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Revised historical solar irradiance forcing (1804.00287v1)

Published 1 Apr 2018 in astro-ph.SR

Abstract: Context. There is no consensus on the amplitude of the historical solar forcing. The estimated magnitude of the total solar irradiance difference between Maunder minimum and present time ranges from 0.1 to 6 W/m2 making uncertain the simulation of the past and future climate. One reason for this disagreement is the applied evolution of the quiet Sun brightness in the solar irradiance reconstruction models. This work addresses the role of the quiet Sun model choice and updated solar magnetic activity proxies on the solar forcing reconstruction. Aims. We aim to establish a plausible range of the solar irradiance variability on decadal to millennial time scales. Methods. The spectral solar irradiance (SSI) is calculated as a weighted sum of the contributions from sunspot umbra/penumbra, fac- ulae and quiet Sun, which are pre-calculated with the spectral synthesis code NESSY. We introduce activity belts of the contributions from sunspots and faculae and a new structure model for the quietest state of the Sun. We assume that the brightness of the quiet Sun varies in time proportionally to the secular (22-year smoothed) variation of the solar modulation potential. Results. A new reconstruction of the TSI and SSI covering the period 6000 BCE - 2015 CE is presented. The model simulates solar irradiance variability during the satellite era well. The TSI change between the Maunder and recent minima ranges between 3.7 and 4.5 W/m2 depending on the applied solar modulation potential. The implementation of a new quietest Sun model reduces, by approximately a factor of two, the relative solar forcing compared to the largest previous estimation, while the application of updated solar modulation potential increases the forcing difference between Maunder minimum and the present by 25-40 %.

Citations (59)

Summary

  • The paper refines solar irradiance estimates by reducing TSI uncertainty using the CHRONOS model and updated quiet Sun scenarios.
  • It introduces a novel methodology that integrates contributions from sunspots, faculae, and the quiet Sun using advanced solar modulation datasets.
  • Findings show TSI changes of 3.7 to 4.5 W/m², offering crucial insights for more accurate historical climate simulations.

Revised Historical Solar Irradiance Forcing: An Expert Analysis

The paper, "Revised Historical Solar Irradiance Forcing" by Egorova et al., presents a critical examination and update of the methodologies employed to reconstruct historical solar irradiance, focusing on solar forcing over time scales from decades to millennia. The authors emphasize the discrepancies in estimates of total solar irradiance (TSI) variations between the Maunder Minimum and the present, ranging from 0.1 to 6 W/m². They attribute this inconsistency primarily to different models of the quiet Sun's brightness used in irradiance reconstruction.

Methodological Innovations

Egorova et al. introduce advancements to bridge gaps in existing irradiance models. Central to their approach is the CHRONOS (Code for the High spectral ResolutiOn recoNstructiOn of Solar irradiance) model, which refines previous models such as that proposed by Shapiro et al. (2011, SSR11). They incorporate a refined quiet Sun model, based on a re-evaluation of minimum state scenarios, leading to differences in irradiance variability driven by small-scale magnetic fields. This model considers solar magnetic activity proxies like the solar modulation potential to describe the quiet Sun's brightness variations over time.

The authors distinguish between sunspot umbra/penumbra, faculae, and quiet Sun contributions, which are integrated to calculate spectral solar irradiance (SSI). The model uses solar modulation potential from different datasets (PHI-MC17, PHI-US16, PHI-MU16) to provide uncertainty estimates. Importantly, this work reduces the previous uncertainty in solar irradiance variation by half, presenting a more cohesive view of solar influences on climate.

Findings and Implications

The CHRONOS model places the change in TSI from the Maunder Minimum to the present between 3.7 and 4.5 W/m², contrasting with earlier estimates. This finer resolution in TSI variability is significant for climate model inputs, enabling more accurate simulations of historical climate states and improving our understanding of natural climate variability. The use of different solar modulation datasets yields variability estimates for SSI, particularly in UV bands crucial for stratospheric chemistry.

Egorova et al. address observed solar variability effectively, capturing features like the observed enhancement in UV variability at certain wavelengths associated with CN molecule absorption. The implications are profound for understanding solar contributions to climate change over long time scales, providing data to refine past climate models and assess future scenarios under varying solar conditions.

Future Directions

This research sets the stage for further explorations using high-precision solar proxies and potentially validating the model predictions with ongoing and future satellite observations. As solar activity is anticipated to decrease in upcoming solar cycles, presenting an opportunity to validate the CHRONOS predictions, future studies might focus on continuous monitoring of solar modulation potential and its integration into climate models.

Conclusion

The authors provide a robust update to historical solar irradiance forcing models, refining estimates of solar impact on climate through improved treatment of the quiet Sun's influence on irradiance. This research contributes valuable insights into solar-climate interactions, underpinning more reliable future climate projections and facilitating a deeper scientific understanding of solar variability's role in climate systems. As such, the paper presents refined tools and pathways for improving both theoretical understanding and practical applications of climate modeling in the context of historical and potential future solar forcing scenarios.

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