多源遥测参数质量控制的FY-3C MWHTS观测亮温质量评分
FY-3C MWHTS observed brightness temperature quality score based on the multi-source telemetry parameter quality control
- 2022年26卷第11期 页码：2147-2161
纸质出版日期： 2022-11-07
DOI： 10.11834/jrs.20220130
扫 描 看 全 文
浏览全部资源
扫码关注微信
摘要
微波湿温探测仪（MWHTS）是中国第二代极轨气象卫星风云三号C星（FY-3C）的主要传感器之一，其观测资料的同化受到国内外科学家的广泛关注。卫星观测资料的精度和稳定性是决定其能否被同化及同化效果好坏的关键之一，而卫星平台环境变化和星上到地面进行数据传输时的误码都会直接影响观测资料精度和稳定性，从而影响资料的同化效果。为了解决这一问题，建立了多源遥测参数质量控制模型。首先从星上直接获取的FY-3C MWHTS原始数据包出发，对解码后影响仪器性能的各类遥测参数进行长时间（5年半）序列时变特征分析，建立质量控制方案，完成了多源遥测参数质量控制技术的开发；再从仪器定标原理和观测机理出发，提取直接影响MWHTS定标精度的5个关键参数（热源黑体温度、仪器温度、热源黑体观测计数值、冷空计数值和扫描周期），利用MWHTS实际观测亮温和快速辐射传输模式RTTOV正演模拟结果（O-B）对关键参数敏感性进行分析。结果表明，扫描周期质控对O-B结果影响最大，仪器温度质控的影响最小。基于敏感性分析结果得到五个关键参数对仪器定标质量的评分准则，用百分制对FY-3C MWHTS逐通道逐扫描线逐像元观测亮温进行评分，构建了MWHTS质量评分体系来刻画仪器观测数据的定标质量以保证数据的定量应用。该质量控制模型已经用于FY-3C MWHTS业务数据处理中，逐条扫描线逐通道逐像元的评分结果也写入到仪器L1级数据中对全球实时业务发布。
Abstract
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.
关键词
风云三号C星MWHTS质量控制观测亮温评分遥测参数
Keywords
Fengyun-3CMicroWave Humidity and Temperature Sounder (MWHTS)quality controlobserved brightness temperature scoretelemetry parameters
references
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 [DOI: 10.1175/WAF-D-15-0025.1http://dx.doi.org/10.1175/WAF-D-15-0025.1]
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 [DOI: 10.1002/2016MS000826http://dx.doi.org/10.1002/2016MS000826]
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 [DOI: 10.1175/2009BAMS2798.1http://dx.doi.org/10.1175/2009BAMS2798.1]
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 [DOI: 10.1109/TGRS.2012.2214391http://dx.doi.org/10.1109/TGRS.2012.2214391]
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
谷松岩, 王振占, 李靖, 张升伟. 2010. 风云三号A星微波湿度计主探测通道辐射特性. 应用气象学报, 21(3): 335-342 [DOI: 10.3969/j.issn.1001-7313.2010.03.009http://dx.doi.org/10.3969/j.issn.1001-7313.2010.03.009]
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
郭杨, 卢乃锰, 漆成莉, 谷松岩, 许健民. 2015. 风云三号C星微波湿温探测仪的定标和验证. 地球物理学报, 58(1): 20-31 [DOI: 10.6038/cjg20150103http://dx.doi.org/10.6038/cjg20150103]
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
贺秋瑞, 王振占, 何杰颖. 2017. FY-3C/MWHTS资料反演陆地晴空大气温湿廓线. 遥感学报, 21(1): 27-39 [DOI: 10.11834/jrs.20176006http://dx.doi.org/10.11834/jrs.20176006]
JPL. 2000. Airs project: algorithm theoretical basis document part 3: microwave instruments. JPL D-17005, version 2.1, Pasadena, California, USA, 1-59
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[https://www.ecmwf.int/sites/default/files/elibrary/2008/10435-evaluation-impact-space-component-global-observing-system-through-observing-system-experiments.pdfhttps://www.ecmwf.int/sites/default/files/elibrary/2008/10435-evaluation-impact-space-component-global-observing-system-through-observing-system-experiments.pdf]
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 [DOI: 10.1175/2009WAF2222329.1http://dx.doi.org/10.1175/2009WAF2222329.1]
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[DOI: 10.1109/TGRS.2018.2798292http://dx.doi.org/10.1109/TGRS.2018.2798292]
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
卢乃锰, 谷松岩. 2016. 气象卫星发展回顾与展望. 遥感学报, 20(5): 832-841 [DOI: 10.11834/jrs320166194http://dx.doi.org/10.11834/jrs320166194]
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
陆其峰. 2011. 风云三号A星大气探测资料数据在欧洲中期天气预报中心的初步评价与同化研究. 中国科学: 地球科学, 41(7): 890-894 [DOI: 10.1360/zd-2011-41-7-890http://dx.doi.org/10.1360/zd-2011-41-7-890]
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 [DOI: 10.1002/qj.680http://dx.doi.org/10.1002/qj.680]
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[https://doi.org/10.1029/2018JD028657https://doi.org/10.1029/2018JD028657]
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
孟翔晨, 历华, 杜永明, 曹彪, 柳钦火, 李彬. 2018. Landsat 8地表温度反演及验证——以黑河流域为例. 遥感学报, 22(5): 857-871 [DOI: 10.11834/jrs.20187411http://dx.doi.org/10.11834/jrs.20187411]
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 [DOI: 10.5194/gmd-11-2717-2018http://dx.doi.org/10.5194/gmd-11-2717-2018]
Xue J S. 2009. Scientific issues and perspective of assimilation of meteorological satellite data. Acta Meteorologica Sinica, 67(6): 903-911
薛纪善. 2009. 气象卫星资料同化的科学问题与前景. 气象学报, 67(6): 903-911 [DOI: 10.3321/j.issn:0577-6619.2009.06.001http://dx.doi.org/10.3321/j.issn:0577-6619.2009.06.001]
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
杨军, 董超华, 卢乃锰, 杨忠东, 施进明, 张鹏, 刘玉洁, 蔡斌. 2009. 中国新一代极轨气象卫星——风云三号. 气象学报, 67(4): 501-509 [DOI: 10.11676/qxxb2009.050http://dx.doi.org/10.11676/qxxb2009.050]
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
杨以坤, 历华, 孙林, 杜永明, 曹彪, 柳钦火, 朱金山. 2019. 高分五号全谱段光谱成像仪地表温度与发射率反演. 遥感学报, 23(6): 1132-1146 [DOI: 10.11834/jrs.20198053http://dx.doi.org/10.11834/jrs.20198053]
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
张淼, 陆其峰, 谷松岩, 胡秀清, 武胜利. 2019. 风云三号C星微波成像仪升降轨偏差问题分析及订正. 遥感学报, 23(5): 841-849 [DOI: 10.11834/jrs.20198235http://dx.doi.org/10.11834/jrs.20198235]
文章被引用时，请邮件提醒。
提交
相关作者
暂无数据
相关机构
中国气象局中国遥感卫星辐射测量和定标重点开放实验室 国家卫星气象中心
解放军理工大学
国家卫星气象中心
中国遥感卫星辐射测量和定标重点开放实验室
中国气象局数值预报中心
选择翻译语言
- 地址：北京市海淀区北四环西路19号 《遥感学报》编辑部 邮编：100190
- 联系电话：010-58887052 Email：nrsb@aircas.ac.cn
- 技术支持由北京北大方正电子有限公司提供 京ICP备20021838号-9
京公网安备11010802024621 - 本系统建议在Chrome、 IE9+ 以上版本浏览器阅读本站内容，360浏览器请切换至极速模式
- Cookies帮助我们提供服务并提供个性化体验。使用本网站，即表示您同意我们使用Cookies
0
回到顶部