Citation:
Sun, M. C., Zhu, Q. L., Dong, X., and Wu, J. J. (2022). Analysis of inversion error characteristics of stellar occultation simulation data. Earth Planet. Phys., 6(1), 61–69. http://doi.org/10.26464/epp2022013
2022, 6(1): 61-69. doi: 10.26464/epp2022013
Analysis of inversion error characteristics of stellar occultation simulation data
| 1. | China Research Institute of Radiowave Propagation, Qingdao 266107, China |
| 2. | Xidian University, Xi’an 710126, China |
Atmospheric stellar occultation observation technology is an advanced space-based detection technology that can measure the vertical distribution of trace gas composition, temperature, and aerosol content in a planet’s atmosphere. In this study, an inversion algorithm of the onion-peeling method was constructed to invert the transmittance obtained from the forward mask. The method used a three-dimensional ray-tracing simulation to obtain the transmission path of the light in the Earth’s atmosphere. The relevant parameters were then combined in the high-resolution transmission molecular absorption (HITRAN) database, and line-by-line integration was performed to calculate the atmospheric transmittance. The transmittance value was then used as an input to calculate the vertical distribution of oxygen molecules when using the single-wavelength inversion of the onion-peeling method. Finally, the oxygen molecule content was compared with the value attained by the Mass Spectrometer and Incoherent Scatter Radar Extended (MSISE00) atmospheric model to determine the relative error of our model. The maximum error was found to be 0.3%, which is low enough to verify the reliability of our algorithm. Using Global-scale Observations of the Limb and Disk (GOLD) measured data to invert the oxygen number density, we calculated its relative deviation from the published result to further verify the algorithm. The inversion result was affected by factors such as prior data, the absorption spectral line type, the ellipticity of the Earth, and the accuracy of the orbit. Analysis of these error-influencing factors showed that the seasons and the Earth’s ellipticity affected the accuracy of the model only 0.001% and could therefore be ignored. However, latitude and solar activity had a greater impact on accuracy, on the order of 0.1%. The absorption line type affected the accuracy of the model by as much as 1%. All three of these factors therefore need to be considered during the inversion process.
|
Bertaux, J. L., Hauchecorne, A., Dalaudier, F., Cot, C., Kyrölä, E., Fussen, D., Tamminen, J., Leppelmeier, G. W., Sofieva, V., … Fraisse, R. (2004). First results on GOMOS/ENVISAT. Adv. Space Res., 33(7), 1029–1035. https://doi.org/10.1016/j.asr.2003.09.037 |
|
Bertaux, J. L., Vandaele, A. C., Korablev, O., Villard, E., Fedorova, A., Fussen, D., Quemerais, E., Belyaev, D., Mahieux, A., … the SPICAV/SOIR team. (2007). A warm layer in Venus' cryosphere and high-altitude measurements of HF, HCl, H2O and HDO. Nature, 450(7170), 646–649. https://doi.org/10.1038/nature05974 |
|
Bertaux, J. L., Kyrölä, E., Fussen, D., Hauchecorne, A., Dalaudier, F., Sofieva, V., Tamminen, J., Vanhellemont, F., d'Andon, O. F., … Fraisse, R. (2010). Global ozone monitoring by occultation of stars: an overview of GOMOS measurements on ENVISAT. Atmos. Chem. Phys., 10(24), 12091–12148. https://doi.org/10.5194/acp-10-12091-2010 |
|
DeMajistre, R., and Yee, J. H. (2002). Atmospheric remote sensing using a combined extinctive and refractive stellar occultation technique 2. Inversion method for extinction measurements. J. Geophys. Res. :Atmos., 107(D15), ACH 6-1-ACH 6-18. https://doi.org/10.1029/2001JD000795 |
|
Eastes, R. (2009). NASA mission to explore forcing of Earth's space environment. Eos Trans. AGU, 90(18), 155. https://doi.org/10.1029/2009EO180002 |
|
Eastes, R. W., McClintock, W. E., Burns, A. G., Anderson, D. N., Andersson, L., Codrescu, M., Correira, J. T., Daniell, R. E., England, S. L., … Oberheide, J. (2017). The global-scale observations of the limb and disk (GOLD) mission. Space Sci. Rev., 212(1), 383–408. https://doi.org/10.1007/s11214-017-0392-2 |
|
Festou, M. C., Atreya, S. K., Donahue, T. M., Sandel, B. R., Shemansky, D. E., and Broadfoot, A. L. (1981). Composition and thermal profiles of the Jovian upper atmosphere determined by the Voyager Ultraviolet Stellar Occultation Experiment. J. Geophys. Res. :Space Phys., 86(A7), 5715–5725. https://doi.org/10.1029/JA086iA07p05715 |
|
Forget, F., Montmessin, F., Bertaux, J. L., González-Galindo, F., Lebonnois, S., Quémerais, E., Reberac, A., Dimarellis, E., and López-Valverde, M. A. (2009). Density and temperatures of the upper Martian atmosphere measured by stellar occultations with Mars Express SPICAM. J. Geophys. Res. :Planets, 114(E1), E01004. https://doi.org/10.1029/2008JE003086 |
|
Gong, X. Y., Hu, X., Wu, X. C., and Zhang, X. X. (2007). Preliminary analysis of error characteristics in atmospheric inversion of GPS radio occultation. Chin. J. Geophys., 50(4), 1017–1029. https://doi.org/10.3321/j.issn:0001-5733.2007.04.009 |
|
Greer, K. R., England, S. L., Becker, E., Rusch, D., and Eastes, R. (2018). Modeled gravity wave-like perturbations in the brightness of far ultraviolet emissions for the GOLD mission. J. Geophys. Res. :Space Phys., 123(7), 5821–5830. https://doi.org/10.1029/2018JA025501 |
|
Hays, R. G., and Roble, P. B. (1968). Stellar spectra and atmospheric composition. J. Atomos. Sci., 25, 1141–1153. |
|
Herman, J. R., and Mentall, J. E. (1982). O2 absorption cross sections (187–225 nm) from stratospheric solar flux measurements. J. Geophys. Res. :Oceans, 87(C11), 8967–8975. https://doi.org/10.1029/JC087iC11p08967 |
|
Kyrölä, E., Tamminen, J., Leppelmeier, G. W., Sofieva, V., Hassinen, S., Bertaux, J. L., Hauchecorne, A., Dalaudier, F., Cot, C., … Vanhellemont, F. (2004). GOMOS on Envisat: an overview. Adv. Space Res., 33(7), 1020–1028. https://doi.org/10.1016/S0273-1177(03)00590-8 |
|
Kyrölä, E., Tamminen, J., Sofieva, V., Bertaux, J. L., Hauchecorne, A., Dalaudier, F., Fussen, D., Vanhellemont, F., D'Andon, O. F., … Fraisse, R. (2010). Retrieval of atmospheric parameters from GOMOS data. Atmos. Chem. Phys., 10(23), 11881–11903. https://doi.org/10.5194/acp-10-11881-2010 |
|
Lumpe, J. D., Floyd, L. E., Herring, L. C., Gibson, S. T., and Lewis, B. R. (2007). Measurements of thermospheric molecular oxygen from the Solar Ultraviolet Spectral Irradiance Monitor. J. Geophys. Res. :Atmos., 112(D16), D16308. https://doi.org/10.1029/2006JD008076 |
|
Lumpe, J. D. , Correira, J. , Evans, J. S. , Eastes, R. , McClintock, B. , and Beland, S. (2016). Measurements of thermospheric O2 density from GOLD. In AGU Fall Meeting. American Geophysical Union.222 |
|
Ning, L. X., Wang, H. M., Cheng, P., Chu, Y. N., and Cao, D. Z. (2001). Research development on kinetic behavior of the Herzberg states of O2 in the upper atmosphere. Chin. J. Quant. Electr., 18(1), 9–15. https://doi.org/10.3969/j.issn.1007-5461.2001.01.002 |
|
Qi, R. B., He, S. K., Li, X. T., and Wang, X. Z. (2015). Simulation of TDLAS direct absorption based on HITRAN database. Spectrosc. Spect. Anal., 35(1), 172–177. https://doi.org/10.3964/j.issn.1000-0593(2015)01-0172-06 |
|
Qian, L. Y., Solomon, S. C., and Kane, T. J. (2009). Seasonal variation of thermospheric density and composition. J. Geophys. Res. :Space Phys., 114(A1), A01312. https://doi.org/10.1029/2008JA013643 |
|
Ratier, G., Levrini, G., Popescu, A., Paulsen, T., Readings, C., and Langen, J. (1999). GOMOS: Envisat’s contribution to trace gas measurements. Air Space Eur., 1(5-6), 33–39. https://doi.org/10.1016/S1290-0958(00)88868-1 |
|
Roble, R. G., and Hays, P. B. (1972). A technique for recovering the vertical number density profile of atmospheric gases from planetary occultation data. Planet. Space Sci., 20(10), 1727–1744. https://doi.org/10.1016/0032-0633(72)90194-8 |
|
Siegmund, O. H. W., McPhate, J., Curtis, T., Jelinsky, S., Vallerga, J. V., Hull, J., and Tedesco, J. (2016). Ultraviolet imaging detectors for the GOLD mission. Proc. SPIE, 9905, 99050D. https://doi.org/10.1117/12.2232219 |
|
Sun, M. C., Wu, X. C., and Hu, X. (2020a). Analysis of simulation results of orbit observation of stellar occultation technology. Spectrosc. Spect. Anal., 40(1), 298–304. https://doi.org/10.3964/j.issn.1000-0593(2020)01-0298-07 |
|
Sun, M. C., Wu, X. C., Gong, X. Y., and Hu, X. (2020b). Transmittance simulation calculation based on 3D ray tracing and HITRAN database. Spectrosc. Spect. Anal., 40(7), 2092–2097. https://doi.org/10.3964/j.issn.1000-0593(2020)07-2092-06 |
|
Swartz, W. H., Yee, J. H., Vervack, R. J. Jr., Lloyd, S. A., and Newman, P. A. (2002). Photochemical ozone loss in the Arctic as determined by MSX/UVISI stellar occultation observations during the 1999/2000 winter. J. Geophys. Res.:Atmos., 107(D20), 8296. https://doi.org/10.1029/2001JD000933 |
|
Yee, J. H., Vervack, R. J. Jr., DeMajistre, R., Morgan, F., Carbary, J. F., Romick, G. J., Morrison, D., Lloyd, S. A., DeCola, P. L., … Meng, C. I. (2002). Atmospheric remote sensing using a combined extinctive and refractive stellar occultation technique 1. Overview and proof-of-concept observations. J. Geophys. Res., 107(D14), 4213. https://doi.org/10.1029/2001JD000794 |
|
Zhang, H., and Shi, G. Y. (2000). A fast and efficient line-by-line calculation method for atmospheric absorption. Chin. J. Atmos. Sci., 24(1), 111–121. https://doi.org/10.3878/j.issn.1006-9895.2000.01.12 |
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