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Supporting Data and Guidance: Modeling policy pathways to maximize renewable energy growth and investment in Democratic Republic of the Congo using OSeMOSYS

This repository contains data files and guidance documents that are supplementary materials to accompany the policy paper "Modeling policy pathways to maximize renewable energy growth and investment in Democratic Republic of the Congo using OSeMOSYS" available on Research Square here: <a href="https://www.researchsquare.com/article/rs-2702275/v1">https://www.researchsquare.com/article/rs-2702275/v1</a>

Model data and code supporting "Updated Isoprene and Terpene Emission Factors for the Interactive BVOC Emission Scheme (iBVOC) in the United Kingdom Earth System Model (UKESM1.0) "

Model data and analysis code supporting the Geoscientific Model Development manuscript "Updated Isoprene and Terpene Emission Factors for the Interactive BVOC Emission Scheme (iBVOC) in the United Kingdom Earth System Model (UKESM1.0) "

Model data for "Influence of Asian Topography on the Arctic Stratospheric Ozone"

The CTL_Data_0004_0008.rar, CTL_Data_0009_0013.rar, CTL_Data_0014_0018.rar, CTL_Data_0019_0023.rar, and CTL_Data_0024_0032.rar provide the results of the control experiment that takes the real topography into account (CTL, 29 years in total, ignoring the spin-up). The FLAT_Data_0004_0008.rar, FLAT_Data_0009_0013.rar, FLAT_Data_0014_0018.rar, FLAT_Data_0019_0023.rar, and FLAT_Data_0024_0032.rar provide the results of the flattening of the Asian mountains above 500 m to an altitude of 500 m (FLAT, 29 years in total, ignoring the spin-up). Topography_CTL.nc is the topographic height in the CTL experiment. Topography_FLAT.nc is the topographic height in the FLAT experiment. Detailed description is shown in the paper "Influence of Asian Topography on the Arctic Stratospheric Ozone".

Data for: Fishing triggers trophic cascade in terms of variation, not abundance, in an allometric trophic network model

Trophic cascade studies often rely on linear food chains instead of complex food webs and are typically measured as biomass averages, not as biomass variation. We study trophic cascades propagating across a complex food web including a measure of biomass variation in addition to biomass average. We examined whether different fishing strategies induce trophic cascades and whether the cascades differ from each other. We utilized an allometric trophic network (ATN) model to mechanistically study fishing-induced changes in food web dynamics. Different fishing strategies did not trigger traditional, reciprocal trophic cascades, as measured in biomass averages. Instead, fishing triggered a variation cascade that propagated across the food web, including fish, zooplankton and phytoplankton species. In fisheries that removed a large amount of top-predatory and cannibalistic fish, the biomass oscillations started to decrease after fishing was started. In fisheries that mainly targeted large planktivorous fish, the biomass oscillations did not dampen but slightly increased over time. Removing species with specific ecological functions might alter the food web dynamics and potentially affect the ecological resilience of aquatic ecosystems.

Data Collection and Manipulation Template for MAED (Model for Analysis of Energy Demand)

A Data Collection and Manipulation Template for MAED (Model for Analysis of Energy Demand).

opencc-by-4.0Dec 2022View details →

CLUBB Single Column Model simulation scripts and data

This archive contains run scripts for CLUBB single-column model (SCM) simulations and post-processed data and analysis scripts used in Zhang et al. (2023, JAMES) entitled "removing numerical pathologies in a turbulence parameterization through convergence testing".  There are two compressed files included: 1. <a href="https://zenodo.org/api/files/f1bd6537-5c11-40df-91c9-b562fa0debfe/Figure_scripts.tar.gz">Figure_scripts.tar.gz</a>: contains scripts and figures used in the paper  2. <a href="https://zenodo.org/api/files/f1bd6537-5c11-40df-91c9-b562fa0debfe/run_scripts.tar.gz">run_scripts.tar.gz</a> : contains scripts to run CLUBB-SCM simulations.  The versions of the CLUBB-SCM code used for the simulations to generate the model output for analysis in our study can be found on Zenodo under <a href="http://doi.org/10.5281/zenodo.7803749">10.5281/zenodo.7803749</a>.

Data from: One model to rule them all: Identifying priority bat habitats from multi‐species habitat suitability models

Bats are important components of global ecosystems, providing essential ecosystem services with substantial economic benefit. Yet North American bat populations have been negatively affected by numerous factors (e.g., disease, habitat loss, and wind energy development) with compounding effects. Bats use habitats at a variety of scales, from small, isolated patches to large, contiguous corridors. Landscape‐level research is necessary to identify important habitats, patches, and corridors to strategically target management interventions. We created habitat suitability models (HSMs) for hoary bats (Lasiurus cinereus), eastern red bats (L. borealis), and tri‐colored bats (Perimyotis subflavus) across Illinois, USA using species-specific landscape and climate variables. With the 3 models from this study and a previously published HSM for Indiana bats (Myotis sodalis), we stacked binary HSMs, thereby identifying priority conservation areas across Illinois. Species exhibited different distributional patterns and habitat preferences across Illinois. Multi‐species HSMs highlight high quality habitat (i.e., ecologically important habitat that provides preferred resources for roosting, foraging, and raising young) in southern Illinois and along river riparian areas. This approach identified priority conservation areas mainly following hydrologic zones, which allows managers to strategically target restoration and conservation measures, invest funds in habitat likely to have high return‐on‐investment, and assist with decisions that affect bats (e.g., siting wind turbines and purchasing mitigation lands).

opencc-by-4.0Jan 2023View details →

Strong lensing mass models for the paper "Model-Independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS \\ Based on Self-Consistent Strong Lensing Data"

Codes for evaluating multiple image scatters The code "eval_source_scatter.py" generates the source plane scatters for multiple images. In the folder "Image_plane_scatters", there are codes for computing image plane scatters. "lens_rms.py": to find the location of the multiple images in the image plane. "plot_result.py": to plot the result rms scatters. We uploaded our results and code for computing scatters in both the source and the image planes.   Results from the MARS algorithm In each folder, there are 'result_fits.fits', 'resut_kappa_w_header.fits', 'deflection_angle_w_header.fits', and 'catalog.txt' files. All kappa and deflection angle maps are scaled to Dds/Ds= 1. "result_fits.fits" contains all parameters produced by MARS and has a size of (140x140 + alpha), where alpha is the number of model redshifts. "result_kappa_w_header.fits" is the 100x100 convergence map. "deflection_angle_w_header.fits" is the 100x100 deflection angle map in the unit of arc second. "catalog.txt" is the multiple image catalog. The positions are given in pixel unit. For more details, readers are referfed to arXiv:2301.08765. Also, feel free to contact us (<a href="mailto:sang6199@yonsei.ac.kr">sang6199@yonsei.ac.kr</a>) if you have any questions. <ul> <li>We found errors in WCS for the fits files and re-uploaded corrected files on 2023-01-27. We thank Jori Liesenborgs for pointing this out.</li> <li>We updated files on 2023-04-06.</li> </ul>

opencc-by-4.0Aug 2022View details →

OSeMOSYS model file and alternative data files (i.e. scenarios) of electricity trade in the Eastern Mediterranean and Middle East (EMME) Region

This set of files consists of an OSeMOSYS model file and five separate scenarios exploring electricity trade across the Eastern Mediterranean and Middle East Region. Two sensitivity scenarios are also available.

Replication Data for: CHEEREIO 1.0: a versatile and user-friendly ensemble-based chemical data assimilation and emissions inversion platform for the GEOS-Chem chemical transport model

This dataset includes three files necessary for understanding CHEEREIO model output in the demo section of my initial submission to GMD for the paper: CHEEREIO 1.0: a versatile and user-friendly ensemble-based chemical data assimilation and emissions inversion platform for the GEOS-Chem chemical transport model. Detailed guides for how to handle these datasets are provided in the <a href="https://cheereio.readthedocs.io/en/latest/Postprocess-workflow.html">CHEEREIO documentation postprocessing page</a>. <ul> <li>control_hemco_diagnostics.nc contains the source-separated prior methane emissions.</li> <li>combined_hemco_diagnostics.nc contains the source-separated and ensemble member separated posterior methane emissions.</li> <li>bigY.pkl contains a Python dictionary which aligns TROPOMI XCH4 with simulated prior and posterior GEOS-Chem XCH4.</li> </ul>

opencc-by-4.0Jan 2023View details →

Gravity change data used in the paper "Insights into the magmatic feeding system of the 2021 eruption at Cumbre Vieja (La Palma, Canary Islands) inferred from gravity data modeling"

Gravity changes data observed in the network between July 2021 and January 2022  Reference: Insights into the magmatic feeding system of the 2021 eruption at Cumbre Vieja (La Palma, Canary Islands) inferred from gravity data modeling  F. G. Montesinos1,7, S. Sainz-Maza2,7, D. Gómez-Ortiz3, J. Arnoso4,7, I. Blanco-Montenegro5,7, M. Benavent1,7 E. Vélez4,7, N. Sánchez6 and T. Martín-Crespo3 1 Facultad de CC. Matemáticas, Universidad Complutense de Madrid. Plaza de Ciencias 3, 28040 Madrid, Spain. 2 Observatorio Geofísico Central (IGN). C/ Alfonso XII, 3. 28014 Madrid, Spain. 3 Dpt. Biología y Geología, Física y Química Inorgánica, ESCET, Universidad Rey Juan Carlos. C/Tulipán s/n, 28933 Móstoles, Madrid, Spain. 4 Instituto de Geociencias (IGEO), CSIC-UCM. C/ Doctor Severo Ochoa, 7. 28040 Madrid, Spain. 5 Departamento de Física, Escuela Politécnica Superior, Universidad de Burgos. Avda. de Cantabria s/n, 09006 Burgos, Spain. 6 Instituto Geológico y Minero de España (IGME, CSIC), Unidad Territorial de Canarias, Alonso Alvarado, 43, 2A, 35003 Las Palmas de Gran Canaria, Spain. 7 Research Group ‘Geodesia’, Universidad Complutense de Madrid, Spain. Corresponding author: Fuensanta G. Montesinos (fuensant@ucm.es) This research is supported by the project PID2019-104726GB-I00/AEI/10.13039/501100011033 funded by the Spanish Research Agency. Further, the University Complutense of Madrid (grants Financiación Grupos 2021, UCM 2022-GRFN14/22) and the Spanish Ministry of Science and Innovation (RD 1078/2021, funding for research activities of the CSIC-PIE project CSIC-LAPALMA-07) supported this research.

Input data and model implementation from: How do terrestrial wildlife communities respond to small-scale Acacia plantations embedded in harvested tropical forest?

To offset the declining timber supply from shifting towards more sustainable forestry practices, industrial tree plantations are expanding in tropical production forests. The conversion of natural forest to tree plantation is generally associated with loss of biodiversity and shifts toward more generalist and disturbance tolerant communities; but effects of mixed-landuse landscapes integrating natural and plantation forest remain little understood. Using camera traps, we surveyed the medium-to-large bodied terrestrial wildlife community across two mixed-land-use forest management areas in Sarawak, Malaysia Borneo which include areas dedicated for logging of natural forest and adjacent planted Acacia forests. We analysed data from a 25-wildlife species community using a Bayesian community occupancy model to assess species richness and species-specific occurrence responses to Acacia plantations at a broad scale, and to remote-sensed local habitat conditions within the different forest land-use types. All species were estimated to occur in both land-use types, but species-level percent area occupied and predicted average local species richness were slightly higher in the natural forest management areas compared to licensed planted forest. Similarly, occupancy-based species diversity profiles and defaunation indices for both a full community and only threatened and endemic species suggested the diversity and occurrence were slightly higher in the natural forest management areas. At the local scale, forest quality was the most prominent predictor of species occurrence. These associations with forest quality varied among species but were predominantly positive. Our results highlight the ability of a mixed-land-use landscape with small-scale Acacia plantations embedded in natural forest to retain terrestrial wildlife communities while providing an alternate source of timber. Nonetheless, there was a tendency towards reduced biodiversity in planted forests, which would likely be more pronounced in plantations that are larger or embedded in a less natural matrix.

Sn velocity model and original catalogue data for essay "Uppermost mantle structure of the Japan subduction zone from Sn tomography"

Sn velocity model and original catalogue data for essay “Uppermost mantle structure of the Japan subduction zone from Sn tomography”

opencc-by-4.0Feb 2023View details →

Data supporting "Machine Learning-based Modeling of Olfactory Receptors: Human OR51E2 as a Case Study"

Simulation data and input files in support of the Manuscript:"Machine Learning-based Modeling of Olfactory Receptors: Human OR51E2 as a Case Study". The archive is organized in 6 different folders: 1. 7x7_rmsd, which contains a tcl script (to be run in VMD) to compute the 7x7 RMSD matrix (see Wang et al. J Struct. Bio, (2017)). 2. a100_plumed, which contains PLUMED input files to compute A100 index on OR51E2 trajectories. 3. initial_structures, which contains the 6 different conformation for hOR51E2 obtained by the different predictors in the pdb format. 4. mdp_files, which contains the GROMACS mdp files to perform all the protocol described in the paper. 5. topologies, which contains the 6 different topologies (in .top format) and the initial conformation (in .gro format) for the hOR51E2 embedded in the membrane and solvated. 6. trajectories, which contains the 18 (6 systems, 3 replicas per system) different trajectories with the sodium in place close to D692.50 without solvent and ions (in .xtc format with a frame every 100 ps) and a reference conformation (in .gro format). Here we have also added the trajectory for the SwissModel-derived simulation without sodium ion in place, where we observed the ion binding. This last trajectory contains also solvent and ions, but with a lower printing frequency (1 ns).

Cancer Health Disparities drivers with BERTopic Modelling and PyCaret Evaluation - Text data

The complex interplay of social, behavioral, lifestyle, environmental, health system, and natural health variables contribute to disparities in cancer treatment across racial and ethnic groups. Consequently, it is necessary to identify the variables contributing to cancer health inequalities and develop strategies to achieve health equality. PubMed abstract on Cancer health disparities was scraped with a bio.Entrez python package. Preprocessed data with regex and Natural tool kit (NLTK), topic modelling with BERTopic embeddings, and c-TF-IDF to construct dense clusters and analyze top topics linked with Cancer health disparities. Model evaluation with PyCaret coherence score and web app deployment with Streamlit. The results showed that Topic 32 with terms obese, female, male, school, survey, student, poet, and discrepancy had the best coherence score of 0.3687. In contrast, topic 8, with terms prevalence, adult, income, high, usage, diabetes, education, elderly, change and low, received the least coherence score of 0.3255. The model classifies each Subject Word score based on the scores, the granular topic concerns and trends related to cancer health disparities, investigates the connection between drivers of cancer health disparities, and evaluates the model with their coherence score values

Variability of Eddy Kinetic Energy in the Eurasian Basin of the Arctic Ocean inferred from a Model Simulation at 1-km Resolution (data)

Data for "Variability of Eddy Kinetic Energy in the Eurasian Basin of the Arctic Ocean inferred from a Model Simulation at 1-km Resolution"

Data from: Prediction of three years of annual rain attenuation statistics at Ka-band in French Guiana using the Numerical Weather Prediction model WRF

This study highlights the interest in using an Atmospheric Numerical Simulator (ANS) relying on a high-resolution weather forecast model coupled with an ElectroMagnetic Module (EMM) to compute Ka-band rain attenuation statistics in an equatorial region. An optimization of the parametrisation of the Weather Research and Forecasting meteorological model (WRF) is carried out using measurements collected from a propagation experiment carried out by CNES and ONERA near Kourou in French Guiana. Both simulated and experimental annual Complementary Cumulative Distribution Functions (CCDF) of rain attenuation are presented in this dataset. More specifically, this dataset includes the statistical distribution from both the WRF-EMM model and from the propagation experiment for the years 2017, 2018, 2020 and the whole three-year period.

Data accompanying "Diurnal variability of the upper ocean simulated by a climate model"

Data used for creating figures in the draft article "Diurnal variability of the upper ocean simulated by a climate model". This includes: <ul> <li>Multi-year, monthly mean diurnal cycle metrics at all model grid points.</li> <li>Monthly mean diurnal cycle data for individual years at selected locations.</li> </ul> Code used to create these data files, and to create the plots, is in a Github repository (https://github.com/JackReevesEyre/cfs-analysis-gaea/). The repository is also archived on Zenodo (https://doi.org/10.5281/zenodo.7846095).

Data for: Ensemble-based data assimilation of significant wave height from Sofar Spotters and satellite altimeters with a global operational wave model

An ensemble-based method for wave data assimilation is implemented using significant wave height observations from the globally distributed network of Sofar Spotter buoys and satellite altimeters. The Local Ensemble Transform Kalman Filter (LETKF) method generates skillful analysis fields resulting in reduced forecast errors out to 2.5 days when used as initial conditions in a cycled wave data assimilation system. The LETKF method provides more physically realistic model state updates that better reflect the underlying sea state dynamics and uncertainty compared to methods such as optimal interpolation. Skill assessment far from any included observations and inspection of specific storm events highlights the advantages of LETKF over an optimal interpolation method for data assimilation. This advancement has immediate value in improving predictions of the sea state and, more broadly, enabling future coupled data assimilation and utilization of global surface observations across domains (atmosphere-wave-ocean).