GNSS约束的MERSI/FY-3A PWV校准方法

doi:10.11947/j.AGCS.2022.20210060

摘要/Abstract

摘要： 精确的水汽信息对于短临天气预警和长期气候监测具有重要意义。本文针对搭载在我国第2代极轨卫星风云三号A星（FY-3A）上中分辨率光谱成像仪（medium-resolution spectral imager，MERSI）获取水汽精度较低的现状，提出一种GNSS约束的MERSI/FY-3A PWV校准方法。首先，对MERSI/FY-3A的PWV段产品进行处理得到水汽日产品，并利用GNSS和无线电探空（radiosonde，RS）数据对其进行评估；然后，根据PWV的季节分布特性，构建GNSS约束的MERSI/FY-3A PWV季节自适应校准模型；最后，分别利用GNSS、RS和再分析资料对校准后的MERSI/FY-3A水汽进行对比，验证提出方法的有效性。研究表明：本文提出的PWV校准方法，能够有效改善MERSI/FY-3A水汽日产品和旬产品的精度，改善率分别为58.63%和68.72%。该方法可为遥感水汽快速校准研究提供重要的理论依据。

关键词: GNSS, 无线电探空, MERSI, 校准

Abstract: Accurate water vapor information is of great importance for short-range weather warnings and long-term climate monitoring. A MERSI/FY-3A PWV correction method is proposed in this paper to address the low water vapor accuracy obtained by the Medium-Resolution Spectral Imager (MERSI) of the second generation of Chinese polar-orbit meteorological satellite FY-3A. Firstly, the daily product data were obtained by processing the 5 min product of MERSI/FY-3A and evaluated by using ground-based GNSS and Radiosonde data in China; then, according to the seasonal distribution of PWV, the GNSS-based PWV seasonal calibration model is constructed; finally, a comparison of the calibrated MERSI/FY-3A PWV using Radiosonde data was performed to verify the validity of the proposed method. The results show that the proposed PWV seasonal calibration correction model can effectively improve water vapor accuracy in MERSI/FY-3A 5 min and 10 days products, with an improvement rate of 58.63% and 68.72%, respectively. This method can provide a theoretical foundation for the rapid correction of water vapor in remote sensing.

Key words: global navigation satellite system, radiosonde, MERSI, calibration

中图分类号:

P228

赵庆志, 杜正, 姚顽强, 姚宜斌. GNSS约束的MERSI/FY-3A PWV校准方法[J]. 测绘学报, 2022, 51(2): 159-168.

ZHAO Qingzhi, DU Zheng, YAO Wanqiang, YAO Yibin. The MERSI/FY-3A PWV correction method based on GNSS[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(2): 159-168.

参考文献

[1] YAO Yibin, SUN Zhangyu, XU Chaoqian. Applicability of Bevis formula at different height levels and global weighted mean temperature model based on near-Earth atmospheric temperature[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(1):1-11. DOI:10.11947/j.JGGS.2020.0101.
[2] 柳典, 刘晓阳. 地基GPS遥感观测北京地区水汽变化特征[J]. 应用气象学报, 2009, 20(3):346-353. LIU Dian, LIU Xiaoyang. Variation features of atmospheric precipitable water vapor derived from ground-based GPS in Beijing[J]. Journal of Applied Meteorological Science, 2009, 20(3):346-353.
[3] CHAHINE M T. The hydrological cycle and its influence on climate[J]. Nature, 1992, 359(6394):373-380.
[4] 黄良珂, 彭华, 刘立龙, 等. 顾及垂直递减率函数的中国区域大气加权平均温度模型[J]. 测绘学报, 2020, 49(4):432-442. DOI:10.11947/j.AGCS.2020.20190168. HUANG Liangke, PENG Hua, LIU Lilong, et al. An empirical atmospheric weighted mean temperature model considering the lapse rate function for China[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(4):432-442. DOI:10.11947/j.AGCS.2020.20190168.
[5] DURRE I, VOSE R S, WUERTZ D B. Overview of the integrated global radiosonde archive[J]. Journal of Climate, 2006, 19(1):53-68.
[6] BEVIS M, BUSINGER S, HERRING T A, et al. GPS meteorology:remote sensing of atmospheric water vapor using the global positioning system[J]. Journal of Geophysical Research:Atmospheres, 1992, 97(D14):15787-15801.
[7] SÁNCHEZ J L, POSADA R, GARCÍA-ORTEGA E, et al. A method to improve the accuracy of continuous measuring of vertical profiles of temperature and water vapor density by means of a ground-based microwave radiometer[J]. Atmospheric Research, 2013, 122:43-54.
[8] LI Xia, ZHANG Lei, CAO Xianjie, et al. Retrieval of precipitable water vapor using MFRSR and comparison with other multisensors over the semi-arid area of northwest China[J]. Atmospheric Research, 2016, 172-173:83-94.
[9] WANG Min, FANG Xin, HU Shunxing, et al. Variation characteristics of water vapor distribution during 2000-2008 over Hefei (31.9°N, 117.2°E) observed by L625 LiDAR[J]. Atmospheric Research, 2015, 164-165:1-8.
[10] HALTHORE R N, ECK T F, HOLBEN B N, et al. Sun photometric measurements of atmospheric water vapor column abundance in the 940-nm band[J]. Journal of Geophysical Research:Atmospheres, 1997, 102(D4):4343-4352.
[11] KAUFMAN Y J, GAO B C. Remote sensing of water vapor in the near IR from EOS/MODIS[J]. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30(5):871-884.
[12] NELSON R R, CRISP D, OTT L E, et al. High-accuracy measurements of total column water vapor from the Orbiting Carbon Observatory-2[J]. Geophysical Research Letters, 2016, 43(23):12261-12269.
[13] 施闯, 张卫星, 曹云昌, 等. 基于北斗/GNSS的中国-中南半岛地区大气水汽气候特征及同降水的相关分析[J]. 测绘学报, 2020, 49(9):1112-1119. DOI:10.11947/j.AGCS.2020.20200339. SHI Chuang, ZHANG Weixing, CAO Yunchang, et al. Atmospheric water vapor climatological characteristics over Indo-China region based on BeiDou/GNSS and relationships with precipitation[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(9):1112-1119. DOI:10.11947/j.AGCS.2020.20200339.
[14] ZHANG Hongxing, YUAN Yunbin, LI Wei, et al. GPS PPP-derived precipitable water vapor retrieval based on T_m/P_s from multiple sources of meteorological data sets in China[J]. Journal of Geophysical Research:Atmospheres, 2017, 122(8):4165-4183.
[15] 姚宜斌, 张顺, 孔建. GNSS空间环境学研究进展和展望[J]. 测绘学报, 2017, 46(10):1408-1420. DOI:10.11947/j.AGCS.2017.20170333. YAO Yibin, ZHANG Shun, KONG Jian. Research progress and prospect of GNSS space environment science[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10):1408-1420. DOI:10.11947/j.AGCS.2017.20170333.
[16] LEE S W, KOUBA J, SCHUTZ B, et al. Monitoring precipitable water vapor in real-time using global navigation satellite systems[J]. Journal of Geodesy, 2013, 87(10-12):923-934.
[17] CHEN Biyan, LIU Zhizhao. Global water vapor variability and trend from the latest 36 year (1979 to 2014) data of ECMWF and NCEP reanalyses, radiosonde, GPS, and microwave satellite[J]. Journal of Geophysical Research:Atmospheres, 2016, 121(19):11442-11462.
[18] 刘备, 王勇, 娄泽生, 等. CMONOC观测约束下的中国大陆地区MODIS PWV校正[J]. 测绘学报, 2019, 48(10):1207-1215. DOI:10.11947/j.AGCS.2019.20180386. LIU Bei, WANG Yong, LOU Zesheng, et al. The MODIS PWV correction based on CMONOC in Chinese mainland[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(10):1207-1215. DOI:10.11947/j.AGCS.2019.20180386.
[19] 张俊东, 陈秀万, 李颖, 等. 基于GPS数据的MODIS近红外水汽改进反演算法研究[J]. 地理与地理信息科学, 2013, 29(2):40-44. ZHANG Jundong, CHEN Xiuwan, LI Ying, et al. Research on improved retrieval algorithm of MODIS Near-IR water vapor based on GPS data[J]. Geography and Geo-Information Science, 2013, 29(2):40-44.
[20] 曹艳丰, 陈宝献, 陈秀万, 等. 基于GPS数据的MODIS大气可降水量反演精度提高模型[J]. 遥感信息, 2014, 29(2):23-27. CAO Yanfeng, CHEN Baoxian, CHEN Xiuwan, et al. A real-time accuracy model of MODIS PWV using GPS PWV data[J]. Remote Sensing Information, 2014, 29(2):23-27.
[21] 方圣辉, 毕创, 乐源, 等. 利用GPS可降水量校正MODIS近红外水汽数据[J]. 测绘科学, 2016, 41(9):38-41. FANG Shenghui, BI Chuang, LE Yuan, et al. Calibration of MODIS near infrared vapor products using precipitable water vapor retrieved from GPS data[J]. Science of Surveying and Mapping, 2016, 41(9):38-41.
[22] GUI Ke, CHE Huizheng, CHEN Quanliang, et al. Evaluation of radiosonde, MODIS-NIR-Clear, and AERONET precipitable water vapor using IGS ground-based GPS measurements over China[J]. Atmospheric Research, 2017, 197(3):461-473.
[23] GONG Shaoqi, HAGAN D F T, ZHANG Cunjie. Analysis on precipitable water vapor over the Tibetan Plateau using FengYun-3A medium resolution spectral imager products[J]. Journal of Sensors, 2019, 2019(12):607-619.
[24] DU Zheng, ZHAO Qingzhi, YAO Wanqiang, et al. Improved GPT2w (IGPT2w) model for site specific zenith tropospheric delay estimation in China[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2020, 198(3):1052-1064.
[25] SAASTAMOINEN J. Atmospheric correction for the troposphere and stratosphere in radio ranging satellites[M]//HENRIKSEN S W, MANCINI A, CHOVITZ B H. The Use of Artificial Satellites for Geodesy Volume 15. Washington, D.C.:American Geophysical Union, 1972:247-251.
[26] SUN Zhangyu, ZHANG Bao, YAO Yibin. An ERA5-based model for estimating tropospheric delay and weighted mean temperature over China with improved spatiotemporal resolutions[J]. Earth and Space Science, 2019, 6(10):1926-1941.
[27] PÉREZ-RAMÍREZ D, WHITEMAN D N, SMIRNOV A, et al. Evaluation of AERONET precipitable water vapor versus microwave radiometry, GPS, and radiosondes at ARM sites[J]. Journal of Geophysical Research:Atmospheres, 2014, 119(15):9596-9613.
[28] ZHAO Qingzhi, YAO Yibin, YAO Wanqiang, et al. GNSS-derived PWV and comparison with radiosonde and ECMWF ERA-Interim data over mainland China[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2019, 182:85-92.
[29] GONG Shaoqi, HAGAN D F, LU Jing, et al. Validation on MERSI/FY-3A precipitable water vapor product[J]. Advances in Space Research, 2018, 61(1):413-425.
[30] GONG Shaoqi, HAGAN D F T, WU Xinyi, et al. Spatio-temporal analysis of precipitable water vapour over northwest china utilizing MERSI/FY-3A products[J]. International Journal of Remote Sensing, 2018, 39(10):3094-3110.
[31] 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 Jun, DONG Chaohua, LU Neimeng, et al. FY-3A:the new generation polar-orbiting meteorological satellite of China[J]. Acta Meteorologica Sinica, 2019, 67(4):501-509.
[32] ZHANG Yonglin, CAI Changsheng, CHEN Biyan, et al. Consistency evaluation of precipitable water vapor derived from ERA5, ERA-Interim, GNSS, and radiosondes over China[J]. Radio Science, 2019, 54(7):561-571.
[33] DEE D P, UPPALA S M, SIMMONS A J, et al. The ERA-Interim reanalysis:configuration and performance of the data assimilation system[J]. Quarterly Journal of the Royal Meteorological Society, 2011, 137(656):553-597.
[34] KLOS A, HUNEGNAW A, TEFERLE F N, et al. Statistical significance of trends in zenith wet delay from re-processed GPS solutions[J]. GPS Solutions, 2018, 22(2):51-62.
[35] ZHAO Qingzhi, MA Xiongwei, YAO Wanqiang, et al. A drought monitoring method based on precipitable water vapor and precipitation[J]. Journal of Climate, 2020, 33(24):10727-10741.
[36] LI Xueying, LONG Di. An improvement in accuracy and spatiotemporal continuity of the MODIS precipitable water vapor product based on a data fusion approach[J]. Remote Sensing of Environment, 2020, 248(10):111-122.
[37] YAO Yibin, XU Xingyu, XU Chaoqian, et al. Establishment of a real-time local tropospheric fusion model[J]. Remote Sensing, 2019, 11(11):1321-1336.