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Validated meteorological data are required to make climate assessments, related decisions and to appropriately compute other important parameters such as reference evapotranspiration (ET0), vital to accurately estimate crops water requirements. In addition, quality meteorological datasets will increase the reliability of the results obtained by scientific or technical models that use them. In semiarid regions, with a structural water deficit as province of Mendoza (Argentina), the integrity and quality of these data are crucial to improve ET0 estimates, ensuring an adequate irrigation water management. In this work, several quality, assurance procedures were applied to meteorological data-as a pre-requisite for ET0 computations-in order to detect erroneous and invalid data of each parameter from automated weather stations located in the three irrigated areas of province of Mendoza (Northern oasis, Western oasis and Southern oasis). Due to the lack and poor quality of solar radiation data, calibration of new based temperature solar radiation prediction models for each of the station are proposed. Results show the data flagged for each variable by range/limits, step, internal consistency and persistence tests, providing guidance of great value to end users. Finally, a simple comparison of ET0 estimations using original and validated meteorological datasets for each irrigated area in province of Mendoza is also reported. (C) 2016 Elsevier B.V. All rights reserved.