The tenth IMSC, Beijing, China, 2007 - International Meetings on ...

analysis of the secular linear MSR trend for Crikvenica and Hvar as well as the application of
non-parametric Mann-Kendall rank test indicate an increase in the MSR for both stations in all
months of the warm season except in May, where slightly negative trend was noticed for Hvar.
Significant monthly increase (confidence level is 0.05) in the MSR were observed for
Crikvenica for all months of the period considered and for Hvar only for June and July. This
increase is particularly important for June, as it indicates the possibility of the earlier onset of
the forest fire season on the Adriatic area.<strong>The</strong> analysis also showed that higher risk for forest
fire has been spread from the middle Adriatic to the northern, especially in July and August.
<strong>The</strong> reason for that is the significant increase in the mean monthly air temperature and
decrease in the monthly precipitation amount in summer months.
Fitting a power law model for low frequencies of ERA40 air temperature spectra
Dmitry Vyushin
Department of Physics, University of Toronto
vyushin@atmosp.physics.utoronto.ca
<strong>The</strong> question of which statistical model best describes the low frequency behavior of
climatic variables is an important one that relates to the predictability of such variables and to
confidence intervals for detecting trends and periodicities. Dating from the seminal papers of
Hasselmann over 30 years ago, the dominant model for climatic spectra has been an
autoregressive model of the first order (AR1). But more recent studies indicate that
geophysical time series do not always follow the AR1 or at least that it is not superior to an
alternative power law approximation. We investigate the spatial distribution of ERA40 air
temperature power law exponents estimated by means of five different statistical methods:
detrended fluctuation analysis (DFA), Geweke Porter-Hudak estimator, Gaussian
semiparametric estimator, and multitapered versions of the last two. We also test the
sensitivity of these spatial distributions to filtering of various climatic modes of variability, such
as linear trend, QBO, ENSO, etc. We find that the DFA method is particularly non-robust in the
presence of periodic signals, and that for all these methods significant power exponents are
concentrated in the tropical troposphere and the subtropical stratosphere. We present
preliminary evidence that links the tropical power exponents to ENSO and the subtropical
stratospheric power exponents to volcanic forcing.
Impact of Long-Range Correlations on Trend Detection in Total Ozone
Dmitry Vyushin
Department of Physics, University of Toronto
vyushin@atmosp.physics.utoronto.ca
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