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New validation methods for ARGO profilers data Preliminary results

New validation methods for ARGO profilers data Preliminary results. Carole Saout Hocer company for Coriolis. Argo Steering Team, 18-20 March 2008 – Exeter - UK. Objectives of the study.

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New validation methods for ARGO profilers data Preliminary results

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  1. New validation methods • for ARGO profilers data • Preliminary results • Carole Saout • Hocer company for Coriolis • Argo Steering Team, 18-20 March 2008 – Exeter - UK.

  2. Objectives of the study This study is done in the framework of CORIOLIS project to define new diagnosis to approve quality controls on ARGO profilers data in real-time and delayed-mode. • 1) - Compare ARGO data with : • two different climatologies : Levitus WOD05 and Argo Climatology of Gaillard et al. (LPO, Ifremer Brest)‏ • objective analysis maps produced by the Coriolis Data Center (CDC) at Ifremer Brest in delayed-mode. • Compare nearby profilers, profilers of the same type, or equipped with same sensors. New validation methods for ARGO profilers data Carole Saout / Hocer Cie 2) -Build a validation prototype, which could be easily integrated into the operational CDC (GDAC)

  3. Reading of ARGO data • One Netcdf file per month, for year 2007, from the CDC website and its data selection tool -> delayed-mode time, which have been controlled by the ARGO automatic tests and by the Coriolis Objective Analysis. • Only ARGO data with TEMP_QC and PSAL_QC = 1 or 2, ie good or probably good • Extraction of all profiles existing in a temporal window (Ta - 21 days,Ta), Ta is an analysis date specified by the user.‏ New validation methods for ARGO profilers data Carole Saout / Hocer Cie 5126 profiles for Ta= 20.05.2007 (2311 profilers) : 3179 apex sbe 421 provor sbe 19 provor fsi 1165 solo sbe 52 solo fsi

  4. Reading of data : Levitus Climatology WOD05 • built-in thanks to all data available from 1950 to 2005, and obtained from the NODC website in the Netcdf format • Monthly analyzed fields of (T,S) on a 1°*1° horizontal grid, and 24 depth levels ([0:10:30,50:25:150,200:50:300,400:100:1500] • Associated standard deviations New validation methods for ARGO profilers data Carole Saout / Hocer Cie Mean May (left): Temperature and (right) Salinity WOD05 fields at 1000m.

  5. Reading of data : ARGO climatology • built-in by Gaillard and Von Schukmann (LPO, Ifremer Brest) in the framework of ARIVO project. For more details, see : http://www.ifremer.fr/lpo/arivo • based on the objective analysis of delayed-mode ARGO data available from 2003-2006, and real-time ARGO data for 2007. • Monthly analyzed fields of (T,S) in Netcdf files (one file per month) on a 0.5°*0.5° horizontal grid, and 152 depth levels ([0:5:100,110:10:800,820:20:2000] • Associated standard deviations, calculated from the monthly mean std values between 2003-2007 New validation methods for ARGO profilers data Carole Saout / Hocer Cie (left): ARGO climatology std and (right) : WOD05 std, at 1000m.

  6. Reading of data : Coriolis Objective Analysis (OA)‏ • Results of operational Objective Analysis running at the CDC • Gridded (T,S) fields, written in Netcdf files, on a 0.5°*0.5° horizontal grid and 59 depth levels ([5,10:10:80,100:20:400,440:1600,1650:50:1950])‏ New validation methods for ARGO profilers data Carole Saout / Hocer Cie 23.05.2007 Objective Analysis map at 1000m for Temperature (left) and Salinity (right). -> To compare OA results with ARGO data, we interpolate OA profiles at ARGO profiles, and we consider an average of all OA results existing inside the last three months from Ta, excluding the temporal window (Ta-21,Ta).

  7. First diagnosis on global ocean • We have calculated three types of anomalies at profiles locations : • ∆1 = (T,S) argo-(T,S) wod05 • ∆2 = (T,S) argo – (T,S) argo clim. • ∆3 = (T,S) argo – (T,S) ao mean • 1st test : detect ∆ i > 3 or 10 std.levitus on more than the half of the water column height • 2nd test : detect ∆i > 3 or 10 std argoclim. on more than the half of the water column height New validation methods for ARGO profilers data Carole Saout / Hocer Cie ->listingin a file of those bad profiles, with all of their characteristics (no wmo, no platform, long, lat,date...)‏ -> plot of their positions, with : green points if ∆i >3std red points if ∆i >10std‏ Anomalies in Salinity > 3stdlev (green points) or >10 stdlev (red points)‏

  8. Examples of bad profiles detected in salinity 10*std argo clim. New validation methods for ARGO profilers data Carole Saout / Hocer Cie > 10 std argo climatology 10*std Levitus > 10 std levitus

  9. Examples of bad profiles detected in temperature > 10 std Lev. ∆ greater than 10std levitus but not always greater than 10std argo clim.

  10. First statistics on global ocean New validation methods for ARGO profilers data Carole Saout / Hocer Cie ∆ 2 at 100m in Salinity ∆ 2 at 100m in Temperature Mean and std of anomalies in Salinity : < ∆ 1> = -0.002 +/- 0.138 < ∆ 2> = -0.0023 +/- 0.122 < ∆ 3> = 0.0013 +/- 0.112 Mean and std of anomalies in Temperature : < ∆ 1> = 0.0675 +/- 0.9 < ∆ 2> = -0.014 +/- 0.83 < ∆ 3>= 0.043 +/- 0.938 • Argo clim. better than WOD05 clim. • AO results better than Argo clim. in salinity • bad XBTs in OA results may explain that Argo clim. is better than AO in temperature

  11. First statistics on global ocean For Ta= 20.05.2007, it represents : in temperature: 0% of ∆> 10 stdargoclim. 0,4 % of ∆> 10 stdlev 0.78% of ∆ > 3 stdargoclim. 4.91% of ∆> 3 stdlev in salinity : 0,039% of ∆ > 10 std argoclim. 3.45 % of ∆> 10 stdlev 0.88% of ∆ > 3 std argoclim. 12.3 % of ∆> 3 stdlev New validation methods for ARGO profilers data Carole Saout / Hocer Cie • Those first simple diagnosis allow us to detect bad profiles not yet detected by automatic quality controls. • It will allow the operational CDC to look closer to those bad profiles • We didn't consider them for incoming diagnosis

  12. More general diagnosis on global ocean New validation methods for ARGO profilers data Carole Saout / Hocer Cie Mean temperature function of depth estimated on global ocean from argo data (red), wod05 colocated data (blue) and colocated argo climatology data (magenta). Mean salinity function of depth estimated on global ocean from argo data (red), wod05 colocated data (blue) and colocated argo climatology data (magenta). • Similar temperature estimations from ARGO data and the 2 climatologies • Mean salinity from ARGO lower than mean salinity from the 2 climatologies, mainly below 600m.

  13. More general diagnosis by latitude strips MID-LATITUDES EQUATOR New validation methods for ARGO profilers data Carole Saout / Hocer Cie HIGH-LATITUDES Mean and std of salinity by latitude strips

  14. More general diagnosis by basins ATLANTIC PACIFIC New validation methods for ARGO profilers data Carole Saout / Hocer Cie INDIAN Mean and std of salinity by basins.

  15. First Conclusions and Perspectives • FIRST CONCLUSIONS • The calculation of ARGO data anomalies in reference of three independent sources (two different climatologies, and CDC objective analysis results) allows to detect bad profiles very far from the std of Levitus climatology or std of Argo climatology. • the Argo climatology standard deviation is very different from the Levitus standard deviation. • Argo Climatology seems to give an accurate and more recent information of the ocean content for years 2003-2006. It has to be improved for year 2007 incorporating delayed-mode controlled data. • CDC Objective Analysis temperature for 2007 have to be corrected avoiding doubtful XBT data due to wrong fall rate. • For Ta= 20.05.2007, the number of bad profiles compared to std of Argo climatology is negligible. New validation methods for ARGO profilers data Carole Saout / Hocer Cie • PERSPECTIVES • Run all year 2007, and compare results with Guinehut et al. • zoom in analysis zone. Diagnosis in specific geographical boxes of interest • Compare ARGO profiles with nearby profilers • Develop the validation prototype for CDC • Work on a delayed mode ARGO clim and delayed mode OA

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