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  • Biogeochemical data assimilation  (1)
  • Phytoplankton functional groups  (1)
  • Salinity  (1)
  • Tropical Pacific Ocean (15°N to 15°S and 125°E to 95°W)
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  • 1
    Publication Date: 2022-05-25
    Description: Author Posting. © Elsevier B.V., 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Marine Systems 76 (2009): 113-133, doi:10.1016/j.jmarsys.2008.05.010.
    Description: Depth-integrated primary productivity (PP) estimates obtained from satellite ocean color based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BOGCMs) represent a key resource for biogeochemical and ecological studies at global as well as regional scales. Calibration and validation of these PP models are not straightforward, however, and comparative studies show large differences between model estimates. The goal of this paper is to compare PP estimates obtained from 30 different models (21 SatPPMs and 9 BOGCMs) to a tropical Pacific PP database consisting of ~1000 14C measurements spanning more than a decade (1983- 1996). Primary findings include: skill varied significantly between models, but performance was not a function of model complexity or type (i.e. SatPPM vs. BOGCM); nearly all models underestimated the observed variance of PP, specifically yielding too few low PP (〈 0.2 gC m-2d-2) values; more than half of the total root-mean-squared model-data differences associated with the satellite-based PP models might be accounted for by uncertainties in the input variables and/or the PP data; and the tropical Pacific database captures a broad scale shift from low biomass-normalized productivity in the 1980s to higher biomass-normalized productivity in the 1990s, which was not successfully captured by any of the models. This latter result suggests that interdecadal and global changes will be a significant challenge for both SatPPMs and BOGCMs. Finally, average root-mean-squared differences between in situ PP data on the equator at 140°W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison six years ago. The success of these types of comparison exercises is illustrated by the continual modification and improvement of the participating models and the resulting increase in model skill.
    Description: This research was supported by a grant from the National Aeronautics and Space Agency Ocean Biology and Biogeochemistry program (NNG06GA03G), as well as by numerous other grants to the various participating investigators
    Keywords: Primary production ; Modeling ; Remote sensing ; Satellite ocean color ; Statistical analysis ; Tropical Pacific Ocean (15°N to 15°S and 125°E to 95°W)
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
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  • 2
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Roemmich, D., Alford, M. H., Claustre, H., Johnson, K., King, B., Moum, J., Oke, P., Owens, W. B., Pouliquen, S., Purkey, S., Scanderbeg, M., Suga, T., Wijffels, S., Zilberman, N., Bakker, D., Baringer, M., Belbeoch, M., Bittig, H. C., Boss, E., Calil, P., Carse, F., Carval, T., Chai, F., Conchubhair, D. O., d'Ortenzio, F., Dall'Olmo, G., Desbruyeres, D., Fennel, K., Fer, I., Ferrari, R., Forget, G., Freeland, H., Fujiki, T., Gehlen, M., Greenan, B., Hallberg, R., Hibiya, T., Hosoda, S., Jayne, S., Jochum, M., Johnson, G. C., Kang, K., Kolodziejczyk, N., Kortzinger, A., Le Traon, P., Lenn, Y., Maze, G., Mork, K. A., Morris, T., Nagai, T., Nash, J., Garabato, A. N., Olsen, A., Pattabhi, R. R., Prakash, S., Riser, S., Schmechtig, C., Schmid, C., Shroyer, E., Sterl, A., Sutton, P., Talley, L., Tanhua, T., Thierry, V., Thomalla, S., Toole, J., Troisi, A., Trull, T. W., Turton, J., Velez-Belchi, P. J., Walczowski, W., Wang, H., Wanninkhof, R., Waterhouse, A. F., Waterman, S., Watson, A., Wilson, C., Wong, A. P. S., Xu, J., & Yasuda, I. On the future of Argo: A global, full-depth, multi-disciplinary array. Frontiers in Marine Science, 6, (2019): 439, doi:10.3389/fmars.2019.00439.
    Description: The Argo Program has been implemented and sustained for almost two decades, as a global array of about 4000 profiling floats. Argo provides continuous observations of ocean temperature and salinity versus pressure, from the sea surface to 2000 dbar. The successful installation of the Argo array and its innovative data management system arose opportunistically from the combination of great scientific need and technological innovation. Through the data system, Argo provides fundamental physical observations with broad societally-valuable applications, built on the cost-efficient and robust technologies of autonomous profiling floats. Following recent advances in platform and sensor technologies, even greater opportunity exists now than 20 years ago to (i) improve Argo’s global coverage and value beyond the original design, (ii) extend Argo to span the full ocean depth, (iii) add biogeochemical sensors for improved understanding of oceanic cycles of carbon, nutrients, and ecosystems, and (iv) consider experimental sensors that might be included in the future, for example to document the spatial and temporal patterns of ocean mixing. For Core Argo and each of these enhancements, the past, present, and future progression along a path from experimental deployments to regional pilot arrays to global implementation is described. The objective is to create a fully global, top-to-bottom, dynamically complete, and multidisciplinary Argo Program that will integrate seamlessly with satellite and with other in situ elements of the Global Ocean Observing System (Legler et al., 2015). The integrated system will deliver operational reanalysis and forecasting capability, and assessment of the state and variability of the climate system with respect to physical, biogeochemical, and ecosystems parameters. It will enable basic research of unprecedented breadth and magnitude, and a wealth of ocean-education and outreach opportunities.
    Description: DR, MS, and NZ were supported by the US Argo Program through the NOAA Grant NA15OAR4320071 (CIMEC). WO, SJ, and SWi were supported by the US Argo Program through the NOAA Grant NA14OAR4320158 (CINAR). EuroArgo scientists were supported by the two grants: (1) AtlantOS funding by the European Union’s Horizon 2020 Research and Innovation Programme under the Grant Agreement No. 633211 and (2) Monitoring the Oceans and Climate Change with Argo (MOCCA) Co-funded by the European Maritime and Fisheries Fund (EMFF) Project No. SI2.709624. This manuscript represents a contribution to the following research projects for HC, CaS, and FD: remOcean (funded by the European Research Council, grant 246777), NAOS (funded by the Agence Nationale de la Recherche in the frame of the French “Equipement d’avenir” program, grant ANR J11R107-F), AtlantOS (funded by the European Union’s Horizon 2020 Research and Innovation Programme, grant 2014-633211), and the BGC-Argo project funded by the CNES. DB was funded by the EU RINGO project (730944 H2020-INFRADEV-2016-1). RF was supported by the AGS-1835576. GCJ was supported by the Global Ocean Monitoring and Observing Program, National Oceanic and Atmospheric Administration (NOAA), U.S., and the Department of Commerce and NOAA Research. LT was funded under the SOCCOM Grant No. NSF PLR-1425989. VT’s contribution was supported by the French National Research Agency (ANR) through the EQUIPEX NAOS (Novel Argo Observing System) under the reference ANR-10-EQPX-40 and by the European H2020 Research and Innovation Programme through the AtlantOS project under the reference 633211. WW was supported by the Argo Poland program through the Ministry of Sciences and Higher Education Grant No. DIR/WK/2016/12. AmW was funded by the NSF-OCE1434722. K-RK is funded by the National Institute of Meteorological Sciences’ Research and Development Program “Development of Marine Meteorology Monitoring and Next-generation Ocean Forecasting System” under the grant KMA2018-00421. CSchmid is funded by NOAA/AOML and the US Argo Program through NOAA/OOMD. MBa is funded by NOAA/AOML.
    Keywords: Argo ; Floats ; Global ; Ocean ; Warming ; Circulation ; Temperature ; Salinity
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C08001, doi:10.1029/2006JC003852.
    Description: Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.
    Description: This research was supported by the U.S. National Science Foundation through the JGOFS Synthesis and Modeling Project (OCE-0097285) and the National Aeronautics and Space Agency (NAG5-11259 and NNG05GO04G), as well as numerous other grants to the various investigators who participated.
    Keywords: Ecosystem model comparison ; Biogeochemical data assimilation ; Phytoplankton functional groups
    Repository Name: Woods Hole Open Access Server
    Type: Article
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