Case 2 of Li et al. (2016) LES simulations for the DISCOVER-AQ 11 campaign, including three different grid resolutions (96, 197 and 320 grid cell resolutions), plus simulations at the 192 grid resolution with and without aqueous chemistry
This dataset contains three data files used in: King, A.E. and J. Blesh, 2017. Crop rotations for increased soil carbon: perenniality as a guiding principle. Ecological Applications. There are also three corresponding metadata files.
The file “CRMA 2017 Main.csv” contains data for the control and treatment rotations used to construct pairwise comparisons for meta-analysis, response ratios calculated for soil organic carbon concentration, and change in carbon input. The dataset also includes management, soil, and other environmental characteristics for each site.
The file “CRMA 2017 Diversity x Nitrogen.csv” contains data used to test whether N fertilizer inputs mediated the effect of functional diversity on SOC concentrations.
The file “CRMA Annual grain.csv” contains data used to test for effects of crop rotation species diversity (one vs. two species, or two vs. three species) on SOC concentrations and C input (i.e., for the “grain-only” rotations). The dataset also includes management, soil, and other environmental characteristics for each site.
The corresponding metadata files: “CRMA 2017 Main_metadata.csv”, “CRMA 2017 Diversity x Nitrogen_metadata.csv”, and “CRMA Annual grain _metadata.csv” provide a detailed description of all variables in each dataset.
Note: On Jan 12, 2018 the following information was added to the three metadata files: the name of the data file the metadata refers to, an explanation as to the meaning of blank cells in the data file, a full citation to the paper where the author describes her findings and contact information for the author.
Mathematica Diffusion Simulation: Programmed by Coburn, Caleb. Simulation of diffusion in organic heterostructures, including least square fits and statistical goodness of fit analysis. Used to calculate fits to transient data in Fig 1, 3 and Extended Data Fig.2. Example data file included for download
Matlab Montecarlo simulation: Programmed by Coburn, Caleb. Montecarlo simulation of charge diffusion on a cubic lattice to determine lateral diffusion length as a function of barrier height, assuming thermionic emission over the barrier.
Matlab 2D Diffusion Simulation:Programmed by Coburn, Caleb. Modified from BYU Physics 430 Course Manual. Simulates diffusion around a film discontinuity, such a cut. Used to generate fits to Extended Data Fig. 1
Each pdf is an electronic version of the paper output for each experiment.
Each text file is the electronic version of the data on the computer cards for each experiment. These text files are directly readable by Excel. Once in Excel, the data can be manipulated as desired.
Additional information is in the theses.
The data are the 13 target structures used in developing our model for predicting colloidal crystal structures from the geometries of particular shapes. The target structures are: simple cubic (SC), body-centered cubic (BCC), face-centered cubic (FCC), simple chiral cubic (SCC), hexagonal (HEX-1-0.6), diamond (D), graphite (G), honeycomb (H), body-centered tetragonal (BCT-1-1-2.4), high-pressure Lithium (Li), Manganese (beta-Mn), Uranium (beta-U), Tungsten (beta-W). At least nine simulations were run on each of the target structures. All of the data are formatted as .pos files.
Greenhouse gas (GHG) additions to Earth’s atmosphere initially reduce global outgoing longwave radiation (OLR), thereby warming the planet. In select environments with temperature inversions, however, increased GHG concentrations can actually increase local OLR. Negative top-of-atmosphere and effective radiative forcing (ERF) from this situation give the impression that local surface temperatures could cool in response to GHG increases. Here we consider an extreme scenario in which GHG concentrations are increased only within the warmest layers of winter near-surface inversions of the Arctic and Antarctic. We find, using a fully coupled Earth system model, that the underlying surface warms despite the GHG addition exerting negative ERF and cooling the troposphere in the vicinity of the GHG increase. This unique radiative forcing and thermal response is facilitated by the high stability of the polar winter atmosphere, which inhibits thermal mixing and amplifies the impact of surface radiative forcing on surface temperature. These findings also suggest that strategies to exploit negative ERF via injections of short-lived GHGs into inversion layers would likely be unsuccessful in cooling the planetary surface. and Note: A revised data description file was added to this work on April 11, 2018 containing additional information about the data set than was provided in the original description. Additional keywords and a full citation to the related article were added as well.
Note: The "Readme_Metadata" file was updated on March 15, 2018 to include a citation to the related article making use of this data and was reformatted to be presented as a pdf file rather than as a docx file. and This data set is comprised of synchrotron-based X-ray transmission and absorption spectroscopy data as well as X-ray diffraction patterns that were performed to characterize the best-preserved examples of nanoscale iron silicate mineral inclusions from 2.5 billion-year-old Banded Iron Formations (BIFs) and ferruginous cherts.
The global magnetosphere-ionosphere-thermosphere (M-I-T) system is intrinsically coupled and susceptible to external drivers such as solar wind dynamic pressure enhancements. In order to understand the large-scale dynamic processes in the M-I-T system due to the compression from the solar wind, the 17 March 2015 sudden commencement was studied in detail using global numerical models. This data set is comprised of the simulation data
generated from these models. and NOTE: The following changes were made to this dataset on March 28, 2018. First, two mp4 files were added. Second, the symbol representing "degree" was not rendering properly in the README file. The symbols were removed and replaced with the word "degree". Third, the metadata in the "methodology" and "description" fields were revised for content and clarity. On April 16, 2018 a citation to the corresponding article was added to the metadata record.