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Review of Pre-processing Techniques for Meteorological Satellite Data Assimilation in Numerical Prediction
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摘要: 在数值天气预报变分同化中, 利用同化前处理将卫星资料完成有效信息优选、资料拼接和稀疏化、初级通道选择、下边界参数耦合等处理, 实现卫星资料同化对数值天气预报业务的正贡献, 是决定海量卫星资料同化效率、质量和效果的重要环节。针对多种格式的卫星资料, 中国气象局研发标准格式的高时效卫星资料拼接等技术, 有效减小整轨卫星资料时间滞后对数值天气预报业务的负面影响。对于风云气象卫星资料, 将云和降水检测、资料质量分析等处理置于同化前处理中, 实现多光谱资料融合的同化预质量控制, 保证了风云卫星微波温度探测资料和红外高光谱资料的同化正贡献。利用统一资料格式对预处理卫星资料进行再处理, 拓展针对卫星成像和主动探测资料的处理, 将卫星资料同化的部分质量控制功能置于卫星资料同化前处理中, 是风云卫星资料同化前处理技术发展的重要趋势。Abstract: Satellite data assimilation pre-processing plays a crucial role in bridging satellite data pre-processing and numerical weather prediction model assimilation. It involves integrating pre-processed satellite measurements, orbital splicing and sparsification of satellite data, the fusion of boundary condition parameters under satellite pixels, and the assimilation pre-processing quality control of satellite data by using a unified file format and in accordance with the requirements of the data assimilation system. In the variational assimilation of numerical forecasts, assimilation pre-processing filters effective information from satellite pre-processed measurements, supports the positive contribution of satellite data assimilation to numerical forecast operations, and is an important link in determining the efficiency, quality and effectiveness of assimilation of large quantities of satellite data. In response to the complex format of satellite data from multiple channels, CMA has developed a standard format of high time-sensitive satellite data splicing technology in the pre-processing of satellite data assimilation, which effectively reduces the negative impact of the time lag of whole-orbit satellite data on operational numerical prediction. In the assimilation pre-processing of Fengyun satellite data, the assimilation prequality control of multi-spectral data fusion is achieved by front-loading cloud and precipitation detection, data analysis, analysis and other processing into the assimilation pre-processing, which ensures the positive assimilation contribution of Fengyun microwave temperature sounding data and infrared hyperspectral data. In the development of satellite data assimilation pre-processing technology, reprocessing of pre-processed satellite data by using a unified data format, expanding the processing for satellite imagery and active detection data, and front-loading a part of satellite data assimilation quality control function into data assimilation pre-processing are important trends in the development of future assimilation pre-processing technology for Fengyun satellite data.
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图 1 2023年12月14日12:00 CMA-GFS在6 h时间窗内应该同化的NOAA-19 AMSUA通道1的资料覆盖(a)和实际同化的卫星资料覆盖(b)
Fig. 1 Measurements to Channel 1 of NOAA-19 AMSUA supposed to be assimilated(a) and multi-satellites measurements actually assimilated(b) within 6-hour assimilation time window at 1200 UTC 14 Dec 2023
图 2 2023年12月17日06：00对应6 h同化时间窗内佳木斯、广州和乌鲁木齐3个HRPT站接力拼接的SNPP ATMS通道1的观测亮温覆盖
Fig. 2 Relay stitched mosaic brightness temperature measurements to Channel 1 of SNPP ATMS from HRPT stations of Jiamusi, Guangzhou and Urumqi within 6-hour assimilation time window at 0600 UTC 17 Dec 2023
图 3 2023年12月17日06：00对应6 h同化时间窗内NOAA-18、NOAA-19、METOP-A、METOP-C AMSUA和NOAA-20 ATMS通道1的观测亮温覆盖
Fig. 3 Relay stitched mosaic brightness temperature measurements to Channel 1 of AMSUA of NOAA-18, NOAA-19,METOP-A, METOP-C and ATMS of NOAA-20 global multi-satellite orbital measurements within 6-hour assimilation time window at 0600 UTC 17 Dec 2023
表 1 2019年中国气象局获取的ATOVS轨道和HRPT观测资料
Table 1 ATOVS orbital and HRPT measurements obtained in CMA in 2009
来源 覆盖范围 滞后时效/h 卫星 搭载仪器 资料类型 起始获取年份 NESDIS(GTS) 全球 3~9 NOAA15-19、AQUA AMSU、MHS、AIRS L1B 2004 EUMETSAT(GTS) 全球 3~7 NOAA15-17 AMSU、MHS、HIRS L1B 2007 EUMETSAT(GTS) 全球 3~7 NOAA15-21、SNPP、METOP2-A-C AMSU、MHS、HIRS、CrIS、ATMS、IASI L1C 2009 EUMETCAST (卫星转发) 全球 3~7 NOAA15-21、SNPP、METOP A-C、AQUA AMSU、MHS、IASI、CrIS、ATMS、AIRS L1C 2009 EUMETCAST (卫星转发) 北半球 1~2 NOAA15-21、SNPP、METOP A/B/C、AQUA AMSU、MHS、IASI、CrIS、ATMS、AIRS L1C 2007 RARS (GTS的HRPT站) 全球大部分地区 1.5 NOAA15-21、SNPP、METOP A-C、AQUA AMSU、MHS、IASI、CrIS、ATMS、AIRS L1C 2005 DBnet(GTS的50多个HRPT站) 全球 1~2 NOAA15-21、SNPP、METOP A-C、AQUA AMSU、MHS、IASI、CrIS、ATMS、AIRS L1C 2016 NSMC 东亚 0.5 NOAA15-19、SNPP、AQUA AMSU、MHS、ATMS 源包 1999 
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[1] English S J, Renshaw R J, Dibben P C, et al.A comparison of the impact of TOVS arid ATOVS satellite sounding data on the accuracy of numerical weather forecasts.Q J R Meteor Soc, 2000, 126(569):2911-2931. [2] Eyre J R, Bell W, Cotton J, et al. Assimilation of satellite data in numerical weather prediction. Part Ⅱ: Recent years. Q J R Meteor Soc, 2022, 148(743): 521-556. doi: 10.1002/qj.4228 [3] Kaplan L D. Inference of atmospheric structure from remote radiation measurements. J Opt Soc Amer, 1959, 49(10): 1004-1007. doi: 10.1364/JOSA.49.001004 [4] McMillin L M, Dean C. Evaluation of a new operational technique for producing clear radiances. J Appl Meteor, 1982, 21(7): 1005-1014. doi: 10.1175/1520-0450(1982)021<1005:EOANOT>2.0.CO;2 [5] Stogryn A. Estimates of brightness temperatures from scanning radiometer data. IEEE Trans Anntenas Propag, 1978, 26(5): 720-726. doi: 10.1109/TAP.1978.1141919 [6] Andersson E, Pailleux J, Thepaut J N, et al. Use of cloud-cleared radiances in three/four-dimensional variational data assimilation. Q J R Meteor Soc, 1994, 120(517): 627-653. [7] McNally A P, Vesperini M. Variational analysis of humidity information from TOVS radiances. Q J R Meteor Soc, 1996, 122(535): 1521-1544. doi: 10.1002/qj.49712253504 [8] 周雪松, 郭启云, 夏元彩, 等. 基于往返式平漂探空的FY-3D卫星反演温度检验. 应用气象学报, 2023, 34(1): 52-64. doi: 10.11898/1001-7313.20230105Zhou X S, Guo Q Y, Xia Y C, et al. Inspection of FY-3D satellite temperature data based on horizontal drift round-trip sounding data. J Appl Meteor Sci, 2023, 34(1): 52-64. doi: 10.11898/1001-7313.20230105 [9] Ohring G. Impact of satellite temperature sounding data on wea- ther forecasts. Bull Amer Meteor Soc, 1979, 60(10): 1142-1147. doi: 10.1175/1520-0477(1979)060<1142:IOSTSD>2.0.CO;2 [10] Lorenc A C. Analysis methods for numerical weather prediction. Q J R Meteor Soc, 1986, 112(474): 1177-1194. doi: 10.1002/qj.49711247414 [11] Talagrand O, Courtier P. Variational assimilation of meteorological observations with the adjoint vorticity equation. Ⅰ: Theory. Q J R Meteor Soc, 1987, 113(478): 1311-1328. doi: 10.1002/qj.49711347812 [12] Eyre J. A Fast Radiative Transfer Model for Satellite Sounding Systems. ECMWF Technical Memorandum, 176, 1991. [13] McMillin L M, Crone L J, Goldberg M D, et al. Atmospheric transmittance of an absorbing gas. 4. OPTRAN: A computationally fast and accurate transmittance model for absorbing gases with fixed and with variable mixing ratios at variable viewing angles. Appl Opt, 1995, 34(27): 6269-6274. doi: 10.1364/AO.34.006269 [14] Eyre J R, Kelly G A, McNally A P, et al. Assimilation of TOVS radiance information through one-dimensional variational analysis. Q J R Meteor Soc, 1993, 119(514): 1427-1463. [15] Derber J C, Wu W S. The use of TOVS cloud-cleared radiances in the NCEP SSI analysis system. Mon Wea Rev, 1998, 126(8): 2287-2299. doi: 10.1175/1520-0493(1998)126<2287:TUOTCC>2.0.CO;2 [16] McNally A, Andersson E, Kelly G, et al. The Use of Raw TOVS/ATOVS Radiances in the ECMWF 4D-var Assimilation System//Technical Proceedings of the 10th International TOVS Study Conference, 1999: 377-384. [17] 王金成, 陆慧娟, 韩威, 等. GRAPES全球三维变分同化业务系统性能. 应用气象学报, 2017, 28(1): 11-24. doi: 10.11898/1001-7313.20170102Wang J C, Lu H J, Han W, et al. Improvements and performances of the operational GRAPES_GFS 3Dvar system. J Appl Meteor Sci, 2017, 28(1): 11-24. doi: 10.11898/1001-7313.20170102 [18] Zhang L, Liu Y Z, Liu Y, et al. The operational global four-dimensional variational data assimilation system at the China Meteorological Administration. Q J R Meteor Soc, 2019, 145(722): 1882-1896. doi: 10.1002/qj.3533 [19] Lorenc A C. A global three-dimensional multivariate statistical interpolation scheme. Mon Wea Rev, 1981, 109(4): 701-721. doi: 10.1175/1520-0493(1981)109<0701:AGTDMS>2.0.CO;2 [20] Smith W L, Woolf H M. The use of eigenvectors of statistical covariance matrices for interpreting satellite sounding radiometer observations. J Atmos Sci, 1976, 33(7): 1127-1140. doi: 10.1175/1520-0469(1976)033<1127:TUOEOS>2.0.CO;2 [21] Saunders R, Matricardi M, Brunel P. An improved fast radiative transfer model for assimilation of satellite radiance observations. Q J R Meteor Soc, 1999, 125(556): 1407-1425. doi: 10.1002/qj.1999.49712555615 [22] McNally A P, Derber J C, Wu W, et al. The use of TOVS level-1b radiances in the NCEP SSI analysis system. Q J R Meteor Soc, 2000, 126(563): 689-724. [23] 李喆, 陈炯, 马占山, 等. CMA-GFS云预报的偏差分布特征. 应用气象学报, 2022, 33(5): 527-540. doi: 10.11898/1001-7313.20220502Li Z, Chen J, Ma Z S, et al. Deviation distribution features of CMA-GFS cloud prediction. J Appl Meteor Sci, 2022, 33(5): 527-540. doi: 10.11898/1001-7313.20220502 [24] English S, Renshaw R, Dibben P, et al. The AAPP Module for Identifying Precipitation, Ice Cloud, Liquid Water and Surface Types on the AMSU-A grid//Technical Proceedings of the 9th International TOVS Study Conference, 1997: 119-130. [25] Saunders R, Andersson E, Kelly G, et al. Developments in Assimilating Global TOVS Data at the UK Met Office//Technical Proceedings of the 9th International TOVS Study Conference, 1997: 417-428. [26] English S J, Eyre J R, Smith J A. A cloud-detection scheme for use with satellite sounding radiances in the context of data assimilation for numerical weather prediction. Q J R Meteor Soc, 1999, 125(559): 2359-2378. [27] 董超华, 张凤英, 郑波, 等. 卫星区域大气探测业务处理系统. 应用气象学报, 1991, 2(1): 22-31. http://qikan.camscma.cn/article/id/19910103Dong C H, Zhang F Y, Zheng B, et al. A regional satellite atmosphere sounding data operational processing system. J Appl Meteor Sci, 1991, 2(1): 22-31. http://qikan.camscma.cn/article/id/19910103 [28] 钱建梅, 郑旭东. 国家卫星气象中心气象卫星资料存档系统. 应用气象学报, 2003, 14(6): 756-762. doi: 10.3969/j.issn.1001-7313.2003.06.015Qian J M, Zheng X D. The satellite data archive system of National Satellite Meteorological Center. J Appl Meteor Sci, 2003, 14(6): 756-762. doi: 10.3969/j.issn.1001-7313.2003.06.015 [29] Geer A J, Baordo F, Bormann N, et al. The growing impact of satellite observations sensitive to humidity, cloud and precipitation. Q J R Meteor Soc, 2017, 143(709): 3189-3206. doi: 10.1002/qj.3172 [30] Menzel W P, Schmit T J, Zhang P, et al. Satellite-based atmospheric infrared sounder development and applications. Bull Amer Meteor Soc, 2018, 99(3): 583-603. doi: 10.1175/BAMS-D-16-0293.1 [31] Noh Y, Sohn B, Kim Y, et al. A new infrared atmospheric sounding interferometer channel selection and assessment of its impact on Met Office NWP Forecasts. Adv Atmos Sci, 2017, 34: 1265-1281. doi: 10.1007/s00376-017-6299-8 [32] Rodgers C D. Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation. Rev Geophys, 1976, 14(4): 609-624. doi: 10.1029/RG014i004p00609 [33] Goldberg M D, Qu Y, McMillin L M, et al. AIRS near-real-time products and algorithms in support of operational numerical weather prediction. IEEE Trans Geosci Remote Sens, 2003, 41(2): 379-389. doi: 10.1109/TGRS.2002.808307 [34] Zhang Q. Impacts on initial condition modification from hyperspectral infrared sounding data assimilation: Comparisons between full-spectrum and channel-selection scheme based on two-month experiments using CrIS and IASI observation. Inter J Geosci, 2021, 12(9): 763-783. doi: 10.4236/ijg.2021.129043 [35] Chen Y, Han Y. Evaluation of Different Calibration Approaches for S-NPP CRIS Full Spectral Resolution SDR Processing//IEEE International Geoscience and Remote Sensing Symposium(IGARSS), 2015: 2127-2130. [36] Collard A D. Selection of IASI channels for use in numerical weather prediction. Q J R Meteor Soc, 2007, 133(629): 1977-1991. doi: 10.1002/qj.178 [37] Smith J, Gambacorta A, Barnet C, et al. The NPP and J1 CrIS Operational High-Resolution Channel Selection for the NUCAPS algorithm: A Demonstration of Global Applicability to Meet Users Needs//AGU Fall Meeting, 2016. [38] 马刚, 郭杨, 苏婧, 等. 卫星探测通道晴空大气吸收透过率快速计算研究进展. 地球物理学报, 2023, 66(6): 2275-2291. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWX202306005.htmMa G, Guo Y, Su J, et al. An overview of fast calculation to clear atmospheric absorption transmittance of satellite channel. Chinese J Geophys, 2023, 66(6): 2275-2291. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWX202306005.htm [39] Pavelin E G, Candy B. Assimilation of surface-sensitive infrared radiances over land: Estimation of land surface temperature and emissivity. Q J R Meteor Soc, 2014, 140(681): 1198-1208. doi: 10.1002/qj.2218 [40] Duan S B, Han X J, Huang C, et al. Land surface temperature retrieval from passive microwave satellite observations: State-of-the-art and future directions. Remote Sens, 2020, 12(16). DOI: 10.3390/rs12162573. [41] Prigent C, Aires F, Wang D, et al. Sea-surface emissivity parametrization from microwaves to millimetre waves. Q J R Meteor Soc, 2017, 143(702): 596-605. doi: 10.1002/qj.2953 [42] Karbou F, Prigent C, Eymard L, et al. Microwave land emissivity calculations using AMSU measurements. IEEE Trans Geosci Remote Sens, 2005, 43(5): 948-959. doi: 10.1109/TGRS.2004.837503 [43] Xiao H Y, Li J, Liu G Q, et al. Assimilation of AMSU-A surface-sensitive channels in CMA-GFS 4D-var system over land. Wea Forecasting, 2023, 38(9): 1777-1790. doi: 10.1175/WAF-D-23-0032.1 [44] Noh Y C, Lim A H N, Huang H L, et al. Global forecast impact of low data latency infrared and microwave sounders observations from polar orbiting satellites. Remote Sens, 2020, 12(14). DOI: 10.3390/rs12142193. [45] Diaz S W, CIMAS, Miami F L, et al. Impact of Satellite Data Latency on Global Weather Forecasts. 100th American Meteorological Society, 2020. [46] Lin H D, Weygandt S S, Benjamin S G, et al. Satellite radiance data assimilation within the hourly updated rapid refresh. Wea Forecasting, 2017, 32(4): 1273-1287. doi: 10.1175/WAF-D-16-0215.1 [47] Liou K N. An Introduction to Atmospheric Radiation. New York, 2002. [48] 沈学顺, 苏勇, 胡江林, 等. GRAPES_GFS全球中期预报系统的研发和业务化. 应用气象学报, 2017, 28(1): 1-10. doi: 10.11898/1001-7313.20170101Shen X S, Su Y, Hu J L, et al. Development and operation transformation of GRAPES global middle-range forecast system. J Appl Meteor Sci, 2017, 28(1): 1-10. doi: 10.11898/1001-7313.20170101 [49] Liu Z Q, Jiang L P, Shi C X, et al. CRA-40/Atmosphere-The first-generation Chinese atmospheric reanalysis(1979-2018): System description and performance evaluation. J Meteor Res, 2023, 37(1): 1-19. doi: 10.1007/s13351-023-2086-x [50] 张进, 孙健, 沈学顺, 等. CMA-GFS V4.0模式关键技术研发和业务化. 应用气象学报, 2023, 34(5): 513-526. doi: 10.11898/1001-7313.20230501Zhang J, Sun J, Shen X S, et al. Key model technologies of CMA-GFS V4.0 and application to operational forecast. J Appl Meteor Sci, 2023, 34(5): 513-526. doi: 10.11898/1001-7313.20230501 [51] Zhang P, Lu Q F, Hu X Q, et al. Latest progress of the Chinese meteorological satellite program and core data processing technologies. Adv Atmos Sci, 2019, 36(9): 1027-1045. doi: 10.1007/s00376-019-8215-x [52] 董佩明, 王海军, 韩威, 等. 水物质对云雨区卫星微波观测模拟影响. 应用气象学报, 2009, 20(6): 682-691. doi: 10.3969/j.issn.1001-7313.2009.06.005Dong P M, Wang H J, Han W, et al. The effect of water content on the simulation of satellite microwave observation in cloudy and rainy area. J Appl Meteor Sci, 2009, 20(6): 682-691. doi: 10.3969/j.issn.1001-7313.2009.06.005 [53] 谷松岩, 王振占, 马刚, 等. 气象卫星微波大气遥感. 北京: 科学出版社, 2021.Gu S Y, Wang Z Z, Ma G. Meteorological Satellite Microwave Atmospheric Remote Sensing. Beijing: Science Press, 2021. [54] English S, McNally A, Bormann N, et al. Impact of satellite data. ECMWF Technical Memorandum 804, 2013. [55] Wang L K, Tremblay D, Zhang B, et al. Fast and accurate collocation of the visible infrared imaging radiometer suite measurements with cross-track infrared sounder. Remote Sens, 2016, 8(1). DOI: 10.3390/rs8010076. [56] Li J, Liu G Q. Direct assimilation of Chinese FY-3C microwave temperature sounder-2 radiances in the global GRAPES system. Atmos Meas Tech, 2016, 9(7): 3095-3113. doi: 10.5194/amt-9-3095-2016 [57] Qin L Y, Chen Y D, Yu T L, et al. Dynamic channel selection of microwave temperature sounding channels under cloudy conditions. Remote Sens, 2020, 12(3). DOI: 10.3390/rs12030403. [58] Qin L Y, Chen Y D, Ma G, et al. Assimilation of FY-3D MWTS-Ⅱ radiance with 3D precipitation detection and the impacts on typhoon forecasts. Adv Atmos Sci, 2023, 40(5): 900-919. doi: 10.1007/s00376-022-1252-x [59] Kan W L, Dong P M, Weng F Z, et al. Impact of Fengyun-3E microwave temperature and humidity sounder data on CMA global medium range weather forecasts. Remote Sens, 2022, 14(19). DOI: 10.3390/rs14195014. [60] Ventress L, Dudhia A. Improving the selection of IASI channels for use in numerical weather prediction. Q J R Meteor Soc, 2014, 140(684): 2111-2118. doi: 10.1002/qj.2280 [61] Yin R Y, Han W, Gao Z Q, et al. The evaluation of FY4A's Geostationary Interferometric Infrared Sounder(GIIRS) long-wave temperature sounding channels using the GRAPES global 4D-Var. Q J R Meteor Soc, 2020, 146(728): 1459-1476. doi: 10.1002/qj.3746 [62] Yan X S, Chen Y D, Ma G, et al. A 3-D cloud detection method for FY-4A GIIRS and its application in operational numerical weather prediction system. IEEE Trans Geosci Remote Sens, 2023, 61: 1-13. [63] 王素娟, 崔鹏, 张鹏, 等. FY-3C/VIRR海表温度产品及质量检验. 应用气象学报, 2020, 31(6): 729-739. doi: 10.11898/1001-7313.20200608Wang S J, Cui P, Zhang P, et al. FY-3C/VIRR sea surface temperature products and quality validation. J Appl Meteor Sci, 2020, 31(6): 729-739. doi: 10.11898/1001-7313.20200608 [64] 崔鹏, 王素娟, 陆风, 等. FY-4A/AGRI海表温度产品和质量检验. 应用气象学报, 2023, 34(3): 257-269. doi: 10.11898/1001-7313.20230301Cui P, Wang S J, Lu F, et al. FY-4A/AGRI sea surface temperature product and quality validation. J Appl Meteor Sci, 2023, 34(3): 257-269. doi: 10.11898/1001-7313.20230301 [65] Xiao H Y, Han W, Wang H, et al. Impact of FY-3D MWRI radiance assimilation in GRAPES 4DVar on forecasts of Typhoon Shanshan. J Meteor Res, 2020, 34(4): 836-850. doi: 10.1007/s13351-020-9122-x [66] 郭杨, 陆其峰, 卢乃锰, 等. 多源遥测参数质量控制的FY-3C MWHTS观测亮温质量评分. 遥感学报, 2022, 26(11): 2147-2161. https://www.cnki.com.cn/Article/CJFDTOTAL-YGXB202211003.htmGuo Y, Lu Q F, Lu N M, et al. FY-3C MWHTS observed brightness temperature quality score based on the multi-source telemetry parameter quality control. National Remote Sens Bull, 2022, 26(11): 2147-2161. https://www.cnki.com.cn/Article/CJFDTOTAL-YGXB202211003.htm [67] Qi C L, Wu C Q, Hu X Q, et al. High spectral infrared atmospheric sounder(HIRAS): System overview and on-orbit performance assessment. IEEE Trans Geosci Remote Sens, 2020, 58(6): 4335-4352. doi: 10.1109/TGRS.2019.2963085 [68] McNally C. Assimilation of Radiance Products from Geostationary Satellites: 1-year Report. EUMET/ECMWF Fellowship Programme Research Reports 21, 2011. [69] Burrows C. Assimilation of Radiance Observations from Geostationary Satellites: Third Year Report. EUMET/ECMWF Fellowship Programme Research Reports 52, 2020. [70] Li J, Geer A J, Okamoto K, et al. Satellite all-sky infrared radiance assimilation: Recent progress and future perspectives. Adv Atmos Sci, 2022, 39(1): 9-21. doi: 10.1007/s00376-021-1088-9 [71] Lu Y H, Zhang F Q. A novel channel-synthesizing method for reducing uncertainties in satellite radiative transfer modeling. Geophys Res Lett, 2018, 45(10): 5115-5125. doi: 10.1029/2018GL077342 [72] Yu T L, Ma G, Lu F, et al. Quality scoring of the Fengyun 4A clear sky radiance product. Remote Sens, 2021, 13(18). DOI: 10.3390/rs13183658. [73] 王春芳, 李湘, 陈永涛, 等. 中国气象局卫星广播系统(CMACast)设计. 应用气象学报, 2012, 23(1): 113-120. doi: 10.3969/j.issn.1001-7313.2012.01.013Wang C F, Li X, Chen Y T, et al. Design of CMA's broadcast system for meteorological data-CMACast. J Appl Meteor Sci, 2012, 23(1): 113-120. doi: 10.3969/j.issn.1001-7313.2012.01.013 [74] 黄丽萍, 邓莲堂, 王瑞春, 等. CMA-MESO关键技术集成及应用. 应用气象学报, 2022, 33(6): 641-654. doi: 10.11898/1001-7313.20220601Huang L P, Deng L T, Wang R C, et al. Key technologies of CMA-MESO and application to operational forecast. J Appl Meteor Sci, 2022, 33(6): 641-654. doi: 10.11898/1001-7313.20220601 -
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