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Register a new userACRIM total solar irradiance satellite composite validation versus TSI proxy models
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The satellite total solar irradiance (TSI) database provides a valuable record for investigating models of solar variation used to interpret climate changes. The 35-year ACRIM TSI satellite composite was updated using corrections to ACRIMSAT/ACRIM3 results derived from recent testing at the Laboratory for Atmospheric and Space Physics/Total solar irradiance Radiometer Facility (LASP/TRF). The corrections lower the ACRIM3 scale by ~5000 ppm, in close agreement with the scale of SORCE/TIM results (solar constant ~1361 W/m^2). Relative variations and trends are not changed. Differences between the ACRIM and PMOD TSI composites, e.g. the decadal trending during solar cycles 21-22, are tested against a set of solar proxy models, including analysis of Nimbus7/ERB and ERBS/ERBE results available to bridge the ACRIM Gap (1989-1992). Our findings confirm: (1) The validity of the TSI peak in the originally published ERB results in early 1979 during solar cycle 21; (2) The correctness of originally published ACRIM1 results during the SMM spin mode (1981-1984); (3) The upward trend of originally published ERB results during the ACRIM Gap; (4) The occurrence of a significant upward TSI trend between the minima of solar cycles 21 and 22 and (5) a decreasing trend during solar cycles 22-23. Our findings do not support: (1) The downward corrections to originally published ERB and ACRIM1 results during solar cycle 21; (2) A step function sensitivity change in ERB results at the end-of-September 1989; (3) the validity of ERBEs downward trend during the ACRIM Gap or (4) the use of ERBE results to bridge the ACRIM Gap. Our analysis provides a first order validation of the ACRIM TSI composite approach and its 0.037%/decade upward trend during solar cycles 21-22. Thus, solar forcing of climate change may be a significantly larger factor than represented in the CMIP5 general circulation climate models.
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Many observational records critically rely on our ability to merge different (and not necessarily overlapping) observations into a single composite. We provide a novel and fully-traceable approach for doing so, which relies on a multi-scale maximum likelihood estimator. This approach overcomes the problem of data gaps in a natural way and uses data-driven estimates of the uncertainties. We apply it to the total solar irradiance (TSI) composite, which is currently being revised and is critical to our understanding of solar radiative forcing. While the final composite is pending decisions on what corrections to apply to the original observations, we find that the new composite is in closest agreement with the PMOD composite and the NRLTSI2 model. In addition, we evaluate long-term uncertainties in the TSI, which reveal a 1/f scaling
The Earths primary source of energy is the radiant energy generated by the Sun, which is referred to as solar irradiance, or total solar irradiance (TSI) when all of the radiation is measured. A minor change in the solar irradiance can have a significant impact on the Earths climate and atmosphere. As a result, studying and measuring solar irradiance is crucial in understanding climate changes and solar variability. Several methods have been developed to reconstruct total solar irradiance for long and short periods of time; however, they are physics-based and rely on the availability of data, which does not go beyond 9,000 years. In this paper we propose a new method, called TSInet, to reconstruct total solar irradiance by deep learning for short and long periods of time that span beyond the physical models data availability. On the data that are available, our method agrees well with the state-of-the-art physics-based reconstruction models. To our knowledge, this is the first time that deep learning has been used to reconstruct total solar irradiance for more than 9,000 years.
Data gaps are ubiquitous in spectral irradiance data, and yet, little effort has been put into finding robust methods for filling them. We introduce a data-adaptive and nonparametric method that allows us to fill data gaps in multi-wavelength or in multichannel records. This method, which is based on the iterative singular value decomposition, uses the coherency between simultaneous measurements at different wavelengths (or between different proxies) to fill the missing data in a self-consistent way. The interpolation is improved by handling different time scales separately. Two major assets of this method are its simplicity, with few tuneable parameters, and its robustness. Two examples of missing data are given: one from solar EUV observations, and one from solar proxy data. The method is also appropriate for building a composite out of partly overlapping records.
We analyze the long-term behavior of supergranule scale parameter, in active and quiet regions (AR, QR), using the Kodaikanal digitized data archive. This database provides century-long daily full disc observations of the Sun in Ca-II K wavelength. In this paper, we study the distributions of the supergranular scales, over the whole data duration, which show identical shape in these two regimes. We found that the AR mean scale values are always higher than that of the QR for every solar cycle. The mean scale values are highly correlated with the sunspot number cycle amplitude and also with total solar irradiance (TSI) variations. Such correlation establishes the cycle-wise mean scale as a potential calibrator for the historical data reconstructions. We also see an upward trend in the mean scales, as already been reported in TSI. This may provide new input for climate forcing models. These results also give us insight into the different evolutionary scenarios of the supergranules in the presence of strong (AR) and weak (QR) magnetic fields.
The variation of total solar irradiance (TSI) has been measured since 1978 and that of the spectral irradiance for an even shorter amount of time. Semi-empirical models are now available that reproduce over 80% of the measured irradiance variations. An extension of these models into the more distant past is needed in order to serve as input to climate simulations. Here we review our most recent efforts to model solar total and spectral irradiance on time scales from days to centuries and even longer. Solar spectral irradiance has been reconstructed since 1947. Reconstruction of solar total irradiance goes back to 1610 and suggests a value of about 1-1.5 Wm$^{-2}$ for the increase in the cycle-averaged TSI since the end of the Maunder minimum, which is significantly lower than previously assumed but agrees with other modern models. First steps have also been made towards reconstructions of solar total and spectral irradiance on time scales of millennia.
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