Wang Hong, Zhou Houfu, Wang Chen, et al. Accuracy validation of FY-4A temperature profile based on microwave radiometer and radiosonde. J Appl Meteor Sci, 2023, 34(3): 295-308. DOI:  10.11898/1001-7313.20230304.
Citation: Wang Hong, Zhou Houfu, Wang Chen, et al. Accuracy validation of FY-4A temperature profile based on microwave radiometer and radiosonde. J Appl Meteor Sci, 2023, 34(3): 295-308. DOI:  10.11898/1001-7313.20230304.

Accuracy Validation of FY-4A Temperature Profile Based on Microwave Radiometer and Radiosonde

DOI: 10.11898/1001-7313.20230304
  • Received Date: 2023-01-14
  • Rev Recd Date: 2023-02-28
  • Publish Date: 2023-05-31
  • To take full advantage of FY-4A temperature profile data to understand the evolutions of weather processes and nowcasting, based on the atmospheric temperature profile of radiosonde, microwave radiometer and FY-4A satellite from 1 January 2021 to 31 March 2022, 897 samples are matched and their deviation characteristics are evaluated. The results show that the correlation coefficient between FY-4A satellite temperature and that of microwave radiometer is 0.9891, and the correlation coefficient between FY-4A satellite temperature and that of radiosonde is 0.9820. The mean temperature of FY-4A satellite is 0.51℃ smaller than that of the radiosonde below 10 km height, and the standard deviation is 0.50℃. The mean temperature of FY-4A satellite is 0.53℃ larger than that of the microwave radiometer below 10 km, and the standard deviation is 0.75℃. FY-4A temperature is consistent with the mean deviation trend of the radiosonde at 0000 UTC and 1200 UTC. Compared with 0000 UTC, the deviation sample of FY-4A at 1200 UTC is less discrete. When there is precipitation, the temperature deviation of microwave radiometer and FY-4A gradually increases above 600 m height, and the deviation reaches the maximum (about 9.35℃) near 1500 m height. In the range of 3000-8500 m height, the deviation ranges from 1.35℃ to 5.10℃, and the standard deviation ranges from 1.41℃ to 4.99℃. In the case of precipitation, the deviation values and standard deviations of FY-4A temperature and radiosonde are small. Although the deviation values and standard deviations of FY-4A temperature and radiosonde are different at different heights in the whole layer, the deviation is between -0.31 and 3.60℃. When there are clouds, the mean deviation between FY-4A temperature and that of microwave radiometer is -0.40℃, and the mean standard deviation is 3.79℃. The overall mean deviation between FY-4A temperature and radiosonde is 0.31℃, and the mean standard deviation is 2.66℃. Both the deviation and standard deviation between FY-4A temperature and that of microwave radiometer are larger than those between FY-4A and radiosonde when there are clouds. The deviation and standard deviation of microwave radiometer temperature and that of radiosonde with FY-4A are small in clear sky. The above conclusions can provide reference for the further use of FY-4A satellite data, as well as for the quality control of FY-4A satellite data and its application in weather analysis and forecast.
  • Fig. 1  Temperature deviation NCFADs at different heights from 1 Jan 2021 to 31 Mar 2022

    Fig. 2  Temperature deviation frequency distribution of microwave radiometer and radiosonde from FY-4A from 1 Jan 2021 to 31 Mar 2022

    Fig. 3  Temperature deviation frequency distribution of microwave radiometer and radiosonde from FY-4A at different heights from 1 Jan 2021 to 31 Mar 2022

    Fig. 4  Temperature deviation NCFADs of microwave radiometer and radiosonde from FY-4A at different times from 1 Jan 2021 to 31 Mar 2022

    Fig. 5  Temperature deviation NCFADs of microwave radiometer and radiosonde from FY-4A under different precipitation backgrounds from 1 Jan 2021 to 31 Mar 2022

    Fig. 6  Temperature deviation NCFADs of microwave radiometer and radiosonde from FY-4A under different cloud backgrounds from 1 Jan 2021 to 31 Mar 2022

    Table  1  Temperature profile information of microwave radiometer, radiosonde and FY-4A satellite

    参数 微波辐射计 探空 FY-4A/GIIRS
    最大探测高度 10 km 25 km 大气层顶
    垂直层数 93 约90 101
    垂直分辨率 20~400 m 6~700 m 200~1000 m
    时间分辨率 2~3 s 12 h 2 h
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    Table  2  Deviation statistics of microwave radiometer and radiosonde relative to FY-4A at different levels(unit:℃)

    高度 探空与FY-4A的温度偏差 微波辐射计与FY-4A的温度偏差
    平均值 标准差 平均值 标准差
    0~220 m -0.04 0.72 -1.61 0.59
    250~1000 m 0.16 0.71 -0.43 0.92
    1040~3000 m 0.69 0.21 0.06 0.53
    3100~8700 m 0.74 0.12 -0.73 0.10
    9000~10000 m 0.48 0.15 0.75 0.10
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  • [1]
    Bao Y S, Qian C, Min J Z, et al. 0~10 km temperature and humidity profiles retrieval from ground-based microwave radiometer. J Trop Meteor, 2016, 32(2): 163-171. https://www.cnki.com.cn/Article/CJFDTOTAL-RDQX201602003.htm
    [2]
    Liu H Y, Li J, Cao X Y, et al. Characteristics of the atmosphere remote sensed by the ground-based 12-channel radiometer. Remote Sens Technol Appl, 2007, 22(2): 222-229. https://www.cnki.com.cn/Article/CJFDTOTAL-YGJS200702019.htm
    [3]
    Cui X D, Tang P Y, Yao Z G, et al. Result analysis of observations by airborne microwave instruments on multi-altitude flights. J Trop Meteor, 2019, 35(2): 224-233. https://www.cnki.com.cn/Article/CJFDTOTAL-RDQX201902008.htm
    [4]
    Yang Y H, Yin Q, Shu J. Channel selection of atmosphere vertical sounder(GⅡRS) onboard the FY-4A geostationary satellite. J Infrared Millim Waves, 2018, 37(5): 545-552. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYH201805007.htm
    [5]
    Han F, Yang L, Zhou C X, et al. An experimental study of the short-time heavy rainfall event forecast based on ensemble learning and sounding data. J Appl Meteor Sci, 2021, 32(2): 188-199. doi:  10.11898/1001-7313.20210205
    [6]
    Zhou 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
    [7]
    Liu H Y, Wang Y C, Wang J L, et al. Preliminary analysis of the characteristics of precipitable water vapor measured by the ground-based 12-channel microwave radiometer in Beijing. Chinese J Atmos Sci, 2009, 33(2): 388-396. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXK200902017.htm
    [8]
    Lin X M, Wei Y H, Zhang N, et al. Construction of air-sounding-profile system based on foundation-remote-sensing equipment. J Appl Meteor Sci, 2022, 33(5): 568-580. doi:  10.11898/1001-7313.20220505
    [9]
    Chen S C, Li X B, Cui M, et al. Error analysis of detection data of microwave radiometer and wind profiler radar under different weather conditions. J Meteor Environ, 2021, 37(1): 67-72. https://www.cnki.com.cn/Article/CJFDTOTAL-LNQX202101009.htm
    [10]
    Xu G R, Sun Z T, Li W J, et al. Observational comparison among microwave water radiometer, GPS radiosonde and GPS/MET. Torrential Rain Disaster, 2010, 29(4): 315-321. doi:  10.3969/j.issn.1004-9045.2010.04.003
    [11]
    Yang Z G, Chen H B. Retrieval of atmospheric temperature profiles with neural network inversion of microwave radiometer data in 6 channels near 118.75 GHz. Scientia Meteor Sinica, 2006, 26(3): 3252-3259. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKX200603002.htm
    [12]
    Li G, Wang H Y, Chai S Y, et al. An analysis on troposphere and stratosphere thermal structure by radiosonde data. Journal of Yunnan University(Nat Sci Ed), 2014, 36(3): 384-391. https://www.cnki.com.cn/Article/CJFDTOTAL-YNDZ201403015.htm
    [13]
    Liang Z H, Wang D H, Liang Z M. Spatio-temporal characteristics of boundary layer height derived from soundings. J Appl Meteor Sci, 2020, 31(4): 447-459. doi:  10.11898/1001-7313.20200407
    [14]
    Wu H K, Chen Q Y, Hua W, et al. A statistical study of gravity wave with second-level radiosonde data in Sichuan. J Appl Meteor Sci, 2019, 30(4): 491-501. doi:  10.11898/1001-7313.20190409
    [15]
    Cao Y Y, Zhang P, Ma G, et al. An improvement of brightness temperature simulation of FY-3 IRAS infrared water vapor channel. J Appl Meteor Sci, 2016, 27(6): 698-708. doi:  10.11898/1001-7313.20160606
    [16]
    Luo Q, Min W B, Peng J. Contrastive analysis of humidity data between FY-2E and sounding. Plateau Mountain Meteor Res, 2014, 34(1): 29-32. https://www.cnki.com.cn/Article/CJFDTOTAL-SCCX201401005.htm
    [17]
    Tang W Y, Bao Y S, Zhang X Y, et al. Comparison of FY-3A/MERSI, MODIS C5.1, C6 and AERONET aerosol optical depth in China. Acta Meteor Sinica, 2018, 76(3): 449-460. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB201803009.htm
    [18]
    Zhou A M. Atmospheric Temperature and Humidity Profiles Retrieval from Hyperspectral Infrared Simulation Data Based on FY-4. Nanjing: Nanjing University of Information Science & Technology, 2017.
    [19]
    Wang S J, Cui P, Zhang P, et al. The improvement of FY-3B/VIRR SST algorithm and its accuracy. J Appl Meteor Sci, 2014, 25(6): 701-710. http://qikan.camscma.cn/article/id/20140606
    [20]
    Kuo Y H, Schreiner W S, Wang J, et al. Comparison of GPS radio occultation soundings with radiosondes. Geophys Res Lett, 2005, 32(5). DOI: / 10.1029/2004GL021443.
    [21]
    Zhang Q C, Gong D L, Wang J, et al. Characteristics of water vapor and liquid water content retrieved by ground-based microwave radiometer in Jinan. J Meteor Environ, 2017, 33(5): 35-43. https://www.cnki.com.cn/Article/CJFDTOTAL-LNQX201705005.htm
    [22]
    Zhang Q C, Gong D L, Feng J J. Analysis and evaluation of retrieval products of RPG-HATPRO-G3 ground-based microwave radiometers. J Mar Meteor, 2017, 37(1): 104-110. https://www.cnki.com.cn/Article/CJFDTOTAL-SDQX201701012.htm
    [23]
    Zhang D G, Wang H, Cui Y Q, et al. Analysis of atmospheric boundary layer inversion characteristics based on microwave radiometer observations in Jinan in 2015. Arid Meteor, 2017, 35(1): 43-50. https://www.cnki.com.cn/Article/CJFDTOTAL-GSQX201701006.htm
    [24]
    Cui Y Q, Zhang D G, Gong D L, et al. Application of new detecting instrument data in short-time heavy rainfall. Meteor Sci Technol, 2016, 44(6): 875-881. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ201606005.htm
    [25]
    Cui Y Q, Zhang D G, Wang H, et al. Preliminary analysis of atmospheric physical quantity characteristics during haze weather in Jinan area in 2015. Chinese J Atmos Sci, 2019, 43(4): 705-718. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXK201904001.htm
    [26]
    Liu B C, Zhou B C, Lian P. Typical error analysis of antenna feeder subsystem of GFE(L)1 secondary wind measuring radar. Heilongjiang Meteor, 2010, 27(6): 35-36. https://www.cnki.com.cn/Article/CJFDTOTAL-HLJQ201002017.htm
    [27]
    Fu Y F, Lin Y H, Liu G S, et al. Seasonal characteristics of precipitation in 1998 over East Asia as derived from TRMM PR. Adv Atmos Sci, 2003, 20(4): 511-529.
    [28]
    Luo Y, Zhang R H, Wang H. Comparing occurrences and vertical structures of hydrometeors between eastern China and the Indian monsoon region using Cloud Sat/CALIPSO data. J Climate, 2009, 22(4): 1052.
    [29]
    Yin J F, Wang D H, Zhai G Q, et al. A study of cloud vertical profiles from the Cloudsat data over the East Asian Continent. Acta Meteor Sinica, 2013, 71(1): 121-133. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB201301010.htm
    [30]
    Yuter S E, Houze Jr R A. Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part Ⅱ: Frequency distributions of vertical velocity, reflectivity, and differential reflectivity. Mon Wea Rev, 1995, 123(7): 1941-1963.
    [31]
    He M, Wang D H, Ding W Y, et al. A validation of Fengyun4A temperature and humidity profile products by radiosonde observations. Remote Sens-Basel, 2019, 11(17): 2039.
    [32]
    Yang J, Zhang Z Q, Wei C Y, et al. Introducing the new generation of Chinese geostationary weather satellites, Fengyun-4. Bull Amer Meteor Soc, 2017, 98(8): 1637-1658.
    [33]
    Xue Q M. Research on Retrieval Algorithm of All Sky Atmospheric Temperature and Humidity Profiles from the FY-4A GⅡRS. Nanjing: Nanjing University of Information Science & Technology, 2022.
    [34]
    Huang Y W, Liu Q, He M, et al. Research on inversion precision of temperature profile of GⅡRS/FY-4A satellite in Shanghai typhoon season based on radiosonde data. Infrared, 2019, 40(9): 28-38. https://www.cnki.com.cn/Article/CJFDTOTAL-HWAI201909006.htm
    [35]
    Ma Y, Yao W, Huang B X. Comparison of temperature and geopotential height records between L-band and RS90/92 radiosonde systems using first-guess field. J Appl Meteor Sci, 2011, 22(3): 336-345. http://qikan.camscma.cn/article/id/20110310
    [36]
    Ma Y, Yao W, Huang B X. Comparison of temperature and geopotential height records between 59 type and L-band radiosonde systems. J Appl Meteor Sci, 2010, 21(2): 214-220. http://qikan.camscma.cn/article/id/20100211
    [37]
    Yao W, Ma Y. Evaluation on the random error of second level sounding data. J Appl Meteor Sci, 2015, 26(5): 600-609. doi:  10.11898/1001-7313.20150509
    [38]
    He Q Y, Li Y J, Ran G H, et al. Performance evaluation of three new digital radiosondes: GTS11, GTS12 and GTS13. Mid-low Latitude Mountain Meteorology, 2022, 46(2): 114-117. https://www.cnki.com.cn/Article/CJFDTOTAL-GZQX202202019.htm
    [39]
    Chen R, Li K, Yang W J, et al. Comparative analysis of parallel observation data of changeover sondes at Yinchuan Station. Ningxia Eng Technol, 2022, 21(2): 114-117;123. https://www.cnki.com.cn/Article/CJFDTOTAL-NXGJ202202004.htm
    [40]
    Wang H, Lei H C, Yang C, et al. A comparison of datasets of precipitable water vapor over Jinan retrieved by three kinds of equipments. J Mar Meteor, 2017, 37(2): 83-89. https://www.cnki.com.cn/Article/CJFDTOTAL-SDQX201702010.htm
    [41]
    Zhang W G, Xu G R, Yan G P, et al. Comparative analysis of microwave radiometer and radiosonde data. Meteor Sci Technol, 2014, 42(5): 737-741. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ201405002.htm
    [42]
    Chen Y Y, Yang F, Xu G R, et al. Comparative analysis of the zenith and off-zenith retrieved results from microwave radiometer in rain and snow weather conditions. Torrential Rain Disaster, 2015, 34(4): 375-383. https://www.cnki.com.cn/Article/CJFDTOTAL-HBQX201504011.htm
    [43]
    Li Z, Chen J, Ma Z S, et al. Deviation distribution features of CMA-GFS cloud precipitation. J Appl Meteor Sci, 2022, 33(5): 527-540. doi:  10.11898/1001-7313.20220502
    [44]
    Chang Y, Chen H B, Shi H R, et al. Comparison of atmospheric temperature and humidity sounding by different sensors onboard a new composite wing UAV. J Appl Meteor Sci, 2023, 34(1): 78-90. doi:  10.11898/1001-7313.20230107
    [45]
    Ren S L, Niu N, Qin D Y, et al. Extreme cold and snowstorm event in North America in February 2021 based on satellite data. J Appl Meteor Sci, 2022, 33(6): 696-710. doi:  10.11898/1001-7313.20220605
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    • Received : 2023-01-14
    • Accepted : 2023-02-28
    • Published : 2023-05-31

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