不同资料同化对登陆台风菲特(2013)短时预报的影响研究

为定量评估地面、探空、飞机报、卫星辐射亮温、雷达反射率及径向风等不同观测资料同化对台风预报性能的影响,本文以2013年严重影响我国的登陆台风菲特为例,利用WRF模式与GSI-3DVAR同化系统开展观测系统试验(OSE)研究,探讨了不同类型资料同化对"菲特"(2013)路径、强度、形势场和降水短时预报的相对贡献及可能影响机理。结果表明:(1)不同类型资料同化对模拟结果贡献程度有明显差别,其中探空、雷达反射率和飞机报对模拟结果有较大影响,分别"拒绝"这三种资料后模式模拟的高空各要素均方根误差分别上升约54.8%~62.0%、9.2%~16.5%和6.1%~6.4%。(2)对于不同的台风预报效果评估参数,各类资料的贡献率大小排序不同。对高空场和台风路径模拟影响较大的是探空和飞机报,对台风强度模拟影响较大的依次是雷达径向风、反射率、探空和飞机报,而对降水模拟影响较大的依次是雷达反射率、探空和飞机报。(3)各类资料对降水模拟的贡献率随时间变化不同。雷达反射率资料对降水的贡献随着模式积分时间明显下降,而飞机报、探空资料等对降水的贡献在模式积分3 h之后开始出现。(4)资料同化对降水模拟的改进与其对台风路径、水物质及强度模拟改进有关,因此影响高空场、台风路径和强度较大的雷达反射率、探空和飞机报资料,也是对降水模拟贡献较大的资料。     

Ten Years of Science Based on the Canadian Precipitation Analysis: A CaPA System Overview and Literature Review†

Near real-time quantitative precipitation estimates are required for many applications including weather forecasting, flood forecasting, crop management, forest fire prevention, hydropower production, and dam safety. Since April 2011, such a product has been available from Environment and Climate Change Canada for a domain covering all North America. This product, known as the Regional Deterministic Precipitation Analysis, is generated using the Canadian Precipitation Analysis (CaPA) system. Although it was designed for near real-time use, an archive of pre-operational and operational products going back to 2002 is now available and has been used in numerous studies. This paper presents a review of the various scientific publications that have reported either using or evaluating CaPA products. We find that the product is used with success both for scientific studies and operational applications and compares well with other precipitation datasets. We summarize the strengths and weaknesses of the system as reported in the literature. We also provide users with information on how the system works, how it has changed over time, and how the archived and near real-time analyses can be accessed and used. We finally briefly report on recent and upcoming improvements to the product based, in part, on the results of this literature review.     

Estimating the Correlated Observation-Error Characteristics of the Chinese FengYun Microwave Temperature Sounder and Microwave Humidity Sounder

In operational data assimilation systems, observation-error covariance matrices are commonly assumed to be diagonal.However, inter-channel and spatial observation-error correlations are inevitable for satellite radiances. The observation errors of the Microwave Temperature Sounder(MWTS) and Microwave Humidity Sounder(MWHS) onboard the FengYun-3A(FY-3A) and FY-3B satellites are empirically assigned and considered to be uncorrelated when they are assimilated into the WRF model's Community Variational Data Assimilation System(WRFDA). To assimilate MWTS and MWHS measurements optimally, a good characterization of their observation errors is necessary. In this study, background and analysis residuals were used to diagnose the correlated observation-error characteristics of the MWTS and MWHS. It was found that the error standard deviations of the MWTS and MWHS were less than the values used in the WRFDA. MWTS had small inter-channel errors, while MWHS had significant inter-channel errors. The horizontal correlation length scales of MWTS and MWHS were about 120 and 60 km, respectively. A comparison between the diagnosis for instruments onboard the two satellites showed that the observation-error characteristics of the MWTS or MWHS were different when they were onboard different satellites. In addition, it was found that the error statistics were dependent on latitude and scan positions.The forecast experiments showed that using a modified thinning scheme based on diagnosed statistics can improve forecast accuracy.     

Assimilation of Feng-Yun-3B Satellite Microwave Humidity Sounder Data over Land

The ECMWF has been assimilating Feng-Yun-3B(FY-3B) satellite microwave humidity sounder(MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz(vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS(Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.     

A Prototype Regional GSI-based EnKF-Variational Hybrid Data Assimilation System for the Rapid Refresh Forecasting System:Dual-Resolution Implementation and Testing Results

A dual-resolution(DR) version of a regional ensemble Kalman filter(EnKF)-3D ensemble variational(3DEnVar) coupled hybrid data assimilation system is implemented as a prototype for the operational Rapid Refresh forecasting system. The DR 3DEnVar system combines a high-resolution(HR) deterministic background forecast with lower-resolution(LR) EnKF ensemble perturbations used for flow-dependent background error covariance to produce a HR analysis. The computational cost is substantially reduced by running the ensemble forecasts and EnKF analyses at LR. The DR 3DEnVar system is tested with 3-h cycles over a 9-day period using a 40/13-km grid spacing combination. The HR forecasts from the DR hybrid analyses are compared with forecasts launched from HR Gridpoint Statistical Interpolation(GSI) 3D variational(3DVar)analyses, and single LR hybrid analyses interpolated to the HR grid. With the DR 3DEnVar system, a 90% weight for the ensemble covariance yields the lowest forecast errors and the DR hybrid system clearly outperforms the HR GSI 3DVar.Humidity and wind forecasts are also better than those launched from interpolated LR hybrid analyses, but the temperature forecasts are slightly worse. The humidity forecasts are improved most. For precipitation forecasts, the DR 3DEnVar always outperforms HR GSI 3DVar. It also outperforms the LR 3DEnVar, except for the initial forecast period and lower thresholds.     

一次局地大暴雨的地面观测资料同化预报试验研究

基于WRF（Weather Research and Forecasting）模式及其3DVAR（3-Dimentional Variational）资料同化系统,采用36 km、12 km 、4 km三层嵌套网格进行逐3 h资料同化和快速更新循环预报,对2011年5月8日鲁中一次局地大暴雨过程进行了资料同化敏感性试验。试验结果表明,地面观测资料同化和快速更新循环对本次降水的预报起到了关键性作用。在快速更新循环预报时不同化地面观测资料,或同化全部观测资料进行冷启动预报,模式均不能预报出山东的降水。同化地面观测资料后,显著改进了模式降水落区预报。地面观测资料同化可以影响到700 hPa高度以上温压湿风要素的变化,从而改变了大气初始场的温湿结构,导致模式预报的700 hPa附近高空大气湿度和热力不稳定增强,700 hPa以下低层风场更强,850 hPa鲁中以南风速较无观测资料同化的偏强2～4 m·s-1,低层风场的动力作用触发高空的不稳定大气,降水出现在山东。     

EXPERIMENTAL APPLICATION OF A THINNING SCHEME FOR THE ASSIMILATION OF SURFACE OBSERVATION DATA IN GRAPES-3DVAR

To reduce the spatial correlation of representation error in observations and computational complexity, we propose a thinning scheme that can extract typical observations within a certain range. This scheme is applied to the Global/Regional Assimilation and Prediction System (GRAPES) with three-dimensional variation (3DVAR) to study the effect of the thinning radius on the assimilation results. The assimilation experiments indicate that when the ratio of the model resolution to the observational resolution is 1:3, the simulated results for precipitation are relatively good and have a relatively high equitable threat score (ETS). Moreover, the analysis errors in the temperature and the specific humidity are the smallest, the dependence of the norm gradient vector of the objective function on the number of iterations is slow, gentle, and close to 0, and the minimization results in improved conditions.     

基于卫星资料梯度信息的新型变分同化方法对于台风数值模拟的研究

卫星资料凭着卫星遥感的全球性、连续性和高频次观测等优势,成为一种重要的非常规资料源,但卫星观测仍然存在各种各样的观测误差,其中包含由于观测偶然性所造成的统计学上的随机误差及仪器本身和辐射传输模式等造成的系统性偏差,这些误差在很大程度上影响了卫星资料的质量。文中提出了一种能有效订正卫星观测资料系统性偏差的梯度信息同化算法,该方法用一个梯度算子进行模式变量与观测变量的梯度变换,从而达到订正系统性偏差的目的。本文利用WRF（Weather Research Forecast）模式及其同化模式WRFDA（WRF Data Assimilation system）,以及AIRS（Atmospheric Infrared Sounder）资料,对台风“圆规”进行了实际的数值模拟和同化试验,数值结果表明,梯度信息同化方法能明显改善台风路径的模拟,在处理可信度较低的资料时仍然适用。另外,通过同化诊断分析,发现卫星资料的系统性偏差对于台风数值模拟有较大影响,而文中提出的梯度信息同化方法能较好的解决此类问题。     

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。     

EnSRF雷达资料同化对一次强对流天气模拟的影响研究

利用ARPS(Advanced Regional Prediction System)模式和具有流依赖背景误差协方差的集合均方根滤波(Ensemble Square Root Filter,简称En SRF)方法,通过同化多部多普勒雷达资料,对2013年6月23日的强对流天气过程进行了研究。首先对比同化试验和观测的组合反射率因子,检验了同化效果。通过计算均方根误差和离散度,进一步定量评估了同化结果。再对比模式变量,综合分析了En SRF雷达资料同化对模式热力、动力、湿度和微物理量等变量的影响。最后对集合平均场进行1 km的高分辨率数值模拟。结果表明:En SRF能够同化出与观测类似的对流系统,且减弱了南北部的虚假回波。径向风和反射率因子的均方根误差明显减少。En SRF雷达同化能够明显优化模式的初始场,同化试验的回波在垂直方向上范围增加,强度偏弱。在强对流区域,低层的冷池温度最多降低6 K,相对湿度最多增加30%。对流区域的雨水、冰晶和雪的混合比均有明显增加。模拟发现同化试验能够较好地模拟出对流系统的结构和位置。