1. 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

2. 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

3. 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
( : CMIP5 historical; : CMIP5 RCP8.5)
CMIP6 solar forcing (Matthes et al., 2017)
Experiment
UV-SSI ( nm)
F10.7 (EUV-Param.)
Kp (aurora)
VIS&NIR-SSI ( nm)
top-down
bottom-up
full solar
= varying
= constant
Kruschke et al.: Disentangling top-down and bottom-up solar cycle climate signals

4. 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

5. 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

6. 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

7. Zonal mass stream function @ equator
Results – Tropospheric composit.
hatched areas
not significant (p>0.1)
Zonal mass stream 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

8. 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

9. 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

10. 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

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

12. 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

13. 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

14. 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

15. 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

16. 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

17. 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

18. 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

19. 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

20. 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