This document discusses research analyzing tree ring data to determine how well tree rings track decadal climate variability. It notes that tree rings may provide good or poor proxies for decadal patterns depending on their correlation with winter precipitation and decadal patterns versus being just moisture sensitive. The research also examines the variance explained by climate patterns versus proxies and reconstructions, and notes the challenges of extracting clear decadal signals due to noisy proxy data and narrowband climate patterns.

1. reading the BASS LINE
How well do moisture-sensitive
tree rings track decadal variability?

2. HIGHexplained variance
LOWexplained variance
robust
decadal proxies
need to
verify

3. ~10 yrvariability

4. ~10 yrvariability
~100 yrobservations

5. ~10 yrvariability
~100 yrobservations
= low ‘n’

7. Mean squared coherence
Coherence between the NADA and the PDO at low (7yr+) frequencies

8. How well do moisture-sensitive tree rings track decadal variability?

11. Decadal ‘hotspots’ in winter precipitation
0% 10% 20% 30% variance
Ault and St. George, 2010

12. highly energetic

17. well resolved

18. Sacramento-San Joaquin
streamflow anomaly (m3/s)Precipitation anomaly (mm)
Levee failure records from Florsheim and Dettinger, GRL, 2007

19. Levee failure records from Florsheim and Dettinger, GRL, 2007
Precipitation anomaly (mm)
Sacramento-San Joaquin
streamflow anomaly (m3/s)

20. Photograph: Neil Pederson

22. correlation with winter precipitation
correlation with decadal pa ern
“moisture-sensitive”

23. correlation with winter precipitation
correlation with decadal pa ern
“moisture-sensitive”
good
decadal
proxies

25. correlation with winter precipitation
correlation with decadal pa ern
“moisture-sensitive”

26. correlation with winter precipitation
correlation with decadal pa ern
poor decadal proxies
“moisture-sensitive”

27. PATTERN
~30%variance
climate variable

28. PATTERN
~30%variance
climate variable
PROXY
~50%variance
climate variable
*

29. PATTERN
~30%variance
climate variable
PROXY
~50%variance
climate variable
*
PATTERN
~15%variance
reconstruction

30. PATTERN
~30%variance
climate variable
PROXY
~50%variance
climate variable
*
narrowband pattern noisy proxy murky signals
PATTERN
~15%variance
reconstruction

31. really
decadal
not that
decadal

34. 1900 1920 1940 1960 1980 2000
Year (A.D.)
-10
-5
0
5
10
-3
-2
-1
0
1
2
3
PDSI Ringwidth
drought-sensitive tree-ring records Eastern Canadian Rockies
St. George et al., (2009), Journal of Climate

35. LOWfrequency

36. St. George et al., The Holocene, 2010
Seasonal precipitation ‘bias’ of NADA

37. HIGHexplained variance
LOWexplained variance
robust
decadal proxies
need to
verify