HE Ke,BAI Aijuan,HU Xiuqing.Analysis and Fusion of Water Vapor Error between Satellite and ERA5 over the Tibetan Plateau based on TC Method[J].Journal of Chengdu University of Information Technology,2022,37(04):449-455.[doi:10.16836/j.cnki.jcuit.2022.04.014]
基于TC方法青藏高原卫星与ERA5水汽误差分析及融合
- Title:
- Analysis and Fusion of Water Vapor Error between Satellite and ERA5 over the Tibetan Plateau based on TC Method
- 文章编号:
- 2096-1618(2022)04-0449-07
- Keywords:
- satellite remote sensing; precipitable water vapor product; TC; error analysis; product fusion
- 分类号:
- P405
- 文献标志码:
- A
- 摘要:
- 为分析中国的静止卫星FY-4A搭载的多通道光谱成像仪(AGRI)、国外的极轨卫星Terra搭载的中分辨率光谱成像仪(MODIS)和ERA5再分析数据的水汽产品在青藏高原地区的差异，采用Triple-Collocation方法，在该地区0.25°×0.25°空间尺度上对AGRI、MODIS和ERA5来源的大气可降水量产品进行随机误差分析，并开展基于随机误差融合算法的研究。结果表明:不同来源的大气可降水量产品的随机误差存在空间上的差异，随机误差从小到大依次为ERA5、AGRI和MODIS。根据该随机误差，计算3种产品的融合权重系数，随机误差越大则融合权重系数越小，反之越大。基于该融合系数进行数据融合，得到的融合产品在空间完整性上较卫星数据有较大改善，并且对于MODIS的大气可降水量产品在青藏高原地区的应用有了较大的改善。
- Abstract:
- In order to analyze the Advanced Geostationary Radiation Imager(AGRI)carried by the Chinese geostationary satellite FY-4A, the Moderate Resolution Imaging Spectroradiometer(MODIS) carried by the foreign polar-orbiting satellite Terra, and the water vapor products of the ERA5 reanalyzed data, the water vapor products in the Qinghai-Tibet Plateau difference, the Triple-Collocation method is used to analyze the random error of the precipitable water vapor products from AGRI, MODIS and ERA5 on the spatial scale of the region, and to carry out the research based on the random error fusion algorithm. The results show that there are spatial differences in the random errors of the precipitable water vapor products from different sources, and the random errors are ERA5, AGRI and MODIS in descending order. According to the random error, the fusion weight coefficient of the three products is calculated. The larger the random error, the smaller the fusion weight coefficient, and vice versa. Based on the fusion coefficient for data fusion, the spatial integrity of the obtained fusion product has been greatly improved compared with the satellite data, and the precipitable water vapor product of MODIS has been greatly improved in the Qinghai-Tibet Plateau.
参考文献/References:
[1] 高凤玲,崔国民,陶乐仁,等.大气对流层水汽对温室效应的影响分析[J].工程热物理学报,2014(4):722-725.
[2] Trenberth K E,Fasullo J,Smith L.Trends and variability in column-integrated atmospheric water vapor[J].Climate dynamics,2005,24(7-8):741-758.
[3] 陈隆勋,龚知本,陈嘉滨,等.东亚地区大气辐射能收支(三)——云天大气的地气系统热量收支[J].气象学报,1965(1):8-19.
[4] 王西地.基于GPS和MODIS数据的大气可降水量算法研究[D].南京:东南大学,2017.
[5] Giorgi F.Climate change hot-spots[J].Geophysical research letters,2006,33(8).
[6] 李星光.极端天气条件下大气可降水量地基GPS反演研究[D].徐州:中国矿业大学,2015.
[7] Niell A E,Coster A J,Solheim F S,et al.Comparison of measurements of atmospheric wet delay by radiosonde,water vapor radiometer,GPS,and VLBI[J].Journal of Atmospheric and Oceanic Technology,2001,18(6):830-850.
[8] 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.
[9] 毛节泰.GPS的气象应用[J].气象科技,1993(4):45-49.
[10] 梁宏,张人禾,刘晶淼.青藏高原大气水汽探测误差及其成因[J].气象学报,2012,70(1):155-164.
[11] 曹云昌,陈永奇,李炳华,等.利用地基GPS测量大气水汽廓线的方法[J].气象科技,2006,34(3):241-245.
[12] 梁宏,刘晶淼,章建成,等.青藏高原大气总水汽量的反演研究[J].高原气象,2006,25(6):1055-1063.
[13] 梁宏,刘晶淼,李世奎.青藏高原及周边地区大气水汽资源分布和季节变化特征分析[J].自然资源学报,2006(4):28-36.
[14] 李国平,黄丁发.GPS气象学研究及应用的进展与前景[J].气象科学,2005,25(6):651-661.
[15] 曹云昌,方宗义,夏青,等.中国地基GPS气象应用站网建设展望[J].气象,2006,32(11):42-47.
[16] Liang H,Cao Y,Wan X,et al.Meteorological applications of precipitable water vapor measurements retrieved by the national GNSS network of China[J].Geodesy and geodynamics, 2015,6(2):135-142.
[17] 梁宏,张人禾,刘晶淼,等.青藏高原探空大气水汽偏差及订正方法研究[J].大气科学,2012,36(4):795-810.
[18] Alishouse J C,Snyder S A,Vongsathorn J,et al.Determination of oceanic total precipitable water from the SSM/I[J].IEEE Transactions on Geoscience and Remote Sensing,1990,28(5):811-816.
[19] Frouin R,Deschamps P Y,Lecomte P.Determination from space of atmospheric total water vapor amounts by differential absorption near 940 nm:Theory and airborne verification[J].Journal of Applied Meteorology and Climatology,1990,29(6):448-460.
[20] Chesters D,Uccellini L W,Robinson W D.Low-level water vapor fields from the VISSR Atmospheric Sounder(VAS)“split window”channels[J].Journal of Applied Meteorology and Climatology,1983,22(5):725-743.
[21] Gao B C,Kaufman Y J.Water vapor retrievals using Moderate Resolution Imaging Spectroradiometer(MODIS)near-infrared channels[J].Journal of Geophysical Research:Atmospheres,2003,108(D13).
[22] King M D,Menzel W P,Kaufman Y J,et al.Cloud and aerosol properties,precipitable water,and profiles of temperature and water vapor from MODIS[J].IEEE Transactions on Geoscience and Remote Sensing,2003,41(2):442-458.
[23] Chang L,Xiao R,Prasad A A,et al.Cloud mask-related differential linear adjustment model for MODIS infrared water vapor product[J].Remote Sensing of Environment,2019,221:650-664.
[24] Shi F,Xin J,Yang L,et al.The first validation of the precipitable water vapor of multisensor satellites over the typical regions in China[J].Remote Sensing of Environment,2018,206:107-122.
[25] Albergel C,Dutra E,Munier S,et al.ERA-5 and ERA-Interim driven ISBA land surface model simulations:which one performs better[J].Hydrology and Earth System Sciences,2018,22(6):3515-3532.
[26] Afshar M H,Yilmaz M T,Crow W T.Impact of rescaling approaches in simple fusion of soil moisture products[J].Water Resources Research,2019,55(9):7804-7825.
[27] Li D,Andreadis K M,Margulis S A,et al.A Data Assimilation Framework for Generating Space-Time Continuous Daily SWOT River Discharge Data Products[J].Water Resources Research,2020,56(6).
[28] Zhu X,Chen J,Gao F,et al.An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions[J].Remote Sensing of Environment,2010,114(11):2610-2623.
[29] Stoffelen A.Toward the true near-surface wind speed: Error modeling and calibration using triple collocation[J].Journal of geophysical research:oceans,1998,103(C4):7755-7766.
[30] O’Carroll A G,Eyre J R,Saunders R W.Three-way error analysis between AATSR,AMSR-E,and in situ sea surface temperature observations[J].Journal of atmospheric and oceanic technology,2008,25(7):1197-1207.
[31] Vogelzang J,Stoffelen A,Verhoef A F S.On the quality of high-resolution scatterometer winds[J].J Geophys Res Ocean,2011,116(10).
[32] Roebeling R A,Wolters E L A,Meirink J F,et al.Triple collocation of summer precipitation retrievals from SEVIRI over Europe with gridded rain gauge and weather radar data[J].Journal of hydrometeorology,2012,13(5):1552-1566.
[33] Scipal K,Holmes T,De Jeu R,et al.A possible solution for the problem of estimating the error structure of global soil moisture data sets[J].Geophysical Research Letters,2008,35(24).
[34] Zwieback S,Scipal K,Dorigo W,et al.Structural and statistical properties of the collocation technique for error characterization[J].Nonlinear Processes in Geophysics,2012,19(1):69-80.
[35] Gruber A,Su C H,Crow W T,et al.Estimating error cross-correlations in soil moisture data sets using extended collocation analysis[J].Journal of Geophysical Research:Atmospheres,2016,121(3):1208-1219.
[36] Yilmaz M T,Crow W T,Anderson M C,et al.An objective methodology for merging satellite-and model-based soil moisture products[J].Water Resources Research,2012,48(11).
[37] Long D,Pan Y,Zhou J,et al.Global analysis of spatiotemporal variability in merged total water storage changes using multiple GRACE products and global hydrological models[J].Remote Sensing of Environment,2017,192:198-216.
[38] Davis J L,Herring T A,Shapiro I I,et al.Geodesy by radio interferometry:Effects of atmospheric modeling errors on estimates of baseline length[J].Radio science,1985,20(6):1593-1607.
[39] Bevis M,Businger S,Chiswell S,et al.GPS meteorology:Mapping zenith wet delays onto precipitable water[J].Journal of applied meteorology,1994,33(3):379-386.
[40] Rüeger J M.Refractive index formulae for radio waves[J].Integration of techniques and corrections to achieve accurate engineering,2002:19-26.
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备注/Memo
收稿日期:2021-02-26
基金项目:青海省科技厅应用基础研究基金资助项目(2020-ZJ-739-1)