We thank the reviewer for the positive and constructive assessment of our manuscript.

(1) Precipitation variability across years and months

We agree that information on precipitation variability would help better contextualize the interpretation of ET differences between precipitation-driven models and reference datasets over irrigated areas. While Table 2 reports mean precipitation during the peak irrigation season, we will explicitly address interannual and intra-seasonal precipitation variability by presenting precipitation anomalies together with ET anomalies in the supplementary material, aggregated across the studied irrigated areas and relative to a common climatological reference period. These results will be briefly discussed in the main text to provide general climatic context and support the interpretation of the systematic behavior observed in precipitation-driven ET models.

(2) Precipitation variability in relation to Figure 7

We agree that showing precipitation variability alongside ET and NDVI would facilitate the interpretation of interannual ET variations during the irrigation season. Accordingly, we will complement Figure 7 by adding precipitation anomalies for the California case study and discuss these results in the text to enable a joint interpretation of precipitation variability, vegetation dynamics, and irrigation effects.

(3) Role of input data discrepancies

We acknowledge that differences in input datasets across ET products contribute to the observed differences, alongside model structural choices. While the manuscript already describes how key input variables (e.g. LST, LAI, meteorological forcings) shape ET estimates, we will clarify in the discussion that discrepancies in input datasets themselves (e.g. sensor characteristics, spatial and temporal resolution, and the quality and consistency of meteorological forcings) can also contribute to differences between ET products over irrigated areas.

A detailed, point-by-point response together with the revised manuscript will be provided at the revision stage.

We thank the reviewer for the very positive assessment of our study.

(1) Representation of irrigated regions in East Asia

We agree that East Asia, and in particular the North China Plain, hosts some of the world’s most intensively irrigated agricultural systems and exhibits strong irrigation-induced ET signals. The present analysis focuses on CONUS, Europe, and South Asia for data consistency reasons, as the irrigated-area map used in this study (GMIA v5) is most representative of conditions around the 2000-2010 period, whereas irrigated areas in the North China Plain have expanded rapidly since then. To avoid inconsistencies between irrigated-area information and the evaluation period, this region was not included in the quantitative analysis. Given the key role of East Asia at the global scale of irrigation, we will include a literature-based discussion on documented irrigation impacts on ET in this region.

(2) Role of climate conditions and irrigation practices

We agree that irrigation impacts on ET are influenced not only by irrigated area but also by regional climate conditions and irrigation practices. The revised manuscript will make this link more explicit in the discussion by clarifying how differences in climate regimes and irrigation methods across irrigated regions help explain the contrasted performance of ET products.

A detailed, point-by-point response together with the revised manuscript will be provided at the revision stage.

We thank the commenter for this detailed and constructive feedback. We appreciate the careful reading of the manuscript and the remarks concerning spatial aggregation effects, the representation of irrigated areas, sub-pixel heterogeneity in the eddy-covariance validation, the interpretation of model behavior during the 2014 California drought, and the references to recent irrigation-aware modeling studies.

These comments provide useful perspectives and will be taken into account where appropriate in the revised manuscript.