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\begin{document}

\title{Data Fusion of Total Solar Irradiance Composite Time Series Using 41
years of Satellite Measurements}



\author[1,1]{jean-philippe montillet}%
\author[2,2]{Wolfgang Finsterle}%
\author[3,3]{Werner Schmutz}%
\author[4,4]{Margit Haberreiter}%
\author[5,5]{Thierry Dudok de Wit}%
\author[6,6]{Gaël Kermarrec}%
\author[7,7]{Rok sikonja}%
\affil[1]{PMODWRC}%
\affil[2]{PMOD}%
\affil[3]{PMOD/WRC, Switzerland}%
\affil[4]{PMOD/WRC}%
\affil[5]{CNRS, CNES and University of Orléans}%
\affil[6]{Leibniz University Hanover}%
\affil[7]{ETH Zurich}%


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  \date{May 08, 2024}


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\begin{abstract}
Since the late 70's, successive satellite missions have been monitoring
the sun's activity, recording the total solar irradiance (TSI). Some of
these measurements last for more than a decade. It is then mandatory to
merge them to obtain a seamless record whose duration exceeds that of
the individual instruments. Climate models can be better validated using
such long TSI records which can also help provide stronger constraints
on past climate reconstructions (e.g.,back to the Maunder minimum). We
propose a 3-stepmethod based on data fusion, including a stochastic
noise model to take into account short and long-term correlations.
Compared with previous products, the difference in terms of mean value
over the whole time series and at the various solar minima are below
0.2W/m2. Next, we model the frequency spectrum of this 41-year TSI
composite time series with a Generalized Gauss-Markov model to help
describing 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~-0.009\selectlanguage{ngerman}±0.010 W/(m2.yr)
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 com-posite time series is mostly an
artefact due to the coloured noise.%
\end{abstract}\selectlanguage{ngerman}%



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