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Diego Miralles   Professor  Other 
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Diego Miralles published an article in June 2018.
Top co-authors See all
Eric F. Wood

308 shared publications

Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA

Matthew F. McCabe

299 shared publications

Animal and Bioscience Research Department, Animal and Grassland Research and Innovation Centre, Teagasc, Ireland

Yongqian Zhang

188 shared publications

CSIRO Land and Water; Canberra Australia

Yongqiang Zhang

177 shared publications

CSIRO Land and Water, Black Mountain, Canberra, ACT 2601, Australia

Lixin Wang

167 shared publications

Department of Earth Sciences, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA

Publication Record
Distribution of Articles published per year 
(2016 - 2018)
Publications See all
Article 0 Reads 2 Citations Land-atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges Diego G. Miralles, Pierre Gentine, Sonia I. Seneviratne, Adr... Published: 25 June 2018
Annals of the New York Academy of Sciences, doi: 10.1111/nyas.13912
DOI See at publisher website
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Droughts and heatwaves cause agricultural loss, forest mortality, and drinking water scarcity, especially when they occur simultaneously as combined events. Their predicted increase in recurrence and intensity poses serious threats to future food security. Still today, the knowledge of how droughts and heatwaves start and evolve remains limited, and so does our understanding of how climate change may affect them. Droughts and heatwaves have been suggested to intensify and propagate via land–atmosphere feedbacks. However, a global capacity to observe these processes is still lacking, and climate and forecast models are immature when it comes to representing the influences of land on temperature and rainfall. Key open questions remain in our goal to uncover the real importance of these feedbacks: What is the impact of the extreme meteorological conditions on ecosystem evaporation? How do these anomalies regulate the atmospheric boundary layer state (event self‐intensification) and contribute to the inflow of heat and moisture to other regions (event self‐propagation)? Can this knowledge on the role of land feedbacks, when available, be exploited to develop geo‐engineering mitigation strategies that prevent these events from aggravating during their early stages? The goal of our perspective is not to present a convincing answer to these questions, but to assess the scientific progress to date, while highlighting new and innovative avenues to keep advancing our understanding in the future.
Article 0 Reads 0 Citations Relation between Convective Rainfall Properties and Antecedent Soil Moisture Heterogeneity Conditions in North Africa Irina Y. Petrova, Diego G. Miralles, Chiel C. Van Heerwaarde... Published: 17 June 2018
Remote Sensing, doi: 10.3390/rs10060969
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Recent observational studies have demonstrated the relevance of soil moisture heterogeneity and the associated thermally-induced circulation on deep convection and rainfall triggering. However, whether this dynamical mechanism further influences rainfall properties—such as rain volume or timing—has yet to be confirmed by observational data. Here, we analyze 10 years of satellite-based sub-daily soil moisture and precipitation records and explore the potential of strong spatial gradients in morning soil moisture to influence the properties of afternoon rainfall in the North African region, at the 100-km scale. We find that the convective rain systems that form over locally drier soils and anomalously strong soil moisture gradients have a tendency to initiate earlier in the afternoon; they also yield lower volumes of rain, weaker intensity and lower spatial variability. The strongest sensitivity to antecedent soil conditions is identified for the timing of the rain onset; it is found to be correlated with the magnitude of the soil moisture gradient. Further analysis shows that the early initiation of rainfall over dry soils and strong surface gradients yet requires the presence of a very moist boundary layer on that day. Our findings agree well with the expected effects of thermally-induced circulation on rainfall properties suggested by theoretical studies and point to the potential of locally drier and heterogeneous soils to influence convective rainfall development. The systematic nature of the identified effect of soil moisture state on the onset time of rainstorms in the region is of particular relevance and may help foster research on rainfall predictability.
Article 0 Reads 0 Citations Response to Comment on “Satellites reveal contrasting responses of regional climate to the widespread greening of Earth” Giovanni Forzieri, Ramdane Alkama, Diego G. Miralles, Alessa... Published: 14 June 2018
Science, doi: 10.1126/science.aap9664
DOI See at publisher website
Article 2 Reads 0 Citations Global hydro-climatic biomes identified via multi-task learning Christina Papagiannopoulou, Diego G. Miralles, Matthias Demu... Published: 25 April 2018
Geoscientific Model Development Discussions, doi: 10.5194/gmd-2018-92
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The most widely-used global land cover and climate classifications are based on vegetation characteristics and/or climatic conditions derived from observational data. However, these classification schemes do not directly stem from the interaction between the local climate and the biotic environment. In this work, we model the dynamic interplay between vegetation and local climate in order to delineate ecoregions that share a coherent response to hydro-climate variability. Our novel framework is based on a multi-task learning approach that discovers the spatial relationships among different locations by learning a low-dimensional representation of predictive structures. This low-dimensional representation is combined with a clustering algorithm that yields a classification of biomes with coherent behaviour. Experimental results using global observation-based data sets indicate that, without the need to prescribe any land cover information, our method is able to identify regions of coherent climate-vegetation interactions that agree well with the expectations derived from traditional global land cover maps. The resulting global hydro-climatic biomes can be used to analyse the anomalous behaviour of specific ecosystems in response to climate extremes and to benchmark climate-vegetation interactions in Earth system models.
Article 0 Reads 4 Citations A mesic maximum in biological water use demarcates biome sensitivity to aridity shifts Stephen P. Good, Georgianne W. Moore, Diego G. Miralles Published: 13 November 2017
Nature Ecology & Evolution, doi: 10.1038/s41559-017-0371-8
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Article 3 Reads 24 Citations The future of Earth observation in hydrology Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego... Published: 28 July 2017
Hydrology and Earth System Sciences, doi: 10.5194/hess-21-3879-2017
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In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smartphones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3–5m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the internet of things as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this...