1. Expressions of ENSO and the SAM in Modeled Antarctic Surface Temperatures The Transantarctic Mountains, A. Huerta, 2003 David B. Reusch EMS Earth and Environmental Systems Institute and Department of Geosciences The Pennsylvania State University David B. Reusch EMS Earth and Environmental Systems Institute and Department of Geosciences The Pennsylvania State University Funded by the Office of Polar Programs, National Science Foundation Special thanks to David Bromwich and Andy Monaghan for sharing their data

2. Introduction Questions Are there robust spatial relationships between surface temperatures and ENSO/SAM? Does SAM modulate the ENSO fingerprint? Methods Extract patterns of variability in temperature and circulation data (SOMs) Stratify data by SAM/ENSO states and hope there’s something to interpret in the patterns Questions Are there robust spatial relationships between surface temperatures and ENSO/SAM? Does SAM modulate the ENSO fingerprint? Methods Extract patterns of variability in temperature and circulation data (SOMs) Stratify data by SAM/ENSO states and hope there’s something to interpret in the patterns Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

3. Polar MM5 initialized by ERA-40 Jan 1979 - Aug 2002 60 km grid, 6-hourly Daily averages, DJF (Jul) T-2m (Z850, Z700, Z500) See Monaghan et al, 2006 Polar MM5 initialized by ERA-40 Jan 1979 - Aug 2002 60 km grid, 6-hourly Daily averages, DJF (Jul) T-2m (Z850, Z700, Z500) See Monaghan et al, 2006 The Model Dataset Grid Domain Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

4. Self-organizing Maps (SOMs) Patterns arranged in a grid by their relative similarity 1) Generalized pattern extractor Holocene ice core chemistry Each input record matches one pattern most closely Concise summary of data variability expressed as a user-defined number of generalized patterns Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

5. Subset input by time period, external index, etc. Self-organizing Maps (SOMs) Group input records that match the same pattern; use pattern instead 2) Data classifier by pattern matching Basis for frequency, transition and trajectory maps Sample Frequency Map Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

11. 125 m 200 m Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

12. Seasonal Land-Only Temperatures Broadening study period Switch to land-only Focus on ice sheet Ocean temperatures of less interest Still daily resolution Broadening study period Switch to land-only Focus on ice sheet Ocean temperatures of less interest Still daily resolution Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

13. Land-only Surface Temperature Climatology Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

17. SAM and Temperature Create data subsets using high/low values of the SAM index Create frequency maps for each year in each subset Identify which pattern frequencies are statistically unusual Count how often each pattern is unusual Create data subsets using high/low values of the SAM index Create frequency maps for each year in each subset Identify which pattern frequencies are statistically unusual Count how often each pattern is unusual Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

18. Marshall SAM Index, J. Climate 2003 http://www.antarctica.ac.uk/met/gjma/sam.html 40 °S 65 °S Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

19. 80% 20%

22. Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

25. T = f(ENSO) o g(SAM)? r 2 ~ 0 Background ● ENSO ● Land-only T-2m ● SAM ● T <= SAM,ENSO

29. December 1982 Low SAM/El Niño

30. December 1994 High SAM/El Niño

33. Potential Next Steps Work with READER data Not high spatial density like a model grid… But the records are longer Then again, it’s monthly not daily… Other fields that express the SAM Compare notes with those using other methodologies! Work with READER data Not high spatial density like a model grid… But the records are longer Then again, it’s monthly not daily… Other fields that express the SAM Compare notes with those using other methodologies!

34. Summary Intriguing signatures of both El Niño and the SAM are in the data Untangling joint effects SAM/ENSO remains a challenging task dbr120@psu.edu NSF ANT 06-36618

35. J-M05 Manifestation of anthropogenic forcing and natural variability in the Arctic and Antarctic climate systems June 28 – July 11, Melbourne, AUS www.iugg2011.com Call for Abstracts still TBA J-M05 Manifestation of anthropogenic forcing and natural variability in the Arctic and Antarctic climate systems June 28 – July 11, Melbourne, AUS www.iugg2011.com Call for Abstracts still TBA