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The correlation analysis between precipitation indices and aerobiological variables could lead to different results if seasonal rainfall is considered. The number of significant correlations, as well as the ratio of positive/negative correlations, is higher when previous autumn rainfall is taken into account than for annual rainfall. However, the percentage of significant correlations is only 5.1 % of the total possible correlations. The autumn indices showing more correlations are related to rainfall duration and persistence, while those for winter were related to rainfall amount and intensity. Since the influence of moderately extreme rainfall seems to be low, the reported probable increase, due to climate change, of the occurrence of intense and short rainy events in the Mediterranean area in autumn does not seem that will have an appreciable effect by itself on the subsequent pollen production.

A long and complete series of monthly rainfall amounts corresponding to Barcelona city (Catalonia, NE Spain), exceeding two centuries (years 1786–2019), is analysed in detail. The obtained results of periodicity (annual scale), time trends (monthly, seasonal and annual scales), statistical distribution (seasonal and annual scale) and fractal/multifractal structures and self-similarity at monthly scale depict the complex structure of this pluviometric regime, which is characterized by moderate increasing and decreasing trends on rain amounts, varying from +0.08¿mm·year-1 (February) to -0.07¿mm·year-1 (September) and quite evident changes on the pluviometric trends at annual and seasonal scales when the rainfall data are analysed for segments of 50¿years from 1800 up to 2019. A good example could be the relevant change on the annual scale time trend, from +0.77¿mm·year-1 (years 1800–1850) to -0.17¿mm·year-1 (years 1950–2019). Clear evidences of decreasing pluviometry for spring, summer and autumn for the last segment (1950–2019) in comparison with the other three segments, including years 1800–1950, are also detected. Additionally, increasing rainfall patterns complexity, expected difficulties on monthly rainfall forecasting and the increasing irregularity of monthly amounts is also detected by interpreting fractal and multifractal results. Irregularity increases on the monthly rainfall series and on the rainfall regime complexity derived from multifractal parameters, could be associated with the very notable increase of CO2 emissions into the atmosphere, globally varying from 51.1¿×¿106 metric tonnes (year 1820) to 36.6¿×¿109 metric tonnes (year 2019) and the tropospheric concentration increasing from 280.8 ppm (year 1850) to 397.5 ppm (year 2014), being the probable relationship between tropospheric concentrations and changes on rainfall patterns the objective of future researches.

Advantages offered by a pluviometric network in Catalonia (NE Spain) have permitted a detailed analysis of the two primary results derived from the autoregressive ARIMA process applied to monthly rainfall amounts. The first was the spatial distribution of the necessary number of previous monthly amounts needed to predict the next amount. The second was the spatial distribution of discrepancies between the real recorded amount and those derived from the autoregressive process. The heterogeneous spatial distribution of both parameters of the ARIMA process is in accordance with the complex spatial distribution of the monthly rainfall regime in Catalonia and fractal/multifractal analyses of several monthly rainfall time series. The statistical distribution of monthly discrepancies also permits a prediction of the probable evolution at monthly scale of drought episodes in terms of length and accumulated rainfall deficit. The results of the ARIMA algorithm are characterised by a few cases of raingauges with remarkable differences (10-20¿mm/month) between real and autoregressive amounts, a predominant number of emplacements lowering 10¿mm/month and a not negligible number of cases with discrepancies lower than 5¿mm/month. In terms of percentages with respect to average monthly amounts, most of discrepancies do not exceed 15%, and only in a very few cases they are within the 20-40% range. It is also worth mentioning that the discrepancies between real and predicted drought lengths use to be no longer than one month. Results corresponding to monthly series recorded at two Earth Sciences observatories are described with more detail to illustrate the advantages offered by the ARIMA autoregressive process in the prediction of beginning, continuity and end of drought episodes.

The pluviometric regime in the Western Mediterranean and concretely in Catalonia (NE Spain) is characterised by irregular amounts at monthly and annual scales, sometimes with copious short episodes causing foods and, conversely, sometimes with long dry spells exceeding 1 month length, depending on the chosen threshold level to defne the dry episode. Taking advantage of a dense network of rain gauges, most of them with records length of 50–60 years and some others exceeding 85 years, the evolution of these monthly and annual amounts is quantifed by means of their time trends, statistical signif- cance and several irregularity parameters. In agreement with the evolution of the CO2 emissions into the atmosphere and the increasing concentration, in parts per million (ppm), of this greenhouse gas, diferent time trends at annual scale have been detected up to approximately years 1960–1970 in comparison with the interval 1960–1970 to nowadays. Consequently, besides the greenhouse efects on the temperature regime, the infuence on the pluviometric regime could not be negligible. Rainfall data have been supplied by Servei Mete‑ orològic de Catalunya (Generalitat de Catalunya), Fabra Observatory (RACA, Barcelona) and Ebro Observatory (Ramón Llull University and CSIC, Spanish Government). This research was supported by the Spanish Ministry of Science, Innovation and Universities: grant 460 number PID2019-105976RB-I00] and grant number AGL201787658-R. The authors also thank the editor and the anonymous reviewers for their valuable comments and suggestions to improve the manuscript

Collected rainfall records by gauges lead to key forcings in most hydrological studies. Depending on sensor type and recording systems, such data are characterized by different time-resolutions (or temporal aggregations), ta. We present an historical analysis of the time-evolution of ta based on a large database of rain gauge networks operative in many study areas. Globally, ta data were collected for 25,423 rain gauge stations across 32 geographic areas, with larger contributions from Australia, USA, Italy and Spain. For very old networks early recordings were manual with coarse time-resolution, typically daily or sometimes monthly. With a few exceptions, mechanical recordings on paper rolls began in the first half of the 20th century, typically with ta of 1 h or 30 min. Digital registrations started only during the last three decades of the 20th century. This short period limits investigations that require long time-series of sub-daily rainfall data, e.g, analyses of the effects of climate change on short-duration (sub-hourly) heavy rainfall. In addition, in the areas with rainfall data characterized for many years by coarse time-resolutions, annual maximum rainfall depths of short duration can be potentially underestimated and their use would produce errors in the results of successive applications. Currently, only 50% of the stations provide useful data at any time-resolution, that practically means ta = 1 min. However, a significant reduction of these issues can be obtained through the information content of the present database. Finally, we suggest an integration of the database by including additional rain gauge networks to enhance its usefulness particularly in a comparative analysis of the effects of climate change on extreme rainfalls of short duration available in different locations.

For a few decades the local rainfall measurements are generally obtained by tipping bucket sensors, that allow to record each tipping time corresponding to a well-known rain depth. However, a considerable part of rainfall data to be used in the hydrological practice is available in aggregated form within constant time intervals. This can produce undesirable effects, like the underestimation of the annual maximum rainfall depth, Hd, associated with a given duration, d, that is the basic quantity in the development of rainfall depth-duration-frequency relationships. The errors in the evaluation of Hd from data characterized by a coarse temporal aggregation, ta, and a procedure to reduce the non-homogeneity of the Hd series are here investigated. Our results show that for ta = 1 min the underestimation is practically negligible, whereas for larger temporal aggregations with d = ta the error in a single Hd can reach values up to 50% and in a series of Hd in the average up to 17%. Relationships between the non-dimensional ratio ta/d and the average underestimation of Hd, derived through continuous rainfall data observed in many stations of Central Italy, are presented to overcome this issue. These equations allow to improve the Hd estimates and the associated depth-duration-frequency curves at least in areas with similar climatic conditions. The effect of the correction of the Hd series on the rainfall depth-duration-frequency curves is quantified. Our results indicate that the improvements obtained by the proposed procedure are of the order of 10%.

This is a copy of the author 's final draft version of an article published in the journal Theoretical and applied climatology. The final publication is available at Springer via http://dx.doi.org/10.1007/s00704-016-1998-0 The fractal behavior of extreme rainfall intensities registered between 1940 and 2012 by the Retiro Observatory of Madrid (Spain) has been examined, and a simple scaling regime ranging from 25 min to 3 days of duration has been identified. Thus, an intensity-duration-frequency (IDF) master equation of the location has been constructed in terms of the simple scaling formulation. The scaling behavior of probable maximum precipitation (PMP) for durations between 5 min and 24 h has also been verified. For the statistical estimation of the PMP, an envelope curve of the frequency factor (k m ) based on a total of 10,194 station-years of annual maximum rainfall from 258 stations in Spain has been developed. This curve could be useful to estimate suitable values of PMP at any point of the Iberian Peninsula from basic statistical parameters (mean and standard deviation) of its rainfall series.