ࡱ> LNK ,bjbjFF +*$${  8<^C[[qqqBBBBBBB6EGBBqqhB4jqqBBn>A~Oj? B<"C<^C @HH@AAB }:   GTSPP National Data Management Report 2009 National Marine Data & Information Service, China Annual report 2009 Version 1.0 2010-04-20 Status NMDIS has set up an operational data processing system which downloads GTSPP real time data everyday and the best data each month. The system reformats the data to a more easy-reading format, QCs the data automatically and manually and loads the data into the RT & DM GTSPP database. Meanwhile the data are delivered on the website so the users can access to them. Besides, NMDIS has been devoting to collecting the temperature and salinity data observed by other projects in China, such as the data from ocean stations, China Argo Project, section observing in east and south sea of China and polar research etc. The below list are the data NMDIS has forwarded to NODC. Data acquired from ships, gliders, sea-mammal numbers, locations, platform types, SOOP line numbers List of the platforms that reported temperature and/or salinity profiles: SHIPS : 4 ships near north of china sea Gliders : none Sea-mammals : none Coastal observation station:13 ocean stations with temperature salinity wind and wave data Data issued to US-NODC after real-time QC Real-time data from 13 ocean stations daily update since Jan of 2010 Data issued for delayed QC Argo data, section data and the polar research data are all issued for delayed QC Delayed mode data sent to US-NODC Section observing data from 2000 to 2007and the number of it is about 875. Delayed mode data from 13 ocean stations expand from1989 to 2009. Web pages Set up the website in 2007 and all the data after QC are available Statistics of GTSPP data usage: according to the statistics of the GTSPP website, number of visitors is 2000. Products generated from GTSPP data Monthly global and pacific temperature and salinity distribution map; reanalysis product of the China coastal waters and adjacent seas from 1986 to 2008 Research operations NMDIS has been making efforts to the improvement of the delayed mode data QC methods and the QC system to make sure a higher quality data. With some expert looking over the data after the automatic QC, we find the problems in the data and try to figure out them. Also we have done a lot of work on identifying the unique data internal GTSPP and also between GTSPP and other projects like WOD or Argo. Now a primary system has been set up to mark the data may be the same.      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