This study assesses the accuracy of estimating daily grass reference evapotranspiration (PM-ET_o) using daily shortwave radiation (R_s) and reference evapotranspiration (ET_REF) products provided by the Meteosat Second Generation (MSG) geostationary satellite delivered by the Satellite Applications Facility on Land Surface Analysis (LSA-SAF) framework. The accuracy of using reanalysis ERA5 shortwave radiation data (R_{s ERA5}) provided by the European Center for Medium-Range Weather Forecasts (ECMWF) is also evaluated. The assessments were performed using observed weather variables at 37 weather stations distributed across continental Portugal, where climate conditions range from semi-arid to humid, and 12 weather stations located in Azores islands, characterized by humid, windy and often cloudy conditions. This study's use of data from a variety of climate conditions contributed to a unique and innovative assessment of the usability of LSA-SAF and ERA5 products for ET_o estimation. The first assessment focused on comparing LSA-SAF estimates of R_s (R_{s LSA-SAF}) against ground stations (R_{s ground}). The results showed a good matching between the two R_s data sets for continental Portugal but a tendency for R_{s LSA-SAF} to under-estimate R_{s ground} in the cloudy islands of Azores. ET_o values computed using R_{s LSA-SAF} data and observed temperature, humidity and wind speed (ET_{o LSA-SAF}) were then compared with PM-ET_o estimates with ground-based data, which were used as benchmark; input data of temperature and humidity needed for PM-ET_o were quality checked for surface aridity effects. It was observed that ET_{o LSA-SAF} is strongly correlated with PM-ET_o (R² > 0.97) for most locations in continental Portugal, with regression coefficient of a linear regression forced to the origin ranging between 0.95 and 1.05, mean root mean square error (RMSE) of 0.13 mm d⁻¹, and Nash and Sutcliff efficiency of modeling (EF) above 0.95. For most Azores locations, ET_{o LSA-SAF} over-estimated PM-ET_o. This is likely a consequence of the high spatio-temporal heterogeneity of weather conditions that occur in these oceanic islands together with the different footprints of satellite (averaged over the pixel) and station observations. Reanalysis ERA5 shortwave radiation data presented similar behavior to the LSA-SAF products, however with slightly lower accuracy. The daily LSA-SAF ET_REF product (ET_{REF LSA-SAF}) was assessed and results have shown a good accuracy of this product, with acceptable RMSE and high EF values, for continental Portugal but a low accuracy for the Azores islands. A simplified bias correction approach was shown to improve both ET_o derived from the LSA-SAF products, namely for Azores stations, which seem to be representative of smaller areas. The use of the FAO-PM temperature approach (PMT) was also assessed using the R_{s LSA-SAF} and R_{s ERA5} data, which showed a superiority of the LSA-SAF product for ET_o estimations (ET_{o PMT LSA-SAF}). No significant differences (p < 0.05) were observed in terms of the median value of the RMSE when adopting ET_{o PMT} and ET_{REF LSA-SAF}. Differently, results showed that using the R_{s LSA-SAF} in the PMT approach (ET_{o PMT LSA-SAF}) produces significantly better RMSE results than ET_{o PMT} and ET_{REF LSA-SAF}. Overall, the performed assessment allows concluding that the use of R_{s LSA-SAF,} and to a lesser extent the use of the R_{s ERA5}, highly improves the accuracy of computation of ET_o when R_s observations are not available, including when only temperature data are accessible. The use of the ET_{REF LSA-SAF} product is a good alternative when observed weather data are not available.

这项研究使用由卫星应用设施提供的Meteosat第二代（MSG）对地静止卫星提供的每日短波辐射（R _s）和参考蒸散量（ET _REF）产品评估估算每日草皮参考蒸散量（PM-ET _o）的准确性。地表分析（LSA-SAF）框架。使用重新分析ERA5短波辐射数据（R _{s ERA5}还对欧洲中型天气预报中心（ECMWF）提供的）进行了评估。评估是使用观测到的天气变量在分布于葡萄牙大陆（气候条件从半干旱到潮湿）的37个气象站以及位于亚速尔群岛的12个气象站进行的，这些气象站的特点是潮湿，多风和经常多云。这项研究对来自各种气候条件的数据的使用有助于对LSA-SAF和ERA5产品用于ET _o估计的可用性进行独特而创新的评估。第一次评估的重点是将R _s（R _{s LSA-SAF}）与地面站（R _{s ground}）的LSA-SAF估计值进行比较。结果表明两个R之间有很好的匹配葡萄牙大陆_的数据集，但R_的LSA-SAF趋势低估了亚速尔群岛阴天岛屿上的R_地面。ET _ø值，使用R计算_{小号LSA-SAF}数据和观察到的温度，湿度和风速（ET _öLSA-SAF）然后用PM-ET相比_ö与基于地面的数据，该数据被用作基准估算; 对PM-ET _o所需的温度和湿度输入数据进行了表面干旱效应的质量检查。观察到ET _{o LSA-SAF}与PM-ET _o（R ²> 0.97），在葡萄牙大陆上的大多数地区，线性回归的回归系数被迫介于0.95和1.05之间，均方根误差（RMSE）为0.13 mm d ^-1，建模的纳什和苏克利夫效率（ EF）高于0.95。对于大多数亚速尔群岛地区，ET _{o LSA-SAF}高估了PM-ET _o。这可能是由于这些大洋岛屿上天气条件的时空高度异质性以及卫星（在像素上平均）和站台观测的不同足迹所致。重新分析ERA5短波辐射数据的行为与LSA-SAF产品相似，但准确性略低。每日LSA-SAF ET _REF产品（ET_{对REF LSA-SAF}进行了评估，结果表明该产品对于葡萄牙大陆具有良好的精度，具有可接受的RMSE和较高的EF值，但对于亚速尔群岛则为低精度。结果表明，一种简化的偏差校正方法可以改善源自LSA-SAF产品的两种ET _o，即对于亚速尔群岛台站而言，这似乎是较小区域的代表。还使用R _{s LSA-SAF}和R _{s ERA5}数据评估了FAO-PM温度法（PMT）的使用，这表明LSA-SAF产品在ET _o估计（ET _{o PMT LSA-SAF}）方面具有优势。 。采用ET _{o PMT}时，RMSE的中位数方面无显着差异（p <0.05）和ET _{REF LSA-SAF}。不同的是，结果表明，在PMT方法中使用R _{s LSA-SAF}（ET _{o PMT LSA-SAF}）产生的RMSE结果要比ET _{o PMT}和ET _{REF LSA-SAF}好得多。总体而言，所执行的评估可以得出结论，在没有R _s观测值时（包括仅当R _s观测值可用时），使用R _{s LSA-SAF}以及在较小程度上使用R _{s ERA5}可以_大大提高ET _o的计算精度。温度数据是可访问的。当没有观测到的天气数据时，可以使用ET _{REF LSA-SAF}产品。