@B-Argo profile 3.1 1.2 1950010100000020190715200006202604230746572902748 2902748 PROVOR PROVOR CHINA ARGO PROJECT CHINA ARGO PROJECT FEI CHAI FEI CHAI PRES FLUORESCENCE_CHLA CHLA BETA_BACKSCATTERING700 BBP700 PRES FLUORESCENCE_CHLA CHLA BETA_BACKSCATTERING700 BBP700 | | AAHZHZ0423_siobio003_124 0423_siobio003_124 2B 2B RRRRRRRARRRAP41305-17CH001 P41305-17CH001 V3.01 V3.01 841 841 11e@e@uV>@uV>@nb@nb@11GPS GPS A Primary sampling: averaged [] Secondary sampling: discrete [] ? ? @Y@̌@̬@ @ @ AffA 0AQA pA A ĄA A33A A33A A Bff B Bff B $B ,B 4B C3?Cf@C BCLCCffDCffEC3FC HC33IC JC3KCLC33NC OC3PC RCLSCffTC3UC WC33XC YCZCf[C]C ^C_C aCLbCffcCdCfeC gCLhC iCjCfkCLmCffnC3oC qCrCffsC3tCuCwCffxC yCzC|C33}C ~CfC Cf&CفCffCC CYC3C CمC @C3C C3sC3CLC C @CCC͌C3C3sC3CLČCLC3C33C3Cf&CfCf&CCCfC CCf&CfC33C3Cf&C3C33CfC33C̗C @C̘CLC CLCfCffC C͌C C͌CCC33C3Cf&C CLC̡CLC̢C33C CLC C @C C33C C @CCCfC C C3CffC٪CYC̯C3sCf&C3CLC C C C3C3CYC3C3C3CCfC3D3DfDf
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!9dq9c9m9q9!G~9!~9`9jp9E9[p9bb9)9r}9Ub9yb9U9WT9T9aT9 9:9 000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000OGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOG OGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGPRES FLUORESCENCE_CHLA CHLA BETA_BACKSCATTERING700 BBP700 PRES FLUORESCENCE_CHLA CHLA BETA_BACKSCATTERING700 BBP700 Adjusted values are provided in the core profile file none none none none none none CHLA_ADJUSTED = CHLA_NPQ for PRES in [0,ZMaxFluo], CHLA_ADJUSTED = ((FLUORESCENCE_CHLA-MEDIAN(PRELIM_DARK_CHLA))*SCALE_CHLA)/PHYSIO_RATIO otherwise none none none none none none none none none CHLA_NPQ = [], ZMaxFluo = [], PRELIM_DARK_CHLA = [50,50,50,50,50], SCALE_CHLA = 0.0073, PHYSIO_RATIO = 2.2334 none none none none none none none none none CHLA real time adjustment (specified in http://dx.doi.org/10.13155/35385 and computed with MLD_LIMIT = 0.03, and following recommendations of Roesler et al., 2017 (https://doi.org/10.1002/lom3.10185)) none none 20260423074657 HZ HZ HZ HZ OGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOG e@e@