Harmonizing Sunspot Datasets Consistency: Focusing on SOHO/MDI and SDO/HMI Data
To ensure the long-term consistency of sunspot group data, it is essential to harmonize measurements from SOHO/MDI and SDO/HMI, two major solar observatories with overlapping coverage. In our analysis, we use two complementary sets of data: SOHO/MDI–Debrecen Sunspot Data (SDD) and SDO/HMI–Debrecen S...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Universe |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2218-1997/11/6/176 |
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| Summary: | To ensure the long-term consistency of sunspot group data, it is essential to harmonize measurements from SOHO/MDI and SDO/HMI, two major solar observatories with overlapping coverage. In our analysis, we use two complementary sets of data: SOHO/MDI–Debrecen Sunspot Data (SDD) and SDO/HMI–Debrecen Sunspot Data (HMIDD). Our objective is to identify systematic differences between their recorded parameters and to assess whether their data can be combined into a coherent time series. While the overlap between the datasets spans only about one year, this period allows for a direct statistical comparison without the need for additional image processing. Though the two instruments do not measure identical area values, our results reveal a strong linear relationship between them, which is in line with earlier studies. On the other hand, a systematic discrepancy in their magnetic field strength measurements was observed. Contrary to previous findings, SDO/HMI magnetic field values tend to be higher than those from SOHO/MDI. These differences may arise from the use of different calibration procedures and measurement techniques, or from the physical characteristics of the sunspot groups themselves. These results highlight the challenges involved in unifying data from multiple solar instruments that have been captured over extended time periods. While broad consistencies are observable, the differences between sunspot groups and measurement parameters demonstrate the importance of using careful, instrument-aware calibration approaches when combining such datasets. |
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| ISSN: | 2218-1997 |