949 resultados para global ocean economy
Resumo:
A set of four eddy-permitting global ocean reanalyses produced in the framework of the MyOcean project have been compared over the altimetry period 1993–2011. The main differences among the reanalyses used here come from the data assimilation scheme implemented to control the ocean state by inserting reprocessed observations of sea surface temperature (SST), in situ temperature and salinity profiles, sea level anomaly and sea-ice concentration. A first objective of this work includes assessing the interannual variability and trends for a series of parameters, usually considered in the community as essential ocean variables: SST, sea surface salinity, temperature and salinity averaged over meaningful layers of the water column, sea level, transports across pre-defined sections, and sea ice parameters. The eddy-permitting nature of the global reanalyses allows also to estimate eddy kinetic energy. The results show that in general there is a good consistency between the different reanalyses. An intercomparison against experiments without data assimilation was done during the MyOcean project and we conclude that data assimilation is crucial for correctly simulating some quantities such as regional trends of sea level as well as the eddy kinetic energy. A second objective is to show that the ensemble mean of reanalyses can be evaluated as one single system regarding its reliability in reproducing the climate signals, where both variability and uncertainties are assessed through the ensemble spread and signal-to-noise ratio. The main advantage of having access to several reanalyses differing in the way data assimilation is performed is that it becomes possible to assess part of the total uncertainty. Given the fact that we use very similar ocean models and atmospheric forcing, we can conclude that the spread of the ensemble of reanalyses is mainly representative of our ability to gauge uncertainty in the assimilation methods. This uncertainty changes a lot from one ocean parameter to another, especially in global indices. However, despite several caveats in the design of the multi-system ensemble, the main conclusion from this study is that an eddy-permitting multi-system ensemble approach has become mature and our results provide a first step towards a systematic comparison of eddy-permitting global ocean reanalyses aimed at providing robust conclusions on the recent evolution of the oceanic state.
Resumo:
Intercomparison and evaluation of the global ocean surface mixed layer depth (MLD) fields estimated from a suite of major ocean syntheses are conducted. Compared with the reference MLDs calculated from individual profiles, MLDs calculated from monthly mean and gridded profiles show negative biases of 10–20 m in early spring related to the re-stratification process of relatively deep mixed layers. Vertical resolution of profiles also influences the MLD estimation. MLDs are underestimated by approximately 5–7 (14–16) m with the vertical resolution of 25 (50) m when the criterion of potential density exceeding the 10-m value by 0.03 kg m−3 is used for the MLD estimation. Using the larger criterion (0.125 kg m−3) generally reduces the underestimations. In addition, positive biases greater than 100 m are found in wintertime subpolar regions when MLD criteria based on temperature are used. Biases of the reanalyses are due to both model errors and errors related to differences between the assimilation methods. The result shows that these errors are partially cancelled out through the ensemble averaging. Moreover, the bias in the ensemble mean field of the reanalyses is smaller than in the observation-only analyses. This is largely attributed to comparably higher resolutions of the reanalyses. The robust reproduction of both the seasonal cycle and interannual variability by the ensemble mean of the reanalyses indicates a great potential of the ensemble mean MLD field for investigating and monitoring upper ocean processes.
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The paleoclimate version of the National Center for Atmospheric Research Community Climate System Model version 3 (NCAR-CCSM3) is used to analyze changes in the water formation rates in the Atlantic, Pacific, and Indian Oceans for the Last Glacial Maximum (LGM), mid-Holocene (MH) and pre-industrial (PI) control climate. During the MH, CCSM3 exhibits a north-south asymmetric response of intermediate water subduction changes in the Atlantic Ocean, with a reduction of 2 Sv in the North Atlantic and an increase of 2 Sv in the South Atlantic relative to PI. During the LGM, there is increased formation of intermediate water and a more stagnant deep ocean in the North Pacific. The production of North Atlantic Deep Water (NADW) is significantly weakened. The NADW is replaced in large extent by enhanced Antarctic Intermediate Water (AAIW), Glacial North Atlantic Intermediate Water (GNAIW), and also by an intensified of Antarctic Bottom Water (AABW), with the latter being a response to the enhanced salinity and ice formation around Antarctica. Most of the LGM intermediate/mode water is formed at 27.4 < sigma(theta) < 29.0 kg/m(3), while for the MH and PI most of the subduction transport occurs at 26.5 < sigma(theta) < 27.4 kg/m(3). The simulated LGM Southern Hemisphere winds are more intense by 0.2-0.4 dyne/cm(2). Consequently, increased Ekman transport drives the production of intermediate water (low salinity) at a larger rate and at higher densities when compared to the other climatic periods.
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[EN] Marine N2 fixing microorganisms, termed diazotrophs, are a key functional group in marine pelagic ecosystems. The biological fixation of dinitrogen (N2) to bioavailable nitrogen provides an important new source of nitrogen for pelagic marine ecosystems 5 and influences primary productivity and organic matter export to the deep ocean. As one of a series of efforts to collect biomass and rates specific to different phytoplankton functional groups, we have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling about 12 000 direct field measurements of cyanobacterial diazotroph abundances (based on microscopic cell counts or qPCR 10 assays targeting the nifH genes) and N2 fixation rates. Biomass conversion factors are estimated based on cell sizes to convert abundance data to diazotrophic biomass. The database is limited spatially, lacking large regions of the ocean especially in the Indian Ocean. The data are approximately log-normal distributed, and large variances exist in most sub-databases with non-zero values differing 5 to 8 orders of magnitude. 15 Lower mean N2 fixation rate was found in the North Atlantic Ocean than the Pacific Ocean. Reporting the geometric mean and the range of one geometric standard error below and above the geometric mean, the pelagic N2 fixation rate in the global ocean is estimated to be 62 (53–73) TgNyr−1 and the pelagic diazotrophic biomass in the global ocean is estimated to be 4.7 (2.3–9.6) TgC from cell counts and to 89 (40–20 200) TgC from nifH-based abundances. Uncertainties related to biomass conversion factors can change the estimate of geometric mean pelagic diazotrophic biomass in the global ocean by about ±70 %. This evolving database can be used to study spatial and temporal distributions and variations of marine N2 fixation, to validate geochemical estimates and to parameterize and validate biogeochemical models. The database is 25 stored in PANGAEA (http://doi.pangaea.de/10.1594/PANGAEA.774851).
Resumo:
The global ocean is a significant sink for anthropogenic carbon (Cant), absorbing roughly a third of human CO2 emitted over the industrial period. Robust estimates of the magnitude and variability of the storage and distribution of Cant in the ocean are therefore important for understanding the human impact on climate. In this synthesis we review observational and model-based estimates of the storage and transport of Cant in the ocean. We pay particular attention to the uncertainties and potential biases inherent in different inference schemes. On a global scale, three data-based estimates of the distribution and inventory of Cant are now available. While the inventories are found to agree within their uncertainty, there are considerable differences in the spatial distribution. We also present a review of the progress made in the application of inverse and data assimilation techniques which combine ocean interior estimates of Cant with numerical ocean circulation models. Such methods are especially useful for estimating the air–sea flux and interior transport of Cant, quantities that are otherwise difficult to observe directly. However, the results are found to be highly dependent on modeled circulation, with the spread due to different ocean models at least as large as that from the different observational methods used to estimate Cant. Our review also highlights the importance of repeat measurements of hydrographic and biogeochemical parameters to estimate the storage of Cant on decadal timescales in the presence of the variability in circulation that is neglected by other approaches. Data-based Cant estimates provide important constraints on forward ocean models, which exhibit both broad similarities and regional errors relative to the observational fields. A compilation of inventories of Cant gives us a "best" estimate of the global ocean inventory of anthropogenic carbon in 2010 of 155 ± 31 PgC (±20% uncertainty). This estimate includes a broad range of values, suggesting that a combination of approaches is necessary in order to achieve a robust quantification of the ocean sink of anthropogenic CO2.
Resumo:
We compare the ocean temperature evolution of the Holocene as simulated by climate models and reconstructed from marine temperature proxies. This site provides informations about the Holocene temperature trends as simulated by the models. We use transient simulations from a coupled atmosphere-ocean general circulation model, as well as an ensemble of time slice simulations from the Paleoclimate Modelling Intercomparison Project. The general pattern of sea surface temperature (SST) in the models shows a high latitude cooling and a low latitude warming. The proxy dataset comprises a global compilation of marine alkenone- and Mg/Ca-derived SST estimates. Independently of the choice of the climate model, we observe significant mismatches between modelled and estimated SST amplitudes in the trends for the last 6000 years. Alkenone-based SST records show a similar pattern as the simulated annual mean SSTs, but the simulated SST trends underestimate the alkenone-based SST trends by a factor of two to five. For Mg/Ca, no significant relationship between model simulations and proxy reconstructions can be detected. We tested if such discrepancies can be caused by too simplistic interpretations of the proxy data. We tested different seasons and depths in the model to compare the proxy data trends, and can reconcile only part of the mismatches on a regional scale. We therefore considered the additional environmental factor changes in the planktonic organisms' habitat depth and a time-shift in the recording season to diagnose whether invoking those environmental factors can help reconciling the proxy records and the model simulations. We find that invoking shifts in the living season and habitat depth can remove some of the model-data discrepancies in SST trends. Regardless whether such adjustments in the environmental parameters during the Holocene are realistic, they indicate that when modeled temperature trends are set up to allow drastic shifts in the ecological behavior of planktonic organisms, they do not capture the full range of reconstructed SST trends. Our findings indicate that climate model and reconstructed temperature trends are to a large degree only qualitatively comparable, thus providing a challenge for the interpretation of proxy data as well as the models' sensitivity to orbital forcing.
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In situ data was collected between 2008-2014 in upper ocean. This data set includes the date, local time, coordinate, lifetime value, and variable fluorescence values.
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The CMCC Global Ocean Physical Reanalysis System (C-GLORS) is used to simulate the state of the ocean in the last decades. It consists of a variational data assimilation system (OceanVar), capable of assimilating all in-situ observations along with altimetry data, and a forecast step performed by the ocean model NEMO coupled with the LIM2 sea-ice model. KEY STRENGTHS: - Data are available for a large number of ocean parameters - An extensive validation has been conducted and is freely available - The reanalysis is performed at high resolution (1/4 degree) and spans the last 30 years KEY LIMITATIONS: - Quality may be discontinuos and depend on observation coverage - Uncertainty estimates are simply derived through verification skill scores
Resumo:
Large-scale studies of ocean biogeochemistry and carbon cycling have often partitioned the ocean into regions along lines of latitude and longitude despite the fact that spatially more complex boundaries would be closer to the true biogeography of the ocean. Herein, we define 17 open-ocean biomes classified from four observational data sets: sea surface temperature (SST), spring/summer chlorophyll a concentrations (Chl a), ice fraction, and maximum mixed layer depth (maxMLD) on a 1° × 1° grid. By considering interannual variability for each input, we create dynamic ocean biome boundaries that shift annually between 1998 and 2010. Additionally we create a core biome map, which includes only the grid cells that do not change biome assignment across the 13 years of the time-varying biomes. These biomes can be used in future studies to distinguish large-scale ocean regions based on biogeochemical function.
Resumo:
The efficiency of the biological pump of carbon to the deep ocean depends largely on the biologically mediated export of carbon from the surface ocean and its remineralization with depth. Global satellite studies have primarily focused on chlorophyll concentration and net primary production (NPP) to understand the role of phytoplankton in these processes. Recent satellite retrievals of phytoplankton composition now allow for the size of phytoplankton cells to be considered. Here, we improve understanding of phytoplankton size structure impacts on particle export, remineralization and transfer. Particulate organic carbon (POC) flux observations from sediment traps and 234Th are compiled across the global ocean. Annual climatologies of NPP, percent microplankton, and POC flux at four time series locations and within biogeochemical provinces are constructed, and sinking velocities are calculated to align surface variables with POC flux at depth. Parameters that characterize POC flux vs. depth (export flux ratio, labile fraction, remineralization length scale) are then fit to the aligned dataset. Times of the year dominated by different size compositions are identified and fit separately in regions of the ocean where phytoplankton cell size showed enough dynamic range over the annual cycle. Considering all data together, our findings support the paradigm of high export flux but low transfer efficiency in more productive regions and vice versa for oligotrophic regions. However, when parsing by dominant size class, we find periods dominated by small cells to have both greater export flux and lower transfer efficiency than periods when large cells comprise a greater proportion of the phytoplankton community.
Resumo:
The JGOFS International Collection Volume 2: Integrated Data Sets CD is a coherent, organised compilation of existing data sets produced by member countries which participated in JGOFS. In most cases, the data were gathered from the JGOFS International Collection, Volume 1: Discrete Datasets DVD. To produce Vol. 1 data were taken from the original sources and copied "as is" on the DVD. For Vol. 2 data and metadata have been harmonized using the conversion software PanTool and the import routine of PANGAEA checking for completeness of metadata and defining the relations between data and metadata. Prior to the import, data had performed a technical quality control, i.e. format and readability of the file, availability and combination of parameters and units, range of values.