Précédent|Prochain

FY-3C MWHTS observed brightness temperature quality score based on the multi-source telemetry parameter quality control

  • role： First author第一作者
  • Affiliation：

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

    Innovation Center for Fengyun Meteorological Satellite (FYSIC), China Meteorological Administration, Beijing 100081, China

  • Email：guoyang@cma.gov.cn
  • Introduction：郭杨，研究方向为星载微波仪器定标、微波资料应用。E-mail： guoyang@cma.gov.cn
GUO Yang,  
  • role： Corresponding author通信作者
  • Affiliation：

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

    Innovation Center for Fengyun Meteorological Satellite (FYSIC), China Meteorological Administration, Beijing 100081, China

  • Email：luqf@cma.gov.cn
  • Introduction：陆其峰，研究方向为气象卫星资料同化、卫星探测资料观测系统偏差诊断、订正及卫星观测系统性能优化。E-mail： luqf@cma.gov.cn
LU Qifeng*,  
  • Affiliation：

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

    Innovation Center for Fengyun Meteorological Satellite (FYSIC), China Meteorological Administration, Beijing 100081, China

LU Naimeng,  
  • Affiliation：

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

    Innovation Center for Fengyun Meteorological Satellite (FYSIC), China Meteorological Administration, Beijing 100081, China

GU Songyan,  
  • Affiliation：

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

    Innovation Center for Fengyun Meteorological Satellite (FYSIC), China Meteorological Administration, Beijing 100081, China

LI Xiaoqing,  
  • Affiliation：

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

    Innovation Center for Fengyun Meteorological Satellite (FYSIC), China Meteorological Administration, Beijing 100081, China

QI Chengli,  
  • Affiliation：

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

    Innovation Center for Fengyun Meteorological Satellite (FYSIC), China Meteorological Administration, Beijing 100081, China

DOU Fangli,  
  • Affiliation：

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

    Innovation Center for Fengyun Meteorological Satellite (FYSIC), China Meteorological Administration, Beijing 100081, China

WU Qiong,  
  • Affiliation：

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

    Innovation Center for Fengyun Meteorological Satellite (FYSIC), China Meteorological Administration, Beijing 100081, China

LIU Hui

résumé

FengYun-3C (FY-3C) is the first satellite of the second-generation polar-orbiting operational meteorological satellite in China. As one of the key payloads onboard FY-3C, the MicroWave Humidity and Temperature Sounder (MWHTS) is a cross-track microwave sounder and has 15 channels ranging from 89.0 GHz to 191.0 GHz, with eight (channels 2—9) located near 118.75 GHz along an oxygen absorption line, five (channels 11—15) close to the 183.31 GHz water vapor absorption line, and the remaining two window channels (1 and 10) centered at 89.0 and 150.0 GHz. This instrument’s measurement allows for probing the atmospheric temperature and moisture under clear and cloudy conditions. The MWHTS attracted worldwide attention because of its special configuration. FY-3C MWHTS radiance data have already been assimilated into operational numerical weather prediction models in the European Centre for Medium-Range Weather Forecasts, UK Met Office, and China Meteorological Administration. The calibration accuracy and stability of MWHTS can directly affect the data assimilation effects in NWP. This research establishes a quality control model and observed brightness temperature quality score for MWHTS to filter out the poor quality data during the calibration processing. The five and a half years historical raw data from MWHTS are analyzed. The telemetry parameters from the raw data considered in this study include the blackbody target temperature, instrument temperature, instrument component temperature, counts of the blackbody target and cold space, scan angles, and scan periods. These telemetry parameters thresholds were set accordingly for quality control. Then, based on the radiometer calibration transfer function and observation mechanism of MWHTS, five key parameters (instrument temperature, blackbody target temperature, blackbody view counts, cold space view counts, and scan periods) were selected to score the MWHTS calibration data quality. The sensitivity analysis of each parameter to the differences between the observations and radiance transfer simulations were carried out. The results show that the scan period has the most significant influence on the O-B results, and the instrument temperature has the least effect. The effect proportion was used as the weight to score the observed brightness temperature in centesimal system. The results show that the quality control scheme of each parameter can eliminate abnormal data, and the quality scoring system characterizes the MWHTS calibration quality, and the data application is ensured. The quality control model is established for FY-3C MWHTS to meet the application requirements of onboard microwave observation data. The threshold of the quality control mode depends on the various characteristics of the telemetry data in orbit. This model has been used in the operational calibration algorithm of FY-3C MWHTS, and the score results are included in the MWHTS L1 data to global real-time releases. The MWHTS observed brightness temperature quality score can indicate the data quality throughout the operational in-orbit radiometer calibration. The higher the score, the better the data quality. Accordingly, users can choose the score threshold for data availability according to the application requirements. The quality scoring system is based on only five key telemetry parameters, and more parameters will be analyzed to improve this system in the future.

mots-clés

Fengyun-3C;Microwave Humidity and Temperature Sounder (MWHTS);quality control;observed brightness temperature score;telemetry parameters

References

  1. 1.
    Chen K Y, English S, Bormann N and Zhu J. 2015. Assessment of FY-3A and FY-3B MWHS observations. Weather and Forecasting, 30(5): 1280-1290
  2. 2.
    Choi Y, Cha D H, Lee M I, Kim J, Jin C S, Park S H and Joh M S. 2017. Satellite radiance data assimilation for binary tropical cyclone cases over the western North Pacific. Journal of Advances in Modeling Earth Systems, 9(2): 832-853
  3. 3.
    Dong C H, Yang J, Zhang W J, Yang Z D, Lu N M, Shi J M, Zhang P, Liu Y J and Cai B. 2009. An overview of a new Chinese weather satellite FY-3A. Bulletin of the American Meteorological Society, 90(10): 1531-1544
  4. 4.
    Gu S Y, Guo Y, Wang Z Z and Lu N M. 2012. Calibration analyses for sounding channels of MWHS onboard FY-3A. IEEE Transactions on Geoscience and Remote Sensing, 50(12): 4885-4891
  5. 5.
    Gu S Y, Wang Z Z, Li J and Zhang S W. 2010. The radiometric characteristics of sounding channels for FY-3A/MWHS. Journal of Applied Meteorological Science, 21(3): 335-342
  6. 6.
    Guo Y, Lu N M, Qi C L, Gu S Y and Xu J M. 2015. Calibration and validation of microwave humidity and temperature sounder onboard FY-3C satellite. Chinese Journal of Geophysics, 58(1): 20-31
  7. 7.
    He Q R, Wang Z Z and He J Y. 2017. Retrieval of clear sky temperature and humidity profiles over land using measurements of FY-3C/MWHTS. Journal of Remote Sensing, 21(1): 27-39
  8. 8.
    JPL. 2000. Airs project: algorithm theoretical basis document part 3: microwave instruments. JPL D-17005, version 2.1, Pasadena, California, USA, 1-59
  9. 9.
    Kelly G A and Thépaut J N. 2007. Evaluation of the Impact of the Space Component of the Global Observing System Through Observing System Experiments. ECMWF Newsletter: 16-28[]
  10. 10.
    Kim Y J, Campbell W F and Swadley S D. 2010. Reduction of middle-atmospheric forecast bias through improvement in satellite radiance quality control. Weather and Forecasting, 25(2): 681-700
  11. 11.
    Lawrence H, Bormann N, Geer A J, Lu Q and English S. 2018. Evaluation and assimilation of the microwave sounder MWHS-2 onboard FY-3C in the ECMWF numerical weather prediction system. IEEE Transactions on Geoscience and Remote Sensing, 56(6): 3333-3349
  12. 12.
    Lu N M and Gu S Y. 2016. Review and prospect on the development of meteorological satellites. Journal of Remote Sensing, 20(5): 832-841
  13. 13.
    Lu Q F. 2011. Initial evaluation and assimilation of FY-3A atmospheric sounding data in the ECMWF System. Science China Earth Sciences, 54(10): 1453-1457
  14. 14.
    Matricardi M. 2010. A principal component based version of the RTTOV fast radiative transfer model[J]. Quarterly Journal of the Royal Meteorological Society, 136(652):1823-1835
  15. 15.
    Matricardi M, López Puertas M Funke B. 2018. Modeling of nonlocal thermodynamic equilibrium effects in the principal component based version of the RTTOV fast radiative transfer model. Journal of Geophysical Research: Atmospheres, 123: 5741–5761[]
  16. 16.
    Meng X C, Li H, Du Y M, Cao B, Liu Q H and Li B. 2018. Retrieval and validation of the land surface temperature derived from Landsat 8 data: a case study of the Heihe River Basin. Journal of Remote Sensing, 22(5): 857-871
  17. 17.
    Saunders R, Hocking J, Turner E, Rayer P, Rundle D, Brunel P, Vidot J, Roquet P, Matricardi M, Geer A, Bormann N and Lupu C. 2018. An update on the RTTOV fast radiative transfer model (currently at version 12). Geoscientific Model Development, 11(7): 2717-2737
  18. 18.
    Xue J S. 2009. Scientific issues and perspective of assimilation of meteorological satellite data. Acta Meteorologica Sinica, 67(6): 903-911
  19. 19.
    Yang J, Dong C H, Lu N M, Yang Z D, Shi J M, Zhang P, Liu Y J and Cai B. 2009. FY-3A: the new generation polar-orbiting meteorological satellite of China. Acta Meteorologica Sinica, 67(4): 501-509
  20. 20.
    Yang Y K, Li H, Sun L, Du Y M, Cao B, Liu Q H and Zhu J S. 2019. Land surface temperature and emissivity separation from GF-5 visual and infrared multispectral imager data. Journal of Remote Sensing, 23(6): 1132-1146
  21. 21.
    Zhang M, Lu Q F, Gu S Y, Hu X Q and Wu S L. 2019. Analysis and correction of the difference between the ascending and descending orbits of the FY-3C microwave imager. Journal of Remote Sensing, 23(5): 841-849

Lire l'article complet

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website