我国地基GNSS/MET水汽观测站网建设进展与挑战

Advances and challenges in developing the ground-based GNSS/MET water vapor observation network in China

摘要

地基全球卫星导航系统气象 (GNSS/MET) 水汽观测站网已成为我国综合气象观测系统的重要组成部分。然而，我国站网布局与欧美日等发达地区或国家仍然存在差距，尚未满足 WMO 推荐的覆盖中小尺度天气系统的需求。另外，观测装备性能需要进一步提升，以增加抗电磁干扰能力和信号捕获跟踪水平。在国家推进北斗卫星导航系统 (以下简称“北斗”) 在气象等重点行业规模化应用的政策背景下，如何建设、布局和发展该观测站网以及如何结合气象部门优势和特点发挥该观测站网的最大价值是目前面临的重要问题。针对上述问题，本文回顾了自 2008 年以来国内地基 GNSS/MET 水汽观测站网建设进展，阐述了目前其面临的挑战。近 20 a 我国地基 GNSS/MET 水汽观测站网快速发展，站点数量从 2008 年 87 站增加至 2024 年底 1 000 余站。2025 年底总站点数量超过 2 300 个，其中 1 650 余站实现“北斗”信号接收以及对流层水汽和电离层参量观测一体化，站点平均间距在我国东部地区达到 50~80 km，西部地区约 100 km。目前已建立较完整的观测数据质量控制流程和指标体系，大气可降水量 (PWV) 业务产品误差小于 2 mm，满足世界气象组织 (WMO) 提出的最优性价比指标要求，在数值天气预报、天气诊断会商等业务中发挥了重要作用。在此基础上，对该站网的升级优化和观测产品应用进行了展望，以期为我国地基 GNSS/MET 水汽观测业务站网发展提供有价值的参考依据。

Abstract

The ground-based global navigation satellite system meteorology (GNSS/MET) water vapor observation network has become an important part of China's integrated meteorological observation system. However, there is still a considerable gap between China's network layout and those of developed regions or countries such as Europe, the United States, and Japan. And, it has not yet met the WMO's recommended coverage for meso- and micro-scale weather systems. Furthermore, the performance of observation instruments needs to be further improved to enhance its anti-electromagnetic interference ability and signal capture and tracking capabilities. With the promulgation of the national policy promoting the large-scale application of the Beidou navigation satellite system (BDS) in key sectors such as meteorology, this paper discusses how to construct, deploy, and develop this network, and how to maximize its value by leveraging the strengths and characteristics of the meteorological departments. To address these issues, this paper reviews the progress in the construction of domestic ground-based GNSS/MET water vapor observation networks since 2008 and elaborates on the current challenges it faces. The ground-based GNSS/MET water vapor observation network in China has developed rapidly, with the number of stations increasing from 87 in 2008 to more than 1 000 by the end of 2024. The total number of stations is expected to exceed 2 300 by the end of 2025. More than 1 650 stations will be equipped with BDS signal receiving technology and achieve integrated monitoring of atmospheric parameters in both the troposphere and ionosphere. In eastern China, the average distance between stations will be 50-80 km, while in the western regions, it will be about 100 km. Currently, a relatively complete observation quality control procedure and the indices for the observation data have been established, with the uncertainty of precipitable water vapor (PWV) operational products being less than 2 mm, meeting the requirements of the optimal cost-effectiveness indicators proposed by World Meteorological Organization (WMO). These products have played a significant role in operational numerical weather prediction, weather diagnosis, and other meteorological services. Finally, this paper gives a perspective on the upgrade, optimization, and product applications of the network. This study can provide valuable reference basis for the development of the ground-based GNSS/MET water vapor observation network in China.

关键词

全球卫星导航系统气象 / 大气可降水量 / 观测站网 / 中小尺度天气系统

Key words

GNSS/MET / precipitable water vapor / observation network / meso- and micro-scale weather systems

参考文献

[1] 安琳,权晨,沈晓燕,等. 2025.青海“8·18”短时强降水过程的水汽特征分析[J].暴雨灾害,44(1):41-51.

[2] An L, Quan C, Shen X Y, et al. 2025. Analysis of water vapor characteristics of the "8·18" short-duration heavy rainfall event in Qinghai [J].Torrential Rain and Disasters,44(1):41-51 (in Chinese). doi:10.12406/byzh.2023-240

[3] 毕研盟,毛节泰,杨光林,等. 2004.地基GPS 遥感观测安徽地区水汽特征[J].气象科技,32(4):225-228.

[4] Bi Y M, Mao J T, Yang G L, et al. 2004. Remote sensing of atmospheric water vapor characteristics in Anhui province using ground-based GPS [J].Meteorological Science and Technology,32(4):225-228 (in Chinese). doi:10.19517/j.1671-6345.2004.04.006

[5] 曹云昌,方宗义,夏青. 2005. GPS 遥感的大气可降水量与局地降水关系的初步分析[J].应用气象学报,16(1):54-59.

[6] Cao Y C, Fang Z Y, Xia Q. 2005. Relationship between GPS precipitable water vapor and precipitation [J].Journal of Applied Meteorological Science,16(1):54-59 (in Chinese). doi:10.3969/j.issn.1001-7313.2005.01.006

[7] 丁一汇,柳艳菊,宋亚芳. 2020.东亚夏季风水汽输送带及其对中国大暴雨与洪涝灾害的影响[J].水科学进展,31(5):629-643.

[8] Ding Y H, Liu Y J, Song Y F. 2020. East Asian summer monsoon moisture transport belt and its impact on heavy rainfalls and floods in China [J].Advances in Water Science,31(5):629-643 (in Chinese). doi:10.14042/j.cnki.32.1309.2020.05.001

[9] 丁一汇. 2019.中国暴雨理论的发展历程与重要进展[J].暴雨灾害,38(5):395-406.

[10] Ding Y H. 2019. The major advances and development process of the theory of heavy rainfalls in China [J].Torrential Rain and Disasters,38(5):395-406 (in Chinese). doi:10.3969/j.issn.1004-9045.2019.05.001

[11] 甘卫军,李强,张锐,等. 2012.中国大陆构造环境监测网络的建设与应用[J].工程研究,4(4):324-331.

[12] Gan W J, Li Q, Zhang R, et al. 2012. Construction and application of tectonic and environmental observation network of China's mainland [J].Journal of Engineering Studies,4(4):324-331 (in Chinese). doi:10.3724/SP.J.1224.2012.00324

[13] 国务院新闻办公室. 2022.新时代的中国北斗[Z].[2022-11-04]. https://www.gov.cn/zhengce/2022-11/04/content_5724523.htm.

[14] The State Council Information Office of the People's Republic of China. 2022. China's BeiDou Navigation Satellite System in the New Era [Z].[2022-11-04]. https://www.gov.cn/zhengce/2022-11/04/content_5724523.htm (in Chinese)

[15] 李成才,毛节泰,李建国,等. 1999.全球定位系统遥感水汽总量[J].科学通报,44(3):333-336.

[16] Li C C, Mao J T, Li J G, et al. 1999. Remote sensing atmospheric integrated water vapor using ground-based GPS [J].Science Bulletin,44(3):333-336 (in Chinese). doi:10.3321/j.issn:0023-074X.1999.03.024

[17] 李如琦,李桉孛,李海花,等. 2022.塔克拉玛干沙漠南缘两次极端暴雨的气流模型与水汽输送特征[J].沙漠与绿洲气象,16(6):1-10.

[18] Li R Q, Li A B, Li H H, et al. 2022. Air flow model and water vapor transport characteristics of two extreme rainstorms in the southern edge of Taklimakan Desert [J].Desert and Oasis Meteorology,16(6):1-10 (in Chinese). doi:10.12057/j.issn.1002-0799.2022.06.001

[19] 中国卫星导航系统管理办公室.2023.全球卫星导航系统 (GNSS) 定向设备性能要求及测试方法:BD 420073-2022 [S] China Satellite Navigation System Management Office. 2023.

[20] Performance Requirements and Testing Methods for Global Navigation Satellite System (GNSS) Directional Equipment:BD 420073-2022 [S]. Beijing:China Standard Press (in Chinese)

[21] 梁宏,曹云昌,梁静舒,等. 2020.地基 GNSS 遥感探测气象应用[J].中国地震,36(4):744-755.

[22] Liang H, Cao Y C, Liang J S, et al. 2020. A review of the ground-based GNSS remote sensing in meteorological applications [J].Earthquake Research in China,36(4):744-755 (in Chinese)

[23] 刘晶,杨莲梅,李俊江,等. 2024.中昆仑山北坡水汽含量的计算及特征分析[J].暴雨灾害,43(2):224-233.

[24] Liu J, Yang L M, Li J J, et al. 2024. Calculation and characteristic analysis of water vapor content in the north slope of the Middle Kunlun Mountains [J].Torrential Rain and Disasters,43(2):224-233 (in Chinese). doi:10.12406/byzh.2023-053

[25] 宋淑丽,朱文耀. 2003.区域 GPS 网实时计算可降水量的若干问题[J].中国科学院上海天文台年刊,24:20-27.

[26] Song S L, Zhu W Y. 2003. Some problems about real-time retrieving PWV from local GPS network [J].Annals of Shanghai Observatory Academia Sinica,24:20-27 (in Chinese)

[27] 宋淑丽. 2004.地基 GPS 网对水汽三维分布的监测及其在气象学中的应用[D].上海:中国科学院研究生院 (上海天文台):118.

[28] Song S L. 2004. Sensing three dimensional water vapor structure with ground-based GPS network and the application in meteorology [D]. Shanghai: Shanghai Astronomical Observatory of Chinese Academy of Sciences:118 (in Chinese)

[29] 孟智勇,张福青,罗德海,等. 2019.新中国成立 70 年来的中国大气科学研究:天气篇[J].中国科学:地球科学,49(12):1875-1918.

[30] Meng Z Y, Zhang F Q, Luo D H, et al. 2019. Review of Chinese atmospheric science research over the past 70 years: Synoptic meteorology [J].Science China Earth Sciences,49(12):1875-1918 (in Chinese). doi:10.1360/SSTe-2019-0175

[31] 王小亚,朱文耀,严豪健,等. 1999.地面 GPS 探测大气可降水量的初步结果[J].大气科学,23(5):605-612.

[32] Wang X Y, Zhu W Y, Yan H J, et al. 1999. Preliminary results of precipitable water vapor monitored by ground-based GPS [J].Chinese Journal of Atmospheric Sciences,23(5):605-612 (in Chinese). doi:10.3878/j.issn.1006-9895.1999.05.11

[33] 武冰路,赵京波,纪策,等. 2023.多源观测资料在冰雹监测预警中的应用[J].沙漠与绿洲气象,17(5):79-85.

[34] Wu B L, Zhao J B, Ji C, et al. 2023. Application of multi-source observation data in hail monitoring and warning [J].Desert and Oasis Meteorology,17(5):79-85 (in Chinese). doi:10.12057/j.issn.1002-0799.2023.05.010

[35] 吴尧,肖天贵,假拉. 2024. 8 月高原季风对成都降水的影响研究[J].高原山地气象研究,44(2):133-142.

[36] Wu Y, Xiao T G, Jia L. 2024. Study on the influence of plateau monsoon on precipitation in Chengdu in August [J].Plateau and Mountain Meteorology Research,44(2):133-142 (in Chinese). doi:10.3969/j.issn.1674-2184.2024.02.017

[37] 张朝林. 2006.环北京四维大气水汽实时监测的“天眼”-环北京地基全球定位系统气象监测平台投入应用[J].中国高校科技与产业化,8:44-45.

[38] Zhang C L. 2006. The "eye in the sky" for real-time monitoring of four-dimensional atmospheric water vapor around Beijing-the ground-based global positioning system meteorological monitoring platform around Beijing was put into use [J].Chinese University Technology Transfer,8:44-45 (in Chinese). doi:10.16209/j.cnki.cust.2006.08.012

[39] 张人禾,徐祥德. 2012.青藏高原及东缘新一代大气综合探测系统应用平台-中日合作 JICA 项目[J].中国工程科学,14(9):102-112.

[40] Zhang R H, Xu X D. 2012. Applying platform for the new generation of the comprehensive atmospheric observing system over the Tibetan Plateau and its eastern region-a China-Japan cooperative JICA Project [J].Strategic Study of Chinese Academy of Engineering,14(9):102-112 (in Chinese)

[41] 中国气象局.2020.气象观测资料质量控制-地面: QX/T 118-2020 [S].北京:中国标准出版社. China Meteorological Administration. 2020.

[42] Quality Control of Meteorological Observation Data - Ground: QX/T 118-2020 [S]. Beijing:China Standard Press (in Chinese)

[43] Aichinger-Rosenberger M, Aregger M, Kopp J, et al. 2023. Detecting signatures of convective storm events in GNSS-SNR: Two case studies from summer 2021 in Switzerland [J].Geophysical Research Letters,50:e2023GL104916. doi:10.1029/2023GL104916

[44] Bevis M, Businger S, Herring T A, et al. 1992. GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system [J].Journal of Geophysical Research,97(D14):15787-15801. doi:10.1029/92JD01517

[45] Bock Y, Fang F, Knox A, et al. 2023. Extended Solid Earth Science Esdr System (ES3): algorithm theoretical basis document (ATBD) [R].http://garner.ucsd.edu/pub/measuresESESES_products/ATBD/ESESES-ATBD.pdf

[46] Bonafoni S, Biondi R, Brenot H, et al. 2019. Radio occultation and ground-based GNSS products for observing, understanding and predicting extreme events: A review [J].Atmospheric Research,230:104624 doi:10.1016/j.atmosres.2019.104624

[47] Dach R, Lutz S, Walser P, et al. 2015. Bernese GNSS Software Version 5.2 [R]//User manual, Astronomical Institute, University of Bern. Bern: Bern Open Publishing. doi:10.7892/boris.72297

[48] Douville H, Raghavan K, Renwick J, et al. 2021. Water Cycle Changes [R]//In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I To The Sixth Assessment Report Of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press: 1055-1210. doi:10.1017/9781009157896.010

[49] GCOS. 2015. Status of the Global Observing System for Climate [R]//WMO/GCOS-195:373. https://public.wmo.int/en/resources/bulletin/status-of-global-observing-system-climate

[50] Gong Y, Liu Z, Chan P W, et al. 2023. Assimilating GNSS PWV and radiosonde meteorological profiles to improve the PWV and rainfall forecasting performance from the Weather Research and Forecasting (WRF) model over the South China [J].Atmospheric Research,286:106677. doi:10.1016/j.atmosres.2023.106677

[51] Guerreiro S B, Fowler H J, Barbero R, et al. 2018. Detection of continental-scale intensification of hourly rainfall extremes [J].Nature Climte Change,8:803-807. doi:10.1038/s41558-018-0245-3

[52] Guerova G, Jones J, Douša J, et al. 2016. Review of the state-of-the-art and future prospects of the ground-based GNSS meteorology in Europe [J].Atmospheric Measurement Techniques,9:5385-5406. doi:10.5194/amt-9-5385-2016

[53] Haase J, Ge M, Vedel H, et al. 2003. Accuracy and variability of GPS tropospheric delay measurements of water vapor in the western Mediterranean [J].Journal of Applied Meteorology,42(11):1547-1568. doi:10.1175/1520-0450(2003)042<1547:AAVOGT>2.0.CO;2

[54] Herring T A, Melbourne T I, Murray M H, et al. 2016. Plate boundary observatory and related networks: GPS data analysis methods and geodetic products [J].Reviews of Geophysics,54:1-50. doi:10.1002/2016RG000529

[55] Herring T A, King R W, Floyd M A, et al. 2018. GPS Analysis at MIT [R]//Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute Of Technology:168. http://geoweb.mit.edu/gg/docs/GAMIT_Ref.pdf

[56] IGS. 2015. IGS Site Guidelines [R].http://igsorg.zendesk.com/hc/en-us/articles/202011433-Current-IGS-Site- Guidelines

[57] IGS. 2023. RINEX: The Receiver Independent Exchange Format (Version 4.01) [S].http://files.igs.org/pub/data/format/rinex_4.01.pdf

[58] Jones J, Guerova G, Douša J, et al. 2020. Advanced GNSS Tropospheric Products for Monitoring Severe Weather Events and Climate [R]//COST Action ES1206 Final Action Dissemination Report: 577

[59] Kometani T. 2005. GPS Earth observation network system [J].Journal of the Japan Society for Precision Engineering,71(11):1339-1343. doi:10.2493/jjspe.71.1339

[60] Larson K M. 2016. GPS interferometric reflectometry: Applications to surface soil moisture, snow depth, and vegetation water content in the western United States [J].Wiley Interdisciplinary Reviews:Water,3:775-787. doi:10.1002/wat2.1167

[61] Liang H, Cao Y C, Wan X M, et al. 2015. Meteorological applications of precipitable water vapor measurements retrieved by the national GNSS network of China [J].Geodesy and Geodynamics,6(2):135-142. doi:10.1016/j.geog.2015.03.001

[62] Liu J, Liang H, Sun Z, et al. 2006. Validation of the moderate-resolution imaging spectroradiometer precipitable water vapor product using measurements from GPS on the Tibetan Plateau [J].Journal of Geophysical Research,111:D14103. doi:10.1029/2005JD007028

[63] Liu J N, Ge M R. 2003. PANDA software and its preliminary result of positioning and orbit determination [J].Wuhan University Journal of Natural Sciences,8:603-609. doi:10.1007/BF02899825

[64] Liu R L, Zhong B, Li X P, et al. 2022. Analysis of groundwater changes (2003-2020) in the North China Plain using geodetic measurements [J].Journal of Hydrology: Regional Studies,41:101085. doi:10.1016/j.ejrh.2022.101085

[65] Lorenz E N. 1963. Deterministic nonperiodic flow [J].Journal of the Atmospheric Sciences,20:130-141. doi:10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2

[66] Mears C A, Smith D K, Ricciardulli L, et al. 2018. Construction and uncertainty estimation of a satellite-derived total precipitable water data record over the world’s oceans [J].Earth and Space Science,5:197-210. doi:10.1002/2018EA000363

[67] Nash J, Oakley T, Vömel H, et al. 2011. WMO Intercomparison of High Quality Radiosonde Systems [R]//Instruments and Observing Methods Report No.107 (WMO/TD-No.1580). http://library.wmo.int/viewer/50499/#page=1&viewer=picture&o=bookmarks&n=0&q=

[68] Neelin J D, Martinez-Villalobos C, Stechmann S N, et al. 2022. Precipitation extremes and water vapor [J].Current climate change reports,8:17-33. doi:10.1007/s40641-021-00177-z

[69] Ning T, Wang J, Elgered G, et al. 2016. The uncertainty of the atmospheric integrated water vapor estimated from GNSS observations [J].Atmospheric Measurement Techniques,9:79-92. doi:10.5194/amt-9-79-2016

[70] OSCAR. 2024. Requirements Defined for Integrated Water Vapour (IWV) [R].https://space.oscar.wmo.int/variables/view/integrated_water_vapour_iwv

[71] Rocken C, Ware R, Van Hove T, et al. 1993. Sensing atmospheric water vapor with the global positioning system [J].Geophysical Research Letters,20(23):2631-2634. doi:10.1029/93GL02935

[72] Shi C, Zhao Q, Geng J, et al. 2008. Recent Development Of Panda Software In Gnss Data Processing [R]//Li D, Gong J, Wu H. International Conference on Earth Observation Data Processing and Analysis (ICEODPA).International Society for Optical Engineering (SPIE Proceedings), 7285: 558-566. doi:https://doi.org/10.1117/12.816261

[73] Stull R. 2015. Meteorology for Scientists and Engineers (Third Edition) [M]. Vancouver: The University of British Columbia:924

[74] Teunissen P J G, Montenbruck O, 2017. Handbook of Global Navigation Satellite Systems [M]. Switzerland:Springer International Publishing:1327. doi:10.1007/978-3-319-42928-1

[75] Wan W, Larson K M, Small E E, et al. 2015. Using geodetic GPS receivers to measure vegetation water content [J].GPS Solutions,19:237-248. doi:10.1007/s10291-014-0383-7

[76] Wan W, Zhang J, Dai L, et al. 2022. A new snow depth data set over northern China derived using GNSS interferometric reflectometry from a continuously operating network (GSnow-CHINA v1.0, 2013-2022) [J].Earth System Science Data,14(8):3549-3571. doi:https://doi.org/10.5194/essd-14-3549-2022

[77] Wang J H, Rannat K, Jones J, 2019. Global Navigation Satellite System (GNSS)-Precipitable Water (PW) Omnibus [R]//GRUAN-TD-6(v2.0). http://www.gruan.org/gruan/editor/documents/gruan/GRUAN-TD-6_GNSS-PW_v2.0_2019-08-21.pdf

[78] WMO. 2019. Vision for the WMO Integrated Global Observing System in 2040 [R]//WMO-No.1243. https://library.wmo.int/viewer/57028/download?file=1243_en.pdf&type=pdf&navigator=1

[79] Wolfe D E, Gutman S I. 2000. Developing an operational, surface-based, GPS, water vapor observing system for NOAA:network design and results [J].Journal of Atmospheric and Oceanic Technohyphenlogy,17(4):426-440. doi:10.1175/1520-0426(2000)017<0426:daosbg>2.0.co;2

[80] Yang T, Wan W, Chen X, et al. 2019. Land surface characterization using BeiDou signal-to-noise ratio observations [J].GPS Solutions,23(32):112-118. doi:10.1007/s10291-019-0824-4

[81] Zhao Q Z, Ma X W, Yao W Q, et al. 2020. A drought monitoring method based on precipitable water vapor and precipitation [J].Journal of Climate,33(24):10727-10741. doi:10.1175/JCLI-D-19-0971.1

[82] Zhao Q Z, Liu K, Sun T T, et al. 2023. A novel regional drought monitoring method using GNSS-derived ZTD and precipitation [J].Remote Sensing of Environment,297:113778. doi:10.1016/J.RSE.2023.113778

[83] Zhang W, Lou Y, Cao Y, et al. 2019. Corrections of radiosonde-based precipitable water using ground-based GPS and applications on historical radiosonde data over China [J].Journal of Geophysical Research: Atmospheres,124:3208-3222. doi:10.1029/2018JD029662

[84] Zhang W, Lou Y, Zhou Y, et al. 2024. GNSS meteorological ensemble tools (GMET): a free-access online service for GNSS meteorological applications [J].GPS Solutions,28:202. doi:10.1007/s10291-024-01743-2

基金资助

国家自然科学基金项目(U2442214，42174027)

中国气象局创新发展专项(CXFZ2024J061)

中国气象局气象探测中心观测试验计划项目(GCSYJH13-04)

北部湾大气水分循环综合观测试验项目(BEIGAWEX2023to2028)