A New Methodology to Process the Total Solar Irradiance observations Using Machine Learning and Data Fusion
Abstract
Across the last decades, various space missions have measured the total solar irradiance (TSI) such as the Variability of Irradiance and Gravity Oscillations (VIRGO) experiment on the Solar and Heliospheric Observatory (SOHO) starting in 1996. Since the beginning of its recording time, one challenge is to correct the measurements from the degradation of the TSI sensors in space. Various groups have proposed different methodologies to produce a continuous TSI time series (TSI composite) which is essential to monitor the sun activity and its influence on the Earth's climate.
However, the benchmark to test all those solutions is source of a debate in the community. Moreover, the input data for the TSI composite are the degradation-corrected measurements provided by each individual instrument team. Here, we propose a different approach using a machine learning and data fusion algorithm to produce automatically the degradation-corrected TSI time series based on a small number of generic assumptions. The algorithm is applied to the VIRGO/PMO6, VIRGO/DIARAD and PREMOS/PMO6 data. The time series agree between each other in terms of mean value with a difference of ~ 0.14 W/m2 (PREMOS), ~ 0.23 W/m2 (VIRGO) and ~ -0.18 W/m2 (DIARAD). Finally, taking a conservative value of 0.3 W/m2 between our different TSI products, induces a variation of the global mean surface temperature of ~ 0.02 K based on global climate simulations, which is within the uncertainties of simulated global mean surface temperatures, hence not impacting significantly any climate forcing scenarios.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMA237...06M
- Keywords:
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- 3305 Climate change and variability;
- ATMOSPHERIC PROCESSES;
- 3359 Radiative processes;
- ATMOSPHERIC PROCESSES;
- 7536 Solar activity cycle;
- SOLAR PHYSICS;
- ASTROPHYSICS;
- AND ASTRONOMY;
- 7538 Solar irradiance;
- SOLAR PHYSICS;
- ASTROPHYSICS;
- AND ASTRONOMY