Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    2017, Vol. 29 Issue (4) : 1-5     DOI: 10.6046/gtzyyg.2017.04.01
|
A review on geostationary earth orbit microwave atmospheric sounding technology
QIAN Bo1, CAO Anjie2, WU Ying1, WANG Pengkai1
1. Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing 210044, China;
2. Shanghai Institute of Satellite Engineering, Shanghai 200240, China
Download: PDF(680 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  The cloudy and raining atmosphere can be detected by the microwave atmospheric sounding system in polar orbit meteorology satellites, but its long sounding cycle is a great limit for small and medium scale of severe weather (SMSSW) monitoring. Although SMSSW can be detected by geostationary earth orbit satellites (GEOS) with high temporal resolution, internal atmospheric parameters cannot be acquired because of the lack of microwave sounder on GEOS. Working in concert, microwave atmospheric sounding and GEOS at high-temporal resolution together comprise the geostationary earth orbit microwave atmospheric sounding (GEOMAS) system. Developing GEOMAS technology is of great significance for improving SMSSW forecast in all-weather and all-time sounding. In this paper, the research status on GEOMAS was described, the difficulties and challenges of GEOMAS were recounted, the advantages and disadvantages of synthetic aperture antenna system (SAAS) and real aperture antenna system (RAAS) were analyzed and the prospects for GEOMAS development were discussed.
Keywords Wuhan City      construction land expansion      remote sensing      standard deviational ellipse(SDE)      spatial variation     
:  P412  
Issue Date: 04 December 2017
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
CHANG Bianrong
LI Rendong
Cite this article:   
CHANG Bianrong,LI Rendong. A review on geostationary earth orbit microwave atmospheric sounding technology[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(4): 1-5.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2017.04.01     OR     https://www.gtzyyg.com/EN/Y2017/V29/I4/1
[1] 卢乃锰.静止轨道微波探测——风云气象卫星发展的新挑战[EB/OL].(2012-09-19).http://www.meeting.edu.cn/meeting/media/flashmediadetail.jsp?mediaId=11912&url=qixiang2012video/3.flv.
Lu N M.Geostationary earth orbit microwave atmospheric sounding:A new challenge for Fengyun meteorological satellites[EB/OL].(2012-09-19).http://www.meeting.edu.cn/meeting/media/flashmediadetail.jsp?mediaId=11912&url=qixiang2012video/3.flv.
[2] NASA官网对AMSU仪器的介绍[EB/OL].http://disc.sci.gsfc.nasa.gov/AIRS/documentation/amsu_instrument_guide.shtml.
An introduction on AMSU instrument in NASA official website[EB/OL].http://disc.sci.gsfc.nasa.gov/AIRS/documentation/amsu_instrument_guide.shtml.
[3] Muth C,Lee P S,Shiue J C,et al.Advanced technology microwave sounder on NPOESS and NPP[C]//Proceedings of the 2004 IEEE International Geoscience and Remote Sensing Symposium. Anchorage,AK,USA:IEEE,2004:2454-2458.
[4] 杨 军,董超华,卢乃锰,等.中国新一代极轨气象卫星——风云三号[J].气象学报,2009,67(4):501-509.
Yang J,Dong C H,Lu N M,et al.FY-3A:The new generation polar-orbiting meteorological satellite of China[J].Acta Meteorologica Sinica,2009,67(4):501-509.
[5] Staelin D H,Rosenkranz P W.Applications review panel:High resolution passive microwave satellites[R].Report for NASA contract NAS5-23677.Cambridge,MA:MIT Press,1978.
[6] Chedin A,Pick D,Rizzi R.Definition study and impact analysis of a microwave radiometer on a geostationary spacecraft[C]//ESA Second Generation Meteosat Definition Studies on Microwave and Infrared Vertical Sounders.Bracknell:STI,1986:58.
[7] Gasiewski A J,Barret J W,Bonanni P G,et al.Aircraft-based radiometric imaging of tropospheric temperature and precipitation using the 118.75 GHz oxygen resonance[J].Journal of Applied Meteorology,1990,29:620-632.
[8] Evans K F,Walter S J,Heymsfield A J,et al.Modeling of sub-millimeter passive remote sensing of cirrus clouds[J].Journal of Applied Meteorology,1998,37(2):184-205.
[9] Evans K F,Evans A H,Marshall B T,et al.The prospect for remote sensing of cirrus clouds with a submillimeter-wave spectrometer[J].Journal of Applied Meteorology,1999,38(5):514-525.
[10] Gurka J J,Heil J N.The national weather service operational requirements for the evolution of future NOAA operational geostationary satellites[C]//Processing of the 16th International Conference on Interactive Information and Processing Systems(IIPS) for Meteorology,Oceanography, and Hydrology.Copenhagen,Denmark:IIPS,2000:69-76.
[11] Boncyk W C,Wilson W J,Lambrigtsen B H.The enabling technologies of the geostationary synthetic aperture microwave sounder(GEO/SAMS)[C]//Proceedings of IEEE 2000 International Geoscience and Remote Sensing Symposium.Honolulu,HI,USA:IEEE,2000:3169-3171.
[12] Lambrigtsen B H.GEO/SAMS-the geostationary synthetic aperture microwave sounder[C]//Proceedings of IEEE 2000 International Geoscience and Remote Sensing Symposium.Honolulu,HI,USA:IEEE,2000,7:2984-2987.
[13] Lambrigtsen B,Gaier T,Kangaslahti P,et al.A geostationary microwave sounder for NASA and NOAA[C]//Proceedings of the 16th international TOVS study conference. Angra dos Reis,Brazil:International TOVS Working Group,2008.
[14] Lambrigtsen B H,Brown S T,Dinardo S J,et al.Progress in developing GeoSTAR:A microwave sounder for GOES-R[C]//Proceedings of Earth Observing Systems X. San Diego,CA,USA:SPIE,2005,5882:58820L.
[15] Lambrigtsen B H,Wilson W J,Tanner A B,et al.GeoSTAR:A microwave sounder for geostationary satellite[C]//Proceedings of 2004 IEEE International Geoscience and Remote Sensing Symposium.Anchorage,AK,USA:IEEE,2004:777-780.
[16] Tanner A B,Wilson W J,Lambrigsten B H,et al.Initial results of the geostationary synthetic thinned array radiometer(GeoSTAR) demonstrator instrument[J].IEEE Transactions on Geoscience and Remote Sensing,2007,45(7):1947-1957.
[17] Bizzarri B.MW/Sub-mm sounding form geostationary orbit[R].Report to EUMETSAT Science W.G.,EUM/STG/SWG/9/00/DOC/11,2000:11.
[18] Bizzarri B,Albin J G,David H S,et al.Requirements and perspectives for MW/Sub-mm sounding from geostationary satellite[C]//Proceedings of the 2002 EUMETSAT Meteorological Satellite Conference.Dublin,Ireland,2002:97-105.
[19] Christensen J,Carlstrom A,Ekstrom H,et al.GAS:The geostationary atmospheric sounder[C]//Proceedings of IEEE International Geoscience and Remote Sensing Symposium.Barcelona,Spain:IEEE,2007:223-226.
[20] 中华人民共和国科学技术部.前沿技术[C]//中国科学技术发展报告2009.北京:科学技术文献出版社,2010:136.
Ministry of Science and Technology of the PRC.Advanced technology[C]//2009 China Science and Technology Development Report.Beijing:Science and Technical Document Press,2010:136.
[21] 吴 季,刘 浩,孙伟英,等,综合孔径微波辐射计的技术发展及其应用展望[J].遥感技术与应用,2005,20(1):24-29.
Wu J,Liu H,Sun W Y,et al.Technical development and application prospect of synthetic aperture radiometer[J].Remote Sensing Technology and Application,2005,20(1):24-29.
[22] Liu H,Wu J,Zhang S W,et al.The geostationary interferometric microwave sounder(GIMS):Instrument overview and recent progress[C]//Proceedings of 2011 IEEE International Geoscience and Remote Sensing Symposium.Vancouver,BC,Canada:IEEE,2011:3629-3632.
[23] Xiao H,Yu S L,Yao C B,et al.Geostationary millimetre and submillimetre-wave sounder for “FengYun-4” meteorological satellite[C]//Proceedings of the 3rd China-Europe Workshop on Millimetre-Waves and Terahertz Technologies.2010.
[24] Dietrich S,Paola F D,Bizzarri B.MTG:Resolution enhancement for MW measurements from geostationary orbits[J].Advances in Geosciences,2006,7:293-299.
[25] 陈洪滨.利用高频微波被动遥感探测大气[J].遥感技术与应用,1999,14(2):49-54.
Chen H B.Remote sensing of the atmosphere with the millimeter and sub-millimeter wave radiometry from the space[J].Remote Sensing Technology and Application,1999,14(2):49-54.
[26] 郭 杨,卢乃锰,谷松岩.毫米/亚毫米波探测大气温度和湿度的通道选择[J].应用气象学报,2010,21(6):716-723.
Guo Y,Lu N M,Gu S Y.Channel selection of millimeter/submillimeter wave for temperature and humidity sounding[J].Journal of Applied Meteorological Science,2010,21(6):716-723.
[27] Jiang H B,Su Y Y,Jiao Q S,et al.Typical geologic disaster surveying in Wenchuan 8.0 earthquake zone using high resolution ground LiDAR and UAV remote sensing[C]//Proceedings SPIE 9262,Lidar Remote Sensing for Environmental Monitoring XIV.Beijing,China:SPIE,2014:926219.
[28] 欧空局土壤湿度与海水盐度卫星-SMOS介绍[EB/OL].http://www.esa.int/Our_Activities/Observing_the_Earth/SMOS/Facts_and_figures.
An introduction on ESA soil moisture and ocean salinity-SMOS[EB/OL].http://www.esa.int/Our_Activities/Observing_the_Earth/SMOS/Facts_and_figures.
[1] LIU Wen, WANG Meng, SONG Ban, YU Tianbin, HUANG Xichao, JIANG Yu, SUN Yujiang. Surveys and chain structure study of potential hazards of ice avalanches based on optical remote sensing technology: A case study of southeast Tibet[J]. Remote Sensing for Natural Resources, 2022, 34(1): 265-276.
[2] WANG Qian, REN Guangli. Application of hyperspectral remote sensing data-based anomaly extraction in copper-gold prospecting in the Solake area in the Altyn metallogenic belt, Xinjiang[J]. Remote Sensing for Natural Resources, 2022, 34(1): 277-285.
[3] LYU Pin, XIONG Liyuan, XU Zhengqiang, ZHOU Xuecheng. FME-based method for attribute consistency checking of vector data of mines obtained from remote sensing monitoring[J]. Remote Sensing for Natural Resources, 2022, 34(1): 293-298.
[4] ZHANG Daming, ZHANG Xueyong, LI Lu, LIU Huayong. Remote sensing image segmentation based on Parzen window density estimation of super-pixels[J]. Remote Sensing for Natural Resources, 2022, 34(1): 53-60.
[5] XUE Bai, WANG Yizhe, LIU Shuhan, YUE Mingyu, WANG Yiying, ZHAO Shihu. Change detection of high-resolution remote sensing images based on Siamese network[J]. Remote Sensing for Natural Resources, 2022, 34(1): 61-66.
[6] SONG Renbo, ZHU Yuxin, GUO Renjie, ZHAO Pengfei, ZHAO Kexin, ZHU Jie, CHEN Ying. A method for 3D modeling of urban buildings based on multi-source data integration[J]. Remote Sensing for Natural Resources, 2022, 34(1): 93-105.
[7] LI Weiguang, HOU Meiting. A review of reconstruction methods for remote-sensing-based time series data of vegetation and some examples[J]. Remote Sensing for Natural Resources, 2022, 34(1): 1-9.
[8] DING Bo, LI Wei, HU Ke. Inversion of total suspended matter concentration in Maowei Sea and its estuary, Southwest China using contemporaneous optical data and GF SAR data[J]. Remote Sensing for Natural Resources, 2022, 34(1): 10-17.
[9] GAO Qi, WANG Yuzhen, FENG Chunhui, MA Ziqiang, LIU Weiyang, PENG Jie, JI Yanzhen. Remote sensing inversion of desert soil moisture based on improved spectral indices[J]. Remote Sensing for Natural Resources, 2022, 34(1): 142-150.
[10] ZHANG Qinrui, ZHAO Liangjun, LIN Guojun, WAN Honglin. Ecological environment assessment of three-river confluence in Yibin City using improved remote sensing ecological index[J]. Remote Sensing for Natural Resources, 2022, 34(1): 230-237.
[11] HE Peng, TONG Liqiang, GUO Zhaocheng, TU Jienan, WANG Genhou. A study on hidden risks of glacial lake outburst floods based on relief amplitude: A case study of eastern Shishapangma[J]. Remote Sensing for Natural Resources, 2022, 34(1): 257-264.
[12] YU Xinli, SONG Yan, YANG Miao, HUANG Lei, ZHANG Yanjie. Multi-model and multi-scale scene recognition of shipbuilding enterprises based on convolutional neural network with spatial constraints[J]. Remote Sensing for Natural Resources, 2021, 33(4): 72-81.
[13] LI Yikun, YANG Yang, YANG Shuwen, WANG Zihao. A change vector analysis in posterior probability space combined with fuzzy C-means clustering and a Bayesian network[J]. Remote Sensing for Natural Resources, 2021, 33(4): 82-88.
[14] AI Lu, SUN Shuyi, LI Shuguang, MA Hongzhang. Research progress on the cooperative inversion of soil moisture using optical and SAR remote sensing[J]. Remote Sensing for Natural Resources, 2021, 33(4): 10-18.
[15] LI Teya, SONG Yan, YU Xinli, ZHOU Yuanxiu. Monthly production estimation model for steel companies based on inversion of satellite thermal infrared temperature[J]. Remote Sensing for Natural Resources, 2021, 33(4): 121-129.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
Copyright © 2017 Remote Sensing for Natural Resources
Support by Beijing Magtech