Nonlinear (MARS) modeling of long-term variations of surface UV-B radiation as revealed from the analysis of Belsk, Poland data for the Period 1976-2000

Abstract

A new, powerful statistical technique, multivariate adaptive regression splines (MARS), is applied to reproduce monthly fractional deviations of UV-B doses over Belsk, Poland, during the snowless (May-October) part of the year in the period 1976-2000. Two kinds of regressors were used: local ones (total ozone, percentage of sky covered by low-, mid-, high-level clouds or total solar radiation over Belsk) and non-local ones, i.e. those describing the long-distance forcings on the surface UV-B due to changes in the global atmospheric circulation. Standard indices of the Quasi-Biennial, North Atlantic, El Nino-Southern Oscillations, and the 11-year solar activity were used as non-local regressors. The results there indicate that the MARS procedure is able to reproduce the observed year-to-year and decadal oscillations in the UV data. The MARS model yields better model-observation agreement than an ordinary leastsquares fit based on the same set of regressors. It is found that MARS is capable of handling interactions between the local and non-local regressors, suggesting a possible nonlinear nature of connections between variables characterizing the atmospheric transparency over Belsk and the long-distance forcings. MARS enables a reconstruction of the surface UV-B variations over any site based on the cloud and ozone data presently stored on web pages.