GODAE Quality Control Pilot Project

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Presentation transcript:

GODAE Quality Control Pilot Project An initiative aimed at improving the effectiveness of automated quality control procedures for GODAE prototype systems History Apr 2001 - need for systematic approach to ocean data quality control in support of GODAE recognized at US GODAE Workshop Jul 2001 - need reiterated at GODAE IPRC workshop at U. Hawaii Dec 2001 - model and data assimilation quality control monitoring and evaluation project formulated at the IGST VI meeting May 2002 - became integral part of the GODAE implementation plan Jun 2002 - QC workshop held in conjunction with GODAE symposium in Biarritz Oct 2003 - initiate QC methods and outcomes intercomparison project Biarritz Workshop Report: www.bom.gov.au/bmrc/ocean/GODAE/frames.html

Ocean Data Quality Control Data quality control is a fundamental component of any ocean data assimilation system accepting erroneous data can cause incorrect analysis rejecting extreme data can miss important events and anomalous features Quality control involves checking data against a pre-established set of standards requires clearly documented procedures depends on the reliability of the standards and the choice(s) made for measuring goodness of fit assumptions concerning the distribution and coherences of observation errors relative to the standards need to be routinely examined

Goals GODAE Quality Control Pilot Project Document ocean data quality control procedures in use today real-time or delayed-mode fully automated or man-machine mix of operations any data type that directly impacts ocean state estimation process (in situ and remotely sensed) Initiate intercomparison projects among groups performing QC routine sharing of QC results (real-time and delayed mode) define QC outcomes (metadata) that can be shared among data users describe QC test procedures needed in the future (e.g. specific instrumentation error checks) Develop partnerships with data providers feedback on model-data differences data acceptance, data rejection rates identification of systematic problems in observing systems

Participants GODAE Quality Control Pilot Project US Navy (NRL - FNMOC, NAVOCEANO) - J. Cummings real-time, fully automated all operational data sources (profile and in situ off GTS, satellite data from NAVOCEANO) Met Office (FOAM, ENACT) - M. Huddleston, B. Ingleby real-time, delayed mode, automated and manual (visual inspection) profile, in situ data (GTS) MEDS (GTSPP) - B. Keeley profile, in situ data off GTS Coriolis Center (SOAP/MERCATOR) - T. Carval

Status GODAE Quality Control Pilot Project QC Pilot Project web page created on GODAE server QC system documentation available - MEDS, FOAM/ENACT, Coriolis, NRL QC data on GODAE server NRL QC data files updated daily (all sources, in situ and satellite) MEDS GTSPP files updated every 3 days links to Coriolis Center Mercator/SOAP data code to read different formats and produce common ASCII text format for intercomparison of QC outcomes under development formed liaison with CLIVAR GSOP/DPM (SIO, Feb 2004) access to additional scientific QC data for intercomparison access to delayed mode/scientific QC procedures: can delayed mode QC procedures be automated and run in real-time?

Plans GODAE Quality Control Pilot Project Focus on Argo data for initial intercomparison study existing, well defined data management strategy real-time and delayed mode QC in place with feedback mechanisms observations are readily available and widely used Reanalysis effort using expertly QC’d Indian Ocean data from CSIRO compare with Enact dataset, NRL R/T system, World Ocean Database, others? examine regional and/or temporal variability in patterns of rejection detailed cross-evaluation of profiles rejected by one system and accepted by another (knowing “truth” from expert) test down-stream effects of QC decisions what is added value of a model to the process what is effect of differential profile acceptance/rejection on derived ocean products define factors that influence both R/T and scientific QC acceptance and rejection rates