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Register a new userMethodology to create a new Total Solar Irradiance record: Making a composite out of multiple data records
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Added by
Thierry Dudok de Wit
Publication date
2017
fields
Physics
and research's language is
English
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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
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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.
During the last decades there is a continuing international endeavor in developing realistic space weather prediction tools aiming to forecast the conditions on the Sun and in the interplanetary environment. These efforts have led to the need of developing appropriate metrics in order to assess the performance of those tools. Metrics are necessary for validating models, comparing different models and monitoring adjustments or improvements of a certain model over time. In this work, we introduce the Dynamic Time Warping (DTW) as an alternative way to validate models and, in particular, to quantify differences between observed and synthetic (modeled) time series for space weather purposes. We present the advantages and drawbacks of this method as well as applications on WIND observations and EUHFORIA modeled output at L1. We show that DTW is a useful tool that permits the evaluation of both the fast and slow solar wind. Its distinctive characteristic is that it warps sequences in time, aiming to align them with the minimum cost by using dynamic programming. It can be applied in two different ways for the evaluation of modeled solar wind time series. The first way calculates the so-called sequence similarity factor (SSF), a number that provides a quantification of how good the forecast is, compared to a best and a worst case prediction scenarios. The second way quantifies the time and amplitude differences between the points that are best matched between the two sequences. As a result, it can serve as a hybrid metric between continuous measurements (such as, e.g., the correlation coefficient) and point-by-point comparisons. We conclude that DTW is a promising technique for the assessment of solar wind profiles offering functions that other metrics do not, so that it can give at once the most complete evaluation profile of a model.
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.
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.
Reliable historical records of total solar irradiance (TSI) are needed for climate change attribution and research to assess the extent to which long-term variations in the Suns radiant energy incident on the Earth may exacerbate (or mitigate) the more dominant warming in recent centuries due to increasing concentrations of greenhouse gases. We investigate potential impacts of the new Sunspot Index and Long-term Solar Observations (SILSO) sunspot-number time series on model reconstructions of TSI. In contemporary TSI records, variations on time scales longer than about a day are dominated by the opposing effects of sunspot darkening and facular brightening. These two surface magnetic features, retrieved either from direct observations or from solar activity proxies, are combined in TSI models to reproduce the current TSI observational record. Indices that manifest solar-surface magnetic activity, in particular the sunspot-number record, then enable the reconstruction of historical TSI. Revisions to the sunspot-number record therefore affect the magnitude and temporal structure of TSI variability on centennial time scales according to the model reconstruction methodologies. We estimate the effects of the new SILSO record on two widely used TSI reconstructions, namely the NRLTSI2 and the SATIRE models. We find that the SILSO record has little effect on either model after 1885 but leads to greater amplitude solar-cycle fluctuations in TSI reconstructions prior, suggesting many 18th and 19th century cycles could be similar in amplitude to those of the current Modern Maximum. TSI records based on the revised sunspot data do not suggest a significant change in Maunder Minimum TSI values, and comparing that era to the present we find only very small potential differences in estimated solar contributions to climate with this new sunspot record.
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