A regression-based statistical correction of mesoscale simulations for near-surface wind speed using remotely sensed surface observations

Wind speed is an important meteorological variable for various scientific communities. In this study, numerical mesoscale simulations were performed over the Republic of Korea in 2006, to produce wind information distributed homogeneously with space. Then, an attempt was made to statistically correct the simulated nearsurface wind speed using remotely sensed surface observations. The weak wind season (WWS, from May to October) and strong wind season (SWS, from November to April) were classified on the basis of the annual mean wind speed. Although the spatial features and monthly variation pattern of the near-surface wind speed were reasonably simulated in the Weather Research and Forecasting (WRF) model, the simulations overestimated the observed values. To correct the simulated wind speeds, a regression-based statistical algorithm with different constants and coefficients for WWS and SWS was developed using match-up datasets of wind observations and satellitederived variables (land surface temperature and normalized difference water index). The corrected wind speeds showed reasonable performance for both WWS and SWS with respect to observed values. The monthly variation in the corrected wind speeds over the Republic of Korea also matched better with observations throughout the year, within a monthly bias range of approximately ± 0.2 m s^?1. The proposed algorithm using remotely sensed surface observations may be useful for correcting simulated near-surface wind speeds and improving the accuracy of wind assessments over the Republic of Korea.     

风电场风速降尺度预报方法对比分析

使用中尺度数值天气预报业务模式9 km和3 km分辨率的模式输出产品,分别应用小尺度模式CALMET模式和双线性插值(BLI)方法将预报风速进行降尺度处理,并对比预报风速和风塔观测资料。结果表明：WRF模式9 km分辨率的模式输出经过CALMET模式降尺度以后得到的风速预报效果比3 km分辨率的模式输出略好。同时,由于中尺度数值预报模式分辨率本身较高,使用BLI也可以得到较好的风速预报。将风速分为0 m·s^-1≤风速<5 m·s^-1,5 m·s^-1≤风速<10 m·s^-1和风速≥10 m·s^-1共3个等级,检验3个风速等级的预报偏差百分比得出,CALMET模式和BLI方法对10 m·s^-1以上的大风的预报效果相对较差;如何对大风预报进行订正对风速预报准确率的提高具有重要的意义。     

Estimating the surface wind speed over drifting pack ice from surface weather charts

Routine surface wind speed data, vital for the study of drifting pack ice, are not available for the polar oceans. Over sea, it has been demonstrated by Hasse that estimates of surface wind speed may be obtained from the geostrophic wind speed using linear formulae. Comparing estimated with observed data for six sites in Canada, it is found that the formulae may also be applied to obtain estimates of surface wind speed over pack ice.     

风电场两种超短期风速预报方法的效果对比

针对风电场所需的时效在0~4 h,且时间分辨率不低于15 min的超短期风速预报。根据测风塔实时发回的实测风速序列,建立了基于BP神经网络的风电场风速时间序列外延预报模型。另一方面,建立 MM5模式预报风速与实测风速的误差序列,并利用BP神经网络作误差序列的外延预报,从而利用误差的预报值对MM5风速预报值进行订正,获得新的预报值。综合对两种方法的预报效果指标分析以及拟合曲线的比较结果表明:使用BP神经网络对MM5风速预报值进行修订的方法在总体上效果较优,特别是当影响风电场的天气系统变化明显,近地层风速变率较大时,该方法的预报效果更具有明显的优势。     

Temporal change of some statistical characteristics of wind speed over the Great Hungarian Plain

Summary  The objective of this study is to assess whether changes in the surface pressure field over Europe are reflected in the statistical structure of the wind field over the Great Hungarian Plain. The data basis consists of hourly wind speed data from 1968–72 and 1991–95, from three meteorological stations (Debrecen, Békéscsaba and Szeged) located in the Great Hungarian Plain. A new statistical test and its application for determining the statistical significance of differences between expected values of non-independent wind speed time series is presented in the paper. The summer wind field over the Great Hungarian Plain shows evidence of change: wind speeds have been decreasing and a tertiary maximum, in July, has become less pronounced. Received August 31, 2000 Revised January 2, 2001     

A technique of radiosonde launch under the surface wind of high speed

Upper-air sounding is impacted by the surface wind of high speed in polar regions and in the areas affected by tropical cyclones. Considered are the main existing methods of radiosonde launching under such conditions. It is suggested to use the cone tower in order to provide a greater initial height of launching of the instrumental box as compared with the routine launching method. The employement of the tower allows using the wind force jointly with the lifting force of the balloon to deliver the instrumental box up to the top of the tower. Installation of the tower into the wind shelter secures the operator and provides the radiosonde launching even in the case of the very strong wind. The field model experiment corroborated the efficiency of the proposed scheme of radiosonde launching.     

华东地区地面和高空风场的多模式集成精细化预报研究

基于欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts, ECMWF)、中国国家气象中心业务运行的中尺度数值预报系统(Global/Regional Assimilation and Prediction Enhanced System Meso, GRAPES-Meso)、美国国家环境预报中心(National Centers for Environmental Prediction, NCEP)的全球预报系统(Global Forecast System, GFS)、GRAPES全球预报系统(GRAPES-GFS)4个模式风场预报资料,利用双线性、反距离加权、三次样条、克里格等插值方法对华东及周边地区(110°～130°E,20°～40°N)2020年1—4月逐日地面和高空风0～72 h集合预报资料进行降尺度处理,得到满足机场及终端区气象保障的精细化风场预报。此外,还对精细化风场预报做多模式集成。结果表明,对于风场的精细化格点预报,反距离加权插值方法误差最小,为最优水平插值方法。基于扩展复卡尔曼滤波的多模式集成...     

湍流频散对边界层风廓线的影响

应用包括湍流粘性和频散的新的Reynolds平均动量方程，分析了边界层的垂直风速廓线，发现包含湍流频散的地面层的风速廓线对经典的风廓线指数规律有一个对数规律的修改；而且在不稳定层结下比在稳定层结下，湍流的频散效应更为显；在中性条件下，指数规律退化为对数规律并且Karman常数被另外一个常数所代替，而这个新常数也可以通过相似理论来获得。     

A discussion of statistical methods used to estimate extreme wind speeds

Summary Wind speeds in extra-tropical latitudes are known to be approximately Weibull distributed. Hence a Weibull distribution fitted to all available data is often used to predict extreme winds. The most extreme values then, however, have little influence on the estimated parent Weibull distribution, and the accuracy of the extreme value predictions obtained in this manner may be questioned. In the present paper such a “Weibull method” is compared to a method based on statistical extreme value theory, “the annual maxima method”. The comparison is based on 30 years of 10 minute wind speed averages measured hourly at 12 meteorological stations located at airports in Sweden. Results show that the Weibull method generates incorrect estimates of the tails of the distributions of wind speeds and of the distribution of yearly maximum wind speed, and that serial dependence of individual measurements has to be taken into account. In addition, it is inherent in the Weibull method that it does not provide any confidence bounds for the estimates. The annual maxima method avoids these problems. The measurements were rounded, first to entire knots, and then to m/s. A further, “technical”, result is that if this rounding were disregarded in the estimation procedure, then the computed standard errors of the parameter estimates would be erroneously low. Hence, if rounding is done, it should be taken into account in the estimation procedure. We also believe this to be a clear indication that rounding of the data decreases estimation accuracy.     

Short-term temporal variability of atmospheric surface pressure and wind speed in the Canadian Arctic

In this study, the spatial differences and interannual fluctuations in temporal variability of surface pressure and wind speed on different timescales at 12 locations in the Canadian Arctic are documented. Temporal variability is defined as the mean-squared value of time tendencies smoothed by running means over different intervals. It is shown that variability on timescales of up to 1 month is itself highly variable, both in space and time. Due to the significant impacts from the immediate geographical environment, for surface wind speed, these variations show no spatial pattern on a continental scale, and only a few persistent trends over periods of more than 10 years. Also, spatial and temporal anomalies do not significantly depend on timescale. Contrary to this, spatial and temporal variations in the variability of surface pressure and its changes with time show well-defined regional similarities, as well as a strong spatial and temporal dependence on timescale. As a result, variability of surface pressure on timescales between 1 and 3 days increases from the northeast region of the domain towards the southwest. On longer timescales, this spatial gradient is reversed. The consistent spatial pattern across the study domain suggests that variability of surface pressure is primarily governed by large-scale atmospheric processes, and is to a large extent independent of the exact geographical setting.     

应用泊松耿贝尔分布估算海上极端风速

采用泊松耿贝尔分布,基于中国气象局发布的《CMA-STI热带气旋最佳路径数据集》资料来估算海上极端风速,并以上川岛气象站多年实测资料通过概率评估来加以验证。结果表明,采用泊松耿贝尔分布可以得到较为保守的海上极值风速取值。对于海上的小面积区域的重现期风速估算,采用50 km半径区域进行评估,可以得到较为合理的估算结果,当评估区域较大时,则需考虑适当扩大评估半径。     

Comparative analysis of regression and artificial neural network models for wind speed prediction

In this study, wind speed was modeled by linear regression (LR), nonlinear regression (NLR) and artificial neural network (ANN) methods. A three-layer feedforward artificial neural network structure was constructed and a backpropagation algorithm was used for the training of ANNs. To get a successful simulation, firstly, the correlation coefficients between all of the meteorological variables (wind speed, ambient temperature, atmospheric pressure, relative humidity and rainfall) were calculated taking two variables in turn for each calculation. All independent variables were added to the simple regression model. Then, the method of stepwise multiple regression was applied for the selection of the “best” regression equation (model). Thus, the best independent variables were selected for the LR and NLR models and also used in the input layer of the ANN. The results obtained by all methods were compared to each other. Finally, the ANN method was found to provide better performance than the LR and NLR methods.     

城市化对近地层风速概率分布及参数的影响

通过地面风速Weibull概率分布参数的阶段变化来描述城市化对地面风速的影响,并通过理论分析得出城市化进程导致其尺度参数c缩小,位置参数r增大的趋势效应的结论。将北京等8个城市1982—2005年地面天气资料定时数据按时间划分为前、后两个时段,分别拟合分布曲线的参数,对比前、后两个时段的拟合结果,验证了理论分析所得结论,即随城市的发展,各城市风参数c不同程度地缩小,r不同程度地增大,同时概率密度曲线的峰值均增大;不同城市的风速概率密度函数曲线变化特征有所不同,根据前、后时段概率密度曲线变化的特征,8个城市风速概率分布变化大致可分为A、B两种类型,两者的主要差异是A型变化特征为在曲线两端(大风和静风)的概率都减少,曲线分布更加集中;B型则是大风概率减少而静风的概率则增大,曲线向左移动;A型变化城市的r参数平均增大46.3%,明显大于B型城市的15.7%。初步资料分析还表明,风参数c和r变化幅度与城市化扩张速度有关。     

利用对数正态分布计算年最大风速

本文提出用对数正态分布计算年最大风速,这种方法与当前使用的计算方法主要的不同是,它具有较完善的子样检验方法,并且能计算最大风速的容忍上限。     

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。     

高分辨率统计降尺度数据集NEX-GDDP对中国极端温度指数模拟能力的评估

利用1986—2005年中国地面气象台站观测的格点化逐日气温资料（CN05.1）评估了高分辨率统计降尺度数据集NASA Earth Exchange/Global Daily Downscaled Projections（NEX-GDDP）中21个全球气候模式对中国极端温度指数的模拟能力。在选用了日最低温度最大值（TNx）、日最高温度最大值（TXx）、暖夜指数（TN90p）和暖昼指数（TX90p）来研究极端温度事件的变化。结果显示:（1）除MRI-CGCM3模拟的日最高温度最大值外,其余模式对4个指数的模拟结果均表现出与观测一致的上升趋势,但模拟结果的平均值相对观测平均低0.26℃/（10 a）（日最低温度最大值）、0.19℃/（10 a）（日最高温度最大值）、2.21%/（10 a）（暖夜指数）、1.04%/（10 a）（暖昼指数）。（2）不同模式对各指数变化趋势空间分布特征的模拟存在较大差别,对日最低温度最大值、日最高温度最大值、暖夜指数和暖昼指数模拟能力最优模式分别为CCSM4、CESM1-BGC、MIROC-ESM-CHEM和bcc-csm1-1。模式模拟的日最低温度最大值和日最高温度最大值气候态平均值与观测值的相关系数在0.97以上。暖夜指数和暖昼指数模拟结果与观测值的标准差比值为0.34—1.58,均方根误差变化为1.6%—3.47%,对这两个指数模拟能力较优的模式分别为MIROC-ESM-CHEM（暖夜指数）和CESM1-BGC（暖昼指数）。（3）综合模式对4个指数在气候态平均值和变化趋势模拟能力的评估结果来看,CanESM2、CESM1-BGC和MIROC-ESM-CHEM显示了相对较高的模拟能力。因此,在利用GDDP-NEX研究未来极端温度事件时,建议将它们作为优选模式。      

Comparison of prediction performance using statistical postprocessing methods

As the 2018 Winter Olympics are to be held in Pyeongchang, both general weather information on Pyeongchang and specific weather information on this region, which can affect game operation and athletic performance, are required. An ensemble prediction system has been applied to provide more accurate weather information, but it has bias and dispersion due to the limitations and uncertainty of its model. In this study, homogeneous and nonhomogeneous regression models as well as Bayesian model averaging (BMA) were used to reduce the bias and dispersion existing in ensemble prediction and to provide probabilistic forecast. Prior to applying the prediction methods, reliability of the ensemble forecasts was tested by using a rank histogram and a residualquantile-quantile plot to identify the ensemble forecasts and the corresponding verifications. The ensemble forecasts had a consistent positive bias, indicating over-forecasting, and were under-dispersed. To correct such biases, statistical post-processing methods were applied using fixed and sliding windows. The prediction skills of methods were compared by using the mean absolute error, root mean square error, continuous ranked probability score, and continuous ranked probability skill score. Under the fixed window, BMA exhibited better prediction skill than the other methods in most observation station. Under the sliding window, on the other hand, homogeneous and non-homogeneous regression models with positive regression coefficients exhibited better prediction skill than BMA. In particular, the homogeneous regression model with positive regression coefficients exhibited the best prediction skill.     

Climate change scenarios for surface temperature in Emilia-Romagna (Italy) obtained using statistical downscaling models

Summary Possible changes of mean climate and the frequency of extreme temperature events in Emilia-Romagna, over the period 2070–2100 compared to 1960–1990, are assessed. A statistical downscaling technique, applied to HadAM3P experiments (control, A2 and B2 scenarios) performed at the Hadley Centre, is used to achieve this objective. The method applied consists of a multivariate regression based on Canonical Correlation Analysis (CCA), using as possible predictors mean sea level pressure (MSLP), geopotential height at 500 hPa (Z500) and temperature at 850 hPa (T850), and as predictands the seasonal mean values of minimum and maximum surface temperature (T_min and T_max), 90^th percentile of maximum temperature (T_max90), 10^th percentile of minimum temperature (T_min10), number of frost days (T_nfd) and heat wave duration (HWD) at the station level. First, the statistical model is optimised and calibrated using NCEP/NCAR reanalysis to evaluate the large-scale predictors. The observational data at 32 stations uniformly distributed over Emilia-Romagna are used to compute the local predictands. The results of the optimisation procedure reveal that T850 is the best predictor in most cases, and in combination with MSLP, is an optimum predictor for winter T_max90 and autumn T_min10. Finally, MSLP is the best predictor for spring T_min while Z500 is the best predictor for spring T_max90 and heat wave duration index, except during autumn. The ability of HadAM3P to simulate the present day spatial and temporal variability of the chosen predictors is tested using the control experiments. Finally, the downscaling model is applied to all model output experiments to obtain simulated present day and A2 and B2 scenario results at the local scale. Results show that significant increases can be expected to occur under scenario conditions in both maximum and minimum temperature, associated with a decrease in the number of frost days and with an increase in the heat wave duration index. The magnitude of the change is more significant for the A2 scenario than for the B2 scenario.     

孟加拉湾的叶绿素a,海表温度和风速的趋势

孟加拉湾（BoB）是一个高能量活跃的地区,其短期内的动态变化将对浮游环境产生巨大影响."风泵"能够在BoB海域导致垂直的混合从而影响海表温度和叶绿素浓度.本文对2006——2016年的月平均Aqua-MODIS叶绿素a （chl-a）浓度数据和Sea WiFS月度气候态数据进行了分析,研究了叶绿素浓度的时间/季节变化和温度以及风速的关系.基于季风期间的chl-a变异与海表温度（SST）,评估了在BoB海域它们之间的关系和变化.chl-a浓度值的趋势分析表明,该区域的垂直混合非常低,冬季最高,夏季最低.冬季最大chl-a浓度值为0.50 mg/m³,并且从2月开始下降到夏季季风期间.与冬季季风相比,夏季季风期间叶绿素表现出较低的浓度.在夏季季风期间,特别是在7月和8月,由于云层密集,卫星传感器无法准确捕获chl-a浓度值.chl-a浓度和SST之间相关系数R²值为0.218 1.