Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , 3 erent ff ) profiles ) for the , 4 S Discussions , S. Pouliquen Science 2 , V. Turpin 3 ) and salinity ( T ´ e, France , G. Reverdin 6 , M. Hamon ´ e, France 2 , N. Ferry 5 1274 1273 , C. Boone 5 , K. von Schuckmann ´ e, France 1 orts to produce such an ideal dataset have been done for ). ff 3 ´ eanographie Spatiale, IFREMER, Plouzan , S. Guinehut 4 erent, especially with in situ oceanographic data such as temperature , A. Grouazel ff 1 This discussion paper is/has beenPlease under refer review to for the the corresponding journal final Ocean paper Science in (OS). OS if available. SISMER, IFREMER, Plouzan CLS-Space Division, Ramonville Saint-Agne, France MERCATOR OCEAN, Ramonville St Agne, France CNRS, LOCEAN, Paris, France Laboratoire d’Oc Division technique de l’INSU, UPS855, CNRS, Plouzan http://www.myocean.eu/ 4 5 6 Received: 1 March 2012 – Accepted: 8Correspondence March to: 2012 C. – Cabanes Published: ([email protected]) 21 MarchPublished 2012 by Copernicus Publications on behalf of the European Geosciences Union. 2 3 and P.-Y. Le Traon 1 1 Introduction An ideal set ofin time, oceanographic is in-situ subject datapasses to comprehends several regular global scales quality coverage, inity controls continuity and is space calibration often and procedures, di and time. and salinity. This encom- Those goal datatives is have to basically not collect as easymany many them. to years, origins E reach especially as since and thereCoriolis Levitus real- are (1982). has During scientific developed this initia- thehttp://www.coriolis.eu.org/Science/Data-and-Products/CORA-Documentation decade, yearly the up-dated French program dataset for Re-Analysis (CORA, tions. This Coriolis product is( available on request through the MyOcean Service Desk this dataset, several tests have beenquality developed of to the improve raw in datasetactivities a and (assimilation homogeneous to and way fit the validation). the These leveltests include required and some by a simple the model tests, physical background climatological oceanity check re-analysis control based (QC) on is a performed globalidentified on ocean by all reanalysis. the suspicious Visual tests temperature qual- anddition, ( quality improved diagnostic flags tools are were modifiedwhich developed in give – the information including on dataset global the if ocean potential necessary. indicators and In – quality ad- of the CORA dataset for all applica- The French program Coriolistem produces as the part COriolisis of based dataset the on for French temperature Re-Analysis anddata oceanographic (CORA) salinity types. operational measurements on The sys- on a latest observed yearly levels release from basis of di which CORA covers the period 1990 to 2010. To qualify C. Coatanoan Abstract The CORA dataset: validation and diagnostics of ocean temperature and salinity in situ measurements C. Cabanes Ocean Sci. Discuss., 9, 1273–1312, 2012 www.ocean-sci-discuss.net/9/1273/2012/ doi:10.5194/osd-9-1273-2012 © Author(s) 2012. CC Attribution 3.0 License. 5 20 25 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | http: http: ), to the ) (e.g. von Schuckmann and cult task. els et al., 2008; Levitus et al., 2009; ffi http://www.mercator-ocean.fr ffi els (2008). Statistical tests are performed ff 1276 1275 ), as well as to several national systems. The http://www.clivar.org ). The CORA dataset has been developed by the Corio- ). erent issues with the data of eXpendable ) and the ocean forecasting system GODAE-OceanView ( ff http://www.myocean.eu Estimation of Global Ocean Indicators (GOIs, von Schuckmann and Le Traon, 2011) Correction of known instrumental bias was also a priority in developing a dataset The French program Coriolis is an element of operational oceanography at na- Quality control is very important both for re-analysis and research projects. A wide http://www.myocean.eu Willis et al., 2008; Barker et al., 2011). In this paper, GOIs are estimated using the such as the global OHCa or considerable the global challenge steric as seasensitive long-term level to (GSSL) trend any from estimations in-situ sensor of datathese drift global remains global or quantities quantities systematic are using instrumental very and the bias. sensitivity Any CORA3 studies attempt dataset asany to should we instrumental estimate include cannot drifts careful guaranty orpaper. comparison that bias. However ours These GOIs quality sensitivity estimatesa controls studies can global do are in-situ be not out dataset. alarge miss This of useful scale type the errors tool of due scope data to to of validation measurement monitor this tool drifts the and is systematic in quality instrumental particular of biases ideal (e.g., such to detect made or are in progressArgo in floats. each Data No Assembly supplementary CentreCORA3 data (DAC) dataset. responsible correction However, for simple have a diagnostics been partdata have of applied been quality to developed and to state asses of data the correction in Argo in the our dataset. correction applied to thein CORA3 Hamon dataset et issalinity al. an subsurface (2011). measurements application After became ofby 2004–2005 the the the autonomous the method Argo profiling dominant described models Program. floats source equipped Several deployed with of widespread FSI temperaturetute problems sensor and (WHOI), and (software deployed negative error by bias Woodsin for in Hole SOLO the APEX Oceanographic float past Insti- pressureWillis measurements) few et have years al., been 2007; and discovered Barker are et al., known 2011). to Corrections for impact these estimates data problems of have been the global OHC (e.g., such as CORAresearch as studies. the impact Di (XBTs) of exist such and, bias ifoceanic can not heat corrected, be content they (OHC) drasticallyIshii are variability important (e.g., and known Wij Kimoto for to 2009; climate contribute Gouretski to and anomalous Resghetti, global 2010; Lyman et al., 2010). The XBT oceanographic research purposesthe including international climate program change CLIVAR studies ( in the frame of tional and international level.fied and The integrated program ocean aims inysis situ to and measurements provide to forecasting regularly the systemEuropean French real-time operational GMES (Mercator quali- ocean (Global Ocean, anal- Monitoringvice for MyOcean Environment and ( Security)program Marine Coriolis Core Ser- contributes//www.argo.ucsd.edu to the global//www.godae-oceanview.org Argo array (Roemmich etlis Research al., and 2009, Development teamof to ocean target models validation, (Mercator initializationysis (Lellouche and et and assimilation al., Simulations 2012), GLORYS project, (Global Ferry Ocean et Reanal- al., 2010) and MyOcean) as well as general variety of quality control methods existsfully for automated in methods situ oceanographic (i.e. datasets Ingleby rangingprofile. and from Huddleston, The 2007) CORA to manual datasetto check is of the every re-qualified one withon presented a the in semiautomated whole Gronell methodand CORA and quite a dataset. Wij close model These background(Ferry include check et some al., based 2010). simple on Usingsuspicious tests, threshold the profiles values, climatological global that the are tests ocean statistical then tests reanalysis visually help GLORYS2V1 checked. to isolate a part of ( Le Traon, 2011; Souza et al.,data 2011; and Guinehut quick et updates al., 2012) ofof . the data Dealing required dataset with by required the research by quantity projects re-analysis of remains projects a and di the quality period 1990 to 2010, which is available on request through the MyOcean Service Desk 5 5 25 15 20 10 15 10 25 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ), ), data ) and as each scheme.shtml ) and delayed mode http://www.ego-network.org ), data from the Global Ocean ) program, data from voluntary ob- http://www.argo.ucsd.edu 1277 1278 http://www.vos.noaa.gov/vos ), data from gliders ( http://www.wmo.int http://www.gosud.org Finally, we present the perspective for the evolution of CORA http://www.oceansites.org In this paper we first introduce the CORA dataset by explaining its links with the telecommunication system (GTS, Surface Underway (GOSUD, point for allXCTD Argo data data. from Each French day and the some European Coriolis research data ships, centre data collects from XBT, the CTD global and serving and merchant shipsfrom (VOS, moorings (in particularprogram data TAO/TRITON/PIRATA from PMEL and OceanSites objective analysis is re-runafter once acquisition a and month therefore as are new not data statistically may arrive qualified more through than the 3 daily weeks analysis. The Coriolis data centre collectsthe data operational mainly oceanography in needs. realthe or Coriolis Argo near-real is time program a inDAC, (Roemmich order Data it et to Assembly is meet al., Centredecoding responsible 2009, (DAC) them for for and collectingalso qualifying the one and raw of distributing messages theIt the from two thus data. Global a The collects Data part Coriolis the Assembly of data Centres Argo centre Argo (GDACs) data is for floats, from the Argo the program. others DACs and serves as a distribution is attributed todata). each For measurement Argo floats (flag managedthe 1 by DAC other stands DACs are for than kept. Coriolis, goodavailable. A quality The data, flags statistical attributed statistical and analysis by testet flag is al., is 4 then 1976) performed for based with once bad Residuals on a between a three an the day weeks objective raw using window dataResiduals analysis all (see and larger method Gaillard the data than gridded et (Bretherton a fields al.,Control are defined 2009 quality computed value for flags by further produce are the details). alerts then analysis. changed that if are necessary. then The checked statistical visually. test based on the availability of inimportant situ to data know at howcentre. global the scale. data To is understand first the collected and content2.1 processed of by CORA the Data it collect Coriolis at is data the Coriolis Centre The Coriolis data centreCoriolis processes data centre the runs data a duplicate inEach check real measurement to ensure of and the the near-real data Coriolis isof time. database unique the Each in is the data day then database. (Coatanoan flagged the et toare al., inform first about 2005). going the All through quality automatic theand QC data most (Argo managed Quality of by Control the the Manual, Coriolis data Wong data et are centre al., checked 2012) visually. A control quality flag ranging from 0 to 9 within Coriolis and MyOceanII contexts. 2 From the Coriolis data centreThe to CORA the CORA dataset dataset correspondsity to profiles an during extraction thedatabase of period all at 1990 in a to situ giveninitial 2010 temperature time. requirement from and Beside to the salin- data ensure daily processing delivery up-dated and of real a validation time high-quality infrastructures, Coriolis CORA the dataset is an adequate of Natural History). ThreeSPP times files a week preparedhttp://www.meds-sdmm.dfo-mpo.gc.ca/isdm-gdsi/index-eng.html the by Coriolis the data centreCTD Canadian loads data Marine GTS are and EnvironmentalCTD regularly GT- data, Data uploaded Boyer et Service from al., (MEDS, 2009). the World Ocean2.2 Database (high Data resolution processing at the Coriolis data centre of the level of quality reached (or not) by theCoriolis CORA data database. centre (Sect.are 2). presented. In In Sect. Sect.including 3, the 4, use validation quality of procedures GOIs. diagnostics and are XBT performed corrections on the CORA data set, and data from sea mammals equipped with CTD by the MNHN (National Museum method introduced in von Schuckmann and Le Traon (2011) and used as a diagnostic 5 5 25 20 25 15 15 20 10 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | set. ff values are outside an acceptable http://www.coriolis.eu.org/Science/ S erent types of files (e.g. CT, OC, TE ff and T ). For the recent version of CORA (CORA3) cult for the user to find all the data from one 1280 1279 ffi erent types of instruments including mainly Argo ff ort has been made to identify the type of data among ff erent types of files (see the CORA documentation for more details). Information ff dataset. A profile fails a simple test for several reasons. This arises when a pressure value is CORA3 dataset not only contains the raw parameters such as temperature, salinity, CORA thus contains data from di The data are stored in 7 netcdf file types which include PF files (Argo data from the The Coriolis data centre does not perform delayed mode correction of the data re- negative (within instrument accuracy), when 3.1 Validation Quality control flagsfloats) attributed in by real the orvalidation Coriolis near procedures. data real Procedures Centre time forlogical (or CORA are tests validation kept other as include and DACs well simple arefloat for as over tests, the Argo all tests climato- it starting life designed point period.reanalysis for Finally of GLORYS2V1 Argo a (Ferry supplementary model et floats, background al., that check 2010) based consider is on applied. the each global suspicious ocean data, the adjusted parametersmethod present described in in Sect. CORA3 3.3. have been calculated following the 3 CORA data processing pressure or depth as receivedeters, from the i.e. instrument. temperature, It salinity, canThe pressure also include data or adjusted types depth param- concerned correcteddata, adjusted by from parameters these a are mainly adjustments drifttime salinity are or and in pressure Argo an an and floats o can automatedWong be and manner et adjusted XBT. in al., or For real 2012 in Argo forfor delayed more Argo mode data details). are For (see those the Argo received CORA3 at quality dataset, the control the global adjusted DAC manual, at parameters the date of the retrieval. For XBT type of instrument (e.g.files CTD) for as CTD it instruments), is anthe found e di in di on each data type, suchand as depth/pressure file is type given and Table the 1. nominal accuracy for temperature, salinity resolution. However, since it can be di array as downloaded each day fromThis PMEL), classification TE and of BA the files data (data received in from netcdf GTS). files depends mainly on the data sources and for the 1990–2008 period, 9the September 2010 year for 2010, the respectively. year 2009, and 22 March 2011 for floats, XBT, CTD and XCTD, moorings, sea mammal’s data, andnational some drifting assembly buoys. centres), XBCTD files data, (shipboard CTD XBTCTD data and or from XCTD XCTD), data), sea CT MO mammals files files and ( (shipboard data some from sea TAO/TRITON, RAMA Glider), and PIRATA OC files (WOD09 The CORA dataset correspondsity to profiles an from extraction thedetails of daily can all up-dated be in real found situData-and-Products/CORA-Documentation in time temperature the Coriolis and CORA database salin- documentation atwhich ( covers a the given time period time. 1990 More to 2010, the dates of data retrieval are 25 May 2010 float by comparing the observed valueWong, to 2003; neighbouring historical Boehme CTD et data al.,APEX (Owens floats), and 2005; the Owens pressure parameter et alsoall al., needs Argo 2009). adjustments (Barker For floats, et some raw al.,parameters Argo pressure, 2011). For are temperature floats stored and (mainly in salinity the as Coriolis well database. as2.3 adjusted (corrected) Data retrieval from the Coriolis database and organisation of the CORA necessary. Data that arrive withautomatic more procedures than a until month they enter delay will the only CORA be dataset. qualified through ceived, except for the French andIn this European case, Argo salinity floats is managed corrected by in delayed the mode Coriolis by DAC. the principal investigator (PI) of the New alerts are produced and visually checked. Control quality flags are changed if 5 5 20 25 15 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (1) ftp://ftp. erence between ff ) are verified sys- ort (Ferry et al., 2011), ff grid on the horizontal, the ◦ 5 × are equal to zero at the bottom ◦ S or T 1282 1281 and standard deviation STD. Those parameters climatological range. The climatology used is the M 2 ) σ values are constant at depth or if there is large salinity bias envelope in this area where the standard deviation is S − σ )) or z ( T global is part of MyOcean “Global Ocean clim ◦ T 4 − / ) z ( STD, (2) T ( × ( ) N values are outside the 10 z ( + being an empirical parameter. | 1 S 2 clim M N | or σ First, the collected innovations are binned on a 5 GLORYS2V1 1 To check the dataset as a whole, Argo floats pointed out several times by the previ- In the framework of MyOcean global ocean reanalyses e Each time a profile failed a test it is checked visually and control quality flags are then 1 = T = N z known as background quality control. model vertical grid, and thetwo season. parameters We which estimate are in the each mean are cell used of to the define 4-dimensional the grid following space and seasonT dependent threshold value: with reanalysis, observation minus modeltemperature background and (i.e. salinity innovation) profiles statisticsprofiles have for and in been to situ collected provideassume and a that used innovations black to have listbility a detect of density Gaussian suspicious observations function distribution contains present and suspicious that in observations. the CORA This tails observation data of screening base. the is We proba- a close collaboration withfrom the CORA data French base GLORYS additional reanalysis in(1993–2009) situ project global profiles ocean identified enabled reanalysis as to (Ferry suspicious et inas remove al., GLORYS2V1 an 2010). This additional stage step can inthe be the considered method quality used to control detect of those CORA suspicious data profiles. base. WePhysics describe Reanalysis hereafter and Referenceperature Simulations” and product salinity and assimilates profiles, in SST situ and tem- SLA observations. Based on this 17-yr long ous systematic tests and those pointedifremer.fr/ifremer/argo/etc/argo-ast9-item13-AltimeterComparison/ out by comparison to satellitetematically altimetry over ( all their lifeA detailed period description and of quality the control altimetry flags test are is modified given in if Guinehut necessary. et al. (2009). can be used as ais first a estimation necessary of step. the quality of an observation but that visual control changed if necessary. The visualit check allows is the a rejection very of important additionalit step observations also in that allows the have the passed procedure requalification through since first of the rejected tests example observations and shows into good anacceptable measurements. XBT The range test profile (Fig. than 2)should has but be been it rejected. This is partially is proved invalidatedthe done that example thanks as all on part to observations Fig. of bellow the the 3thermocline 350 visual m shows are check. that depth Unlike slightly a the outside few previousfew temperature the profile, observations observations have climatology been at test. considered the good During bottom which the shows of that visual the climatological process, envelope these field but it is applied inThe the salinity same way observations for the(WOA09) are salinity field. but about An example inside 0.5 psu is thelarge. given fresher on This 10 Fig. profile than 1. passes the all the climatological tests estimate and was only detected thanks to the bias test. when a systematic bias occurs.the The observed bias and is the calculated climatological by profile fitting and the by di minimizing: averaged climatological standard deviation. The equation is written for the temperature or at the surface, when gradient at the surface (moreif than 5 psu within 2annual dB). fields There of is also World a Oceanand test the Atlas range to 2009 is determine (Locarnini 10 times et the al., standard deviation. 2010; A Antonov profile et also fails al., a 2010) climatological test X The profile fails this test if the calculated bias is at least 3 times larger than the vertically- range, depending on depth and region, when 5 5 25 15 20 10 20 25 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | and ◦ longitude and latitude and 1 h when ◦ 1284 1283 | innovation | 0.5 erent (ex BA-XB pairs). The temporal criterion is extended up to 24 h > > T ff | | clim erent paths can be used to transmit the data from the sensor to the data- − ff innovation obs | | cult to evaluate. i. ii. The duplicate check looks for pairs within 0.1 The background quality control allowed identifying 2760 suspicious temperature and We represent in Fig. 5 the spatial distribution of suspicious temperature and salinity The results of this background quality control are summarized in Fig. 4 where the In a second stage, we perform the observation screening for each profile. At a given ffi The XBT system measuresthus inaccuracies the in time the fall elapsed rate equation since result the in depth probe errors. It entered has the been known water since and with highest vertical resolution.meta-data If available no or choice theduplicate still one is has excluded. that been Finally made, appears ifis the none more made of report about often those the with than suppression stepsin less of is the excluding one conclusive 1.5 other of % an the of in arbitrary two the decision the profiles. whole The list profiles duplicate in of 3.3 check CORA3. resulted XBT bias correction when TE-PF pairs are(ex looked TE-TE for. When pairs), it0.00001 both day). is temporal Then, looked it and is forFirst, chosen spatial pairs which there within report criterions is should the are a be samedecisive retained preference sharpened format the in for the (0.0001 preference report CORA is dataset. sion with given (i.e. both to GTS temperature formats the and – report salinity. TE If with and this BA the is – format are not allowing of highest lower precision), preci- then the deepest report 3.2 Check of duplicate profiles Identical profiles can because found di with several occurrencescentre. in A duplicate the check Coriolisthrough. is database A performed be- duplicate at check is Coriolis thus in performed real again time on but thetheir whole format some CORA is profiles dataset. di slide salinity profiles that were reportedprofiles to CORIOLIS have to then improve been CORA visuallybe data controlled base. bad All and quality these about profiles. 50di % The of other them half were confirmed were to false alarms or profiles whose quality is with defective sensors. An example ofanalysis suspicious can profiles be and found their in impact Lellouche on et an ocean al. (2012). ENSO event, more suspiciousPacific. salinity This profiles happens than until usualthat 2001 are the with detected threshold the in values strong defined thebecause for La Tropical the the Nina. statistics quality may This control not is salinityvariability. contain may attributed enough be to ENSO underestimated events the to fact fully sample the ocean profiles in 2009. Itis is almost expected the the case.Tropical profile Pacific We to or can be East note randomly distributed to at in the some space, place Philippines. which accumulation This points, corresponds in to the a Central moving Argo float percentage of suspicious temperatureof and the salinity year during profilesrelatively 1993–2009. is stable We displayed during expect the as this reanalysis a percentageprofiles, time of function period. with suspicious It little is profiles almost year to1999 the be and to case 2001. for year temperature A variability. more For detailed salinity, analysis one reveals that can following see the a strong 1997/1998 peak between The first criterion diagnosesdue if to the an innovation erroneous is(i.e. observations observation. abnormally that large Condition are close which (ii)ground. to is avoids the In most climatology) rejecting the in likely “good” the case(ii) case observations of of is a a small biased good model andsignificantly back- observation reduces r.h.s. the and is number a of large, biased good meaning observations model that that background, may condition be l.h.s rejected. is of not satisfied. This criterion depth, an observation is consideredfied: suspicious if the two following criterions are satis- 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | er ff S, even tough ◦ ). Profiles in XB square box (this ◦ set is not straightforward, as ff erent from 3 and 4 (suspicious ers from Hamon et al. (2011), ff ff erent instruments types are gathered in ff 1286 1285 of latitude and longitude and a temporal frame ◦ square box after the target of 3000 Argo floats has ◦ set (although the determination of this depth o C of vertically averaged ocean temperatures in the top 400 m. ◦ ff To compute the empirical correction of XBT data, weFor used each a XBT, we collocation selected method all CTD, Argo profiler, drifting buoys and mooring buoys As information on the XBT type is missing for a large part of XBT profiles in the reaches 3–4 profiles per yearbeen in met 1 by the end of 2007). Ice-covered or shallow-depth regions are less sampled Figure 6 shows global dataera coverage in for 1990–1999 two and periods thespread in period out CORA3 2000–2010 over dataset: during the the whichin pre-Argo Argo global 2005). profiles In ocean progressively the (those(mostly earlier XBTs). really Large period gaps start high are to seenthis coverage in cover is region the Southern the concentrated was Ocean, on near-global southgram relatively main of in ocean well 30 1990–1998. shipping During sampled lanes theprofiles during more ensures recent this a period period 2000–2010, minimum the owing coverage spreading to of of 1–2 Argo the profiles WOCE per pro- year in 1 4 CORA diagnostics 4.1 Data coverage profiles selected in the regionby of subtracting collocation. this The reference temperature profile biasof from profile the the XBT is profile calculated XBT is profile.puted deducted Then from from the this error the bias of andto reference immersion the situations profile. gradient with of We sea anshelf found temperature or XBT com- that the deployed continental several over slope. comparisonsfronts, Thus, the we to corresponded deep ensured avoid that potential ocean ocean biases andby depth resulting more where from CTD the than cross-shelf stations XBTs 1000 m have over been from the deployed where did CTDs not have di been deployed. between XBT and reference profiles withand quality bad flags quality). di geographically distant by lessless than than 2 15 days. Then, we computed a reference profile as the median of all those those files. XB files, we decideddepth not computed to with apply the thewhere old Hanawa the fall Hanawa (Hanawa correction rate et was equation. first al.,we applied This 1995) made when di possible. fall-rate for Thus, for the the XBT onlyfrom XBT correction in XB, the BA CORA3http://www.nodc.noaa.gov/GTSPP/document/codetbls/gtsppcode.html or dataset is TE statistical. files Chosenfiles with XBT with profiles an an come instrument unknownconsidered instrument type as type that XBT. and But referscannot no profiles to be salinity with an data qualified an XBT (to as unknown avoid probe XBT XCTD) instrument (see since are type many also in di BA or TE files data in several categories: shallowand XBTs, deep which XBTs are which predominantlytemperature T4/T6 are influence, instruments predominantly we T7above have or 10 also Deep separated Blue. To profiles take deployed into in account water the below or discussed by di Nezio andof Goni, the 2010). probe/wire The are weightKuleshov and (1982) known hydrodynamic for to characteristics example, strongly8.8 indicate m influence depth that the error a at fall 750of weight m. rate the The uncertainty statistical equation. correction method of applied Seaver described on 2for in and % CORA3 each Hamon dataset could year et is and al. induce an (2011). is application temperature This divided correction correction in based is on two calculated comparisons parts:rection in first the of the near the computation surface depth layer of and with a then a depth-independent a second cor- order polynomial function. We also separated XBT ical characteristics, with forof example sea a water dependency (Thadathilearly on on et viscosity/temperature/density that al., the assumption 2002;ticular of in Kizu a the et terminal surface velocity al.,a layer, might depth and, 2011). not o compounded be It with always has correct, time in also constant par- been issues, can suggested result in the early uses of the probes that the fall rate should depend on the sea water phys- 5 5 20 25 15 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | measurements. Bad temperature pro- T/S 1288 1287 Position flags are attributed mainly during real time tests performed at the Coriolis Figure 9 shows the percentage of profile in CORA dataset that have a bad quality Figure 8 shows the number of profiles in CORA3 divided by data type as a function The TAO/TRITON PIRATA and RAMA array imprint is also clearly visible on Fig. 7 Figure 7 shows the number of temperature and salinity profiles per month and at be note that TAO/TRITONreceived PIRATA and in real RAMA time data from PMEL in and the GTS. Therefore, CORA3 positions are dataset the are theoretical ones those position is on land2010, the or Coriolis at data seaand centre using the was a also depth 5-min usingHowever reached in bathymetry a case by comparison of (ETOPO5). steep the between Until bathymetrica profile variations the September flag the bathymetry to latter 4 test to determine can the erroneouslyin position. if attribute CORA3 As dataset the shown is in position highly Fig.profile variable was 5, with for the a good one percentage bad year of or position toof profiles is not. another. with TAO/TRITON close In moorings. bad 1999 to position At the 8 % percentage this in of the date dataset, we mainly have due no to wrong explanation positions about this. It should profile available is used, meaningdelayed that mode if (for temperature Argo or and salinity XBTflags have data) are been then taken corrected the into in adjusted account profile instead and of associated the quality raw profile. data centre. These tests check if the latitude and longitude are sensible and if the 4.2.1 Overview Part of the qualitycentre; the flags others were were set applied during during the validation the phase real offlag CORA. either time for tests the atfiles position, the have the more date Coriolis or than data or the 75 % bad of (quality temperature flagmeasurements measurement with 3 quality uncontrolled or flag (quality 4) equal flag and to 0, 0) bad 3 salinity or profiles 4. To have produce more these statistics than the 75 % best of salinity tions around the continental US,distributed Alaska, trough Hawaii, the and GTS. the Great Lakes. These data4.2 are Data quality and known data problems measurements from moored buoys and shore and platform-based coastal marine sta- from the NDBC (National Data Buoys Centre) and consist primarily of high frequency It can be noted that theCoriolis subsurface database salinity data and from in thesesubsurface CORA mooring salinity are before not before 2003 found this even in date. the if part of the buoysof have time. measured The numberconnected of into profile increases real afterin time 2001 the data as acquisition streams. Coriolis ofas It data TAO/TRITON PIRATA the data. centre can complete This has be time will been ter series noted be will 2004, corrected that be in the in made next importance 2000 available version by of there PMEL coastal is through moorings OceanSites. a Af- is gap growing up. These data are mainly was transmitting mainly subsurface temperatureor at about 750 m 10 levels depth. overATLAS the By buoys first (next the 500 m generation endsubsurface atlas salinity of data. mooring) First 2001 and buoys of the more the1997/1998, array PIRATA while full sites were RAMA deployed array array in were started the was also to Atlantic be in transmitting replaced deployed in with the Indian more Ocean in modern 2000/2001. CTD and often reach downsalinity 3000 profiles m reaching depth. down 2000 After mprogram, 2000, depth has the but gradually number at increased of owing the temperature tocantly same the and reduced. Argo time, Since the 2004–2005, Argo numbermeasurements data in of the is deeper CORA the CTD dataset. major profiles source of has global been subsurface and signifi- appears as several distinctBy well the sampled end depths of between 1994, the the surface Tropical and Atmosphere 750 Ocean m. (TAO) array was completed and of the North PacificEuropean Ocean, coasts. along Some the areas in USmammals the equipped and Southern with Canadian Ocean CTD east (first are coasts data also in and highly 2004). sampled the by westa sea of given depth in CORA3. Before the year 2000, salinity profiles are essentially from however. Highly sampled regions with more than 10 profiles a year are in the west side 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | set due to a software ff 1290 1289 cient surface pressure data or floats with Apf-8 ffi cient information, insu ffi However, among APEX floats, some of them are uncorrectable. This is the case for In early 2009, a problem with the Druck pressure sensor has been found. It revealed Figure 10 shows the percentage of Argo profiles that have a bad quality flag either For the CORA3 dataset, the adjusted parameters for Argo data are those received The percentage of bad temperature profiles ranges between 1–3 % while the per- Date flags are also attributed during the real time tests at the Coriolis data centre by or earlier controllers that set all negative surface pressure to zero. Truncated Negative et al., 2009). While PROVOR andAPEX SOLO are floats designed do to self-correct not anysures. pressure make In drift, any consequence, re-adjustment internal shouldmode pressure be to correction applied both all as in APEX they real-timefloats. floats return Most and by of delayed “raw” the using pres- DACs theAs started the surface to CORA3 pressure apply dataset such values was apressure extracted returned pressure in correction by 2010–2011, correction state the it during in is year APEX the important 2009. CORA3 to dataset. give an insightfloats of with insu unusable in the CORA3 dataset,the because temperature either are the flagged position, as the bad. date, the pressure or an increase in the occurrencefloats rate deployed of in floats 2007 exhibiting negative and surface later pressures from (3 % prior to 2007 and 25–35 % after 2007, Barker of Argo profiles with(mainly a SOLO floats bad with temperature FSInumber and CTD of sensor). a SOLO At bad the FSIerror, salinity beginning resulting floats comes of in were the from a found year significant SOLOtified 2007, to cold floats and a have bias large by a for the these pressurefloats end instruments. (39), o while of The the 2007, problem uncorrectable was floats correctionsments (165) iden- were flagged were put grey as listed on bad (i.e.was pressure the data). applied. measure- GDACs In Finally for CORA3 about some 87 dataset % of it of these has the been profiles from checked SOLO that floats the with greylist FSI sensors are in real time in an automated manner). for the position, therepresent date less or than the 1 T/S %profiles measurements. of with Argo the a profiles total bad with number date a of is bad Argo increasing position profiles. after The 2007 percentage reaching of up Argo 2 %. A large proportion float profiles are adjusted in pressure and/or salinity (63 % in delayed mode and 12 % at the global DAC at the date of the retrieval. In the CORA3 dataset about 75 % of Argo the GDACs ftp servers. Therefore, itCORA3 is dataset important reflects to the have state in ofat mind the the that, Argo for date database Argo of found data, on data the for the retrievals GDACs the (mid-2010 ftp for year servers data 2010). thatCORA3 These span (as 1990–2009 data and have described March beenway, 2011 in but re-qualified no Sect. supplementary during data 3.1) the correctionabout has validation to the been phase improve applied. Argo of Some the data simplehighly diagnostics data quality necessary. and quality state in of a corrections homogeneous in the CORA3 dataset are then 2004–2005 and thus Argo dataevolution became the of most the important global informationdata to ocean problems estimate state. have the been Since identified the andin corrections beginning each have DAC. of been As made the a ordata Argo consequence are acquired in the program progress some Argo several database years is agodata constantly as acquisition evolving some (1–2 even yr floats for can the in be average). reprocessed The long most time up-to-date after Argo the database is found on the year 1990, the percentage of profile with a badcentage date of is lower bad than2–8 salinity 1 % % profiles after. in CORA3. is lower than 24.2.2 % before 2003 Particular and case of ranges Argo between floats Argo floats are the main source of subsurface measurements in CORA3 dataset after some high frequency coastal moorings,to probably the because coast, they in are port located or estuary very close areas. checking if the date and timeprofiles are does sensitive not and if exceed the a platform maximum travel speed value between defined two for each platform type. Except for and not the measured ones. After 2005, profiles with bad position are mainly those from 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | et al., ff anomalies that T/S erences of the 6-yr trends remain ff ect) and hence change the ff 1292 1291 erent estimation periods, instrumental biases, ff cient information and surface pressure data). Among ffi erences in these global statistical analyses. These inconsis- ff ect of a warming climate on globally averaged sea level (Bindo ff 50 %). Changes in the storage of heat and in the distribution of ocean salinity > Using the CORA dataset to estimate GSSL needs careful comparison and sensitivity Several GSSL estimations based on Argo and/or other in situ observations have Figure 11 gives the state of corrections for APEX float profiles that are correctable in for CORA does not miss to much erroneous data. Di systematic instrumental bias. studies. However, GSSL from the2005–2010, CORA i.e. dataset a is time evaluatedglobal period here where Argo for global the observing time coverage array isvon period (Fig. Schuckmann guaranteed 12). and mainly The Le due method Traon toto (2011) to their the and results. evaluate In the GSSL their CORA is studyand GSSL they introduced re-qualified used time in the only series data the is Argo toThe compared data reach comparison from the shows the quality good Coriolis level data agreement, required centre meaning by that the the estimation validation of procedure GOIs. used quality control and processingthe reference issues, depth the for GSSL rolePurkey calculations of and (Leuliette and Johnson, salinity Miller, 2011; as 2009; Palmersullo, Trenberth, et well 2010; 2011). al., In as 2011; particular, the Meehl GSSLlong-term et influence from trend al., in of estimations situ 2011, of data Trenberth global and remains quantities Fa- a are considerable very challenge sensitive as to any sensor drift or shown that about 30–50 %(Cazenave of and global Llovel, sea 2010; level Church rise et can al., be 2011; explained Hansen by etbeen steric al., derived changes 2011). over the2009; past Leuliette couple and of Miller, years2010; 2009; (e.g., Church von et Willis Schuckmann al., et et 2011; al.,There al., Hansen 2008; are 2009; et al., Cazenave substantial Cazenave 2011; and et di vontencies Llovel, al., Schuckmann have and been Le Traon, mainly 2011). related to di well as considerable socioeconomic impactsareas for those ( who live in coastalcause and the low-lying ocean toboth expand regionally or and contract globally and (steric areof e as GSSL well linked contributes to to changes a in ocean large circulation. part Rise to global total . Recent studies have 2007). Rising sea levels have a broad range of implications for climate science as climate change as onechange of is the the most e alarming consequences of anthropogenic climate drift than in the GDAC Argoof data APEX set as profiles of still January need 2009. a However a pressure substantial correction. amount 4.3 Global ocean indicators Oceanic parameters from in situfor temperature analyzing and the salinity measurements physical state canapplications of be useful the in global the ocean multidisciplinary andestimation they field of have of a Global climate large Steric range research Sea of studies. Level vital (GSSL) In is particular, an the important aspect in the analysis of them, about 50 % arelast not case, corrected this (27 could %)more be probably or because because have the a the floatsalinity correction has float parameter. been equal The does processed geographical to not in repartition zero. delayedthe need of In mode Fig. the any but 5 the corrections only of pressure can for Barker correction be the et compared or al. to (2011). In CORA3, more profiles are corrected for a pressure details). Following theet method al., described 2012), in weprofiles) identified the in 100 955 the Argo CORA3 profiles quality dataset. withprofiles We control TNPD but did part (about manual not of 20 performed (Wong % them specificprevious of quality have tests: been all checks among for already APEX these flagged all floats bad as profiles either bad for we by pressure, identified the temperature PIs as or or salinity. TNPD, thanks about to 13 the CORA3 % (not are TNPD flagged and as with su pressure reads continuously zeroleast 6 without months. reverting In delayed back mode,and to the PSAL) float positive of PIs values TNPD areare during asked floats to consistent to at flag with 4 the when data increasinglyfloats (TEMP, float PRES negative to data pressure 2 show drift otherwise observable and (see the to Argo flag quality the control data manual, of Wong et TNPD al., 2012 for more Pressure Drift (TNPD) refers to the part of these floats’ time series from which surface 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erences. ff erences at interannual and lower ff ciency of our validation procedure cient information to help the user in ffi ffi er if they intend to use the database for ff ˜ no Southern Oscillation (ENSO) event in erent type of users to evaluate if the database 1294 1293 ff ´ ement de Boyer Montegut for useful discussions during the cient to allows di ffi The research leading to these results has received funding from the Eu- The use of GOIs such as GSSL to evaluate the quality of a global dataset is in- The delivery of a global database such as CORA should be accompanied by support- Background quality control based on the global ocean reanalysis GLORYS2V1 was improve, and finally fullysitu implement data this validation procedure. type of global oceanAcknowledgements. quality control inropean the Community’s Seventh in Framework Program218812 FP7/2007-2013 (MyOcean). under We grant agreement thankpreparation no Cl of th CORA dataset. teresting. In our casecompared this to allows the to onedoes check not used the exclude in that e vonther still Schuckmann sensitivity unknown and studies drifts on Le and/or GOI Traon biases estimations (2011). are need However, present this to in be the addressed data. in Fur- future studies to coverage of the European seasthematic assembly will centre be partners achieved and in SeaDataNetIIity partnership FP7 it project. with In appears MyOceanII term to in ofevaluating us data situ the qual- that state it of is correctionsdataset. for crucial In known this to instrumental paper deliver bias, we su mainlywhich drift focussed corrections or on are problems known made in bias or the ordata in problems re-processed progress. for in Argo Future delayed floats mode versions for by ofmoorings the CORA or originator will sea (e.g. include mammal’s TAO/TRITON PIRATA RAMA more data). ing documentation su can meet their own needsexample (those needs in can global di re-analysisoceanic projects, changes). to For study this amonitor purpose, specific data region quantity we and or developed coverage to a and monitor series data global of quality. In simple term diagnostics of to data quantity, a better in ocean reanalysis quality.especially These in the kinds framework of of MyOceanII feedback project. with modellers will be pursued Argo profiles processed in delayed modeif by an the PIs error were was generallyregions evident. not (e.g. modified Statistical except Southern tests Ocean) could or also for be certain ameliorated, type especially ofimplemented data in (e.g. some for coastal this moorings). versionquality of of in CORA. situ observation It datacentres bases. revealed It and as also operational highlighted a the forecasting powerful mutualimprovement centres benefits of tool can that delayed data to have time when observation improve data working the bases closely and together: consequently improvements time-consuming. However human intervention was found toavoid be rejecting highly to necessary much both good to dataamount or of leaving profiles some over gross the errors. global Whenwhereas ocean, checking a a it regional large can expert happen would that haveto let we do it flagged not as a good flag profile or as a vice-versa. bad profile Our as general bad rule was if we had some doubts. In the same way, quality flags of 5 Conclusion and perspectives This paper waslis intended database to (which presentcontrols) condition and the the the CORA3 data supplementaryCORA sources dataset, validation dataset. procedure This and its validation applied step real linkscious to relies profiles. and re-qualify on with The statistical the near-real suspicious the tests whole profiles time designedare Corio- are modified to quality if then isolate judged visually suspi- necessary. checked Anyto validation and deal system their is with quality perfect the flags and number it was of necessary suspicious profiles scrutinized as this can rapidly becomes time scales, especially during thethe strong year El Ni 2010, which(Fig. can 12, be red line). not Further explained studies by are additional needed in to fully situ understand data these other di than Argo in the error bar estimation. There are substantial di 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ce, ffi , 2009. ce, Washing- ffi , 2010. doi:10.5194/os-5-685-2009 , 2005. els S. E.: Pressure sensor drifts in Argo ff ort of MyOcean: description and early re- ff http://www.coriolis.eu.org/content/download/ http://www.mercator-ocean.fr/documents/lettre/ 1296 1295 ´ eon, L.: Coriolis Data Centre, In-situ data quality control , 2011. , 2010. doi:10.1146/annurev-marine-120308-081105 en.pdf ´ e, C., Levitus, S., Nojiri, Y., Shum, C. K., Talley, L. D., and Unnikrishnan, A.: Cli- ´ er 36 , N. L., Willebrand, J., Artale, V., Cazenave, A., Gregory, J., Gulev, S., Hanawa, K., ff satellite altimeter data in Argo quality control, J. Atmos.ture Ocean. Tech., and 26, salinity 395–402, fields 2009. (MyOcean derived Special from Issue), in submitted, 2012. situ and satellite observations, Ocean Sci. Discuss., and Storto, A.:sults, The EGU global Poster EGU2011-11250, ocean European GeosciencesVienna, reanalysis Union Austria, General e 3–8 Assembly April 2011, 2011. of large Argo datasets, J. Atmos. Ocean. Tech., 26, 337–351, 2009. cator global permitting oceantor reanalysis Quarterly GLORYS1V1: description Newsletter and 36, results, January Merca- 2010, Component of Multiple Observing Systems.Assimilation Ninth Systems Symposium for the on Atmosphere, Integratedcan , Observing Meteorological and and Society, Land 2005. Surface (IOAS-AOLS), Ameri- lettre 4918/36060/file/cordo-rap-04-047-quality-control.pdf gory, J. M.,Earth’s van sea level den and Broeke, energydoi:10.1029/2011GL048794 budgets M. from R., 1961 to Monaghan, 2008, A. Geophys. Res. J.,procedures, Lett., Ifremer 38, and report, L18601, 17 Velicogna, pp., available I.: at: Revisiting the 2, 145–173, Larnicol, G.: Sea level budgettry, over satellite 2003–2008: altimetry a and reevaluation Argo, from Global GRACE Planet. space Change, gravime- 65, 83–88, 2009. salinities in highly variable environments, Deep-Sea Res. Pt. II, 52, 651–664, 2005. oceanic experiments applied to Mode-73, Deep-Sea Res., 23, 559–582, 1976. Fedak, M.: Technical Note:oceanographic data Animal-borne collection, Ocean CTD-Satellite Sci., Relay 5, Data 685–695, Loggers for real-time Le Qu mate change 2007:Fourth The Assessment Physical Report Science ofSolomon, Basis, the S., Contribution Intergovernmental Qin, of Panel D.,Miller, Working on H. Manning, Group Climate L., M., Intergovernmental Change, 1 Panel Chen, edited to on by: Z., Climate the Change, Marquis, Camebridge, M., 385–342,Mishonov, A. 2007. Averyt, V., K. 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F.: The NWS Marine Observation Network: Coastal Marine Coatanoan, C. and Petit de la Vill Church, J. A., White, N. J., Konikow, L. F., Domingues, C. M., Cogley, J. G., Rignot, E., Gre- Cazenave, A. and Llovel, W.: Contemporary sea level rise,Cazenave, Annual A., Review Dominh, of K., Marine Guinehut, Science, S., Berthier, E., Llovel, W., Ramillien, G., Ablain, M., and Bohme, L. and Send, U.: Objective analyses of hydrographic data for referencing profiling float Bretherton, F., Davis, R., and Fandry, C.: A technique for objective analysis and design of Boehme, L., Lovell, P., Biuw, M., Roquet, F., Nicholson, J., Thorpe, S. E., Meredith, M. P., and Boyer, T. P., Antonov, J. I., Baranova, O. K., Garcia, H. E., Johnson, D. R., Locarnini, R. A., Bindo Barker, P. M., Dunn, J. R., Domingues C. M., and Wij Antonov, J. I., Seidov, D., Boyer, T. P., Locarnini, R. A., Mishonov, A. V., Garcia, H. E., Bara- The publication of this article is financed by CNRS-INSU. 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ATLAS 0.003–0.02 (Achieved 0.08 doi:10.1029/2011GL049359 ´ -S Climatology, J. Atmos. Ocean. Tech., 20, 308–318, 2003. egut, C., Cabanes, C., and Klein, P.:Estimation of the Agulhas over/sensors.shtml , 2008. Θ , 2008. erent data types found in CORA3. The type of netcdf files where ff , OC, XB, CT 0.02 , TE, BA, CT 0.001–0.005 , BA, TE 0.03–0.01 , TE 0.001–0.005 , TE 0.01 , MO, BA Standard ATLAS: , CT 0.01 , BA 0.002–0.01 , BA Nominal 1 XB OC BA, TE PF TE CT TE TE TE Accuracies for the di http://www.pmel.noaa.gov/tao/proj Data typeXBT Type of files TEMP accuracy Salinity accuracy PRESS/DEPTH CTD XCTD Argo Floats TAO/TRITON PIRATA/RAMA Glidders Sea mammals Drifting buoys Coastal and others moorings els, S. E., Willis, J., Domingues, C. M., Barker, P., White, N. J., Gronell, A., Ridg- ff trol manual, Version 2.7, 47341/2650/file/argo-quality-control-manual-V2.7.pdf pp., available at: profiling float salinity data by budget ondoi:10.1029/2007JC004517 seasonal to interannual timescales, J. Geophys. Res., 113, C06015, way, K.,their and impact Church,doi:10.1175/2008JCLI2290.1 on J. estimates A.: of Changing thermosteric expendableupper sea ocean”, bathythermograph Geophys. level Res. Lett., fall rise, 34, L16601, rates J. Climate, and 21, 5657–5672. during 2003–2008, J. Geophys. Res., 114, C09007, ring impacts on meridionalGeophys. heat Res. Lett., fluxes 38, and L21602, transport using ARGO floatsXBT and fall rate satellite in data, waters ofOcean. extreme temperature: Tech., 19, a 391–396, case study 2002. in the Antarctic Ocean, J. Atmos. mograph, J. Phys. Oceanogr., 12, 592–600, 1982. Boehme et al. (2009). For NDBC boys, Conlee and Moersdorf (2005). World Ocean database 2009, Boyer etJohnson al. (1995). (2009). See 4 5 1 2 3 Wong, A. L. S., Keeley, R., Carval, T., and the Argo Data Management Team: Argo quality con- Wong, A. L. S., Johnson, J. M., and Owens, W. B.: Delayed-mode calibration of autonomous ctd Table 1. Willis, J., Chambers, D., and Nerem, R.: Assessing the globally averaged sea level each data type can bedata found is received also from listed the (indecimal bold GTS point for are the for not most TESAC frequent (TE) full occurrences). type resolution: Note and that data one are place beyond truncated decimal two point places for beyond BATHY (BA) the type. Willis, J. K., Lyman, J. M., Johnson, G. C., and Gilson, J.: Correction to “Recent cooling of the Wij Trenberth, K. E. and Fasullo, J. T.: Tracking Earth’s energy, Science, 328, 316–317, 2010. Trenberth, K.: The ocean is warming, isn’t it?, Nature, 465, p. 304, 2010. von Schuckmann, K., Gaillard, F., and Le Traon, Global P.-Y.: hydrographic variability patterns Thadathil, P., Saran, A. K., Gopalakrishna, V. V., Vethamony, P., Araligidad, N., and Bailey, R.: Souza, J. M. A. C., de Boyer Mont Seaver, G. A. and Kuleshov, S.: Experimental and analytical error of the expendable bathyther- 5 25 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

1302 1301

Temperature profile partially invalidated because the temperature values are outside Profile that fails the bias test for the salinity observations. The in situ profile is in black, acceptable range (red dots). Visual check is needed to invalidate the other bad values. Fig. 2. Fig. 1. the climatology and its envelope in green. Red dots indicate observations extracted by the test. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | but requalified good after σ

1304 1303

Percentage of suspicious temperature (black) and salinity profiles (red) as a function of Profile that fails the climatology test, using an envelope at 10 Fig. 4. year. Fig. 3. visual check. Red dots indicate observations extracted by the test. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 12 150 150 10 100 100 8 50 50 6 0

0 1306 1305 boxes for the period 1990–1999 (upper panel) and ◦ 4 −50 −50 2 −100 −100 Number of profiles per year : Argo era 2000−2010 −150 −150 0

Number of profiles per year : Pre−Argo era 1990−1999 Number of profiles per year : Pre−Argo 0 0 50 50 −50 −50 Number of profiles per year in 1 Geographical location of suspicious temperature (top) and salinity (bottom) profiles di- 2000–2010 (lower panel) in CORA3 database. Fig. 6. agnosed in 2009 with GLORYS2V1 quality control. Fig. 5. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 4 4 2 1.5 1 0.5 0 2 1.5 1 0.5 0 x 10 x 10 2010 2008 2010 2010 2006 2004 2005 2005 2002 2000 1308 1307 2000 2000 1998 Number of profiles by data type Number of profiles PSAL Number of profiles TEMP Number of 1996 1995 1995 1994 unknow xbt ctd xctd floats TAO/Triton/pirata/Rama glidders sea mammals drifting buoys coastal and other moorings 1992 5 0 0 1990 1990

1990

1000 2000 1000 2000 x 10

all data types data all all data types data all 6 4 2 1 0 8 12 10 Number of stations divided by data type as a function of time. Number of profiles per month as a function of time at a given depth in CORA3. Fig. 8. Fig. 7. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 2010 2010 2010 2010 2005 2005 2005 2005 2000 2000 bad date 2000 2000 profiles with bad date 1995 profiles with bad salinity 1995 bad salinity data (all levels) 1990 1990 1995 1995 5 % 0 % 10 % 15 % 8 % 6 % 4 % 2 % 0 % 2 % 1 % 0 % 6 % 4 % 2 % 0 % 1.5 % 0.5 % 10 % 1310 1309 2010 2010 2010 2010 glidders drifting buoys sea mammals TAO/Triton/Pirata/Rama coastal and other moorings 2005 2005 2005 2005 Percentage of float profiles with bad quality flag 2000 2000 Percentage of profiles with a bad quality flag with a bad quality of profiles Percentage APEX ( with TNPD) SOLO ( with FSI sensor) PROVOR − ARVOR NINJA NEMO bad position 2000 2000 TAO/Triton/Pirata/Rama glidders sea mammals unknow xbt ctd xctd floats 1995 1995 profiles with bad position profiles with bad temperature bad temperature data (all levels) 1995 1990 1990 1995 6 % 4 % 2 % 0 % 0 % 1 % 8 % 6 % 4 % 2 % 0 % 4 % 3 % 2 % 1 % 0 % 0.8 % 0.6 % 0.4 % 0.2 % Percentage of the Argo profiles with a bad quality flag as a function of time. Percentage of the profiles with a bad quality flag in CORA3 as a function of time and Fig. 10. data type. Fig. 9. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | with with 1 1 − −

0.12 mm yr 0.14 mm yr ± ± 2010 2009 CORA3.2 alldata CORA3.2 Argo data only ARIVO 2008

1312 1311 STERIC HEIGHT 2007 for CORA3 with only Argo data) and 0.69 1 − 2006

0.10 mm yr

± 0

0.4 0.3 0.2 0.1 0.6 0.5

−0.4 −0.1 −0.2 −0.3 [cm] (top) Distribution of the pressure corrections for APEX floats profiles that are adjusted Estimation of GSSL for the year 2005–2010 with a 1500m reference depth. The calcu- Fig. 12. lation is based onResults a obtained simple box with averaging CORA3ARIVO method (red dataset described and (von in Schuckmann von greenCORA3 Scuckmann et curves) et al., (0.58 are al. 2011). compared (2011). TheARIVO. to 6-yr those trends obtained are with 0.64 (either in delayed mode or incorrections. real time) Most in CORA3 of and the (bottom)bias geographical are corrections repartition truncated of are these to forbe zero positive correctable for with bias Apf-8 the and of Apf-9 earlier version. the versions pressure of sensor controller. Negative as bias negative started to Fig. 11.