Matthes, K., Funke, B., Andersson, M. E., Barnard, L., Beer, J., Charbonneau, P., Clilverd, M. A., Dudok de Wit, T., Haberreiter, M., Hendry, A., Jackman, C. H., Kretzschmar, M., Kruschke, T., Kunze, M., Langematz, U., Marsh, D. R., Maycock, A. C., Misios, S., Rodger, C. J., Scaife, A. A., Seppälä, A., Shangguan, M., Sinnhuber, M., Tourpali, K., Usoskin, I., van de Kamp, M., Verronen, P. T., and Versick, S.: Solar forcing for CMIP6 (v3.2), Geosci. Model Dev., 10, 2247-2302, https://doi.org/10.5194/gmd-10-2247-2017, 2017
Solar forcing for CMIP6 (v3.2)
|Author:||Matthes, Katja1,2; Funke, Bernd3; Andersson, Monika E.4;|
1GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
2Christian-Albrechts-Universität zu Kiel, Kiel, Germany
3Instituto de Astrofísica de Andalucía (CSIC), Granada, Spain
4Finnish Meteorological Institute, Helsinki, Finland
5University of Reading, Reading, UK
6EAWAG, Dübendorf, Switzerland
7University of Montreal, Montreal, Canada
8British Antarctic Survey (NERC), Cambridge, UK
9Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center, Davos, Switzerland
10Department of Physics, University of Otago, Dunedin, New Zealand
11Emeritus, NASA Goddard Space Flight Center, Greenbelt, MD, USA
12LPC2E, CNRS and University of Orléans, Orléans, France
13Freie Universität Berlin, Berlin, Germany
14National Center for Atmospheric Research, Boulder, CO, USA
15University of Leeds, Leeds, UK
16Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece
17Met Office Hadley Centre, Fitz Roy Road, Exeter, Devon, UK
18Karlsruhe Institute of Technology, Karlsruhe, Germany
19Space Climate Research Unit and Sodankylä Geophysical Observatory, University of Oulu, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 14.1 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe201706277487
|Publish Date:|| 2017-06-27
This paper describes the recommended solar forcing dataset for CMIP6 and highlights changes with respect to CMIP5. The solar forcing is provided for radiative properties, namely total solar irradiance (TSI), solar spectral irradiance (SSI), and the F10.7 index as well as particle forcing, including geomagnetic indices Ap and Kp, and ionization rates to account for effects of solar protons, electrons, and galactic cosmic rays. This is the first time that a recommendation for solar-driven particle forcing has been provided for a CMIP exercise. The solar forcing datasets are provided at daily and monthly resolution separately for the CMIP6 preindustrial control, historical (1850–2014), and future (2015–2300) simulations. For the preindustrial control simulation, both constant and time-varying solar forcing components are provided, with the latter including variability on 11-year and shorter timescales but no long-term changes. For the future, we provide a realistic scenario of what solar behavior could be, as well as an additional extreme Maunder-minimum-like sensitivity scenario. This paper describes the forcing datasets and also provides detailed recommendations as to their implementation in current climate models.
For the historical simulations, the TSI and SSI time series are defined as the average of two solar irradiance models that are adapted to CMIP6 needs: an empirical one (NRLTSI2–NRLSSI2) and a semi-empirical one (SATIRE). A new and lower TSI value is recommended: the contemporary solar-cycle average is now 1361.0 W m⁻². The slight negative trend in TSI over the three most recent solar cycles in the CMIP6 dataset leads to only a small global radiative forcing of −0.04 W m⁻². In the 200–400 nm wavelength range, which is important for ozone photochemistry, the CMIP6 solar forcing dataset shows a larger solar-cycle variability contribution to TSI than in CMIP5 (50 % compared to 35 %).
We compare the climatic effects of the CMIP6 solar forcing dataset to its CMIP5 predecessor by using time-slice experiments of two chemistry–climate models and a reference radiative transfer model. The differences in the long-term mean SSI in the CMIP6 dataset, compared to CMIP5, impact on climatological stratospheric conditions (lower shortwave heating rates of −0.35 K day⁻¹ at the stratopause), cooler stratospheric temperatures (−1.5 K in the upper stratosphere), lower ozone abundances in the lower stratosphere (−3 %), and higher ozone abundances (+1.5 % in the upper stratosphere and lower mesosphere). Between the maximum and minimum phases of the 11-year solar cycle, there is an increase in shortwave heating rates (+0.2 K day⁻¹ at the stratopause), temperatures ( −1 K at the stratopause), and ozone (+2.5 % in the upper stratosphere) in the tropical upper stratosphere using the CMIP6 forcing dataset. This solar-cycle response is slightly larger, but not statistically significantly different from that for the CMIP5 forcing dataset.
CMIP6 models with a well-resolved shortwave radiation scheme are encouraged to prescribe SSI changes and include solar-induced stratospheric ozone variations, in order to better represent solar climate variability compared to models that only prescribe TSI and/or exclude the solar-ozone response. We show that monthly-mean solar-induced ozone variations are implicitly included in the SPARC/CCMI CMIP6 Ozone Database for historical simulations, which is derived from transient chemistry–climate model simulations and has been developed for climate models that do not calculate ozone interactively. CMIP6 models without chemistry that perform a preindustrial control simulation with time-varying solar forcing will need to use a modified version of the SPARC/CCMI Ozone Database that includes solar variability. CMIP6 models with interactive chemistry are also encouraged to use the particle forcing datasets, which will allow the potential long-term effects of particles to be addressed for the first time. The consideration of particle forcing has been shown to significantly improve the representation of reactive nitrogen and ozone variability in the polar middle atmosphere, eventually resulting in further improvements in the representation of solar climate variability in global models.
Geoscientific model development
|Pages:||2247 - 2302|
|Type of Publication:||
A2 Review article in a scientific journal
|Field of Science:||
I. Usoskin’s work was done in the framework of the ReSoLVE Centre of Excellence (Academy of Finland, project 272157).
|Academy of Finland Grant Number:||
272157 (Academy of Finland Funding decision)
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.