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COMING ATTRACTIONS. A GEDALOF, MANTUA, PETERSON PRODUCTION CIG / JISAO PRESENTS.

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Presentation on theme: "COMING ATTRACTIONS. A GEDALOF, MANTUA, PETERSON PRODUCTION CIG / JISAO PRESENTS."— Presentation transcript:

1 COMING ATTRACTIONS

2 A GEDALOF, MANTUA, PETERSON PRODUCTION CIG / JISAO PRESENTS

3 A multi-century perspective of variability in the Pacific Decadal Oscillation: new insights from tree rings and coral

4 Reconstructed PDO Index R = 0.64 Based on leading principal component of five published paleoproxy reconstructions. Collective skill better than individual skill

5 Mean Intercorrelation... Note Interval of Poor Intercorrelation

6 Period of Poor Intercorrelation...

7 Evans Linsley Gedalof

8 APPEARING SOON IN GEOPHYSICAL RESEARCH LETTERS

9 COLUMBIA RIVER FLOW SINCE A.D. 1750 RECONSTRUCTED FROM TREE RINGS A Gedalof / Peterson / Mantua Joint

10 Based on 32 tree-ring sites R = 0.59

11 Residuals exhibit positive trend over time (ca. +1.2 percent per century) Validates model results of Matheussen et al. (2000).

12 Persistent Droughts: The 1930s were not an anomaly...

13 MANUSCRIPT IN INTERNAL REVIEW...

14 FEATURE PRESENTATION

15 FIRE & CLIMATE IN THE AMERICAN NORTHWEST Douglas-Fir

16 CO-CONSPIRATORS Ze’ev Lolita (and Dave) Nate

17 Q. What causes wildfire? A. Fuels Accumulation "As with other areas of the country, we have experienced the unintended consequences of our very effective wildfire fighting program: The wildfires of today are getting bigger, more dangerous, harder to control, and are adversely affecting the safety of the public and our fire fighters.” National Fire Plan Strategy For the Pacific Northwest (2002)

18 Q. What causes wildfire? B. Weather "…forest fire behavior is determined primarily by weather variation among years rather than fuel variation associated with stand age." Bessie and Johnson (1995)

19 Q. What causes wildfire? C. You

20 Evidence for fuels... Area burned by wildfire in 11 Western States Source: National Interagency Fire Center

21 On national forest lands in the Pacific Northwest wildfires are more frequent and more extensive during the warm phase of the PDO. Cool PDO Warm PDO …for climate...

22 …and you.

23 Study Overview To characterize patterns in annual area burned To relate those patterns to climatic features and ecological context To determine the extent to which climatic factors can be used to predict seasonal wildfire

24 Literature Review Lots of work in the Canadian boreal forest. Very little work in the Pacific Northwest

25 Previous Studies Have generally treated area west of the Rocky Mountains as a single coherent unit –No allowance for spatial variability –No recognition of underlying ecology Emphasis has been on weather (not climate)

26 New Ideas: (1) I do not treat the area west of the Rocky Mountains as a single coherent unit (2) I address large fire seasons, rather than individual large fires (3) I identify several key atmospheric structures that can potentially be used to forecast fire-season severity

27 ?

28 EOF Analysis Empirical Orthogonal Function (EOF) analysis identifies underlying patterns in large data sets –The EOFs describe the spatial variability in the data set –Associated principal components (PCs) describe the temporal variability

29 Spatial Regressions Can “regress” fields of climate data onto time series Produces characteristic response of climate field to 1  perturbation in time series

30 Superposed Epoch Analysis Develop map composites for selected years (i.e. epochs) based on quantitative criteria Derive descriptive statistics for subsets –Can focus on extreme events –More powerful than correlations / regressions –Does not assume linear relationship

31 EOF 1 - 17%

32 PC1 / 500 hPa Regression Shaded areas indicate significant correlation Pattern exhibits strong blocking

33 Five largest fire years minus five smallest fire years Patterns consistent, but magnitude greater PC1 / 500 hPa Composite

34 Area burned is correlated to drought in winter and spring preceding the fire season Correlations: -0.59 -0.55 -0.61 June, July, Aug. PC1 / PDSI Correlations

35 EOF 2 - 13%

36

37 PC2 / 500 hPa Regression Resembles “Summer PNA” Matches results across border

38 Area burned is weakly correlated to drought in winter preceding the fire season Correlations: -0.06 -0.09 -0.11 June, July, Aug. PC2 / PDSI Correlations

39 EOF 3 - 12%

40

41 3 only large fire years represented by PC-3 Characterized by very strong, highly persistent blocking PC3 / 500 hPa Composite

42 Correlations Composite

43 EOF 4 - 10%

44

45 Large fire years correspond to fire season cyclone activity PC4 / 500 hPa Composite

46 Fire season is wet on the west side, dry on the east side Preceding season is drier than normal

47 Summary 1. Climate Matters Region wide increases in area burned are characterized by antecedent drought accompanied by persistent blocking events

48 Summary 2. Ecology Matters Underlying ecology appears to modulate the response to drought and circulation –more mesic forests require persistent drought, blocking events, and a source of ignition and spread –drier forests are more responsive to shorter-scale (i.e. synoptic) processes

49 Summary 3. These relationship are non-linear Implies that eigenvector techniques may not be the most appropriate method of investigation Small changes in mean climate may lead to dramatic changes in wildfire activity

50 Discussion ?


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