Stable water isotopes in the MITgcm

Völpel, Rike; Paul, André; Krandick, Annegret; Mulitza, Stefan; Schulz, Michael

doi:10.5194/gmd-10-3125-2017

Cited by 12 publications

(30 citation statements)

References 74 publications

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“…The climatological monthly isotopic composition of precipitation and water vapor was obtained from a water isotope‐enabled simulation with the Community Atmosphere Model version 3.0 (IsoCAM3.0, Tharammal et al, ) and are prescribed as boundary conditions for the water isotope module. The prescribed isotopic composition of precipitation was previously used by Völpel et al (), who compared it to observations from the Global Network of Isotopes in Precipitation and found a good agreement. The isotopic composition of river runoff is defined in the model by the isotopic composition of precipitation at the location of the river mouth because the model does not explicitly simulate the isotopic composition of precipitation over river catchment areas (Völpel et al, ).…”

Section: Methodsmentioning

confidence: 96%

“…The prescribed isotopic composition of precipitation was previously used by Völpel et al (), who compared it to observations from the Global Network of Isotopes in Precipitation and found a good agreement. The isotopic composition of river runoff is defined in the model by the isotopic composition of precipitation at the location of the river mouth because the model does not explicitly simulate the isotopic composition of precipitation over river catchment areas (Völpel et al, ).…”

Section: Methodsmentioning

confidence: 96%

“…The MITgcm is extended with a water isotope module that comprises the fractionation processes of water isotopes during evaporation over the ocean and allows the model to simulate stable water isotopes in the entire water column (Völpel et al, ). The module does not include the simulation of the isotopic composition of sea ice, and therefore, the isotopic composition of precipitation does not affect the seawater in areas with sea ice.…”

Section: Methodsmentioning

confidence: 99%

“…This allows generating the adjoint of the MITgcm model code with a source‐to‐source translator (Giering, ; Giering & Kaminski, ) and, hence, applying the adjoint method. We adjusted the model code of the newly added water isotope module (Völpel et al, ) to make it suitable for the generation of the adjoint code.…”

Section: Methodsmentioning

confidence: 99%

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A Dynamical Reconstruction of the Global Monthly Mean Oxygen Isotopic Composition of Seawater

et al. 2018

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We present a dynamically consistent gridded data set of the global, monthly mean oxygen isotope ratio of seawater ( 18 O sw ). The data set was created from an optimized simulation of an ocean general circulation model constrained by global monthly 18 O sw data collected from 1950 to 2011 and climatological salinity and temperature data collected from 1951 to 1980. The optimization was obtained using the adjoint method for variational data assimilation, which yields a simulation that is consistent with the observational data and the physical laws embedded in the model. Our data set performs equally well as a previous data set in terms of model-data misfit but brings an improvement in terms of the seasonal cycle and physical consistency. As a result the data set does not show any sharp transitions between water masses or in areas where the data coverage is low. The data assimilation method shows high potential for interpolating sparse data sets in a physically meaningful way. Comparatively big errors, however, are found in our data set in the surface levels in the Arctic Ocean mainly because the influence of isotopically highly depleted precipitation is not preserved in the sea ice model, and the low model resolution of about 285 km horizontally. The data set is publicly available, and it is anticipated to be useful for a large range of applications in (paleo-) oceanographic studies. Plain Language SummaryThe ratio of the heavier to the lighter oxygen isotope in seawater varies over different areas and for different water masses in the ocean. In this study we present a global gridded data set of the monthly mean oxygen isotope ratio of seawater ( 18 O sw ). The data set is publicly available and will be useful for a large range of applications. It can, for example, help to reconstruct past ocean states or be used as lower boundary for an atmospheric model to investigate the isotopic composition of the atmosphere. The data set is taken from a simulation of a numerical ocean model that is in consistency with global 18 O sw observations collected from 1950 to 2011 and monthly salinity and temperature observations collected from 1951 to 1980. To obtain the model simulation, we used a data assimilation method that brings the model simulation into consistency with the observational data. The ocean model is based on physical laws, and therefore, our data set is also in consistency with the ocean physics. Our data set is similarly close to the observations than a previous data set but brings an improvement because it is based on the ocean physics and because it has a seasonal cycle.

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Section: Methodsmentioning

confidence: 96%

Section: Methodsmentioning

confidence: 96%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

A Dynamical Reconstruction of the Global Monthly Mean Oxygen Isotopic Composition of Seawater

et al. 2018

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“…To implement the vertical dimension, we used an approach in which we first updated PLAFOM (hereafter referred to as PLAFOM2.0) by including light dependency for symbiontbearing planktonic foraminifera and then applied the previously used spatial parameterization of carbon biomass as a function of temperature, nutrition, and competition, together with light, on depth-resolved parameter fields. By combining PLAFOM2.0 with the CESM1.2(BGC) configuration (hereafter referred to as the CESM1.2(BGC+PLA) configuration), the vertical dimension can be resolved throughout the ocean, with 24 layers in the top 250 m. Thus, PLAFOM2.0, belonging to a suite of proxy system models (e.g., Pollard and Schulz, 1994;Schmidt, 1999;Fraile et al, 2008;Evans et al, 2013;Dee et al, 2015;Völpel et al, 2017), will aid the interpretation of paleoclimate reconstructions. In addition, PLAFOM2.0 has the potential to be used in a paleoclimate data assimilation framework (see, e.g., Goosse et al, 2010;Steiger et al, 2014;Dee et al, 2016;Hakim et al, 2016).…”

Section: Approachmentioning

confidence: 99%

Modeling seasonal and vertical habitats of planktonic foraminifera on a global scale

et al. 2018

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Abstract. Species of planktonic foraminifera exhibit specific seasonal production patterns and different preferred vertical habitats. The seasonal and vertical habitats are not constant throughout the range of the species and changes therein must be considered when interpreting paleoceanographic reconstructions based on fossil foraminifera. However, detecting the effect of changing vertical and seasonal habitat on foraminifera proxies requires independent evidence for either habitat or climate change. In practice, this renders accounting for habitat tracking from fossil evidence almost impossible. An alternative method that could reduce the bias in paleoceanographic reconstructions is to predict speciesspecific habitat shifts under climate change using an ecosystem modeling approach. To this end, we present a new version of a planktonic foraminifera model, PLAFOM2.0, embedded into the ocean component of the Community Earth System Model version 1.2.2. This model predicts monthly global concentrations of the planktonic foraminiferal species Neogloboquadrina pachyderma, N. incompta, Globigerina bulloides, Globigerinoides ruber (white), and Trilobatus sacculifer throughout the world ocean, resolved in 24 vertical layers to 250 m of depth. The resolution along the vertical dimension has been implemented by applying the previously used spatial parameterization of carbon biomass as a function of temperature, light, nutrition, and competition on depth-resolved parameter fields. This approach alone results in the emergence of species-specific vertical habitats, which are spatially and temporally variable. Although an explicit parameterization of the vertical dimension has not been carried out, the seasonal and vertical distribution patterns predicted by the model are in good agreement with sediment trap data and plankton tow observations. In the simulation, the colder-water species N. pachyderma, N. incompta, and G. bulloides show a pronounced seasonal cycle in their depth habitat in the polar and subpolar regions, which appears to be controlled by food availability. During the warm season, these species preferably occur in the subsurface (below 50 m of water depth), while towards the cold season they ascend through the water column and are found closer to the sea surface. The warm-water species G. ruber (white) and T. sacculifer exhibit a less variable shallow depth habitat with highest carbon biomass concentrations within the top 40 m of the water column. Nevertheless, even these species show vertical habitat variability and their seasonal occurrence outside the tropics is limited to the warm surface layer that develops at the end of the warm season. The emergence in PLAFOM2.0 of species-specific vertical habitats, which are consistent with observations, indicates that the population dynamics of planktonic foraminifera species may be driven by the same factors in time, space, and with depth, in which case the model can provide a reliable and robust tool to aid the interpretation of proxy records.

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The mineralogic and isotopic fingerprint of equatorial carbonates: Kepulauan Seribu, Indonesia

Utami

Reuning

Hallenberger

et al. 2021

Int J Earth Sci (Geol Rundsch)

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Kepulauan Seribu is an isolated patch reef complex situated in the Java Sea (Indonesia) and is a typical example for a humid, equatorial carbonate system. We investigate the mineralogical and isotopic fingerprint of Panggang, one of the reef platforms of Kepulauan Seribu, to evaluate differences to other carbonate systems, using isotope in combination with XRD and SEM analysis. A characteristic property of shallow water (< 20 m) sediments from Kepulauan Seribu is their increased LMC content (~ 10%) derived from some genera of rotaliid foraminifers and bivalves. The relative abundance of these faunal elements in shallow waters might be related to at least temporary turbid conditions caused by sediment-laden river runoff. This influence is also evidenced by the presence of low amounts of siliciclastic minerals below the regional wave base. Kepulauan Seribu carbonates are characterized by very low δ13C and δ18O values. This is related to the isotopically depleted riverine input. The δ13CDIC in riverine water is reduced by the contribution of 12C from riverside mangroves. Deep atmospheric convection and intensive rains contribute 18O-depleted freshwater in the river catchments, finally reducing salinity in the Java Sea. The depleted δ13C signature in carbonates is further enhanced by the lack of green algae and inorganic carbonates and abundance of coral debris. Low δ18O values in carbonates are favored by the high water temperatures in the equatorial setting. Since equatorial carbonates in SE Asia, including the Java Sea, are typically influenced by high turbidity and/or river runoff, the observed distinctively low isotope values likely are characteristic for equatorial carbonate systems in the region.

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Stable water isotopes in the MITgcm

Cited by 12 publications

References 74 publications

A Dynamical Reconstruction of the Global Monthly Mean Oxygen Isotopic Composition of Seawater

A Dynamical Reconstruction of the Global Monthly Mean Oxygen Isotopic Composition of Seawater

Modeling seasonal and vertical habitats of planktonic foraminifera on a global scale

The mineralogic and isotopic fingerprint of equatorial carbonates: Kepulauan Seribu, Indonesia

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