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Santiago Beguería  - - - 
Top co-authors See all
Siobhan M. White

185 shared publications

European Synchrotron Radiation Facility, BP 220, 38043 Grenoble CEDEX, France

Petr Štěpánek

159 shared publications

Institute of Macromolecular Chemistry, Prague, Czech Republic

J. Julio Camarero

135 shared publications

Instituto Pirenaico de Ecología (IPE-CSIC); Zaragoza Spain

Manuel Seeger

95 shared publications

Klinik für Innere Medizin I, UKSH, Campus Kiel, Sonografie, Kiel, Deutschland

P. Serrano

90 shared publications

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA

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Publication Record
Distribution of Articles published per year 
(2000 - 2018)
Total number of journals
published in
 
40
 
Publications See all
Article 0 Reads 0 Citations Recent trends reveal decreasing intensity of daily precipitation in Spain Roberto Serrano-Notivoli, Santiago Beguería, Miguel Ángel Sa... Published: 18 July 2018
International Journal of Climatology, doi: 10.1002/joc.5562
DOI See at publisher website
Article 0 Reads 0 Citations Comparison of precipitation measurements by OTT Parsivel2 and Thies LPM optical disdrometers Marta Angulo-Martínez, Santiago Beguería, Borja Latorre, Mar... Published: 08 May 2018
Hydrology and Earth System Sciences, doi: 10.5194/hess-22-2811-2018
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Optical disdrometers are present weather sensors with the ability of providing detailed information on precipitation such as rain intensity, radar reflectivity or kinetic energy, together with discrete information on the particle size and fall velocity distribution (PSVD) of the hydrometeors. Disdrometers constitute a step forward towards a more complete characterization of precipitation, being useful in several research fields and applications. In this article the performance of two extensively used optical disdrometers, the most recent version of OTT Parsivel2 disdrometer and Thies Clima Laser Precipitation Monitor (LPM), is evaluated. During 2 years, four collocated optical disdrometers, two Thies Clima LPM and two OTT Parsivel2, collected up to 100000min of data and up to 30000min with rain in more than 200 rainfall events, with intensities peaking at 277mmh−1 in 1 minute. The analysis of these records shows significant differences between both disdrometer types for all integrated precipitation parameters, which can be explained by differences in the raw PSVD estimated by the two sensors. Thies LPM recorded a larger number of particles than Parsivel2 and a higher proportion of small particles than OTT Parsivel2, resulting in higher rain rates and totals and differences in radar reflectivity and kinetic energy. These differences increased greatly with rainfall intensity. Possible causes of these differences, and their practical consequences, are discussed in order to help researchers and users in the choice of sensor, and at the same time pointing out limitations to be addressed in future studies.
Article 0 Reads 1 Citation Regional Crop Gross Primary Productivity and Yield Estimation Using Fused Landsat-MODIS Data Mingzhu He, John Kimball, Marco Maneta, Bruce Maxwell, Alvar... Published: 28 February 2018
Remote Sensing, doi: 10.3390/rs10030372
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Accurate crop yield assessments using satellite remote sensing-based methods are of interest for regional monitoring and the design of policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations is generally too coarse to capture cropland heterogeneity. The fusion of data from different sensors can provide enhanced information and overcome many of the limitations of individual sensors. In thitables study, we estimate annual crop yields for seven important crop types across Montana in the continental USA from 2008–2015, including alfalfa, barley, maize, peas, durum wheat, spring wheat and winter wheat. We used a satellite data-driven light use efficiency (LUE) model to estimate gross primary productivity (GPP) over croplands at 30-m spatial resolution and eight-day time steps using a fused NDVI dataset constructed by blending Landsat (5 or 7) and Terra MODIS reflectance data. The fused 30-m NDVI record showed good consistency with the original Landsat and MODIS data, but provides better spatiotemporal delineations of cropland vegetation growth. Crop yields were estimated at 30-m resolution as the product of estimated GPP accumulated over the growing season and a crop-specific harvest index (HIGPP). The resulting GPP estimates capture characteristic cropland productivity patterns and seasonal variations, while the estimated annual crop production results correspond favorably with reported county-level crop production data (r = 0.96, relative RMSE = 37.0%, p < 0.05) from the U.S. Department of Agriculture (USDA). The performance of estimated crop yields at a finer (field) scale was generally lower, but still meaningful (r = 0.42, relative RMSE = 50.8%, p < 0.05). Our methods and results are suitable for operational applications of crop yield monitoring at regional scales, suggesting the potential of using global satellite observations to improve agricultural management, policy decisions and regional/global food security.
Article 0 Reads 0 Citations Comparison of precipitation measurements by Ott Parsivel2 and Thies LPM optical disdrometers Marta Angulo-Martínez, Santiago Beguería, Borja Latorre, Mar... Published: 14 November 2017
Hydrology and Earth System Sciences Discussions, doi: 10.5194/hess-2017-652
DOI See at publisher website
ABS Show/hide abstract
Optical disdrometers are present weather sensors with the ability of providing detailed information of precipitation such as rain intensity, kinetic energy or radar reflectivity, together with discrete information on the distribution of particle sizes and fall velocities (PSVD) of the hydrometeors. Disdrometers constitute a step forward towards a more complete characterisation of precipitation, being highly useful in several research fields and applications. In this article the performance of the two optical disdrometer most extensively used, the most recent version of Ott PARSIVEL2 disdrometer and Thies Clima Laser Precipitation Monitor, is evaluated. During a two years precipitation observation experiment, four collocated optical disdrometers, two Thies Clima LPM and two Ott PARSIVEL2, recorded 58761 common one-minute precipitation observations, totalling 221 natural rainfall events, with intensities peaking at 220&thinsp;mm&thinsp;h&minus;1. The results show significant differences between both disdrometer types for all integrated precipitation parameters, which can be explained by differences in the raw particle size and velocity distribution (PSVD). Thies LPM recorded in average double number of particles than PARSIVEL2. PSVD percentile comparison showed Thies LPM measuring more small particles than Ott Parsivel2, resulting in higher rain rates and totals. These differences increased greatly with rainfall intensity. At rain rates above 10&thinsp;mm&thinsp;h&minus;1 Thies LPM recorded nine times the number of particles of PARSIVEL2, affecting all precipitation variables. The practical consequences of these differences, and possible reasons, are discussed, in order to help researchers and users in the election of the sensor, pointing out at the same time limitations to be fixed in future versions.
Article 0 Reads 1 Citation SPREAD: A high-resolution daily gridded precipitation dataset for Spain Roberto Serrano-Notivoli, Santiago Beguería, Miguel Ángel Sa... Published: 07 June 2017
Earth System Science Data Discussions, doi: 10.5194/essd-2017-35
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A high-resolution daily gridded precipitation dataset was built from raw data of 12,858 observatories covering a period from 1950 to 2012 in peninsular Spain and 1971 to 2012 in Balearic and Canary Islands. The original data were quality controlled and gaps were filled on each day and location independently. Using the serially-complete dataset, a grid with a 5 x 5 kilometres spatial resolution was constructed by estimating daily precipitation amounts and their corresponding uncertainty at each grid node. Daily precipitation estimations were compared to original observations to assess the quality of the gridded dataset. Four daily precipitation indices were computed to characterize the spatial distribution of daily precipitation and nine extreme precipitation indices were used to describe the frequency and intensity of extreme precipitation events. The use of the total available data in Spain, the independent estimation of precipitation for each day and the high spatial resolution of the grid allowed for a precise spatial and temporal assessment of daily precipitation that are difficult to achieve when using other methods, pre- selected long-term stations or global gridded datasets. SPREAD dataset is publicly available at http://dx.doi.org/10.20350/digitalCSIC/7393.
Article 0 Reads 10 Citations Ongoing and Emerging Questions in Water Erosion Studies José M. García-Ruiz, Santiago Beguería, Noemí Lana-Renault, ... Published: 12 December 2016
Land Degradation & Development, doi: 10.1002/ldr.2641
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