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
目的比较硫酸镁钠钾口服液(OSS)与复方聚乙二醇电解质散(PEG)在结肠镜检查前肠道准备中的安全性和有效性。方法回顾性分析2023月9月-2024年9月该院采用OSS与PEG在肠镜检查行前肠道准备的患者2000例。根据不同肠道准备药物,将患者分为OSS...目的比较硫酸镁钠钾口服液(OSS)与复方聚乙二醇电解质散(PEG)在结肠镜检查前肠道准备中的安全性和有效性。方法回顾性分析2023月9月-2024年9月该院采用OSS与PEG在肠镜检查行前肠道准备的患者2000例。根据不同肠道准备药物,将患者分为OSS组(1000例,口服OSS)和PEG组(1000例,口服4 L PEG)。比较两组患者肠道清洁度、清洁效果、肠腔气泡、结肠镜检查阳性率和不良反应发生率。结果OSS组肠道准备成功率为92.5%(925/1000),PEG组肠道准备成功率为91.7%(917/1000),两组患者比较,差异无统计学意义(P>0.05);两组患者左侧结肠波士顿肠道准备量表(BBPS)评分比较,差异无统计学意义(P>0.05),OSS组BBPS总分,以及中段和右侧结肠BBPS评分明显高于PEG组,差异均有统计学意义(P<0.05);OSS组气泡评估满意率为96.2%,高于PEG组的90.3%,差异有统计学意义(P<0.05);两组患者结肠镜检查阳性率和不良反应发生率比较,差异均无统计学意义(P>0.05)。结论OSS在肠道准备方面具有较好的去泡效果,清洁效果与PEG相当,且有较高的安全性。展开更多
相较于5G时代,运营商的运营支撑系统(operation support systems,OSS)将在6G时代迎来算力、存力及网络实时分析等全新数据的融入。针对6G网络数据量庞大、格式多元化及实时性要求严苛等现状,提出6G OSS域基于数据面的数据治理体系构建思...相较于5G时代,运营商的运营支撑系统(operation support systems,OSS)将在6G时代迎来算力、存力及网络实时分析等全新数据的融入。针对6G网络数据量庞大、格式多元化及实时性要求严苛等现状,提出6G OSS域基于数据面的数据治理体系构建思路,并提出具体方案,包括6G OSS域数据治理顶层战略设计、数据面功能架构设计、数据治理能力开发底座设计、数据治理成果智能应用设计,通过知识图谱赋予数据快速响应和推理能力,同时利用专家知识和人工智能(artificial intelligence,AI)算法构建6G OSS域特征数据集,为进一步的网络智能感知、预测、优化提供重要支撑,以期为数据治理工作提供参考。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
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.
文摘目的比较硫酸镁钠钾口服液(OSS)与复方聚乙二醇电解质散(PEG)在结肠镜检查前肠道准备中的安全性和有效性。方法回顾性分析2023月9月-2024年9月该院采用OSS与PEG在肠镜检查行前肠道准备的患者2000例。根据不同肠道准备药物,将患者分为OSS组(1000例,口服OSS)和PEG组(1000例,口服4 L PEG)。比较两组患者肠道清洁度、清洁效果、肠腔气泡、结肠镜检查阳性率和不良反应发生率。结果OSS组肠道准备成功率为92.5%(925/1000),PEG组肠道准备成功率为91.7%(917/1000),两组患者比较,差异无统计学意义(P>0.05);两组患者左侧结肠波士顿肠道准备量表(BBPS)评分比较,差异无统计学意义(P>0.05),OSS组BBPS总分,以及中段和右侧结肠BBPS评分明显高于PEG组,差异均有统计学意义(P<0.05);OSS组气泡评估满意率为96.2%,高于PEG组的90.3%,差异有统计学意义(P<0.05);两组患者结肠镜检查阳性率和不良反应发生率比较,差异均无统计学意义(P>0.05)。结论OSS在肠道准备方面具有较好的去泡效果,清洁效果与PEG相当,且有较高的安全性。
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。
