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1.
机载多普勒天气雷达及应用研究进展 总被引：1，自引：1，他引：0
机载多普勒天气雷达由于其灵活机动性,在台风、暴雨等灾害性天气系统中尺度三维精细结构研究中发挥着重要作用.对机载多普勒天气雷达技术及其资料应用进行了概要性综述,主要从机载多普勒天气雷达发展历程、4种主要机载多普勒雷达技术特点、雷达天线扫描策略、单多普勒雷达风场反演技术、双多普勒雷达风场反演技术、雷达资料同化以及目标观测等方面进行阐述和分析;着重讨论了应用中需要解决的问题.最后,指出发展具有快速扫描和双偏振功能的机载相控阵多普勒雷达是机载天气雷达的发展方向,它可以获取高时空分辨率的探测数据,能够对云和降水系统的三维精细动力结构、热力结构以及微物理结构等进行综合研究. 相似文献
2.
定量反演降水及其在青藏高原东北边缘地区面雨量估算中的应用 总被引：1，自引：0，他引：1
雷达-雨量计联合校准降水结合了雷达区域覆盖和雨量计单点精度高的优势, 利用雷达进行区域降水量估计是提高雷达应用能力的重要方向之一. 通过利用在青藏高原东北边坡地区的雷达回波-降水反演关系式, 对2012年5月10日的这一地区的一次区域性强降水过程进行反演比较, 并利用平均校准法、 最优插值法和用卡尔曼滤波确定变分系数的变分-卡尔曼滤波进行空间校准. 结果表明:利用最优化法得到的本地降水反演关系式效果要明显优于其他波段或地域的固有关系式, 可以有效改变过低估计的状况; 变分-卡尔曼滤波由于考虑了雷达区域扫描的优势, 校准效果最好, 可以细致反映空间降水分布, 对降水预报、 地质灾害预警等都有重要意义.通过建立多仰角多变量的降水关系式, 并进一步对反演结果采用有效的数学校正法可能会对空间面雨量估测取得更好的效果. 相似文献
3.
《地球科学进展》2019,(11)
云和降水区微波观测包含大量与天气系统,特别是台风、暴雨等灾害性天气系统发生发展密切相关的大气信息,因此微波资料的全天候同化应用成为当前数值预报领域的热点研究问题。过去20年间,全球几大数值预报中心逐步开展了全天候同化技术的研究和业务应用,证实了全天候卫星微波观测资料能够改进模式中的质量、风场、湿度以及云和降水场的初始信息,从而改进数值预报模式的预报效果。通过梳理和评述全天候卫星微波观测资料同化方法,分析其中的关键技术问题和目前存在的困难和挑战,为未来在我国数值天气预报领域开展全天候同化研究提供依据。随着我国新一代数值天气预报模式的发展应用,加强我国全天候资料同化技术的研究将会在业务中发挥更大的科学效益和应用效益。 相似文献
4.
多普勒天气雷达风场反演技术研究进展 总被引：15，自引：0，他引：15
多普勒天气雷达是研究中小尺度天气系统的重要工具，但却只能提供风场的径向速度，因而必须通过风场反演技术来求解二维或三维风场。详细分析了各种单部、多部和多基地多普勒天气雷达风场反演技术及其优缺点，同时指出了应重点研究的方向。从反演结果来看，基于变分法的反演技术明显优于其它方法，这是今后的一个主要研究方向；利用四维同化理论，在数值模式初始场中使用反演数据，是反演技术应用的重点。 相似文献
5.
随着全球气候变化、自然变迁及陆表生境改变,极端天气频发且呈现出多尺度时空变异特征,对其进行预报和预警一直是气象水文领域关注的焦点。临近预报可较准确地预报未来短时间天气显著变化,是当前预报强降水等极端事件的主要手段。从基于天气雷达0~3 h外推临近预报、融合数值模式0~6 h临近预报的发展历程梳理了临近预报的研究进展,阐述了雷达外推算法的发展进程、雷达外推预报与数值模式预报融合技术进展,指出"取长补短"的0~6 h融合预报在提高降水预报精度、延长降水预见期等多方面有较大的发展潜力,进一步探寻及提升融合技术是未来融合预报发展的核心。将临近预报以气象水文耦合的方式引入水文预报是从源头提高水文预报精度、保障水文预报效果的主要途径,总结了现阶段主流耦合方式、空间尺度匹配技术、水文模型不确定等陆气耦合中的关键问题,阐述了外推临近预报、融合临近预报作为水文预报输入的研究进展,明确了融合临近预报在延长洪水预见期、提高洪水预报精度中存在优势,并讨论了未来的研究重点及发展方向。 相似文献
6.
基于数值大气模式WRF、三维变分数据同化WRF-3DVar、河北雨洪模型以及实时校正模型ARMA,在北方半湿润半干旱地区的大清河流域构建了陆气耦合洪水预报系统,并利用2012、2013年发生的3场降雨洪水,对系统的降雨洪水预报结果进行分析。结果表明:雷达反射率与GTS数据的同时同化,可有效改善数值大气模式对中小尺度流域的降雨预报效果,从而降低系统的洪水预报误差,ARMA模型的应用,能够进一步提升系统的洪水预报精度,随着预见期的延长,系统的预报精度下降,但系统在6h预见期内仍表现出较好的应用效果。因此,在数据同化和实时校正的"双校正"模式下,陆气耦合洪水预报系统在延长洪水预报预见期的同时,具有较高的洪水预报精度,具有一定的应用前景。 相似文献
7.
8.
WMO第八届阳江国际探空比对辅助遥感综合试验 总被引：1，自引：0，他引：1
第八届阳江国际探空比对辅助遥感综合试验为分析探空仪系统在高空出入云的温湿特性,评估高层云红外辐射对温度传感器的影响以及湿度传感器的系统偏差提供有力帮助。通过试验,还评估了国产X波段双偏振雷达与毫米波云雷达的优缺点和性能差异,以及国产多普勒激光雷达、微脉冲激光雷达的探测性能和应用能力,在改进微波辐射计温湿反演算法、X波段偏振雷达参数的云中粒子相态模糊逻辑识别算法,以及多普勒天气雷达风场反演、云分类算法、高空业务测风算法等方面开展广泛研究并取得一定进展。试验还利用先进的各类遥感设备对阳江热带地区的云、局地对流以及海陆风系统的结构进行了观测和分析,取得了较好的研究结果。 相似文献
9.
云分析预报方法研究进展 总被引：2，自引：1，他引：1
云作为地球大气系统的重要组成部分,不仅影响着气候变化和天气系统的发展演变,还与航空活动密切相关,一直以来是空军和民航部门非常关注的气象要素之一。在云探测、资料同化和反演方法发展的基础上,从实际业务保障和数值模式发展需求出发,综述国内外云分析、预报方法和云分析预报系统开发的研究成果,分析各类方法的优势和不足,明确国内外研究的主要差距,并探讨国内未来研究的方向。云分析方法中,探空对云廓线识别较好,卫星可见光和红外资料在云顶信息反演方面优势明显,多普勒雷达能够获取对流层中层和底层的云信息,而毫米波雷达能够很好地反映云三维结构信息,发展潜力巨大。云预报方法中,传统的统计和诊断方法发展较为成熟,而考虑了大气温湿和云微物理状况的大气辐射传输模式正演模拟云顶亮温的方法是未来的发展趋势。加强云探测技术,综合利用云分析预报方法,借鉴国外先进云分析预报系统的设计理念,积极开发我国自主的云分析预报系统,推动天气预报、航空气象保障和数值预报模式的发展将会是我国云研究的重要方面。 相似文献
10.
边界层参数化影响“梅花”台风的敏感性试验 总被引：3，自引：0，他引：3
以GRAPES-TCM为试验模式,对1109台风“梅花”进行了36次72 h的预报试验,通过试验分析了2种边界层参数化方案——MRF方案与YSU方案在不同情况下对台风预报的影响.结果显示:“梅花”路径与强度对边界层方案的变化都表现出一定的敏感性,敏感性大小与对流参数化方案、台风的初始强度等因素有关,强度的敏感性比路径更明显;对弱台风的路径与强度,YSU方案的总体预报效果优于MRF方案,对于强台风,2种边界层方案中MRF方案的路径预报效果更好,哪种方案的强度预报效果更好与对流参数化方案有关;无论何种情况,YSU方案预报的“梅花”强度都明显强于MRF方案,YSU方案预报的降水及感热通量与潜热通量总体上大于MRF方案;YSU方案时更多的感热通量和潜热通量与该方案时边界层更强的湍流混合有关,更多的潜热通量导致更多的降水,从而释放更多的潜热,更多的潜热释放以及更多的感热通量导致台风强度更强. 相似文献
11.
Impact of additional surface observation network on short range weather forecast during summer monsoon 2008 over Indian subcontinent 总被引：1，自引：0，他引：1
The three dimensional variational data assimilation scheme (3D-Var) is employed in the recently developed Weather Research
and Forecasting (WRF) model. Assimilation experiments have been conducted to assess the impact of Indian Space Research Organisation’s
(ISRO) Automatic Weather Stations (AWS) surface observations (temperature and moisture) on the short range forecast over the
Indian region. In this study, two experiments, CNT (without AWS observations) and EXP (with AWS observations) were made for
24-h forecast starting daily at 0000 UTC during July 2008. The impact of assimilation of AWS surface observations were assessed
in comparison to the CNT experiment. The spatial distribution of the improvement parameter for temperature, relative humidity
and wind speed from one month assimilation experiments demonstrated that for 24-h forecast, AWS observations provide valuable
information. Assimilation of AWS observed temperature and relative humidity improved the analysis as well as 24-h forecast.
The rainfall prediction has been improved due to the assimilation of AWS data, with the largest improvement seen over the
Western Ghat and eastern India. 相似文献
12.
Performance of nested WRF model in typhoon simulations over West Pacific and South China Sea 总被引：2，自引：1，他引：1
Forecasting skill of weather research and forecasting (WRF) model in simulating typhoons over the West Pacific and South China Sea with different trajectories has been studied in terms of track direction and intensity. Four distinct types of typhoons are chosen for this study in such a way that one of them turns toward left during its motion and had landfall, while the second took a right turn before landfall. The third typhoon followed almost a straight line path during its course of motion, while the fourth typhoon tracked toward the coast and just before landfall, ceased its motion and travelled in reverse direction. WRF model has been nested in one way with a coarse resolution of 9?km and a fine resolution of 3?km for this study, and the experiments are performed with National Center for Environmental Prediction-Global Forecasting System (NCEP-GFS) analyses and forecast fields. The model has been integrated up to 96?h and the simulation results are compared with observed and analyzed fields. The results show that the WRF model could satisfactorily simulate the typhoons in terms of time and location of landfall, mean sea-level pressure, maximum wind speed, etc. Results also show that the sensitivity of model resolution is less in predicting the track, while the fine-resolution model component predicted slightly better in terms of central pressure drop and maximum wind. In the case of typhoon motion speed, the coarse-resolution component of the model predicted the landfall time ahead of the actual, whereas the finer one produced either very close to the best track or lagging little behind the best track though the difference in forecast between the model components is minimal. The general tendency of track error forecast is that it increases almost linearly up to 48?h of model simulations and then it diverges quickly. The results also show that the salient features of typhoons such as warm central core, radial increase of wind speed, etc. are simulated well by both the coarse and fine domains of the WRF model. 相似文献
13.
Performance of a hybrid assimilation system combining 3D Var based NGFS (NCMRWF Global Forecast System) with ETR (Ensemble Transform with Rescaling) based Global Ensemble Forecast (GEFS) of resolution T-190L28 is investigated. The experiment is conducted for a period of one week in June 2013 and forecast skills over different spatial domains are compared with respect to mean analysis state. Rainfall forecast is verified over Indian region against combined observations of IMD and NCMRWF. Hybrid assimilation produced marginal improvements in overall forecast skill in comparison with 3D Var. Hybrid experiment made significant improvement in wind forecasts in all the regions on verification against mean analysis. The verification of forecasts with radiosonde observations also show improvement in wind forecasts with the hybrid assimilation. On verification against observations, hybrid experiment shows more improvement in temperature and wind forecasts at upper levels. Both hybrid and operational 3D Var failed in prediction of extreme rainfall event over Uttarakhand on 17 June, 2013. 相似文献
14.
Numerical simulation of cyclonic storms FANOOS, NARGIS with assimilation of conventional and satellite observations using 3-DVAR 总被引：3，自引：2，他引：1
C. V. Srinivas V. Yesubabu K. B. R. R. Hari Prasad B. Venkatraman S. S. V. S. Ramakrishna 《Natural Hazards》2012,63(2):867-889
In this work, the impact of assimilation of conventional and satellite data is studied on the prediction of two cyclonic storms in the Bay of Bengal using the three-dimensional variational data assimilation (3D-VAR) technique. The FANOOS cyclone (December 6?C10, 2005) and the very severe cyclone NARGIS (April 28?CMay 2, 2008) were simulated with a double-nested weather research and forecasting (WRF-ARW) model at a horizontal resolution of 9?km. Three numerical experiments were performed using the WRF model. The back ground error covariance matrix for 3DVAR over the Indian region was generated by running the model for a 30-day period in November 2007. In the control run (CTL), the National Centers for Environmental Prediction (NCEP) global forecast system analysis at 0.5° resolution was used for the initial and boundary conditions. In the second experiment called the VARCON, the conventional surface and upper air observations were used for assimilation. In the third experiment (VARQSCAT), the ocean surface wind vectors from quick scatterometer (QSCAT) were used for assimilation. The CTL and VARCON experiments have produced higher intensity in terms of sea level pressure, winds and vorticity fields but with higher track errors. Assimilation of conventional observations has meager positive impact on the intensity and has led to negative impact on simulated storm tracks. The QSCAT vector winds have given positive impact on the simulations of intensity and track positions of the two storms, the impact is found to be relatively higher for the moderate intense cyclone FANOOS as compared to very severe cyclone NARGIS. 相似文献
15.
S. Abhilash Someshwar Das S. R. Kalsi M. Das Gupta K. Mohankumar J. P. George S. K. Banerjee S. B. Thampi D. Pradhan 《Journal of Earth System Science》2007,116(4):275-304
Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model prediction of convective
events. This work is the first attempt in utilizing the India Meteorological Department (IMD) Doppler radar data in a numerical
model for the prediction of mesoscale convective complexes around Chennai and Kolkata. Three strong convective events both
over Chennai and Kolkata have been considered for the present study. The simulation experiments have been carried out using
fifth-generation Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) mesoscale model (MM5) version
3.5.6. The variational data assimilation approach is one of the most promising tools available for directly assimilating the
mesoscale observations in order to improve the initial state. The horizontal wind derived from the DWR has been used alongwith
other conventional and non-conventional data in the assimilation system. The preliminary results from the three dimensional
variational (3DVAR) experiments are encouraging. The simulated rainfall has also been compared with that derived from the
Tropical Rainfall Measuring Mission (TRMM) satellite. The encouraging result from this study can be the basis for further
investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present study indicates that Doppler
radar data assimilation improves the initial field and enhances the Quantitative Precipitation Forecasting (QPF) skill. 相似文献
16.
In this paper, impact of Indian Doppler Weather Radar (DWR) data, i.e., reflectivity (Z), radial velocity (Vr) data individually and in combination has been examined for simulation of mesoscale features of a land-falling
cyclone with Advance Regional Prediction System (ARPS) Model at 9-km horizontal resolution. The radial velocity and reflectivity
observations from DWR station, Chennai (lat. 13.0°N and long. 80.0°E), are assimilated using the ARPS Data Assimilation System
(ADAS) and cloud analysis scheme of the model. The case selected for this study is the Bay of Bengal tropical cyclone NISHA
of 27–28 November 2008. The study shows that the ARPS model with the assimilation of radial wind and reflectivity observations
of DWR, Chennai, could simulate mesoscale characteristics, such as number of cells, spiral rain band structure, location of
the center and strengthening of the lower tropospheric winds associated with the land-falling cyclone NISHA. The evolution
of 850 hPa wind field super-imposed vorticity reveals that the forecast is improved in terms of the magnitude and direction
of lower tropospheric wind, time, and location of cyclone in the experiment when both radial wind and reflectivity observations
are used. With the assimilation of both radial wind and reflectivity observations, model could reproduce the rainfall pattern
in a more realistic way. The results of this study are found to be very promising toward improving the short-range mesoscale
forecasts. 相似文献
17.
An abnormal warming condition with 3?C5?°C rise in temperature above its normal value was observed in the Indian state of Odisha during 12?C16 November 2009. This study aims at examining the impact of additional weather observations obtained from the automatic weather stations (AWS) installed in the recent past on the numerical simulation of such abnormal warming. AWS observations, such as temperature at 2?m (T2m), dew point temperature at 2?m (Td2m), wind vector at 10?m (speed and direction), and sea level pressure (SLP) have been assimilated into the state-of-the-art Weather Research and Forecasting (WRF) model using the three-dimensional variational data assimilation (3DVAR). Six sets of experiments have been conducted here. There is no data assimilation in the control experiment, whereas AWS and radiosonde observations have been assimilated in rest of the five experiments. The model integrations have been made for 72?h in each experiment starting from 0000 UTC November 12 to 0000 UTC November 15, 2009. Assimilation experiments have also been performed to assess the impact of individual surface parameters on the model simulations. Impact of AWS observations on model simulation has been examined with reference to the control simulation and quantified in terms of root-mean-square error and forecast skill score for temperature, sea level pressure, and relative humidity at three selected stations Bonaigarh, Brahmagiri, and Nuapada in Odisha. Results indicate improvements in the surface air temperature and SLP simulations in the timescale of 72?h at all the three stations due to additional weather data assimilation into the model. Improvements in simulation are significant up to 24?h. The assimilation of additional wind fields significantly improved the temperature simulation at all the three stations. The simulated SLP has also improved significantly due to the assimilation of surface temperature and moisture. 相似文献
18.
Someshwar Das Raghavendra Ashrit Gopal Raman Iyengar Saji Mohandas M. Das Gupta John P. George E. N. Rajagopal Surya Kanti Dutta 《Journal of Earth System Science》2008,117(5):603-620
Performance of four mesoscale models namely, the MM5, ETA, RSM and WRF, run at NCMRWF for short range weather forecasting has been examined during monsoon-2006. Evaluation is carried out based upon comparisons between observations and day-1 and day-3 forecasts of wind, temperature, specific humidity, geopotential height, rainfall, systematic errors, root mean square errors and specific events like the monsoon depressions.It is very difficult to address the question of which model performs best over the Indian region? An honest answer is ‘none’. Perhaps an ensemble approach would be the best. However, if we must make a final verdict, it can be stated that in general, (i) the WRF is able to produce best All India rainfall prediction compared to observations in the day-1 forecast and, the MM5 is able to produce best All India rainfall forecasts in day-3, but ETA and RSM are able to depict the best distribution of rainfall maxima along the west coast of India, (ii) the MM5 is able to produce least RMSE of wind and geopotential fields at most of the time, and (iii) the RSM is able to produce least errors in the day-1 forecasts of the tracks, while the ETA model produces least errors in the day-3 forecasts. 相似文献