FN Archimer Export Format
PT J
TI Quantifying observational errors in Biogeochemical‐Argo oxygen, nitrate and chlorophyll a concentrations
BT 
AF MIGNOT, A
   D'ORTENZIO, F
   TAILLANDIER, V
   COSSARINI, G
   SALON, S
AS 1:1;2:1;3:1;4:2;5:2;
FF 1:;2:;3:;4:;5:;
C1 Sorbonne Universités, UPMC Univ. Paris 06, CNRS, UMR 7093, Laboratoire d’Océanographie de Villefranche (LOV), 181 Chemin du Lazaret, 06230 Villefranche-sur-mer, France.
   Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Borgo Grotta Gigante 42/c, 34010 Sgonico (TS), Italy
C2 UNIV PARIS 06, FRANCE
   INGV, ITALY
IF 4.497
TC 17
UR https://archimer.ifremer.fr/doc/00486/59745/62845.pdf
   https://archimer.ifremer.fr/doc/00486/59745/62846.pdf
LA English
DT Article
CR BIO-ARGO-MED-2015
BO Téthys II
AB BGC‐Argo floats observations are becoming a major data source for assimilation into and constraining of ocean biogeochemical models. An important prerequisite for a successful synthesis between models and observations is the characterization of the observational errors in BGC‐Argo float data. The root‐mean‐squared error, multiplicative and additive biases in quality‐controlled data sets of oxygen, nitrate and chlorophyll a concentrations collected with 17 BGC‐Argo floats in the Mediterranean Sea between 2013 and 2017 are assessed using the triple collocation analysis. The analysis suggests that BGC‐Argo float oxygen, nitrate and chlorophyll a data suffer from an additive bias of 2.9± 5.5 μmol kg‐1, 0.46± 0.07 μmol kg‐1 and ‐0.06 ± 0.02 mg m‐3, respectively. The root‐mean‐squared error is evaluated at 5.1 ± 0.8 μmol kg‐1, 0.25 ± 0.07 μmol kg‐1 and 0.03 ± 0.01 mg m‐3. Additional studies should determine whether these values are applicable to the global ocean. Plain Language Summary The Biogeochemical‐Argo program is a network of ocean robots whose sensors monitor, oxygen, nitrate and chlorophyll a concentration, information which is needed to detect decadal changes in biological carbon production, ocean acidification, ocean carbon uptake, and hypoxia in the world ocean. One of the goals of the Biogeochemical‐Argo program is to incorporate these observations into ocean models to understand and forecast the changing state of the carbon cycle. The successful integration of the float data into numerical models, however, requires the specification of the observational errors. This study provides, for the first time, the biases and errors of the three cores variables of the BGC‐Argo floats network: oxygen, nitrate and chlorophyll a concentrations. 
PY 2019
PD APR
SO Geophysical Research Letters
SN 0094-8276
PU American Geophysical Union
VL 46
IS 8
UT 000467949200029
BP 4330
EP 4337
DI 10.1029/2018GL080541
ID 59745
ER

EF