Reprocessing the complete history of VLBI observations with VieVS

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VieVS User Workshop 7 – 9 September, 2010 Vienna Reprocessing the complete history of VLBI observations with VieVS Sigrid Böhm

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Reprocessing the complete history of VLBI observations with VieVS. Sigrid Böhm. Why should one do that?. There are new solution methods/strategies. There is a new software. You would like to create a database with the optimal parameterization for each session. - PowerPoint PPT Presentation

Transcript of Reprocessing the complete history of VLBI observations with VieVS

Page 1: Reprocessing the complete history of VLBI observations with VieVS

VieVS User Workshop7 – 9 September, 2010

Vienna

Reprocessing the complete history of VLBI observations with VieVS

Sigrid Böhm

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Why should one do that?There are new solution methods/strategies.There is a new software.You would like to create a database with the optimal parameterization for each session.You are interested in time series of special parameters (such as ERP) covering the longest time span available.

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TS of special parameters - EOPWhich sessions to choose for processing?

Define exclusion/suitability criteriahttp://vlbi.geod.uni-bonn.de/IVS-AC/data/exclude.txt

No local or regional networksNo sessions with < 3 stations (except for dUT1 determination from Intensives)No sessions with < 250 observations

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Create a process listBasic list to start: e.g. use mk_list to get a list of intensive sessions, add this int_list to exclude.txt and then use mk_list with the option ‘ALL’ except ‘exclude.txt’.

Use preliminary list and process all sessions with a basic parameterization

Then you can use the data in LEVEL3 to make an extended exclude list according to the previously defined criteria and find sessions which are not working properly

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Interesting parameters for the criteria and for “not working properly“

DATA/LEVEL3/SUBDIR/opt_sessname.mat:opt_.total_obs = number of observationslength(opt_.stat) = number of stationsopt_.mo = error of unit weight a posterioriopt_.cond = condition number of N-matrix (a bit difficult to judge)

In Matlab: you can use diary(‘thisrun.log’) to store the output from the command window, diary off to stop the function

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e.g. log-file: search for “RCOND”

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check “geometry“Take the information from the files stored in DATA/LEVEL1 and plot the network

Regional network

→ exclude the session

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Other log-file “messages“Problems with tidal ocean loading at station VLBA85 3 Problems with tidal atmosphere loading at station VLBA85 3 Problems with non-tidal atmosphere loading at station VLBA85 3 Problems with thermal correction at station VLBA85 3 Problems with VMF1 at station VLBA85 3

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For the remaining sessions with high 0

There is no other way than … going through all of them individuallyfinding clock breaks, bad stations etc.creating hundreds of OPT files

Most welcome alternative … write a module for the automatic detection of clock breaks and creation of OPT files

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Update process listAdd all sessions you have sorted out to the „exclude“-file and run mk_list againCreate an outlier file for each session with some simple parameterization

Decide about your final parameterization according to your needs

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Some rules for EOP estimationBasic approach for daily resolution:

Estimate all five EOP xp,yp,dUT1,dX,dY with 1440 min intervalEstimate station coordinates and apply NNR, NNT conditions

Polar motion with subdaily resolution:Do not estimate but fix nutation!!Fix station coordinates

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R1 and R4 networks

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Comment on correlation coefficients

The Matlab function corrcoef works correctly but not for our purpose.

It does not take a covariance matrix as input! (Refer to Matlab Help for further info)

Correlation coefficient:

yyxx

xyxyr

Qxx = inv(atpa_.mat);varii = diag(Qxx);Rxy = Qxx./sqrt(varii*varii');

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5 EOP 24 hours, NNR/NNT

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3 ERP 1h, nut 24 h, NNR/NNT

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3 ERP 1h, nut fix, NNR/NNT

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3 ERP 1h, nut fix, coord fix

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