Accurate atmospheric temperature and moisture information with high temporal/spatial resolutions are two of the key parameters needed in regional numerical weather prediction(NWP) models to reliably predict high-impac...Accurate atmospheric temperature and moisture information with high temporal/spatial resolutions are two of the key parameters needed in regional numerical weather prediction(NWP) models to reliably predict high-impact weather events such as local severe storms(LSSs). High spectral resolution or hyperspectral infrared(HIR) sounders from geostationary orbit(GEO) provide an unprecedented source of near time-continuous, three-dimensional information on the dynamic and thermodynamic atmospheric fields—an important benefit for nowcasting and NWP-based forecasting. In order to demonstrate the value of GEO HIR sounder radiances on LSS forecasts, a quick regional OSSE(Observing System Simulation Experiment)framework has been developed, including high-resolution nature run generation, synthetic observation simulation and validation, and impact study on LSS forecasts. Results show that, on top of the existing LEO(low earth orbit) sounders, a GEO HIR sounder may provide value-added impact [a reduction of 3.56% in normalized root-mean-square difference(RMSD)] on LSS forecasts due to large spatial coverage and high temporal resolution, even though the data are assimilated every 6 h with a thinning of 60 km. Additionally, more frequent assimilations and smaller thinning distances allow more observations to be assimilated, and may further increase the positive impact from a GEO HIR sounder. On the other hand, with denser and more frequent observations assimilated, it becomes more difficult to handle the spatial error correlation in observations and gravity waves due to the limitations of current assimilation and forecast systems(such as a static background error covariance). The peak reduction of 4.6% in normalized RMSD is found when observations are assimilated every 3 h with a thinning distance of 30 km.展开更多
High spectral resolution(or hyperspectral)infrared(IR)sounders onboard low earth orbiting satellites provide high vertical resolution atmospheric information for numerical weather prediction(NWP)models.In contrast,ima...High spectral resolution(or hyperspectral)infrared(IR)sounders onboard low earth orbiting satellites provide high vertical resolution atmospheric information for numerical weather prediction(NWP)models.In contrast,imagers on geostationary(GEO)satellites provide high temporal and spatial resolution which are important for monitoring the moisture associated with severe weather systems,such as rapidly developing local severe storms(LSS).A hyperspectral IR sounder onboard a geostationary satellite would provide four-dimensional atmospheric temperature,moisture,and wind profiles that have both high vertical resolution and high temporal/spatial resolutions.In this work,the added-value from a GEO-hyperspectral IR sounder is studied and discussed using a hybrid Observing System Simulation Experiment(OSSE)method.A hybrid OSSE is distinctively different from the traditional OSSE in that,(a)only future sensors are simulated from the nature run and(b)the forecasts can be evaluated using real observations.This avoids simulating the complicated observation characteristics of the current systems(but not the new proposed system)and allows the impact to be assessed against real observations.The Cross-track Infrared Sounder(CrIS)full spectral resolution(FSR)is assumed to be onboard a GEO for the impact studies,and the GEO CrIS radiances are simulated from the ECMWF Reanalysis v5(ERA5)with the hyperspectral IR all-sky radiative transfer model(HIRTM).The simulated GEO CrIS radiances are validated and the hybrid OSSE system is verified before the impact assessment.Two LSS cases from 2018 and 2019 are selected to evaluate the value-added impacts from the GEO CrIS-FSR data.The impact studies show improved atmospheric temperature,moisture,and precipitation forecasts,along with some improvements in the wind forecasts.An added-value,consisting of an overall 5%Root Mean Square Error(RMSE)reduction,was found when a GEO CrIS-FSR is used in replacement of LEO ones indicat-ing the potential for applications of data from a GEO hyperspectral IR sounder to improve local severe storm forecasts.展开更多
在业务和技术的双重驱动下,通信行业聚焦网络智慧运营,以自智网络为牵引推进网络智慧运营是行业共识。首先,分析了运营支撑系统(operational support system,OSS)是自智网络三层架构的核心,且提升自智网络水平等级的关键是提升OSS智能...在业务和技术的双重驱动下,通信行业聚焦网络智慧运营,以自智网络为牵引推进网络智慧运营是行业共识。首先,分析了运营支撑系统(operational support system,OSS)是自智网络三层架构的核心,且提升自智网络水平等级的关键是提升OSS智能化能力。其次,详细阐述了OSS产品业务范围界定方法,分析了自智网络牵引的OSS产品的能力短板、提出了OSS产品能力体系化规划提升等具体实施方案,并以宽带业务数字化运营价值场景为例详细描述了该方案。最后,论述了自智网络牵引的OSS智能化能力图谱。面向自智网络提升OSS智能化能力可有效牵引OSS研发方向,指导运营商OSS产品的规划和研发。展开更多
The present work aims is to propose a solution for automating updates (MAJ) of the radio parameters of the ATOLL database from the OSS NetAct using Parsing. Indeed, this solution will be operated by the RAN (Radio Acc...The present work aims is to propose a solution for automating updates (MAJ) of the radio parameters of the ATOLL database from the OSS NetAct using Parsing. Indeed, this solution will be operated by the RAN (Radio Access Network) service of mobile operators, which ensures the planning and optimization of network coverage. The overall objective of this study is to make synchronous physical data of the sites deployed in the field with the ATOLL database which contains all the data of the coverage of the mobile networks of the operators. We have made an application that automates, updates with the following functionalities: import of radio parameters with the parsing method we have defined, visualization of data and its export to the Template of the ATOLL database. The results of the tests and validations of our application developed for a 4G network have made it possible to have a solution that performs updates with a constraint on the size of data to be imported. Our solution is a reliable resource for updating the databases containing the radio parameters of the network at all mobile operators, subject to a limitation in terms of the volume of data to be imported.展开更多
利用基于集合预报的相关方法对2009年7月23日发生在北京及周边地区的暴雨过程的观测敏感区进行了分析。通过WRF(Weather Research Forecast)三维变分方法对初始场进行随机扰动,形成30个初始集合样本,做了预报时效为12 h的集合预报。利...利用基于集合预报的相关方法对2009年7月23日发生在北京及周边地区的暴雨过程的观测敏感区进行了分析。通过WRF(Weather Research Forecast)三维变分方法对初始场进行随机扰动,形成30个初始集合样本,做了预报时效为12 h的集合预报。利用该方法分析检验区(北京及周边地区)累积降水[14:00(北京时间,下同)至20:00]相对于初始时刻(08:00)各基本要素的敏感性,确定感性要素及其对应的区域。研究发现初步确定的敏感性要素为水汽和温度,对应的敏感区分别位于北京的西南侧和北京的东北侧,且通过实况分析可知初步确定的敏感性要素和对应的敏感区具有明确的物理意义。还进一步通过观测系统模拟试验(OSSE)的资料同化验证所确定的敏感区,结果表明在水汽对应的敏感区内同化水汽对降水的预报结果有明显的改进;在温度对应的敏感区内同化温度,降水的预报准确率有了明显的提高,说明了初步确定的敏感性要素和敏感区的正确性。在水汽对应的敏感区内同化水汽的同时在温度对应的敏感区内同化温度,使降水预报的技巧有大幅度的提高,说明了温度和水汽的共同作用对提高降水预报准确率贡献最大。因此,通过基于集合预报的相关方法能够快速的确定敏感区。研究结果将为确定北京暴雨的观测敏感区提供参考。展开更多
基金supported by the NESDIS OPPA OSSE program (Grant No. NA15NES4320001)
文摘Accurate atmospheric temperature and moisture information with high temporal/spatial resolutions are two of the key parameters needed in regional numerical weather prediction(NWP) models to reliably predict high-impact weather events such as local severe storms(LSSs). High spectral resolution or hyperspectral infrared(HIR) sounders from geostationary orbit(GEO) provide an unprecedented source of near time-continuous, three-dimensional information on the dynamic and thermodynamic atmospheric fields—an important benefit for nowcasting and NWP-based forecasting. In order to demonstrate the value of GEO HIR sounder radiances on LSS forecasts, a quick regional OSSE(Observing System Simulation Experiment)framework has been developed, including high-resolution nature run generation, synthetic observation simulation and validation, and impact study on LSS forecasts. Results show that, on top of the existing LEO(low earth orbit) sounders, a GEO HIR sounder may provide value-added impact [a reduction of 3.56% in normalized root-mean-square difference(RMSD)] on LSS forecasts due to large spatial coverage and high temporal resolution, even though the data are assimilated every 6 h with a thinning of 60 km. Additionally, more frequent assimilations and smaller thinning distances allow more observations to be assimilated, and may further increase the positive impact from a GEO HIR sounder. On the other hand, with denser and more frequent observations assimilated, it becomes more difficult to handle the spatial error correlation in observations and gravity waves due to the limitations of current assimilation and forecast systems(such as a static background error covariance). The peak reduction of 4.6% in normalized RMSD is found when observations are assimilated every 3 h with a thinning distance of 30 km.
基金This work is supported by the NOAA GeoXO program(NA15NES4320001).
文摘High spectral resolution(or hyperspectral)infrared(IR)sounders onboard low earth orbiting satellites provide high vertical resolution atmospheric information for numerical weather prediction(NWP)models.In contrast,imagers on geostationary(GEO)satellites provide high temporal and spatial resolution which are important for monitoring the moisture associated with severe weather systems,such as rapidly developing local severe storms(LSS).A hyperspectral IR sounder onboard a geostationary satellite would provide four-dimensional atmospheric temperature,moisture,and wind profiles that have both high vertical resolution and high temporal/spatial resolutions.In this work,the added-value from a GEO-hyperspectral IR sounder is studied and discussed using a hybrid Observing System Simulation Experiment(OSSE)method.A hybrid OSSE is distinctively different from the traditional OSSE in that,(a)only future sensors are simulated from the nature run and(b)the forecasts can be evaluated using real observations.This avoids simulating the complicated observation characteristics of the current systems(but not the new proposed system)and allows the impact to be assessed against real observations.The Cross-track Infrared Sounder(CrIS)full spectral resolution(FSR)is assumed to be onboard a GEO for the impact studies,and the GEO CrIS radiances are simulated from the ECMWF Reanalysis v5(ERA5)with the hyperspectral IR all-sky radiative transfer model(HIRTM).The simulated GEO CrIS radiances are validated and the hybrid OSSE system is verified before the impact assessment.Two LSS cases from 2018 and 2019 are selected to evaluate the value-added impacts from the GEO CrIS-FSR data.The impact studies show improved atmospheric temperature,moisture,and precipitation forecasts,along with some improvements in the wind forecasts.An added-value,consisting of an overall 5%Root Mean Square Error(RMSE)reduction,was found when a GEO CrIS-FSR is used in replacement of LEO ones indicat-ing the potential for applications of data from a GEO hyperspectral IR sounder to improve local severe storm forecasts.
文摘在业务和技术的双重驱动下,通信行业聚焦网络智慧运营,以自智网络为牵引推进网络智慧运营是行业共识。首先,分析了运营支撑系统(operational support system,OSS)是自智网络三层架构的核心,且提升自智网络水平等级的关键是提升OSS智能化能力。其次,详细阐述了OSS产品业务范围界定方法,分析了自智网络牵引的OSS产品的能力短板、提出了OSS产品能力体系化规划提升等具体实施方案,并以宽带业务数字化运营价值场景为例详细描述了该方案。最后,论述了自智网络牵引的OSS智能化能力图谱。面向自智网络提升OSS智能化能力可有效牵引OSS研发方向,指导运营商OSS产品的规划和研发。
文摘The present work aims is to propose a solution for automating updates (MAJ) of the radio parameters of the ATOLL database from the OSS NetAct using Parsing. Indeed, this solution will be operated by the RAN (Radio Access Network) service of mobile operators, which ensures the planning and optimization of network coverage. The overall objective of this study is to make synchronous physical data of the sites deployed in the field with the ATOLL database which contains all the data of the coverage of the mobile networks of the operators. We have made an application that automates, updates with the following functionalities: import of radio parameters with the parsing method we have defined, visualization of data and its export to the Template of the ATOLL database. The results of the tests and validations of our application developed for a 4G network have made it possible to have a solution that performs updates with a constraint on the size of data to be imported. Our solution is a reliable resource for updating the databases containing the radio parameters of the network at all mobile operators, subject to a limitation in terms of the volume of data to be imported.
文摘利用基于集合预报的相关方法对2009年7月23日发生在北京及周边地区的暴雨过程的观测敏感区进行了分析。通过WRF(Weather Research Forecast)三维变分方法对初始场进行随机扰动,形成30个初始集合样本,做了预报时效为12 h的集合预报。利用该方法分析检验区(北京及周边地区)累积降水[14:00(北京时间,下同)至20:00]相对于初始时刻(08:00)各基本要素的敏感性,确定感性要素及其对应的区域。研究发现初步确定的敏感性要素为水汽和温度,对应的敏感区分别位于北京的西南侧和北京的东北侧,且通过实况分析可知初步确定的敏感性要素和对应的敏感区具有明确的物理意义。还进一步通过观测系统模拟试验(OSSE)的资料同化验证所确定的敏感区,结果表明在水汽对应的敏感区内同化水汽对降水的预报结果有明显的改进;在温度对应的敏感区内同化温度,降水的预报准确率有了明显的提高,说明了初步确定的敏感性要素和敏感区的正确性。在水汽对应的敏感区内同化水汽的同时在温度对应的敏感区内同化温度,使降水预报的技巧有大幅度的提高,说明了温度和水汽的共同作用对提高降水预报准确率贡献最大。因此,通过基于集合预报的相关方法能够快速的确定敏感区。研究结果将为确定北京暴雨的观测敏感区提供参考。
