Non linear prediction of Earth Orientation Parameters

Loading...

Flash Player 9 (or above) is needed to view presentations.
We have detected that you do not have it on your computer. To install it, go here.

0 comments

Post a comment

    Post a comment
    Embed Video
    Edit your comment Cancel

    Favorites, Groups & Events

    Non linear prediction of Earth Orientation Parameters - Presentation Transcript

    1. Non linear Prediction of Earth Orientation Parameters N. Rouveyrollis, D. Gambis IERS Orientation Center - Paris Observatory UMR 8630 (France) $&# 6800$5< 'LIIHUHQWDSSURDFKHVDUHXVHGIRUWKHSUHGLFWLRQRI(DUWK2ULHQWDWLRQ3DUDPHWHUV (23
    2.  7KHFXUUHQWPHWKRGXVHGDWWKH,(56(DUWK2ULHQWDWLRQ&HQWHULVEDVHGRQDILOWHULQJ GHFRPSRVLWLRQRIWKHPDLQFRPSRQHQWVRIWKHVLJQDO ,QWKHSUHVHQWVWXGZHLQYHVWLJDWH DQRWKHUDOJRULWKPEDVHGRQ6LQJXODU6SHFWUXP$QDOVLV 66$
    3. 66$LVDIRUPRI3ULQFLSDO&RPSRQHQW$QDOVLVLQWKHWLPHGRPDLQWKDWSURYLGHVGDWD DGDSWDWLYHOLQHDUILOWHURU)XQFWLRQDO3ULQFLSDO&RPSRQHQWV DOVRFDOOHG(PSLULFDO2UWKRJRQDO )XQFWLRQ(2)
    4. IRUGHVFULELQJWKHVLJQDOYDULDELOLWLQWHUPVRILWVODJFRYDULDQFHVWUXFWXUH,Q VXFKDZDDGHFRPSRVLWLRQRI3RODU0RWLRQLVSHUIRUPHG)RUWKLVDSSURDFKDQRQOLQHDU SUHGLFWHGVROXWLRQLVREWDLQHGIURPWKHVXPRIWKHSUHGLFWLRQVSHUIRUPHGRYHUHDFKFRPSRQHQW 3UHOLPLQDUUHVXOWVZHUHREWDLQHGDQGFRPSDUHGWRSUHGLFWLRQVFXUUHQWOGHULYHGDWWKH,(56 3URGXFW&HQWHU
    5.  3974/:.9 ,QWURGXFWLRQ Different approaches are used for prediction of the Earth rotation parameters. The IERS product center uses the following techniques : N Polar Motion: The formalism uses at first a floating period fit (Bevington, 1969 [2]) for both the Chandler and annual components estimation over a past time interval of several 0 years. An autoregressive filter is then applied on the short-term residuals series and used for the prediction. The predictions of the nutation offsets d and dH are based on an empirical model (Conventions 1996). N Universal Time: The present formalism used is based on the assumption that the long- term fluctuations (annual and semi-annual) of the preceding year are valid over the next few months. For short-term variations prediction, an autoregressive process is used.
    6.  42 &RPELQLQJ 66$ DQG 3UHGLFWLRQ ,3/ !7 Another approach to predict EOP series, is using SSA method (R. Vautard et al [1]) to SUHGLFWHGVROXWLRQEDVHGRQQRQOLQHDUDQDOVLVLVWKHQREWDLQHGIURPWKHVXPRIWKH extract significant components instead of adjusting the data to an a-priori model. A SUHGLFWLRQVSHUIRUPHGRYHUHDFKFRPSRQHQW We obtain the following algorithm : 6LJQLILFDQW 3UHGLFWLRQ FRPSRQHQW ,3  15  $ 6  '(  ,'  $ 6 *LYHQ $ 6  9, ,&  & 8 *OREDO VLJQDO 3UHGLFWLRQ  $ 6LJQLILFDQW '7 3UHGLFWLRQ  0 FRPSRQHQWQ 8, Q $2 /1 5HVLGXDO 3UHGLFWLRQ Q
    7. Performing a SSA decomposition we obtain the following decomposition for the x- component of polar motion:  ,(56FVHULHV S er es 1 i . 300 PHDVXUHGDW . 200 . 100 ZHHNVLQWHUYDO . 000 - 100 .  - 200 . &KDQGOHU  - 300 . FRPSRQHQW  0 200 400 600 800 1000 S er es 2 i . 250 . 200 . 150 . 100 . 050 &KDQGOHU . 000 - 050 . $QQXDO - 100 . $QQXDO  - 150 . WUDQVLWRUWHUP - 200 . FRPSRQHQW 0 200 400 600 800 1000 S er es 3 i . 140 7UHQG . 120 . 100 . 080 5HVLGXDO . 060 . 040 . 020 . 000 - 020 . - 040 . 7UHQG - 060 . - 080 . - 100 . 0 200 400 600 800 1000 S er es 4 i . 0000  - 0100 . - 0200 . - 0300 . - 0400 . 7UDQVLWRUWHUP - 0500 . 0 200 400 600 800 1000 S er es 5 i . 0200 . 0100 . 0000 - 0100 . 5pVLGXDO - 0200 . 0 200 400 600 800 1000 S er es 6 i . 060 5HSDUWLWLRQRILQGLYLGXDOYDULDQFHVWRWDOYDULDQFH . 040 . 020 . 000 - 020 . - 040 . - 060 . 0 200 400 600 800 1000
    8. ,QGLYLGXDO PRGHOLVDWLRQV $VVXPLQJWKDWHDFKSHULRGLFFRPSRQHQWLVVWDWLRQDUVHYHUDOVLPSOHPRGHOLVDWLRQPHWKRGV FDQEHSHUIRUPHGXVLQJ,760>@DQGFRPSDUHGRYHUDFKRVHQSHULRG$FRPSDULVRQ FULWHULRQWKDWFDQEHXVHGLVWKHVLPXODWLRQRIWKH0HDQ6TXDUHG(UURU 06(
    9. RYHUIXWXUH GDWHV )RUWKH±  SHULRG&KDQGOHUFRPSRQHQWFDQEH  PRGHOLVHGZLWK     $5 PRGHO XVLQJ%XUJRU<XOH VTUW 06(
    10. <XOH  VTUW 06(
    11. %XUJ :DONHUPHWKRG
    12.  VTUW 06(
    13. $50$$5RSWLPDO VTUW 06(
    14. $5$5  $50$PRGHOZLWKRSWLPDO$5  RUGHU   $5$5PRGHO ,760>@
    15.                  VLPXODWLRQRI6457 06(
    16. IRUGLIIHUHQWPRGHOVIRU&KDQGOHUFRPSRQHQW 2SWLPDO$5PRGHOLVJLYHQZLWKWKH RYHUWKHQH[WGDWHV PLQLPL]DWLRQRI$NDLNH¶VFULWHULRQ
    17.   6LPLODUZRUNFDQEHREWDLQHG  IRU$QQXDODQG7UDQVLWRU FRPSRQHQWVRYHUWKHVDPH  VTUW 06(
    18. <: VTUW 06(
    19. %XUJ SHULRG  VTUW 06(
    20. $5$5  7KH+ROW:LQWHUSUHGLFWLRQ  PHWKRGFDQEHXVHGIRUWKH  7UHQG                     VLPXODWLRQRI6457 06(
    21. IRUGLIIHUHQWPRGHOVIRU$QQXDOFRPSRQHQW RYHUWKHQH[WGDWHV 5HVLGXDOLVPRGHOLVHGZLWK 1$5;PRGHOXVLQJWKH 116<6,'WRROER[>@ 5HVLGXDOFRPSRQHQWHVWLPDWLRQ VDPSOH
    22. VLPXODWLRQ VDPSOHVHQG
    23. DQGUHDOVLJQDO RYHUWKHIXOOSHULRG
    24.  42 &RPSDULVRQ RI PHWKRGV 1 209 8VLQJFSRODUPRWLRQVHULHVIURP WRDWZHHNVLQWHUYDO FDOFXODWHGH[SHFWHGYDOXHVFDQEHFRPSDUHGZLWKUHDOVLJQDORYHUWKHQH[WZHHNV  6LPXODWLRQDFFXUDF PDV
    25.  UHDOVLJQDO       6XPRI              FRPSRQHQWV        :((.V 6DPHZRUNFDQEHSHUIRUPHGRQWKHF[FRPSRQHQWRISRODUPRWLRQ PHDVXUHGDWGDVLQWHUYDOWRSUHGLFWYDOXHVRYHUWKHHDU  3UHGLFWLRQDFFXUDF PDV
    26. ,(56  66$ 3UHGLFWLRQDFFXUDF GDV GDV GDV GDV GDV   ,(56 WSZ XS^ ZS[ ]S` `S]  66$  WS` X XS^ ]S` XWS`        GDV
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
    28. OHDGVWRDEHWWHUDFFXUDFWKDQXVLQJWKH FXUUHQWSURFHGXUHV 5HIHUHQFHV >@ 6LQJXODUVSHFWUXPDQDOVLVLQQRQOLQHDUGQDPLFVZLWKDSSOLFDWLRQVWRSDOHRFOLPDWLFWLPHVHULHV 5YDXWDUGDQG0*KLO² 3KVLFD' 
    29.  >@ 'DWD5HGXFWLRQDQG(UURU$QDOVLVIRUWKH3KVLFDO6FLHQFHV %HYLQJWRQ35 0F*UDZ+LOO1HZ<RUN >@ ,760$Q,QWHUDFWLYH7LPH6HULHV0RGHOLQJ3DFNDJHIRUWKH63$5&:RUNVWDWLRQ 3-%URFNZHOO 5$'DYLV6SULQJHU9HUODJ 
    30. 1HZ<RUN >@ 116<6,' 11&75/ 7RROVIRU6VWHP,GHQWLILFDWLRQDQG&RQWUROZLWK1HXUDO1HWZRUN 01¡UJDDUG25DYQ1.3RXOVHQ,((&RPSXWLQJ &RQWURO(QJLQHHULQJ-RXUQDO9RO1R)HESS
    SlideShare Zeitgeist 2009

    + NicolasRRNicolasRR Nominate

    custom

    68 views, 0 favs, 0 embeds more stats

    Prediction of Earth Orientation Parameters mixing E more

    More info about this document

    © All Rights Reserved

    Go to text version

    • Total Views 68
      • 68 on SlideShare
      • 0 from embeds
    • Comments 0
    • Favorites 0
    • Downloads 0
    Most viewed embeds

    more

    All embeds

    less

    Flagged as inappropriate Flag as inappropriate
    Flag as inappropriate

    Select your reason for flagging this presentation as inappropriate. If needed, use the feedback form to let us know more details.

    Cancel
    File a copyright complaint
    Having problems? Go to our helpdesk?