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Natural Climate Variability on Decade-to-Century Time Scales (1995)
Commission on Geosciences, Environment and Resources (CGER)

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. "THE OCEAN." Natural Climate Variability on Decade-to-Century Time Scales. Washington, DC: The National Academies Press, 1995.

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Natural Climate Variability on Decade-to-Century Time Scales

TABLE 3 Statistics for the Wind Time Series Shown in Figure 8

Wind Series

(a)

(b)

Observed Trend

- 0.27

+ 0.19

Derived Trend

-0.03

+ 0.40

r(O, D)

+ 0.87

+ 0.89

r(Odt, Ddt)

+ 0.94

+ 0.88

NOTES:

Wind series (a) and (b) are those shown in Figure 8 (a) and (b), respectively.

Trends are in 10 × m s-1 yr-1. For series (a), mean zonal wind is negative (i.e., easterly), so negative trend implies strengthening wind. For series (b), mean zonal wind is positive.

r(O,D) is the correlation between observed wind and derived wind.

r(Odt, Ddt) is the correlation after removing the linear trend from the series.

change over 1949 to 1988 was suggested by the pressure data to be negative. Figure 8(b) illustrates this using the newly derived wind for March to May for the 10° box centered at 55°N, 15°W. The relationship between the observed and the derived winds seems to change around 1962. After about 1962, there is particularly good agreement between the observed and derived winds with no appreciable systematic difference in the two series. However, before about 1962, the year-to-year agreement is less good, and there is an appreciable bias; the derived wind is more easterly than the observed. This bias leads to differing linear trends in the observed and derived winds (Table 3); this difference in trends broadly supports the results of Ward (1992). Similar results are found for other nearby boxes in this and other seasons. The discrepancy before 1962 may be caused by biases in either the SLP or the wind data, or by the method used to derive the wind from the SLP data. These possibilities are to be investigated.

"CLIMATE OF THE TWENTIETH CENTURY" INTEGRATIONS

Atmospheric simulations are being commenced using the climate version of the U.K. Meteorological Office Unified Model forced with GISST 1.1. The simulations will require much-improved surface pressure and marine surface wind data sets for their verification. We anticipate substantial benefits from interactions between data analysis, modeling, and studies of the mechanisms of recent climatic variations.

ACKNOWLEDGMENTS

This work was partially supported by the Commission of the European Communities under Contract EPOC-0003C(MB), and by the U.K. Department of the Environment under Contract PECD/7/12/37.

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