Solar signals in CMIP‐5 simulations: the ozone response

Abstract

A multiple linear regression statistical method is applied to model data taken from the Coupled Model Intercomparison Project, phase 5 (CMIP-5) to estimate the 11-yr solar cycle responses of stratospheric ozone, temperature, and zonal wind during the 1979-2005 period. The analysis is limited to the six CMIP-5 models that resolve the stratosphere (high-top models) and that include interactive ozone chemistry. All simulations assumed a conservative 11-yr solar spectral irradiance (SSI) variation based on the NRL model. These model responses are then compared to corresponding observational estimates derived from two independent satellite ozone profile data sets and from ERA Interim Reanalysis meteorological data. The models exhibit a range of 11-yr responses with three models (CESM1-WACCM, MIROC-ESM-CHEM, and MRI-ESM1) yielding substantial solar-induced ozone changes in the upper stratosphere that compare favorably with available observations. The remaining three models do not, apparently because of differences in the details of their radiation and photolysis rate codes.During winter in both hemispheres, the three models with stronger upper stratospheric ozone responses produce relatively strong latitudinal gradients of ozone and temperature in the upper stratosphere that are associated with accelerations of the polar night jet under solar maximum conditions. This behavior is similar to that found in the satellite ozone and ERA Interim data except that the latitudinal gradients tend to occur at somewhat higher latitudes in the models. The sharp ozone gradients are dynamical in origin and assist in radiatively enhancing the temperature gradients, leading to a stronger zonal wind response. These results suggest that simulation of a realistic solar-induced variation of upper stratospheric ozone, temperature and zonal wind in winter is possible for at least some coupled climate models even if a conservative SSI variation is adopted.

Solar forcing for CMIP6 (v3.2)

“…Several CMIP5 models included a stratospheric chemical scheme (Hood et al, 2015), and it seems likely that more models will have this capability in CMIP6. However, there will be CMIP6 models that do not include chemistry but which resolve the stratosphere and specify SSI, and thus have some of the major ingredients for simulating a topdown pathway for solar-climate coupling (Mitchell et al, 2015b).…”

“…Recent modeling efforts have made progress in defining the prerequisites to simulate solar influence on regional climate more realistically (e.g., Gray et al, 2013;Scaife et al, 2013;Thieblemont et al, 2015), but the lessons learned from CMIP5 show that a more process-based analysis of climate models within CMIP6 is required to better understand the differences in model responses to solar forcing (e.g., Mitchell et al, 2015b;Misios et al, 2016;Hood et al, 2015). In particular, the role of solar-induced ozone changes and the need for a suitable resolution of climate model radiation schemes to capture SSI variations is becoming increasingly evident, and will be touched upon in this paper.…”

“…However, the observed lag and the spatial pattern of the solar-cycle response are poorly represented in CMIP5 models (e.g., Mitchell et al, 2015b;Misios et al, 2016;Hood et al, 2015).…”

“…Possible errors in climate model responses could be related to biases in the representation of dynamical processes and dynamical variability, the inability of model radiation schemes to properly resolve SSI changes (Forster et al, 2011), or to the missing or inadequate representation of UV and particle-induced ozone signals (Hood et al, 2015). Any comparison of climate model simulations with observations could be affected by a combination of these possible sources of error.…”

Climate responses to SATIRE and SIM-based spectral solar forcing in a 3D atmosphere-ocean coupled GCM

“…Climate model results are often used to estimate the climate responses to solar variations and to understand associated mechanisms (e.g., Haigh 1996Haigh , 2003Shindell et al 1999;Matthes et al 2006;Meehl et al 2009;Rind et al 2008Rind et al , 2013Ineson et al 2011;Frame & Gray 2010;Gray et al 2013;Misios et al 2015;Hood et al 2015;Kidston et al 2015;Mitchell et al 2015). The earlier modeling studies to assess the implication of SORCE SIM measurements mainly focused on the time scale of the 11-year solar cycle by comparing the responses to the out-of-phase SORCE SSI and the in-phase SSI (e.g., NRLSSI and SATIRE SSI).…”