Session B1 - Meteorology and climate change

Urban drainage systems designed under assumptions of climate stationarity face mounting challenges due to changing precipitation patterns. This study assesses trends in five indices critical for the design and operation of urban water infrastructure—1-day and 3-day maximum precipitation, dry days, total annual precipitation, and wet-season variability—using data from 24,585 rain gauge stations across Latin America and Europe (1900–2024). Results reveal distinct regional patterns with direct implications for urban management. Northern and Central Europe show an intensification of the hydrological cycle, characterized by increased total precipitation and extremes, while the Mediterranean exhibits trends toward prolonged droughts. In Latin America, spatial heterogeneity is evident: Colombia, Peru, and Southern Brazil show increased precipitation, whereas Central Brazil presents a significant reduction in rainfall totals. Analysis of the 20 largest metropolitan areas indicates that a widespread increase in precipitation extremes poses a critical challenge for urban infrastructure. Of particular concern is the pattern observed in Latin American cities such as São Paulo, Belo Horizonte, Medellín, and Fortaleza, which display a concurrent rise in both extreme events and dry days, contrasting with European cities where extremes are accompanied by a wetter regime.

There exists an urgent need to assess the possible climate change impacts on the design storm for improving the design of urban water infrastructures. This design storm is commonly estimated from the intensity-duration-frequency (IDF) relations at the location of interest. Consequently, the derivation of IDF relations in the climate change context has been recognized as one of the most challenging tasks in current engineering practice. The main challenge is how to establish the linkages between the climate projections given by climate models at global/regional scales and the observed extreme rainfalls at a given local site. If these linkages could be established, then the projected climate change conditions given by climate models could be used to predict the resulting changes of local extreme rainfalls and related runoff characteristics.  Hence, different downscaling approaches were proposed to describe these linkages. Therefore, the overall objective of the present paper is to provide an overview of some recent progress and shortcomings of existing downscaling methods. In particular, an innovative statistical downscaling procedure was developed for modeling extreme rainfall processes over a wide range of temporal scales using the scale-invariance Generalized Extreme Value (GEV) model. Results of an illustrative application using historical extreme rainfall data from 39 stations located across Canada and simulation outputs from 21 climate models have indicated the accuracy and reliability of the proposed scale-invariance GEV downscaling method.

This paper presents a comparative analysis of Intensity-Duration-Frequency (IDF) curves derived from two distinct sources: traditional rain gauge stations and weather radar precipitation estimates. The study focuses on four critical urban catchments in São Paulo, Brazil: Aricancuva, Mandaqui, Jaguaré, and Pacaembu. The objective is to highlight the differences, advantages, and limitations of each data source for hydrological design and urban flood management. The methodology describes the generation of IDF curves from point-based historical rainfall series from rain gauges versus spatially distributed rainfall fields retrieval from polarimetric weather radar that required specific processing, including polarimetric adjustments and bias correction. The results indicate that radar-derived IDF curves show accumulated rainfall amounts that depend on the areas and durations used, with no specific patterns being identified. In contrast, the study suggests that with longer event durations, the effect of the spatial distribution, more faithfully described by radar, is mitigated, approaching the information provided by rain gauges. The discrepancies found have significant implications for the design of hydraulic structures and urban drainage systems, suggesting that the integration of radar data can lead to more resilient and safe infrastructure, better adapted to the spatial variability of extreme rainfall events in large metropolitan areas, specially in short duration events.