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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
Lixin Wang

128 shared publications

Indiana University‐Purdue University Indianapolis Department of Earth Sciences Indianapolis Indiana USA

Eric F. Wood

126 shared publications

Xuhui Lee

84 shared publications

Nanjing University of Information Science & Technology Yale‐NUIST Center on Atmospheric Environment Nanjing Jiangsu China

Alessandro Cescatti

78 shared publications

European Commission, Joint Research Centre, Directorate for Sustainable Resources, Ispra, Italy

Yongqiang Zhang

57 shared publications

14
Publications
12
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57
Citations
Publication Record
Distribution of Articles published per year 
(2016 - 2018)
Total number of journals
published in
 
11
 
Publications See all
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
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Li et al. contest the idea that vegetation greening has contributed to boreal warming and argue that the sensitivity of temperature to leaf area index (LAI) is instead likely driven by the climate impact on vegetation. We provide additional evidence that the LAI-climate interplay is indeed largely driven by the vegetation impact on temperature and not vice versa, thus corroborating our original conclusions.
Article 1 Read 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 2 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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Biome function is largely governed by how efficiently available resources can be used and yet for water, the ratio of direct biological resource use (transpiration, E T) to total supply (annual precipitation, P) at ecosystem scales remains poorly characterized. Here, we synthesize field, remote sensing and ecohydrological modelling estimates to show that the biological water use fraction (E T/P) reaches a maximum under mesic conditions; that is, when evaporative demand (potential evapotranspiration, E P) slightly exceeds supplied precipitation. We estimate that this mesic maximum in E T/P occurs at an aridity index (defined as E P/P) between 1.3 and 1.9. The observed global average aridity of 1.8 falls within this range, suggesting that the biosphere is, on average, configured to transpire the largest possible fraction of global precipitation for the current climate. A unimodal E T/P distribution indicates that both dry regions subjected to increasing aridity and humid regions subjected to decreasing aridity will suffer declines in the fraction of precipitation that plants transpire for growth and metabolism. Given the uncertainties in the prediction of future biogeography, this framework provides a clear and concise determination of ecosystems' sensitivity to climatic shifts, as well as expected patterns in the amount of precipitation that ecosystems can effectively use. Field, remote sensing and ecohydrological modelling estimates provide a framework to determine ecosystem sensitivity to climatic shifts, as well as expected patterns in the amount of precipitation that ecosystems can effectively use.
Article 1 Read 17 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 (3–5 m) 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 array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems.
Article 1 Read 3 Citations Recent increases in terrestrial carbon uptake at little cost to the water cycle Ying-Ping Wang, Josep G. Canadell, Francis H. S. Chiew, Jaso... Published: 24 July 2017
Nature Communications, doi: 10.1038/s41467-017-00114-5
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Quantifying the responses of the coupled carbon and water cycles to current global warming and rising atmospheric CO2 concentration is crucial for predicting and adapting to climate changes. Here we show that terrestrial carbon uptake (i.e. gross primary production) increased significantly from 1982 to 2011 using a combination of ground-based and remotely sensed land and atmospheric observations. Importantly, we find that the terrestrial carbon uptake increase is not accompanied by a proportional increase in water use (i.e. evapotranspiration) but is largely (about 90%) driven by increased carbon uptake per unit of water use, i.e. water use efficiency. The increased water use efficiency is positively related to rising CO2 concentration and increased canopy leaf area index, and negatively influenced by increased vapour pressure deficits. Our findings suggest that rising atmospheric CO2 concentration has caused a shift in terrestrial water economics of carbon uptake.