Eduardo García-Ortega

Prof. Dr. Eduardo García-Ortega

Environmental Institute. Universidad de LeónLeón
orcid

Research Focus & Metrics

Academic Career Length

32Years (1995-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2012 in Atmospheric Research
Verified
Journal Article
Closed access
FTFrancisco J. Tapiador
Francisco J. Tapiador
FTF.J. Turk
F.J. Turk
WPWalt Petersen
Walt Petersen
AHArthur Y. Hou
Arthur Y. Hou
Eduardo García-OrtegaEduardo García-Ortega
Eduardo García-Ortega
MCManuel de Castro
Manuel de Castro

1 May 2020 in Atmospheric Research
Verified
Journal Article
Closed access
FTFrancisco J. Tapiador
Francisco J. Tapiador
Andrés NavarroAndrés Navarro
Andrés Navarro
RMRaúl Moreno
Raúl Moreno
JSJosé Luis Sánchez
José Luis Sánchez
Eduardo García-OrtegaEduardo García-Ortega
Eduardo García-Ortega

1 November 2017 in Atmospheric Research
Verified
Journal Article
Closed access
FTF.J. Tapiador
F.J. Tapiador
Andrés NavarroAndrés Navarro
Andrés Navarro
Vincenzo LevizzaniVincenzo Levizzani
Vincenzo Levizzani
Eduardo García-OrtegaEduardo García-Ortega
Eduardo García-Ortega
GHG.J. Huffman
G.J. Huffman
WTW.-K. Tao
W.-K. Tao

23 October 2019 in Remote Sensing
Verified
Journal Article
Open access
PDF file
Andrés NavarroAndrés Navarro
Andrés Navarro
Eduardo García-OrtegaEduardo García-Ortega
Eduardo García-Ortega
AMAndrés Merino
Andrés Merino
JSJOSE LUIS SANCHEZ
JOSE LUIS SANCHEZ
CKChristian Kummerow
Christian Kummerow
Francisco J. TapiadorFrancisco J. Tapiador
Francisco J. Tapiador
This paper evaluates Integrated Multi-Satellite Retrievals from GPM (IMERG-F) over Europe for the period 2014–2018 in order to evaluate application of the retrievals to hydrology. IMERG-F is compared with a large pan-European precipitation dataset built on rain gauge stations, i.e., the ENSEMBLES OBServation (E-OBS) gridded dataset. Although there is overall agreement in the spatial distribution of mean precipitation (R2 = 0.8), important discrepancies are revealed in mountainous regions, specifically the Alps, Pyrenees, west coast of the British Isles, Scandinavia, the Iberian and Italian peninsulas, and the Adriatic coastline. The results show that the strongest contributors to poor performance are pixels where IMERG-F has no gauges available for adjustment. If rain gauges are available, IMERG-F yields results similar to those of the surface observations, although the performance varies by region. However, even accounting for gauge adjustment, IMERG-F systematically underestimates precipitation in the Alps and Scandinavian mountains. Conversely, IMERG-F overestimates precipitation in the British Isles, Italian Peninsula, Adriatic coastline, and eastern European plains. Additionally, the research shows that gauge adjustment worsens the spatial gradient of precipitation because of the coarse resolution of Global Precipitation Climatology Centre data.

1 March 2018 in Journal of Applied Meteorology and Climatology
Verified
Journal Article
Open access
SFSergio Fernández-González
Sergio Fernández-González
MMMaría Luisa Martín
María Luisa Martín
Eduardo García-OrtegaEduardo García-Ortega
Eduardo García-Ortega
AMAndrés Merino
Andrés Merino
JLJesús Lorenzana
Jesús Lorenzana
JRJavier Sanz Rodrigo
Javier Sanz Rodrigo
Wind energy requires accurate forecasts for adequate integration into the electric grid system. In addition, global atmospheric models are not able to simulate local winds in complex terrain, where wind farms are sometimes placed. For this reason, the use of mesoscale models is vital for estimating wind speed at wind turbine hub height. In this regard, the Weather Research and Forecasting (WRF) Model allows a user to apply different initial and boundary conditions as well as physical parameterizations. In this research, a sensitivity analysis of several physical schemes and initial and boundary conditions was performed for the Alaiz mountain range in the northern Iberian Peninsula, where several wind farms are located. Model performance was evaluated under various atmospheric stabilities and wind speeds. For validation purposes, a mast with anemometers installed at 40, 78, 90, and 118 m above ground level was used. The results indicate that performance of the Global Forecast System analysis and European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) as initial and boundary conditions was similar, although each performed better under certain meteorological conditions. With regard to physical schemes, there is no single combination of parameterizations that performs best during all weather conditions. Nevertheless, some combinations have been identified as inefficient, and therefore their use is discouraged. As a result, the validation of an ensemble prediction system composed of the best 12 deterministic simulations shows the most accurate results, obtaining relative errors in wind speed forecasts that are <15%.

1 February 2020 in Journal of Hydrometeorology
Verified
Journal Article
Closed access
FTFrancisco J. Tapiador
Francisco J. Tapiador
Andrés NavarroAndrés Navarro
Andrés Navarro
Eduardo García-OrtegaEduardo García-Ortega
Eduardo García-Ortega
AMAndrés Merino
Andrés Merino
JSJosé Luis Sánchez
José Luis Sánchez
CKChristian Kummerow
Christian Kummerow
After 5 years in orbit, the Global Precipitation Measurement (GPM) mission has produced enough quality-controlled data to allow the first validation of their precipitation estimates over Spain. High-quality gauge data from the meteorological network of the Spanish Meteorological Agency (AEMET) are used here to validate Integrated Multisatellite Retrievals for GPM (IMERG) level 3 estimates of surface precipitation. While aggregated values compare notably well, some differences are found in specific locations. The research investigates the sources of these discrepancies, which are found to be primarily related to the underestimation of orographic precipitation in the IMERG satellite products, as well as to the number of available gauges in the GPCC gauges used for calibrating IMERG. It is shown that IMERG provides suboptimal performance in poorly instrumented areas but that the estimate improves greatly when at least one rain gauge is available for the calibration process. A main, generally applicable conclusion from this research is that the IMERG satellite-derived estimates of precipitation are more useful (r2 > 0.80) for hydrology than interpolated fields of rain gauge measurements when at least one gauge is available for calibrating the satellite product. If no rain gauges were used, the results are still useful but with decreased mean performance (r2 ≈ 0.65). Such figures, however, are greatly improved if no coastal areas are included in the comparison. Removing them is a minor issue in terms of hydrologic impacts, as most rivers in Spain have their sources far from the coast.