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Land‐use/cover change (LUCC) is an important driver of environmental change, occurring at the same time as, and often interacting with, global climate change. Reforestation and deforestation have been critical aspects of LUCC over the past two centuries and are widely studied for their potential to perturb the global carbon cycle. More recently, there has been keen interest in understanding the extent to which reforestation affects terrestrial energy cycling and thus surface temperature directly by altering surface physical properties (e.g., albedo and emissivity) and land–atmosphere energy exchange. The impacts of reforestation on land surface temperature and their mechanisms are relatively well understood in tropical and boreal climates, but the effects of reforestation on warming and/or cooling in temperate zones are less certain. This study is designed to elucidate the biophysical mechanisms that link land cover and surface temperature in temperate ecosystems. To achieve this goal, we used data from six paired eddy‐covariance towers over co‐located forests and grasslands in the temperate eastern United States, where radiation components, latent and sensible heat fluxes, and meteorological conditions were measured. The results show that, at the annual time scale, the surface of the forests is 1–2°C cooler than grasslands, indicating a substantial cooling effect of reforestation. The enhanced latent and sensible heat fluxes of forests have an average cooling effect of −2.5°C, which offsets the net warming effect (+1.5°C) of albedo warming (+2.3°C) and emissivity cooling effect (−0.8°C) associated with surface properties. Additional daytime cooling over forests is driven by local feedbacks to incoming radiation. We further show that the forest cooling effect is most pronounced when land surface temperature is higher, often exceeding −5°C. Our results contribute important observational evidence that reforestation in the temperate zone offers opportunities for local climate mitigation and adaptation. [ABSTRACT FROM AUTHOR]

• Water balance models on different timescales were integrated into a unified framework. • Interannual water storage change is an important factor for an accurate annual water balance model. • Precipitation seasonality closely correlated with the performance of monthly water balance model. • Supply and demand limits of evapotranspiration is the commonality over varying timescales. At present, many conceptual water balance models have been proposed on monthly, annual, and mean annual timescales. With the increasing applications of these models, an emerging question is whether the water balance models on different timescales have some commonalities and can be integrated. To this end, this study established and applied a practical unified framework of water balance models that can be applied to different timescales. The framework was first developed on monthly timescale, where the water balance was captured by combining the "abcd" model and Budyko hypothesis with four parameters. Then, this framework was extended to annual and mean annual timescales under which certain parameters can be eliminated or assumed to be certain values. To be specific, on the annual timescale, the water balance was simulated by a Budyko-type model incorporating the water storage change; on the mean annual timescale the water balance was further simplified into a Budyko-type model which neglects the water storage change. Thus, all of the three typical water balance models on different timescales were unified to a general framework. The models were applied to 437 catchments in the contiguous United States with satisfying results achieved. Considering the water storage changes can improve the performance of annual water balance models in regions with clear interannual carrying water storage. Furthermore, the water balance models on different timescales share common supply and demand limits which is similar to Budyko hypothesis. [ABSTRACT FROM AUTHOR]