Noise and solar-wind/magnetosphere coupling studies: Data
Using artificial data sets it was earlier demonstrated that noise in solar-wind variables alters the functional form of best-fit solar-wind driver functions (coupling functions) of geomagnetic activity. Using real solar-wind data that noise effect is further explored here with an aim at obtaining be...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Astronomy and Space Sciences |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fspas.2022.990789/full |
| _version_ | 1798035771318337536 |
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| author | Joseph E. Borovsky |
| author_facet | Joseph E. Borovsky |
| author_sort | Joseph E. Borovsky |
| collection | DOAJ |
| description | Using artificial data sets it was earlier demonstrated that noise in solar-wind variables alters the functional form of best-fit solar-wind driver functions (coupling functions) of geomagnetic activity. Using real solar-wind data that noise effect is further explored here with an aim at obtaining better best-fit formulas by removing noise in the real solar-wind data. Trends in the changes to best-fit solar-wind formulas are examined when Gaussian random noise is added to the solar-wind variables in a controlled fashion. Extrapolating those trends backward toward lower noise makes predictions for improved solar-wind driver formulas. Some of the error (noise) in solar-wind data comes from using distant L1 monitors for measuring the solar wind at Earth. An attempt is made to confirm the improvements in the solar-wind driver formulas by comparing results of best-fit formulas using L1 spacecraft measurements with best-fit formulas obtained from near-Earth spacecraft measurements from the IMP-8 spacecraft. However, testing this methodology fails owing to observed large variations in the best-fit-formula parameters from year-to-year and spacecraft-to-spacecraft, with these variations probably overwhelming the noise-correction variations. As an alternative to adding Gaussian random noise to the solar-wind variables, replacing a fraction of the values of the variables with other values was explored, yielding essentially the same noise trends as adding Gaussian noise. |
| first_indexed | 2024-04-11T21:01:45Z |
| format | Article |
| id | doaj.art-4e32ca795af74710b00db05785645f30 |
| institution | Directory Open Access Journal |
| issn | 2296-987X |
| language | English |
| last_indexed | 2024-04-11T21:01:45Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Astronomy and Space Sciences |
| spelling | doaj.art-4e32ca795af74710b00db05785645f302022-12-22T04:03:27ZengFrontiers Media S.A.Frontiers in Astronomy and Space Sciences2296-987X2022-09-01910.3389/fspas.2022.990789990789Noise and solar-wind/magnetosphere coupling studies: DataJoseph E. BorovskyUsing artificial data sets it was earlier demonstrated that noise in solar-wind variables alters the functional form of best-fit solar-wind driver functions (coupling functions) of geomagnetic activity. Using real solar-wind data that noise effect is further explored here with an aim at obtaining better best-fit formulas by removing noise in the real solar-wind data. Trends in the changes to best-fit solar-wind formulas are examined when Gaussian random noise is added to the solar-wind variables in a controlled fashion. Extrapolating those trends backward toward lower noise makes predictions for improved solar-wind driver formulas. Some of the error (noise) in solar-wind data comes from using distant L1 monitors for measuring the solar wind at Earth. An attempt is made to confirm the improvements in the solar-wind driver formulas by comparing results of best-fit formulas using L1 spacecraft measurements with best-fit formulas obtained from near-Earth spacecraft measurements from the IMP-8 spacecraft. However, testing this methodology fails owing to observed large variations in the best-fit-formula parameters from year-to-year and spacecraft-to-spacecraft, with these variations probably overwhelming the noise-correction variations. As an alternative to adding Gaussian random noise to the solar-wind variables, replacing a fraction of the values of the variables with other values was explored, yielding essentially the same noise trends as adding Gaussian noise.https://www.frontiersin.org/articles/10.3389/fspas.2022.990789/fullmagnetospheresolar windgeomagnetic activitygeomagnetic indicessolar wind magnetosphere couplingspace weather borovsky: noise solar-wind/magnetosphere coupling |
| spellingShingle | Joseph E. Borovsky Noise and solar-wind/magnetosphere coupling studies: Data Frontiers in Astronomy and Space Sciences magnetosphere solar wind geomagnetic activity geomagnetic indices solar wind magnetosphere coupling space weather borovsky: noise solar-wind/magnetosphere coupling |
| title | Noise and solar-wind/magnetosphere coupling studies: Data |
| title_full | Noise and solar-wind/magnetosphere coupling studies: Data |
| title_fullStr | Noise and solar-wind/magnetosphere coupling studies: Data |
| title_full_unstemmed | Noise and solar-wind/magnetosphere coupling studies: Data |
| title_short | Noise and solar-wind/magnetosphere coupling studies: Data |
| title_sort | noise and solar wind magnetosphere coupling studies data |
| topic | magnetosphere solar wind geomagnetic activity geomagnetic indices solar wind magnetosphere coupling space weather borovsky: noise solar-wind/magnetosphere coupling |
| url | https://www.frontiersin.org/articles/10.3389/fspas.2022.990789/full |
| work_keys_str_mv | AT josepheborovsky noiseandsolarwindmagnetospherecouplingstudiesdata |