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Detecting Change in the Bering Sea Ecosystem. Sergei Rodionov 1 , James E. Overland 2 , Nicholas A. Bond 1 1 JISAO, University of Washington, Seattle, WA. 2 PMEL, NOAA, Seattle, WA. The SARS Method. Searching for the first regime shift. January PDO. 1. 5% significance level. l = 10. 0.5.
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Detecting Change in the Bering Sea Ecosystem Sergei Rodionov1, James E. Overland2, Nicholas A. Bond1 1JISAO, University of Washington, Seattle, WA.2PMEL, NOAA, Seattle, WA.
The SARS Method Searching for the first regime shift January PDO 1 5% significance level l = 10 0.5 RSI 0 1900 1905 1910 1910 1915 1920 1925 1930 0.6 -0.5 0.5 0.4 -1 1910 0.3 -1.5 0.2 -2 0.1 0 -2.5 SARS – Sequential Analysis of Regime Shifts RSI – Regime Shift Index
Searching for the next regime shift January PDO 2.5 l = 10 2 RSI 1910 1922 1.5 0.8 1914 0.7 1 0.6 0.5 0.5 0.4 0 0.3 1900 1905 1910 1915 1920 1925 1930 0.2 -0.5 0.1 5% significance level -1 0 1912 -1.5
The North Pacific Index (Nov-Mar)1899-2003 1977 l = 10 1948 1924 1977 p = 0.05 0.1 1948 1924 RSI 1958 1989 2003
Arctic Oscillation, 1951-2003 p = 0.05 l = 10 7 5 1996 1972 1994 1989 1977
Regime Shifts in Climatic Indices p = 10 l = 0.1 1943 PDOa PDOw PDOs 1977 PDOw ALPI NPINCAR PNA 1976 PDOa 1998 PDOs 1934 1989 NPICPC EPI AO PDOa EPI PDOs PDOw PDOs NPICPC AI NPINCAR
Arctic Oscillation, Winter (DJF) l = 10 p = 0.1 1989
Pacific Decadal Oscillation, Winter (DJF) l = 10 p = 0.1 1989
The North Pacific Index, Winter (NDJFM) 1989 l = 10 p = 0.1
NPICPC l = 10 p = 0.1 1998 1990 R = -0.26 Data: 1950-2003 EPI R = -0.70 Data: 1980-2003 1998 1990
Correlations with SLP1950-2003 East Pacific Index (AMJJ) North Pacific Index (AMJJ)
Regime Shifts in Atmospheric Indices l = 10 p = 0.1 1977 SATw SATa SLPw 1929 1997 1938 1959 1969 SATa OWS SATa BSPI 1989 BSPI MIX SLPw SATa – Annual surface air temperature, St. Paul. SATw – Winter surface air temperature, St. Paul SLPw – Winter SLP over the Bering Sea BSPI – Bering Sea pressure index OWS – Optimal wind speed for larval feeding, Mooring 2 MIX – Summer wind mixing, Mooring 2
Mean Winter (NDJFM) SLP over the Bering Sea 1911 1924 1947 1977 1989 1998
Mean Winter (DJFM) SAT at St. Paul 1924 1940 1947 1977 1989 1998
Regime Shifts in Oceanic Indices 1983 l = 10 p = 0.1 1977 SSTPrib SSTPrib SSTM2 ICI 1965 SSTPrib 2000 IRI 1988 SSTM2 SATPrib – Winter SST near the Pribilof Islands SATM2 – Winter SST at Mooring 2 ICI – Ice Cover Index IRI – Ice Retreat Index
Ice Cover Index and Surface Temperature at Mooring 2 ICI 1978 l = 10 p = 0.1 1977 1988 Temperature
Regime Shifts in Biological Indices l = 10 p = 0.1 1981 1992 1977 1984 1966
Time Series of Fish Stocks Herring year-class strength 1989 l = 10 p = 0.1 1977 Bristol Bay sockeye salmon runs 1997 l = 10 p = 0.1 1979 Pollock recruitment at age 1 1985 l = 5 p = 0.1 2001 1989 1978
Conclusions • Characteristics of the SARS method: • Automatic detection of regime shifts, • Improved performance at the ends of time series, • Can be tuned up to detect regimes of different scales, • Can handle the incoming data regardless of whether they are presented in the form of anomalies or absolute values, • Works well with the time series containing a trend, • Can be applied to a large set of variables.
Conclusions (continued) • An application of SARS to the Bering Sea ecosystem demonstrated that • The shift of 1977 was the strongest one in the last 50 years; • A number of indices experienced a regime shift around 1989 (AO, PDOw, temperature at Mooring 2, herring), 1998 (PDOs, salmon), or both (NPICPC, EPI, winter SLP, flathead sole); • The regime of 1989-1997 was characterized by a relative winter cooling and reduced cyclonic activity; • Regime shifts in biological indices are not concentrated around certain, dominant years. The RSI values are rather evenly distributed between 1977 and 1992.