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Selecting the optimal method to calculate daily global reference potential evaporation from CFSR reanalysis data for application in a hydrological model study

机译:从CFSR再分析数据中选择最佳方法来计算每日全球参考潜能,以用于水文模型研究

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Potential evaporation (PET) is one of the main inputs of hydrological models. Yet, there is limited consensus on which PET equation is most applicable in hydrological climate impact assessments. In this study six different methods to derive global scale reference PET daily time series from Climate Forecast System Reanalysis (CFSR) data are compared: Penman-Monteith, Priestley-Taylor and original and re-calibrated versions of the Hargreaves and Blaney-Criddle method. The calculated PET time series are (1) evaluated against global monthly Penman-Monteith PET time series calculated from CRU data and (2) tested on their usability for modeling of global discharge cycles. A major finding is that for part of the investigated basins the selection of a PET method may have only a minor influence on the resulting river flow. Within the hydrological model used in this study the bias related to the PET method tends to decrease while going from PET, AET and runoff to discharge calculations. However, the performance of individual PET methods appears to be spatially variable, which stresses the necessity to select the most accurate and spatially stable PET method. The lowest root mean squared differences and the least significant deviations (95% significance level) between monthly CFSR derived PET time series and CRU derived PET were obtained for a cell-specific re-calibrated Blaney-Criddle equation. However, results show that this re-calibrated form is likely to be unstable under changing climate conditions and less reliable for the calculation of daily time series. Although often recommended, the Penman-Monteith equation applied to the CFSR data did not outperform the other methods in a evaluation against PET derived with the Penman-Monteith equation from CRU data. In arid regions (e.g. Sahara, central Australia, US deserts), the equation resulted in relatively low PET values and, consequently, led to relatively high discharge values for dry basins (e.g. Orange, Murray and Zambezi). Furthermore, the Penman-Monteith equation has a high data demand and the equation is sensitive to input data inaccuracy. Therefore, we recommend the re-calibrated form of the Hargreaves equation which globally gave reference PET values comparable to CRU derived values for multiple climate conditions. The resulting gridded daily PET time series provide a new reference dataset that can be used for future hydrological impact assessments in further research, or more specifically, for the statistical downscaling of daily PET derived from raw GCM data. The dataset can be downloaded from http://opendap.deltares.nl/thredds/dodsC/opendap/ deltares/FEWS-IPCC.
机译:潜在蒸发(PET)是水文模型的主要输入之一。然而,关于哪种PET方程最适用于水文气候影响评估的共识有限。在这项研究中,比较了六种从气候预测系统再分析(CFSR)数据中得出全球规模参考PET每日时间序列的方法:Penman-Monteith,Priestley-Taylor以及Hargreaves和Blaney-Criddle方法的原始版本和重新校准版本。对计算的PET时间序列进行(1)对照从CRU数据计算得出的全球每月Penman-Monteith PET时间序列进行评估,以及(2)测试其对全球放电周期建模的可用性。一个主要发现是,对于部分被调查流域,PET方法的选择可能只对最终的河流流量产生较小的影响。在本研究中使用的水文模型中,与PET方法相关的偏差会随着从PET,AET和径流到流量计算的趋向而减小。但是,各个PET方法的性能似乎在空间上是可变的,这强调了选择最准确和空间稳定的PET方法的必要性。对于特定于细胞的重新校准的Blaney-Criddle方程,获得了每月CFSR衍生的PET时间序列和CRU衍生的PET之间的最低均方差和最低显着性差异(95%显着性水平)。但是,结果表明,这种重新校准的表格在变化的气候条件下可能不稳定,并且对于每日时间序列的计算不太可靠。尽管经常被推荐,但是在对从CRU数据得出的Penman-Monteith方程得出的PET进行评估时,应用于CFSR数据的Penman-Monteith方程并没有优于其他方法。在干旱地区(例如撒哈拉沙漠,澳大利亚中部,美国沙漠),该方程式得出的PET值相对较低,因此导致干盆地(例如Orange,Murray和Zambezi)的排放量较高。此外,Penman-Monteith方程对数据的要求很高,并且该方程对输入数据的不精确性敏感。因此,我们建议采用Hargreaves方程的重新校准形式,该方程可全局给出与多个气候条件下CRU得出的值相当的参考PET值。由此产生的网格化的每日PET时间序列提供了一个新的参考数据集,可用于将来的水文影响评估,以进行进一步的研究,或更具体地说,可用于从原始GCM数据得出的每日PET的统计缩减。可以从http://opendap.deltares.nl/thredds/dodsC/opendap/deltares/FEWS-IPCC下载数据集。

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