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- Creator:
- Sun, Hu, Ren, Jiaen, Chen, Yang, Zou, Shasha, Chang, Yurui, Wang, Zihan, and Coster, Anthea
- Description:
- Our research focuses on providing a fully-imputed map of the worldwide total electron content with high resolution and spatial-temporal smoothness. We fill in the missing values of the original Madrigal TEC maps via estimating the latent feature of each latitude and local time along the 2-D grid and give initial guess of the missing regions based on pre-computed spherical harmonics map. The resulting TEC map has high imputation accuracy and the ease of reproducing. All data are in HDF5 format and are easy to read using the h5py package in Python. The TEC map is grouped in folders based on years and each file contains a single-day data of 5-min cadence. Each individual TEC map is of size 181*361. and WARNING: 2023-12-01 the data file for 2019-Jan-03 has badly fitted values. Please avoid using it. All other days' files are ready to use.
- Keyword:
- Total Electron Content, Matrix Completion, VISTA, Spherical Harmonics, and Spatial-Temporal Smoothing
- Citation to related publication:
- Sun, H., Hua, Z., Ren, J., Zou, S., Sun, Y., & Chen, Y. (2022). Matrix completion methods for the total electron content video reconstruction. The Annals of Applied Statistics, 16(3), 1333-1358., Sun, H., Chen, Y., Zou, S., Ren, J., Chang, Y., Wang, Z., & Coster, A. (2023). Complete Global Total Electron Content Map Dataset based on a Video Imputation Algorithm VISTA. Scientific Data, in press., and Zou, S., Ren, J., Wang, Z., Sun, H., & Chen, Y. (2021). Impact of storm-enhanced density (SED) on ion upflow fluxes during geomagnetic storm. Frontiers in Astronomy and Space Sciences, 8, 746429.
- Discipline:
- Science and Engineering
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- Creator:
- Sun, Hu, Ren, Jiaen, Chen, Yang, and Zou, Shasha
- Description:
- Our research focuses on providing a fully-imputed map of the worldwide total electron content with high resolution and spatial-temporal smoothness. We fill in the missing values of the original Madrigal TEC maps via estimating the latent feature of each latitude and local time along the 2-D grid and give initial guess of the missing regions based on pre-computed spherical harmonics map. The resulting TEC map has high imputation accuracy and the ease of reproducing. and All data are in HDF5 format and are easy to read using the h5py package in Python. The TEC map is grouped in folders based on years and each file contains a single-day data of 5-min cadence. Each individual TEC map is of size 181*361.
- Keyword:
- Total Electron Content, Matrix Completion, VISTA, Spherical Harmonics, and Spatial-Temporal Smoothing
- Citation to related publication:
- Sun, H., Hua, Z., Ren, J., Zou, S., Sun, Y., & Chen, Y. (2020). Matrix Completion Methods for the Total Electron Content Video Reconstruction. arXiv preprint arXiv:2012.01618. and Zou, S., Ren, J., Wang, Z., Sun, H., & Chen, Y. (2021). Impact of Storm-Enhanced Density (SED) on Ion Upflow Fluxes During Geomagnetic Storm. Frontiers in Astronomy and Space Sciences, 162.
- Discipline:
- Science
-
- Creator:
- Ponder, Brandon M., Ridley, Aaron J., Bougher, Stephen W., Pawlowski, David, and Brecht, Amanda
- Description:
- This research was completed to introduce a state-of-the-art Venus GCM to the modeling community. Validation studies were performed to give credence to the model's results. and This data set is made available under a Creative Commons Public Domain license (CC0 1.0). The python scripts contained were ran on macOS Monterey version 12.7 with Python 3.9. Numpy version: 1.19.4 Pandas version: 1.2.0
- Keyword:
- Venus, GITM, Ionosphere, Thermosphere, Solar minimum, Navier-stokes, Fluid dynamics, Shocks, V-GITM, and VGITM
- Citation to related publication:
- Ponder, Brandon & Ridley, Aaron J. & Bougher, Stephen W. & Pawlowski, D. & Brecht, A. (2023). The Venus Global Ionosphere-Thermosphere Model (V-GITM): A Coupled Thermosphere and Ionosphere Formulation. JGR Planets. In Press.
- Discipline:
- Science
-
Supporting data: Domain-agnostic predictions of nanoscale interactions in proteins and nanoparticles
- Creator:
- Saldinger, Jacob, Raymond, Matt , Elvati, Paolo, and Violi, Angela
- Description:
- The accurate and rapid prediction of generic nanoscale interactions is a challenging problem with broad applications. Much of biology functions at the nanoscale, and our ability to manipulate materials and purposefully engage biological machinery requires knowledge of nano-bio interfaces. While several protein-protein interaction models are available, they leverage protein-specific information, limiting their abstraction to other structures. Here, we present NeCLAS, a general, and rapid machine learning pipeline that predicts the location of nanoscale interactions, providing human-intelligible predictions. Two key aspects distinguish NeCLAS: coarse-grained representations, and the use of environmental features to encode the chemical neighborhood. We showcase NeCLAS with challenges for protein-protein, protein-nanoparticle and nanoparticle-nanoparticle systems, demonstrating that NeCLAS replicates computationally- and experimentally-observed interactions. NeCLAS outperforms current nanoscale prediction models, and it shows cross-domain validity, qualifying as a tool for basic research, rapid prototyping, and design of nanostructures., Software: - To reproduce all-atom molecular dynamics (MD) NAMD is required (version 2.14 or later is suggested). NAMD software and documentation can be found at https://www.ks.uiuc.edu/Research/namd/, - To reproduce coarse-grained MD simulations, LAMMPS (version 29 Sep 2021 - Update 2 or later is suggested). LAMMPS software and documentation can be found at https://www.lammps.org, - To rebuild free energy profiles, the PLUMED plugin (version 2.6) was used. PLUMED software and documentation can be found at https://www.plumed.org/ , and - To generate force matching potentials, the was used the OpenMSCG software was used. OpenMSCG software and documentation can be found at https://software.rcc.uchicago.edu/mscg/
- Keyword:
- Neural Networks, Proteins, Dimensionality Reduction, Nanoparticles, and Coarse-Graining
- Citation to related publication:
- https://www.biorxiv.org/content/10.1101/2022.08.09.503361v2
- Discipline:
- Science
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- Creator:
- Brenner, Austin, M
- Description:
- Coupling between the solar wind and magnetosphere can be expressed in terms of energy transfer through the separating boundary known as the magnetopause. Geospace simulation is performed using the Space Weather Modeling Framework (SWMF) of a multi-ICME impact event on February 18-20, 2014 in order to study the energy transfer through the magnetopause during storm conditions. The magnetopause boundary is identified using a modified plasma $\beta$ and fully closed field line criteria to a downstream distance of $-20R_{e}$. Observations from Geotail, Themis, and Cluster are used as well as the Shue 1998 model to verify the simulation field data results and magnetopause boundary location. Once the boundary is identified, energy transfer is calculated in terms of total energy flux \textbf{K}, Poynting flux \textbf{S}, and hydrodynamic flux \textbf{H}. Surface motion effects are considered and the regional distribution of energy transfer on the magnetopause surface is explored in terms of dayside $\left(X>0\right)$, flank $\left(X<0\right)$, and tail cross section $\left(X=X_{min}\right)$ regions. It is found that total integrated energy flux over the boundary is nearly balanced between injection and escape, and flank contributions dominate the Poynting flux injection. Poynting flux dominates net energy input, while hydrodynamic flux dominates energy output. Surface fluctuations contribute significantly to net energy transfer and comparison with the Shue model reveals varying levels of cylindrical asymmetry in the magnetopause flank throughout the event. Finally existing energy coupling proxies such as the Akasofu $\epsilon$ parameter and Newell coupling function are compared with the energy transfer results.
- Keyword:
- Space plasma, Magnetosphere, MHD simulations, Magnetopause, Substorm, Energy transfer, and Poynting flux
- Citation to related publication:
- Brenner A, Pulkkinen TI, Al Shidi Q and Toth G (2021) Stormtime Energetics: Energy Transport Across the Magnetopause in a Global MHD Simulation. Front. Astron. Space Sci. 8:756732. doi: 10.3389/fspas.2021.756732
- Discipline:
- Science
-
- Creator:
- Al Shidi, Q. and Pulkkinen, T.
- Description:
- Provided are the resultant and processed data.
- Keyword:
- space physics, ground magnetometers, magnetosphere, numerical space physics, solar wind, numerical space physics, and ionosphere
- Discipline:
- Science
-
- Creator:
- Wang, Zihan
- Description:
- SWMF is used to study the segmentation of SED plume into polar cap patches during the geomagnetic storm on Sep 7, 2017. The database includes the 3D output in the upper atmosphere from GITM, the 2D output from Ionospheric Electrodynamics (IE) and 3D output from BATSRUS. The output from GITM can be read with thermo_batch_new.pro. The output from IE can be opened with Spacepy at https://pythonhosted.org/SpacePy/. The output from BATSRUS can be opened with tecplot. More details can be found in Readme.txt.
- Keyword:
- MHD and Ionosphere
- Citation to related publication:
- Wang, Z., Zou, S., Coppeans, T., Ren, J., Ridley, A., & Gombosi, T. (2019). Segmentation of SED by Boundary Flows Associated With Westward Drifting Partial Ring current. Geophysical Research Letters, 46(14), 7920–7928. https://doi.org/10.1029/2019GL084041
- Discipline:
- Science
-
- Creator:
- Brasch, Jonathan M, Elipot, Shane, and Arbic, Brian
- Description:
- For Drifters, HYCOM, MITgcm: Spectra and kinetic energy files. Please see readme.txt for a description of all data and code contained here. and - Compare kinetic energies (KE) of high-resolution global ocean models estimated from rotary spectra to KE in surface drifter observations. - Near-inertial KE is closer to drifter observations in models with frequently updated wind forcing - Internal tide KE is closer to drifter observations in models with topographic wave drag
- Keyword:
- oceanography, rotary spectra, kinetic energy, sea surface velocity, and drifters
- Citation to related publication:
- Elipot, S., Lumpkin, R., Perez, R. C., Lilly, J. M., Early, J. J., & Sykulski, A. M. (2016). A global surface drifter data set at hourly resolution. Journal of Geophysical Research: Oceans, 121(5), 2937–2966. https://doi.org/10.1002/2016JC011716
- Discipline:
- Science
-
- Creator:
- Iong, Daniel, Chen, Yang, Toth, Gabor, Zou, Shasha, Pulkkinen, Tuija I., Ren, Jiaen, Camporeale, Enrico, and Gombosi, Tamas I. I.
- Description:
- In this work, we trained gradient boosted trees using XGBoost to predict the SYM-H forecasting using different combinations of solar wind and interplanetary magnetic field (IMF) parameters. Data are in csv and Python pickle formats.
- Keyword:
- SYM-H forecasting
- Citation to related publication:
- Iong, D., Y. Chen, G. Toth, S. Zou, T. I. Pulkkinen, J. Ren, E. Camporeale, and T. I. Gombosi, New Findings from Explainable SYM-H Forecasting using Gradient Boosting Machines, Space Weather,11, accepted, 2022. https://doi.org/10.1002/essoar.10508063.3
- Discipline:
- Science
-
- Creator:
- Xiantong Wang
- Description:
- We perform a geomagnetic event simulation using a newly developed magnetohydrodynamic with adaptively embedded particle-in-cell (MHD-AEPIC) model. We have developed effective criteria to identify reconnection sites in the magnetotail and cover them with the PIC model. The MHD-AEPIC simulation results are compared with Hall MHD and ideal MHD simulations to study the impacts of kinetic reconnection at multiple physical scales. At the global scale, the three models produce very similar SYM-H and SuperMag Electrojet (SME) indexes, which indicates that the global magnetic field configurations from the three models are very close to each other. At the mesoscale we compare the simulations with in situ Geotail observations in the tail. All three models produce reasonable agreement with the Geotail observations. The MHD-AEPIC and Hall MHD models produce tailward and earthward propagating fluxropes, while the ideal MHD simulation does not generate flux ropes in the near-earth current sheet. At the kinetic scales, the MHD-AEPIC simulation can produce a crescent shape distribution of the electron velocity space at the electron diffusion region which agrees very well with MMS observations near a tail reconnection site. These electron scale kinetic features are not available in either the Hall MHD or ideal MHD models. Overall, the MHD-AEPIC model compares well with observations at all scales, it works robustly, and the computational cost is acceptable due to the adaptive adjustment of the PIC domain.
- Keyword:
- MHD, PIC, and Magnetosphere
- Discipline:
- Science
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