雷达降水资料一维变分同化研究——湿度廓线调整

采用η坐标中尺度有限区域模式进行了数字化天气雷达探测降水资料的一维变分(1DVAR)同化试验,结果表明充分利用高时空分辨率的雷达降水资料所包含的丰富的中尺度信息,调整湿度廓线,从而改善模式初始湿度场,能有效提高模式暴雨预报能力。“98·7”鄂东沿江特大暴雨的数值试验结果表明,应用1DVAR方法同化1h雷达降水资料调整模式湿度廓线后,极大地缩小了分析降水与观测降水间的差距,而且24h预报能模拟出与实际降水发生区域相对应的位于鄂东的大暴雨区,而变分前模式预报效果不佳。进一步的分析表明,应用雷达降水资料对短时预报(0～12h)的改进更为显著,而对12h之后降水预报的改善则不明显。     

用一种新的同化方法同化降水量资料

Observations of accumulated precipitation are extremely valuable for effectively improving rainfall analysis and forecast. It is, however, difficult to use such observations directly through sequential assimilation methods, such as three-dimensional variational data assimilation or an Ensemble Kalman Filter. In this study, the authors illustrate a new approach that makes effective use of precipitation data to improve rainfall forecast. The new method directly obtains an optimal solution in a reduced space by fitting observations with historical time series generated by the model; it also avoids the implementation of tangent linear model and its adjoint. A lot of historical samples are produced as the ensemble of precipitation observations with the fully nonlinear forecast model. The results show that the new approach is capable of extracting information from precipitation observations to improve the analysis and forecast. This method provides comparable performance with the standard four- dimensional variational data assimilation at a much lower computational cost.     

同化风廓线雷达资料对浙江降水预报改进评估

采用中尺度模式WRF和美国俄克拉荷马大学风暴分析预测中心的资料同化系统开展中国东部地区35部风廓线雷达资料同化试验研究,在同化1 h平均采样产品前,对其进行气候极值检查、一致性检查、垂直稀疏化等质量控制,选取2014年5月16-17日暴雨过程评估同化风廓线雷达资料对降水预报的影响,探讨其对初始场改进作用,之后,通过批量试验再次确认同化风廓线雷达资料可有效提高降水预报能力。个例同化试验对比分析表明:同化风廓线雷达资料后,暴雨区及其上游地区850 hPa的风速增强20%~30%,水汽通量增加30%~50%,大气层结不稳定性增强,小雨和大雨TS评分分别提高0.06和0.07,暴雨漏报率和空报率分别降低0.04和0.05,降水预报得到改进。     

散射计风场的三维变分对海雾数值模拟的影响

为了评估同化QuikSCAT海面风场资料对海雾模拟的影响,对发生在2006年4月3—5日的海雾过程,首先通过3个敏感性试验,研究了不同边界层参数化方案对海雾模拟的影响,发现YSU边界层参数化方案更适合海雾过程的模拟。然后对2006年4月3—5日平流雾过程和2005年6月23—24日辐射雾过程利用WRF-3DVAR系统将QuikSCAT海面风场资料同化到模式中,并以未同化和同化了QuikSCAT海面风场资料的数据为初始场,应用WRF模式进行模拟预报,同时对模拟预报得到的结果与实况 (卫星云图和地面观测) 进行对比,结果表明:QuikSCAT海面风场资料的三维变分同化能够改善低层其他要素场,对海雾预报有明显的正效应,但对高层的影响相对有限。     

The Effects of Assimilating Satellite Brightness Temperature and Bogus Data on the Simulation of Typhoon Kalmaegi (2008)

Observational and bogus satellite data are directly assimilated into the Weather Research and Forecasting (WRF) model in simulations of Typhoon Kalmaegi (2008). The data assimilation is performed using the Radiative Transfer for TIROS-N Operational Vertical Sounder (RTTOV) model and the three-dimensional variational data assimilation (3DVAR) technique, with satellite observations taken from the National Oceanic and Atmospheric Administration-16 (NOAA-16) Advanced TIROS Vertical Sounder (ATOVS) system composed of the High-resolution Infrared Radiation Sounder (HIRS), the Advanced Microwave Sounding Unit-A (AMSU-A), and the Advanced Microwave Sounding Unit-B (AMSU-B). Data assimilation experiments are initialized at three different times. Improvements in the numerical simulation of the typhoon are discussed in the context of wind, temperature, pressure, and geopotential fields. The results indicate that assimilation of satellite data can improve both the representation of the initial conditions and the subsequent simulation of the typhoon. Different satellite data have different impacts on the typhoon track. In these simulations, data from AMSU-A play a greater role in improving the simulation of the typhoon than data from AMSU-B or HIRS. Assimilation of satellite data significantly affects the simulation of the subtropical high and the steering of the typhoon by the environmental flow. The subtropical high is enhanced and extends westward in the data assimilation experiments. The background flow therefore steers the typhoon more westward, improving the simulated typhoon track. Although direct assimilation of satellite brightness temperature improves the simulated environmental conditions, it does not significantly improve the simulated intensity of the typhoon. By contrast, initializing the typhoon simulation using bogus data in tandem with satellite data improves not only the environmental conditions but also the simulated inner-core structure of the typhoon. Assimilation of both types of data therefore improves the simulation of both the typhoon track and the typhoon intensity. The results of these experiments offer new insight into improving numerical simulations of typhoons.     

晨昏轨道微波温度计资料同化对降水定量预报的影响及其对三轨卫星系统的意义

极轨卫星的高级微波温度计(Advanced Microwave Sounding Unit-A,简称AMSU-A)辐射资料对提高降水定量预报的水平有重要作用.但是极轨卫星的轨道特征导致乘载其上的微波温度计资料在区域同化系统中存在严重缺测.本研究重点分析了晨昏轨道卫星上微波温度计资料同化对墨西哥湾沿岸定量降水预报的重要影响.研究选取了早晨星NOAA-15、上午星MetOp-A和下午星NOAA-18,利用美国NCEP(National Centers for Environmental Prediction)的业务同化系GSI(Gridpoint Statistical Interpolation)资料同化系统,进行了加和不加NOAA-15 AMSU-A资料的两组资料同化和预报试验,来阐明晨昏轨道卫星上微波温度计资料同化对墨西哥湾沿岸降水预报的重要影响.试验结果分析表明如果仅同化NOAA-18和MetOp-A资料,在协调世界时00:00和12:00的同化时间,在墨西哥湾和美国西部大陆就是卫星观测资料缺测区,而早晨星NOAA-15资料正好可以填补这个资料空缺.模式预报也表明,同化NOAA-15的AMSU-A资料可以对墨西哥湾降水有持续的正影响.这一研究证明了保持有搭载着AMSU-A或者相似仪器的早晨星,对区域降水预报的重要性.由于目前NOAA-15是唯一的一颗正在运行的、已远超过其正常运行期的早晨星,通过技术手段维持NOAA-15的AMSU-A仪器更超长期运行也就特别重要.     

降水资料同化在GRAPES-MESO模式中应用试验研究

利用国家气象中心中尺度业务数值预报模式GRAPES-MESO v3.0,以2010年6月1～30日为例,开展地面降水率1DVAR(one-dimensional variational assimilation)同化方案在GRAPES-3DVAR(three-dimensional variational assimilation)同化系统中的应用试验研究(ASSI试验),并以未加降水资料同化的试验为对照试验(CNTL试验),以评估全国1h加密雨量资料在模式中同化应用的效果。结果表明:1)在相对湿度背景误差和降水率观测误差范围内,1DVAR同化方案能够对湿度廓线进行有意义的调整,使分析降水向观测降水靠近;ASSI试验对初始温、压、湿、风场的修正主要为正效果;2)对2010年6月17～21日江南、华南连续性降水过程进行了分析,整体而言ASSI试验对逐日及逐时降水强度的预报普遍强于CNTL试验,与实况更加接近;3)ASSI试验对2010年6月1～30日08时起报的0～24 h模式预报的小雨、中雨、大雨、暴雨、大暴雨各个降水量级TS评分及ETS评分相比CNTL试验均有较明显提高,预报偏差也更接近于1;4)ASSI试验较CNTL试验能更好地模拟雨带的分布、雨带演变特征和降水强度的变化;5)对降水所做的典型个例和统计检验分析从不同角度说明了地面降水资料1DVAR同化方案在GRAPES-3DVAR系统中的应用改善了GRAPES-MESO v3.0的降水模拟效果。     

Improvement in Background Error Covariances Using Ensemble Forecasts for Assimilation of High-Resolution Satellite Data

Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper distribution of satellite-observed information in variational data assimilation. In the NMC (National Meteorological Center) method, background error covariances are underestimated over data-sparse regions such as an ocean because of small differences between different forecast times. Thus, it is necessary to reconstruct and tune the background error covariances so as to maximize the usefulness of the satellite data for the initial state of limited-area models, especially over an ocean where there is a lack of conventional data. In this study, we attempted to estimate background error covariances so as to provide adequate error statistics for data-sparse regions by using ensemble forecasts of optimal perturbations using bred vectors. The background error covariances estimated by the ensemble method reduced the overestimation of error amplitude obtained by the NMC method. By employing an appropriate horizontal length scale to exclude spurious correlations, the ensemble method produced better results than the NMC method in the assimilation of retrieved satellite data. Because the ensemble method distributes observed information over a limited local area, it would be more useful in the analysis of high-resolution satellite data. Accordingly, the performance of forecast models can be improved over the area where the satellite data are assimilated.     

郁江南宁17场洪水之合成面雨量特征分析

对郁江南宁 17场洪水的合成面雨量分布特征作了较系统的分析 ,发现引发南宁洪水的主要天气系统及其配置、合成面雨量的流域值及“6 8.8”大洪水和“0 1.7”特大洪水的合成面雨量表征 ,对今后进一步做好重大洪水的气象服务具有十分积极的意义     

雷达径向风速同化对台风麦莎模拟的影响

本文应用WRF-3DVAR系统同化多普勒雷达径向风速资料,并利用WRF模式对台风麦莎（2005年8月6日00时至7日00时）进行数值模拟,以此检验多普勒雷达径向风速资料在改进模式初始场及提高台风路径和降水预报准确度等方面的应用效果及意义,探讨不同同化时间间隔对同化效果的影响。通过对比同化试验和控制试验发现：雷达径向风速资料能通过调整初始风场结构,改进对台风结构的模拟,从而提高模式对台风麦莎的路径、强度和降水的模拟能力;雷达资料信号在进入模式后有一定的时效性,在一定程度上缩小同化时间间隔有助于提高同化效果。     

不同同化方案在一次梅雨锋暴雨预报中的应用研究

基于ATOVS辐射率资料和GTS常规观测资料融合,通过不同化任何观测资料的控制试验、3DVAR同化试验和ETKF-3DVAR混合同化试验,对2013年7月4—5日一次梅雨锋暴雨天气过程进行模拟分析。结果表明:混合同化方案能够明显地提高暴雨预报准确率,且有效改善了风场、温度场和相对湿度场等各个气象要素的初始场结构,而这些气象要素对于暴雨的预报准确性具有重要作用。且混合同化方案对于中低层大气改进效果较为明显。在数值积分过程中,随着时间的推移,混合同化方案的优势逐渐减弱。     

Altimetric Data Assimilation by EnOI and 3DVAR in a Tropical Pacific Model: Impact on the Simulation of Variability

When altimetric data is assimilated,3DVAR and Ensemble Optimal Interpolation(EnOI) have different ways of projecting the surface information downward.In 3DVAR,it is achieved by minimizing a cost function relating the temperature,salinity,and sea level.In EnOI,however,the surface information is propagated to other variables via a stationary ensemble.In this study,the differences between the two methods were compared and their impacts on the simulated variability were evaluated in a tropical Pacific model.Sea level anomalies(SLA) from the TOPEX/Poseidon were assimilated using both methods on data from 1997 to 2001 in a coarse resolution model.Results show that the standard deviation of sea level was improved by both methods,but the EnOI was more effective in the central/eastern Pacific.Meanwhile,the SLA evolution was better reproduced with EnOI than with 3DVAR.Correlations of temperature with the reanalysis data increased with EnOI by 0.1-0.2 above 200 m.In the eastern Pacific below 200 m,the correlations also increased by 0.2.However,the correlations decreased with 3DVAR in many areas.Correlations with the independent TAO profiles were also compared at two locations.While the correlations increased by up to 0.2 at some depths with EnOI,3DVAR generally reduced the correlations by 0.1-0.3.Though both methods were able to reduce the model-data difference in climatological sense,3DVAR appears to have degraded the simulated variability,especially during El Nin o-Southern Oscillation events.For salinity,similar results were found from the correlations.This tendency should be considered in future SLA assimilations,though the comparisons may vary among different model implementations.     

The Impact of Assimilating FY-3C GNOS GPS Radio Occultation Observations on GRAPES Forecasts

In the present study, a gross quality control (QC) procedure is proposed for the Global Navigation Satellite System Occultation Sounder (GNOS) Global Positioning System radio occultation (GPS RO) refractivity data to remove abnormal data before they are assimilated. It consists of a climate extreme check removing data outside the range of the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) climate maxima and minima over approximately five years, and a vertical gradient check that rejects profiles containing super-refractions. These two QC steps were applied sequentially to identify outliers in GNOS GPS RO refractivity data during boreal winter 2013/2014. All of the abnormal refractivity profiles and the outliers at each level of the GNOS GPS RO observations were effectively removed by the proposed QC procedure. The post-QC GNOS GPS RO refractivity observations were then assimilated in the Global/ Regional Analysis and PrEdiction System (GRAPES) using the three-dimensional variational (3D-Var) system. The impacts of the GNOS refractivity observation on GRAPES analysis and forecasting were evaluated and analyzed using an observation system experiment run over one whole winter season of 2013 / 2014. The experiment results demonstrated a positive impact of GNOS GPS RO data on analysis and forecast quality. The root mean squared error of GRAPES analysis temperature was reduced by 1% in the Southern Hemisphere (SH) extratropics and in the tropics, and the anomaly correlation scores of the forecasted 500-hPa geopotential height over the SH increased significantly during days 1 to 5. Overall, the benefits of using GNOS GPS RO data are significant in the SH and tropics.     

太行山地形对“96.8”暴雨影响的数值试验研究

利用ＭＭ４模型,设计了４种模式地形方案,讨论了太行山地形对“９６．８”暴雨降水量的贡献;并利用垂直运动和水汽通量等物理量,探讨了太行山地形对本次暴雨过程增幅作用的机制。结果显示,太行山地形对本次暴雨过程的降水中心强度及位置有显著影响,具有６０％增幅作用。太行山地形对垂直运动及水汽辐合也都具有增幅作用。模式地形越真实,预报结果越好,地形越高,降水增幅作用越明显。     

西南涡加密资料同化对西南区域模式降水预报的影响

本文基于2017年西南涡加密观测试验的四川省11个观测站的探空资料,利用西南区域9km和3km分辨率数值天气预报模式系统,开展了数值预报同化试验。同化试验每日06和18UTC各进行一次,持续40天。西南区域9km分辨率数值预报系统(SWC-WARMS)的模拟结果表明,加密探空观测资料对四川高空观测起到了补充。同化后可以改善模式初始场,有助于提升24小时降水预报的ETS评分,对小雨到大雨量级的BIAS评分也有一定的改善。西南区域3km分辨率系统得益于分辨率的提升,相比SWC-WARMS减小了大暴雨空报面积。同化加密探空观测可以提升降水预报的ETS评分,但空报面积也有所增加。     

哈密地区7·1 1大降水天气分析

对哈密地区7·11大降水天气进行了分析,结果表明：大降水是由充足的水汽,高、低空各物理量场的合理配置及不稳定能量的释放共同作用的结果。     

Numerical Assessing Experiments on the Individual Component Impact of the Meteorological Observation Network on the ＂July 2000＂ Torrential Rain in Beijing

In an effort to assess the impact of the individual component of meteorological observations (ground-based GPS precipitable water vapor,automatic and conventional meteorological observations) on the torrential rain event in 4-5 July 2000 in Beijing (with the 24-h accumulated precipitation reaching 240 mm),24-h observation system experiments are conducted numerically by using the MM5/WRF 3DVAR system and the nonhydrostatic MM5 model.Results indicate that,because the non-conventional GPS observations are directly assimilated into the initial analyses by 3DVAR system,better initial fields and 24-h simulation for the severe precipitation event are achieved than those under the MM5/Litter_R objective analysis scheme. Further analysis also shows that the individual component of meteorological observation network plays their special positive role in the improvement of initial field analysis and forecasting skills.3DVAR scheme with or without radiosonde and pilot observation has the most significant influence on numerical simulation,and automatic and conventional surface meteorological observations rank second.After acquiring the supplement information from the other meteorological observations,the ground-based GPS precipitable water vapor data can more obviously reflect initial field assimilation and precipitation forecast.By incorporating the ground- based GPS precipitable water vapor data into the 3DVAR analyses at the initial time,the threat scores (TS) with thresholds of 1,5,10,and 20 mm are increased by 1%-8% for 6- and 24-h accumulated precipitation observations,respectively.This work gives one helpful example that assesses the impact of individual component of the existing meteorological observation network on the high influence weather event using 3DVAR numerical system.     

ATOVS资料同化方案对暴雨模拟效果的影响

本文利用WRF 模式及其3DVar 同化系统,以2009 年6 月29 日00 时到30 日00 时的湖北鹤峰暴雨为研究个例,对ATOVS 探测器的AMSU-A、AMSU-B 和HIRS 三类资料进行了不同的同化方案试验。结果表明:同化ATOVS 三类资料对暴雨模拟的影响不同,HIRS 资料对暴雨模拟效果改进最大,AMSU-B 次之,AMSU-A 最小。同时同化ATOVS 三类资料时,AMSU-A 资料起主要作用,其同化效果与同时同化ATOVS 三类资料相近,优化组合同化AMSU-B 和HIRS 资料的效果最好。同化ATOVS 不同资料对初始要素场的影响不同,AMSU-A 资料主要影响大气温度场,AMSU-B 资料对中高空要素场的影响较大,HIRS 资料对低空湿度场及风场的协同改变最有利于降水模拟的改善。同时ATOVS 资料的稀疏分辨率也是影响同化效果的一个因子,在模式分辨率不变时,同化资料稀疏分辨率可能存在最佳选择。     

资料同化对一次华南暴雨影响的数值试验研究

针对一次华南暴雨过程,采用WRF区域中尺度模式进行了控制试验和同化试验.利用WRF-3DVAR同化系统同化了常规探空和地面观测资料,分析了两种资料对初值场的影响,以及对降水和各物理量预报效果的影响.结果表明:同化能改进初始场,并可改进暴雨落区和强度预报;同化可提高WRF模式对风场、温度场、高度场以及水汽场的预报能力.但有一定的时效性;同时同化探空和地面资料,比仅同化探空资料对大气低层物理量的预报能力要提高较多.