MWO polar faculae count calibrated to WSO polar fields and SOHO/MDI polar flux

• Main Authors: A. Muñoz-Jaramillo, N. R. Sheeley, Jr.
• Other Authors: Muñoz-Jaramillo, Andrés
• Language: unknown
• Published: Harvard Dataverse 2016
• Subjects: Astronomy and Astrophysics; Polar Faculae; Solar Polar Fields; Solar Cycle; Solar Dynamo; South Pole; North Pole; Muñoz; South pole
• Online Access: https://doi.org/10.7910/DVN/KF96B2

Citation and Acknowledgements Please cite both this database the paper describing it, as well as adding the following acknowledgement: "MWO calibrated polar faculae data were 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 paper describing this database is A. Muñoz-Jaramillo, N. R. Sheeley Jr., J. Zhang, & E. E. DeLuca, Calibrating 100 years of polar faculae measurements: Implications for the evolution of the heliospheric magnetic field, ApJ, 753, 146 (2012). http://adsabs.harvard.edu/abs/2012ApJ.753.146M Main Limitations The main limitations of these data are: Polar field measurements are limited to a cadence of one measurement per year, and Polar faculae are a strictly possitive quantity. Prior to 1976, magnetic polarity has been assigned by assuming that reversal takes place when facular counts reach a minimum . Description Faculae counted by hand on the best 5 images during the periods of maximum pole coverage (August 15-September 15 for the North pole and February 15-March 15 for the South pole) and averaged. Standard deviation has been turned into standard error by dividing it by sqrt(5). Years with multiple observations have been averaged as well as their their standard errors. Calibration between campaigns was made taking advantage of the overlaps between them. All campaigns were standardized to the values of the 3rd campaign in order to reduce error propagation. Original papers reporting the different data reduction campaigns are: 1st Campaign: Sheeley N. R. Jr. 1964 ApJ 140 731 Sheeley N. R. Jr. 1966 ApJ 144 723 2nd Campaign: Sheeley N. R. Jr. 1976 J. Geophys. Res. 81 3462 3rd Campagin: Sheeley N. R. Jr. 1991 ApJ 374 386 4th Campagin: Sheeley N. R. Jr. 2008 ApJ 680 1553 Calibration factors used were: To turn 1st campaign values into 2nd campaign: ...