fine fuel loading more closely than stylized fuel models. However, results of 7 out of 10 statistical tests comparing surface flame length between custom and stylized fuel models were not significant (P 0.05), suggesting that both methods used to assign surface fuel loads will predict fairly similar trends in fire behavior. FOR .S CI. ❚❚(❚):000-000.

Stabilization of Flapping-Wing Micro-Air Vehicles in Gust Environments

This study presents an approach to develop a controller for stabilization of a flapping-wing micro-air vehicle operating in gusty environments. The rigid-wing micro-air vehicle is modeled as a nonlinear periodic system and the periodic shooting method is used to find a trimmed periodic orbit. A linearized discrete-time representation of the system is created about this trimmed periodic orbit. This linearized representation is used for control synthesis based on linear quadratic regulator theory. The kinematic variables defining the wing motion are used as control inputs. The controller is implemented on the nonlinear system model to stabilize the system in the presence of external disturbances, modeled as discrete gusts in this study. The performance of the controller in terms of the gust speed tolerance of the nonlinear, closed-loop system is compared for different sets of controller parameters. The linear quadratic regulator based controller is capable of stabilizing the system under both longitudinal and lateral gust disturbances; however, the maximum gust speed that can be tolerated by a given controller is influenced by a variety of parameters, as discussed in the paper. Numerical simulations show that tolerance of longitudinal gusts is far higher than lateral gust tolerance. The study also shows that lateral control of the micro-air vehicle can be achieved using only the wing-stroke magnitude and wing-stroke offset as the control inputs for each wing.

Extreme Wind and Gust Speed at the Territorial Waters of Kuwait, Arabian Gulf

Kuwait is planning to install wind mills in its territorial waters in the Arabian Gulf. For optimal design of offshore wind mills and marine infrastructures, extreme wind and gust speed for different return periods, say 25 yr, 50 yr and 100 yr is an important input. Without such information, the design will be either very conservative and expensive or unsafe. A scientific estimate of the extreme wind and gust speed is hence obligatory. Recently Kuwait has approved a multi-billion dollar plan to develop Boubyan Island into a commercial seaport to serve as the main gateway for Kuwait, Iraq and the surrounding region. Kuwaiti government is also planning to develop Failaka Island as a tourist hub in this region. Knowledge of extreme wind and gust will be required for appropriate design of all marine infrastructures in these islands. The present work is carried out for nine marine locations in the territorial waters of Kuwait. Extreme 10 minute average wind and Gust speed from different directions and for different return periods were predicted for these nine locations. Measured wind speed by the climatological office of Directorate General of Civil Aviation is used for this analysis. The extreme wind speeds are predicted based on Gumbel distribution. Within these 9 locations, the 10 min. average 100 year wind speed in the marine area of Kuwait from different directions is in the range of 25.5 to 33.0 m/s. Without considering the effect of direction, it is in the range of 24.5 to 33.5 m/s. Similarly, the extreme gust speed for 100 year return period from different directions is in the range of 38.5 to 77.5 m/s. Without considering the effect of direction, it is in the range of 38.0 to 92.5 m/s.

Can dynamically downscaled windstorm footprints be improved by observations through a probabilistic approach?

AbstractWindstorms are a main feature of the European climate and exert strong socioeconomic impacts. Large effort has been made in developing and enhancing models to simulate the intensification of windstorms, resulting footprints, and associated impacts. Simulated wind or gust speeds usually differ from observations, as regional climate models have biases and cannot capture all local effects. An approach to adjust regional climate model (RCM) simulations of wind and wind gust toward observations is introduced. For this purpose, 100 windstorms are selected and observations of 173 (111) test sites of the German Weather Service are considered for wind (gust) speed. Theoretical Weibull distributions are fitted to observed and simulated wind and gust speeds, and the distribution parameters of the observations are interpolated onto the RCM computational grid. A probability mapping approach is applied to relate the distributions and to correct the modeled footprints. The results are not only achieved for single test sites but for an area‐wide regular grid. The approach is validated using root‐mean‐square errors on event and site basis, documenting that the method is generally able to adjust the RCM output toward observations. For gust speeds, an improvement on 88 of 100 events and at about 64% of the test sites is reached. For wind, 99 of 100 improved events and ~84% improved sites can be obtained. This gives confidence on the potential of the introduced approach for many applications, in particular those considering wind data.

Application of Hybrid Geo-Spatially Granular Fragility Curves to Improve Power Outage Predictions

Fragility curves depict the relationship between a weather variable (wind speed, gust speed, ice accumulation, precipitation rate) and the observed outages for a targeted infrastructure network. This paper describes an empirical study of the county by county distribution of power outages and one minute weather variables during Hurricane Irene with the objective of comparing 1) ‘as built’ fragility curves (statistical approach) to engineering ‘as designed’ (bottom up) fragility curves for skill in forecasting outages during future hurricanes; 2) county specific fragility curves to find examples of significant deviation from average behavior; and 3) the engineering practices of outlier counties to suggest future engineering studies of robustness. Outages in more than 90% of the impacted counties could be anticipated through an average or ‘generic’ fragility curve. The remaining counties could be identified and handled as exceptions through geographic data sets. The counties with increased or decreased robustness were characterized by terrain more or less susceptible to persistent flooding in areas where above ground poles located their foundations. Land use characteristics of the area served by the power distribution system can suggest trends in the “as built” power grid vulnerabilities to extreme weather events that would be subjects for site specific studies.

Santa Ana winds and predictors of wildfire progression in southern California.

Santa Ana winds have been implicated as a major driver of large wildfires in southern California. While numerous anecdotal reports exist, there is little quantitative analysis in peer-reviewed literature on how this weather phenomenon influences fire progression rates. We analysed fire progression within 158 fire events in southern California as a function of meteorologically defined Santa Ana conditions between 2001 and 2009. Our results show quantitatively that burned area per day is 3.5-4.5 times larger on Santa Ana days than on non-Santa Ana days. Santa Ana definition parameters (relative humidity, wind speed) along with other predictor variables (air temperature, fuel temperature, 10-h fuel moisture, population density, slope, fuel loading, previous-day burn perimeter) were tested individually and in combination for correlation with subsets of daily burned area. Relative humidity had the most consistently strong correlation with burned area per day. Gust and peak wind speed had a strong positive correlation with burned area per day particularly within subsets of burned area representing only the first day of a fire, >500 ha burned areas, and on Santa Ana days. The suite of variables comprising the best-fit generalised linear model for predicting burned area (R 2 = 0.41) included relative humidity, peak wind speed, previous-day burn perimeter and two binary indicators for first and last day of a fire event.

Explosive development of winter storm Xynthia over the subtropical North Atlantic Ocean

Abstract. In winter of 2009–2010 south-western Europe was hit by several destructive windstorms. The most important was Xynthia (26–28 February 2010), which caused 64 reported casualties and was classified as the 2nd most expensive natural hazard event for 2010 in terms of economic losses. In this work we assess the synoptic evolution, dynamical characteristics and the main impacts of storm Xynthia, whose genesis, development and path were very uncommon. Wind speed gusts observed at more than 500 stations across Europe are evaluated as well as the wind gust field obtained with a regional climate model simulation for the entire North Atlantic and European area. Storm Xynthia was first identified on 25 February around 30° N, 50° W over the subtropical North Atlantic Ocean. Its genesis occurred on a region characterized by warm and moist air under the influence of a strong upper level wave embedded in the westerlies. Xynthia followed an unusual SW–NE path towards Iberia, France and central Europe. The role of moist air masses on the explosive development of Xynthia is analysed by considering the evaporative sources. A lagrangian model is used to identify the moisture sources, sinks and moisture transport associated with the cyclone during its development phase. The main supply of moisture is located over an elongated region of the subtropical North Atlantic Ocean with anomalously high SST, confirming that the explosive development of storm Xynthia had a significant contribution from the subtropics.

The Study of Wind Turbine Based on Fuzzy Logic

Due to the lack of fossil fuels, people are paying more and more attention to renewable energy. Wind energy is one of the important renewable energy. Unpredictability and volatility of the wind source make the output power unstable, so we need to control the active Power. This paper uses fuzzy control method, and the simulation results show that fuzzy control method mentioned in this paper is better than the conventional PI control for Wind power, the nonlinear system. Based on the analysis of pitch control theory and control process, we design fuzzy pitch controller and its model. We simulates gust wind speed imitates, wind turbine control and verifies the effects of the blur pitch control in a constant speed and constant frequency wind power generation system. According to the results of the simulation, we know the pitch controller of fuzzy logic has a better effect on the active control of the generator of the wind power generation system.

Wind hazard assessment

Airport mean wind and gust speed data is used with past and future simulated data to estimate the maximum gust speed for a 500 year return period. It is demonstrated that the instantaneous speeds lead to the same result as data giving maximums over some time period. The airport mean wind speed was related to the gust speed, and the future simulations related to the past simulations. However, the relation between measured airport data and the simulations is poor. A Weibull distributions fitted to the upper part of the gust data is extrapolated to give the 500 year return period. An alternative approach using techniques similar to some actuarial analyses is also demonstrated.

Mangrove Microclimate: A Case Study from Southeastern Brazil

Abstract A mangrove is a transitional coastal ecosystem between marine and terrestrial environments that is characterized by salinity and constant tidal flooding. Mangroves contain plant communities that are adapted to several physical constraints, including the climate. The purpose of this study was to analyze the variations in climatic attributes (air temperature, relative air humidity, global solar radiation, wind, and rainfall) in the mangroves located in the municipality of Iguape, on the southern coast of the state of São Paulo, Brazil. In addition, it was determined whether the existing variation is related to the presence of the canopy environment. A microclimate tower was installed with two weather stations to obtain an analysis of the variation of the climatic attributes above and below the canopy. The results indicate that global solar radiation had an average transmissivity of 26.8%. The air temperature at 10 m was higher than that at the sensor at 2 m. The average rainfall interception for the mangrove environment was 19.6%. Both the maximum gust and average wind speed decreased by approximately 63.7% at 2 m. The mangrove canopy was found to be an important control on the variation of climatic attributes. On a microclimatic scale, the climate attributes had a direct influence on the spatial distribution of vegetation. Additionally, characteristics of the canopy are the main control for this variation, especially for the distribution of rainfall and the amount of solar radiation below the canopy, which influence the distribution of plant species in the environment.

1980–2010 Variability in U.K. Surface Wind Climate

Abstract The climate of the northeast Atlantic region comprises substantial decadal variability in storminess. It also exhibits strong inter- and intra-annual variability in extreme high and low wind speed episodes. Here the authors quantify and discuss causes of the variability seen in the U.K. wind climate over the recent period 1980–2010. Variations in U.K. hourly mean (HM) wind speeds, in daily maximum gust speeds and in associated wind direction measurements, made at standard 10-m height and recorded across a network of 40 stations, are considered. The Weibull distribution is shown to generally provide a good fit to the hourly wind data, albeit with the shape parameter k spatially varying from 1.4 to 2.1, highlighting that the commonly assumed k = 2 Rayleigh distribution is not universal. It is found that the 10th and 50th percentile HM wind speeds have declined significantly over this specific period, while still incorporating a peak in the early 1990s. The authors' analyses place the particularly “low wind” year of 2010 into longer-term context and their findings are compared with other recent international studies. Wind variability is also quantified and discussed in terms of variations in the exceedance of key wind speed thresholds of relevance to the insurance and wind energy industries. Associated interannual variability in energy density and potential wind power output of the order of ±20% around the mean is revealed. While 40% of network average winds are in the southwest quadrant, 51% of energy in the wind is associated with this sector. The findings are discussed in the context of current existing challenges to improve predictability in the Euro-Atlantic sector over all time scales.

Extreme wind gust hazard in Australia and its sensitivity to climate change

For consideration of structural design of buildings and infrastructure in Australia, this paper presents hazard modelling and mapping of extreme wind gusts under the current climate and likely future climate change. Statistical and probabilistic approaches are applied to analyse the daily extreme wind gust data recorded between 1939 and 2007 at 545 anemometer stations around Australia. The estimated hazards are compared with the regional design wind speeds specified by the structural design standard, AS/NZS 1170.2:2011. Our results indicate that, under the current climate, structures in the areas on the west of and around Brisbane, Queensland and Newcastle, New South Wales, may be under higher gust hazard than they are designed for. Sensitivity study shows that these areas are also sensitive to the projected synoptic wind intensity changes. When subjected to ±20 % intensity change and ±50 % occurrence frequency change of tropical cyclones, the northwest coast of Western Australia, the northern part of Northern Territory, and the northeast coast between Cairns and Townsville, Queensland, will experience around ±10 m/s changes in extreme wind gust speeds of 500-year return period.

Computationally inexpensive way to study windstorms on small scale

Windstorms are a major source of economic damage in Europe. To study their impacts on regional scales, scientists need large data sets of detailed, high‐resolution wind field data. However, high‐resolution regional simulations are computationally expensive. Haas and Pinto developed a statistical approach to downscale wind characteristics from large‐scale atmospheric models to obtain wind speed data on smaller scales. They use their method to derive windstorm‐related gust speeds on a small‐scale grid over Europe for a sample of windstorm events. The method is computationally inexpensive and reproduces observed windstorm events adequately, the authors report. The technique can be applied to ensembles of global climate models to project the potential future regional impacts of wind in a changing climate. (Geophysical Research Letters, doi:10.1029/2012GL054014, 2012)

A combined statistical and dynamical approach for downscaling large‐scale footprints of European windstorms

The occurrence of mid‐latitude windstorms is related to strong socio‐economic effects. For detailed and reliable regional impact studies, large datasets of high‐resolution wind fields are required. In this study, a statistical downscaling approach in combination with dynamical downscaling is introduced to derive storm related gust speeds on a high‐resolution grid over Europe. Multiple linear regression models are trained using reanalysis data and wind gusts from regional climate model simulations for a sample of 100 top ranking windstorm events. The method is computationally inexpensive and reproduces individual windstorm footprints adequately. Compared to observations, the results for Germany are at least as good as pure dynamical downscaling. This new tool can be easily applied to large ensembles of general circulation model simulations and thus contribute to a better understanding of the regional impact of windstorms based on decadal and climate change projections.

Microclimatic differences between young longleaf-pine silvopasture and open-pasture

Information is needed relative to changes that occur in microclimatic conditions in the early stages of open-pasture to pine silvopasture conversion in the Southeastern USA. This research tested the hypothesis that microclimatic conditions would vary between young-pine silvopasture and open-pasture. The research was conducted in a longleaf-pine (Pinus palustris Mill.)-bahiagrass (Paspalum notatum Flugge) silvopasture and adjacent open bahiagrass pasture at Americus, Georgia. Longleaf-pine was planted in the bahiagrass pasture in December 2000; the trees were not pruned or thinned until the study was completed. Microclimatic parameters (air temperature, soil temperature at 5 and 10 cm, wind speed, gust speed, wind direction, humidity, dew point, rainfall, soil-moisture content, total solar radiation, and photosynthetically active radiation) were collected from November 2005 to October 2008 using HOBO© weather stations located in each pasture type. Data were analyzed to determine overall, as well as seasonal, monthly, and diurnal differences between pasture types. Evapotranspiration was calculated from air temperature, wind speed, relative humidity, and total solar radiation. With the exception of rainfall, overall average values for all microclimatic parameters were different between pasture types. Silvopasture had higher overall average values for air temperature, soil temperature at both depths, and soil water content, but lower values for all remaining microclimatic parameters. Seasonal, monthly, and diurnal differences between pasture types were also detected for several parameters. The results suggested that water loss can be significantly reduced in the early stages of open-pasture to longleaf-pine silvopasture conversion in the Southeastern USA.

Downscaling future wind hazard for SE London using the UKCP09 regional climate model ensemble

Extreme weather events present a risk to urban communities, which under future cli- mate change may require greater resilience to reduce susceptibility to potential damage and loss of life. Improved resilience requires detailed information on both current and future levels of weather-related hazards; however, climate models do not provide output at a sufficiently high res- olution to provide usable information at the city scale. Furthermore, uncertainties in future climate projections need to be communicated in an appropriate manner to facilitate better local decision- making and adaptation. This paper addresses the problem of providing local-scale projections of hazards associated with high wind speeds over south-east London, along with quantified esti- mates of uncertainty. It describes a 2-step method for downscaling daily mean wind speed from a 25 km regional climate model (RCM) perturbed physics ensemble. This links climatological bias correction and engineering downscaling approaches to derive projections of maximum hourly mean wind speed and maximum 3 second gust speed at a resolution of 1 km. This employs tem- poral downscaling factors that have previously been used to estimate structural loading on new buildings but are here implemented at the city scale. The ensemble indicates that future changes in mean daily wind speed for the 2050s are not significantly different to those for a baseline period (1961�1990). Further, whilst the area is projected to experience an increase in exposure to events with the potential to cause damage to buildings, changes are small and considerable uncertainties remain in modelling such extremes.

Temporal, seasonal and weather effects on cycle volume: an ecological study

BackgroundCycling has the potential to provide health, environmental and economic benefits but the level of cycling is very low in New Zealand and many other countries. Adverse weather is often cited as a reason why people do not cycle. This study investigated temporal and seasonal variability in cycle volume and its association with weather in Auckland, New Zealand's largest city.MethodsTwo datasets were used: automated cycle count data collected on Tamaki Drive in Auckland by using ZELT Inductive Loop Eco-counters and weather data (gust speed, rain, temperature, sunshine duration) available online from the National Climate Database. Analyses were undertaken using data collected over one year (1 January to 31 December 2009). Normalised cycle volumes were used in correlation and regression analyses to accommodate differences by hour of the day and day of the week and holiday.ResultsIn 2009, 220,043 bicycles were recorded at the site. There were significant differences in mean hourly cycle volumes by hour of the day, day type and month of the year (p < 0.0001). All weather variables significantly influenced hourly and daily cycle volumes (p < 0.0001). The cycle volume increased by 3.2% (hourly) and 2.6% (daily) for 1°C increase in temperature but decreased by 10.6% (hourly) and 1.5% (daily) for 1 mm increase in rainfall and by 1.4% (hourly) and 0.9% (daily) for 1 km/h increase in gust speed. The volume was 26.2% higher in an hour with sunshine compared with no sunshine, and increased by 2.5% for one hour increase in sunshine each day.ConclusionsThere are temporal and seasonal variations in cycle volume in Auckland and weather significantly influences hour-to-hour and day-to-day variations in cycle volume. Our findings will help inform future cycling promotion activities in Auckland.

Probabilistic Wind Gust Forecasting Using Nonhomogeneous Gaussian Regression

Abstract A joint probabilistic forecasting framework is proposed for maximum wind speed, the probability of gust, and, conditional on gust being observed, the maximum gust speed in a setting where only the maximum wind speed forecast is available. The framework employs the nonhomogeneous Gaussian regression (NGR) statistical postprocessing method with appropriately truncated Gaussian predictive distributions. For wind speed, the distribution is truncated at zero, the location parameter is a linear function of the wind speed ensemble forecast, and the scale parameter is a linear function of the ensemble variance. The gust forecasts are derived from the wind speed forecast using a gust factor, and the predictive distribution for gust speed is truncated according to its definition. The framework is applied to 48-h-ahead forecasts of wind speed over the North American Pacific Northwest obtained from the University of Washington mesoscale ensemble. The resulting density forecasts for wind speed and gust speed are calibrated and sharp, and offer substantial improvement in predictive performance over the raw ensemble or climatological reference forecasts.

Peak factor estimation in hurricane surface winds

The peak factor is a critical parameter in estimating short duration peak gust speeds. An analysis of sixty-four 10m wind field records measured during the 1999–2008 Atlantic hurricane seasons shows a mildly positive non-Gaussian trend in the skewness of velocity with increasing longitudinal turbulence intensity (Iu). Kurtosis values exhibit slightly platykurtic behavior (kurtosis values less than 3) in open exposure but trend toward Gaussian as Iu increases. Average peak factors are computed from the data, stratified by wind speed and turbulence regime. Gust factor models are also examined; differences between the theoretical and observed zero up-crossing rates and power spectral density functions are used to discuss uncertainty propagation in the model. The results indicate that a non-Gaussian peak factor in theoretical peak gust (or gust factor) calculation appears to be warranted. Additional field measurements in built-up terrain are required to validate this finding.

Reply

AbstractA reexamination of the wind hazard from tropical cyclones for the city of Darwin (Northern Territory), Australia, by Cook and Nicholls concluded that its wind hazard is substantially underestimated by its allocation to region C in the Australian wind code. This conclusion was dismissed by Harper et al. on the basis of interpretation of anemometer records and Dvorak central pressure estimates as well as criticism of the simple technique and data used to interpret historic records. Of the 44 years of historical anemometer records presented by Harper et al. for Darwin, however, only one record was for a direct hit by an intense tropical cyclone. The other records derive from distant and/or weak tropical cyclones, which are not applicable to understanding the wind hazard at long return periods. The Dvorak central pressure estimates from which Harper et al. conclude that Port Hedland (Western Australia), Australia, has a greater wind hazard than Darwin does, when back transformed to Dvorak current-intensity values and gust speeds, indicate the converse. The simple technique used to derive wind hazard from historical cyclone occurrence is defended in detail and shown to produce estimates of wind hazard that are close to those accepted for five locations on the hurricane-affected coastline of the U.S. mainland. Thus the criticisms by Harper et al. of Cook and Nicholl’s work are shown to be invalid and the original conclusion that Darwin’s wind hazard is substantially underestimated in the current Australian wind code is supported.