## 3 Results  
### Spatiotemporal Comparison among New and Existing Modeled Evaporative Fluxes  
Figure 2a presents the annual evapotranspiration (ET) estimates across the study region from all models. As expected, the total annual ET varies based on climatic conditions. Lower values (0-500 mm) are observed over Turkey, the Middle East-North African belt, and Spain, reflecting their aridity. Conversely, regions like Italy, the Balkans, France, and Portugal exhibit higher ET (>500 mm), indicating a more humid climate with a larger contribution of ET (Figure 2a). Interestingly, the SCOPE model shows comparatively higher ET estimates for semi-arid regions like Turkey compared to other models. This discrepancy highlights the importance of model selection and the influence of input data on ET estimates. In the case of SCOPE, the lack of explicit water availability constraints may be leading to overestimations in semi-arid regions. The spatial patterns of ET in cultivated regions like the Nile Delta in Egypt are generally well captured by STEPS, TSEB, and SCOPE, but not by GLEAM and TerraClimate. This highlights the difference in how these models estimate ET. Studies have shown that average ET rates in the Nile Delta range from 705 mm/year for croplands to 1099 mm/year for forests [47]. Our findings of comparable ET patterns over the Nile with STEPS, TSEB, and SCOPE are consistent with these observations. The discrepancies in the annual pattern between models and products highlight the difference of approaches for ET estimation. Models like STEPS, SCOPE, TSEB, and MOD16A2 rely on LAI- and LST-driven schemes. These models perform well in capturing ET over cultivated semi-arid regions. However, models like GLEAM and TerraClimate take precipitation as the main input, which can lead to significant underestimations in the arid areas. The variability in ET in agroecosystems is largely influenced by vegetation characteristics like species composition and LAI [48]. For example, the spatial pattern of STEPS-ET closely resembles MOD16A2, particularly over southern Europe. This similarity is likely due to their use of a common LAI dataset and the Penman-Monteith approach. In contrast, TSEB and SCOPE, which incorporate LST, canopy temperature, and radiative responses, show greater spatial variability in ET across irrigated and non-irrigated zones. This study represents the first combined regional-scale evaluation of these models (STEPS, SCOPE, TSEB) for ET estimation in the Mediterranean. The results provide some  
Figure 2: (**a**) Total ET estimated from observed models [TSEB, SCOPE, STEPS] and reference products [GLEAM, MOD16, TerraClimate] over the Mediterranean region with their aggregated sum over major land cover types (**b**). Uncertainty is expected from the use of high-resolution land cover data (ESA—100 m WorldCover) for comparison. confidence in the ability of these models, particularly those incorporating LAI or LST, to capture ET over cultivated areas. However, limitations were also identified in areal coverage. Models relying solely on LAI exhibited missing values in arid regions of North Africa. Using precipitation as the main input in the case of GLEAM and TerraClimate also showed negligible ET estimates over irrigated zones. Figure 2b highlights the differential responses of the models to different land cover types across the Mediterranean. TSEB's estimates show minimal variation across land cover types at the 10 km resolution, likely due to pixel heterogeneity leading to uncertainty in canopy parameterization. This results in smaller gaps in ET between different land cover types. In contrast, SCOPE, due to its lack of explicit water limitations and its land cover-independent parameterization, produces higher ET values across all land cover types. However, LAI plays a dominant role in differentiating canopy response. Irrigated crops can also show higher ET than grasslands or shrublands, it is determined by SCOPE and TSEB.