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Improved Prediction of Polar Motions by Piecewise Parameterization

Treść / Zawartość
Identyfikatory
Warianty tytułu
Konferencja
Proceedings of the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) Workshop, online, February 15-16, 2022
Języki publikacji
EN
Abstrakty
EN
Natioinal Time Service Center of Chinese Academy of Sciences, Lintong, Shaanxi, China e-mail: yuanwei.wu@ntsc.ac.cn ABSTRACT. On seanonal timescale, the variation of Earth rotation is mainly regulated by angular momentum exchanges between the solid Earth and the fluidal atmosphere, ocean and hydrosphere. In the 2nd EOP PCC, we developed Dill2019’s method for polar motion prediction, using piecewise autoagressive parameters. The maximum prediction errors within 90 days are 36 and 16 mas for polar motion x and y components, respectively. Compared with Bulletin A, the mean absolute error of polar motion y prediction is improved by 20% in all timescale, and with a maximum improvement of 49% on the 5th day. Whereas, for polar motion x, the performance is slightly better (2% - 8%) within 30 days but worse (−7%∼ −19%) within 30∼90 days. We found that the prediction accuracy is very sensitive to the quality of the angular momentum data. For example, on average, the prediction of polar motion y is around 2 times better than polar motion x. In addition, we found the accuracy of 30-90 days prediction is dramatically decreased in the year 2020. We suspect that such deterioration might be due to the pandemic of coronavirus COVID-19, which suppressed global airline activities by more than 60%, then result in a lose of air-borne meteorological data, which are important for weather forecast.
Rocznik
Strony
290--299
Opis fizyczny
Bibliogr. 10 poz., rys., tab.
Twórcy
autor
  • Natioinal Time Service Center of Chinese Academy of Sciences, Lintong, Shaanxi, China
autor
  • Natioinal Time Service Center of Chinese Academy of Sciences, Lintong, Shaanxi, China
autor
  • Natioinal Time Service Center of Chinese Academy of Sciences, Lintong, Shaanxi, China
Bibliografia
  • Akaile, H., (1971) Autoregressive model fitting for control, Ann. Inst. Stat. Math., Vol. 23, 163-180.
  • Barnes R.T.H., Hide, R., White A.A. Wilson, C.A., (1983) Atmospheric angular momentum fluctuations, length-of-day changes and polar motion, Proc. R. Soc. Lond. A, Vol. 387, 31.
  • Boy J.P., Longuevergne L., Boudin F., Jacob T., Lyard F., Llubes M., Florsch N., Esnoult M.F., (2009) Modelling atmospheric and induced non-tidal oceanic loading contributions to surface gravity and tilt measurements, Journal of Geodynamics, Vol. 48, Issues 3-5, 182-188.
  • Brockwell, P.J., Davis, R.A., (1996) Introduction to Time Series and Forecasting, Springer, New York, 420 pp.
  • Dill R., Dobslaw H, Thomas M. (2013) Combination of modeled shortterm angular momentum function forecasts from atmosphere, ocean, and hydrology with 90-day EOP predictions, Journal of Geodesy, Vol.87, 567-577.
  • Dill R., Dobslaw H, Thomas M. (2019) Improved 90-day Earth orientation predictions from angular momentum forecasts of atmosphere, ocean, and terrestrial hydrosphere, Journal of Geodesy, Vol.93, 287-295.
  • Dobslaw H., Dill R., Grötzsch A., Brzezinski A., Thomas M. (2010) Seasonal polar motion excitation from numerical models of atmosphere, ocean, and continental hydrosphere. Journal of Geophysical Research (Solid Earth), Vol. 115, Issue B10, 406-417.
  • Gross R.S., Fukumori I., Menemenlis D. (2003) Atmospheric and oceanic excitation of the Earth’s wobbles during 1980-2000. Journal of Geophysical Research, Vol. 108, 2370.
  • Gross R.S., (2007) Earth Rotation Variations - long period, Phisical Geodesy, eds. Herring T. A., Treatise on Geophysics, Vol. 11, Amsterdam, 2007.
  • Petit G. & Luzum B. (2010) IERS Technical Note 36, IERS Conventions (2010).
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4f37d761-de95-48d0-9d67-77d7456f1341
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