Abstract
Abstract. A set of observing system simulation experiments was performed.
This assessed the impact on global ocean biogeochemical reanalyses of assimilating chlorophyll from remotely sensed ocean colour and in situ observations of chlorophyll, nitrate, oxygen, and pH from a proposed array of Biogeochemical-Argo (BGC-Argo) floats.
Two potential BGC-Argo array distributions were tested: one for which biogeochemical sensors are placed on all current Argo floats and one for which biogeochemical sensors are placed on a quarter of current Argo floats.
Assimilating BGC-Argo data greatly improved model results throughout the water column.
This included surface partial pressure of carbon dioxide (pCO2), which is an important output of reanalyses.
In terms of surface chlorophyll, assimilating ocean colour effectively constrained the model, with BGC-Argo providing no added benefit at the global scale.
The vertical distribution of chlorophyll was improved by assimilating BGC-Argo data.
Both BGC-Argo array distributions gave benefits, with greater improvements seen with more observations.
From the point of view of ocean reanalysis, it is recommended to proceed with development of BGC-Argo as a priority.
The proposed array of 1000 floats will lead to clear improvements in reanalyses, with a larger array likely to bring further benefits.
The ocean colour satellite observing system should also be maintained, as ocean colour and BGC-Argo will provide complementary benefits.
Subject
Earth-Surface Processes,Ecology, Evolution, Behavior and Systematics
Reference107 articles.
1. Altieri, A. H. and Gedan, K. B.: Climate change and dead zones, Glob. Change Biol., 21, 1395–1406, https://doi.org/10.1111/gcb.12754,
2015. a
2. Anderson, L. A., Robinson, A. R., and Lozano, C. J.: Physical and biological
modeling in the Gulf Stream region: I. Data assimilation methodology, Deep-Sea Res. Pt. I, 47, 1787–1827,
https://doi.org/10.1016/S0967-0637(00)00019-4,
2000. a
3. Argo: Argo float data and metadata from Global Data Assembly Centre (Argo
GDAC), https://doi.org/10.17882/42182, 2000. a
4. Arnold, C. P. and Dey, C. H.: Observing-Systems Simulation Experiments: Past,
Present, and Future, B. Am. Meteorol. Soc., 67,
687–695, https://doi.org/10.1175/1520-0477(1986)067<0687:OSSEPP>2.0.CO;2,
1986. a, b
5. Bannister, R. N.: A review of forecast error covariance statistics in
atmospheric variational data assimilation. I: Characteristics and
measurements of forecast error covariances, Q. J. Roy. Meteor. Soc., 134, 1951–1970, https://doi.org/10.1002/qj.339,
2008. a
Cited by
15 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献