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Temperature inversions up to the 500-mbar level are studied in 50-mbar depth layers over Hemsby, in eastern England. The inversions are characterized by vertical gradients of temperature, potential temperature, dew point temperature, and depth. An inversion index, which is the product of potential temperature gradient and frequency of occurrence, is used. The zone of maximum activity for elevated inversions is 950-800 mbar, resulting from subsidence within anticyclones. A theoretical explanation of the processes is given. Inversion characteristics are essentially similar for day and night, except in the 1000-950-mbar layer, where daytime frequency is greater. It is suggested that turbulence-capping inversions and/or sea-breeze effects may be the reason. The implications of elevated inversions for air pollution dispersion are discussed. KEY WORDS Temperature inversions Elevated temperature inversions Air pollution Hemsby (UK).

ABSTRACT:The unanimously accepted dependence of the static stability of the lower troposphere on the prevailing weather has, so far, not been expressed quantitatively. This work is the first systematic attempt at expressing this dependence quantitatively. Two weather classifications, an index expressing the activity of the atmospheric temperature inversion layers, and various other inversion statistics are considered for this purpose. Radiosonde data from Hemsby (UK) are used. Lamb's weather classification, which is used initially, shows clear differences in the statistics of inversions for different weather classes. The anticyclonic class is associated with the maximum activity, and the cyclonic class with the minimum activity. The weather class is also shown to affect the vertical variation of the activity of inversions. Differences in the activity of inversions due to the weather class are maximized in the layer 900-800 mb. Given that it is within this layer where the top of the atmospheric boundary layer is usually found, this result is of particular importance for air pollution modelling. An alternative weather classification is also used with the objective of associating inversion statistics not just to a particular weather type, but also to the physical reasons that are responsible for their formation. This classification shows that, in the absence of an anticyclone, the activity of inversions is rather independent of the prevailing weather pattern. However, when the anticyclonic category is also included, the differences become significant. As the results of this work express quantitatively the strong dependence of inversion statistics on the prevailing weather, they can be used for the creation of correction factors for many characteristics related to an inversion climatology (e.g. for the annual cycle of the activity of inversions). Such corrections are necessary in cases where the weather types in the study period do not reflect their frequency in the average climate.

The examination for the possible existence of predictive power in the moving average trading rule has been used extensively to test the hypothesis of weak form market efficiency in capital markets. This work focuses mainly on the study of the variation of the moving average (MA) trading rule performance as a function of the length of the longer MA. Empirical analysis of daily data from NYSE and the Athens Stock Exchange reveal high variability of the performance of the MA trading rule as a function of the MA length and on some occasions the series of successive trading rule total returns is non-stationary. These findings have direct implications in weak form market efficiency testing. Indeed, given this high variability of the performance of the MA trading rule, by just finding out that trading rules with some specific combinations of MA lengths can or cannot beat the market, as is the case in most of the published work thus far, is not enough evidence for or against the existence of weak form market efficiency. Results also show that on average in about three out of four cases trading rule signals are false, a fact that leaves a lot of space for improved trading rule performance if trading rule signals are combined with other information (e.g. filters, or volume of trade). Finally, some evidence of enhanced trading rule performance for the shorter MA lengths was found. This enhanced performance is partly attributed to the higher probability that a trading rule signal is not a whipsaw, as well as to the larger number of days out-of-the-market which are associated with shorter MA lengths.(J.E.L.: G14, G15, C22).