An X-band phased-array meteorological radar （XPAR） was developed in China and will be installed in an airplane to observe precipitation systems for research purposes.In order to examine the observational capability ...An X-band phased-array meteorological radar （XPAR） was developed in China and will be installed in an airplane to observe precipitation systems for research purposes.In order to examine the observational capability of the XPAR and to test the operating mode and calibration before installation in the airplane,a mobile X-band Doppler radar （XDR） and XPAR were installed at the same site to observe convective precipitation events.Nearby S-band operational radar （SA） data were also collected to examine the reflectivity bias of XPAR.An algorithm for quantitative analysis of reflectivity and velocity differences and radar sensitivity of XPAR is presented.The reflectivity and velocity biases of XPAR are examined with SA and XDR.Reflectivity sensitivities,the horizontal and vertical structures of reflectivity by the three radars are compared and analyzed.The results indicated that while the XPRA with different operating modes can capture the main characteristic of 3D structures of precipitation,and the averaged reflectivity differences between XPAR and XDR,and XDR and SA,were 0.4 dB and 6.6 dB on 13 July and-4.5 dB and 5.1 dB on 2 August 2012,respectively.The minimum observed reflectivities at a range of 50 km for XPAR,XDR and SA were about 15.4 dBZ,13.5 dBZ and-3.5 dBZ,respectively.The bias of velocity between XPAR and XDR was negligible.This study provides a possible method for the quantitative comparison of the XPAR data,as well as the sensitivity of reflectivity,calibration,gain and bias introduced by pulse compression.展开更多
A prototype space-based cloud radar has been a precipitation system over Tianjin, China in July developed and was installed on an airplane to observe 2010. Ground-based S-band and Ka-band radars were used to examine t...A prototype space-based cloud radar has been a precipitation system over Tianjin, China in July developed and was installed on an airplane to observe 2010. Ground-based S-band and Ka-band radars were used to examine the observational capability of the prototype. A cross-comparison algorithm between different wavelengths, spatial resolutions and platform radars is presented. The reflectivity biases, correlation coefficients and standard deviations between the radars are analyzed. The equivalent reflectivity bias between the S- and Ka-band radars were simulated with a given raindrop size distribution. The results indicated that reflectivity bias between the S- and Ka-band radars due to scattering properties was less than 5 dB, and for weak precipitation the bias was negligible. The prototype space-based cloud radar was able to measure a reasonable vertical profile of reflectivity, but the reflectivity below an altitude of 1.5 km above ground level was obscured by ground clutter. The measured refiectivity by the prototype space-based cloud radar was approximately 10.9 dB stronger than that by the S-band Doppler radar （SA radar）, and 13.7 dB stronger than that by the ground-based cloud radar. The reflectivity measured by the SA radar was 0.4 dB stronger than that by the ground-based cloud radar. This study could provide a method for the quantitative examination of the observation ability for space-based radars.展开更多
Millimeter-wavelength radar has proved to be an effective instrument for cloud observation and research. In this study, 8-mm-wavelength cloud radar （MMCR） with Doppler and polarization capabilities was used to inves...Millimeter-wavelength radar has proved to be an effective instrument for cloud observation and research. In this study, 8-mm-wavelength cloud radar （MMCR） with Doppler and polarization capabilities was used to investigate cloud dynamics in China for the first time. Its design, system specifications, calibration, and application in measuring clouds associated with typhoon are discussed in this article. The cloud radar measurements of radar reflectivity （Z）, Doppler velocity （Vr）, velocity spectrum width （Sw） and the depolar-ization ratio （LDR） at vertical incidence were used to analyze the microphysical and dynamic processes of the cloud system and precipitation associated with Typhoon Nuri, which occurred in southern China in August 2008. The results show the reflectivity observed using MMCR to be consistent with the echo height and the melting-layer location data obtained by the nearby China S-band new-generation weather radar （SA）, but the Ka-band MMCR provided more detailed structural information about clouds and weak precipitation data than did the SA radar. The variation of radar reflectivity and LDR in vertical structure reveals the transformation of particle phase from ice to water. The vertical velocity and velocity spectrum width of MMCR observations indicate an updraft and strong turbulence in the stratiform cloud layer. MMCR provides a valuable new technology for meteorological research in China.展开更多
DATA AND COMPUTILITY ISLANDS IN REMOTE SENSING FOR EO The rapid advancement of Earth observation(EO)capabilities is driving an explosive increase in remote sensing data.There is an urgent need for advanced processing ...DATA AND COMPUTILITY ISLANDS IN REMOTE SENSING FOR EO The rapid advancement of Earth observation(EO)capabilities is driving an explosive increase in remote sensing data.There is an urgent need for advanced processing techniques to unleash their application value.1 Generalist EO intelligence refers to the ability to provide unified support for qualitative interpretation,quantitative inversion,and interactive dialogue across diverse EO data and tasks.It has attracted significant attention recently,prompting academia,industry,and government to invest substantial resources.2 Through developing remote sensing foundation models(RSFMs),generalist EO intelligence can ultimately offer humanity a shared spatial-temporal intelligence service in various fields(e.g.,agriculture,forestry,and oceanography).3 However,a critical question remains:have we truly unleashed the potential of RSFMs for generalist EO intelligence?Despite the vast volume of remote sensing data,their distribution is often fragmented and decentralized due to privacy concerns,storage bottlenecks,industrial competition,and geo-information security.This fragmentation leads to data islands,which limit the full utilization of multi-source remote sensing data.Moreover,computility(i.e.,computational resources)typically develops in isolation,inadequately supporting the large-scale training and application of RSFMs.展开更多
基金funded by National High-Tech Research and Development Projects (863 Grant No. 2007AA061901)+2 种基金the National Key Program for Developing Basic Sciences (Grant No. 2012CB417202)the National Natural Science Foundation of China (Grant No. 41175038)the Public Welfare Meteorological Special Project (Grant No. GYHY201106046)
文摘An X-band phased-array meteorological radar （XPAR） was developed in China and will be installed in an airplane to observe precipitation systems for research purposes.In order to examine the observational capability of the XPAR and to test the operating mode and calibration before installation in the airplane,a mobile X-band Doppler radar （XDR） and XPAR were installed at the same site to observe convective precipitation events.Nearby S-band operational radar （SA） data were also collected to examine the reflectivity bias of XPAR.An algorithm for quantitative analysis of reflectivity and velocity differences and radar sensitivity of XPAR is presented.The reflectivity and velocity biases of XPAR are examined with SA and XDR.Reflectivity sensitivities,the horizontal and vertical structures of reflectivity by the three radars are compared and analyzed.The results indicated that while the XPRA with different operating modes can capture the main characteristic of 3D structures of precipitation,and the averaged reflectivity differences between XPAR and XDR,and XDR and SA,were 0.4 dB and 6.6 dB on 13 July and-4.5 dB and 5.1 dB on 2 August 2012,respectively.The minimum observed reflectivities at a range of 50 km for XPAR,XDR and SA were about 15.4 dBZ,13.5 dBZ and-3.5 dBZ,respectively.The bias of velocity between XPAR and XDR was negligible.This study provides a possible method for the quantitative comparison of the XPAR data,as well as the sensitivity of reflectivity,calibration,gain and bias introduced by pulse compression.
基金the Chinese Academy of Meteorological Sciences Basic Scientific and Operational Project(observation and retrieval methods of microphysics and dynamic parameters of cloud and precipitation with multi-wavelength remote sensing)the National Key Program for Developing Basic Sciences under Grant 2012CB417202+1 种基金the Meteorological Special Project(study and data process and key technology for space-borne precipitation radar)the National Natural Science Foundation of China(Grant Nos.40775021 and 41075098)
文摘A prototype space-based cloud radar has been a precipitation system over Tianjin, China in July developed and was installed on an airplane to observe 2010. Ground-based S-band and Ka-band radars were used to examine the observational capability of the prototype. A cross-comparison algorithm between different wavelengths, spatial resolutions and platform radars is presented. The reflectivity biases, correlation coefficients and standard deviations between the radars are analyzed. The equivalent reflectivity bias between the S- and Ka-band radars were simulated with a given raindrop size distribution. The results indicated that reflectivity bias between the S- and Ka-band radars due to scattering properties was less than 5 dB, and for weak precipitation the bias was negligible. The prototype space-based cloud radar was able to measure a reasonable vertical profile of reflectivity, but the reflectivity below an altitude of 1.5 km above ground level was obscured by ground clutter. The measured refiectivity by the prototype space-based cloud radar was approximately 10.9 dB stronger than that by the S-band Doppler radar （SA radar）, and 13.7 dB stronger than that by the ground-based cloud radar. The reflectivity measured by the SA radar was 0.4 dB stronger than that by the ground-based cloud radar. This study could provide a method for the quantitative examination of the observation ability for space-based radars.
基金National Meteorological Information Centerfunded by the National Natural Science Foundation of China (Grant No. 40775021)+2 种基金the National Key Basic Research and Development Project of China (Grant No. 2004CB418305)National 863 plans project "Re-search on Application System of Airborne Radar"the meteorological project "Tropical West Pacific Ocean Observation and Predictability"
文摘Millimeter-wavelength radar has proved to be an effective instrument for cloud observation and research. In this study, 8-mm-wavelength cloud radar （MMCR） with Doppler and polarization capabilities was used to investigate cloud dynamics in China for the first time. Its design, system specifications, calibration, and application in measuring clouds associated with typhoon are discussed in this article. The cloud radar measurements of radar reflectivity （Z）, Doppler velocity （Vr）, velocity spectrum width （Sw） and the depolar-ization ratio （LDR） at vertical incidence were used to analyze the microphysical and dynamic processes of the cloud system and precipitation associated with Typhoon Nuri, which occurred in southern China in August 2008. The results show the reflectivity observed using MMCR to be consistent with the echo height and the melting-layer location data obtained by the nearby China S-band new-generation weather radar （SA）, but the Ka-band MMCR provided more detailed structural information about clouds and weak precipitation data than did the SA radar. The variation of radar reflectivity and LDR in vertical structure reveals the transformation of particle phase from ice to water. The vertical velocity and velocity spectrum width of MMCR observations indicate an updraft and strong turbulence in the stratiform cloud layer. MMCR provides a valuable new technology for meteorological research in China.
基金supported by the National Natural Science Foundation of China under grants 42030102 and 42371321 and by the Ant Group。
文摘DATA AND COMPUTILITY ISLANDS IN REMOTE SENSING FOR EO The rapid advancement of Earth observation(EO)capabilities is driving an explosive increase in remote sensing data.There is an urgent need for advanced processing techniques to unleash their application value.1 Generalist EO intelligence refers to the ability to provide unified support for qualitative interpretation,quantitative inversion,and interactive dialogue across diverse EO data and tasks.It has attracted significant attention recently,prompting academia,industry,and government to invest substantial resources.2 Through developing remote sensing foundation models(RSFMs),generalist EO intelligence can ultimately offer humanity a shared spatial-temporal intelligence service in various fields(e.g.,agriculture,forestry,and oceanography).3 However,a critical question remains:have we truly unleashed the potential of RSFMs for generalist EO intelligence?Despite the vast volume of remote sensing data,their distribution is often fragmented and decentralized due to privacy concerns,storage bottlenecks,industrial competition,and geo-information security.This fragmentation leads to data islands,which limit the full utilization of multi-source remote sensing data.Moreover,computility(i.e.,computational resources)typically develops in isolation,inadequately supporting the large-scale training and application of RSFMs.
