Abstract. 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 (1850CMIP6 preindustrial control, historical ( -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 Maunderminimum-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 onePublished by Copernicus Publications on behalf of the European Geosciences Union. 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 timeslice 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 wi...

The influence of solar variability on the polar atmosphere and climate due to energetic electron precipitation (EEP) has remained an open question largely due to lack of a long-term EEP forcing data set that could be used in chemistry-climate models. Motivated by this, we have developed a model for 30-1000 keV radiation belt driven EEP. The model is based on precipitation data from low Earth orbiting POES satellites in the period 2002-2012 and empirically described plasmasphere structure, which are both scaled to a geomagnetic index. This geomagnetic index is the only input of the model and can be either Dst or Ap. Because of this, the model can be used to calculate the energy-flux spectrum of precipitating electrons from 1957 (Dst) or 1932 (Ap) onward, with a time resolution of 1 day. Results from the model compare well with EEP observations over the period of 2002-2012. Using the model avoids the challenges found in measured data sets concerning proton contamination. As demonstrated, the model results can be used to produce the first ever >80 year long atmospheric ionization rate data set for radiation belt EEP. The impact of precipitation in this energy range is mainly seen at altitudes 70-110 km. The ionization rate data set, which is available for the scientific community, will enable simulations of EEP impacts on the atmosphere and climate with realistic EEP variability. Due to limitations in this first version of the model, the results most likely represent an underestimation of the total EEP effect.

Derivation of the auroral ionospheric currents from magnetic field measurements can produce drastically different results depending on the data and method used. We have cross tested several methods for obtaining instantaneous field‐aligned and horizontal currents from Swarm satellite and International Monitor for Auroral Geomagnetic Effects (IMAGE) ground magnetic field measurements. We found that Swarm can yield latitude profiles of the east‐west component of the divergence‐free current density at most at ∼200 km resolution, typically resolving the electrojets. The north‐south divergence‐free component, on the other hand, is not always well reproduced due to the small longitudinal distance between the side‐by‐side flying satellite pair. Swarm can yield the field‐aligned and curl‐free current density at a wider range of latitude resolutions (∼7.5–200 km) than the divergence‐free current density. While 7.5 km is suitable for comparison with auroras, 200 km typically resolves the Regions 1 and 2 field‐aligned currents. IMAGE can yield maps of the divergence‐free current density at ∼50 km resolution. Induced telluric currents should be accounted for in the derivation. Not accounting for them in the Swarm analysis, however, does not appear to introduce significant errors. Ionospheric conductances can be estimated by combining the total horizontal current density, consisting of the curl‐free and divergence‐free components, with the electric field measurements. Our results indicate that Swarm can only yield these at ∼200 km scale size when there is no significant dependence on longitude. However, combining the divergence‐free current from IMAGE with the curl‐free current and electric field from Swarm could yield conductance maps at ∼50 km resolution.

Geomagnetically induced currents (GIC) are a space weather phenomenon that can interfere with power transmission and even cause blackouts. The primary drivers of GIC can be represented as ionospheric equivalent currents. We used International Monitor for Auroral Geomagnetic Effects (IMAGE) magnetometer data from 1994–2013 to analyze the extreme behavior of the time derivative of the equivalent current density (|ΔJeq|/Δt) together with the occurrence of modeled GIC in the European high‐voltage power grids (1996–2008). Typically, when intense |ΔJeq|/Δt occurred, geomagnetic activity extended to latitudes <60°, Kp ≥ 8, and modeling suggested large GIC in the European high‐voltage power grids. Intense, although short‐lived, |ΔJeq|/Δt also occurred when geomagnetic activity was confined to latitudes >60°. In such cases, typically 5≤Kp<8, and modeling suggested that there were no large GIC in the European high‐voltage power grids. Intense |ΔJeq|/Δt and GIC occurred preferentially before midnight or at dawn and were rare after noon. There was a seasonal peak in October and a minimum around midsummer. Intense |ΔJeq|/Δt and GIC occurred preferentially in the declining phase of the solar cycle and were rare around solar minima. A longer perspective (1975–2013) was obtained by comparison with the time derivative of the magnetic field from the IMAGE station Nurmijärvi (NUR, MLAT ∼57°). NUR data indicated that the quietness of summer months may have been due to a coincidental lack of intense storms during the shorter period. NUR data agreed with the increased activity in the declining phase but demonstrated that extreme events could also occur during solar minima.

In this study 30‐ to 1,000‐keV energetic electron precipitation (EEP) data from low Earth orbiting National Oceanic and Atmospheric Administration and MetOp Polar Orbiting Environmental Satellites were processed in two improved ways, compared to previous studies. First, all noise‐affected data were more carefully removed, to provide more realistic representations of low fluxes during geomagnetically quiet times. Second, the data were analyzed dependent on magnetic local time (MLT), which is an important factor affecting precipitation flux characteristics. We developed a refined zonally averaged EEP model, and a new model dependent on MLT, which both provide better modeling of low fluxes during quiet times. The models provide the EEP spectrum assuming a power law gradient. Using the geomagnetic index Ap with a time resolution of 1 day, the spectral parameters are provided as functions of the L shell value relative to the plasmapause. Results from the models compare well with EEP observations over the period 1998–2012. Analysis of the MLT‐dependent data finds that during magnetically quiet times, the EEP flux concentrates around local midnight. As disturbance levels increase, the flux increases at all MLT. During disturbed times, the flux is strongest in the dawn sector and weakest in the late afternoon sector. The MLT‐dependent model emulates this behavior. The results of the models can be used to produce ionization rate data sets over any time period for which the geomagnetic Ap index is available (recorded or predicted). This ionization rate data set will enable simulations of EEP impacts on the atmosphere and climate with realistic EEP variability.