Kelly, T. B., Goericke, R., Kahru, M., Song, H., & Stukel, M. R. (2018). CCE II: Spatial and interannual variability in export efficiency and the biological pump in an eastern boundary current upwelling system with substantial lateral advection. Deep Sea Research Part I: Oceanographic Research Papers, 140, 14–25.
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Armstrong, E. M., Bourassa, M. A., Cram, T., Elya, J. L., Greguska, F. R., III, Huang, T., et al. (2018). An information technology foundation for fostering interdisciplinary oceanographic research and analysis. In American Geophysical Union (Vol. Fall Meeting).
Abstract: Before complex analysis of oceanographic or any earth science data can occur, it must be placed in the proper domain of computing and software resources. In the past this was nearly always the scientist's personal computer or institutional computer servers. The problem with this approach is that it is necessary to bring the data products directly to these compute resources leading to large data transfers and storage requirements especially for high volume satellite or model datasets. In this presentation we will present a new technological solution under development and implementation at the NASA Jet Propulsion Laboratory for conducting oceanographic and related research based on satellite data and other sources. Fundamentally, our approach for satellite resources is to tile (partition) the data inputs into cloud-optimized and computation friendly databases that allow distributed computing resources to perform on demand and server-side computation and data analytics. This technology, known as NEXUS, has already been implemented in several existing NASA data portals to support oceanographic, sea-level, and gravity data time series analysis with capabilities to output time-average maps, correlation maps, Hovmöller plots, climatological averages and more. A further extension of this technology will integrate ocean in situ observations, event-based data discovery (e.g., natural disasters), data quality screening and additional capabilities. This particular activity is an open source project known as the Apache Science Data Analytics Platform (SDAP) (https://sdap.apache.org), and colloquially as OceanWorks, and is funded by the NASA AIST program. It harmonizes data, tools and computational resources for the researcher allowing them to focus on research results and hypothesis testing, and not be concerned with security, data preparation and management. We will present a few oceanographic and interdisciplinary use cases demonstrating the capabilities for characterizing regional sea-level rise, sea surface temperature anomalies, and ocean hurricane responses.
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Hoffman, R. N., Privé, N., & Bourassa, M. (2017). Comments on “Reanalyses and Observations: What's the Difference?”. Bull. Amer. Meteor. Soc., 98(11), 2455–2459.
Abstract: Are there important differences between reanalysis data and familiar observations and measurements? If so, what are they? This essay evaluates four possible answers that relate to: the role of inference, reliance on forecasts, the need to solve an ill-posed inverse problem, and understanding of errors and uncertainties. The last of these is argued to be most significant. The importance of characterizing uncertainties associated with results—whether those results are observations or measurements, analyses or reanalyses, or forecasts—is emphasized.
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Kelly, T. B., Goericke, R., Kahru, M., Song, H., & Stukel, M. R. (2018). CCE II: Spatial and interannual variability in export efficiency and the biological pump in an eastern boundary current upwelling system with substantial lateral advection. Deep Sea Research Part I: Oceanographic Research Papers, 140, 14–25.
Abstract: Estimating interannual variability in carbon export is a key goal of many marine biogeochemical studies. However, due to variations in export mechanisms between regions, generalized models used to estimate global patterns in export often fail when used for intra-regional analysis. We present here a region-specific model of export production for the California Current Ecosystem (CCE) parameterized using intensive Lagrangian process studies conducted during El Niño-Southern Oscillation (ENSO) warm and neutral phases by the CCE Long-Term Ecological Research (LTER) program. We find that, contrary to expectations from prominent global algorithms, export efficiency (e-ratio = export / primary productivity) is positively correlated with temperature and negatively correlated with net primary productivity (NPP). We attribute these results to the substantial horizontal advection found within the region, and verify this assumption by using a Lagrangian particle tracking model to estimate water mass age. We further suggest that sinking particles in the CCE are comprised of a recently-produced, rapidly-sinking component (likely mesozooplankton fecal pellets) and a longer-lived, slowly-sinking component that is likely advected long distances prior to export. We determine a new algorithm for estimating particle export in the CCE from NPP (Export = 0.08 · NPP + 72 mg C m-2 d-1). We apply this algorithm to a two-decade long time series of NPP in the CCE to estimate spatial and interannual variability across multiple ENSO phases. Reduced export during the warm anomaly of 2014-2015 and El Niño 2015-2016 resulted primarily from decreased export in the coastal upwelling region of the CCE; the oligotrophic offshore region exhibited comparatively low seasonal and interannual variability in flux. The model resolves intra-regional patterns of in situ export measurements, and provides a valuable contrast to global export models.
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Stukel, M. R., Décima, M., Landry, M. R., & Selph, K. E. (2018). Nitrogen and isotope flows through the Costa Rica Dome upwelling ecosystem: The crucial mesozooplankton role in export flux. Global Biogeochemical Cycles, 32(12), 1815–1832.
Abstract: The Costa Rica Dome (CRD) is an open-ocean upwelling ecosystem, with high biomasses of picophytoplankton (especially Synechococcus), mesozooplankton, and higher trophic levels. To elucidate the food web pathways supporting the trophic structure and carbon export in this unique ecosystem, we used Markov Chain Monte Carlo techniques to assimilate data from four independent realizations of δ15N and planktonic rate measurements from the CRD into steady state, multicompartment ecosystem box models (linear inverse models). Model results present well-constrained snapshots of ecosystem nitrogen and stable isotope fluxes. New production is supported by upwelled nitrate, not nitrogen fixation. Protistivory (rather than herbivory) was the most important feeding mode for mesozooplankton, which rely heavily on microzooplankton prey. Mesozooplankton play a central role in vertical nitrogen export, primarily through active transport of nitrogen consumed in the surface layer and excreted at depth, which comprised an average 36-46% of total export. Detritus or aggregate feeding is also an important mode of resource acquisition by mesozooplankton and regeneration of nutrients within the euphotic zone. As a consequence, the ratio of passively sinking particle export to phytoplankton production is very low in the CRD. Comparisons to similar models constrained with data from the nearby equatorial Pacific demonstrate that the dominant role of vertical migrators to the biological pump is a unique feature of the CRD. However, both regions show efficient nitrogen transfer from mesozooplankton to higher trophic levels (as expected for regions with large fish, cetacean, and seabird populations) despite the dominance of protists as major grazers of phytoplankton.
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