1. Uma S. Bhatt 1, I. Polyakov 2, R. Bekryaev 3 et al. 1. Geophysical Institute & 2. International Arctic Research Institute at Univ. Alaska, Fairbanks AK 3. Arctic & Antarctic Research Institute, St. Petersburg, Russia 30th Climate Diagnostics Workshop October 24-28, 2005, State College, PA Regional expression of Arctic multi-decadal variability Main Points Multi-decadal variability is evident in climate variables of the Arctic Arctic sectors vary with North Atlantic North Pacific displays multi-decadal variability and strongest impacts in the Alaska sector Siberian High also displays multi-decadal variability and influences pressure variability in the Arctic

2. 2 Motivation Must understand natural climate variability mechanisms in order to distinguish from trends due to anthropogenic forcing 100 cm rise sea level [ACIA Report, 2004] 10cm total

3. 3 Outline Document Observed Arctic Multi-decadal Variability Regional Examination of Multi-decadal Variability in Arctic

4. 4 Data Information Monthly Station Data Surface Air Temperature Sea Level Pressure Consolidated several databases Russian drifting stations International Arctic Buoy Program Land stations Russian Arctic fast ice thickness & ice area Gridded Data

5. 5 Composite Arctic Multi-decadal SAT & SLP Variability [Polyakov et al., 2002] Composite time series created from stations north of 62N SLP peaks offset by 15 years from SAT

6. 6 Compare with Arctic SAT Trends from Other Studies [Polyakov et al.,2002]

7. 7 Eastern Arctic Sea Ice Extent Displays Multi-decadal Signal and is Decreasing August sea ice extent (in 1000 km) in the Kara, Laptev, E. Siberian, and Chukchi, from Russian ship and aircraft observations & since 1990 satellite records. Ice lags SAT [Polyakov et al., 2003b]

8. 8 April Ice Edge in Barents: Retreat since 1850 Multi-century scale variability is prominent in Arctic [Shapiro and Colony, 2002, Polar Record] Ice edge since 1750, Vinje, 2002

9. 9 Intermediate Atlantic Water Displays Multi- decadal Variability & Long Term Trend [Polyakov et al., 2004] Atlantic Water Pathway Ice Thickness Atlantic Water Temperature

10. 10 Origins of this Pattern of Variability - N. Atlantic Monthly NAO correlated with Arctic station Surface Air Temperatures Strongest in North Atlantic Sector Mechanisms - thermohaline circ. - solar variability - greenhouse forcing - MLM + ozone/solar [Polyakov et al., 2003b] How is multi-decadal variability expressed regionally in the Arctic?

11. 11 Climatically Consistent Regional Divisions 1.Greenland Sea 2.Barents Sea 3.Kara-Laptev 4.Central Arctic 5.E. Siberian/Chukchi 6.Beaufort Sea 7.Canadian Archipelago 8.Greenland

12. 12 SAT Displays Multi-decadal Variability close to N. Atlantic  = 1.1  = 0.58  = 1.05  = 1.15 Red line is Smoothed time series Surface Air Temperature, (Wavelet Analysis) - 1880-1920 Cool; 1920-60 Warm; 1960-80 Cool; 1980-00 Warm.

13. 13 SAT in Regions that Display Different Variability  = 1.30  = 0.97  = 1.09  = 0.83 Hard to tell due to short data set Multi-decadal but a bit different More decadal variability in these sectors

14. 14 SLP Regions That Display Multi-decadal Variability  = 1.79  = 1.44  = 1.59  = 1.76 Sea Level Pressure (Wavelet Analysis) - 1880-1900 High ; 1900-35 Low ; 1935-75 High; 1975-00 Low

15. 15 Regions not displaying Multi-decadal Variability  = 2.26  = 1.13  = 1.12  = 1.15 Sea Level Pressure: Regions 5-7, 1950-80 High SLP

16. 16 Large amplitude multi-decadal oscillations impacts calculation of trends SAT - all regions are warming (orange) except Region 3 SLP -decreasing (green) in regions 1,2,5,6,7 & increasing in Regions 3 & 8. Significance of trends decreases as the record gets shorter. Greenland Sea Barents Kara-Laptev Central Arctic Greenland Canada Beaufort E.Siberian/Chukchi

17. 17 Large amplitude multi-decadal oscillations impacts calculation of trends SAT - all regions are warming (orange) except Region 3 SLP -decreasing (green) in regions 1,2,5,6,7 & increasing in Regions 3 & 8. Significance of trends decreases as the record gets shorter. Greenland Sea Barents Kara-Laptev Central Arctic Greenland Canada Beaufort E.Siberian/Chukchi

18. 18 Spatial Variability in Arctic Surface Temperature Trends last 20 years: Cooling over Kara Sea? ( Comiso, 2003) Trend all months Surface Temperature is decreasing over Taimyr Peninsula, between Kara Sea and Laptev Sea.

19. 19 Pacific Decadal Oscillation & Arctic PDO is the leading PC of monthly SST anomalies in the North Pacific Ocean. S. Minobe showed 15-to-25 & 50-to-70 years. + phase- phase

20. 20 Annual Average SAT-Index Correlations 5-E.Siberia/Chukchi NAO (0.28) 1-GIN 2-Barents 3-Kara/Laptev 4 -Central Arctic 6-E.Alaska/Beaufort 7-Canadian Arch. 8-Greenland NAO (0.34) NAO (0.44) NAO (0.49) NAO (-0.39) NAO (-0.68) PDO (0.41) Black - 99.9% Green - 95.0% NAO is SLP index, positive==> Icelandic low is deeper PDO, positive==> Stronger Aleutian low and more warm southerly winds. DJF similar

21. 21 Siberian High [Gong & Ho, 2002] October-March feature, Shallow high over Asia, 40-60N & 70-120E Highs move out of this region into the Arctic Trend in High since 1980, not as strong…

22. 22 Recent Changes in Siberian High Siberian High has trend and displays some low frequency variability What is this variability associated with? Multi-decadal fluctuations in Indian Ocean… hPa

23. 23 Siberian High, Arctic SLP, & NAO Recent low pressure seen in Arctic SLP follows Siberian High Anomalies

24. 24 SLP differences between warm and cold decades in the Arctic What may be happening? Highs (from Siberian High) entering Arctic are weaker acting to maintain a lower SLP NCEP reanalysis shows about half the anomaly

25. 25 Annual Average SLP-Index Correlations 5-E.Siberia/Chukchi NAO (-0.25) 1-GIN 2-Barents 3-Kara/Laptev 4 -Central Arctic 6-E.Alaska/Beaufort 7-Canadian Arch. 8-Greenland NAO (-.71) NAO (-.31) NAO (-0.64) NAO (-0.28) NAO (-0.23) Black - 99.0% Blue - 95.0% SHi (0.35) SHi (0.37) SHi (0.23) SHi (0.24) NAO negative correlations, positive phase means lower pressures Siberian High - positive correlations, strong high ==> higher SLP PDO negative correlations DJF in R 5 & 6

26. 26 Summary Multi-decadal variability is more prevalent in North Atlantic sector of Arctic North Pacific displays multi-decadal variability that influences impacts the Alaska sector Siberian High also displays low frequency variability and influences pressure variability in the Arctic Records are short (two realizations) so we need to find analogs in GCMs to study the mechanisms (working on this)

27. Acknowledgements Frontier Research System for Global Change Geophysical Institute (GI) International Arctic Research Center (IARC) Others on Multi-decadal Variability Team G. Alexeev, R. Colony, M. Johnson, H. Simmons, L. Timokov, D.Walsh, & J. Walsh

28. 28

29. 29 Correlations between Indices DJF NAO => SiHi-0.28 (95%) SOI => SiHi0.26 (95%) AO => SiHi-0.50 (99%) NAO => SiHi : Changing Correlation over time… 1920-59: -0.05 1960-00: -0.29

30. 30 NAO Relationship to SAT & Ice -20 +20 More southerly (northerly) advection less (more) ice Deser et al. 2000 Observed Sea Level Pressure pattern associated with ice anomalies (Red-less ice and Blue-more ice)

31. 31 DJF SAT-Index Correlations Similar to Annual 5-E.Siberia/Chukchi NAO (0.38) 1-GIN 2-Barents 3-Kara/Laptev 4 -Central Arctic 6-E.Alaska/Beaufort 7-Canadian Arch. 8-Greenland NAO (0.45) NAO (0.48) NAO (0.66) NAO (-0.55) NAO (-0.4) PDO (0.32) Black - 99.9%