Assimilation of <Emphasis Type="Italic">HY-2A</Emphasis> scatterometer ambiguous winds based on feature thinning

This paper focuses on the data assimilation methods for sea surface winds, based on the level-2B HY-2A satellite microwave scatterometer wind products. We propose a new feature thinning method, which is herein used to screen scatterometer winds while maintaining the key structure of the wind field in the process of data thinning for highresolution satellite observations. We also accomplish feeding the ambiguous wind solutions directly into the data assimilation system, thus making better use of the retrieved information while simplifying the assimilation process of the scatterometer products. A numerical simulation experiment involving Typhoon Danas shows that our method gives better results than the traditional approach. This method may be a valuable alternative for operational satellite data assimilation.     

Assimilation of ERS‐2 scatterometer winds using the Canadian 3D‐var

Abstract

The goal of this study is to evaluate the impact of incorporating the marine surface winds retrieved from the ERS‐2 scatterometer in the Canadian three‐dimensional variational analysis system, (3D‐var). The aspects of the 3D‐var most relevant to the assimilation of surface ‐wind observations and a general method for resolving the directional ambiguity of the retrieved scatterometer ‐winds are first described. A comparison ‐with 6‐h forecasted winds is then made to demonstrate that these data are of high quality, but exhibit a speed bias that can be removed by increasing their amplitudes by about 5%. The analysis increment from a single scatterometer wind observation is calculated to illustrate the response of the 3D‐var to surface wind observations. As a consequence of the forecast error covariance model, the assimilation of surface wind observations produces meteorologically consistent increments for both the rotational and divergent wind components and the mass field. The results from a series of cross‐validation experiments using ship‐based wind data demonstrate a positive impact of assimilating scatterometer winds and the effectiveness of a simple method for estimating and removing the speed bias. The impact of assimilating scatterometer data within a short assimilation cycle is also evaluated. Overall, the results show that including scatterometer data in the analysis decreases the 6‐h forecast error of surface wind by 13%. Over the northern extra‐tropics the improvement is only 4% and for the southern extra‐tropics it is 16%. Results from a series of two‐day forecasts produced using the analyses from the assimilation cycles with and without retrieved scatterometer winds included are also presented. Using radiosonde observations at 850 hPa, 500 hPa, 250 hPa and 100 hPafor verification, the impact on the forecasts is nearly neutral in the northern hemisphere and the tropics. Conversely, a significant positive impact is found on both wind and mass fields in the southern hemisphere over the entire two‐day forecast.     

Assimilating QuikSCAT Ocean Surface Winds with the Weather Research and Forecasting Model for Surface Wind-Field Simulation over the Chukchi/Beaufort Seas

To achieve a high-quality simulation of the surface wind field in the Chukchi/Beaufort Sea region, quick scatterometer (QuikSCAT) ocean surface winds were assimilated into the mesoscale Weather Research and Forecasting model by using its three-dimensional variational data assimilation system. The SeaWinds instrument on board the polar-orbiting QuikSCAT satellite is a specialized radar that measures ice-free ocean surface wind speed and direction at a horizontal resolution of 12.5 km. A total of eight assimilation case studies over two five-day periods, 1–5 October 2002 and 20–24 September 2004, were performed. The simulation results with and without the assimilation of QuikSCAT winds were then compared with QuikSCAT data available during the subsequent free-forecast period, coastal station observations, and North American Regional Reanalysis data. It was found that QuikSCAT winds are a potentially valuable resource for improving the simulation of ocean near-surface winds in the Chukchi/Beaufort Seas region. Specifically, the assimilation of QuikSCAT winds improved, (1) offshore surface winds as compared to unassimilated QuikSCAT winds, (2) sea-level pressure, planetary boundary-layer height, as well as surface heat fluxes, and (3) low-level wind fields and geopotential height. Verification against QuikSCAT data also demonstrated the temporal consistency and good quality of QuikSCAT observations.     

The impact of the assimilation of scatterometer winds on surface wind and wave forecasts

Recent work has demonstrated that surface marine winds from the Bureau of Meteorology's operational Numerical Weather Prediction (NWP) systems are typically underestimated by 5 to 10%. This is likely to cause significant bias in modelled wave fields that are forced by these winds. A simple statistical adjustment of the wind components is shown to reduce the observed bias in Significant Wave Height considerably. The impact of increasing the vertical resolution of the NWP model and assimilating scatterometer data into the model is assessed by comparing the resulting forecast wind and waves to observations. It is found that, in general, the inclusion of scatterometer observations improves the accuracy of the surface wind forecasts. However, most of the improvement is shown to arise from the increased number of vertical levels in the atmospheric model, rather than directly from the use of the observations. When the wave model is forced with surface winds from the NWP model that includes scatterometer data, it is found that the scatterometer assimilation does not reduce the systematic bias in surface wave forecasts, but that the random errors are reduced.     

Intercomparison of the performance of MM5/WRF with and without satellite data assimilation in short-range forecast applications over the Indian region

The present study is conducted to verify the short-range forecasts from mesoscale model version5 (MM5)/weather research and forecasting (WRF) model over the Indian region and to examine the impact of assimilation of quick scatterometer (QSCAT) near surface winds, spectral sensor microwave imager (SSM/I) wind speed and total precipitable water (TPW) on the forecasts by these models using their three-dimensional variational (3D-Var) data assimilation scheme for a 1-month period during July 2006. The control (without satellite data assimilation) as well as 3D-Var sensitivity experiments (with assimilating satellite data) using MM5/WRF were made for 48 h starting daily at 0000 UTC July 2006. The control run is analyzed for the intercomparison of MM5/WRF short-range forecasts and is also used as a baseline for assessing the MM5/WRF 3D-Var satellite data sensitivity experiments. As compared to the observation, the MM5 (WRF) control simulations strengthened (weakened) the cross equatorial flow over southern Arabian sea near peninsular India. The forecasts from MM5 and WRF showed a warm and moist bias at lower and upper levels with a cold bias at the middle level, which shows that the convective schemes of these models may be too active during the simulation. The forecast errors in predicted wind, temperature and humidity at different levels are lesser in WRF as compared to MM5, except the temperature prediction at lower level. The rainfall pattern and prediction skill from day 1 and day 2 forecasts by WRF is superior to MM5. The spatial distribution of forecast impact for wind, temperature, and humidity from 1-month assimilation experiments during July 2006 demonstrated that on average, for 24 and 48-h forecasts, the satellite data improved the MM5/WRF initial condition, so that model errors in predicted meteorological fields got reduced. Among the experiments, MM5/WRF wind speed prediction is most benefited from QSCAT surface wind and SSM/I TPW assimilation while temperature and humidity prediction is mostly improved due to latter. The largest improvement in MM5/WRF rainfall prediction is due to the assimilation of SSM/I TPW. The assimilation of SSM/I wind speed alone in MM5/WRF degraded the humidity and rainfall prediction. In summary the assimilation of satellite data showed similar impact on MM5/WRF prediction; largest improvement due to SSM/I TPW and degradation due to SSM/I wind speed.     

ASCAT近岸风场产品与近岸浮标观测风场对比

利用美国西海岸7个近岸浮标2012年全年和中国近岸8个气象浮标2012年1—6月的风场观测数据,检验了卫星散射计ASCAT近岸风场产品中的风速和风向在近岸海域的精度。检验结果表明:在美国西海岸近岸海域,ASCAT近岸风场产品中的风速与浮标的风速一致性高,但ASCAT近岸风场产品中风向的精度受离岸距离、风速和风向等因素的影响,在离岸近的海域ASCAT近岸风场产品与浮标观测风场的一致性较差。统计发现,将低风速 (不超过3 m·s-1) 剔除可明显提高ASCAT近岸风场产品在近岸海域的精度。另外,ASCAT近岸风场产品的风向精度在不同风向上存在差异,表现为从陆地吹向海洋风向精度较小,而从海洋吹向陆地风向精度较高。在中国近岸海域,受地形影响,渤海海域ASCAT近岸风场产品与气象浮标观测的风向差异大,在其他近岸海域的ASCAT近岸风场产品和气象浮标的观测风场的对比结果与美国西海岸风场的对比结果特征相似。     

Intercomparison of Oceansat-2 and ASCAT Winds with In Situ Buoy Observations and Short-Term Numerical Forecasts

Sea surface winds from the Oceansat-2 scatterometer (OSCAT) are important inputs to Numerical Weather Prediction (NWP) models. The Indian Space Research Organization (ISRO) recently updated the OSCAT retrieval algorithm in order to generate better products. An attempt has been made in this study to evaluate the updated OSCAT winds using buoy observations and the 6-hour short-term forecasts from the T574L64 model from the National Centre for Medium Range Weather Forecasting (NCMRWF) during the 2011 monsoon. The results of the OSCAT evaluation are also compared with those from the Advanced Scatterometer (ASCAT) on-board the Meteorological Operational Satellite-A (MetOp-A) which were evaluated in the same way. The root mean square differences (RMSDs) for wind speed and direction, are within 2?m?s^?1 and 20° for both scatterometers. The RMSDs for OSCAT are slightly higher than those for ASCAT, and this difference may be attributed in part to the difference in frequency and resolution of the scatterometer payloads. The bias and standard deviation for ASCAT winds are also lower than those for OSCAT winds with respect to the model short-range forecast, and this can be attributed to the regular assimilation of ASCAT winds in the model.     

Impact of assimilation of conventional and satellite meteorological observations on the numerical simulation of a Bay of Bengal Tropical Cyclone of November 2008 near Tamilnadu using WRF model

The objective of this study is to examine the impact of assimilation of conventional and satellite data on the prediction of a severe cyclonic storm that formed in the Bay of Bengal during November 2008 with the four-dimensional data assimilation (FDDA) technique. The Weather Research and Forecasting (WRF ARW) model was used to study the structure, evolution, and intensification of the storm. Five sets of numerical simulations were performed using the WRF. In the first one, called Control run, the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) was used for the initial and boundary conditions. In the remaining experiments available observations were used to obtain an improved analysis and FDDA grid nudging was performed for a pre-forecast period of 24 h. The second simulation (FDDAALL) was performed with all the data of the Quick Scatterometer (QSCAT), Special Sensor Microwave Imager (SSM/I) winds, conventional surface, and upper air meteorological observations. QSCAT wind alone was used in the third simulation (FDDAQSCAT), the SSM/I wind alone in the fourth (FDDASSMI) and the conventional observations alone in the fifth (FDDAAWS). The FDDAALL with assimilation of all observations, produced sea level pressure pattern closely agreeing with the analysis. Examination of various parameters indicated that the Control run over predicted the intensity of the storm with large error in its track and landfall position. The assimilation experiment with QSCAT winds performed marginally better than the one with SSM/I winds due to better representation of surface wind vectors. The FDDAALL outperformed all the simulations for the intensity, movement, and rainfall associated with the storm. Results suggest that the combination of land-based surface, upper air observations along with satellite winds for assimilation produced better prediction than the assimilation with individual data sets.     

星载双频风场雷达热带气旋降雨区测风模拟

基于大气辐射传输理论分别建立Ku波段和C波段的降雨模型,模拟热带气旋降雨区洋面的雷达回波并反演了洋面10 m风场,用于研究降雨对测风的影响以及风云三号双频风场雷达 (WFR) 的测风能力。分析表明:回波的衰减或增强取决于降雨衰减项和后向散射项的相对大小;热带气旋的降雨使反演风速偏小,风向精度降低,Ku波段相对于C波段更易受影响,在高风速 (超过30 m·s-1) 条件下,可达5~20 m·s-1的负风速偏差。反演结果表明:双频反演的新方法能够结合Ku波段与C波段的优势,双频最大似然估计 (MLE) 方法在分辨率上优于C波段单频反演,相对Ku单频反演能降低降雨对测风的衰减作用,结合双频MLE方法和C波段单频反演优势的分区反演方法可以显著减小降雨偏差,提高风速反演精度,在有风云三号湿度计同步观测的条件下,是提高热带气旋降雨区测风精度的有效手段。     

Comments on the Synergism Between the Analytic Planetary Boundary-Layer Model and Remote Sensing Data

This paper is adapted from a presentation at the session of the European Geophysical Society meeting in 2002 honouring Joost Businger. It documents the interaction of the non-linear planetary boundary-layer (PBL) model (UW-PBL) and satellite remote sensing of marine surface winds from verification and calibration studies for the sensor model function to the current state of verification of the model by satellite data. It is also a personal history where Joost Businger had seminal input to this research at several critical junctures. The first scatterometer in space was on SeaSat in 1978, while currently in orbit there are the QuikSCAT and ERS-2 scatterometers and the WindSat radiometer. The volume and detail of data from the scatterometers during the past decade are unprecedented, though the value of these data depends on a careful interpretation of the PBL dynamics. The model functions (algorithms) that relate surface wind to sensor signal have evolved from straight empirical correlation with simple surface-layer 10-m winds to satellite sensor model functions for surface pressure fields. A surface stress model function is also available. The validation data for the satellite model functions depended crucially on the PBL solution. The non-linear solution for the flow of fluid in the boundary layer of a rotating coordinate system was completed in 1969. The implications for traditional ways of measuring and modelling the PBL were huge and continue to this day. Unfortunately, this solution replaced an elegant one by Ekman with a stability/finite perturbation equilibrium solution. Consequently, there has been great reluctance to accept this solution. The verification of model predictions has been obtained from the satellite data.     

Use of Microwave Radiances from Metop-C and Fengyun-3 C/DSatellites for a Northern European Limited-areaData Assimilation System

正1Swedish Meteorological and Hydrological Institute, Folkborgsv?gen 17, 60361 Norrk?ping, Sweden2Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway     

面向资料同化的风廓线雷达风场特征分析及其质控方法

以美国国家环境预报中心全球预报系统（National Centers for Environmental Prediction/Global Forecast System,NCEP/GFS）0.5°×0.5°分析场作为数值预报背景场,结合地面降水资料,面向资料同化分析了2017年1～12月逐日00时、06时、12时、18时（协调世界时）福建12部L波段风廓线雷达（其中CFL-03系列3部、CFL-06系列9部）水平风产品质量特征,并初步探讨了不同质量控制方案的影响差异。结果表明:（1）CFL-06系列雷达在水平风的最大探测高度、有效数据获取率和低层水平风质量等方面明显优于CFL-03系列;（2）相同系列的不同风廓线雷达探测水平风的数据获取率、有效探测高度、标准差、相关系数及偏差的垂直分布特征等存在极大差异,该差异与风廓线雷达所处的地理位置（沿海或内陆）、海拔高度等并无直接关系;（3）各雷达站探测u风速相对背景场存在明显系统性负偏差,小于背景场,不满足资料同化对背景场的无偏需求,资料同化时需进行偏差订正;v风则相对较好;（4）降水对风廓线雷达探测影响较大,有降水时数据获取率在中低层有所减小,但在中高层则大幅提高;u、v风标准差在中低层有所增加,而在中高层v风标准差有所增加,u风标准差则大幅降低;（5）针对不同风廓线雷达,提出了不同高可信度区间和不同有效探测高度两种质量控制方案,并与固定有效探测高度方案进行了对比,结果表明,这两种质量控制方案皆具有明显优势。不同高可信度区间方案的质量控制效果更为显著,不同雷达站水平测风数据得到更加充分和有效识别,既减少了雷达资料不必要损失,又可将质量差的数据进一步剔除;该方案在有降水情形下也有较好效果。     

Evaluation of wind fields for storm events in the black sea region using a numerical regional atmospheric circulation model

A method of the NCEP/NCAR reanalysis wind data recalculation using a regional atmospheric circulation model is described. A comparison of model results and satellite measurements is performed. The results of wind wave computation using the reanalysis and model winds are presented and their comparison is made. It is shown that the NCEP/NCAR reanalysis wind recalculation using a regional atmospheric circulation model removes the underestimation in the reanalysis winds, provides a better representation of the wind regime, and, consequently, gives a possibility to create the reanalysis of wind regime in the Black Sea region to be used in climate estimates.     

双雷达风场反演拼图在登陆台风“莫兰蒂”(1614)强降水精细预报中的同化应用试验

利用福建龙岩、漳州、泉州新一代多普勒天气雷达和厦门海沧双偏振雷达探测资料,采用动态地球坐标系下双雷达三维风场反演与拼图技术,基于天气研究和预报模式（Weather Research and Forecasting,WRF）及其资料同化系统,对登陆台风“莫兰蒂”（1614）引起的2016年9月14—15日福建强降水过程进行了双雷达风场反演拼图资料检验及其三维变分同化对强降水精细预报影响的数值试验,结果发现:（1）动态地球坐标系下双雷达反演风场能合理反映实际风场分布状况,其误差相对较小。相较厦门翔安风廓线雷达及厦门探空秒级测风数据,反演风风向（风速）平均绝对误差分别为7.8°（2.6 m/s）及3.4°（1.1 m/s）;（2）反演风场水平方向稀疏化对同化及预报结果极为重要,过密的反演风场资料会给同化及预报结果带来负效果。文中采用18、6、2 km 3重嵌套,在3重嵌套区域均进行同化以及仅在2 km区域进行同化两种情况下,均表现为当反演风场资料水平分辨率提高到0.1°时,同化分析及预报的台风环流开始受到负影响;且当反演风场资料水平分辨率越高时,负效果越明显。敏感性试验结果显示,分辨率取0.2°时数值预报效果最好;（3）以美国国家环境预报中心全球预报系统（National Centers for Environmental Prediction/Global Forecast System,NCEP/GFS）0.5°×0.5°分析场为初值,基于3个不同起报时刻（2016年9月14日14时、20时及15日02时）（北京时,下同）模拟的福建省境内台风内核雨带和螺旋雨带逐时演变、台风路径与强度、逐时降水TS评分和空间相关差异显著,其中14日14时起报试验效果最好;而14日20时起报试验效果最差,这与该试验初始台风大风轴风速明显偏大有关;（4）在上述3个不同起报时刻试验基础上,分别增加双雷达反演风场资料的三维变分同化后,福建境内地面风场和台风内核雨带、螺旋雨带逐时分布、逐时降水TS评分和空间相关、台风环流结构以及U、V风垂直廓线分布均有明显改善,最大正影响时效可达24 h;但仅对1—6 h时效内台风路径有改善。      

逐时云迹风资料同化对暴雨预报的模拟试验

文中基于不同的云迹风同化方案,用GRAPES模式对2005年7月11-12日长江中下游一次暴雨强降水过程进行了云迹风资料同化试验及数值模拟,通过对比分析不同方案所得的分析场及预报场的差异,研究逐时云迹风资料三维变分同化对分析场及暴雨预报的影响.首先,根据连续性原理及双通道各层次云迹风资料的误差分析,分3个步骤对7月11日00:00-12:00 UTC共12个时次的双通道云迹风资料进行了初步的质量控制;然后,把经过质量控制的云迹风资料放入基于GRAPES 3D-VAR三维变分同化方案开发的逐小时循环同化系统中进行同化,将得出的分析场与单一时次未经质量控制的云迹风资料同化得出的分析场进行对比,探讨了逐时云迹风资料同化对数值预报分析场的影响;最后,把同化后的分析场作为初始场,用 GRAPES模式对 2005年7月11-12日长江流域暴雨过程做24 h降水预报试验,分析两个同化方案所模拟得到的预报场的差异.结果表明,经资料的筛选、同经纬度单点通道的选择及资料的稀疏化3个步骤控制后,各层次云迹风资料的误差有明显减小;加入经质量控制的逐时云迹风资料其三维变分同化可以提高分析场中风压场及水汽场的质量;而且在暴雨预报试验中可以相对更准确地预报暴雨落区及雨强.     

THE ANALYSIS ON THE STATISTICAL CHARACTER OF QUIKSCAT SCATTEROMETER WINDS AND STRONG WIND FREQUENCY USING REMOTE SENSOR DATA FROM QUIKSCAT

1 INTRODUCTION Most of the conventional sea surface wind data are measurements from ships, buoys and islands, with coverage and spatial resolution far below the requirements of research and application. At present, due to limited understanding of physical processes and efficient exploitation of data, numerical prediction models have not been used as they should be, although routine procedures are able to give sea surface wind fields at the intervals of 6 hours. With the development of sp…     

QuikSCAT散射计矢量风统计特征及南海大风遥感分析

主要分析了QuikSCAT散射计矢量风资料的统计特征,并利用该资料分析了南海大风频数的月变化、空间分布特征以及南海各月风场的空间分布特征.结果显示QuikSCAT矢量风在南海具有可信性;利用散射计风场资料分析发现在南海主要盛行两种风,即冬季东北风和夏季西南风,东北风最大中心在巴士海峡、台湾海峡;南海中南部存在东北季风的次大中心和西南季风的极大中心.     

中尺度区域模式层顶高度对高空风场数值模拟的影响分析

本文基于中尺度区域模式WRF,开展模式层顶高度变化对高空气象要素,特别是高空风场数值模拟影响的研究。通过设计模式顶高45、5 hPa两个试验,同化来源于NOAA-15、NOAA-18、NOAA-19和METOP-2的AMSU-A辐射计高通道数据,表明提高模式层顶能够使卫星更多的高通道样本数量进入同化系统,达到减小背景场误差,同时减小高于层顶通道辐射能量对低层通道影响的目的,一定程度上改进了同化效果,从而改善高空气象要素,特别是风场的模拟效果,与观测值的均方根误差减小了约0.4~0.5 m·s^-1。     

FY-2C云迹风资料同化应用对台风预报的影响试验研究

针对0505号台风“海棠”, 采用WRF区域中尺度模式进行控制试验和两个同化试验, 利用WRF-3DVAR同化系统同化FY-2C红外和水汽两个通道云迹风反演产品, 同化分云迹风经质量控制和未经质量控制两组同化试验。通过三组试验分析云迹风资料对降水和风场等的预报结果的影响, 并进行24小时降水量分级Ts评分检验以及风场点对点检验。结果表明: 同化经质量控制云迹风资料可以提高降水落区和强度预报的准确度, 不同等级的Ts评分较其它试验都有较明显改进; 风场预报模拟也有所改善。增加两例台风, 使用与“海棠” 相似的处理方法进行模拟试验, 并对模拟结果24小时降水分析与检验, 得到与“海棠”类似结论。因此, 经过合理性选择的云迹风资料的加入, 有利于补充初始场中可能未包含的中尺度信息, 从而提高试验中对于降水、风场等的模拟效果, 提高WRF模式的模拟预报能力。     

卫星资料循环同化应用对区域数值预报效果影响分析

为提高卫星资料在同化系统中的利用率及验证卫星微波资料对区域数值预报效果的影响,本文以2008年8月1-31日为研究时段,利用WRF模式及其WRF-3DVAR同化模块,设计并构建了卫星微波资料的快速循环同化方案,分析循环同化方案对数值预报的改进效果.结果表明,相比于单时次同化,循环同化方案使各预报要素的相关系数在一定程度上得到改善,均方差也呈现减小的趋势.此外,对研究时段内暴雨和台风个例的具体分析显示,循环同化方案能够有效改善降水和台风路径的预报.