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Subseasonal-to-seasonal (S2S) precipitation prediction in boreal spring and summer months, which contains a significant number of high-signal events, is scientifically challenging and prediction skill has remained poor for years. Tibetan Plateau (TP) spring observed surface temperatures show a lag correlation with summer precipitation in several remote regions, but current global land-atmosphere coupled models are unable to represent this behavior due to significant errors in producing observed TP surface temperatures. To address these issues, the Global Energy and Water Exchanges (GEWEX) program launched the “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal-to-Seasonal Prediction” (LS4P) initiative as a community effort to test the impact of land temperature in high mountain regions on S2S prediction by climate models: more than 40 institutions worldwide are participating in this project. After using an innovative new land state initialization approach based on observed surface 2-meter temperature over the TP in the LS4P experiment, results from a multi-model ensemble provide evidence for a causal relationship in the observed association between the Plateau spring land temperature and summer precipitation over several regions across the world through teleconnections. The influence is underscored by an out-of-phase oscillation between the TP and Rocky Mountain surface temperatures. This study reveals for the first time that high mountain land temperature could be a substantial source of S2S precipitation predictability, and its effect is probably as large as ocean surface temperature over global “hot spot” regions identified here; the ensemble means in some “hot spots” produce more than 40% of the observed anomalies. This LS4P approach should stimulate more follow-on explorations.

Although native vegetation is a determinant of aquatic ecosystems' maintenance, forest restoration has been linked to decreases in water yields worldwide. Here, we clarify linkages between forest restoration and water services and identify gaps in the literature critical for evaluating the benefits of forest restoration on water yields. Also, we discuss possible strategies to improve forest restoration planning and implementation. We argue that the apparent disconnect between estimates in the literature and real‐world observation reflects the limitation of studies, methods, and approaches in capturing forest and water relationships' complex nature. Future research should focus on hydrologic parameters other than annual streamflow flow (such as infiltration, groundwater recharge, and flow regulation) and encompass broader spatial–temporal scales. More empirical studies are needed, especially in the tropics, as the forest–water dynamics in these areas are unique and poorly understood. Filling this gap is critical to improving the decision‐making process related to water management and governance.

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Climate change is one of the greatest issues for human society. The objective of this study is to assess the impacts of future climate change on seasonal average discharge and monthly water budget in a small headwater catchment, located on the Grande River basin, in Minas Gerais, Brazil. The assessment is carried out using the hydrology model, DHSVM. The atmospheric forcing to drive the Distributed Hydrology-Soil-Vegetation Model (DHSVM) is derived from the downscaling of the HadGEM2-ES projections by the Eta Regional Climate Model, at 5-km high resolution. The projections assume the RCP4.5 and RCP8.5 IPCC AR5 emission scenarios. Baseline period was taken between 1961 and 1990. The projections are assessed in three time slices (2011-2040, 2041-2070 and 2071-2099). The climate change is assessed in time slices of 30 years and in comparison against the baseline period to evaluate the hydrological changes in the catchment. The results showed differences in the hydrological behavior between the emission scenarios and though time slices. Reductions in the magnitude of the seasonal average discharge and monthly water budget may alter the water availability. Under the RCP4.5 scenario, results show greater reductions in the water availability in the first time slice, whereas under RCP8.5 scenario greater reductions are indicated in the third time slice.