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71. Data for Nature Climate Change article 'Regional dry-season climate changes due to three decades of Amazonian deforestation'

Author(s):
Khanna, Jaya; Medvigy, David; Fueglistaler, Stephan; Walko, Robert
Abstract:
More than 20% Amazon rainforest has been cleared in the past three decades triggering important hydroclimatic changes. Small-scale (~few kilometers) deforestation in the 1980s has caused thermally-triggered atmospheric circulations that increase regional cloudiness and precipitation frequency. However, these circulations are predicted to diminish as deforestation increases. Here we use multi-decadal satellite records and numerical model simulations to show a regime shift in the regional hydroclimate accompanying increasing deforestation in Rondônia, Brazil. Compared to the 1980s, present-day deforested areas in downwind western Rondônia are found to be wetter than upwind eastern deforested areas during the local dry season. The resultant precipitation change in the two regions is approximately ±25% of the deforested area mean. Meso-resolution simulations robustly reproduce this transition when forced with increasing deforestation alone, showing a negligible role of large-scale climate variability. Furthermore, deforestation-induced surface roughness reduction is found to play an essential role in the present-day dry season hydroclimate. Our study illustrates the strong scale-sensitivity of the climatic response to Amazonian deforestation and suggests that deforestation is sufficiently advanced to have caused a shift from a thermally- to a dynamically-driven hydroclimatic regime.
Type:
Dataset and Software
Issue Date:
2017

72. Data for food consumption strategies in China

Author(s):
Guo, Yixin; Mauzerall, Denise; He, Pan
Abstract:
This dataset provides the data generated during the project analyzing ‘Food Consumption Strategies for Addressing Air Pollution, Climate Change, Water Use, and Public Health in China’. It includes the code for generating the alternative dietary scenarios, for analyzing the health impacts of alternative diets, and for visualization of results.
Type:
Dataset
Issue Date:
31 October 2020

73. Data for “Global adjoint tomography—model GLAD-M25”

Author(s):
Lei, Wenjie
Abstract:
The dataset contains the model file for the Global Adjoint Tomography Model 25 (GLAD-M25). The model file contains parameters defined on the spectral-element mesh and is recommend to be used in SPECFEM3D GLOBE for seismic wave simulation at the global scale.
Type:
Dataset
Issue Date:
5 April 2022

74. Data for: "Financing Carbon Lock-in in Developing Countries: Bilateral Financing for Power Generation Technologies from China, Japan, and the United States"

Author(s):
Chen, Xu; Li, Zhongshu; Gallagher, Kevin P.; Mauzerall, Denise L.
Abstract:
Power sector decarbonization requires a fundamental redirection of global finance from fossil fuel infrastructure towards low carbon technologies. Bilateral finance plays an important role in the global energy transition to non-fossil energy, but an understanding of its impact is limited. Here, for the first time, we compare the influence of overseas finance from the three largest economies – United States, China, and Japan – on power generation development beyond their borders and evaluate the associated long-term CO2 emissions. We construct a new dataset of Japanese and U.S. overseas power generation finance between 2000-2018 by analyzing their national development finance institutions’ press releases and annual reports and tracking their foreign direct investment at the power plant level. Synthesizing this new data with previously developed datasets for China, we find that the three countries’ overseas financing concentrated in fossil fuel power technologies over the studied period. Financing commitments from China, Japan, and the United States facilitated 101 GW, 95 GW, and 47 GW overseas power capacity additions, respectively. The majority of facilitated capacity additions are fossil fuel plants (64% for China, 87% for Japan, and 66% for the United States). Each of the countries’ contributions to non-hydro renewable generation was less than 15% of their facilitated capacity additions. Together, we estimate that overseas fossil fuel power financing through 2018 from these three countries will lock in 24 Gt CO2 emissions by 2060. If climate targets are to be met, replacing bilateral fossil fuel financing with financing of renewable technologies is crucial.
Type:
Dataset
Issue Date:
8 July 2021

75. Data for: "Structure and Density of Silicon Carbide to 1.5 TPa and Implications for Extrasolar Planets"

Author(s):
Kim, Donghoon
Abstract:
There has been considerable recent interest in the high-pressure behavior of silicon carbide, a potential major constituent of carbon-rich exoplanets. In this work, the atomic-level structure of SiC was determined through in situ X-ray diffraction under laser-driven ramp compression up to 1.5 TPa; stresses more than seven times greater than previous static and shock data. Here we show that the B1-type structure persists over this stress range and we have constrained its equation of state (EOS). Using this data we have determined the first experimentally based mass-radius curves for a hypothetical pure SiC planet. Interior structure models are constructed for planets consisting of a SiC-rich mantle and iron-rich core. Carbide planets are found to be ~10% less dense than corresponding terrestrial planets.
Type:
Dataset
Issue Date:
28 April 2022

76. Data for: "The origin of non-skeletal carbonate mud and implications for global climate"

Author(s):
Geyman, Emily C.; Wu, Ziman; Nadeau, Matthew D.; Edmonsond, Stacey; Turner, Andrew; Purkis, Sam J.; Howes, Bolton; Dyer, Blake; Ahm, Anne-Sofie C.; Yao, Nan; Deutsch, Curtis A.; Higgins, John A.; Stolper, Daniel A.; Maloof, Adam C.
Abstract:
Carbonate mud represents one of the most important geochemical archives for reconstructing ancient climatic, environmental, and evolutionary change from the rock record. Mud also represents a major sink in the global carbon cycle. Yet, there remains no consensus about how and where carbonate mud is formed. In this contribution, we present new geochemical data that bear on this problem, including stable isotope and minor and trace element data from carbonate sources in the modern Bahamas such as ooids, corals, foraminifera, and green algae.
Type:
Dataset
Issue Date:
16 June 2022

77. 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

78. 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

79. 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

80. Data from "Homogeneous ice nucleation in an ab initio machine learning model"

Author(s):
Piaggi, Pablo
Abstract:
This dataset contains input and output files to reproduce the results of the manuscript "Homogeneous ice nucleation in an ab initio machine learning model" by Pablo M. Piaggi, Jack Weis, Athanassios Z. Panagiotopoulos, Pablo G. Debenedetti, and Roberto Car (arXiv preprint https://arxiv.org/abs/2203.01376). In this work, we studied the homogeneous nucleation of ice from supercooled liquid water using a machine learning model trained on ab initio energies and forces. Since nucleation takes place over times much longer than the simulation times that can be afforded using molecular dynamics simulations, we make use of the seeding technique that is based on simulating an ice cluster embedded in liquid water. The key quantity provided by the seeding technique is the size of the critical cluster (i.e., a size such that the cluster has equal probabilities of growing or shrinking at the given supersaturation). Using data from the seeding simulations and the equations of classical nucleation theory we compute nucleation rates that can be compared with experiments.
Type:
Dataset
Issue Date:
4 April 2022