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Register a new userModelling solar irradiance from ground-based photometric observations
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Added by
Theodosios Chatzistergos
Publication date
2020
fields
Physics
and research's language is
English
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Total solar irradiance (TSI) has been monitored from space since 1978. The measurements show a prominent variability in phase with the solar cycle, as well as fluctuations on timescales shorter than a few days. However, the measurements were done by multiple and usually relatively short-lived missions making the possible long-term trend in the TSI highly uncertain. While the variability in the UV irradiance is clearly in-phase with the solar cycle, the phase of the variability in the visible range has been debated. In this paper, we aim at getting an insight into the long-term trend of TSI since 1996 and the phase of the solar irradiance variations in the visible part of the spectrum. We use independent ground-based full-disc photometric observations in Ca~II~K and continuum from the Rome and San Fernando observatories to compute the TSI since 1996. We follow the empirical San Fernando approach based on the photometric sum index. We find a weak declining trend in the TSI of -7.8$^{+4.9}_{-0.8}times10^{-3}$ Wm$^{-2}$y$^{-1}$ between the 1996 and 2008 activity minima, while between 2008 and 2019 the reconstructed TSI shows no trend to a marginally decreasing (but statistically insignificant) trend of -0.1$^{+0.25}_{-0.02}times10^{-3}$ Wm$^{-2}$y$^{-1}$. The reference TSI series used for the reconstruction does not significantly affect the determined trend. The variation in the blue continuum (409.2 nm) is rather flat, while the variation in the red continuum (607.1 nm) is marginally in anti-phase, although this result is extremely sensitive to the accurate assessment of the quiet Sun level in the images. These results provide further insights into the long-term variation of the total solar irradiance. The amplitude of the variations in the visible is below the uncertainties of the processing, which prevents an assessment of the phase of the variations.
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Ground-based whole sky imagers (WSIs) can provide localized images of the sky of high temporal and spatial resolution, which permits fine-grained cloud observation. In this paper, we show how images taken by WSIs can be used to estimate solar radiation. Sky cameras are useful here because they provide additional information about cloud movement and coverage, which are otherwise not available from weather station data. Our setup includes ground-based weather stations at the same location as the imagers. We use their measurements to validate our methods.
We aim to gain insight into the effect of network and faculae on solar irradiance from their apparent intensity. Taking full-disc observations from the Solar Dynamics Observatory, we examined the intensity contrast of network and faculae in the continuum and core of the Fe I 6173 {AA} line and 1700 {AA}, including the variation with magnetic flux density, distance from disc centre, nearby magnetic fields, and time. The brightness of network and faculae is believed to be suppressed by nearby magnetic fields from its effect on convection. The difference in intensity contrast between the quiet-Sun network and active region faculae, noted by various studies, arises because active regions are more magnetically crowded and is not due to any fundamental physical differences between network and faculae. These results highlight that solar irradiance models need to include the effect of nearby magnetic fields on network and faculae brightness. We found evidence that suggests that departures from local thermal equilibrium (LTE) might have limited effect on intensity contrast. This could explain why solar irradiance models that are based on the intensity contrast of solar surface magnetic features calculated assuming LTE reproduce the observed spectral variability even where the LTE assumption breaks down. Certain models of solar irradiance employ chromospheric indices as direct indications of the effect of network and faculae on solar irradiance. Based on past studies of the Ca II K line and on the intensity contrast measurements derived here, we show that the fluctuations in chromospheric emission from network and faculae are a reasonable estimate of the emission fluctuations in the middle photosphere, but not of those in the lower photosphere. The data set, which extends from 2010 to 2018, indicates that intensity contrast was stable to about 3% in this period.
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.
Knowledge of solar irradiance variability is critical to Earths climate models and understanding the solar influence on Earths climate. Direct solar irradiance measurements are only available since 1978. Reconstructions of past variability typically rely on sunspot data. These provide only indirect information on the facular and network regions, which are decisive contributors to irradiance variability on timescales of the solar cycle and longer. Our ultimate goal is to reconstruct past solar irradiance variations using historical full-disc Ca II K observations to describe the facular contribution independently of sunspot observations. Here, we develop the method and test it extensively by using modern CCD-based Ca II K observations and carry out initial tests on two photographic archives. We employ carefully reduced and calibrated Ca II K images from 13 datasets, such as those from the Meudon, Mt Wilson, and Rome observatories. We convert them to unsigned magnetograms and then use them as input to the adapted SATIRE model to reconstruct TSI variations over the period 1978-2019, for which direct irradiance measurements are available. The reconstructed TSI from the analysed Ca II K archives agrees well with direct TSI measurements and existing reconstructions. The model also returns good results on data taken with different bandpasses and images with low spatial resolution. Historical Ca II K archives suffer from numerous inconsistencies, but we show that these archives can still be used to reconstruct TSI with reasonable accuracy provided the observations are accurately processed. By using the unsigned magnetograms of the Sun reconstructed from high-quality Ca II K observations as input into the SATIRE model, we can reconstruct solar irradiance variations nearly as accurately as from directly recorded magnetograms.
The lack of long and reliable time series of solar spectral irradiance (SSI) measurements makes an accurate quantification of solar contributions to recent climate change difficult. Whereas earlier SSI observations and models provided a qualitatively consistent picture of the SSI variability, recent measurements by the SORCE satellite suggest a significantly stronger variability in the ultraviolet (UV) spectral range and changes in the visible and near-infrared (NIR) bands in anti-phase with the solar cycle. A number of recent chemistry-climate model (CCM) simulations have shown that this might have significant implications on the Earths atmosphere. Motivated by these results, we summarize here our current knowledge of SSI variability and its impact on Earths climate. We present a detailed overview of existing SSI measurements and provide thorough comparison of models available to date. SSI changes influence the Earths atmosphere, both directly, through changes in shortwave (SW) heating and therefore, temperature and ozone distributions in the stratosphere, and indirectly, through dynamical feedbacks. We investigate these direct and indirect effects using several state-of-the art CCM simulations forced with measured and modeled SSI changes. A unique asset of this study is the use of a common comprehensive approach for an issue that is usually addressed separately by different communities. Omissis. Finally, we discuss the reliability of the available data and we propose additional coordinated work, first to build composite SSI datasets out of scattered observations and to refine current SSI models, and second, to run coordinated CCM experiments.
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