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首页> 外文期刊>Agricultural Water Management >Accuracy of daily estimation of grass reference evapotranspiration using ERA-Interim reanalysis products with assessment of alternative bias correction schemes
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Accuracy of daily estimation of grass reference evapotranspiration using ERA-Interim reanalysis products with assessment of alternative bias correction schemes

机译：使用ERA-Instim Reanalysis Produper评估替代偏置方案的日期评估蒸发草参考蒸发的准确性

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摘要

This study aims at assessing the accuracy of estimating daily grass reference evapotranspiration (PM-ETo) 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-ETo. With this propose, ETo computed from local observations of weather variables in 24 weather stations distributed across Continental Portugal were compared with reanalysis-based values of ETo (ETo (REAN)). Three different versions of these reanalysis-based ETo were computed: (i) an (uncorrected) ETo based on the individual weather variables for the nearest grid point to the weather station; (ii) the previously calculated ETo corrected for bias with a simple bias-correction rule based only on the nearest grid point; and (iii) the ETo 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 ETo (REAN) without bias correction is strongly correlated with PM-ETo (R-2 & 0.80) but tends to over-estimate PM-ETo, with the slope of the regression forced to the origin b(o) &= 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 ETo. Thus, for irrigation scheduling operational purposes, we propose the use of the additive bias correction with a quarterly aggregation.
机译：本研究旨在评估用ERA-临时再分析产品计算的每日草参考蒸散（PM-ETO）的准确性，以及评估再分析产品的质量作为日常最大和最小温度，净辐射，露点的预测因子温度和风速，用于计算PM-ETO。利用这一提议，与遍布大陆葡萄牙的24个气象站的局部观测结果计算的ETO与EtO的重新分析的值进行了比较（ETO（rean））。基于基于Reanalysical的ETO的三种不同版本：（i）基于最近网格点到气象站的各个天气变量的（未校正的）eto; （ii）仅基于最接近的网格点的简单偏压规则校正先前计算的ETO; （iii）ETO纠正了偏差，具有更复杂的规则，涉及涉及100公里的气象站半径的所有网格点。两个偏压校正方法都在每月，季度和单一的总体上进行聚合数据。交叉验证用于允许评估独立于任何迫使建模的不确定性;为此目的，数据集分为两组。结果表明，没有偏压校正的ETO（雷切）与PM-ETO（R-2＆amp; 0.80）强烈相关，但倾向于过度估计PM-ETO，其中回归的斜率被迫到原点B（O. ）＆amp; = 1.05，平均RMSE为0.79毫米（-1），并且EF通常高于0.70。交叉验证结果表明，使用双偏压校正方法提高了估计的准确性，特别是当使用每月聚合时。另外，结果表明，使用多元回归校正方法优于较低的RMSE的添加剂偏压校正，分别为0.57和0.64mm（-1）的平均RMSE。选择偏置校正方法应采用的易用性，易于使用，质量和捕获eTO的年度内季节性的能力。因此，为了灌溉调度操作目的，我们提出了用季度聚集的添加剂偏压校正。

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