Search Results

Search Constraints

Search Results

  • VISTA TEC Database (ver 2.0)

    work
    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

  • Improving Forecasting Ability of GITM using Data-driven Model Refinement

    work
    Creator:
    Ponder, Brandon M., Ridley, Aaron J., Goel, Ankit, and Bernstein, Dennis S.
    Description:
    This research was completed to statistically validate that a data-model refinement technique could integrate real measurements to remove bias from physics-based models via changing the forcing parameters such as the thermal conductivity coefficients.
    Keyword:
    Thermosphere, GITM, CHAMP, GRACE, MSIS, Upper Atmosphere Modeling, and Data Assimilation
    Citation to related publication:
    Ponder, B. M., Ridley, A. J., Goel, A., & Bernstein, D. S. (2023). Improving forecasting ability of GITM using data-driven model refinement. Space Weather, 21, e2022SW003290.  https://doi.org/10.1029/2022SW003290
    Discipline:
    Engineering and Science