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Zinovy Malkin: CPO Prediction: Accuracy Assessment and Impact on UT1 Intensive Results, IVS 2010 General Meeting Proceedings, p.261­265 http://ivscc.gsfc.nasa.gov/publications/gm2010/malkin.pdf

CPO Prediction: Accuracy Assessment and Impact on UT1 Intensive Results
Zinovy Malkin
Central Astronomical Observatory at Pulkovo of Russian Academy of Sciences e-mail: malkin@gao.spb.ru

Abstract
The UT1 Intensive results heavily depend on the celestial pole offset (CPO) model used during data processing. Since accurate CPO values are available with a delay of two to four weeks, CPO predictions are necessarily applied to the UT1 Intensive data analysis, and errors in the predictions can influence the operational UT1 accuracy. In this paper we assess the real accuracy of CPO prediction using the actual IERS and PUL predictions made in 2007-2009. Also, results of operational processing were analyzed to investigate the actual impact of EOP prediction errors on the rapid UT1 results. It was found that the impact of CPO prediction errors is at a level of several microseconds, whereas the impact of the inaccuracy in the polar motion prediction may be about one order of magnitude larger for ultra-rapid UT1 results. The situation can be amended if the IERS Rapid solution will be updated more frequently.

1. Intro duction
Rapid VLBI UT1 observations are vital for the accuracy of the rapid IERS EOP solution and its prediction. To decrease rapid UT1 latency, special single-baseline 1-hour sessions are conducted practically every day with a delay in processing from several hours to several days. As shown in previous studies [1­3] UT1 estimates obtained from the single-base Intensive programs heavily depend on the celestial pole motion model used during analysis. For the most exacting applications, the celestial pole coordinates are computed as the sum of theoretical values given by an adopted theory of precession-nutation, IAU2000A nowadays, and corrections called celestial pole offset (CPO) that are obtained from observations, exclusively VLBI nowadays. The CPO comprises trends and (quasi)periodic components, Free Core Nutation (FCN) in the first place, caused by the inaccuracy of Earth Rotation theory. The most accurate CPO is obtained from 24-hour VLBI sessions and is available, as a rule, with a delay from two to four weeks1 . Therefore CPO predictions are necessarily applied to the UT1 Intensive data analysis, and errors in the predictions can influence the rapid UT1 accuracy. In this paper the real accuracy of CPO predictions is assessed using the actual predictions made by IERS (USNO) and PUL IVS Analysis Center (Pulkovo Observatory). The required prediction length can be found from analysis of the IVS combination delay, i.e., the time between the date of publication of the IVS combined solution and the last EOP epoch in this solution. For 2009, the median delay was 18 days, while the maximum delay was 37 days. We extend our analysis to the longer length, which may be interesting for other applications. Of course, the IVS series is then updated with new observations processed, but these changes in the IVS data are small enough to significantly influence rapid UT1 results.
Strictly speaking, CPO results from individual Analysis Centers are available with lower delay, but we consider the IVS combined CPO series as the most suitable for the EOP service applications. IVS 2010 General Meeting Proceedings 261
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Zinovy Malkin:

CPO Prediction: Accuracy and Impact on UT1

This paper is aimed at an accuracy assessment of the CPO predictions computed with different models. As usual, the prediction accuracy is derived from a comparison of predicted values with the final ones. For a proper interpretation of the results obtained in this study, the following circumstance should be taken into account. Each CPO model is a result of the fitting of observed CPO series. The models differ not only by the method of fitting, but also by the CPO data used in the analysis, which makes results from the accuracy assessment somewhat ambiguous. One may consider the prediction accuracy with respect to the model itself, which is, in fact, the accuracy of representation of the given model. However, we are interested in the accuracy of the representation of the actual celestial pole motion, which is the most important for the ma jority of users. For this reason we use a comparison of CPO predictions with the IVS combined CPO series, which is intended to be an official standard.

2. Data Used
In this study we present results of processing VLBI observations made in the framework of the IVS UT1 Intensive observing program with different delay and different CPO models. The following data were used: · INT1 sessions, observed on the workdays on the stations KOKEE (Kk) and WETTZELL (Wz); the database is normally available in 2­5 days. · INT2 sessions, observed on weekends on the stations TSUKUB32 (Ts) and WETTZELL; the database is normally available in 1­2 days. · INT3 sessions, observed on Monday on the stations NYALES20 (Ny), TSUKUB32, and WETTZELL; the database is normally available on the same day. The following actual and publicly available CPO models were tested: · IERS final EOP series computed at the Paris Observatory (C04 series) [4]. It does not contain prediction and thus is equivalent to a zero model for rapid data processing. · IERS rapid EOP series computed at the USNO (NEOS model) [4]. It is constructed from analysis of the NEOS combined CPO series and updated daily. · Lambert's FCN series computed at the Paris Observatory (SL model) [5]. As a matter of fact, it can represent only the FCN contribution to CPO. However, this model is recommended by the IERS Conventions (2003) as the substitute for CPO. It is constructed from the analysis of the IERS combined series C04 and updated every several months. · The author's ZM2 model computed at the Pulkovo Observatory [6]. It is constructed from the analysis of the IVS combined CPO series and updated daily. Comparison of these models with IVS data is shown in Fig. 1.

3. Accuracy of CPO Predictions
As usual, the accuracy of CPO predictions was estimated by a comparison of predicted and final values. Predictions made in the period from December 30, 2006 through December 25, 2009 were used. Both the rms and maximum prediction errors were computed; the latter causes the maximum dilution in the UT1 accuracy and thus is very important. Results are presented in Figs 2 and 3. One can see that ZM2 model provides the best accuracy of CPO prediction.
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CPO Prediction: Accuracy and Impact on UT1

0.6 0.4 Xc, mas

IVS NEOS SL ZM2

0.4 0.2 Yc, mas 0 -0.2 -0.4 -0.6

IVS NEOS SL ZM2

0.2 0 -0.2 -0.4 2007 2007.5 2008 2008.5 2009 2009.5 2010 Years

2007 2007.5 2008 2008.5 2009 2009.5 2010 Years

Figure 1. CPO models compared with the IVS combined CPO series.
0.4 NEOS SL ZM2 0.3 dX, mas 0.2 0.1 0.1 0 0 20 40 60 Prediction length, days 80 100 0 0 20 40 60 Prediction length, days 80 100 dX, mas 0.6 0.5 0.4 0.3 0.2 NEOS SL ZM2

0.4

NEOS SL ZM2 0.3 dY, mas 0.2 0.1 dY, mas

0.6 0.5 0.4 0.3 0.2 0.1

NEOS SL ZM2

0 0 20 40 60 80 100 Prediction length, days

0 0 20 40 60 80 100 Prediction length, days

Figure 2. The rms error of CPO prediction for different models.

Figure 3. The maximum absolute error of CPO prediction for different models.

4. Impact of Prediction Errors on Rapid UT1
To investigate the impact of the CPO prediction error on the rapid UT1 estimates, we started an experimental processing of INT1, INT2, and INT3 sessions with different CPO models in October 2009. All the computations presented here were made with the ZM2 model. Using other models gave similar results. Each session was processed three times: 1. immediately after the database is available (O); during INT1 and INT2 processing interpolated polar motion (PM) and extrapolated CPO are used, and during INT3 processing both CPO and PM are extrapolated; 2. 5-7 days after the date of observations (O2); in this case practically the final PM is available, but CPO is still extrapolated;
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CPO Prediction: Accuracy and Impact on UT1

3. at least 10 days after the IVS combined CPO for the date is available (F); during this processing practically both the final CPO and PM are available. In the beginning of this work, only operational processing (O) was performed. The first O2 processing was made in December 2009. The differences between the UT1 estimates obtained with different delays for several sessions are shown in Tables 1 and 2. These results are quite representative for all the computations. Comparisons of F-O, O2-O, and F-O2 differences show that errors in extrapolated PM coordinates have a more significant impact on the UT1 estimates than on the CPO prediction errors. This can be explained by the fact that, while the maximum CPO 30-day prediction error during the last three months was about 0.15 mas (for ZM2 model), the maximum PM error for the IERS Bulletin A 1-day PM prediction during the same period was about 1.7 mas and 0.94 mas for X and Y pole coordinates, respectively. Consequently, the impact of the PM prediction errors is about one order of magnitude larger than the impact of the CPO prediction errors. The latter is at a level of a few microarcseconds, much less than the uncertainty of UT1 estimates. This result is in good agreement with Nothnagel's estimate of a single-baseline UT1 bias at the level of 1 microsecond for a 40-microarcsecond bias in CPO or PM [2]. One can see that INT3 results obtained for the whole 3-station network NyTsWz are similar to the single-baseline solutions TsWz for the same sessions.

5. Conclusion
The impact of a CPO prediction error on the rapid UT1 results seems not to be very significant, much less than the impact of the PM prediction error. The very rapid UT1 observations of the INT3 observing program that are correlated on the day of the observations--so that the database is normally available before the IERS Rapid combination used as a priori EOP is updated-- sometimes show very large biases up to several tens of microseconds as compared with results of processing made after interpolated IERS PM data is published. The situation can be amended if the IERS Rapid solution will be computed and published more frequently, say every 6 hours, after the ultra-rapid IGS combination is ready. Such an approach seems to be much more preferable than a user doing a home-bred combination of the IERS and IGS data. More details of this study are given in [7].

References
[1] Titov O.A. (2000) In: Proc. IAU Coll. 180, Washington DC, 27­30 Mar 2000, Eds. K.J.Johnston, D.D.McCarthy, B.J.Luzum, G.H.Kaplan, 259­262. [2] Nothnagel A. and Schnell D. (2008) J. Geodesy, V. 82, 863­869. [3] Malkin Z. (2009) Presented at the IERS Workshop on EOP Combination and Prediction, Warsaw, 19­21 Oct 2009, http://www.cbk.waw.pl/EOPPW2009/contributions/session1/session1.1/ mon10 Malkin.pdf, visited on January 25, 2010. [4] IERS Annual Report 2007, Verlag des Bundesamts fur Kartographie und GeodЁsie, Frankfurt am Main, Ё a 2009. [5] Lambert S.B. (2009) http://syrte.obspm.fr/lambert/fcn/notice.pdf, visited on January 25, 2010. [6] Malkin Z.M. (2007) Solar System Research, V. 41, 492­497. [7] Malkin Z.M. (2010) Astronomy Reports, in press.

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CPO Prediction: Accuracy and Impact on UT1

Table 1. Differences between UT1 estimates obtained using different delays (µs): INT1 (KkWz). See text.

Session code I09357 I09362 I09363 I09364 I09365 I10004 I10005

Weekday Wed Mon Tue Wed Thu Mon Tue

UT1 F-O -2.0 -1.5 -1.7 -1.5 -1.9 -0.3 -1.8

differences F-O2 O2-O -2.0 0.0 -1.6 0.1 -1.5 -0.2 -1.1 -0.4 -1.6 -0.3 -1.6 1.3 -1.8 0.0

Session code I09348 I09349 I09350 I09351 I09352 I09355 I09356

Weekday Mon Tue Wed Thu Fri Mon Tue

UT1 F-O -2.2 -2.1 -0.2 -0.8 -0.9 -1.3 -1.6

differences F-O2 O2-O -2.2 0.0 -1.6 -0.5 -1.3 1.1 -0.8 0.0 -0.8 -0.1 -1.3 0.0 -1.6 0.0

Table 2. Differences between UT1 estimates obtained using different delays (µs): INT2 and INT3. See text.

Session code K K K K K K K K K K K K K K K K K K K K K K K K K K K K K K K K K K 09299 09304 09305 09306 09311 09312 09313 09318 09319 09320 09325 09326 09327 09332 09333 09334 09339 09340 09341 09346 09347 09348 09353 09354 09355 09360 09361 10002 10003 10004 10011 10018 10025 10032

Weekday Mon Sat Sun Mon Sat Sun Mon Sat Sun Mon Sat Sun Mon Sat Sun Mon Sat Sun Mon Sat Sun Mon Sat Sun Mon Sat Sun Sat Sun Mon Mon Mon Mon Mon

UT1 differences TsWz (INT2) F-O F-O2 O2-O -1.6 -3.2 9.4 47.1 -3.1 1.6 8.4 1.5 -0.4 0.3 -1.6 -1.0 20.8 0.6 5.7 -1.6 -1.0 0.6 -0.9 -0.5 0.5 -1.0 0.2 1.6 -1.4 -9.2 0.1 -9.3 -1.3 -0.6 -0.7 0.2 0.0 0.2 3.5 -0.6 4.1 -1.0 -1.0 0.0 1.7 -1.3 3.0 -2.8 -2.7 -0.1 -1.2 -2.7 1.5 2.9 -1.7 4.6 5.7 -3.0 8.7 -15.3 -2.8 -12.5 -4.7 -2.5 -2.2 -11.9 -3.2 -8.7 NyTsWz (INT3) F-O F-O2 O2-O

0.5 6.4 -13.3 -4.6 -10.7

-2.1 -2.6 -2.7 -2.5 -3.1

2.6 9.0 -10.6 -2.1 -7.6

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