Jaime Gaona
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 research fellow 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.
Sessions
The initiatives to facilitate access to open data cubes and results of digital twins for Earth systems analysis and early warning are gaining momentum. Successful experiences like the Open Earth Monitor Cyberinfrastructure are leading to an increasing awareness and experience in the governance of these datasets. However, data providers (i.e. models, earth observation missions) increasingly offer data in a near-real-time basis presenting the next challenge in the comprehensive integration of datasets into open Earth cyberinfrastructures.
Soil moisture is one of the crucial state variables that are currently transitioning to near-real-time data provision. In this study, we explore the potential of two soil moisture near-real-time data providers to generate end-user early warning drought monitoring capabilities. The study evaluates the feasibility of generating near-real-time (daily) merged soil moisture anomaly maps by merging the recent EUMETSAT ASCAT H122 6.25km resolution surface soil moisture product with the near-real-time outputs of GLOFAS4 modelling system from the European Flood Awareness System (EFAS) at a continental scale. Experiences gained on assessing the strengths and weaknesses of the two types of data in the framework of the Open Earth Monitor Cyberinfraestructure across scales are contrasted with the insights collected in the near-real-time workflow design for the aim of this study. In particular, from the side of data applicability, the study assesses both the coverage and consistency of near-real time anomalies ‘dynamic’ estimates compared to ‘static’ estimates from the ones generated using climate data records of the same products trying to elucidate the actual worth and capabilities of the claim near-real time capacity of the input products. The study secondarily focuses on the strengths and weaknesses of merging data from distinct data types (e.g. model-based and remote-sensing) with special attention to their suitability for identifying the different ranges of events relevant for monitoring (i.e. the progressive changes in anomalies versus those of extreme events).
Therefore, the purpose of this study is to provide an outlook on the incoming opportunities and barriers of processing data at near-real-time for its integration into data cubes and digital twin systems within the framework of the accelerating community efforts to provide readily accessible and operational eErth system data for end-users.