Analysis of the Sub-daily Precipitation Extremes in Mexico City

Precipitation is highly variable in space and time and the variability is known to be scale dependent. The availability of high spatio-temporal resolution of precipitation data is key to the characterisation of it variability. Moreover, knowledge about the nature of the temporal variability of rainfall is required to design urban drainage, and flood mitigation measures. Concentration times in urban hydrology are in the range of a few hours. Researchers and decision makers often face a lack of input data due to sparse measurement networks or poor quality measurements with insufficient temporal and spatial resolution. On the other hand, with the advent of technology, real-time rainfall monitoring systems with high temporal resolution have been developed in several cities, opening the door towards the improvement of our understanding on precipitation extremes acting on urban environments.

In this context, the climate of Mexico City is characterized by the occurrence of convective rains, which show a greater irregularity in its precipitation behaviour. During the 2016 rainy season, in the month of July, the western region of Mexico City was flooded twice; generating affectations on houses and their inhabitants.

This investigation provides temporal and spatial analysis of 1-min precipitation measurements, based on a dense observation network in Mexico City ranging from 2017 to 2018. It quantifies how daytime and season affect these characteristics. For this, we use a data from a real-time monitoring system comprised by 54 individual rainfall stations, spatially distributed over the city. The goal of this work is to quantify the amount of the contribution of the total precipitation over the wettest days of the year. For this, statistical calculations will be carried out to determine the parameters (e.g. 95th percentile, monthly and seasonal averages, wettest days of the year) that define the unevenness of precipitation. This work will open the door towards a better understanding of rainfall variability in one of the biggest and most populated cities of the world.