Classical spectral, Hurst, and detrended fluctuation analysis have been revealed asymptotic power-law correlations for daily average temperature data. For short-time intervals, however, strong correlations characterize the dynamics that permits a satisfactory description of temperature changes as a low order linear autoregressive process (dominating the texts on climate research). Here we propose a unifying stochastic model reproducing correlations for all time scales. The concept is an extension of a first-order autoregressive model with power-law correlated noise. The inclusion of a nonlinear "atmospheric response function" conveys the observed skew for the amplitude distribution of temperature fluctuations. While stochastic models cannot help to understand the physics behind atmospheric processes, they are capable to extract useful features promoting to benchmark physical models, an example is shown. Possible applications for other systems of strong short-range and asymptotic power-law correlations are discussed.

Daily temperature anomaly records are analyzed (61 for Australia, 18 for Hungary) by means of detrended fluctuation analysis. Positive long range asymptotic correlations extending up to 5-10 years are detected for each case. Contrary to earlier claims, the correlation exponent is not universal for continental stations. Interestingly, the dominant factor is geographic latitude over Australia: the general tendency is a decrease of correlation exponent with increasing distance from the equator. This tendency is in a complete agreement with the results found by Tsonis et al. (1999) for 500-hPa height anomalies in the northern hemisphere. The variance of fluctuations exhibits an opposite trend, the larger is the distance from the equator, the larger the amplitude of intrinsic fluctuations. The presence of Tropospheric Biennial Oscillation is clearly identified for three stations at the north-eastern edge of the Australian continent.

A B S T R A C T Several thousands of temperature records from the Global Daily Climatology Network are analysed by means of detrended fluctuation analysis (DFA). Long-range temporal power-law correlations extending up to several years are detected for each station. Contrary to earlier claims, the correlation exponent is not universal for continental locations. Short-range correlations are also evaluated by DFA and by first order autoregressive models. The strength of short-and long-range temporal correlations seems to be coupled for large geographic areas. The spatial patterns are quite complex, simple parameter dependence such as elevation or distance from oceans cannot explain the observed variability.

An extensive investigation of 61 daily temperature records by means of detrended fluctuation analysis has revealed that the value of correlation exponent is not universal, contrary to earlier claims. Furthermore, statistically significant differences are found for daily minimum and maximum temperatures measured at the same station, suggesting different degrees of long-range correlations for the two extremes. Numerical tests on synthetic time series demonstrate that a correlated signal interrupted by uncorrelated segments exhibits an apparently lower exponent value over the usual time window of empirical data analysis. In order to find statistical differences between the two daily extreme temperatures, high frequency (10 min) records were evaluated for two distant locations. The results show that daily maxima characterize better the dynamic equilibrium state of the atmosphere than daily minima, for both stations. This provides a conceptual explanation why scaling analysis can yield different exponent values for minima and maxima.

The effect of the porcine myogenin (Myog) 3' polymorphism on birth weight, growth rate, carcass weight, lean weight, lean meat percentage and backfat thickness has been investigated in Hungarian Large White pigs. MYOG genotypes were determined by PCR-RFLP assay. The obtained MYOG A frequency value was 0.6275. Due to the small number of BB piglets the effect of the MYOG genotypes on birth weight was not significant; however, an increasing tendency was observed from genotype AA to BB. The growth rate difference between MYOG genotypes was significant: BB animals showed the highest growth rate values during the fattening period. Since few results are available on the possible use of MYOG gene polymorphism in selection to improve carcass and growth traits, by this study the authors hope to provide additional data on this particular subject.