The correlations of several daily surface meteorological parameters such as
maximum, minimum, and mean temperature, diurnal temperature range, pressur
e, precipitation, and relative air humidity are analyzed by partly compleme
ntary methods being effective on different timescales: power spectral analy
sis, second- and higher-degree detrended fluctuation analysis, Hurst analys
is, and the direct estimation of the autocorrelation in the time domain. Da
ta from American continental and maritime and European low-elevation and mo
untain stations are used to see possible site dependencies. For all station
types and locations, all meteorological parameters show correlations from
the shortest to the longest statistically reliable timescales of about thre
e decades. The correlations partly show a clear power law scaling with site
-dependent exponents. Mainly, the short-time behavior of the correlations d
epends on the station type and differs considerably among the various meteo
rological parameters. In particular, the detrended fluctuation and the Hurs
t analyses reveal a possible power low behavior for long timescales which i
s less well resolved or even may remain unrecognized by the classical power
spectral analysis and from the autocorrelation. The long-time behavior of
the American temperatures is governed by power laws. The corresponding expo
nents coincide for all temperatures except for the daily temperature range
with different values for the maritime and the continental stations. From t
he European temperatures those from low-elevation stations also scale quite
well, whereas temperatures from mountain stations do not.