B-Argo profile 3.1 1.2 1950010100000020210216160013202604230757012902748 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_283 0423_siobio003_283 2B 2B RRRRRRRARRRAP41305-17CH001 P41305-17CH001 V3.01 V3.01 841 841 11`/^@`/^@(\=@(\=@F b@F b@11GPS GPS A Primary sampling: averaged [] Secondary sampling: discrete [] ̽ ? ? @Y@ @̬@ @33@ A Aff.AffNAffnA33A A A̸A33A33A33A33AB BB B $Bff,B4B g>t$>H>H>t$>g>>Ϊ>H>H>>Z>t$>g>g>t$>t$>H>t$>t$>g>H>H>t$>t$>H>H>g>H>Ϊ>g>H>>Z>H>g>Z>Ϊ>>g>g>H>Ϊ>g>Z>>]>>4>Qk>?C ?( ?_???J
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':"9פ:F:#9,9,9,9Wb9o9T9+G9 9T9v 99r9D69F,9N,9ÿ,9,9,9:9#mG99y,9 S 99qT9|9,9,9,,9O 99 :9M 9,9^G95\G9 YG9Z,9,9R99}9LG9,9}0 9=u9i9, 9ОT999( 99?& 9Ł,9# 9,9T9 99Jo9Ⱦ9 99^9b 9[9 9o,9 9il,9c9i,9A 9
9he,9 9 9G9y 9L 9 9G[,9Z,99b@9 93G9S,9 9FP,9.O,9HN,9 o9bT9G9I,9 9 9 G995D,9N9ޝ99u?,9=,9@99 9i 9993 9q 999 9P 9 9Ɉ99*,9En9F9 k9a9h~99Մ9 9I|9d1T9Ra9F9+T9*_99F9+9ȕ9-`9rF9=+9`9+9!E9Az9R9p79D9 D9)9 C9$=9K69'C9lC9m9B959{'9Z}49c49 A9GA9398&9%9@9|P29
Z99#$9h9G%Y9v#9Hs9d9=9B 09/9k/9ŀ/9<9ֈ<9[.9ij!9E!9c9 9 992V;9CC;99-9fY 9;9:9E1:o-9 9;-9<4U9-8 00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000OGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOG OGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGPRES 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 = 2.2968 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 20260423075701 HZ HZ HZ HZ OGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOGOG `/^@`/^@