共查询到20条相似文献，搜索用时 218 毫秒
1.
Satellite infrared(IR)sounder and imager measurements have become one of the main sources of data used by data assimilation systems to generate initial conditions for numerical weather prediction(NWP)models and atmospheric analysis/reanalysis.This paper reviews the development of satellite IR data assimilation in NWP in recent years,especially the assimilation of all-sky satellite IR observations.The major challenges and future directions are outlined and discussed. 相似文献
2.
The relationship between the radar reflectivity factor(Z) and the rainfall rate(R) is recalculated based on radar observations from 10 Doppler radars and hourly rainfall measurements at 6529 automatic weather stations over the Yangtze–Huaihe River basin. The data were collected by the National 973 Project from June to July 2013 for severe convective weather events. The Z–R relationship is combined with an empirical qr–R relationship to obtain a new Z–qr relationship, which is then used to correct the observational operator for radar reflectivity in the three-dimensional variational(3 DVar) data assimilation system of the Weather Research and Forecasting(WRF) model to improve the analysis and prediction of severe convective weather over the Yangtze–Huaihe River basin. The performance of the corrected reflectivity operator used in the WRF 3 DVar data assimilation system is tested with a heavy rain event that occurred over Jiangsu and Anhui provinces and the surrounding regions on 23 June 2013. It is noted that the observations for this event are not included in the calculation of the Z–R relationship. Three experiments are conducted with the WRF model and its 3 DVar system, including a control run without the assimilation of reflectivity data and two assimilation experiments with the original and corrected reflectivity operators. The experimental results show that the assimilation of radar reflectivity data has a positive impact on the rainfall forecast within a few hours with either the original or corrected reflectivity operators, but the corrected reflectivity operator achieves a better performance on the rainfall forecast than the original operator. The corrected reflectivity operator extends the effective time of radar data assimilation for the prediction of strong reflectivity. The physical variables analyzed with the corrected reflectivity operator present more reasonable mesoscale structures than those obtained with the original reflectivity operator. This suggests that the new statistical Z–R relationship is more suitable for predicting severe convective weather over the Yangtze–Huaihe River basin than the Z–R relationships currently in use. 相似文献
3.
Blacklist methods are used in the CMA Global Forecasting System (CMA-GFS) to improve the application of aircraft temperature data to numerical weather prediction in the Northern Hemisphere and the tropics. In this paper, the ERA5 re-analysis data are used to analyze aircraft temperature observation errors of each aircraft and a blacklist is established using pre-quality controls and threshold methods. The blacklist-filtered and blacklisted aircraft temperature data are then applied to the four-dimensional variational assimilation system, respectively, and an assimilation cycle forecast for the period from September 1 to 30, 2019 is carried out. The results show an uneven distribution in the global aircraft blacklist data. After the application of the blacklist methods, the RMSE of geopotential height and temperature analysis field decrease in the vertical direction by a maximum of ~ 1.5 gpm at 200 hPa and ~ 0.15 K at 250 hPa, respectively. Overall, the blacklist methods of aircraft temperature data improve the analysis and forecast in the CMA-GFS. 相似文献
4.
Aerosol optical depth(AOD) is the most basic parameter that describes the optical properties of atmospheric aerosols,and it can be used to indicate aerosol content. In this study, we assimilated AOD data from the Fengyun-3 A(FY-3 A) and MODIS meteorological satellite using the Gridpoint Statistical Interpolation three-dimensional variational data assimilation system. Experiments were conducted for a dust storm over East Asia in April 2011. Each 0600 UTC analysis initialized a24-h Weather Research and Forecasting with Chemistry model forecast. The results generally showed that the assimilation of satellite AOD observational data can significantly improve model aerosol mass prediction skills. The AOD distribution of the analysis field was closer to the observations of the satellite after assimilation of satellite AOD data. In addition, the analysis resulting from the experiment assimilating both FY-3 A/MERSI(Medium-resolution Spectral Imager) AOD data and MODIS AOD data had closer agreement with the ground-based values than the individual assimilation of the two datasets for the dust storm over East Asia. These results suggest that the Chinese FY-3 A satellite aerosol products can be effectively applied to numerical models and dust weather analysis. 相似文献
5.
To examine the effect of radar data assimilation and increasing horizontal resolution on the short-term numerical weather prediction, comparative numerical experiments are conducted for a Huabei (North China) torrential rainfall event by using the Advanced Regional Prediction System (ARPS) and ARPS Data Analysis System (ADAS). The experiments use five different horizontal grid spacings, i.e., 18, 15, 9, 6, and 3 km,respectively, under the two different types of analyses: one with radar data, the other without. Results show that, when radar data are not used in the analysis (i.e., only using the conventional observation data), increasing horizontal resolution can improve the short-term prediction of 6 h with better representation of the frontal structure and higher scores of the rainfall prediction, particularly for heavy rain situations. When radar data are assimilated, it significantly improves the rainfall prediction for the first 6 h, especially the locality and intensity of precipitation. Moreover, using radar data in the analysis is more effective in improving the short-term prediction than increasing horizontal resolution of the model alone, which is demonstrated by the fact that by using radar data in the analysis and a coarser resolution of the 18-km grid spacing, the predicted results are as good as that by using a higher resolution of the 3-km grid spacing without radar data. Further study of the results under the radar data assimilation with grid spacing of 18-3 km reveals that the rainfall prediction is more sensitive to the grid spacing in heavy rain situations (more than 40 mm) than in ordinary rain situations (less than 40 mm). When the horizontal grid spacing reduces from 6 to 3 km, there is no obvious improvement to the prediction results. This suggests that there is a limit to how far increasing horizontal resolution can do for the improvement of the prediction. Therefore, an effective approach to improve the short-term numerical prediction is to combine the radar data assimilation with an optimal horizontal resolution. 相似文献
6.
Use of data assimilation to initialize hydrometeors plays a vital role in numerical weather prediction(NWP).To directly analyze hydrometeors in data assimilation systems from cloud-sensitive observations,hydrometeor control variables are necessary.Common data assimilation systems theoretically require that the probability density functions(PDFs)of analysis,background,and observation errors should satisfy the Gaussian unbiased assumptions.In this study,a Gaussian transform method is proposed to transform hydrometeors to more Gaussian variables,which is modified from the Softmax function and renamed as Quasi-Softmax transform.The Quasi-Softmax transform method then is compared to the original hydrometeor mixing ratios and their logarithmic transform and Softmax transform.The spatial distribution,the non-Gaussian nature of the background errors,and the characteristics of the background errors of hydrometeors in each method are studied.Compared to the logarithmic and Softmax transform,the Quasi-Softmax method keeps the vertical distribution of the original hydrometeor mixing ratios to the greatest extent.The results of the D′Agostino test show that the hydrometeors transformed by the Quasi-Softmax method are more Gaussian when compared to the other methods.The Gaussian transform has been added to the control variable transform to estimate the background error covariances.Results show that the characteristics of the hydrometeor background errors are reasonable for the Quasi-Softmax method.The transformed hydrometeors using the Quasi-Softmax transform meet the Gaussian unbiased assumptions of the data assimilation system,and are promising control variables for data assimilation systems. 相似文献
7.
The radar ray path equations are used to determine the physical location of each radar measurement. These equations are necessary for mapping radar data to computational grids for diagnosis, display and numerical weather prediction (NWP). They are also used to determine the forward operators for assimilation of radar data into forecast models. In this paper, a stepwise ray tracing method is developed. The influence of the atmospheric refractive index on the ray path equations at different locations related to an intense cold front is examined against the ray path derived from the new tracing method. It is shown that the radar ray path is not very sensitive to sharp vertical gradients of refractive index caused by the strong temperature inversion and large moisture gradient in this case. In the paper, the errors caused by using the simplified straight ray path equations are also examined. It is found that there will be significant errors in the physical location of radar measurements if the earth’s curvature is not considered, especially at lower elevation angles. A reduced form of the equation for beam height calculation is derived using Taylor series expansion. It is computationally more efficient and also avoids the need to use double precision variables to mitigate the small difference between two large terms in the original form. The accuracy of this reduced form is found to be sufficient for modeling use. 相似文献
8.
A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assimilates observations in both the atmosphere and ocean. The assimilation of synoptic atmospheric variability that captures the temporal fluctuation of the weather noise was found to be critical for the estimation of not only the atmospheric, but also oceanic states. The synoptic atmosphere observation was especially important in the mid-latitude system, where oceanic variability is driven by weather noise. The assimilation of synoptic atmospheric variability in the coupled model improved the atmospheric variability in the analysis and the subsequent forecasts, reducing error in the surface forcing and, in turn, in the ocean state. Atmospheric observation was able to further improve the oceanic state estimation directly through the coupled covariance between the atmosphere and ocean states. Relative to the mid-latitude system, the tropical system was influenced more by ocean-atmosphere interaction and, thus, the assimilation of oceanic observation becomes more important for the estimation of the ocean and atmosphere. 相似文献
9.
Assimilating satellite radiances into Numerical Weather Prediction (NWP) models has become an important approach to increase the accuracy of numerical weather forecasting. In this study, the assimilation technique scheme was employed in NOAA’s STMAS (Space-Time Multiscale Analysis System) to assimilate AMSU-A radiances data. Channel selection sensitivity experiments were conducted on assimilated satellite data in the first place. Then, real case analysis of AMSU-A data assimilation was performed. The analysis results showed that, following assimilating of AMSU-A channels 5–11 in STMAS, the objective function quickly converged, and the channel vertical response was consistent with the AMSU-A weighting function distribution, which suggests that the channels can be used in the assimilation of satellite data in STMAS. With the case of the Typhoon Morakot in Taiwan Island in August 2009 as an example, experiments on assimilated and unassimilated AMSU-A radiances data were designed to analyze the impact of the assimilation of satellite data on STMAS. The results demonstrated that assimilation of AMSU-A data provided more accurate prediction of the precipitation region and intensity, and especially, it improved the 0–6h precipitation forecast significantly. 相似文献
10.
By sampling perturbed state vectors from each ensemble prediction run at properly selected time levels in the vicinity of the analysis time, the recently proposed time-expanded sampling approach can enlarge the ensemble size without increasing the number of prediction runs and, hence, can reduce the computational cost of an ensemble-based filter. In this study, this approach is tested for the first time with real radar data from a tornadic thunderstorm. In particular, four assimilation experiments were performed to test the time-expanded sampling method against the conventional ensemble sampling method used by ensemble- based filters. In these experiments, the ensemble square-root filter (EnSRF) was used with 45 ensemble members generated by the time-expanded sampling and conventional sampling from 15 and 45 prediction runs, respectively, and quality-controlled radar data were compressed into super-observations with properly reduced spatial resolutions to improve the EnSRF performances. The results show that the time-expanded sampling approach not only can reduce the computational cost but also can improve the accuracy of the analysis, especially when the ensemble size is severely limited due to computational constraints for real-radar data assimilation. These potential merits are consistent with those previously demonstrated by assimilation experiments with simulated data. 相似文献
11.
GPS资料同化最终归结为一个大规模的无约束优化问题。由于问题的维数很高，使得寻找到一种快速且节约存储的优化算法成为GPS资料同化能否满足在业务数值天气预报上的要求的关键。提出了一种新的优化算法。该方法把L-BFGS和HFN两种方法动态的结合起来，同时利用有限差分技术和截去技术，使算法在存储和计算量适合当前设备的前提下，较大的提高了算法的收敛速度。数值试验表明，该方法的计算效率与L-BFGS方法相比有十分明显的改善。 相似文献
12.
The impact of Global Positioning System data on the prediction of an extratropical cyclone: an observing system simulation experiment 总被引：1，自引：0，他引：1
In this paper, we report a series of observing system simulation experiments that we conducted to assess the potential impact of Global Positioning System/meteorology (GPS/MET) refractivity data on short-range numerical weather prediction. We first conducted a control experiment using the Penn State/NCAR mesoscale model MM5 at 90-km resolution on an extratropical cyclone known as the ERICA (Experiment on Rapidly Intensifying Cyclones over the Atlantic) IOP 4 storm. The results from the control experiment were then used to simulate GPS/MET refractivity observations with different spatial resolution and measurement characteristics. The simulated refractivity observations were assimilated into an 180-km model during a 6-h period, which was followed by a 48-h forecast integration. Key findings can be summarized as follows:
- • The assimilation of refractivity data at the 180-km resolution can recover important atmospheric structures in temperature and moisture fields both in the upper and lower troposphere, and, through the internal model dynamical processes, also the wind fields. The assimilation of refractivity data led to a considerably more accurate prediction of the cyclone.
- • Distributing the refractivity randomly in space and applying a line averaging did not alter the results significantly, while reducing the spatial resolution from 180 km to 360 km produced a moderately degraded result. Even at the 360-km resolution, the GPS-type refractivity data still have a notable positive impact on cyclone prediction.
- • Restricting the refractivity data to altitude 3 km and above considerably degraded its impact on cyclone prediction. This degradation was greater than the combined effects of distributing the refractivity data randomly, performing line averaging, and reducing the resolution to 360 km.
13.
区域GPS气象网反演的可降水量资料（GPS／PWV）对提高灾害性天气的监测和预报能力，改进数值天气预报精度已显示出广阔的应用前景，我国许多省市相继计划建设区域的GPS气象网。在区域GPS气象网中如何科学合理地布设GPS站就成了大家关注的问题。结合长江三角洲地区GPS气象网的情况，从长江三角洲地区的水汽通道，PWV分布的气候统计、GPS反演PWV资料的有效半径和在数值天气预报中资料同化的最大影响半径等4个方面，讨论了区域GPS网站点的分布和间距的几点依据：重点沿区域的水汽通道和强对流天气主要路径上布站，经向（南北向）的站点密度应大于纬向密度，站点的最大间距小于60km才能使反演的PwV的有效代表性和对数值预报的影响覆盖整个区域。 距 相似文献
14.
GPS"射线打靶”模式的并行计算 总被引：3，自引：0，他引：3
全球定位系统（ＧＰＳ）“射线打靶”模式是ＧＰＳ／ＭＥＴ（气象）资料变分同化中联系ＧＰＳ原始观测与大气状况的一种自成一体的观测算子，但因其计算量非常巨大而一直没能得到实用。为了克服这一困难，我们建立一个并行版本的 ＧＰＳ“射线打靶”模式，并在国家重点基础研究发展规划项目“大规模科学计算研究”资助下研制的微机机群系统（ＬＳＳＣ）上成功地实现了并行计算，取得了理想的加速比和并行效率，而且具有良好的可扩展性，为该观测算子达到实用迈出了实质性的一步。 相似文献
15.
The Global Positioning System (GPS) ray-shooting model is a self-sufficient observation operator in GPS/ MET (Meteorology)
data variational assimilation linking up the GPS observation data and the atmospheric state variables. But its huge computations
make it impracticable in real data assimilation so far. In order to overcome this default, a parallel version of the GPS ray-shooting
model has been developed, and has been running successfully on the PC cluster manufactured under the support of the China
National Key Development Planning Project for Basic Research: The Large Scale Scientific Computation Research. High speed-up
and Efficiency as well as good scalability are obtained. This is an important step for this GPS observation operator to become
practicable.
This research was supported by the National Natural Science Foundation of China(Grant No. 49825109), the National Key Development
Planning Project for Basic Research (Grant No. 1999032801) and the CAS Key Innovation Direction Project (Grant No.KZCX2208). 相似文献
16.
GPS气象学（GPS/MET）是20世纪90年代兴起的一种大气遥感技术。经过近10多年的发展,GPS/MET技术正逐步从科研走向业务应用。介绍了地基GPS/MET遥感大气水汽含量的基本原理,简单回顾了地基GPS/MET的发展历程,并根据其发展现状,对地基GPS/MET应用前景和发展趋势进行了展望。认为,未来地基GPS/MET的发展主要体现在加强中尺度站网建设、发展和完善斜路径基础上的层析技术,以及资料产品在天气预报（尤其是临近预报）、气候监测和评估、中尺度数值模式等方面的应用。 相似文献
17.
18.
为了进一步提高GRAPES_Meso的分析和预报效果,该文在GRAPES_Meso三维变分同化系统中建立了同化GNSS/RO反演的大气资料的观测算子,实现了对GNSS/RO反演的大气资料的同化应用,并通过2013年7月1个月的同化和预报试验分析了GNSS/RO反演大气资料对GRAPES_Meso模式系统分析和预报的影响。结果表明:增加了GNSS/RO反演大气资料的同化后,GRAPES_Meso位势高度场的分析误差明显减小,平均分析误差减小约8%,预报误差略有减小,平均预报误差减小约1%;湿度场的分析误差和预报误差变化不明显,常规观测资料稀少的青藏高原地区的降水预报技巧有所提高,小雨到大雨的ETS (equitable threat score) 评分提高约0.01,对全国及其他分区的降水预报技巧总体上有正效果。 相似文献
19.
利用建立在长江三角洲地区GPS观测网中13个站点的资料对2002年6月27~28日影响长江三角洲地区的降水过程进行了MM5背景误差调节和可降水量资料的三维变分同化试验。试验结果表明:背景误差对三维变分同化的效果起着关键作用,模式变量(u,v,T,p和q)误差的水平尺度与NMC方法的平均时间长度有直接的关系。利用NMC方法重新构建的背景误差更接近实际的背景误差。三维变分技术能有效地同化GPS可降水量资料。GPS可降水量资料的同化使用不仅能调整模式初始湿度场,而且也能相应地调整模式初始气压场、温度场和风场。GPS可降水量资料的同化有利于减小模式初始场对可降水量的分析误差,并且有利于减小模式积分初期(3~6 h)可降水量的预报误差。与没有进行GPS可降水量同化相比,通过GPS可降水量资料的三维变分同化,使MM5模式6 h和24 h累计降水能力得到提高,改善了MM5模式降水预报性能。总体上,GPS可降水量资料的变分同化有利于模式降水预报能力的提高。 相似文献
20.
Specifying physically consistent and accurate initial conditions is one of the major challenges of numerical weather prediction (NWP) models. In this study, ground-based global positioning system (GPS) integrated water vapor (IWV) measurements available from the International Global Navigation Satellite Systems (GNSS) Service (IGS) station in Bangalore, India, are used to assess the impact of GPS data on NWP model forecasts over southern India. Two experiments are performed with and without assimilation of GPS-retrieved IWV observations during the Indian winter monsoon period (November–December, 2012) using a four-dimensional variational (4D-Var) data assimilation method. Assimilation of GPS data improved the model IWV analysis as well as the subsequent forecasts. There is a positive impact of ～10 % over Bangalore and nearby regions. The Weather Research and Forecasting (WRF) model-predicted 24-h surface temperature forecasts have also improved when compared with observations. Small but significant improvements were found in the rainfall forecasts compared to control experiments. 相似文献