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Correlation of temperature with solar activity (SSN). Alexey Poyda and Mikhail Zhizhin Geophysical Center & Space Research Institute, Russian Academy of Sciences. Climate History Data.
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Correlation of temperature with solar activity (SSN) Alexey Poyda and Mikhail Zhizhin Geophysical Center & Space Research Institute, Russian Academy of Sciences
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
5 most significant eigenvectors in temperature time series in 2 years window The SVD eigenvectors with the largest eigenvalues correspond to: seasonal (1 year period, interseasonal (1/2 year period) and decadal variations (linear trend)
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
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
Same as above but with 3-years time window smoothing for SSN
St.-Petersburg Minsk
Correlation between surface temperature and smoothed SSN for the last 25 years, Eurasia
Correlation between surface temperature and smoothed SSN for the last 50 years, Eurasia
Correlation between surface temperature and SSN for 25 years
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