1. Global analysis of recent frequency component changes in interannual climate variability Murray Peel 1 & Tom McMahon 1 1 Civil & Environmental Engineering, The University of Melbourne, Victoria, Australia

2. EGU 2006 - Session AS1.07/CL040/CL007 Outline Background Temporal changes in frequency components – Empirical Mode Decomposition – Data set – Results for dividing year = 1970 – Sensitivity of results to the dividing year Conclusions

3. EGU 2006 - Session AS1.07/CL040/CL007 Climate change impact on climate variability Mainly assessed at daily, monthly & seasonal scales – Changes in extreme event frequency – Changes in the shape parameter of the daily frequency distribution Less attention has been paid to the annual scale

4. EGU 2006 - Session AS1.07/CL040/CL007 Background Potential modification of interannual climate variability is important – Multi-year drought severity – Reservoir reliability – Ecosystem dynamics

5. EGU 2006 - Session AS1.07/CL040/CL007 Interannual Climate Variability What drives changes in the mean and variance of an annual time series? – Look at the components of a time series using spectral analysis Source: IPCC, Climate Change 2001

6. EGU 2006 - Session AS1.07/CL040/CL007 Spectral Analysis (EMD) Empirical Mode Decomposition (EMD) – Decomposes a time series into Intrinsic Mode Function(s) (IMFs) A residual (Trend) – Locally adaptive algorithm Robust to non-linear / non-stationary data – No data pre-processing (like removal of “trend”)

7. EGU 2006 - Session AS1.07/CL040/CL007 Spectral Components EMD spectral components – High Frequency (<10 years; Intra-Decadal) Sum of IMFs with average period < 10 years – Low Frequency (>10 years; Inter-Decadal) Sum of IMFs with average period >= 10 years + the residual – Effectively using EMD as a high/low pass filter

8. EGU 2006 - Session AS1.07/CL040/CL007 EMD Example Robe, South Australia Can assess temporal changes in component behaviour (pre and post a dividing date)

9. EGU 2006 - Session AS1.07/CL040/CL007 Data Set Annual temperature and precipitation data from the GHCN (version 2) Choose 1970 as the dividing year – To maximise the number and spatial distribution of stations with >= 15 years of unbroken record pre- and post- the dividing year (N >= 30) – Annual temperature Stations = 1,524, average N = 63 years, ~1930 - 1993 – Annual precipitation Stations = 2,814, average N = 74 years, ~1920 - 1993)

10. EGU 2006 - Session AS1.07/CL040/CL007 Results Robe Example VarRatio 1970 = Variance >=1970 / Variance <1970 – Obs. = 0.65, High = 0.80, Low = 0.64

11. EGU 2006 - Session AS1.07/CL040/CL007 Results Temperature – 1,524 Stations VarRatio 1970 Obs.HighLow Percentiles 5%0.410.450.09 50%0.951.040.67 95%1.972.085.36 % Stations >=144.353.338.3 <155.746.761.7

12. EGU 2006 - Session AS1.07/CL040/CL007 Temperature Observed VarRatio 1970 No. Stations (>=1) > (<1) No. Stations (>=1) = (<1) No. Stations (>=1) < (<1)

13. EGU 2006 - Session AS1.07/CL040/CL007 Results Precipitation – 2,814 Stations VarRatio 1970 Obs.HighLow Percentiles 5%0.460.450.11 50%0.950.980.79 95%2.032.214.43 % Stations >=144.848.640.7 <155.251.459.3

14. EGU 2006 - Session AS1.07/CL040/CL007 Precipitation High Component VarRatio 1970 No. Stations (>=1) > (<1) No. Stations (>=1) = (<1) No. Stations (>=1) < (<1)

15. EGU 2006 - Session AS1.07/CL040/CL007 Sensitivity to dividing year Temperature

16. EGU 2006 - Session AS1.07/CL040/CL007 Sensitivity to dividing year Precipitation

17. EGU 2006 - Session AS1.07/CL040/CL007 Conclusions – Temperature VarRatio 1970 – Observed: slight decrease – High Frequency (intra-decadal): slight increase – Low Frequency (inter-decadal): large decrease Variance moving from low to high frequency component, over much of the last century Decreasing the long-term memory Increasing the degree of randomness

18. EGU 2006 - Session AS1.07/CL040/CL007 Conclusions – Precipitation VarRatio 1970 – Observed: slight decrease – High Frequency (intra-decadal): slight decrease – Low Frequency (inter-decadal): large decrease Variance moving from low to high frequency component, over much of the last century Decreasing the long-term memory Increasing the degree of randomness – To a lesser extent than the temperature results

19. EGU 2006 - Session AS1.07/CL040/CL007 Overall Conclusions Recent increase in intra-decadal fluctuations maybe due to climate change – Consistent with other research indicating that the degree of randomness will increase under a warmer climate Recent decrease in inter-decadal fluctuations may reduce the usefulness of teleconnection based forecasting systems

20. EGU 2006 - Session AS1.07/CL040/CL007 Acknowledgements The analysis presented forms part of a paper under review at – Geophysical Research Letters Funded by – Australian Research Council Discovery Grant Useful Discussions – Geoff Pegram