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Accuracy of daily estimation of grass reference evapotranspiration using ERA-Interim reanalysis products with assessment of alternative bias correction schemes

Published on Nov 1, 2018in Agricultural Water Management 3.18
· DOI :10.1016/j.agwat.2018.08.003
Paula Paredes18
Estimated H-index: 18
(Instituto Politécnico Nacional),
Diogo S. Martins6
Estimated H-index: 6
(Instituto Superior de Agronomia)
+ 2 AuthorsCarlos Pires10
Estimated H-index: 10
(University of Lisbon)
Abstract
Abstract This study aims at assessing the accuracy of estimating daily grass reference evapotranspiration (PM-ET o ) computed with ERA-Interim reanalysis products, as well as to assess the quality of reanalysis products as predictors of daily maximum and minimum temperature, net radiation, dew point temperature and wind speed, which are used to compute PM-ET o . With this propose, ET o computed from local observations of weather variables in 24 weather stations distributed across Continental Portugal were compared with reanalysis-based values of ET o (ET o REAN ). Three different versions of these reanalysis-based ET o were computed: (i) an (uncorrected) ET o based on the individual weather variables for the nearest grid point to the weather station; (ii) the previously calculated ET o corrected for bias with a simple bias-correction rule based only on the nearest grid point; and (iii) the ET o corrected for bias with a more complex rule involving all grid points in a 100 km radius of the weather station. Both bias correction approaches were tested aggregating data on a monthly, quarterly and a single overall basis. Cross-validation was used to allow evaluating the uncertainties that are modelled independently of any forcing; with this purpose, data sets were divided into two groups. Results show that ET o REAN without bias correction is strongly correlated with PM-ET o (R 2 >0.80) but tends to over-estimate PM-ET o , with the slope of the regression forced to the origin b 0  ≥ 1.05, a mean RMSE of 0.79 mm day −1 , and with EF generally above 0.70. Cross-validation results showed that using both bias correction methods improved the accuracy of estimations, in particular when a monthly aggregation was used. In addition, results showed that using the multiple regression correction method outperforms the additive bias correction leading to lower RMSE, with mean RMSE of 0.57 and 0.64 mm day −1 respectively. The selection of the bias correction approach to be adopted should balance the ease of use, the quality of results and the ability to capture the intra-annual seasonality of ET o . Thus, for irrigation scheduling operational purposes, we propose the use of the additive bias correction with a quarterly aggregation.
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  • Citations (1)
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References78
Newest
Published on Jan 1, 2019in Climate Dynamics 3.77
Rita M. Cardoso16
Estimated H-index: 16
(University of Lisbon),
Pedro M. M. Soares19
Estimated H-index: 19
(University of Lisbon)
+ 1 AuthorsPedro M. A. Miranda23
Estimated H-index: 23
(University of Lisbon)
Large temperature spatio-temporal gradients are a common feature of Mediterranean climates. The Portuguese complex topography and coastlines enhances such features, and in a small region large temperature gradients with high interannual variability is detected. In this study, the EURO-CORDEX high-resolution regional climate simulations (0.11° and 0.44° resolutions) are used to investigate the maximum and minimum temperature projections across the twenty-first century according to RCP4.5 and RCP8...
5 Citations Source Cite
Published on Nov 1, 2018in Theoretical and Applied Climatology 2.32
Paula Paredes18
Estimated H-index: 18
(University of Lisbon),
J. C. Fontes4
Estimated H-index: 4
(University of the Azores)
+ 1 AuthorsLuis S. Pereira51
Estimated H-index: 51
(University of Lisbon)
Reference crop evapotranspiration (ETo) estimations using the FAO Penman-Monteith equation (PM-ETo) require a set of weather data including maximum and minimum air temperatures (T max, T min), actual vapor pressure (e a), solar radiation (R s), and wind speed (u 2). However, those data are often not available, or data sets are incomplete due to missing values. A set of procedures were proposed in FAO56 (Allen et al. 1998) to overcome these limitations, and which accuracy for estimating daily ETo...
4 Citations Source Cite
Published on Jan 1, 2018in Theoretical and Applied Climatology 2.32
Javier Almorox14
Estimated H-index: 14
(Technical University of Madrid),
Alfonso Senatore12
Estimated H-index: 12
(University of Calabria)
+ 1 AuthorsGiuseppe Mendicino11
Estimated H-index: 11
(University of Calabria)
When not all the meteorological data needed for estimating reference evapotranspiration ETo are available, a Penman–Monteith temperature (PMT) equation can be adopted using only measured maximum and minimum air temperature data. The performance of the PMT method is evaluated and compared with the Hargreaves–Samani (HS) equation using the measured long-term monthly data of the FAO global climatic dataset New LocClim. The objective is to evaluate the quality of the PMT method for different climate...
8 Citations Source Cite
Published on Sep 1, 2017in Renewable & Sustainable Energy Reviews 9.18
R. Urraca10
Estimated H-index: 10
(University of La Rioja),
E. Martinez-de-Pison1
Estimated H-index: 1
(University of La Rioja)
+ 2 AuthorsF. Antonanzas-Torres13
Estimated H-index: 13
(University of La Rioja)
Solar radiation can be estimated by a variety of methods in an attempt to overcome the limitations of on-ground records. Novel methods are often appearing but these are rarely compared to others from a different approach. This study surveys the main types of estimation methods for daily Global Horizontal Irradiation (GHI), and then, one characteristic technique per group is selected, discarding possible hybrid approaches: a parametric model based on temperatures and precipitation (Antonanzas mod...
17 Citations Source Cite
Published on Sep 1, 2017in Journal of Advances in Modeling Earth Systems 3.97
Alan K. Betts53
Estimated H-index: 53
,
Anton Beljaars44
Estimated H-index: 44
We quantify the biases in the diurnal cycle of temperature in ERA-Interim for both warm and cold season using hourly climate station data for four stations in Saskatchewan from 1979 to 2006. The warm season biases increase as opaque cloud cover decreases, and change substantially from April to October. The bias in mean temperature increases almost monotonically from small negative values in April to small positive values in the fall. Under clear skies, the bias in maximum temperature is of the o...
3 Citations Source Cite
Published on Aug 1, 2017in Water Resources Management 2.64
Luis S. Pereira51
Estimated H-index: 51
(University of Lisbon)
Abstract Population growth, increasing demands for food, ever-growing competition for water, reduced supply reliability, climate change and climate uncertainty and droughts, decline in critical ecosystems services, competition for land use, changing regulatory environments, and less participatory water resources governance are contributing to increasing difficulties and challenges in water resource management for agriculture and food. The need for sustainable food security for our global populat...
14 Citations Source Cite
Published on Jul 1, 2017in Agricultural Water Management 3.18
Paula Paredes18
Estimated H-index: 18
(Instituto Superior de Agronomia),
Luis S. Pereira51
Estimated H-index: 51
(Instituto Superior de Agronomia)
+ 2 AuthorsMaria Odete Torres7
Estimated H-index: 7
(Instituto Superior de Agronomia)
Aiming at improved knowledge on water use, productivity and irrigation scheduling of processing pea, the soil water balance model SIMDualKc was calibrated and validated using field data observed in two farmers’ fields in a wet and a dry year. The model uses the dual crop coefficient approach for partitioning crop evapotranspiration into crop transpiration and soil evaporation. Calibration was performed by minimizing differences between measured and simulated soil water content with a root mean s...
5 Citations Source Cite
Published on May 1, 2017in Journal of Hydrology 3.73
Courtenay Strong17
Estimated H-index: 17
(University of Utah),
Krishna B. Khatri1
Estimated H-index: 1
(University of Utah)
+ 2 AuthorsL. Niel Allen2
Estimated H-index: 2
(Utah State University)
Abstract The main objective of this study was to investigate whether dynamically downscaled high resolution (4-km) climate data from the Weather Research and Forecasting (WRF) model provide physically meaningful additional information for reference evapotranspiration ( E ) calculation compared to the recently published GridET framework that uses interpolation from coarser-scale simulations run at 32-km resolution. The analysis focuses on complex terrain of Utah in the western United States for y...
4 Citations Source Cite
Published on Apr 1, 2017in International Journal of Climatology 3.10
Diogo S. Martins6
Estimated H-index: 6
(Instituto Superior de Agronomia),
Paula Paredes18
Estimated H-index: 18
(Instituto Superior de Agronomia)
+ 3 AuthorsLuis S. Pereira51
Estimated H-index: 51
(University of Lisbon)
Computing crop reference evapotranspiration (ETo) with the FAO Penman–Monteith method (PM-ETo) requires maximum and minimum air temperature, shortwave radiation, relative air humidity and wind speed. These data are often not available, thus requiring alternative computation procedures. Although some proposed approximations may provide ETo values with small estimation errors, the physics of the ET processes may then not be well described. The use of reanalysis data, which is common in climate stu...
6 Citations Source Cite
Published on Mar 1, 2017in Agricultural Water Management 3.18
Miquel Tomas-Burguera10
Estimated H-index: 10
(Spanish National Research Council),
Sergio M. Vicente-Serrano49
Estimated H-index: 49
(Spanish National Research Council)
+ 1 AuthorsSantiago Beguería Portugués46
Estimated H-index: 46
(Spanish National Research Council)
The standard approach for computing reference crop evapotranspiration (ETo) is the FAO-56 Penman-Monteith (FAO-PM) method, which requires data on air temperature, radiation, air humidity and wind speed. Unlike air temperature the other variables are less frequently available, hindering the application of FAO-PM. A lot of efforts exist to find the best method to estimate FAO-PM ETo when some variables are not available. The FAO-56 manual recommends to estimate the missing variables based on those...
12 Citations Source Cite
Cited By1
Newest
Published on Apr 1, 2019in Agricultural Water Management 3.18
Paula Paredes18
Estimated H-index: 18
(Instituto Superior de Agronomia),
Luis S. Pereira51
Estimated H-index: 51
(Instituto Superior de Agronomia)
Abstract The computation of the reference crop evapotranspiration (ET o ) using the FAO Penman-Monteith equation (PM-ET o ) requires data on maximum and minimum air temperatures (T max , T min ), vapour pressure deficit (VPD), solar radiation (R s ) and wind speed at 2 m height (u 2 ). However, those data are often not available, or data sets may be incomplete or have questionable quality. Various procedures were proposed in FAO56 to overcome these limitations and an abundant literature has been...
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