Zonal Similarity of Long‐Term Changes and Seasonal Cycles of Baseline Ozone at Northern Midlatitudes

Abstract. We present an approach to derive a systematic mathematical representation of the statistically significant features of the average long-term changes and seasonal cycle of concentrations of trace tropospheric species. The results for two illustrative data sets (time series of baseline concentrations of ozone and N2O at Mace Head, Ireland) indicate that a limited set of seven or eight parameter values provides this mathematical representation for both example species. This method utilizes a power series expansion to extract more information regarding the long-term changes than can be provided by oft-employed linear trend analyses. In contrast, the quantification of average seasonal cycles utilizes a Fourier series analysis that provides less detailed seasonal cycles than are sometimes represented as twelve monthly means; including that many parameters in the seasonal cycle representation is not usually statistically justified, and thereby adds unnecessary noise to the representation and prevents a clear analysis of the statistical uncertainty of the results. The approach presented here is intended to maximize the statistically significant information extracted from analyses of time series of concentrations of tropospheric species regarding their mean long-term changes and seasonal cycles, including non-linear aspects of the long-term trends. Additional implications, advantages and limitations of this approach are discussed.

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Long-term changes in some benthic species in the Firth of Clyde, with particular reference to Tellina tenuis da Costa

Proceedings of the Royal Society of Edinburgh Section B Biological Sciences ◽

10.1017/s0269727000005042 ◽

1986 ◽

Vol 90 ◽

pp. 287-302 ◽

Cited By ~ 1

Author(s):

P. R. O. Barnett ◽

J. Watson

Keyword(s):

Seawater Temperature ◽

Present Knowledge ◽

Seasonal Cycles ◽

Benthic Species ◽

Temperature Changes ◽

Annual Variations ◽

Long Term Changes ◽

Natural Temperature ◽

A Site

SynopisPresent knowledge of long-term changes in benthic species in the Firth of Clyde is reviewed.Recent work on the annual variations in seasonal cycles of the sand-dwelling bivalve Tellina tenuis da Costa shows some correlations with natural and man-made variations in seawater temperature. Between 1973 and 1984 inclusive good settlements of young occurred on the two beaches examined in the autumns of years when higher mean seawater temperatures occurred in June and July. The implications are discussed in relation to cycles of climatic change. In general, settlements at Hunterston, a thermally enriched area, were considerably greater than at Kames Bay, a site affected only by natural temperature changes. However, T. tenuis at Kames Bay grew to much larger maximum sizes than at Hunterston, except in 1979, when Hunterston animals were larger. The possible interactions of food availability and the modifying effects of heated discharges are discussed.Earlier results by Dr A. C. Stephen between 1926 and 1951 are reassessed in the light of present knowledge.

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Lunar Tides and the Long-Term Variation of the Peak Latitude Anomaly of the Summer Sub-Tropical High Pressure Ridge over Eastern Australia

The Open Atmospheric Science Journal ◽

10.2174/1874282301206010049 ◽

2012 ◽

Vol 6 (1) ◽

pp. 49-60 ◽

Cited By ~ 3

Author(s):

Ian R.G. Wilson

Keyword(s):

High Pressure ◽

Tidal Cycle ◽

Seasonal Cycles ◽

Resonance Model ◽

Lunar Tides ◽

Tidal Forces ◽

Pressure Ridge ◽

Eastern Australia ◽

Long Term Changes

This study looks for evidence of a correlation between long-term changes in the lunar tidal forces and the interannual to decadal variability of the peak latitude anomaly of the summer (DJF) subtropical high pressure ridge over Eastern Australia (L) between 1860 and 2010. A simple “resonance” model is proposed that assumes that if lunar tides play a role in influencing L, it is most likely one where the tidal forces act in “resonance” with the changes caused by the far more dominant solar-driven seasonal cycles. With this type of model, it is not so much in what years do the lunar tides reach their maximum strength, but whether or not there are peaks in the strength of the lunar tides that re-occur at the same time within the annual seasonal cycle. The “resonance” model predicts that if the seasonal peak lunar tides have a measurable effect upon L then there should be significant oscillatory signals in L that vary in-phase with the 9.31 year draconic spring tides, the 8.85 year perigean spring tides, and the 3.80 year peak spring tides. This study identifies significant peaks in the spectrum of L at 9.4 (+0.4/-0.3) and 3.78 (± 0.06) tropical years. In addition, it shows that the 9.4 year signal is in-phase with the draconic spring tidal cycle, while the phase of the 3.8 year signal is retarded by one year compared to the 3.8 year peak spring tidal cycle. Thus, this paper supports the conclusion that long-term changes in the lunar tides, in combination with the more dominant solar-driven seasonal cycles, play an important role in determining the observed inter-annual to decadal variations of L.

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Flexible approach for quantifying average long-term changes and seasonal cycles of tropospheric trace species

Atmospheric Measurement Techniques ◽

10.5194/amt-12-3383-2019 ◽

2019 ◽

Vol 12 (6) ◽

pp. 3383-3394 ◽

Cited By ~ 2

Author(s):

David D. Parrish ◽

Richard G. Derwent ◽

Simon O'Doherty ◽

Peter G. Simmonds

Keyword(s):

Time Series ◽

Seasonal Cycle ◽

Linear Trend ◽

Power Series Expansion ◽

Mathematical Representation ◽

Seasonal Cycles ◽

Data Sets ◽

Significant Information ◽

Long Term Changes

Abstract. We present an approach for deriving a systematic mathematical representation of the statistically significant features of the average long-term changes and seasonal cycle of concentrations of trace tropospheric species. The results for two illustrative data sets (time series of baseline concentrations of ozone and N2O at Mace Head, Ireland) indicate that a limited set of seven or eight parameter values provides this mathematical representation for both example species. This method utilizes a power series expansion to extract more information regarding the long-term changes than can be provided by oft-employed linear trend analyses. In contrast, the quantification of average seasonal cycles utilizes a Fourier series analysis that provides less detailed seasonal cycles than are sometimes represented as 12 monthly means; including that many parameters in the seasonal cycle representation is not usually statistically justified, and thereby adds unnecessary “noise” to the representation and prevents a clear analysis of the statistical uncertainty of the results. The approach presented here is intended to maximize the statistically significant information extracted from analyses of time series of concentrations of tropospheric species, regarding their mean long-term changes and seasonal cycles, including nonlinear aspects of the long-term trends. Additional implications, advantages and limitations of this approach are discussed.

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