Investigating solar cycles using mathematical morphology

Investigating solar cycles using mathematical morphology | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Investigating solar cycles using mathematical morphology Cicero. D. Grangeiro, Tharcísyo S. S. Duarte, Jefferson S. da Costa, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5027355/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Jan, 2026 Read the published version in Solar Physics → Version 1 posted 10 You are reading this latest preprint version Abstract In this study, we report on the processing and analysis of around 9700 images of the solar disk, obtained from the SOHO and SDO satellites, available in the Helioviewer database. Using our own code, PyMoST (Python Morphological Sunspot Tracker), which employs a mathematical morphology technique, we were able to automatically track and analyze approximately 50000 sunspots in these images, covering the period from January 1, 1998 to July 31, 2024. By using PyMoST we were able to obtain the distribution of the number of spots as a function of solar latitude and time, accurately reproducing solar cycles 23, 24 and the current phase of solar cycle 25, in agreement with the literature. In addition, our code was also able to determine the areas and number of sunspots, showing excellent correlation with the results reported by the Royal Greenwich Observatory (RGO), Kodaikanal Solar Observatory (KSO) and the International Sunspot Number - Solar Influences Data Analysis Center (SIDIC), thus consolidating the efficiency of our tool and its importance for the investigation of solar magnetic activity. Sunspots Solar Cycle Observations Full Text Additional Declarations No competing interests reported. Supplementary Files PyMostResults.zip Cite Share Download PDF Status: Published Journal Publication published 05 Jan, 2026 Read the published version in Solar Physics → Version 1 posted Editorial decision: Revision requested 18 Mar, 2025 Reviews received at journal 18 Mar, 2025 Reviewers agreed at journal 12 Mar, 2025 Reviewers agreed at journal 27 Jan, 2025 Reviewers agreed at journal 22 Nov, 2024 Reviewers agreed at journal 18 Sep, 2024 Reviewers invited by journal 16 Sep, 2024 Editor assigned by journal 05 Sep, 2024 Submission checks completed at journal 05 Sep, 2024 First submitted to journal 03 Sep, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5027355","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":355878825,"identity":"92e6c823-794c-4aea-acf3-1cd23df18923","order_by":0,"name":"Cicero. D. 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