Characteristics of daily extreme wind gusts on the Qinghai-Tibet Plateau, China

Severe wind is a major natural hazard and a main driver of deserdficadon on the Qinghai-Tibet Plateau. Generally, studies of Qinghai-Tibet Plateau＇s wind climatology focus on mean wind speeds and its gust speeds have been seldom investigated. Here, we used observed daily maximum gust speeds from a 95- station network over a 5-year period （2008-2012） to analyze the characteristics of extreme wind speeds and directions by fitting Weibull and Gumbel distributions. The results indicated the spatial distribution of extreme wind speeds and their direction on the Qinghai-Tibet Plateau is highly variable, with its western portion prone to greater mean speeds of extreme wind gusts than its eastern portion. Maximum extreme wind speeds of 30.9, 33.0, and 32.2 m/s were recorded at three stations along the Qinghai Tibet Railway. Severe winds occurred mostly from November to April, caused primarily by the westerly jet stream. Terrain greatly enhances the wind speeds. Our spatial analysis of wind speed data showed that the wind speeds increased exponentially with an increasing altitude. We also assessed the local wind hazard by calculating the return periods of maximum wind gusts from the observational data based on the statistical extreme value distributions of these wind speeds. Further attention should be given to those stations where the yearly maximum daily extreme wind speed increased at a rate greater than that of mean value of daily extreme wind speeds. Severe extreme wind events in these regions of the plateau are likely to become more frequent. Consequently, building structural designers working in these areas should use updated extreme wind data rather than relying on past data alone.

Estimation of extreme wind speed in SCS and NWP by a non-stationary model

In offshore engineering design, it is considerably significant to have an adequately accurate estimation of marine environmental parameters, in particular, the extreme wind speed of tropical cyclone （TC） with different return periods to guarantee the safety in projected operating life period. Based on the 71-year （1945-2015） TC data in the Northwest Pacific （NWP） by the Joint Typhoon Warning Center （JTWC） of US, a notable growth of the TC intensity is observed in the context of climate change. The fact implies that the traditional stationary model might be incapable of predicting parameters in the extreme events. Therefore, a non-stationary model is proposed in this study to estimate extreme wind speed in the South China Sea （SCS） and NWP. We find that the extreme wind speeds of different return periods exhibit an evident enhancement trend, for instance, the extreme wind speeds with different return periods by non- stationary model are 4.1%-4.4% higher than stationary ones in SCS. Also, the spatial distribution of extreme wind speed in NWP has been examined with the same methodology by dividing the west sea areas of the NWP 0°-45°N, 105°E-130°E into 45 subareas of 5° × 5°, where oil and gas resources are abundant. Similarly, remarkable spacial in-homogeneity in the extreme wind speed is seen in this area： the extreme wind speed with 50-year return period in the subarea （15°N-20°N, 115°E-120°E） of Zhongsha and Dongsha Islands is 73.8 m/s, while that in the subarea of Yellow Sea （30°N-35°N, 120°E-125°E） is only 47.1 m/s. As a result, the present study demonstrates that non-stationary and in-homogeneous effects should be taken into consideration in the estimation of extreme wind speed.

Extreme Wind Characteristics of Coastal Communities in Bayelsa State: Implications for Community Planning and Development in Nigeria

The study examined extreme wind characteristics of the coastal communities in Bayelsa State, Nigeria for possible community planning and development. To achieve this aim, data on wind speed were sourced from the Nigerian Meteorological Agency (NIMET). Personal interview and focused group discussions were done with the aid of well structured questionnaire in the various coastal communities sampled to identify impact and coping strategies from extreme winds. The Beaufort Winds Scale and regression analysis were the statistical tools used for the analysis of the data in order to achieve the objectives of the study. The results indicate that, the return period to obtain maximum 1-year wind speed value of 29.3 m/s (violent storm), 27.8 m/s (storm), 24.3 m/s (strong Gale) and 20.6 m/s (fresh Gale) will be 17 years, 5.7 years, 2.8 years and 1.4 years respectively. Fresh Gale characterized the extreme wind events in the area. Result further showed that out of 19 occurrences of wind events, 11 were extreme cases, while 2 occurred as violent storm of 29.3 m/s. Findings also showed that extreme winds occurred more (8 cases) during the early part (March-April) of the raining season when the area is under the influence of maritime moisture laden air mass than the dry season which is dried and dusty. Using a combination of return period of the magnitude of extreme wind and the log of wind speed for the 16 years a model predicting the incidence of extreme wind was done. Awareness on the dangers of wind hazard increases while early warning systems are advocated to mitigate the associated dangers with extreme wind events in the study area.

An Extreme Value Analysis of Wind Speed over the European and Siberian Parts of Arctic Region

Multiyear observed time series of wind speed for selected points of the Arctic region (data of station network from the Kola Peninsula to the Chukotka Peninsula) are used to highlight the important peculiarities of wind speed extreme statistics. How largest extremes could be simulated by climate model (the INM-CM4 model data from the Historical experiment of the CMIP5) is also discussed. Extreme value analysis yielded that a volume of observed samples of wind speeds are strictly divided into two sets of variables. Statistical properties of one population are sharply different from another. Because the common statistical conditions are the sign of identity of extreme events we therefore hypothesize that two groups of extreme wind events adhere to different circulation processes. A very important message is that the procedure of selection can be realized easily based on analysis of the cumulative distribution function. The authors estimate the properties of the modelled extremes and conclude that they consist of only the samples, adhering to one group. This evidence provides a clue that atmospheric model with a coarse spatial resolution does not simulate special mechanism responsible for appearance of largest wind speed extremes. Therefore, the tasks where extreme wind is needed cannot be explicitly solved using the output of climate model. The finding that global models are unable to capture the wind extremes is already well known, but information that they are members of group with the specific statistical conditions provides new knowledge. Generally, the implemented analytical approach allows us to detect that the extreme wind speed events adhere to different statistical models. Events located above the threshold value are much more pronounced than representatives of another group (located below the threshold value) predicted by the extrapolation of law distributions in their tail. The same situation is found in different areas of science where the data referring to the same nomenclature are adhering to different statistical models. This result motivates our interest on our ability to detect, analyze, and understand such different extremes.

Prediction of extreme wind velocity at the site of the Runyang Suspension Bridge

This paper presents a distribution free method for predicting the extreme wind velocity from wind monitoring data at the site of the Runyang Suspension Bridge (RSB), China using the maximum entropy theory. The maximum entropy theory is a rational approach for choosing the most unbiased probability distribution from a small sample, which is consistent with available data and contains a minimum of spurious information. In this paper, the theory is used for estimating a joint probability density function considering the combined action of wind speed and direction based on statistical analysis of wind monitoring data at the site of the RSB. The joint probability distribution model is further used to estimate the extreme wind velocity at the deck level of the RSB. The results of the analysis reveal that the probability density function of the maximum entropy method achieves a result that fits well with the monitoring data. Hypothesis testing shows that the distributions of the wind velocity data collected during the past three years do not obey the Gumbel distribution. Finally, our comparison shows that the wind predictions of the maximum entropy method are higher than that of the Gumbel distribution, but much lower than the design wind speed.

Rising future tropical cyclone-induced extreme winds in the Mekong River Basin

热带气旋引起的极端风速对社会的影响使得它成为湄公河流域的最大隐患之一.西北太平洋是影响湄公河流域热带气旋的重要源地之一.从20世纪70年代开始,在越南沿岸登陆的热带气旋强度没有呈现明显的变化趋势.然而,气候模式模拟预测显示西北太平洋的热带气旋强度将会在21世纪内增强,届时将很可能影响到湄公河流域.目前为止,未来湄公河流域的热带气旋活动引起的极端风速将会如何变化尚不明确.因此,本文采用了1个基于海洋大气耦合模型的降尺度技术和5个全球气候模式的输出结果对未来湄公河流域的热带气旋活动进行了模拟.结果显示,相比于1981~2000年,在RCP8.5的情境下,2081~2100年湄公河流域热带气旋的最大风速的重现期将显著缩短.这意味着该区域的热带气旋强度将明显增强.此结果预示着未来热带气旋活动将增加相关灾害的发生,并且这可能会在地区乃至全球范围威胁可持续发展、影响粮食供应和加剧冲突.

Extreme Value Estimation of Beaufort Sea Ice Dynamics Driven by Global Wind Effects

The purpose of the present study is to investigate the extreme values of the ice drift speed,which are also considered in the light of the magnitude of the simultaneous wind speed.The relationship between wind speed and ice drift speed is studied.The long-term ice drift data is collected by using local subsurface measurements based on acoustic Doppler current profilers(ADCP)in the Beaufort Sea during the period of 2006-2017.Upward-looking sonars(ULS)are deployed in order to observe the ice thickness as well as to identify events that correspond to open water conditions.The relationship between the ice drift speed and the wind speed is also investigated.It is found that the magnitude of the average ice drift speed is approximately 2.5%of the wind speed during the winter season.Estimation of the extreme values of the ice drift speed is studied by application of the average conditional exceedance rate(ACER)method.It is found that the extreme ice drift speed during the ice melt season(i.e.the summer season)is approximately20%-30%higher than that during the ice growth season(i.e.the winter season).The extreme ice drift speed can be effectively estimated based on the 2.5%wind speed.Moreover,the extreme ice drift speed can be obtained based on the extreme values of 2.5%of the wind speed based on multiplying with an amplification factor which varies in the range from 1.7 to 2.0 during the growth season,corresponding to increasing return periods of 10,25,50 and 100years.

Extreme Wind Variability and Wind Map Development in Western Java,Indonesia

Wind-related disasters are one of the most frequent disasters in Indonesia.It can cause severe damages of residential construction,especially in the world's most populated island of Java.Understanding the characteristics of extreme winds is crucial for mitigating the disasters and for defining structural design standards.This study investigated the spatiotemporal variations of extreme winds and pioneered a design wind map in Indonesia by focusing on western Java.Based on gust data observed in recent years from 24 stations,the extreme winds exhibit a clear annual cycle where northwestern and southeastern sides of western Java show out-of-phase relationship due to reversal monsoons.Meanwhile,extreme wind occurrences are mostly affected by small-scale weather systems,regardless of seasons and locations.To build the wind map,we used bias-corrected gust from ERA5 and applied the Gumbel method to predict extreme winds with different return periods.The wind map highlights some drawbacks of the current national design standards,which use single wind speed values regardless of location and return period.Beside a fundamental improvement for wind design,this study will benefit disaster risk mapping and other applications that require extreme wind speed distribution.

Study of the Wind Conditions in the South China Sea and Its Adjacent Sea Area

An increasing number of marine structures have been built for coastal protection and marine development in recent years,and wind,which is crucial to marine structures,should be analyzed.Therefore,typhoon frequency,wind climate,wind energy assess-ment,and extreme wind speed in the South China Sea(SCS)are investigated in detail in this study.The data are obtained from the China Meteorological Administration,the European Centre for Medium-range Weather Forecasts,and the National Centers for Envi-ronmental Prediction.The offshore wind energy potential is analyzed at five sites near the coast.The spatial and monthly frequencies of tropical cyclones for different intensity categories are analyzed.The extreme wind speed is fitted by five distribution models,and the generalized extreme value(GEV)distribution is selected as the most suitable function according to the goodness of fit.The spa-tial distributions of extreme wind speeds in the SCS are plotted on the basis of the GEV distribution and ERA5 data sets.The influ-ences of the distribution models and data sets on the calculated results are discussed.Moreover,the monthly extreme wind speed and comparison with the results of previous studies are analyzed.This study provides a reference for the design of wind turbines.

A Study of Wind Statistics Through Auto-Regressive and Moving-Average (ARMA) Modeling

Statistical properties of winds near the Taichung Harbour are investigated. The 26 years'incomplete data of wind speeds, measured on an hourly basis, are used as reference. The possibility of imputation using simulated results of the Auto-Regressive (AR), Moving-Average (MA), and/ or Auto-Regressive and Moving-Average (ARMA) models is studied. Predictions of the 25-year extreme wind speeds based upon the augmented data are compared with the original series. Based upon the results, predictions of the 50- and 100-year extreme wind speeds are then made.

Typhoon wind hazard model and estimation on return period of typhoon wind speed

Typhoons are one of the most serious natural disasters that occur annually on China’s southeast coast.A technique for analyzing the typhoon wind hazard was developed based on the empirical track model,and used to generate 1000-year virtual typhoons for Northwest Pacific basin.The influences of typhoon decay model,track model,and the extreme value distribution on the predicted extreme wind speed were investigated.We found that different typhoon decay models have least influence on the predicted extreme wind speed.Over most of the southeast coast of China,the predicted wind speed by the non-simplified empirical track model is larger than that from the simplified tracking model.The extreme wind speed predicted by different extreme value distribution is quite different.Four super typhoons Meranti(2016),Hato(2017),Mangkhut(2018)and Lekima(2019)were selected and the return periods of typhoon wind speeds along the China southeast coast were estimated in order to assess the typhoon wind hazard.

Mechanisms of the formation of wind-blown sand hazards and the sand control measures in Gobi areas under extremely strong winds along the Lanzhou-Xinjiang high-speed railway

The Lanzhou-Xinjiang high-speed railway(HSR)traverses areas of the Gobi Desert where extremely strong winds are frequent.These strong winds cause sand/gravel hazards,an unaddressed issue that often seriously compromises the safe operation of the HSR.This paper studies the mechanisms leading to wind-blown sand hazards and the outcomes of sand control projects in these areas.The main findings are as follows:(1)Cold northern airflows over the Tian Shan mountain range are accelerated by the wind tunnels and downslope effect as they pass over complex terrain comprising passes,gullies,and proluvial fans.Consequently,the wind intensity often increases two-to threefold,creating frequent high-speed winds that lead to severe sand damage along the HSR.(2)In the Gobi areas with extremely strong winds,sand grains can be lifted as high as 9 m from the ground into the air,far higher than in other areas of the desert.The sand transport rate decreases exponentially with increasing height.Both wind speed and particle size determine saltation height.Coarser particles and stronger winds provide the particles with a higher kinetic energy as they collide with the ground.In the wind zones of Baili and Yandun,the analysed study areas,the saltation layer height of wind-blown sand/gravel exceeds 3 and 2 m,respectively.(3)Based on the above findings,recently emerging sand control materials,suitable for the areas of interest,were screened and developed.Furthermore,under the proposed principle of‘supplementing blocking with trapping’,a comprehensive sand control measure was established,featuring sandblocking belts comprised of multiple rows,and high,vertical sand-trapping installations with a large grids size.The installed system showed a high efficacy,reducing sand transport rate by 87.87%and significantly decreasing the deposition of sand along a trial section of the HSR.

ON ASYMPTOTIC DISTRIBUTIONS FOR EXTREMES OF SURFACE TEMPERATURE AND SURFACE WIND IN CHINA

According to statistical inference method,the asymptotic distributions,concretely,Weibull and Gumbel distributions,for yearly extremes of surface temperature and wind in China were discovered.In this study we used the data of 173 stations for yearly maximum surface temperature and 158 stations for yearly minimum surface temperature and 83 stations for yearly maximum surface wind during the period from 1951 to 1982. Finally,the characteristics of the asymptotic distributions were discussed briefly.

Study of the wind-pressure distribution of flat-roof parabolic condensers based on wind-tunnel tests

The structure of parabolic condensers makes them susceptible to wind load because of their thin and large windward mirrors.In this paper,the wind pressure on a model of a condenser mirror(1:35)on multistorey flat roofs is analysed via pressure measurement in a wind tunnel.The mean wind-pressure distribution law of flat-roof condenser mirrors(including the change law with working conditions and the maximum distribution characteristics)and the distribution law of fluctuating and extreme wind pressure are obtained.Furthermore,by comparison with the ground-based condenser distribution law,similarities and differences between the two are obtained.Research results show that the wind-pressure distribution law of flat-roof parabolic condenser mirrors is the same as those on the ground,but the mean wind-pressure coefficient(absolute value)is generally~30%smaller.Furthermore,the maximum effect is generally located at the windward mirror edge and the mirror is more susceptible to wind pressure in wind directions of 30°and 135°-150°.The results of this study can provide a theoretical reference for wind-resistant structure design and multistorey flat-roof condenser-related research.

Effects of corner modifications on wind loads and local pressures on walls of tall buildings

In this study, the aerodynamic characteristics of tall buildings with corner modifications (e.g., local wind force coefficients, mean pressure distributions, normalized power spectrum density, and extreme local pressure) were examined. Wind tunnel experiments were conducted to measure the wind pressures on building models with different heights and recessed corners of different ratios. At a wind direction of a = 0° (i.e., wind blowing on the front of a building), corner modifications effectively reduced wind forces in all cases. Specifically, small corner modification ratios reduced wind forces more effectively than their larger counterparts. However, corner modifications resulted in extreme local pressure on building surfaces. In addition, for small corner modification ratios, the probability of extreme local pressure occurring at a = 0° was high. This probability was also high for large corner modification ratios at a = 15° (i.e., wind blowing slightly obliquely on the front of a building) because wind blowing obliquely creates substantial vortex shedding on one side surface and extreme negative pressure over one building side surface. Results of computational fluid dynamic modeling were adopted to determine details of the aerodynamic characteristics of tall buildings with corner modifications.