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WU Yao, CHEN Junyu. Error Analysis of Thermosphere Atmospheric Density for HASDM Method Based on SWARM-C Satellite Data (in Chinese). Chinese Journal of Space Science, 2026, 46(1): 1-10 doi: 10.11728/cjss2026.01.2025-0012
Citation: WU Yao, CHEN Junyu. Error Analysis of Thermosphere Atmospheric Density for HASDM Method Based on SWARM-C Satellite Data (in Chinese). Chinese Journal of Space Science, 2026, 46(1): 1-10 doi: 10.11728/cjss2026.01.2025-0012

Error Analysis of Thermosphere Atmospheric Density for HASDM Method Based on SWARM-C Satellite Data

doi: 10.11728/cjss2026.01.2025-0012 cstr: 32142.14.cjss.2025-0012
  • Received Date: 2025-01-09
  • Rev Recd Date: 2025-05-29
  • Available Online: 2025-05-30
  • Accurate thermosphere density modeling is a prerequisite for reliable orbit prediction of satellites and space debris, particularly under the growing demands of modern space traffic management in low Earth orbit. This study systematically evaluates the performance of the High Accuracy Satellite Drag Model (HASDM) using thermosphere density data retrieved from SWARM-C satellite accelerometer measurements spanning the period 2014-2019. The analysis investigates model bias and variability in response to different solar and geomagnetic activity levels, as well as latitude and local time dependencies. Results indicate that solar activity exerts a marked influence on model performance: during moderate to high solar activity years, HASDM exhibits a mean bias of approximately 12.5% with a standard deviation near 0.2, whereas under low solar activity conditions, the bias increases to 18.7% and the standard deviation rises to 0.4. During geomagnetic disturbances, the model maintains an average bias about 17%, though with an elevated standard deviation, particularly during the main phase of storms. In terms of spatial distribution, polar regions demonstrate the lowest bias (5%~10%), with relatively larger variability in the southern hemisphere; conversely, equatorial regions present the highest biases, ranging between 20% and 30%. The diurnal pattern further reveals peak modeling errors during 03:00-06:00 LST and 18:00—24:00 LST, highlighting limitations in representing nighttime density variations. Additionally, during geomagnetic storms, HASDM tends to overestimate density in the initial phase, displays significant fluctuations in the main phase, and gradually stabilizes during recovery. These findings highlight systematic deficiencies in existing empirical parameterizations and suggest the necessity of incorporating enhanced solar-geophysical proxies and regionally adaptive corrections.

     

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  • [1]
    BOWMAN B, TOBISKA W K, MARCOS F, et al. A new empirical thermospheric density model JB2008 using new solar and geomagnetic indices[C]//AIAA/AAS Astrodynamics Specialist Conference and Exhibit. Honolulu: AIAA, 2008
    [2]
    BRUINSMA S, BONIFACE C. The operational and research DTM-2020 thermosphere models[J]. Journal of Space Weather and Space Climate, 2021, 11: 47 doi: 10.1051/swsc/2021032
    [3]
    PICONE J M, HEDIN A E, DROB D P, et al. NRLMSISE-00 empirical model of the atmosphere: statistical comparisons and scientific issues[J]. Journal of Geophysical Research: Space Physics, 2002, 107(A12): SIA 15-1-SIA 15-16
    [4]
    DENG Y, FULLER-ROWELL T J, RIDLEY A J, et al. Theoretical study: influence of different energy sources on the cusp neutral density enhancement[J]. Journal of Geophysical Research: Space Physics, 2013, 118(5): 2340-2349 doi: 10.1002/jgra.50197
    [5]
    FEDRIZZI M, FULLER-ROWELL T J, CODRESCU M V. Global joule heating index derived from thermospheric density physics-based modeling and observations[J]. Space Weather, 2012, 10(3): S03001 doi: 10.1029/2011sw000724
    [6]
    BRUINSMA S L, FORBES J M. Anomalous behavior of the thermosphere during solar minimum observed by CHAMP and GRACE[J]. Journal of Geophysical Research: Space Physics, 2010, 115(A11): A11323 doi: 10.1029/2010ja015605
    [7]
    SOLOMON S C, WOODS T N, DIDKOVSKY L V, et al. Anomalously low solar extreme-uLSTraviolet irradiance and thermospheric density during solar minimum[J]. Geophysical Research Letters, 2010, 37(16): L16103 doi: 10.1029/2010gl044468
    [8]
    STORZ M F, BOWMAN B R, BRANSON M J I, et al. High accuracy satellite drag model (HASDM)[J]. Advances in Space Research, 2005, 36(12): 2497-2505 doi: 10.1016/j.asr.2004.02.020
    [9]
    TOBISKA W K, BOWMAN B R, BOUWER S D, et al. The SET HASDM density database[J]. Space Weather, 2021, 19(4): e2020SW002682 doi: 10.1029/2020SW002682
    [10]
    LICATA R J, MEHTA P M, TOBISKA W K, et al. Qualitative and quantitative assessment of the SET HASDM database[J]. Space Weather, 2021, 19(8): e2021SW002798 doi: 10.1029/2021SW002798
    [11]
    BRUINSMA S L, DOORNBOS E, BOWMAN B R. Validation of GOCE densities and evaluation of thermosphere models[J]. Advances in Space Research, 2014, 54(4): 576-585 doi: 10.1016/j.asr.2014.04.008
    [12]
    BRUINSMA S, SIEMES C, EMMERT J T, et al. Description and comparison of 21st century thermosphere data[J]. Advances in Space Research, 2023, 72(12): 5476-5489 doi: 10.1016/j.asr.2022.09.038
    [13]
    MIAO Juan, LIU Siqing, LI Zhitao, et al. Correlation of thermosphere density variation with different solar and geomagnetic indices[J]. Manned Spaceflight, 2012, 18(5): 24-30 (苗娟, 刘四清, 李志涛, 等. 热层大气密度变化特征与太阳辐射和地磁指数的相关性分析[J]. 载人航天, 2012, 18(5): 24-30 doi: 10.3969/j.issn.1674-5825.2012.05.008

    MIAO Juan, LIU Siqing, LI Zhitao, et al. Correlation of thermosphere density variation with different solar and geomagnetic indices[J]. Manned Spaceflight, 2012, 18(5): 24-30 doi: 10.3969/j.issn.1674-5825.2012.05.008
    [14]
    WENG Libin, FANG Hanxian, JI Chunhua, et al. Comparison between the CHAMP/STAR derived thermospheric density and the NRLMSISE-00 model[J]. Chinese Journal of Space Science, 2012, 32(5): 713-719 (翁利斌, 方涵先, 季春华, 等. 基于卫星加速度数据反演的热层大气密度与NRLMSISE-00模式结果的比较研究[J]. 空间科学学报, 2012, 32(5): 713-719

    WENG Libin, FANG Hanxian, JI Chunhua, et al. Comparison between the CHAMP/STAR derived thermospheric density and the NRLMSISE-00 model[J]. Chinese Journal of Space Science, 2012, 32(5): 713-719
    [15]
    CHEN Xuxing, HU Xiong, XIAO Cunying, et al. Comparison of the thermospheric densities between GRACE/CHAMP satellites data and NRLMSISE-00 model[J]. Chinese Journal of Space Science, 2013, 33(5): 509-517 (陈旭杏, 胡雄, 肖存英, 等. NRLMSISE-00大气模型与GRACE和CHAMP卫星大气密度数据的对比分析[J]. 空间科学学报, 2013, 33(5): 509-517 doi: 10.11728/cjss2013.05.509

    CHEN Xuxing, HU Xiong, XIAO Cunying, et al. Comparison of the thermospheric densities between GRACE/CHAMP satellites data and NRLMSISE-00 model[J]. Chinese Journal of Space Science, 2013, 33(5): 509-517 doi: 10.11728/cjss2013.05.509
    [16]
    LIU Wei, WANG Ronglan, LIU Siqing, et al. Error analysis of typical atmospheric density model[J]Chinese Journal of Space Science, 2017, 37(5): 538-546 (刘卫, 王荣兰, 刘四清, 等. 典型热层密度模式误差分析[J]. 空间科学学报, 2017, 37(5): 538-546

    LIU Wei, WANG Ronglan, LIU Siqing, et al. Error analysis of typical atmospheric density model[J]Chinese Journal of Space Science, 2017, 37(5): 538-546
    [17]
    NAZARENKO A I, CEFOLA P J, YURASOV V. Estimating atmosphere density variations to improve LEO orbit prediction accuracy[J]. Advances in the Astronautical Sciences, 1998, 99(2): 1235-1256
    [18]
    MARCOS F A, RENDRA M J, GRIFFIN J M, et al. Precision low earth orbit determination using atmospheric density calibration[J]. The Journal of the Astronautical Sciences, 1998, 46(4): 395-409 doi: 10.1007/BF03546389
    [19]
    TOBISKA W K, WOODS T, EPARVIER F, et al. The SOLAR2000 empirical solar irradiance model and forecast tool[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2000, 62(14): 1233-1250 doi: 10.1016/S1364-6826(00)00070-5
    [20]
    TOBISKA W K, KNIPP D, BURKE W J, et al. The anemomilos prediction methodology for Dst[J]. Space Weather, 2013, 11(9): 490-508 doi: 10.1002/swe.20094
    [21]
    OLSEN N, FRIIS-CHRISTENSEN E, FLOBERGHAGEN R, et al. The swarm satellite constellation application and research facility (SCARF) and swarm data products[J]. Earth, Planets and Space, 2013, 65(11): 1189-1200 doi: 10.5047/eps.2013.07.001
    [22]
    YIN L R, WANG L, TIAN J W, et al. Atmospheric density inversion based on Swarm-C satellite accelerometer[J]. Applied Sciences, 2023, 13(6): 3610-3622 doi: 10.3390/app13063610
    [23]
    IORFIDA E, DARAS I, HAAGMANS R, et al. Swarm A and C accelerometers: data validation and scientific interpretation[J]. Earth and Space Science, 2023, 10(2): e2022EA002458 doi: 10.1029/2022EA002458
    [24]
    YIN L R, WANG L, ZHENG W F, et al. Evaluation of empirical atmospheric models using Swarm-C satellite data[J]. Atmosphere, 2022, 13(2): 294-308 doi: 10.3390/atmos13020294
    [25]
    SIEMES C, BORRIES C, BRUINSMA S, et al. New thermosphere neutral mass density and crosswind datasets from CHAMP, GRACE, and GRACE-FO[J]. Journal of Space Weather and Space Climate, 2023, 13: 16 doi: 10.1051/swsc/2023014
    [26]
    WANG Hongbo. The application of satellite borne accelerometer data to the study of upper atmosphere[J]. Acta Astronomica Sinica, 2010, 51(4): 435-436
    [27]
    TOBISKA W K, BOUWER S D, BOWMAN B R. The development of new solar indices for use in thermospheric density modeling[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2008, 70(5): 803-819 doi: 10.1016/j.jastp.2007.11.001
    [28]
    HUTCHINSON J A, WRIGHT D M, MILAN S E. Geomagnetic storms over the last solar cycle: a superposed epoch analysis[J]. Journal of Geophysical Research: Space Physics, 2011, 116(A9): A09211 doi: 10.1029/2011ja016463
    [29]
    YOKOYAMA N, KAMIDE Y. Statistical nature of geomagnetic storms[J]. Journal of Geophysical Research: Space Physics, 1997, 102(A7): 14215-14222 doi: 10.1029/97JA00903
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