T. KRUSCHKE, K. MATTHES, W. HUO, M. KUNZE, U. LANGEMATZ, S. WAHL Disentangling top-down- and bottom-up-directed contributions of 11-year solar cycle induced climate signals SCOSTEP14 – Session 3.2 11 July 2018

Solar influence on climate Aims &Scope Solar influence on climate top-down mechanism bottom-up mechanism Final aim: Quantitative comparison of relevance from Seppälä et al. (2014) Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

CESM1(WACCM) (based on cesm1.0.6; Marsh et al., 2013) Model & Experiments CESM1(WACCM) (based on cesm1.0.6; Marsh et al., 2013) including model improvements (Smith et al., 2015; Garcia et al., 2017) spat. resolution: 1.9°lat x 2.5°lon, 66 levels (model top ~ 140 km) MOZART3 chemistry (Kinnison et al., 2007) including POP2 interactive ocean Experiments: 3 simulations with transient external forcings for 1850-2099 (1850-2004: CMIP5 historical; 2005-2099: CMIP5 RCP8.5) CMIP6 solar forcing (Matthes et al., 2017) Experiment UV-SSI (120-351nm) F10.7 (EUV-Param.) Kp (aurora) VIS&NIR-SSI (351-5000nm) top-down bottom-up full solar = varying = constant Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Results Composite analysis*; mean differences between 38 solar maximum & 38 solar minimum years (19 solar maxima and minima, respectively, 2 years selected for each mean TSI-amplitude ~ 0.7 W/m² *data has been high-pass-filtered before to eliminate climate change signals

Zonal mean temperature Results – Zonal mean composites Zonal mean temperature hatched areas not significant (p>0.1) top-down bottom-up full solar January January January annual mean annual mean annual mean top-down: enhanced merid. temperature gradient in stratosphere bottom-up: nothing significant except for (sub-)tropical stratosphere although NH polar signals just slightly weaker full solar: very similar to top-down February February February K Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Results – Zonal mean composites Zonal mean zonal wind hatched areas not significant (p>0.1) top-down bottom-up full solar January January January Just as for zonal mean temperature top-down: intensified polar vortex (NAM+), downward propagation into troposphere (AO/NAO+) bottom-up: nothing significant except for (sub-)tropical stratosphere ( uncertainty) full solar: very similar to top-down February February February So far focus on middle atmosphere (top-down) What about the troposphere? m/s Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Zonal mass stream function @ equator Results – Tropospheric composit. hatched areas not significant (p>0.1) Zonal mass stream function @ equator Walker circulation climatology & changes bottom-up February full solar February Intensification & westward widening Weakening kg/s *10^10 Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Results – Surface composites SST hatched areas not significant (p>0.1) top-down February bottom-up February full solar February lag = 0y lag = 1y lag = 2y correlation top-down: significant NAO+ related SST signals bottom-up: significant LaNina-like SST signals (lagged response) full solar: strong ElNino/IPO-like signals, but unlikely to be solar driven K Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Conclusions experiments separately triggering top-down and bottom-up mechanism exhibit signals in line with current understanding of these processes top-down: UV ( ozone  SW heating)  temperature (gradient)  zonal wind  dynamical feedbacks: poleward & downward propagation  NAO+like anomalies in troposphere & ocean surface bottom-up: VIS  SST (& latent heat)  Walker (& Hadley) circulation ( clouds & precipitation)  SST but the „real world“ is complex: major signals derived by simple composite analysis for full solar experiment unlikely to be related to solar forcing internal climate variability  highlights challenges related to analyses of solar influence on surface climate Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Outlook further work necessary for proper signal attribution accounting for temporal (interannual) evolution of responses develop/improve process understanding (incl. interactions) clean quantitative comparison of relevance next step: Ensemble approach (hopefully further mitigating sampling artefacts): 2nd set of CESM1(WACCM)-simulations ready analogue EMAC-simulations to be completed end of this month Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Thank you! We appreciate funding by the German Federal Ministry of Education and Research within the ROMIC program.

Ozone concentr. / SW heating rates Results – composites Ozone concentr. / SW heating rates hatched areas not significant (p>0.1) top-down bottom-up full solar Ozone annual mean Ozone annual mean Ozone annual mean SW heat. ann. mean SW heat. ann. mean SW heat. ann. mean % K/d Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Top-down: Zonal mean zonal wind Results – composites Top-down: Zonal mean zonal wind hatched areas not significant (p>0.1) top-down December January February March m/s Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Full solar: Zonal mean zonal wind Results – composites Full solar: Zonal mean zonal wind hatched areas not significant (p>0.1) Full solar December January February March m/s Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

225hPa Geopotential height Results – Tropospheric composit. 225hPa Geopotential height hatched areas not significant (p>0.1) top-down bottom-up full solar January January January top-down: effective signal propagation into troposphere bottom-up: hardly anything significant full solar: pronounced signals, but not obviously linked to top-down or bottom up February February February m Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Merid. mass stream function (zonal mean) Results – composites hatched areas not significant (p>0.1) Merid. mass stream function (zonal mean) top-down bottom-up full solar January January January February February February kg/s Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Auroral influence on ozone concentration (annual mean) Results – MLR Auroral influence on ozone concentration (annual mean) MLR analysis with separate regression coefficients for UV, VIS and Kp % Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Climatological differences Mod_Sol-0.9 vs. Sol-0.9 Impact of model improvements Climatological differences Mod_Sol-0.9 vs. Sol-0.9 Zonal mean temperature and zonal wind (annual mean) -9m/s -2.5m/s +2.5K Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Impact of model improvements SSW frequency Impact of model changes on NH winter dynamics ERA-Interim Mod_Sol-0.9 Sol-0.9 Analysis of Lena Ebsen (M.Sc. Student) Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

Radiation & photolysis schemes Models & experiments Radiation & photolysis schemes CESM1(WACCM) Marsh et al. (2013) spat. resolution: 1.9°lat x 2.5°lon, model top ~ 140 km spectral resolution: coarse SW radiation (for z<65km) high resolution photolysis scheme EMAC Jöckel et al. (2016) spatial resolution: T42L47MA, model top ~ 80 km high resolution SW radiation (for p<70hPa) coarse photolysis scheme 19 106 100 9 Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals