TY - JOUR

T1 - Data Fusion of Total Solar Irradiance Composite Time Series Using 41 Years of Satellite Measurements

AU - Montillet, J. P.

AU - Finsterle, W.

AU - Kermarrec, G.

AU - Sikonja, R.

AU - Haberreiter, M.

AU - Schmutz, W.

AU - Dudok de Wit, T.

N1 - Funding Information: We acknowledge the life-long dedication to the total solar irradiance (TSI) community of the late Dr. Claus Fröhlich in memoriam as a former director of PMOD/WRC, PI of SOHO/VIRGO and his invaluable contribution to the analysis of TSI observations. Among them, he produced the first reconstruction of the TSI composite in 2006 which is also used in this work (i.e., C3). Dr. J.-P. Montillet, Dr. W. Finsterle, Dr. M. Haberreiter and Prof. W. Schmutz gratefully acknowledge the support from the Karbacher-Funds. Dr. G. Kermarrec would like to acknowledge the Deutsche Forschungsgemeinschaft under the project KE2453/2-1 which permitted the development of the wavelet filter to analyze correlated noise, opening the door for further studies related to laser observations. The authors thank the anonymous reviewers whose comments/suggestions helped improve and clarify this manuscript.

PY - 2022/7/2

Y1 - 2022/7/2

N2 - 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 ∼−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.

AB - 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 ∼−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.

KW - data fusion

KW - solar physics

KW - stochastic processes

KW - time series analysis

KW - total solar irradiance

UR - http://www.scopus.com/inward/record.url?scp=85133939597&partnerID=8YFLogxK

U2 - 10.1029/2021JD036146

DO - 10.1029/2021JD036146

M3 - Article

AN - SCOPUS:85133939597

VL - 127

JO - Journal of Geophysical Research: Atmospheres

JF - Journal of Geophysical Research: Atmospheres

SN - 2169-897X

IS - 13

M1 - e2021JD036146

ER -