TY - JOUR
T1 - Observing System Simulation Experiments for an array of autonomous biogeochemical profiling floats in the Southern Ocean
AU - Kamenkovich, Igor
AU - Haza, Angelique
AU - Gray, Alison R.
AU - Dufour, Carolina O.
AU - Garraffo, Zulema
N1 - Funding Information:
We thank two anonymous reviewers for their valuable comments that helped to improve this paper. This work was sponsored by NSF’s Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project under the NSF Award PLR- 1425989, with additional support from NOAA and NASA. Igor Kamenkovich acknowledges the support by NOAA Climate Program Office, Climate Observation Division during the initial stages of this study. Alison Gray was supported by a NOAA Climate and Global Change Postdoctoral Fellowship. Carolina Dufour was supported by the National Aeronautics and Space Administration (NASA) under Award NNX14AL40G and by the Princeton Environmental Institute (PEI) Grand Challenge initiative. We are thankful to NRL/NAVO and HYCOM consortium for making their model output publicly available and Joe Metzger for his guidance and support in using these data. The real Argo float profile locations and times were downloaded from the Argo Global Data Assimilation Centre (doi:10.17882/42182). These data were collected and made freely available by the International Argo Program and the national programs that contribute to it. The Argo Program is part of the Global Ocean Observing System. SAF locations were downloaded from http://gcmd.nasa.gov/records/AADC_ southern_ocean_fronts.html. Model data used to produce figures in this study are available from doi:10.5072/ FK2TH8JZ3Z; additional data are available upon request from ikamenkovich@miami.edu.
Publisher Copyright:
© 2017. American Geophysical Union. All Rights Reserved.
PY - 2017/9
Y1 - 2017/9
N2 - This study uses Observing System Simulation Experiments (OSSEs) to examine the reconstruction of biogeochemical variables in the Southern Ocean from an array of autonomous profiling floats. In these OSSEs, designed to be relevant to the Southern Ocean Carbon and Climate Observation and Modeling (SOCCOM) project, the simulated floats move with oceanic currents and sample dissolved oxygen and inorganic carbon. The annual mean and seasonal cycle of these fields are then reconstructed and compared to the original model fields. The reconstruction skill is quantified with the reconstruction error (RErr), defined as the difference between the reconstructed and actual model fields, weighted by a local measure of the spatiotemporal variability. The square of the RErr is small (<0.5) for 150 floats in most of the domain, which is interpreted to mean that the reconstruction skill is high. An idealized analytical study demonstrates that the RErr depends on the magnitude of the seasonal cycle, spatial gradients, speed of float movement, amplitude of mesoscale variability, and number of floats. These factors explain a large part of the spatial variability in the RErr and can be used to predict the reconstruction skill of the SOCCOM array. Furthermore, our results demonstrate that an array size of 150 floats is a reasonable choice for reconstruction of surface properties and annual-mean 2000 m inventories, with the exception of the seasonal cycle in parts of the Indo-Atlantic, and that doubling this number to 300 results in a very modest increase in the reconstruction skill for dissolved oxygen.
AB - This study uses Observing System Simulation Experiments (OSSEs) to examine the reconstruction of biogeochemical variables in the Southern Ocean from an array of autonomous profiling floats. In these OSSEs, designed to be relevant to the Southern Ocean Carbon and Climate Observation and Modeling (SOCCOM) project, the simulated floats move with oceanic currents and sample dissolved oxygen and inorganic carbon. The annual mean and seasonal cycle of these fields are then reconstructed and compared to the original model fields. The reconstruction skill is quantified with the reconstruction error (RErr), defined as the difference between the reconstructed and actual model fields, weighted by a local measure of the spatiotemporal variability. The square of the RErr is small (<0.5) for 150 floats in most of the domain, which is interpreted to mean that the reconstruction skill is high. An idealized analytical study demonstrates that the RErr depends on the magnitude of the seasonal cycle, spatial gradients, speed of float movement, amplitude of mesoscale variability, and number of floats. These factors explain a large part of the spatial variability in the RErr and can be used to predict the reconstruction skill of the SOCCOM array. Furthermore, our results demonstrate that an array size of 150 floats is a reasonable choice for reconstruction of surface properties and annual-mean 2000 m inventories, with the exception of the seasonal cycle in parts of the Indo-Atlantic, and that doubling this number to 300 results in a very modest increase in the reconstruction skill for dissolved oxygen.
KW - OSSE
KW - SOCCOM array
KW - biogeochemical tracers
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U2 - 10.1002/2017JC012819
DO - 10.1002/2017JC012819
M3 - Article
AN - SCOPUS:85030175062
VL - 122
SP - 7595
EP - 7611
JO - Journal of Geophysical Research: Oceans
JF - Journal of Geophysical Research: Oceans
SN - 2169-9291
IS - 9
ER -