Empirical indicators of climate variability and ecosystem response since 1965

1
Empirical indicators of climate variability and
ecosystem response since 1965

• Steven R. Hare1 and Nathan J. Mantua2
• 1International Pacific Halibut Commission, P. O.
  Box 95009, Seattle, WA, 98145-2009. Email
  hare_at_iphc.washington.edu
• 2 Joint Institute for the Study of the Atmosphere
  and Oceans, University of Washington, Box 354235,
  Seattle, WA 98195-4235. Email
  mantua_at_atmos.washington.edu

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Introduction

• Widespread agreement that a climatic regime
  shift, with extensive ecosystem impacts, occurred
  in the winter of 1976-1977.
• The 1977 regime shift appears to follow earlier
  shifts in 1925 and 1947.
• Has a regime shift occurred since 1977?
• 1989 generally pointed at as most likely change
  point
• PDO index used to identify earlier regime shifts
  winter PDO reversed in 1989 but summer/annual PDO
  index did not.
• Collected diverse array of time series to test
  coherency of a 1989 regime shift (and revisit
  1977)

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Data

• We assembled 100 indices of climate and
  biological variability for the period 1965-1997.
• 31 are climatic and 69 are biological time series
• Spatial range is California Current to Bering Sea
• Climate series are mostly winter averages,
  biological series are annual averages.
• All time series were normalized - most biological
  series were log-normalized

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Methods

• Three methods used to detect regime signal
• Principal component analysis - interannual
  variability
• Generates climate patterns (EOFs) and temporal
  indices (PCs) and amount of variance accounted
  for by each EOF/PC pair.
• Ebbesmeyer at al. (1991) step statistic -
  interannual/decadal
• Used to compute magnitude of step in composite of
  all 100 time series. Two regime tests done -
  around 1977 and 1989
• Difference maps - decadal
• SST and SLP averaged within each regime and then
  the difference computed - done for summer and
  winter

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Atmospheric Indices
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Air temperatures and Streamflows
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PDO, ENSO and SST indices
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Upwelling and miscellaneous
9
Lower trophic level biology
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Bering Sea groundfish recruitment
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GOA groundfish recruitment
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West Coast groundfish recruitment
13
Alaska salmon catches
14
Transition Zone salmon catches
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West Coast salmon catches
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Approximate centers of location of 100 time series
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PCA results - all data
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PCA results - separate data
PC scores - physical indices
PC scores - biological indices
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Loadings on PC1 - all data
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Loadings on PC2 - all data
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Loadings on PC1 - biological data
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Loadings on PC2 - biological data
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Loadings on PC1 - climate data
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Loadings on PC2 - climate data
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Loadings on PC3 - climate data
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Ebbesmeyer et al. regime test
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SST difference maps - winter
Regime 2 minus Regime 1
Regime 3 minus Regime 2
Regime 3 minus Regime 1
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SST difference maps - summer
Regime 2 minus Regime 1
Regime 3 minus Regime 2
Regime 3 minus Regime 1
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SLP difference maps - winter
Regime 3 minus Regime 2
Regime 2 minus Regime 1
Regime 3 minus Regime 1
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SLP difference maps - summer
Regime 3 minus Regime 2
Regime 2 minus Regime 1
Regime 3 minus Regime 1
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A 1998 sea change?
SLP
SST
Summer
Winter
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Summary and Conclusions

• Analysis of ecological and climate records
  reproduces previously identified characteristics
  of 1977 regime shift, and lends additional
  support for (and insights into) a 1989 regime
  shift
• 1989 changes less widespread and clearly not a
  simple reversal to pre-1977 Pacific climate and
  ecology
• especially important to Bering Sea and some NE
  Pacific ecosystems
• Arctic vortex persistently more intense, NE
  Pacific and Bering Sea SSTs warmer (especially
  in summer), and winter Aleutian Low circulation a
  little weaker, than in 1977-88 period

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Summary and Conclusions (contd)

• within regimes, ecosystem indices are more steady
  than climate indices
• non-linear ecosystem responses to environmental
  changes highlight the importance of ecosystem
  monitoring because of a strong signal to noise
  ratio
• improved regime shift predictions still hinge on
  an improved understanding of climate dynamics
• a mechanistic understanding is required to know
  what should be monitored, which models might be
  useful, and whether or not there is any
  predictability ...