2026-10-07, 16:30–16:45 (Europe/Amsterdam), Room 18
Extreme hydrometeorological extremes are one of the main focuses of operational early warning systems for natural hazards. The ongoing integration of remote sensing datasets into the monitoring pipelines is aimed at contributing to the refinement of the forecasts and the accurate identification of the risks. However, very few studies have specifically addressed the inherent uncertainties of the remote sensing datasets in the range of extreme events. Multiple factors in the processing of these datasets can impact the capabilities of each type of data to effectively detect potentially hazardous events due to unrealistic recognition of the tails of the distribution of events.
This study is devoted to the intercomparison of remote sensing, model-based and reanalysis products of key variables of the water cycle (rain, soil moisture, flow) to evaluate the consistency of common current operational products for the portrayal of extreme events. The procedure comprises specific extreme value analysis of the distributions of the datasets with special attention to the characterisation of the magnitude and temporal dimensions of the events. In this way, metrics of frequency, duration and intensity are applied to assess the suitability of each product for proper extremes identification against ancillary data of multiple events of well-known impact.
The results indicate relevant differences among products well before the range of true extreme events, which partly explains the struggle of current operational monitoring systems to accurately characterise impactful events. Discussion on the factors influencing such notable differences in the products apprise of multiple aspects of datasets generation and handling that led to distorted capabilities in the tail range of the distributions that need review and coordination between the actors in charge of the generation and application of datasets.
The study encourages further attention to the evaluation of data in the range of their most relevant application, risk assessment, in order to avoid undesired inherited constraints to their application, jeopardising the confidence in early warning systems or the remotely–sensed data.
Open-Earth-Monitor Cyberinfrastructure (Grant agreement ID: 101059548)
Jaime Gaona was born in Burgos, Spain in 1986. Jaime has a background specialized in hydrology during his Civil Engineering studies from the University of Burgos (2013) and his M.Sc. in Hydraulics and Environment from the Polytechnic University of Valencia (2015).
Jaime holds a PhD supported by an Erasmus Mundus Joint Doctorate scholarship in river Sciences (2019) from Freie Universität Berlin and Universitá Degli Studi di Trento, associated with the Leibniz Institute of Freshwater Ecology (Berlin IGB), focused on characterizing and modeling the groundwater-surface water interactions (hyporheic exchange) using innovative measurement techniques such as FO-DTS and hydrogeophysics directed by Jörg Lewandowski and Alberto Bellin.
He started as postdoc in 2019 to study soil moisture and evaporation in the Spanish National Science Project HUMID devoted to the analysis of Iberian drought based on remote sensing and land surface modelling at Ebro Observatory with Pere Quintana-Seguí, while helping to lecture hydraulics and irrigation systems at the Polytechnic University of Barcelona (2020).
Jaime was from 2021 JCYL-supported researcher at the University of Salamanca, Spain, group of Water Resources led by José Martínez Fernández at the Research Institute of Agrobiotechnology (CIALE), working on the analysis of soil moisture relevance to vegetation responses.
Jaime is currently researcher working in soil moisture analysis at the Hydrology group led by Luca Brocca of the Research Institute for Geo-Hydrological Protection IRPI of the Italian National Research Council in Perugia, Italia. The group focus on evaluation of remote sensing tools for hydrology and related fields, with special attention to soil moisture as key variable mediating the water, matter and energy exchanges in the critical zone.