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Accuracy and Stability of Radio Occultation Dry Temperature Profiles from Fengyun Satellites
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摘要: 风云三号气象卫星C星/D星/E星的掩星接收机接收GPS和北斗导航卫星信号，形成掩星事件，进而反演得到大气温度廓线。利用2016—2022年FY-3C/3D/3E GPS和北斗掩星干大气温度廓线，通过与ERA5再分析资料对比，分析掩星干大气温度的精准度特征。结果表明：掩星干大气温度廓线在200 hPa至20 hPa间精度最高，标准偏差约为1 K，且GPS与北斗掩星的误差特征相近。在稳定度方面，FY-3C GPS掩星干大气温度平均偏差线性变化趋势为-0.0055 K·a-1，与国外同类掩星资料稳定性相当。因2021年初掩星天线多径效应订正，FY-3D GPS掩星干大气温度与ERA5再分析资料的平均偏差出现明显跳变，平均偏差值从-0.154 K降为-0.007 K, 负偏差显著减小。总体上，FY-3C GPS掩星干大气温度廓线长序列稳定度较好，北斗掩星干大气温度廓线精度能够达到或优于GPS，风云极轨卫星序列的GPS和北斗掩星在长序列稳定性上具有良好的应用前景。Abstract: The earth's climate has undergone significant changes due to the combined effects of natural changes and human activities. To understand the impact of climate change, the most fundamental work is to establish high-quality data required for climate purposes. Currently, the long series observations mainly come from satellites and sites. However, most satellite sensors are designed for short-term and imminent weather monitoring and numerical prediction, rather than long-term climate monitoring. To meet future research needs, more efforts are needed in data reprocessing such as satellite calibration and multi-source data fusion.Global Navigation Satellite System Radio Occultation (GNSS-RO) is a system that carries a receiver on low orbit satellite to receive radio signals transmitted by the global navigation satellite system. GNSS-RO detects the earth's atmosphere in a borderline manner during relative motion. When propagating in non-vacuum atmosphere, radio signals may appear bent or delay due to different atmospheric physical characteristics. After complex processing, physical parameters such as atmospheric temperature, humidity, and density can be inverted. Each receiver observes approximately 500 occultation events per day, which are almost randomly distributed on the earth and not affected by clouds and underlying surfaces. These data provide a source of observational information with high vertical resolution and long-term stability, extending from near surface to upper stratosphere. The original occultation observation is based on time and position measurements, needing no calibration, which has advantages in climate change study.The occultation receiver on FY-3C/3D/3E meteorological satellite can receive GPS and Beidou Navigation Satellite System (BDS) signals, and the records are almost nine years long. To analyze the accuracy and stability of temperature records from multiple radio occultation, the mean and standard deviation of the dry temperature of FY-3C/3D/3E GPS and BDS radio occultation are studied using ERA5 data. It demonstrats that the accuracy of the dry temperature profile is the highest between 200 hPa and 20 hPa and the error characteristics of GPS and BDS radio occultation are similar. The stability of the average temperature deviation of FY-3C GPS for 5-year time series is very good, which is -0.0055 K·a-1. After several algorithm improvements, the standard deviation of FY-3C GPS dry temperature decreased to about 1 K at the beginning of 2018. BDS radio occultation products are operationally provided since April 2021, and there is a good consistency between FY-3C/3E and between GPS and BDS radio occultation. Due to the algorithm adjustment at the beginning of 2021, the average deviation between FY-3D radio occultation and ERA5 data shows a significant jump. In general, the stability of multiple radio occultation dry temperature records is good and promising for climate change monitoring and research. It is necessary to carry out homogeneity reprocessing.
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Key words:
- Fengyun radio occultation;
- Beidou;
- temperature;
- time series change
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图 1 FY-3C/3D/3E GPS和BDS掩星的日平均廓线数
Fig. 1 Daily profile number of FY-3C/3D/3E GPS and DBS radio occultation
图 2 2022年1月1日掩星干大气温度廓线与湿大气温度廓线对比
Fig. 2 Comparison of radio occultation dry and wet temperature profiles on 1 Jan 2022
图 3 风云卫星掩星干大气温度廓线与ERA5的平均偏差、标准偏差以及垂直样本量
Fig. 3 Deviation, standard deviation and sample number of Fengyun radio occultation dry temperature profiles to ERA5
图 4 GPS掩星干大气温度在300 hPa至30 hPa高度平均偏差的时间序列
Fig. 4 Time series of mean deviation of GPS radio occultation dry temperature from 300 hPa to 30 hPa
图 5 GPS掩星干大气温度在300 hPa至30 hPa高度平均标准偏差的时间序列
Fig. 5 Time series of mean standard deviation of GPS radio occultation dry temperature from 300 hPa to 30 hPa
图 6 BDS掩星干大气温度在300 hPa至30 hPa高度平均偏差的时间序列
Fig. 6 Time series of mean deviation of BDS radio occultation dry temperature from 300 hPa to 30 hPa
图 7 BDS掩星干大气温度在300 hPa至30 hPa高度平均标准偏差的时间序列
Fig. 7 Time series of mean standard deviation of BDS radio occultation dry temperature from 300 hPa to 30 hPa
图 8 掩星干大气温度在300 hPa至30 hPa高度平均偏差的时间序列
Fig. 8 Time series of mean deviation of radio occultation dry temperature from 300 hPa to 30 hPa
表 1 FY-3E GPS与BDS掩星干大气温度廓线在不同高度的平均偏差和标准偏差
Table 1 Mean deviation and mean standard deviation of FY-3E GPS and BDS radio occultation dry temperature profile at different altitudes
高度 GPS BDS 平均偏差/K 标准偏差/K 平均偏差/K 标准偏差/K 500 hPa至225 hPa -1.22 2.13 -0.81 1.45 200 hPa至100 hPa -0.17 1.07 -0.05 0.83 70 hPa至1 hPa 0.01 4.26 0.41 3.96 500 hPa至1 hPa -0.46 2.49 -0.15 2.08 
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表 2 掩星干大气温度在300 hPa至30 hPa高度的平均偏差和标准偏差
Table 2 Mean bias and deviation of radio occultation dry temperature from 300 hPa to 30 hPa
卫星产品 平均偏差/K 标准偏差/K FY-3C GPS -0.10 1.09 FY-3D GPS -0.15 1.08 FY-3D BDS -0.01 1.13 FY-3E GPS -0.22 1.34 FY-3E BDS -0.15 0.99
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[1] 林爱兰, 谷德军, 彭冬冬, 等.近60年我国东部区域性持续高温过程变化特征.应用气象学报, 2021, 32(3):302-314. doi: 10.11898/1001-7313.20210304Lin A L, Gu D J, Peng D D, et al. Climatic characteristics of regional persistent heat event in in the eastern China during recent 60 years. J Appl Meteor Sci, 2021, 32(3): 302-314. doi: 10.11898/1001-7313.20210304 [2] 张人禾. 气候观测系统及其相关的关键问题. 应用气象学报, 2006, 17(6): 705-710. http://qikan.camscma.cn/article/id/200606119Zhang R H. Climate observing system and related crucial issues. J Appl Meteor Sci, 2006, 17(6): 705-710. http://qikan.camscma.cn/article/id/200606119 [3] 赵平, 南素兰. 气候和气候变化领域的研究进展. 应用气象学报, 2006, 17(6): 725-735. http://qikan.camscma.cn/article/id/200606121Zhao P, Nan S L. Some advances in climate and climate change research. J Appl Meteor Sci, 2006, 17(6): 725-735. http://qikan.camscma.cn/article/id/200606121 [4] 任素玲, 牛宁, 覃丹宇, 等. 2021年2月北美极端低温暴雪的卫星遥感监测. 应用气象学报, 2022, 33(6): 696-710. doi: 10.11898/1001-7313.20220605Ren 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 [5] Hurrell J W, Trenberth K E. Spurious trends in satellite MSU temperatures from merging different satelliterecords. Nature, 1997, 386: 164-167. doi: 10.1038/386164a0 [6] 谷松岩, 王振占, 李靖, 等. 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, 2010, 21(3): 335-342. doi: 10.3969/j.issn.1001-7313.2010.03.009Gu S Y, Wang Z Z, Li J, et al. The radiometric characteristics of sounding channels for FY-3A/MWHS. J Appl Meteor Sci, 2010, 21(3): 335-342. doi: 10.3969/j.issn.1001-7313.2010.03.009 [7] Nash J, Forrester G F. Long-term monitoring of stratospheric temperature trends using radiance measurements obtained by the TIROS-N series of NOAA spacecraft. Adv Space Res, 1986, 6(10): 37-44. doi: 10.1016/0273-1177(86)90455-2 [8] Ohring G, Wielicki B, Spencer R, et al. Satellite instrument calibration for measuring global climate change: Report of a workshop. Bull Amer Meteor Soc, 2005, 86(9): 1303-1313. doi: 10.1175/BAMS-86-9-1303 [9] Christy J R, Spencer R W, Lobl E S. Analysis of the merging procedure for the MSU daily temperature time series. J Climate, 1998, 11: 2016-2041. doi: 10.1175/1520-0442(1998)011<2016:AOTMPF>2.0.CO;2 [10] Mears C A, Wentz F J. Construction of the remote sensing systems V3.2 atmospheric temperature records from the MSU and AMSU microwave sounders. J Atmos Oceanic Technol, 2008, 26: 1040-1056. [11] Po-Chedley S, Thorsen T J, Fu Q. Removing diurnal cycle contamination in satellite-derived tropospheric temperatures: Understanding tropical tropospheric trend discrepancies. J Climate, 2015, 28: 2274-2290. doi: 10.1175/JCLI-D-13-00767.1 [12] Spencer R W, Christy J R. Precise monintoring of global temperature trends from satellite. Science, 1990, 247: 1558-1562. doi: 10.1126/science.247.4950.1558 [13] Fu Q, Johanson C M. Stratospheric influences on MSU-derived tropospheric temperature trends: A direct error analysis. J Climate, 2004, 17: 4636-4640. doi: 10.1175/JCLI-3267.1 [14] 邹成治, 高梅. 交叉定标产生的NOAA卫星长期大气温度观测资料. 应用气象学报, 2008, 19(5): 582-587. doi: 10.3969/j.issn.1001-7313.2008.05.009Zou C Z, Gao M. A long-term atmospheric temperature dataset derived from NOAA microwave sounding unit with cross-calibration. J Appl Meteor Sci, 2008, 19(5): 582-587. doi: 10.3969/j.issn.1001-7313.2008.05.009 [15] Thorne P W, Lanzante J R, Peterson T C, et al. Tropospheric temperature trends: History of an ongoing controversy. WIREs Clim Change, 2011, 2(1): 66-88. doi: 10.1002/wcc.80 [16] Melbourne W G, Davis E S, Duncan C B, et al. The Application of Spaceborne GPS to Atmospheric Limb Sounding and Global Change Monitoring. Pasadena, Calif: Jet Propulsion Laboratory, 1994. [17] Ware R, Rocken C, Solheim F, et al. GPS sounding of the atmosphere from lower earth orbit: Preliminary results. Bull Amer Meteor Soc, 1996, 77: 19-40. doi: 10.1175/1520-0477(1996)077<0019:GSOTAF>2.0.CO;2 [18] Sokolovskiy S V. Tracking tropospheric radio occultation signals from low earth orbit. Radio Sci, 2001, 36(3): 483-498. doi: 10.1029/1999RS002305 [19] Steiner A K, Ladstädter F, Randel W J, et al. Observed temperature changes in the troposphere and stratosphere from 1979 to 2018. J Climate, 2020, 33: 8165-8194. doi: 10.1175/JCLI-D-19-0998.1 [20] Gleisner H, Ringer M A, Healy S B. Monitoring global climate change using GNSS radio occultation. npj Climate Atmos Sci, 2022, 5: 6. doi: 10.1038/s41612-022-00229-7 [21] Kursinski E, Hajj G A, Bertiger W I, et al. Initial results of radio occultation observations of earth's atmosphere using the Global Positioning System. Science, 1996, 271: 1107-1110. doi: 10.1126/science.271.5252.1107 [22] Rocken C, Anthes R, Exner M, et al. Analysis and validation of GPS/MET data in the neutral atmosphere. J Geophys Res, 1997, 102: 29849-29866. doi: 10.1029/97JD02400 [23] Schreiner W S, Weiss J P, Anthes R A, et al. COSMIC-2 radio occultation constellation: First results. Geophys Res Lett, 2020, 47: e2019GL086841. [24] Anthes R, Sjoberg J, Feng, X L, et al. Comparison of COSMIC and COSMIC-2 radio occultation refractivity and bending angle uncertainties in August 2006 and 2021. Atmosphere, 2022, 13(5): 790. doi: 10.3390/atmos13050790 [25] Kursinski E R, Hajj G A, Schofield J T, et al. Observing earth's atmosphere with radio occultation measurements using the Global Positioning System. J Geophys Res, 1997, 102(D19): 23429-23465. doi: 10.1029/97JD01569 [26] SteinerA K, Ladstädter F, Ao C O, et al. Consistency and structural uncertainity of multi-mission GPS radio occultation records. Atmos Meas Tech, 2020, 13(5): 2547-2575. doi: 10.5194/amt-13-2547-2020 [27] Ho S P, Hunt D C, Steiner A K, et al. Reproducibility of GPS radio occultation data for climate monitoring: Profile-to-profile intercomparison of CHAMP climate records 2002 to 2008 from six data centers. J Geophys Res, 2012, 117: D18111. [28] Ladstädter F, Steiner A K, Schwärz M, et al. Climate intercomparison of GPS radio occultation, RS90/92 radiosondes and GRUAN from 2002 to 2013. Atmos Meas Tech, 2015, 8: 1819-1834. doi: 10.5194/amt-8-1819-2015 [29] Gleisner H, Lauritsen K B, Nielsen J K, et al. Evaluation of the 15-year ROM SAF monthly mean GPS radio occultation climate data record. Atmos Meas Tech, 2020, 13: 3081-3098. doi: 10.5194/amt-13-3081-2020 [30] 廖蜜, 张鹏, 毕研盟等. 风云三号气象卫星掩星大气产品精度的初步检验. 气象学报, 2015, 73(6): 1131-1140. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB201506011.htmLiao M, Zhang P, Bi Y M, et al. A preliminary estimation of the radio occultation products accuracy from the Fengyun-3C meteorological satellite. Acta Meteor Sinica, 2015, 73(6): 1131-1140. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB201506011.htm [31] Liao M, Healy S B, Zhang P. Processing and quality control of FY-3C GNOS data used in numerical weather prediction applications. Atmos Meas Tech, 2019, 12(5): 2679-2692. doi: 10.5194/amt-12-2679-2019 [32] Liao M, Zhang P, Yang G L, et al. Preliminary validation of the refractivity from the new radio occultation sounder GNOS/FY-3C. Atmos Meas Tech, 2016, 9: 781-792. doi: 10.5194/amt-9-781-2016 [33] 王树志, 朱光武, 白伟华, 等. 风云三号C星全球导航卫星掩星探测仪首次实现北斗掩星探测. 物理学报, 2015, 64(8): 089301. https://www.cnki.com.cn/Article/CJFDTOTAL-WLXB201508054.htmWang S Z, Zhu G W, Bai W H, et al. For the first time Fengyun3 C satellite-global navigation satellite system occultation sounder achieved spaceborne Bei Dou system radio occultation. Acta Physica Sinica, 2015, 64(8): 089301. https://www.cnki.com.cn/Article/CJFDTOTAL-WLXB201508054.htm [34] Healy S, Eyre J. Retrieving temperature water vapour and surface pressure information from a refractive-index profiles derived by radio occultation: A simulation study. Quart J Roy Meteor Soc, 2000, 126: 1661-1683. [35] Poli P, Joiner J, Kursinski E R. 1DVAR analysis of temperature and humidity using GPS radio occultation refractivity data. J Geophys Res, 2002, 107(D20): 4448. [36] Phinney R A, Anderson D L. On the radio occultation method for studing planetary atmospheres. J Geophys Res, 1968, 73(5): 1819-1827. [37] Smith E K, Weintraub S. The constants in the equation for atmosphere index at radio frequencies. Proc IRE, 1953, 41(8): 1035-1037. [38] Danzer J, Foelsche U, Scherllin-Pirscher B, et al. Influence of changes in humidity on dry temperature in GPS RO climatologies. Atmos Meas Tech, 2014, 7: 2883-2896. [39] Schwärz M, Scherllin-Pirscher B, Kirchengast G, et al. Multi-mission Validation by Satellite Radio Occultation. Final Report for ESA/ESRIN No. 01/2013, WEGC, University of Graz, Austria, 2013. [40] 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 [41] 刘健, 王锡津. 主要卫星云气候数据集评述. 应用气象学报, 2017, 28(6): 654-665. doi: 10.11898/1001-7313.20170602Liu J, Wang X J. Assessment on main kinds of satellite cloud climate datasets. J Appl Meteor Sci, 2017, 28(6): 654-665. doi: 10.11898/1001-7313.20170602 [42] 郭启云, 杨荣康, 程凯琪, 等. 基于探空观测的多源掩星折射率质量控制及对比. 应用气象学报, 2020, 31(1): 13-26. doi: 10.11898/1001-7313.20200102Guo Q Y, Yang R K, Cheng K Q, et al. Refractive index quality control and comparative analysis of multi-source occultation based on sounding observation. J Appl Meteor Sci, 2020, 31(1): 13-26. doi: 10.11898/1001-7313.20200102 -
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