A study on correlations between precipitation ETCCDI and airborne pollen/fungal spore parameters in the NE Iberian Peninsula

Precipitation is one of the meteorological variables usually involved in the aerobiological studies, which presents a complex relationship with atmospheric levels of pollen and fungal spores and the temporal characteristics of their seasons. This complexity is due in a large part to rainfall's twofold impact of having, prior to pollination, a positive influence on subsequent pollen production and of contributing, during pollination, to pollen removal from the air through a wash-out effect. To better explore this impact, we place particular emphasis on extreme rainfall by calculating the correlation between airborne pollen and fungal spore parameters and the precipitation indices that the Expert Team on Climate Change Detection and Indices (ETCCDI) proposed for characterising climate extremes. Parameters for twenty-seven pollen and fungal spore taxa measured in six aerobiological stations in the NE Iberian Peninsula have been considered. We have distinguished between annual and winter ETCCDI in order to compare the correlations between extreme rainfall and airborne pollen concentrations and to avoid the wash-out effect as far as possible. Results show a positive influence from an increase in moderately extreme winter rainfall, specifically on subsequent pollen/fungal spore production: the percentage of all possible significant correlations is higher for winter than for annual rainfall. Furthermore, while annual rainfall in this region has nearly the same number of positive as negative correlations, the positive correlations for winter rainfall are more than twice that of the negative ones. The seasonal consideration on rainfall ETCCDI made with the aim to avoid the confounding overlapping of different rainfall impacts has led to more sharpened observations of its positive and negative effects on airborne pollen and fungal spore concentrations.

Multifractal structure of the monthly rainfall regime in Catalonia (NE Spain): Evaluation of the non-linear structural complexity

The complex non-linear regime of the monthly rainfall in Catalonia (NE Spain) is analyzed by means of the reconstruction fractal theorem and the multifractal detrended fluctuation analysis algorithm. Areas with a notable degree of complex physical mechanisms are detected by using the concepts of persistence (Hurst exponent), complexity (embedding dimension), predictive uncertainty (Lyapunov exponents), loss of memory of the mechanism (Kolmogorov exponent), and the set of multifractal parameters (Hölder exponents, spectral asymmetry, spectral width, and complexity index). Besides these analyses permitting a detailed description of monthly rainfall pattern characteristics, the obtained results should also be relevant for new research studies concerning monthly amounts forecasting at a monthly scale. On one hand, the number of necessary monthly data for autoregressive processes could change with the complexity of the multifractal structure of the monthly rainfall regime. On the other hand, the discrepancies between real monthly amounts and those generated by some autoregressive algorithms could be related to some parameters of the reconstruction fractal theorem, such as the Lyapunov and Kolmogorov exponents.