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1.
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. 相似文献
2.
Four-dimensional variational data assimilation for mesoscale and storm-scale applications 总被引：1，自引：0，他引：1
Summary ?The status and progress of the four-dimensional variational data assimilation (4DVAR) are briefly reviewed focusing on application
to prediction of mesoscale/storm-scale atmospheric phenomena. Theoretical background is provided for each important component
of the 4DVAR system – forecast and adjoint models, observations, background, cost function, preconditioning, and minimization.
An overview of practical issues specific for mesoscale/storm-scale 4DVAR is then presented in terms of high-resolution observations,
nonlinearity and discontinuity problem, model error, errors from lateral boundary condition, and precipitation assimilation.
Practical strategies for efficient and simplified 4DVAR are also introduced, e.g., incremental 4DVAR, poor man’s 4DVAR, and
inverse 3DVAR. A new concept on hybrid approach is proposed to combine an efficient 4DVAR scheme and the standard 4DVAR scheme
aiming at reducing computational demand required by the standard 4DVAR while improving the accuracy of the simplified 4DVAR.
Applications to both hydrostatic and nonhydrostatic models are illustrated and our vision on opportunities and directions
for future research is provided.
Received March 12, 2001; revised July 24, 2001; accepted September 5, 2001 相似文献
3.
Recent advances in Global Positioning System （GPS） remote sensing technology allow for a direct estimation of the precipitable water vapor （PWV） from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational （4DVAR） data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavy precipitation was induced by a sequence of meso-β-scale convective systems （MCS） along the mei-yu front in China. The experiments with GPS-PWV assimilation cluster and also eliminated the erroneous rainfall successfully simulated the evolution of the observed MCS systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves. 相似文献
4.
FY-3A气象卫星臭氧总量数据的质量控制方案及其在台风Tembin(2012)和Isaac(2012)中的应用 总被引：1，自引：0，他引：1
我国第二代极轨气象卫星“风云三号”A星(FY-3A)上搭载的紫外臭氧总量探测仪(Total Ozone Unit,TOU)每天可以提供一次覆盖全球的臭氧总量观测。为了在数值预报中应用TOU的臭氧资料,从资料同化角度发展了一套质量控制方案。首先基于臭氧总量和平均位势涡度的高相关性建立了逐日动态更新的臭氧线性回归预报模型,然后使用双权重算法对臭氧资料进行质量控制。将该质量控制方案应用于台风Tembin(2012)和Isaac(2012)个例,试验结果说明该方案可以体现出臭氧总量和平均位势涡度之间相关关系的逐日变化,识别出的离群资料百分比随时间变化较稳定,可以保留原始资料的主体信息,并且显著降低了原始资料的标准差。同时,质量控制后的臭氧数据与统计拟合量更加一致,观测减拟合的概率密度函数分布形式也更接近高斯分布,有利于后续的资料同化。 相似文献
5.
Recent advances in Global Positioning System (GPS) remote sensing technology allow for a direct estimation of the precipitable water vapor (PWV) from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational (4DVAR) data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavy precipitation was induced by a sequence of meso-β-scale convective systems (MCS) along the mei-yu front in China.The experiments with GPS-PWV assimilation successfully simulated the evolution of the observed MCS cluster and also eliminated the erroneous rainfall systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves. 相似文献
6.
Atmospheric Infra Red Sounder(AIRS) measurements are a valuable supplement to current observational data, especially over the oceans where conventional data are sparse. In this study, two types of AIRS-retrieved temperature and moisture profiles, the AIRS Science Team product(Sci Sup) and the single field-of-view(SFOV) research product, were evaluated with European Centre for Medium-Range Weather Forecasts(ECMWF) analysis data over the Atlantic Ocean during Hurricane Ike(2008) and Hurricane Irene(2011). The evaluation results showed that both types of AIRS profiles agreed well with the ECMWF analysis, especially between 200 h Pa and 700 h Pa. The average standard deviation of both temperature profiles was approximately 1 K under 200 h Pa, where the mean AIRS temperature profile from the AIRS Sci Sup retrievals was slightly colder than that from the AIRS SFOV retrievals. The mean Sci Sup moisture profile was slightly drier than that from the SFOV in the mid troposphere. A series of data assimilation and forecast experiments was then conducted with the Advanced Research version of the Weather Research and Forecasting(WRF) model and its three-dimensional variational(3DVAR) data assimilation system for hurricanes Ike and Irene. The results showed an improvement in the hurricane track due to the assimilation of AIRS clear-sky temperature profiles in the hurricane environment. In terms of total precipitable water and rainfall forecasts, the hurricane moisture environment was found to be affected by the AIRS sounding assimilation.Meanwhile, improving hurricane intensity forecasts through assimilating AIRS profiles remains a challenge for further study. 相似文献
7.
A. Routray U. C. Mohanty Dev Niyogi S. R. H. Rizvi Krishna K. Osuri 《Meteorology and Atmospheric Physics》2010,106(1-2):107-125
We present the results of the impact of the 3D variational data assimilation (3DVAR) system within the Weather Research and Forecasting (WRF) model to simulate three heavy rainfall events (25–28 June 2005, 29–31 July 2004, and 7–9 August 2002) over the Indian monsoon region. For each event, two numerical experiments were performed. In the first experiment, namely the control simulation (CNTL), the low-resolution global analyses are used as the initial and boundary conditions of the model. In the second experiment (3DV-ANA), the model integration was carried out by inserting additional observations in the model’s initial conditions using the 3DVAR scheme. The 3DVAR used surface weather stations, buoy, ship, radiosonde/rawinsonde, and satellite (oceanic surface wind, cloud motion wind, and cloud top temperature) observations obtained from the India Meteorological Department (IMD). After the successful inclusion of additional observational data using the 3DVAR data assimilation technique, the resulting reanalysis was able to successfully reproduce the structure of convective organization as well as prominent synoptic features associated with the mid-tropospheric cyclones (MTC). The location and intensity of the MTC were better simulated in the 3DV-ANA as compared to the CNTL. The results demonstrate that the improved initial conditions of the mesoscale model using 3DVAR enhanced the location and amount of rainfall over the Indian monsoon region. Model verification and statistical skill were assessed with the help of available upper-air sounding data. The objective verification further highlighted the efficiency of the data assimilation system. The improvements in the 3DVAR run are uniformly better as compared to the CNTL run for all the three cases. The mesoscale 3DVAR data assimilation system is not operational in the weather forecasting centers in India and a significant finding in this study is that the assimilation of Indian conventional and non-conventional observation datasets into numerical weather forecast models can help improve the simulation accuracy of meso-convective activities over the Indian monsoon region. Results from the control experiments also highlight that weather and regional climate model simulations with coarse analysis have high uncertainty in simulating heavy rain events over the Indian monsoon region and assimilation approaches, such as the 3DVAR can help reduce this uncertainty. 相似文献
8.
9.
Three-dimensional variational data assimilation of WindSat ocean surface winds for the genesis and forecasting of tropical storm Henri 总被引：2，自引：1，他引：1 
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下载免费PDF全文 With available high-resolution ocean surface wind vectors retrieved from the U.S. Naval Research Laboratorys WindSat on Coriolis, the impact of these data on genesis and forecasting of tropical storm Henri is examined using the non-hydrostatic, fifth-generation mesoscale model (MM5) of Pennsylvania State University-National Center for Atmospheric Research plus its newly released three-dimensional variational data assimilation (3DVAR) system. It is shown that the assimilation of the WindSat-retrieved ocean surface wind vectors in the 3DVAR system improves the model initialization fields by introducing a stronger vortex in the lower troposphere. As a result, the model reproduces the storm formation and track reasonably close to the observations. Compared to the experiment without the WindSat surface winds, the WindSat assimilation reduced an error between the model simulated track and observations of more than 80 km and also improved the storm intensity by nearly 2 hPa. It suggests that these data could provide early detection and prediction of tropical storms or hurricanes. 相似文献
10.
中国地形复杂，模式地形与实际观测地形存在一定高度差异，因此设计合理的复杂地形下地面观测资料的同化方案有利于使我国目前仅用作探测手段的地面观测资料（常规地面观测站和地面自动站）在中尺度数值模式中得到充分利用。作者在MM5_3DVAR同化系统中利用近地层相似理论将地面观测资料进行直接三维变分同化分析，并对地面资料同化方案设计中是否需要考虑模式与实际观测站地形高度差异进行探讨研究。研究结果表明：通过近地层相似理论将地面观测资料同化到数值模式能起到一定的作用，并且地面观测资料（温度、 湿度、 风场、 地面气压）中各物理量同化到数值模式都能影响24小时降水数值结果，但各物理量起的作用大小不一样，其中影响最大的是温度，其次为湿度；地面观测资料同化方案设计有必要考虑模式地形与实际观测站地形高度差异，适当考虑这种高度差异能取得较好的结果。 相似文献
11.
该文简要介绍GRAPES三维变分同化技术在MM5数值预报中的应用；利用2003年3月至2003年5月华东地区138个台站实况资料与其预报结果，评价了该模式系统对华东地区降水的预报结果，分析了三维变分同化对MM5数值预报结果的可能影响。结果表明，GRAPES三维变分同化方案是比较合理的，同化后模式对华东大部分地区的降水24 h预报比没有使用同化的总体情况要好；同样，同化后模式对华东大部分地区的晴雨预报准确率较高。 相似文献
12.
Rainfall prediction remains one of the most challenging problems in weather forecasting. In order to improve high-resolution quantitative precipitation forecasts (QPF), a new procedure for assimilating rainfall rate derived from radar composite reflectivity has been proposed and tested in a numerical simulation of the Chicago floods of 17–18 July 1996. The methodology is based on the one-dimensional variation scheme (1DVAR) assimilation approach introduced by Fillion and Errico but applied here using the Ka... 相似文献
13.
利用中尺度WRF模式及其3DVAR同化系统对2014年3月30日发生在我国华南地区的一次飑线过程展开多普勒天气雷达资料的同化效果试验研究。首先对雷达资料进行去地物杂波、退速度模糊等预处理,后设计了基于不同雷达观测量的同化试验及同化频次的敏感性试验。结果表明:直接循环同化雷达径向风资料和雷达反射率因子能够增加数值模式中的中小尺度信息,提供可靠的水汽分布;不同的同化频次对同化结果影响显著,每12 min同化间隔的结果略优于30 min、60 min同化间隔;同化雷达反射率因子和径向风资料分别对模式的总水场和风场有显著调整,联合同化雷达反射率因子和径向风资料比单独同化反射率因子或径向风更能改善飑线垂直结构配置,促使地面冷池和雷暴高压配合,进一步改善模式对大雨和暴雨量级降水预报效果。 相似文献
14.
GPS掩星反演大气温湿资料具有高垂直分辨率、高精度、受云和降水影响小等优点,针对GRAPES同化预报系统,发展设计了一种既考虑预报模式高度-地形追随垂直坐标不均匀分层特点,又结合掩星反演资料特性的新适应性垂直稀疏化方案。通过个例试验和批量试验,探索了该适应性稀疏化方案对分析预报质量的影响。试验结果表明:选取合适的稀疏参数,新稀疏化方案的GPS掩星反演资料对背景场的调整更加有效,分析场质量更高;位势高度、比湿、温度和风场等预报场的均方根误差均更小;适应性稀疏化方案对改善台风路径预报具有积极作用。批量试验则进一步证实了适应性稀疏化方案对分析场质量有明显的改善作用。 相似文献
15.
Four-dimensional variational data assimilation experiments for a heavy rain case during the 2002 IOP in China 总被引：3，自引：0，他引：3
A heavy rainfall event along the mei-yu front during 22-23 June 2002 was chosen for this study. To assess the impact of the routine and additional IOP (intensive observation period) radiosonde observations on the mesoscale heavy rainfall forecast, a series of four-dimensional variational (4DVAR) data assimilation and model simulation experiments was conducted using nonhydrostatic mesoscale model MM5 and the MM5 4DVAR system. The effects of the intensive observations in the different areas on the heavy rainfall forecast were also investigated. The results showed that improvement of the forecast skill for mesoscale heavy rainfall intensity was possible from the assimilation of the IOP radiosonde observations. However,the impact of the IOP observations on the forecast of the rainfall pattern was not significant. Initial conditions obtained through the 4DVAR experiments with a 12-h assimilation window were capable of improving the 24-h forecast. The simulated results after the assimilation showed that it would be best to perform the intensive radiosonde observations in the upstream of the rainfall area and in the moisture passageway area at the same time. Initial conditions created by the 4DVAR led to the low-level moisture convergence over the rainfall area, enhanced frontogenesis and upward motion within the mei-yu front,and intensified middle- and high-level unstable stratification in front of the mei-yu front. Consequently,the heavy rainfall forecast was improved. 相似文献
16.
This paper examines how assimilating surface observations can improve the analysis and forecast ability of a fourdimensional Variational Doppler Radar Analysis System(VDRAS).Observed surface temperature and winds are assimilated together with radar radial velocity and reflectivity into a convection-permitting model using the VDRAS four-dimensional variational(4DVAR) data assimilation system.A squall-line case observed during a field campaign is selected to investigate the performance of the technique.A single observation experiment shows that assimilating surface observations can influence the analyzed fields in both the horizontal and vertical directions.The surface-based cold pool,divergence and gust front of the squall line are all strengthened through the assimilation of the single surface observation.Three experiments—assimilating radar data only,assimilating radar data with surface data blended in a mesoscale background,and assimilating both radar and surface observations with a 4DVAR cost function—are conducted to examine the impact of the surface data assimilation.Independent surface and wind profiler observations are used for verification.The result shows that the analysis and forecast are improved when surface observations are assimilated in addition to radar observations.It is also shown that the additional surface data can help improve the analysis and forecast at low levels.Surface and low-level features of the squall line—including the surface warm inflow,cold pool,gust front,and low-level wind—are much closer to the observations after assimilating the surface data in VDRAS. 相似文献
17.
在分析美国局地分析预报系统 (LAPS) 和GRAPES_Meso数值预报系统,实现GRAPES-LAPS接口的基础上,通过两种数据融合方案,即GRAPES/LAPS方案 (简称LAPS方案) 和GRAPES/3DVAR方案 (3DVAR方案),对2008—2010年华南地区的28个个例的地面、探空常规和加密资料,以及多部多普勒天气雷达数据等融合、同化,开展两种方案的对比模拟试验。结果表明:LAPS方案获得的初始场,水汽条件有所改善,其辐合辐散相耦合触发中小尺度系统发展加强的中尺度环境场,有助于提高模式对强对流天气的预报能力。两种方案的24 h要素场均方根误差检验结果和降水TS评分大体相当,但28个个例中,LAPS方案报出了10个暴雨,而3DVAR方案只报出了5个,LAPS方案的中雨、大雨和暴雨的24 h降水预报TS评分要略好于3DVAR方案相应预报的TS评分,表明LAPS方案对强降水的预报较3DVAR方案有一定改进。 相似文献
18.
本研究利用WRF模式及其三维变分同化系统实现了对NOAA-16 AMSU-A微波资料的直接同化,针对2010年6月19日江西地区的一次强降水过程开展模拟与同化试验,并利用中国区域土壤湿度同化系统(CLSMDAS—China Land Soil Moisture Data Assimilation System)输出的土壤湿度值替换NCEP(National Centers for Environmental Prediction)资料中的土壤湿度,研究土壤湿度初值对辐射率资料直接同化中观测场与背景场偏差调整的影响。结果表明:采用CLSMDAS输出土壤湿度初值条件下模拟的亮温值与实际观测值更为接近,经过质量控制和偏差订正后更多的观测资料能够进入到同化系统中,说明改进的土壤湿度初值条件下观测算子的计算值得到正的调整,对低层地表通道的改进效果明显,尤其以50.3 GHz的窗区通道3的结果最为理想;针对此次强降水过程中24 h累积降水分布的模拟结果,CLSMDAS输出土壤湿度初值条件下同化AMSU-A资料,能够较为准确的把握整个雨带的走向、大雨以上级别降水的落区范围、降水中心落区及强度等。说明准确的土壤湿度初值能够改进卫星辐射率资料的同化结果,进而提高数值模式的模拟预报能力。 相似文献
19.
设计了一个以MM5模式为基础的遗传算法同化系统,并对一次暴雨过程进行了实际降水的模拟,通过对比遗传同化和伴随同化的降水预报效果,对遗传算法同化系统的同化性能进行验证。试验结果表明,遗传算法与四维变分相结合的同化系统能有效地改善模式的初始场,使MM5模式要素预报和降水预报的准确率得到提高。 相似文献
20.
This study examines the performance of coupling the deterministic four-dimensional
variational assimilation system (4DVAR) with an ensemble Kalman filter (EnKF) to produce a
superior hybrid approach for data assimilation. The coupled assimilation scheme (E4DVAR)
benefits from using the state-dependent uncertainty provided by EnKF while taking advantage
of 4DVAR in preventing filter divergence: the 4DVAR analysis produces posterior maximum
likelihood solutions through minimization of a cost function about which the ensemble
perturbations are transformed, and the resulting ensemble analysis can be propagated forward
both for the next assimilation cycle and as a basis for ensemble forecasting. The feasibility
and effectiveness of this coupled approach are demonstrated in an idealized model with
simulated observations. It is found that the E4DVAR is capable of outperforming both 4DVAR
and the EnKF under both perfect- and imperfect-model scenarios. The performance of the
coupled scheme is also less sensitive to either the ensemble size or the assimilation window
length than those for standard EnKF or 4DVAR implementations. 相似文献