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Diego Miralles   Professor  Other 
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Diego Miralles published an article in April 2018.
Top co-authors See all
Lixin Wang

129 shared publications

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

Eric F. Wood

125 shared publications

Arko Lucieer

107 shared publications

Xuhui Lee

83 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.

Publication Record
Distribution of Articles published per year 
(2016 - 2018)
Total number of journals
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Article 0 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 1 Citation 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 0 Reads 13 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 0 Reads 1 Citation Recent increases in terrestrial carbon uptake at little cost to the water cycle Lei Cheng, Ying-Ping Wang, Josep G. Canadell, Francis H. S. ... 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.The response of the coupled carbon and water cycles to anthropogenic climate change is unclear. Here, the authors show that terrestrial carbon uptake increased significantly from 1982 to 2011 and that this increase is largely driven by increased water-use efficiency, rather than an increase in water use.
Article 0 Reads 2 Citations Vegetation anomalies caused by antecedent precipitation in most of the world C Papagiannopoulou, D G Miralles, W A Dorigo, N E C Verhoest... Published: 01 July 2017
Environmental Research Letters, doi: 10.1088/1748-9326/aa7145
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Quantifying environmental controls on vegetation is critical to predict the net effect of climate change on global ecosystems and the subsequent feedback on climate. Following a non-linear Granger causality framework based on a random forest predictive model, we exploit the current wealth of multi-decadal satellite data records to uncover the main drivers of monthly vegetation variability at the global scale. Results indicate that water availability is the most dominant factor driving vegetation globally: about 61% of the vegetated surface was primarily water-limited during 1981–2010. This included semiarid climates but also transitional ecoregions. Intra-annually, temperature controls Northern Hemisphere deciduous forests during the growing season, while antecedent precipitation largely dominates vegetation dynamics during the senescence period. The uncovered dependency of global vegetation on water availability is substantially larger than previously reported. This is owed to the ability of the framework to (1) disentangle the co-linearities between radiation/temperature and precipitation, and (2) quantify non-linear impacts of climate on vegetation. Our results reveal a prolonged effect of precipitation anomalies in dry regions: due to the long memory of soil moisture and the cumulative, non-linear, response of vegetation, water-limited regions show sensitivity to the values of precipitation occurring three months earlier. Meanwhile, the impacts of temperature and radiation anomalies are more immediate and dissipate shortly, pointing to a higher resilience of vegetation to these anomalies. Despite being infrequent by definition, hydro-climatic extremes are responsible for up to 10% of the vegetation variability during the 1981–2010 period in certain areas, particularly in water-limited ecosystems. Our approach is a first step towards a quantitative comparison of the resistance and resilience signature of different ecosystems, and can be used to benchmark Earth system models in their representations of past vegetation sensitivity to changes in climate.
Article 1 Read 0 Citations Relation between precipitation location and antecedent/subsequent soil moisture spatial patterns Hsin Hsu, Min‐Hui Lo, Benoit P. Guillod, Diego G. Miralles, ... Published: 27 June 2017
Journal of Geophysical Research: Atmospheres, doi: 10.1002/2016jd026042
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Recent evidence has shown that relations between soil moisture and precipitation at spatial and temporal aspect are contrary to each other: afternoon precipitation tends to occur at times in which conditions are overall wet and heterogeneous in the morning, but preferentially over those patches that are relatively drier than the surroundings. This study expands the notion of soil moisture-precipitation spatial coupling by analyzing the preferred precipitation location over a range of different soil moisture patterns. Using global observations of precipitation and observationally constrained evaporative stress estimates, we confirm that relatively drier patches have more chances of receiving rain, but the preference is weakened under wetter soil conditions. During extremely wet times, wet patches have more chances of receiving rain. Moreover, the preference of precipitation to occur on drier soils is stronger when soil moisture conditions are heterogeneous. Such results indicate that the positive feedback mechanism becomes more positive as soil wetness increases and the negative feedback mechanism becomes more negative as soils become drier and more heterogeneous. The strength of these two feedback mechanisms jointly affects preferential precipitation location. Counterintuitively, analysis from 1 day after-event soil moisture pattern shows that negative soil moisture-precipitation coupling may in turn further heterogenize soil moisture patterns, because dry patch gets extremely wet with no or less rain in surrounding. Although results here do not necessarily imply a causal relationship, this work contributes to enhancing our understanding of soil moisture-precipitation spatial coupling and exposes the complex nuances of these land-atmosphere interactions.