基于WRF-Fire模式的2009年“5· 21”蒙古国入境大火数值模拟研究

利用WRF-Fire模式对2009年“5·21”蒙古国草原入境大火进行火场发展数值模拟研究，并通过敏感性试验分析了防火隔离带对火势的阻挡作用。结果表明，模式可以较准确地再现环境风场对本次大火蔓延过程的影响，模拟火场面积、蔓延方向与实况基本一致。第一阶段（21日12—22时，世界时，下同）在蒙古国境内起火点附近，地面为裸露地表，可燃物负载量小，近地面为东北风，火线向西南方缓慢蔓延；第二阶段（21日22时—22日11时）风向转为西北，火线经平缓均一草地向东南方发展，在到达中蒙边境前地面风速增大到8～10 m/s，且风向与坡向一致，火线迅速移向中蒙边境防火隔离带；第三阶段（22日11时—23日20时）隔离带和人工灭火有效阻止了火线继续向中国境内蔓延，此阶段风向转为南风，火线向北扩展；第四阶段（23日20时—24日12时）风速达到16 m/s以上且风向转为西北风。受东面隔离带和湖泊的阻碍，火线缓慢向南蔓延。当火线到达南面的隔离带后，受隔离带阻挡及人工扑火作业的共同作用，本次大火于26日08时结束。敏感性试验表明，若不存在隔离带，火线将在风场的驱动下继续向东南、东北方向蔓延，所经区域主要地面可燃物类型从草地过渡到针叶林，火场的蔓延将造成大面积的森林资源损失。     

近50年中国风速变化多气候模式模拟检验

近年来,随着气候模式研究的快速发展,全球气候模式在模拟20世纪气候和气候变化特征,尤其是在模拟温度、降水等要素特征和变化及其人类活动对这些要素的影响等方面取得了丰硕的成果.然而,全球气候模式对近地层风速的模拟情况如何,目前仍缺少分析和检验.本文利用中国区域近地层风速观测资料,检验评估了参与IPCC AR4"20世纪气候耦合模式模拟"(20C3M)的19个伞球气候模式和国家气候中心新一代伞球气候模式(BCC_CSM1.0.1)模拟的1956-1999年中国近地层(10m)风速及其变化的模拟能力.研究发现,20个伞球气候模式基本上都能模拟出中国多年年(或季)平均风速分布状况,但模式模拟的平均风速一般小于观测值,尤以观测风速较大的北部和西北部地区模拟值偏小显著.气候模式模拟秋冬季风速分布的能力强于模拟夏春季的能力.模式基本上能模拟出冬、春季平均风速大于夏、秋季平均风速,但是模拟不出春、冬、夏、秋季平均风速依次减小的季节变化特征.模式及模式集成难以模拟出观测到的近50年中国年(或季)平均风速明显减小的变化趋势,少数模式能模拟出年(或季)平均风速略呈减小的变化趋势,但与观测值比相差约一个量级.模式对北部和西南部地区平均风速的变化模拟效果较好,而模式难以模拟东南-南部地区风速变化特征.     

复杂下垫面风电场风速数值模拟及误差特征

利用WRF模式分别对沿海及山地条件下风电场风速进行高分辨数值模拟,并对其误差特征进行分析,结果表明:1)WRF模式对复杂地形条件下的风速模拟性能良好,模拟值较好地体现天气尺度的周期变化;2)沿海及山地条件下模拟与观测的误差特征各不相同。模式静态数据未能显现沿海的小岛,并且低估了山地测风塔所在的海拔,导致沿海平均模拟风速偏大,山地平均模拟风速偏小;3)分析不同风向的归一化均方根误差,沿海陆风情况下,下垫面相对复杂,误差明显增大;沿海海风情况下,下垫面均一,误差明显减小;4)仅作单个风电场周边数百平方千米的模拟,采用一台12核的服务器进行WRF模式的并行计算可满足48 h短期预测的时效性。仅仅提高模拟的网格分辨率,并不一定能提升模拟的准确性。     

Inland and Offshore Propagation Speeds of a Sea Breeze from Simulations and Measurements

The inland and offshore propagation speeds of a sea breeze circulation cell are simulated using a three-dimensional hydrostatic model within a terrain-following coordinate system. The model includes a third-order semi-Lagrangian advection scheme, which compares well in a one-dimensional stand-alone test with the more complex Bott and Smolarkiewicz advection schemes. Two turbulence schemes are available: a local scheme by Louis (1979) and a modified non-local scheme based on Zhang and Anthes (1982). Both compare well with higher-order closure schemes using the Wangara data set for Day 33–34 (Clark et al., 1971).Two-dimensional cross-sections derived from airborne sea breeze measurements (Finkele et al. 1995) constitute the basis for comparison with two-dimensional numerical model results. The offshore sea breeze propagation speed is defined as the speed at which the seaward extent of the sea breeze grows offshore. On a study day, the offshore sea breeze propagation speed, from both measurements and model, is -3.4 m s^-1. The measured inland propagation speed of the sea breeze decreased somewhat during the day. The model results show a fairly uniform inland propagation speed of 1.6 m s^-1 which corresponds to the average measured value. The offshore sea breeze propagation speed is about twice the inland propagation speed for this particular case study, from both the model and measurements.The influence of the offshore geostrophic wind on the sea breeze evolution, offshore extent and inland penetration are investigated. For moderate offshore geostrophic winds (-5.0 m s^-1), the offshore and inland propagation speeds are non-uniform. The offshore extent in moderate geostrophic wind conditions is similar to the offshore extent in light wind conditions (-2.5 m s^-1). The inland extent is greater in light offshore geostrophic winds than in moderate ones. This suggests that the offshore extent of the sea breeze is less sensitive to the offshore geostrophic wind than its inland extent. However, these results hold only if it is possible to define an inland propagation speed. For stronger offshore geostrophic winds (-7.5 m s^-1), the sea breeze is completely offshore and the inland propagation speed is ill-defined.     

概率密度匹配方法在我国近海海面10 m风速预报中的应用

海面风速对航运及海上生产作业影响重大,但数值模式对于海面的风速预报仍存在较大误差。为降低数值模式海面10 m风速预报的系统性误差,提高海上大风预报准确率,基于2017—2019年中国气象局地面气象观测资料对ECMWF确定性模式的10 m风场预报结果进行检验评估,并采用概率密度匹配方法对模式误差进行订正。分析结果表明,概率密度匹配方法可有效地改善数值模式10 m风速预报的系统性误差,订正后风速在各个预报时效和风速量级的平均误差均较订正前有所降低。对于大量级风速的预报,经概率密度匹配方法订正后的风速预报的漏报率可减少10%以上。订正后12 h预报时效的8、9级风速预报的平均绝对误差分别由4.15 m/s、5.61 m/s降低至3.12 m/s、4.08 m/s,120 h预报时效的8、9级风速预报的平均绝对误差由7.38 m/s、9.35 m/s减小至6.46 m/s、8.07 m/s。在冷空气、台风大风天气过程中,基于概率密度匹配方法订正后的风速与实况观测更接近,能够为我国近海洋面10 m风速的预报提供更准确的参考。      

Extremes of near-surface wind speed over Europe and their future changes as estimated from an ensemble of RCM simulations

In this study, we analyse the uncertainty of the effect of enhanced greenhouse gas conditions on windiness projected by an ensemble of regional model simulations driven by the same global control and climate change simulations. These global conditions, representative for 1961–1990 and 2071–2100, were prepared by the Hadley Centre based on the IPCC SRES/A2 scenario. The basic data sets consist of simulated daily maximum and daily mean wind speed fields (over land) from the PRUDENCE data archive at the Danish Meteorological Institute. The main focus is on the results from the standard 50 km-resolution runs of eight regional models. The best parameter for determining possible future changes in extreme wind speeds and possible change in the number of storm events is maximum daily wind speed. It turned out during this study that the method for calculating maximum daily wind speed differs among the regional models. A comparison of simulated winds with observations for the control period shows that models without gust parameterisation are not able to realistically capture high wind speeds. The two models with gust parametrization estimate an increase of up to 20% of the number of storm peak (defined as gusts?≥?8 Bft in this paper) events over Central Europe in the future. In order to use a larger ensemble of models than just the two with gust parameterisation, we also look at the 99th percentile of daily mean wind speed. We divide Europe into eight sub-regions (e.g., British Isles, Iberian Peninsula, NE Europe) and investigate the inter-monthly variation of wind over these regions as well as differences between today’s climate and a possible future climate. Results show differences and similarities between the sub-regions in magnitude, spread, and seasonal tendencies. The model ensemble indicates a possible increase in future mean daily wind speed during winter months, and a decrease during autumn in areas influenced by North Atlantic extra-tropical cyclones.     

两种模式在风电场风速预测应用中的对比

利用2011年12月至2012年11月贺兰山风电场测风塔实测资料和同期WRF、BJ-RUC模式预测结果,对2种模式在风速预测中的应用进行对比分析。结果发现,月尺度上,2种模式预测的风速月均值普遍较实测值高,且WRF较BJ-RUC更接近实测值;WRF预测的月平均风速标准差普遍较实测低,而BJ-RUC普遍比实测大;春季WRF预测效果整体上较BJ-RUC好,其它季节WRF预测的月平均风速均方根误差较BJ-RUC的小,但与实测风速的相关性较BJ-RUC与实测风速相关性差。日尺度上,凌晨至中午前后和傍晚至前半夜2个时段,2种模式预测风速普遍比实测值大,而中午至傍晚时分正相反,预测值普遍较实测小。2种模式对〉12 m·s^-1风速预测的均方根误差最小,其次是3~12 m·s^-1,〈3 m·s^-1风速预测的均方根误差最大,但BJ-RUC对3~12 m·s^-1范围风速的变化趋势把握能力较好。WRF和BJ-RUC都普遍低估了1~4 m·s^-1风速段的频次,对5~10 m·s^-1范围频次普遍明显高估,对10 m·s^-1以上风速,WRF预测频次较实测低,而BJ-RUC预测频次则较实测高。BJ-RUC对该区风向的预测能力较WRF好。     

OBSERVATION AND ANALYSIS OF SEA SURFACE WIND OVER THE QIONGZHOU STRAIT

The spatial variation and diurnal fluctuation of sea surface wind over the Qiongzhou Strait were described using verified datasets from automatic weather stations on board a ferry, buoys, and on the coast. Results are as follows: (1) On average, sea surface wind speed is 3–4 m/s larger over the Qiongzhou Strait than in the coastal area. Sea surface wind speeds of 8.0 m/s or above (on Beaufort scale five) in the coastal area are associated with speeds 5–6 m/s greater over the surface of the Qiongzhou Strait. (2) Gust coefficients for the Qiongzhou Strait decrease along with increasing wind speeds. When coastal wind speed is less than scale five, the average gust coefficient over the sea surface is between 1.4 and 1.5; when wind speed is equal to scale five or above, the average gust coefficient is about 1.35. (3) In autumn and winter, the diurnal differences of average wind speed and wind consistency over the strait are less than those in the coastal area; when wind speed is 10.8 m/s (scale six) or above, the diurnal difference of average wind speed decreases while wind consistency increases for both the strait and the coast.     

A numerical investigation of wind speed effects on lake-effect storms

Observations of lake-effect storms that occur over the Great Lakes region during late autumn and winter indicate a high sensitivity to ambient wind speed and direction. In this paper, a two-dimensional version of the Penn State University/National Center for Atmospheric Research (PSU/NCAR) model is used to investigate the wind speed effects on lake-effect snowstorms that occur over the Great Lakes region.Theoretical initial conditions for stability, relative humidity, wind velocity, and lake/land temperature distribution are specified. Nine different experiments are performed using wind speeds ofU=0, 2, 4,..., 16 m s^–1. The perturbation wind, temperature, and moisture fields for each experiment after 36 h of simulation are compared.It is determined that moderate (4–6 m s^–1) wind speeds result in maximum precipitation (snowfall) on the lee shore of the model lake. Weak wind speeds (0U<4 m s^–1) yield significantly higher snowfall amounts over the lake along with a spatially concentrated and intense response. Strong wind speeds (6<U16 m s^–1), yield very little, if any, significant snowfall, although significant increases in cloudiness, temperature, and perturbation wind speed occur hundreds of kilometers downwind from the lake.     

河北地区边界层内不同高度风速变化特征

为了研究城市化进程对风速变化的影响,利用1971-2006年河北省境内邢台、张家口和乐亭3个探空站高空风观测资料和对应地面站风观测资料,统计分析了边界层内距地面10m、300m、600m、900m 4个高度的长期风速变化特征,比较了不同高度风速变化趋势的异同.分析结果表明:3站年和季节平均风速随着距地面高度的增加而变大,但最大的风速垂直递增率出现在从10m到300m之间;各站各高度层月平均风速具有明显的季节变化特征,春季风速最大,夏季较小;在近36年里,3站平均的地面(10m高)年和季节平均风速变化存在显著的减少趋势,300m以上各高度层平均风速一般也降低,但远没有地面明显;不同高度平均风速变化趋势的差异可能主要是由城市化以及台站附近观测环境的改变引起的,这使得地面风速明显减弱;但地面以上各层平均风速同样存在一定减弱现象,说明背景大气环流的变化也是地面风速下降的原因之一.     

南京地面风速概率分布律的城乡差异

根据南京气象站及其周边3个乡村自动气象站2005年逐时风速资料,拟合了风速的概率分布函数,分析表明:南京城、乡地面风速的概率分布均与3参数的韦伯分布吻合度很高,风速概率密度函数(PDF)曲线形状存在明显的城乡差别,城市风速PDF曲线更加陡峻,即风速分布更为集中;在0.75~3.75 m/s,城市风速PDF值明显高于周边乡村,而在3.75 m/s和0.75 m/s范围,城市风速概率密度值则低于乡村;城市下垫面的摩擦效应削弱风速而热力效应起增强风速作用,对风速的城乡差值序列的分析发现:多数时间城市风速是小于乡村风速的,但风速小于1.90 m/s条件下,城市风速会出现大于乡村的现象;总体上摩擦效应的作用远大于热力效应;城市效应使全年平均风速下降0.43 m/s。     

基于探空风资料的大气边界层不同高度风速变化研究

利用1981—2014年我国资料齐全的93个高空气象观测站(距离雷达300、600、900 m高度)的探空风资料,按照气象地理区划,借助GIS分析了边界层内不同高度风速及其趋势的时空变化,得到以下结论:300～900 m,东北和华北地区累年平均风速较大,西南和西北地区累年平均风速较小;边界层内各高度同一地区平均风速的月变化趋势基本一致,但各地区季节风速变化不同,同一地区月平均风速的年较差随高度上升而增大;300 m.各地区年平均风速均显著减小:在600和900 m.华北、西北、华中地区年平均风速呈增加趋势,东北地区年平均风速呈减小趋势,但均未通过显著性水平检验;各高度年平均风速空间分布均为东北地区较大,尤其大兴安岭和东北平原地带;从沿海到内陆,由东至西风速逐渐减小;在300 m.全国年平均风速以减小趋势为主;在600 m,全国大部分地区年平均风速呈增加趋势,尤其是中部、西北和华东沿海地区;在900 m高度,全国年平均风速变化趋势呈现由边界向内部的包围态势,中心地区呈增加趋势,边界地区均呈减小趋势,但是通过显著性水平检验的地区不多。     

城市化对石家庄站近地面风速趋势的影响

利用1972—2012年石家庄城市站和4个乡村站地面风速资料,采用城乡对比方法,对石家庄城市站地面风速序列中的城市化影响进行分析,结果表明,石家庄站年和季节平均地面风速和平均10 min最大风速的长期下降趋势,主要是由城市化因素引起。具体结论如下：(1)石家庄站年和四季平均风速、平均10 min最大风速和大风日数均呈极显著的减少趋势,年平均减少速率分别为-0.15 (m/s)/10a、-1.05 (m/s)/10a和-2.90 d/10a;乡村站年平均风速呈微弱下降趋势,年平均10 min最大风速减少较为明显,年大风日数减少趋势非常显著,减少速率分别为-0.02 (m/s)/10a、-0.21 (m/s)/10a和-2.19 d/10a。(2)石家庄站年平均风速下降趋势中的城市化影响为-0.13 (m/s)/10a,城市化影响非常显著,城市化贡献率达到86.0%。该站春、夏、秋、冬季平均风速变化的城市化影响分别为-0.16 (m/s)/10a、-0.10 (m/s)/10a、-0.13 (m/s)/10a和-0.15 (m/s)/10a,城市化贡献率分别为82.8%、87.6%、88.6%和85.4%。(3)石家庄站年平均10 min最大风速变化趋势中的城市化影响为-0.84 (m/s)/10a,城市化贡献率为79.7%;春、夏、秋、冬季平均10 min最大风速变化趋势中的城市化影响分别为-0.94 (m/s)/10a、-0.80 (m/s)/10a、-0.60 (m/s)/10a和-1.01 (m/s)/10a,城市化贡献率分别达到90.4%、78.6%、64.9%和79.1%。(4)城市化对石家庄站年大风日数减少的影响不显著,但冬季大风日数减少仍明显与城市化过程有关。     

恶劣探测环境对风速传感器启动风速的影响

讨论长期处于海风、酸雨、沙尘等恶劣探测环境下,风速传感器启动风速的变化。采用试验分析的方法,利用M3DS型风速传感器自动化检定系统和EL15-1C型风速传感器,分别测量取自不同恶劣探测环境的风速传感器和全新风速传感器的启动风速数据。得到的数据显示:取自海风、酸雨、沙尘等恶劣探测环境的风速传感器启动风速远大于全新风速传感器启动风速。长期海风、酸雨、沙尘天气改变了风速传感器的机械结构,同时降低了风速传感器启动风速的鉴别阀。     

乌鲁木齐机场东南大风数值预报及地形敏感性试验

利用WRF模式和GFS资料对乌鲁木齐机场一次东南大风天气进行了预报和地形敏感性试验。模式预报的结果表明:WRF模式对东南大风的起风时间、持续时间、风速大小等方面有较强的预报能力。地形敏感性试验表明:1乌鲁木齐市区与机场300m左右的高度差对机场风速的影响很大;2机场上空下沉运动的强弱与东南大风的强弱有很好的对应关系;3机场东南大风的风速变化并不总是与峡谷两端气压梯度力的变化同步。此次东南大风天气的产生是低空动量下传、狭管效应和下坡风共同作用的结果。动量下传主要出现在海拔2000m以下的高度,下坡风主要出现在海拔935m以下的高度。     

拖曳系数参数化方案对工程台风模拟风场的影响研究

基于台风边界层的最新观测和研究成果,提出了最大风速半径、边界层风速比、拖曳系数等关键参数的经验方案,并依据垂直平均水平运动方程,建立适用于西北太平洋的工程台风风场模型,最高分辨率为2 km。通过理想试验,验证了所建模型的合理性,并重点关注模拟风场对拖曳系数参数化方案的敏感性。结果表明,不同拖曳系数参数化方案（增长型、饱和型、下降型）对强台风内核区的风场模拟有显著影响,但对最大风速的模拟影响不大。为验证所建模型对实际西北太平洋台风的适用性,选取台风“海葵”（1211）进行个例试验,得到最大风速的平均误差为-0.36 m/s,均方根误差为2.22 m/s。进一步选取我国沿海6个受“海葵”影响的测站,进行模拟风向、风速与观测的对比分析,发现所建台风风场模型能很好地模拟出台风影响过程中的风向转变,但各测站的风速均方根误差在1.61~6.92 m/s之间。较大的风速误差主要出现在位于台风中心附近的测站,意味着我国沿海复杂地形对台风的衰减作用在模型中考虑不足,是未来的改进方向。      

Characteristics of Spatiotemporal Distribution of Sea Surface Wind along the East Coast of Guangdong Province

We analyzed the frequency distribution characteristics of wind speeds occurring at different offshore sites within a range of 0–200 km based on the sea surface wind data captured via buoys and oil platforms located along the east coast of Guangdong Province. The results of the analysis showed that average wind speed measured for each station reached a maximum in winter while minima occurred in summer, corresponding to obvious seasonal variation, and average wind speed increased with offshore distance. The prevailing wind direction at the nearshore site is the easterly wind, and the frequency of winds within 6–10 m s^–1 is considerable with that of winds at > 10 m s^–1. With the increase of the offshore distance, the winds were less affected by the land, and the prevailing wind direction gradually became northerly winds, predominately those at > 10 m s^–1. For areas of shorter offshore distance (< 100 km), surface wind speeds fundamentally conformed to a two-parameter Weibull distribution, but there was a significant difference between wind speed probability distributions and the Weibull distribution in areas more than 100 km offshore. The mean wind speeds and wind speed standard deviations increased with the offshore distance, indicating that with the increase of the wind speed, the pulsation of the winds increased obviously, resulting in an increase in the ratio of the mean wind speed to the standard deviation of wind speed. When the ratio was large, the skewness became negative. When a relatively great degree of dispersion was noted between the observed skewness and the skewness corresponding to the theoretical Weibull curve, the wind speed probability distribution could not be adequately described by a Weibull distribution. This study provides a basis for the verification of the adaptability of Weibull distribution in different sea areas.     

利用浮标站观测资料分析台风“贝碧嘉”过境时风浪变化特征

利用北部湾海域一个大型气象浮标站获取的台风"贝碧嘉"过程实测数据,分析了该台风过境时风浪变化特征。分析结果表明:台风的风速时程变化曲线呈"M"形双峰分布,台风眼壁区风速最大,前眼壁区风速大于后眼壁区,前眼壁区和后眼壁区最大风速分别为22.6m/s和20.8m/s;台风眼区气压和风速最小,波高和波周期最大,其中眼区最大风速为2.7m/s,最大波高为5.4m,最大波周期为5.5s;波高最大值出现时间滞后风速最大值40min;台风眼区以外的波高与风速正相关;在台风从浮标站南侧经过期间,风向和波向均沿着顺时针方向旋转,其中风向和波向10min最大旋转角度分别为50°和150°;风向与波向不在同一个方向,两者之间的夹角平均为171°。     

Estimation of sector roughness lengths and the effect on prediction of the vertical wind speed profile

An estimate of roughness length is required by some atmospheric models and is also used in the logarithmic profile to determine the increase of wind speed with height under neutral conditions. The choice of technique for determining roughness lengths is generally constrained by the available input data. Here, we compare sets of roughness lengths derived by different methods for the same site and evaluate their impact on the prediction of the vertical wind speed profile.Wind speed and direction data have been collected at four heights over a three-year period at the North Norfolk Wind Monitoring Site. Wind speed profiles were used to generate sector roughness lengths based on the logarithmic profile formula. This is the only direct way of determining roughness lengths. The simplest and cheapest method is to use maps with published tables giving roughness length estimates for different terrain types. Alternatively Wieringa (1976, 1986) and Beljaars (1987) give formulae for determining roughness lengths from wind speed gusts or standard deviations.The four sets of estimated roughness lengths vary considerably. They were used to estimate 34 m wind speeds from 12.7 m observations. The profile-derived roughnesses are used simply as a check on the prediction of the wind speed profiles. The terrain-derived roughness lengths give reasonable results. Gust-derived and standard deviation roughnesses both predict wind speeds which are lower than the observed ones. The error is greater in the case of standard deviation roughnesses. If stability corrections are applied in the prediction of the vertical wind speed profile, the results are considerably improved.     

基于自动气象站和风廓线雷达资料的大理机场风切变分析与应用

根据2016—2017年大理机场航空器报告的风切变事件,利用同时段的自动气象观测资料、风廓线雷达资料对大理机场风切变进行了统计和分析。结果表明:①风切变均发生在每年的11月至次年4月,1月、2月最多;主要发生于07:00—13:00,一半出现在晴天;发生在350m以下占83%。②100m以下的风切变,地面均有阵性风,最大最小风速差6m/s;发生在15～91m的6次风切变,5次报告风切变的一端风向变化超过180°,南北两端地面风出现对头风,风速差异明显。AWOS(Automated Weather Observation System)捕捉到风向风速的明显变化可为近地层风切变预警提供参考。③发生在高度较高的风切变,雷达资料在遭遇风切变高度的上下层存在≥8m/s风速差,能确定上下层风不连续的准确高度、开始时间和结束时间。④机场区域常出现地面风速大而上空风速小或地面风速小而上空风速大的情况,结合地面风和风廓线雷达资料可为今后低高度风切变的初步预警提供参考。