Data Fusion of Total Solar Irradiance Composite Time Series Using 41 Years of Satellite Measurements

• Main Authors: Montillet, Jean-Philippe, Finsterle, Wolfgang, Kermarrec, Gael, Sikonja, Rok, Haberreiter, Margit, Schmutz, Werner, de Wit, Thierry Dudok
• Format: Journal Article
• Language: English
• Published: 11-07-2022
• Subjects: Physics - Atmospheric and Oceanic Physics; Physics - Solar and Stellar Astrophysics; Physics - Space Physics
• DOI: 10.48550/arxiv.2207.04926

Journal of Geophysical Research: Atmospheres, 127, e2021JD036146 Since the late 1970s, successive satellite missions have been monitoring the
sun's activity and recording the total solar irradiance (TSI). Some of these
measurements have lasted for more than a decade. In order to obtain a seamless
record whose duration exceeds that of the individual instruments, the time
series have to be merged. Climate models can be better validated using such
long TSI time series which can also help to provide stronger constraints on
past climate reconstructions (e.g., back to the Maunder minimum). We propose a
3-step method based on data fusion, including a stochastic noise model to take
into account short and long-term correlations. Compared with previous products
scaled at the nominal TSI value of 1361 W/m2, the difference is below 0.2 W/m2
in terms of solar minima. Next, we model the frequency spectrum of this 41-year
TSI composite time series with a Generalized Gauss-Markov model to help
describe an observed flattening at high frequencies. It allows us to fit a
linear trend into these TSI time series by joint inversion with the stochastic
noise model via a maximum-likelihood estimator. Our results show that the
amplitude of such trend is $\sim$ -0.004 +/- 0.004 W/(m2yr) for the period 1980
- 2021. These results are compared with the difference of irradiance values
estimated from two consecutive solar minima. We conclude that the trend in
these composite time series is mostly an artifact due to the colored noise.