1 - 8 of 8
Number of results to display per page
Search Results
2. Data for: 'How is sea level change encoded in carbonate stratigraphy?'
- Author(s):
- Geyman, Emily C.; Maloof, Adam C.; Dyer, Blake
- Abstract:
- The history of organismal evolution, seawater chemistry, and paleoclimate is recorded in layers of carbonate sedimentary rock. Meter-scale cyclic stacking patterns in these carbonates often are interpreted as representing sea level change. A reliable sedimentary proxy for eustasy would be profoundly useful for reconstructing paleoclimate, since sea level responds to changes in temperature and ice volume. However, the translation from water depth to carbonate layering has proven difficult, with recent surveys of modern shallow water platforms revealing little correlation between carbonate facies (i.e., grain size, sedimentary bed forms, ecology) and water depth. We train a convolutional neural network with satellite imagery and new field observations from a 3,000 km2 region northwest of Andros Island (Bahamas) to generate a facies map with 5 m resolution. Leveraging a newly-published bathymetry for the same region, we test the hypothesis that one can extract a signal of water depth change, not simply from individual facies, but from sequences of facies transitions analogous to vertically stacked carbonate strata. Our Hidden Markov Model (HMM) can distinguish relative sea level fall from random variability with ∼90% accuracy. Finally, since shallowing-upward patterns can result from local (autogenic) processes in addition to forced mechanisms such as eustasy, we search for statistical tools to diagnose the presence or absence of external forcings on relative sea level. With a new data-driven forward model that simulates how modern facies mosaics evolve to stack strata, we show how different sea level forcings generate characteristic patterns of cycle thicknesses in shallow carbonates, providing a new tool for quantitative reconstruction of ancient sea level conditions from the geologic record.
- Type:
- Dataset
- Issue Date:
- 1 February 2021
3. Why is El Nino warm?
- Author(s):
- Hogikyan, Allison; Resplandy, Laure; Yang, Wenchang; Fueglistaler, Stephan
- Abstract:
- Dataset constructed from GFDL-FLOR preindustrial control experiment run by Wenchang Yang (wenchang@princeton.edu) on Princeton University's tiger CPU. Processing by Allison Hogikyan (hogikyan@princeton.edu) on Princeton University's tigress data processing node. June 2021.
- Type:
- Dataset
- Issue Date:
- 28 June 2021
4. Data for: 'Facies control on carbonate δ13C on the Great Bahama Bank'
- Author(s):
- Geyman, Emily C.; Maloof, Adam C.
- Abstract:
- The carbon isotopic (δ13C) composition of shallow-water carbonates often is interpreted to reflect the δ13C of the global ocean and is used as a proxy for changes in the global carbon cycle. However, local platform processes, in addition to meteoric and marine diagenesis, may decouple carbonate δ13C from that of the global ocean. To shed light on the extent to which changing sediment grain composition may produce δ13C shifts in the stratigraphic record, we present new δ13C measurements of benthic foraminifera, solitary corals, calcifying green algae, ooids, coated grains, and lime mud from the modern Great Bahama Bank (GBB). This survey of a modern carbonate environment reveals δ13C variability comparable to the largest δ13C excursions in the last two billion years of Earth history.
- Type:
- Dataset
- Issue Date:
- 6 May 2021
5. Data for: Three-Dimensional Morphometry of Ooids in Oolites: a new tool for more accurate and precise paleoenvironmental interpretation
- Author(s):
- Howes, Bolton; Mehra, Akshay; Maloof, Adam
- Abstract:
- The prevalence of ooids in the stratigraphic record, and their association with shallow-water carbonate environments, make ooids an important paleoenvironmental indicator. Recent advances in the theoretical understanding of ooid morphology, along with empirical studies from Turks and Caicos, Great Salt Lake, and The Bahamas, have demonstrated that the morphology of ooids is indicative of depositional environment and hydraulic conditions. To apply this knowledge from modern environments to the stratigraphic record of Earth history, researchers measure the size and shape of lithified ooids on two-dimensional surfaces (i.e., thin sections or polished slabs), often assuming that random 2D slices intersect the nuclei and that the orientation of the ooids is known. Here we demonstrate that these assumptions rarely are true, resulting in errors of up to 35% on metrics like major axis length. We present a method for making 3D reconstructions by serial grinding and imaging, which enables accurate measurement of the morphology of individual ooids within an oolite, as well as the sorting and porosity of a sample. We also provide three case studies that use the morphology of ooids in oolites to extract environmental information. Each case study demonstrates that 2D measurements can be useful if the environmental signal is large relative to the error from 2D measurements. However, 3D measurements substantially improve the accuracy and precision of environmental interpretations. This study focuses on oolites, but errors from 2D measurements are not unique to oolites; this method can be used to extract accurate grain and porosity measurements from any lithified granular sample.
- Type:
- Dataset
- Issue Date:
- 22 February 2021
6. Experimental data for paper "hydraulic transmissivity inferred from ice-sheet relaxation following Greenland supraglacial lake drainages"
- Author(s):
- Lai, Ching-Yao
- Abstract:
- This setup mimics ice lying above the drainage system. In the experiment, a fluid-filled blister is generated via liquid injection into the interface between a transparent elastic layer and a porous substrate. After injection of liquid, the fluid permeates from the blister through the porous substrate, the blister volume V(t) relaxes exponentially with time. Our lab experiments show that varying the permeability of the porous substrate k significantly impacts the relaxation timescale in the experiments.
- Type:
- Dataset
- Issue Date:
- 18 May 2021
7. Three dimensional archaeocyathide and coral imagery for morphologic analysis
- Author(s):
- Manzuk, Ryan; Maloof, Adam
- Abstract:
- In our study, we compare the three dimensional (3D) morphologic characteristics of Earth's first reef-building animals (archaeocyath sponges) with those of modern, photosynthetic corals. Within this repository are the 3D image data products for both groups of animals. The archaeocyath images were produced through serial grinding and imaging with the Grinding, Imaging, and Reconstruction Instrument at Princeton University. The images in this repository are the downsampled data products used in our study, and the full resolution (>2TB) image stacks are available upon request from the author. For the coral image data, the computed tomography (CT) images of all samples are included at full resolution. Also included in this repository are the manual and automated outline coordinates of the archaeocyath and coral branches, which can be directly used for morphological study.
- Type:
- Dataset, Image, MovingImage, and StillImage
- Issue Date:
- August 2022
8. Supplementary Model Output to "Climate, soil organic layer, and nitrogen jointly drive forest development after fire in the North American boreal zone"
- Author(s):
- Trugman, Anna
- Abstract:
- This dataset contains all the model output used to generate the figures and data reported in the article "Climate, soil organic layer, and nitrogen jointly drive forest development after fire in the North American boreal zone". The data was generated during spring 2015 using the a modified version of the Ecosystem Demography model version 2, provided as a supplement accompanying the article. The data was generated using the computational resources supported by the PICSciE OIT High Performance Computing Center and Visualization Laboratory at Princeton University. The dataset contains a pdf Readme file which explains in detail how the data can be used. Users are recommended to go through this file before using the data.
- Type:
- Dataset
- Issue Date:
- 2016