Record Details

MDI active region evolution videos for BARD catalog

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Field Value
 
Title MDI active region evolution videos for BARD catalog
 
Identifier https://doi.org/10.7910/DVN/6F25MG
 
Creator Lamb, Derek
Chatterjee, Subhamoy
Muñoz-Jaramillo, Andrés
 
Publisher Harvard Dataverse
 
Description Citation and Acknowledgements


Please cite both this database the paper describing it, as well as adding the following acknowledgement:


"The BARD catalog of BMRs was downloaded from the solar dynamo dataverse (https://dataverse.harvard.edu/dataverse/solardynamo), maintained by Andrés Muñoz-Jaramillo."




Database citation format is shown at the top of this page, underneath the database title. It can be downloaded in a variety of formats directly from this page




The papers describing this database are




S. Chatterjee, A. Munoz-Jaramillo, & D. Lamb. Human-efficient labeling of a solar flux emergence video dataset by a deep learning model, 27 May 2021, PREPRINT (Version 1) available at Research Square https://doi.org/10.21203/rs.3.rs-366908/v1




A. Munoz-Jaramillo, Z. A. Werginz, J. P. Vargas-Acosta, M. D. DeLuca, J. C. Windmueller, J. Zhang, D. W. Longcope, D. A. Lamb, C. E. DeForest, S. Vargas-Dominguez, J. W. Harvey, & P. C. H. Martens , IEEE International Conference on Big Data, 3194 (2016). https://ieeexplore.ieee.org/document/7840975




A. Munoz-Jaramillo, B. Navarrete, & L. A. Campusano , The Astrophysical Journal, Volume 920, Issue 1, id.31, 11 pp. https://ui.adsabs.harvard.edu/abs/2021ApJ...920...31M



Main Limitations


The main limitations of these data are:




  1. Videos are assembled in a constant Carrington rotation frame so, BMRs may drift within the video due to differential rotation.


  2. Many videos have gaps and thus, do not have a constant cadence. We addressed this by interpolating the missing frames. In these videos we do not include interpolated frames
    .





Description

The Active Region (AR) magnetic evolution videos are created by -


  1. Projecting full-disc line-of-sight magnetograms into Carrington grid

  2. Dividing the projected maps into 15 degrees x 15 degrees non-overlapping patches. Each patch is sampled into 90 pixels x 90 pixels resulting into pixel scale of (1/6) degree

  3. Stacking a set of consecutive frames covering about half a solar rotation tied to each AR from Bipolar Active Region Detection (BARD) catalogue


A total of 2453 videos are available over the period 1996 - 2011 in 'fits' format. Within the 'fits' header-

  1. 'NAXIS1' represents number of x-pixels

  2. 'NAXIS2' represents number of y-pixels

  3. 'NAXIS3' represents number of frames

  4. 'TIMEXXXX' represents the time stamp for frame XXXX in YYYY-MM-DDTHH:MM:SS format

  5. 'CRVAL1' represents the starting Carrington Longitude (degrees) for each video

  6. 'CRVAL2' represents the starting Latitude (degrees) for each video


Each video is manually verified and a label of '0' or '1' is added to the name of video with '0' representing 'no new AR emergence within the video' and '1' representing 'AR emergence'.
 
Subject Physics
Sun
Solar
Magnetic Fields
Active Regions
Machine Learning
Mangetic field emergence
 
Contributor Muñoz-Jaramillo, Andrés