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   定量降水估计 的翻译结果: 查询用时:0.011秒
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定量降水估计
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  quantitative precipitation estimation
     A PRELIMINARY STUDY ON METHOD OF QUANTITATIVE PRECIPITATION ESTIMATION(QPE) FOR LANDFALL TYPHOON
     一种可用于登陆台风定量降水估计(QPE)方法的初步建立
短句来源
     By using GMS-5 IR1 TBB of landfalling typhoon(LT) and hourly rainfall from ground automatic weather stations,a preliminary method of quantitative precipitation estimation(QPE) suitable for LT was found. Based on the results from the QPE method,the short-term quantitative precipitation forecast of 0 h to 3 h(QPF) for LT can be realized with the extrapolation method preliminarily.
     利用登陆台风的GMS-5 IR1 TBB资料及地面自动站逐时雨量资料,初步建立了适用于登陆台风的定量降水估计(QPE)方法,基于QPE结果,采用外推法,初步实现了对登陆台风未来0~3 h的短时定量降水预报(QPF)。
短句来源
  相似匹配句对
     b) a G-M estimator of ω'1α, ω'2β and ω'1α+ω'2β under L (Xβ, Aα; δ21V, δ22U} respectively.
     b)G-M估计
短句来源
     First Research on Realtime Quantitative Precipitation Forecasting
     实时定量降水预报初探
短句来源
     THE STUDY OF ESTIMATING RAIN AMOUNT BY GEOSTATIONARY SATELLINT IMAGES
     云图定量降水估测研究
短句来源
     A PRELIMINARY STUDY ON METHOD OF QUANTITATIVE PRECIPITATION ESTIMATION(QPE) FOR LANDFALL TYPHOON
     一种可用于登陆台风定量降水估计(QPE)方法的初步建立
短句来源
     Precipitation Estimation from Remotely Sensed Information Using Nueral Networks
     卫星面降水估计人工神经网络方法
短句来源
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  quantitative precipitation estimation
Due to the scarcity of sufficient spatial ground-based rainfall data in hill areas, quantitative precipitation estimation using remote-sensing techniques such as radar and satellite is needed for debris flow pre-warning.
      
These more stringent requirements relate to both the support of the automated algorithms and the move to quantitative precipitation estimation.
      
The authors describe a comprehensive plan of introducing probabilistic quantitative precipitation estimation into the operational NWS environment.
      


By using GMS-5 IR1 TBB of landfalling typhoon(LT) and hourly rainfall from ground automatic weather stations,a preliminary method of quantitative precipitation estimation(QPE) suitable for LT was found.Based on the results from the QPE method,the short-term quantitative precipitation forecast of 0 h to 3 h(QPF) for LT can be realized with the extrapolation method preliminarily.The applications of the QPF method to 0104 LT Utor and 0414 LT Rananim show that as far as single station hourly rainfall quantitative...

By using GMS-5 IR1 TBB of landfalling typhoon(LT) and hourly rainfall from ground automatic weather stations,a preliminary method of quantitative precipitation estimation(QPE) suitable for LT was found.Based on the results from the QPE method,the short-term quantitative precipitation forecast of 0 h to 3 h(QPF) for LT can be realized with the extrapolation method preliminarily.The applications of the QPF method to 0104 LT Utor and 0414 LT Rananim show that as far as single station hourly rainfall quantitative forecast is concerned,if 50% relative error can be accepted,the accuracies of QPF for 0 h,1 h,2 h and 3 h can reach 20% to 70%,30% to 80%,30% to 70%,and 20% to 60%,respectively;as far as single station process rainfall quantitative forecast is concerned,if 50% relative error can be accepted,the accuracies of QPF for 0h,1 h,2 h and 3 h can all almost reach 60% to 80%;quantitative forecast for 0 h to 3 h area rainfall can also be provided,to a certain extent.The QPF results of 0 to 3 hours can serve as a reference for the operational short-term operational precipitation forecast for LT,to some degree.

利用登陆台风的GMS-5 IR1 TBB资料及地面自动站逐时雨量资料,初步建立了适用于登陆台风的定量降水估计(QPE)方法,基于QPE结果,采用外推法,初步实现了对登陆台风未来0~3 h的短时定量降水预报(QPF)。应用于0104号登陆台风“尤特”和0414号登陆台风“云娜”两个例表明:对单站逐小时雨量定量预报而言,如果50%相对误差可以接受,01、、23、h的QPF准确率分别达20%~70%、30%~80%、30%~70%、20%~60%;对于单站过程雨量定量预报而言,如果50%相对误差可以接受,0、1、2、3 h的QPF准确率基本都达60%~80%;对未来0~3 h的面雨量也具有一定定量预报能力。0~3 h QPF结果对实际短时登陆台风降水业务预报工作具有一定的参考价值。

Drawing on the experiences of Adler-Negri,Goldenberg etc.al and Lijun etc.al with perfection,and combining GMS-5 IR1 TBB characteristics of landfall typhoon as well as hourly precipitation intensity and horizontal distribution feature,a preliminary method of quantitative precipitation estimation(QPE) for landfall typhoon was found.On the basis of 0104 landfall typhoon Utor,the ability of quantitative estimation of the preliminary QPE method was examined in the context of hourly,process and area rainfall.The...

Drawing on the experiences of Adler-Negri,Goldenberg etc.al and Lijun etc.al with perfection,and combining GMS-5 IR1 TBB characteristics of landfall typhoon as well as hourly precipitation intensity and horizontal distribution feature,a preliminary method of quantitative precipitation estimation(QPE) for landfall typhoon was found.On the basis of 0104 landfall typhoon Utor,the ability of quantitative estimation of the preliminary QPE method was examined in the context of hourly,process and area rainfall.The results show that:(1) The QPE method could reflect the horizontal nonuniform distribution of landfall typhoon hourly precipitation and isolate convective and stratum rainfall,however,the ability of estimating strong precipitation over 15mm/h was limited.(2) The process rainfall relative error of 57% stations lower than 20%,and 75.9% smaller than 40%,indicated that the ability of the QPE method to estimate process rainfall was significant,which reflected indirectly its ability to estimate hourly precipitation.(3) The QPE method could estimate hourly area rainfall on some degree,which severed as a reference to defend dry and flood.

借鉴Adler-Negri[1]、Goldenberg等[2]及李俊等[3]的工作,通过对三者工作的有机结合及完善,针对登陆台风GMS-5 IR1TBB特征及逐时观测雨量强度及水平分布特点,初步建立一种可用于登陆台风的定量降水估计(QPE)方法,并结合0104号登陆台风“尤特”个例,从各站点逐时雨量、过程雨量以及区域面雨量角度,分析检验了初步建立的云估计降水方法的定量估计能力。结果表明:(1)所建QPE方法可以反映出登陆台风逐时降水的水平分布不均匀性,可以分离出对流降水和层云降水,但对大于15.0 mm/h的降水强度估计能力有限。(2)51.7%的站点过程雨量相对误差小于20%,过程雨量相对误差小于40%的站点数占总站点数的75.9%,表明所建QPE方法对过程雨量的估计能力还是相当强的,这也间接反映了其对逐时雨量较强的估计能力。(3)所建QPE方法对逐时面雨量也具有一定的估计能力,可以为抗旱、防洪决策服务提供一定的参考。

An automatic identification algorithm for the removal of bright band from radar reflectivity data is introduced and tested by case analysis and pre-operational run.The algorithm has good results of removal of bright band based on the radar reflectivity data which have been transformed into a regular 3-dimensional Cartesian grid while configuration and running setup are relative simple.Firstly,the algorithm performs the recognition of vertical bright band profile.The algorithm considers each point independently,and...

An automatic identification algorithm for the removal of bright band from radar reflectivity data is introduced and tested by case analysis and pre-operational run.The algorithm has good results of removal of bright band based on the radar reflectivity data which have been transformed into a regular 3-dimensional Cartesian grid while configuration and running setup are relative simple.Firstly,the algorithm performs the recognition of vertical bright band profile.The algorithm considers each point independently,and attempts to find the evidence of a bright band by using a pattern recognition approach.Based on the typical reflectivity of the vertical profile attributes in the bright band deducted from statistics,a set of ideal templates of radar reflectivity vertical profiles is established,which can resemble the actual radar reflectivity characteristics in different bright band areas at the utmost.For each horizontal grid the algorithm attempts to couple the templates to the measured vertical profile of radar reflectivity.The couple function is obtained by computing the slope and the correlation of the least squares regression between the template and the measured profile. Secondly,the algorithm finds continuous regions of bright band.Regions of bright band may be further recognized by the horizontal uniformity of the signature.The algorithm attempts to use the goodness-of-fit and height-of-best-fit field computed above to gain further clues of a bright band.A grid kernel-based approach is used,in which a kernel is composed of 5×5 grids in the field.For the grids in the kernel,the algorithm counts the number of difference between contiguous goodness-of-fit values exceeding a given threshold or the difference in the height-of-best-fit values for contiguous points exceeding a given threshold.A high interested value is assigned to points with low numbers,since this indicates uniformity.So bright band areas are identified as those fields with high interested values.Finally,the algorithm removes the bright band signature.It removes the continuous regions of bright band by correcting the reflectivity within the bright band,which employs linear or non-linear interpolation methodology based on the measured reflectivity values in the profile above the band and the measured values below the band.Some thunderstorm cases analysis and pre-operational running tests suggest that the algorithm is able to successfully identify and remove most bright band regions,which influences quantitative precipitation estimation,based on CINRAD/SA radar reflectivity located at Tanggu of Tianjin.However,the algorithm has less effect on actual storms reflectivity data.Results of the analysis also demonstrate that the bright band regions usually appear at 2.5 km over Beijing and Tianjin in early summer.Because the algorithm is relatively easy to configure and run,it is appropriate to use in real-time or operational mode.Of course the algorithm has limitations and needs to be continuously improved for actual operational applications.

该文介绍了一种自动识别和移除雷达反射率因子资料中亮带的算法,并对该算法进行了初步测试。该算法利用的是插值到直角坐标系中的雷达反射率因子资料,其配置和运行也相对简单,但却对移除亮带比较有效。首先,设定一套雷达反射率因子垂直廓线的理想模板,这些理想的模板能够在最大程度上反映不同亮带存在区域的雷达实际反射率因子的垂直廓线特征。然后,在水平方向每个点上,进行理想模板和实际反射率因子垂直廓线在垂直和水平两个方向上的拟合和差异计算,来自动识别雷达反射率因子中存在的连续亮带区域。最后,利用亮带之上和亮带之下的反射率因子值对亮带中的反射率因子值进行插值纠正,就可以移除亮带。利用位于天津塘沽的我国新一代天气雷达(CINRAD/SA)的反射率因子资料,通过个例分析和准业务运行试验,均表明这个简单算法可以识别和移除绝大多数影响雷达定量降水估计的反射率因子亮带区域,但是实际雷暴区域的反射率因子特征受到该算法的影响比较小。计算分析还表明,在京津地区的初夏,上述亮带区域一般容易出现在2.5 km左右的高度处。

 
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