B-Argo profile 3.1 1.2 1950010100000020210524065021202604230758292902748 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 2 2 AAHZHZ0423_siobio003_306 0423_siobio003_306 2B 2B RRRRRRRARRRAP41305-17CH001 P41305-17CH001 V3.01 V3.01 841 841 11rs@rs@~jts=@~jts=@!b@!b@11GPS GPS A Primary sampling: averaged [] Secondary sampling: discrete [] ? ?@ `@33@ @ @ @ AA 0A PAffnÄA33A A A33A AA AffB B B B#B33+B3B;BffDBffLB TB[B dBfflBfftB |B B B B B̑B̕B B33B33B B B B33B33B̹B B33B33B33B B33B B B B B33B B B BB B B CfC CC C Cf C CC CC CfCC C C !C #C %C'C)C+C-C /C 1C 3C 5C 7C 9C;C =Cf>Cf@CfBC EC GCHCfJC MC OC QC SCUC WC YC [C ]C_Cf`CfbCfdCffC iC kCflCfnC qC sC uCwCyCf~C C3sC C CffC C C C͌C͌CfCfC͌C CC͌C C CC CffCffCYC C͌Cf D @DD9D
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B1919,909x09T"9i=94X9/9M/9"9F"9p/99!99ã.94!9˼9C 9> 9 9{ 9ye 99= 9 9 H939 93^9:9 00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000OGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOG OGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGPRES 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 = 0.1022, ZMaxFluo = 12, PRELIM_DARK_CHLA = [50,50,50,50,50], SCALE_CHLA = 0.0073, PHYSIO_RATIO = 2.2968 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 20260423075829 HZ HZ HZ HZ OGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOG rs@rs@