Date: Tue, 4 Mar 2003 16:36:30 -0800
From: Pascal Willis <Pascal.R.Willis@jpl.nasa.gov>
To: Daniel Gambis <gambis@hpopa.obspm.fr>,
    Richard Gross <rsg@mail1.jpl.nasa.gov>,
    Zuheir Altamimi <altamimi@ensg.ign.fr>,
    Meise Barbara <meisel@dgfi.badw.de>
Cc: Martine Feissel <feissel@ensg.ign.fr>,
    Gilles Tavernier <Gilles.Tavernier@cnes.fr>,
    Jean-Paul Berthias <jean-paul.berthias@cnes.fr>,
    Carey Noll <carey.noll@gsfc.nasa.gov>,
    Jean-Jacques Valette <valette@cls.fr>,
    Laurent Soudarin <Laurent.Soudarin@cls.fr>,
    Serguei Kuzin <skuzin@inasan.rssi.ru>,
    Jean-Francois Cretaux <cretaux@cnes.fr>,
    "John C. Ries" <ries@csr.utexas.edu>,
    Yoaz Bar-Sever <Yoaz.Bar-Sever@jpl.nasa.gov>
Subject: DORIS/EOP precision vs epoch of minimum variance

dear all,

following my recent message, I have slightly modified the method to 
look separately for 2 different epochs of minimum variance for the 
EOP (one for XPOLE and another one for YPOLE).

I give you below the statistics of the IGN/JPL DORIS/EOP vs the 
GPS/IGS solution (no mean and no trend removed) by satellite, using 
directly file ign02wd02.eop posted at CDDIS.

The first RMS value compares the EOP series at 12:00
The second RMS value compares the EOP series at 12:00 + delta (epoch 
of minimum variance)
The number of data points is the number of EOP values used to estimate the RMS

#satellites	#datapoints	XPOLE_RMS	YPOLE_RMS
1		29		2.66 / 2.57	2.04 / 2.05
2		615		2.54 / 2.36	1.59 / 1.43
3		1521		1.94 / 1.84	1.38 / 1.32
4		52		2.42 / 2.27	1.42 / 1.16
5		106		2.23 / 1.89	1.25 / 1.01

With the comments that I gave before, you can see that the more DORIS 
satellites we have the best results we get (specially for the 
Y-component).

Secondly, the approach of minimum variance provides better 
consistency with GPS at the 1.0 mas level with 5 satellites in Y, 
which I think is an important aspect in the assessment of the DORIS 
accuracy vs the number of available DORIS satellites.

When doing periodogram on these series, it is easy to show a strong 
5.2 day signal in the Y component (that can be linked to SPOT 
mis-modelling) and for the X-component, weaker signals at 5.2 days 
(SPOT again) and 60.0 days (TOPEX).

I have put a file for you (delta_time) if you want to do similar 
tests or just want to use the correct epoch of minimum variance in 
your tests. For example, I could not do any test before the start of 
the IGS/EOP series (1996, June 30). There is far more tests that can 
be done by selecting which satellites are effectively used that day 
and look for patterns.

I would be very much interested to see other type of accuracy 
assessments for all the available DORIS EOP series. This could help 
us improve our DORIS modelling and/or estimation strategy.

Best regards
Pascal

----------------------------------------------------------------------
How to get the file with the epoch of minimum variance

ftp lareg.ensg.ign.fr
cd incoming
get delta_time

The file looks like that  :

mjd       t_X (day)      t_Y (day)     t_mean (day)
48990.50  0.0941994451  -0.0255479633  0.0343257409
48991.50  0.0848377797  -0.0206493185  0.0320942306
48992.50  0.0647661588  -0.0473589660  0.0087035964
......
52632.50  0.1109600842  -0.0382938349  0.0363331247
52633.50  0.1382624568  -0.0450430384  0.0466097092
52634.50  0.1287056298  -0.0526637502  0.0380209398
52635.50  0.1364617025  -0.0534530551  0.0415043237
52636.50  0.0766129503  -0.0248054967  0.0259037268

column 1 = Modified Juilan Day
column 2 = delta that you need to add to mjd to get the epoch of 
minimum variance for X Pole
column 3 = delta that you need to add to mjd to get the epoch of 
minimum variance for Y Pole
column 4 = average of column 3 and 4 (not the best for correction)



