1. Correlation of temperature with solar activity (SSN) Alexey Poyda and Mikhail Zhizhin Geophysical Center & Space Research Institute, Russian Academy of Sciences

2. Climate History Data NCEP/NCAR Reanalysis climate history database with global weather 2.5 deg lat/lon grids from 1948 till now at 6 h time step Singular Value Decomposition for trend detection at each grid point with 3-4 years time window. Using SVD we can derive the most significant modes in the weather variation, both periodic and long-term quasy- linear

3. 5 most significant eigenvectors in temperature time series in 2 years window The SVD eigenvectors with the largest eigenvalues correspond to: 1.seasonal (1 year period, 2.interseasonal (1/2 year period) and 3.decadal variations (linear trend)

4. SVD-derived linear trend in temperature is equivalent to the same width running time window average Blue is SVD-derived trend, red is 3- years time window average Surface temperature in Moscow for the last 25 years X-axis in bi-weeks (2 observations per month) Y-axis in Celsius degress

5. Linear trend in surface temperature in Moscow vs. Solar Spot Number Temperature trend was derived by SVD decomposition with 3-years time window SSN is from http://spidr.ndgc.noaa.gov

6. Same as above but with 3- years time window smoothing for SSN

7. St.-PetersburgMinsk

8. Correlation between surface temperature and smoothed SSN for the last 25 years, Eurasia

9. Correlation between surface temperature and smoothed SSN for the last 50 years, Eurasia

10. Correlation between surface temperature and SSN for 25 years

11. Temperature at 1000 mbar pressure level and SSN

12. Temperature at 925 mbar pressure level and SSN

13. Temperature at 850 mbar pressure level and SSN

14. Temperature at 700 mbar pressure level and SSN

15. Temperature at 600 mbar pressure level and SSN

16. Temperature at 500 mbar pressure level and SSN

17. Temperature at 400 mbar pressure level and SSN

18. Temperature at 300 mbar pressure level and SSN

19. Temperature at 250 mbar pressure level and SSN

20. Temperature at 200 mbar pressure level and SSN

21. Temperature at 150 mbar pressure level and SSN

22. Temperature at 100 mbar pressure level and SSN

23. Temperature at 70 mbar pressure level and SSN

24. Temperature at 50 mbar pressure level and SSN

25. Temperature at 30 mbar pressure level and SSN

26. Temperature at 20 mbar pressure level and SSN

27. Temperature at 10 mbar pressure level and SSN

28. Conclusion We observe strong regional correlation between linear trends in temperature and SSN both smoothed within 3-4 years time window for the last 25 years The time window length eliminates contributions from seasonal variations, volcanoes and El-Nino oscillations The spatial correlation pattern is persistent for different pressure levels (heights) Linear correlation for the larger time window (50 years NCEP/NCAR Reanalysis database) is not so pronounced in value, but has the same spatial pattern. Possibly we have to remove longer time scale trends (global warming :) from the temperature time series