Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostation...Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostationary(GEO)weather satellites provide continuous observations with seamless coverage with advanced imager, despite their limited capability to penetrate clouds. Combining satellite and ground-radar observations could exploit the advantages of both techniques, providing tracking capability close to that of ground radar while maintaining full spatial coverage. This study presents a novel method called Multi-dimensional satellite Observation information for Radar Estimation(MORE) to reconstruct radar composite reflectivity(CREF). Deep learning techniques are important components of MORE for estimating CREF from China's Fengyun-4B(FY-4B) GEO satellite observations. Two models are developed: an infraredonly(IR-Single) model available for all times, and a visible-infrared(VIS+IR) model for daytime applications. These models incorporate multi-dimensional satellite observation information, including temporal, spatial, spectral, and viewing angle information, to enhance the accuracy of radar echo reconstruction. Results demonstrate that the VIS+IR model outperforms the IR-Single model, and both models achieves a root-mean-square error(RMSE) of less than 6 dBZ and a coefficient of determination(R~2) of greater than 0.7. The models effectively reconstruct radar echoes, including strong echoes exceeding 50 dBZ, and show good agreement with precipitation data in radar-blind areas. This study offers a valuable solution for severe weather monitoring and tracking in regions lacking ground-based radar observations, and provides a potential tool for enhanced data assimilation in numerical weather prediction(NWP) models.展开更多
Precipitable water vapor(PWV)is a key component of the Earth’s climate system,playing a vital role in weather,climate,and hydrological cycling.Passive microwave remote sensing offers a promising approach to measure a...Precipitable water vapor(PWV)is a key component of the Earth’s climate system,playing a vital role in weather,climate,and hydrological cycling.Passive microwave remote sensing offers a promising approach to measure all-sky PWV,though it remains challenging over land.Building on our previous development of a machine learning algorithm,we have created a global terrestrial PWV dataset using measurements from the MicroWave Radiation Imager(MWRI)aboard three FY-3 satellite series(FY-3B,FY-3C and FY-3D).The dataset spans from 2012 to 2020 at a spatial resolution of 0.25°×0.25°.It was validated against SuomiNet GPS and IGRA2(Integrated Global Radiosonde Archive Version 2)PWV products,achieving root-mean-square errors(RMSEs)of 4.47 and 3.89 mm,respectively,with RMSE values ranging from 2.90 to 5.49 mm across diverse surface conditions.As an all-weather PWV product with high-precision,the MWRI PWV dataset addresses gaps in global passive microwave-based terrestrial PWV observations,offering significant value for atmospheric research,climate modeling,hydrological studies,and beyond.展开更多
目的:对80例原发中枢神经系统弥漫大B细胞淋巴瘤(primary diffuse large B cell lymphoma of the central nervous system,PCNS DLBCL)进行临床病理学回顾性研究、免疫表型检测及EB病毒(Epstein-Barr virus,EBV)感染检测。旨在探讨其与...目的:对80例原发中枢神经系统弥漫大B细胞淋巴瘤(primary diffuse large B cell lymphoma of the central nervous system,PCNS DLBCL)进行临床病理学回顾性研究、免疫表型检测及EB病毒(Epstein-Barr virus,EBV)感染检测。旨在探讨其与预后的关系。方法:对80例PCNS DLBCL进行免疫表型检测及EB病毒检测,并进行Hans、Choi和Tally分型、统计学单因素和多因素预后分析。结果:Bcl-2、CD10、Bcl-6、Mum-1、GCET-1、BLIMP-1、FOXP-1和LMO-2的表达率分别为46.1%、8.8%、75.0%、57.5%、27.5%、11.3%、75.0%和26.3%;Ki-67指数为30%~95%,中位数为80%。Hans、Choi和Tally分型中Non-GCB型/ABC型弥漫大B细胞淋巴瘤(diffuse large B cell lymphoma,DLBCL)(63.9%、79.2%和90.0%)为最常见的亚型。EBV及EBER1/2-ISH的表达率均为3.8%。58.8%的患者术后未行其它治疗,其1年、2年和5年生存率分别为36.3%、16.4%和4.6%。术后是否行其它治疗、采用甲氨喋呤(methotrexate,MTX)治疗和环磷酰胺+多柔比星+长春新碱+泼尼松龙(cyclophosphamide,doxorubicin,vincristine,and prednisone,CHOP)治疗是有统计学意义的预后相关因素(P均<0.001)。结论:80例PCNS DLBCL患者年龄较国内外报道的小;以Non-GCB型/ABC型DLBCL为主;个别病例检出EB病毒感染;术后未行其它治疗组、未采用MTX治疗组和未CHOP治疗组的预后较差。展开更多
基金supported by the National Natural Science Foundation of China (NSFC) (Grant No.42205044)Feng Yun Application Pioneering Project (FY-APP) Innovation Center for Feng Yun Meteorological Satellite (FYSIC) Special Project (FY-APP-XC-2023.04)the Wuxi University Research Start-up Fund for Recruited Talent。
文摘Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostationary(GEO)weather satellites provide continuous observations with seamless coverage with advanced imager, despite their limited capability to penetrate clouds. Combining satellite and ground-radar observations could exploit the advantages of both techniques, providing tracking capability close to that of ground radar while maintaining full spatial coverage. This study presents a novel method called Multi-dimensional satellite Observation information for Radar Estimation(MORE) to reconstruct radar composite reflectivity(CREF). Deep learning techniques are important components of MORE for estimating CREF from China's Fengyun-4B(FY-4B) GEO satellite observations. Two models are developed: an infraredonly(IR-Single) model available for all times, and a visible-infrared(VIS+IR) model for daytime applications. These models incorporate multi-dimensional satellite observation information, including temporal, spatial, spectral, and viewing angle information, to enhance the accuracy of radar echo reconstruction. Results demonstrate that the VIS+IR model outperforms the IR-Single model, and both models achieves a root-mean-square error(RMSE) of less than 6 dBZ and a coefficient of determination(R~2) of greater than 0.7. The models effectively reconstruct radar echoes, including strong echoes exceeding 50 dBZ, and show good agreement with precipitation data in radar-blind areas. This study offers a valuable solution for severe weather monitoring and tracking in regions lacking ground-based radar observations, and provides a potential tool for enhanced data assimilation in numerical weather prediction(NWP) models.
基金supported by the National Natural Science Foundation of China(Grant Nos.42075079 and U2442214).
文摘Precipitable water vapor(PWV)is a key component of the Earth’s climate system,playing a vital role in weather,climate,and hydrological cycling.Passive microwave remote sensing offers a promising approach to measure all-sky PWV,though it remains challenging over land.Building on our previous development of a machine learning algorithm,we have created a global terrestrial PWV dataset using measurements from the MicroWave Radiation Imager(MWRI)aboard three FY-3 satellite series(FY-3B,FY-3C and FY-3D).The dataset spans from 2012 to 2020 at a spatial resolution of 0.25°×0.25°.It was validated against SuomiNet GPS and IGRA2(Integrated Global Radiosonde Archive Version 2)PWV products,achieving root-mean-square errors(RMSEs)of 4.47 and 3.89 mm,respectively,with RMSE values ranging from 2.90 to 5.49 mm across diverse surface conditions.As an all-weather PWV product with high-precision,the MWRI PWV dataset addresses gaps in global passive microwave-based terrestrial PWV observations,offering significant value for atmospheric research,climate modeling,hydrological studies,and beyond.
文摘目的:对80例原发中枢神经系统弥漫大B细胞淋巴瘤(primary diffuse large B cell lymphoma of the central nervous system,PCNS DLBCL)进行临床病理学回顾性研究、免疫表型检测及EB病毒(Epstein-Barr virus,EBV)感染检测。旨在探讨其与预后的关系。方法:对80例PCNS DLBCL进行免疫表型检测及EB病毒检测,并进行Hans、Choi和Tally分型、统计学单因素和多因素预后分析。结果:Bcl-2、CD10、Bcl-6、Mum-1、GCET-1、BLIMP-1、FOXP-1和LMO-2的表达率分别为46.1%、8.8%、75.0%、57.5%、27.5%、11.3%、75.0%和26.3%;Ki-67指数为30%~95%,中位数为80%。Hans、Choi和Tally分型中Non-GCB型/ABC型弥漫大B细胞淋巴瘤(diffuse large B cell lymphoma,DLBCL)(63.9%、79.2%和90.0%)为最常见的亚型。EBV及EBER1/2-ISH的表达率均为3.8%。58.8%的患者术后未行其它治疗,其1年、2年和5年生存率分别为36.3%、16.4%和4.6%。术后是否行其它治疗、采用甲氨喋呤(methotrexate,MTX)治疗和环磷酰胺+多柔比星+长春新碱+泼尼松龙(cyclophosphamide,doxorubicin,vincristine,and prednisone,CHOP)治疗是有统计学意义的预后相关因素(P均<0.001)。结论:80例PCNS DLBCL患者年龄较国内外报道的小;以Non-GCB型/ABC型DLBCL为主;个别病例检出EB病毒感染;术后未行其它治疗组、未采用MTX治疗组和未CHOP治疗组的预后较差。
