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Comparison of the ACRIM and PMOD Composite TSI time series. The most significant difference is the ACRIM composite’s + 0.037 %/decade trend during solar cycles 21–23. Different results near the maxima of solar cycles 21 and 22 are caused by PMOD alteration of some Nimbus7/ERB, ACRIM1 and ACRIM2 results to conform the TSI to the predictions of TSI proxy models
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The effects of scattering and diffraction on the observations of the ACRIMSAT/ACRIM3 satellite TSI monitoring mission have been characterized by the preflight calibration approach for satellite total solar irradiance (TSI) sensors implemented at the LASP/TRF (Laboratory for Atmospheric and Space Physics/Total Solar Irradiance Radiometer Facility)....
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... between the two TSI composites are shown in Fig. 7. The most obvious and significant is the so- lar minimum-to-minimum trend during solar cycles 21-23. ACRIM minima levels show an increase from 1980 to 2000 and a decrease afterward. PMOD shows a continuous de- crease since 1978. Other significant differences can be seen during the peak of solar cycles 21 and 22. These arise from ...
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... Earth's revolution causes periodic changes in the Sun's position relative to the equatorial plane. When Earth is at different positions on its elliptical orbit around the Sun, seasonal changes are formed [67][68][69][70][71] . Different seasons and regions receive varying amounts of solar radiation, directly influencing atmospheric temperature and the evaporation and precipitation of water vapor. ...
A few people have gradually realized that the superposition effect of different planets in the solar system on Earth under high-speed motion and dynamic equilibrium can sometimes trigger extreme natural disasters. Due to the relatively regular changes in the relative positions of the Sun, Moon, and Earth, this study considers these three planets as independent systems. The orbits of other planets in the solar system have relatively complex changes in their positions relative to Earth, so they are considered as a whole. By constructing a dynamic quantification model based on proximity difference to eliminate the interference of internal variability of the Earth and extract the influence of different planetary orbit changes on the variation of atmospheric water vapor content, the analysis shows that Earth's rotation accounts for 4%, the Moon's revolution 10%, Earth's revolution 71%, and other planetary orbits 15% of the total impact of planetary orbital changes on atmospheric water vapor. Finally, an LSTM deep learning model was constructed to predict the changes in atmospheric water vapor content on Earth over the next decade, and the results showed that atmospheric water vapor will show a slow upward trend in the future. The research results not only provide a new perspective for understanding the mechanisms of climate change on Earth, but also provide valuable references for the study of climate evolution on other planets.
... and are the maximum and minimum hourly temperatures of year , respectively. 10 This study defines that the contribution of different orbits to the annual Earth's temperature perturbations is equal to the annual temperature variation caused by different orbits divided by the maximum annual temperature variation. Therefore, the contributions of Earth's rotation and revolution to the intra-annual fluctuation of Earth's temperature are calculated by dividing the magnitude of intra-annual temperature variations caused by each of them by the highest annual 15 temperature change (see Eqs. 20−21). ...
... To eliminate the impact of large variations in CO2 concentration in two successive days on temperature, we utilized only D2 values for days in which the CO2 concentration was relatively stable. 10 The changes in the Earth's temperature during each year can be attributed to the variations in solar radiation absorbed by the land and the speed of the Earth's rotation, which are induced by the Earth's revolution to a certain extent ( Supplementary Section 1.3). Thus, the intra-annual temperature change can be used to quantify the contribution of the Earth's revolution to the temperature. ...
... Equation 24 can be rewritten as 25 based on the near-linear relationship between CO2 and Earth's temperature change 13 . 10 where + , is the difference in CO2 concentration between years i+s and i. is the value of the Earth's temperature change caused by 1 ppm CO2. ...
Existing climate studies mainly assessed the effect of greenhouse gases and aerosols, among other forcings on Earth’s temperature. None of them has not evaluated the effect of the planetary orbital changes on Earth’s temperature. Here, we deconvolved the effects of greenhouse gases and planetary orbital changes on Earth’s temperature and to forecast the latter at different time scales. Our results suggest that Earth’s revolution and rotation prompted ~75.4% and 15.9% of the observed Earth’s intra-annual temperature changes, while Moon’s revolution and other planet motions accounted for 8.3% and 0.3%, respectively. Planetary orbits contributed to ~11.5% of global warming since 1837 and will continue to warm the Earth by ~0.13 °C from 2020 to 2027. However, planetary orbits may trigger ~0.25 °C of Earth’s cooling from 2027 to 2050, which is still far below the impact of CO2 and will not be enough to reverse the warming trend.
... We use a linear drift term, c s τ t,s , to account for the harsh conditions of the space environment that can degrade space-borne TSI instruments over time (Kopp, 2014). These drifts have also been empirically observed through the direct inter-comparison of overlapping satellite missions and have been described as primarily linear (Fröhlich, 2009;Lockwood & Ball, 2020;Willson, 2014), although nonlinear long-term correlations have also been observed to contribute to 1/f scaling of satellite errors in frequency space (Dudok de Wit et al., 2017). Solar-exposure degradation can be corrected through redundant sensors, but there remain effects that can bias satellite-based observations. ...
Differences among total solar irradiance (TSI) estimates are most pronounced during the so‐called “ACRIM Gap” of 1989–1991, when available satellite‐based observations disagree in trend and no observations exist from satellites with on‐board calibration. Different approaches to bias‐correcting noisy satellite‐based observations lead to discrepancies of up to 0.7 W/m² in the change in TSI during the Gap. Using a Bayesian hierarchical model for TSI (BTSI), we jointly infer TSI during the ACRIM Gap from satellite‐based observations and proxies of solar activity. In addition, BTSI yields estimates of noise and drift in satellite‐based observations and calibration for proxy records. We find that TSI across the ACRIM Gap changes by only 0.01 W/m², with a 95% confidence interval of [−0.07, 0.09] W/m². Our results are consistent with the PMOD CPMDF and Community Consensus TSI reconstructions and inconsistent with the 0.7 W/m² trend reported in the ACRIM composite reconstruction. Constraints on the trend across the ACRIM Gap are primarily obtained through constraints on the drift in the Nimbus‐7 satellite that are afforded by overlapping satellite and proxy observations.
... The EMD (e.g., Huang et al. 1998) of the solar modulation potential, described in Section 4, provides the long-term modulation, while the dimensionless weights of the plage and sunspot coverages are obtained by fitting with available TSI data, as provided by PMOD composite (Willson 2014). 4 ...
The total solar irradiance (TSI) varies on timescales of minutes to centuries. On short timescales it varies due to the superposition of intensity fluctuations produced by turbulent convection and acoustic oscillations. On longer timescales, it changes due to photospheric magnetic activity, mainly because of the facular brightenings and dimmings caused by sunspots. While modern TSI variations have been monitored from space since the 1970s, TSI variations over much longer periods can only be estimated either using historical observations of magnetic features, possibly supported by flux transport models, or from the measurements of the cosmogenic isotope (e.g., ¹⁴ C or ¹⁰ Be) concentrations in tree rings and ice cores. The reconstruction of the TSI in the last few centuries, particularly in the 17th/18th centuries during the Maunder minimum, is of primary importance for studying climatic effects. To separate the temporal components of the irradiance variations, specifically the magnetic cycle from secular variability, we decomposed the signals associated with historical observations of magnetic features and the solar modulation potential Φ by applying an empirical mode decomposition algorithm. Thus, the reconstruction is empirical and does not require any feature contrast or field transport model. The assessed difference between the mean value during the Maunder minimum and the present value is ≃2.5 W m ⁻² . Moreover it shows, in the first half of the last century, a growth of ≃1.5 W m ⁻² , which stops around the middle of the century to remain constant for the next 50 years, apart from the modulation due to the solar cycle.
... The issue remains unresolved. What we do have now is a good measure of the temporal variation of the total solar irradiance (Willson, 2014), and Peter and his colleagues have provided a plausible explanation of how the angular variation of radiation from active regions is responsible (Foukal et al., 2006). As I presented soon afterwards at a celebration in Davos of Claus Fröhlich's seventieth birthday, that variation is responsible for the (temporal mean) solar luminosity being of order 0.15 per cent higher than that normally inferred by assuming the Sun to radiate spherically symmetrically. ...
This is a summary of my scientific career, biased by my personal view of events and unashamedly concentrating on those aspects of some of the scientific developments to which I have contributed. A selective unbiased alternative has been written by Christensen-Dalsgaard and Thompson (A selective overview. In: Thompson, M.J., Christensen-Dalsgaard, J. (Eds.) Stellar Astrophysical Fluid Dynamics , Cambridge University Press, pp. 1 – 19, 2003), followed by some further remarks by Christensen-Dalsgaard ( Unsolved Problems in Stellar Physics: A Conference in Honour of Douglas Gough , American Institute of Physics Conference Series, 948, xii, 2007).
... In 2005, estimating the sources of uncertainty in a joint effort, including in-orbit degradation of different instruments, the values indicated varied from 0 (ERBE) to 2930 (PMO6V) ppm year −1 . The declared degradation of the ACRIM3 primary sensor has been 900 ppm during the 13 1/ 2 years [10]. The TIM shows primary sensor degradation of 200 ppm in 10 years [11]. ...
Long and reliable total solar irradiance (TSI) time series is one of the essential parameters for understanding solar contributions to climate change. The minor fluctuations of TSI in long timescales could impact the energy balance. Despite the improvement of accurate measurements provided by the instruments, at the time, long-term TSI variability and its effects had not been established. The space-borne radiometer era provided observations in short timescales from minutes to years. Therefore, this study presents an overview of irradiance observations, highlighting the importance of following its variability in different time scales. In this context, the Galileo Solar Space Telescope that has been developed by the Institute for Space Research (INPE), Brazil, includes the Irradiance Monitor Module with a radiometer cavity like the classical design and a next-generation compact radiometer.
... The high scatter was largely the cause of the higher TSI values reported by the other flight TSI instruments, as explained by Kopp and Lean (2011) as being due to a different optical-aperture configuration in all non-TIM instruments. Subsequent corrections based on these TRF diagnostics were retroactively applied to the flight data of those other instruments; first for the ACRIM3 in 2011 (Willson, 2014) and then the VIRGO in 2014 (Fröhlich, 2014), with both being approximately 0.35% erroneously high prior. The Picard/PREMOS, the TSI Continuity Transfer Experiment (TCTE)/TIM, and the Total Spectral and Solar Irradiance Sensor (TSIS-1)/TIM were all calibrated (for the PREMOS; Schmutz et al., 2013) or validated (for the TCTE and TSIS-1 TIMs) on the TRF prior to launch, and all have transferred that calibration to orbit and confirmed the lower TSI value established by the SORCE/TIM. ...
The final version (V.19) of the total solar irradiance data from the SOlar Radiation and Climate Experiment (SORCE) Total Irradiance Monitor has been released. This version includes all calibrations updated to the end of the mission and provides irradiance data from 25 February 2003 through 25 February 2020. These final calibrations are presented along with the resulting final data products. An overview of the on-orbit operations timeline is provided as well as the associated changes in the time-dependent uncertainties. Scientific highlights from the instrument are also presented. These include the establishment of a new, lower TSI value; accuracy improvements to other TSI instruments via a new calibration facility; the lowest on-orbit noise (for high sensitivity to solar variability) of any TSI instrument; the best inherent stability of any on-orbit TSI instrument; a lengthy (17-year) measurement record benefitting from these stable, low-noise measurements; the first reported detection of a solar flare in TSI; and observations of two Venus transits and four Mercury transits.
... This work looks at the development of composite time series based on measurements from different radiometers. TSI satellite composites are at present available: PMOD [90][91][92]; ACRIM [93][94][95], RMIB-TSI [84]; SATIRE [96,97] and Gueymard [12]. The PMOD composite is based on the ACRIM, SMM, and the data from ERBE. ...
Many Total Solar Irradiance (TSI) and Solar Constant (SC) values are given and used in the literature, sometimes leading to confusion. The TSI value is relevant and has great importance in engineering and scientific research in energy. In this study, a review has been done to study the TSI and SC concepts. A reevaluation of the TSI and SC is undertaken to consider state of the art. The effect of three different TSI values concerning different locations is studied for estimating global radiation with the Ångström-Prescott (A-P) formulation over Spain. New seasonal A-P coefficient sets are developed for Spain. The good performance for all the 29 stations and seasons and the slight differences observed for the different TSI values employed ensure global solar radiation (GSR) accuracy with the A-P model. The results highlight the local and seasonal A-P coefficient calibration relevance instead of using a single general pair of calibration coefficients. Based on the TSI study, we recommended calculations of solar radiation models to adopt the TSI value equal to 1361 W·m-2. The revised TSI is lower than the previous values proposed. Therefore, it is highly recommended to review the value and concept of TSI.
... Although each satellite mission typically provides TSI data for only 10 to 15 years, and the data can be affected by gradual long-term orbital drifts and/or instrumental errors that can be hard to identify and quantify [149], there has been an almost continuous series of TSI-monitoring satellite missions since those two initial U.S. missions, including European missions, e.g., SOVAP/Picard [150] and Chinese missions [151,152] as well as international collaborations, e.g., VIRGO/SOHO [153], and further U.S. missions, e.g., ACRIMSAT/ACRIM3 [154] and SORCE/TIM [155]. Therefore, in principle, by rescaling the measurements from different parallel missions so that they have the same values during the periods of overlap, it is possible to construct a continuous time series of TSI from the late-1970s to the present. ...
... The composite of the ACRIM group that was in charge of the three ACRIM satellite missions (ACRIM1, ACRIM2 and ACRIM3) suggests that TSI generally increased during the 1980s and 1990s but has slightly declined since then [52,60,154,159]. The Royal Meteorological Institute of Belgium (RMIB)'s composite implies that, aside from the sunspot cycle, TSI has remained fairly constant since at least the 1980s [160]. ...
... Therefore, the debate over these three rival TSI datasets for the satellite era is quite important. If the ACRIM dataset is correct, then it suggests that much of the global temperature trends during the satellite era could have been due to changes in TSI [29,35,41,42,52,60,154,159]. However, if the PMOD dataset is correct, and we assume for simplicity a linear relationship between TSI and global temperatures, then the implied global temperature trends from changes in TSI would exhibit long-term global cooling since at least the late-1970s. ...
In order to evaluate how much Total Solar Irradiance (TSI) has influenced Northern Hemisphere surface air temperature trends, it is important to have reliable estimates of both quantities. Sixteen different estimates of the changes in Total Solar Irradiance (TSI) since at least the 19th century were compiled from the literature. Half of these estimates are “low variability” and half are “high variability”. Meanwhile, five largely-independent methods for estimating Northern Hemisphere temperature trends were evaluated using: 1) only rural weather stations; 2) all available stations whether urban or rural (the standard approach); 3) only sea surface temperatures; 4) tree-ring widths as temperature proxies; 5) glacier length records as temperature proxies. The standard estimates which use urban as well as rural stations were somewhat anomalous as they implied a much greater warming in recent decades than the other estimates, suggesting that urbanization bias might still be a problem in current global temperature datasets - despite the conclusions of some earlier studies. Nonetheless, all five estimates confirm that it is currently warmer than the late 19th century, i.e., there has been some “global warming” since the 19th century. For each of the five estimates of Northern Hemisphere temperatures, the contribution from direct solar forcing for all sixteen estimates of TSI was evaluated using simple linear least-squares fitting. The role of human activity on recent warming was then calculated by fitting the residuals to the UN IPCC’s recommended “anthropogenic forcings” time series. For all five Northern Hemisphere temperature series, different TSI estimates suggest everything from no role for the Sun in recent decades (implying that recent global warming is mostly human-caused) to most of the recent global warming being due to changes in solar activity (that is, that recent global warming is mostly natural). It appears that previous studies (including the most recent IPCC reports) which had prematurely concluded the former, had done so because they failed to adequately consider all the relevant estimates of TSI and/or to satisfactorily address the uncertainties still associated with Northern Hemisphere temperature trend estimates. Therefore, several recommendations on how the scientific community can more satisfactorily resolve these issues are provided.
... Although each satellite mission typically provides TSI data for only 10 to 15 years, and the data can be affected by gradual long-term orbital drifts and/or instrumental errors that can be hard to identify and quantify [149], there has been an almost continuous series of TSI-monitoring satellite missions since those two initial U.S. missions, including European missions, e.g., SOVAP/Picard [150] and Chinese missions [151,152] as well as international collaborations, e.g., VIRGO/SOHO [153], and further U.S. missions, e.g., ACRIMSAT/ACRIM3 [154] and SORCE/TIM [155]. Therefore, in principle, by rescaling the measurements from different parallel missions so that they have the same values during the periods of overlap, it is possible to construct a continuous time series of TSI from the late-1970s to the present. ...
... The composite of the ACRIM group that was in charge of the three ACRIM satellite missions (ACRIM1, ACRIM2 and ACRIM3) suggests that TSI generally increased during the 1980s and 1990s but has slightly declined since then [52,60,154,159]. The Royal Meteorological Institute of Belgium (RMIB)'s composite implies that, aside from the sunspot cycle, TSI has remained fairly constant since at least the 1980s [160]. ...
... Therefore, the debate over these three rival TSI datasets for the satellite era is quite important. If the ACRIM dataset is correct, then it suggests that much of the global temperature trends during the satellite era could have been due to changes in TSI [29,35,41,42,52,60,154,159]. However, if the PMOD dataset is correct, and we assume for simplicity a linear relationship between TSI and global temperatures, then the implied global temperature trends from changes in TSI would exhibit long-term global cooling since at least the late-1970s. ...
To evaluate the role of Total Solar Irradiance (TSI) on Northern Hemisphere (NH) surface air temperature trends it is important to have reliable estimates of both quantities. 16 different TSI estimates were compiled from the literature. 1/2 of these estimates are low variability and 1/2 are high variability. 5 largely-independent methods for estimating NH temperature trends were evaluated using: 1) only rural weather stations; 2) all available stations whether urban or rural (the standard approach); 3) only sea surface temperatures; 4) tree-ring temperature proxies; 5) glacier length temperature proxies. The standard estimates using urban as well as rural stations were anomalous as they implied a much greater warming in recent decades than the other estimates. This suggests urbanization bias might still be a problem in current global temperature datasets despite the conclusions of some earlier studies. Still, all 5 estimates confirm it is currently warmer than the late 19th century, i.e., there has been some global warming since 1850. For the 5 estimates of NH temperatures, the contribution from direct solar forcing for all 16 estimates of TSI was evaluated using simple linear least-squares fitting. The role of human activity in recent warming was then calculated by fitting the residuals to the UN IPCC's recommended anthropogenic forcings time series. For all 5 NH temperature series, different TSI estimates implied everything from recent global warming being mostly human-caused to it being mostly natural. It seems previous studies (including the most recent IPCC reports) that had prematurely concluded the former failed to adequately consider all the relevant estimates of TSI and/or to satisfactorily address the uncertainties still associated with NH temperature trend estimates. Several recommendations are provided on how future research could more satisfactorily resolve these issues.