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Vegetation is a major contributor of terrestrial evaporation and influences subsequent precipitation over land. Studies suggest that forests are crucial for moisture recycling, although the specific contribution of different vegetation to precipitation remains unclear. Using a moisture recycling approach, we investigate the contribution of transpiration from trees and non‐tree vegetation to precipitation over Africa. We use precipitation source regions from simulated atmospheric moisture trajectories, constrained by observation‐based evaporation and precipitation products, and fractional vegetation cover data. Our findings show that trees provide a higher flux to precipitation (∼777 mm year−1) than non‐tree vegetation (∼342 mm year−1). However, considering the smaller spatial extent of trees compared to non‐tree vegetation, precipitation in most watersheds effectively depends more on the latter. Overall, non‐tree vegetation appears equally important as trees in terms of volumetric contributions to precipitation, and deserves attention in further research, considering ongoing land use changes that affect the continental water cycle. Plain Language Summary: A large part of rainfall on Earth derives from evaporation from land. This process, referred to as terrestrial moisture recycling, is controlled for a large part by vegetation cover. Different classes of vegetation cover use water differently, but it is unclear how they contribute to moisture recycling (and thus precipitation) over land. In this study, we estimate the contribution of trees and other, non‐tree vegetation to precipitation over the African continent. We use major watersheds, and track back the source regions of rainfall. We find that overall, trees contribute relatively more to precipitation compared to non‐tree vegetation. However, due to the extensive coverage of other vegetation classes (such as grass‐ and shrublands), many regions depend on non‐tree vegetation for rainfall. Ongoing land use and land cover (LULC) changes may disturb terrestrial moisture recycling patterns. The findings of this study emphasize that the impacts of all LULC changes, including non‐tree vegetation, on the water cycle should be considered and further researched. Key Points: We provide a first estimate of the contribution of transpiration from trees and non‐tree vegetation to precipitation over major African watershedsOn average, trees contribute more to continental precipitation (777 mm year−1) compared to non‐tree vegetation (342 mm year−1)Considering the extent of non‐tree vegetation, most watersheds depend mostly on non‐tree transpiration for precipitation throughout the year [ABSTRACT FROM AUTHOR]

Groundwater is an important water source for evaporation, especially during dry conditions. Despite this recognition, plant access to groundwater is often neglected in global evaporation models. This study proposes a new, conceptual approach to incorporate plant access to groundwater in existing global evaporation models, and analyses the groundwater contribution to evaporation globally. To this end, the Global Land Evaporation Amsterdam Model (GLEAM) is used. The new GLEAM‐Hydro model relies on the linear reservoir assumption for modeling groundwater flow, and introduces a transpiration partitioning approach to estimate groundwater contributions. Model estimates are validated globally against field observations of evaporation, soil moisture, discharge and groundwater level for the time period 2015–2021, and compared to a regional groundwater model. Representing groundwater access influences evaporation in 22% of the continental surface. Globally averaged, evaporation increases by 2.5 mm year−1 (0.5% of terrestrial evaporation), but locally, evaporation can increase up to 245.2 mm year−1 (149.7%). The groundwater contribution to transpiration is highest for tall vegetation under dry conditions due to more frequent groundwater access. The temporal dynamics of the simulated evaporation improve across 75% of the stations where groundwater is a relevant water source. The skill of the model for variables such as soil moisture and runoff remains similar to GLEAM v3. The proposed approach enables a more realistic process representation of evaporation under water‐limited conditions in satellite‐data driven models such as GLEAM, and sets the ground to assimilate satellite gravimetry data in the future. Plain Language Summary: Groundwater can be a crucial source of water for plants: plants that have access to groundwater through their root system are more likely to survive periods of rainfall scarcity. However, many (satellite‐based) models neglect this water source and assume plants only depend on the unsaturated‐zone soil moisture. This assumption results in underestimated evaporation values during dry conditions, when groundwater may become the main (or even the only) source of water. In this study, we propose a new approach to improve evaporation estimates under water‐stressed conditions by incorporating groundwater in an existing global, satellite‐based evaporation model, and we assess the impact of groundwater on evaporation globally. The impact of this modification on the model's accuracy and on the resulting evaporation is evaluated. Representing groundwater increases the evaporation globally by 2.5 mm year−1 (0.5%) with much higher increases in certain regions. Key Points: Plant access to groundwater is often ignored in global evaporation estimates, yet it can be crucial during dry conditionsA new, conceptual approach to incorporate groundwater‐sourced evaporation in existing global, satellite‐based models is presentedConsidering groundwater affects the dynamics of evaporation in 22% of the continental surface and increases global land evaporation by 0.5% [ABSTRACT FROM AUTHOR]

The WACMOS-ET project has compiled a forcing data set covering the period 2005- 2007 that aims to maximize the exploitation of European Earth Observations data sets for evapotranspiration (ET) estimation. The data set was used to run 4 estab- lished ET algorithms: the Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman-Monteith algorithm from the MODIS evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition, in-situ meteorological data from 24 FLUXNET towers was used to force the models, with results from both forcing sets compared to tower-based flux observations. Model performance was assessed across several time scales using both sub-daily and daily forcings. The PT-JPL model and GLEAM provide the best performance for both satellite- and tower-based forcing as well as for the considered temporal resolutions. Simulations using the PM-MOD were mostly underestimated, while the SEBS performance was characterized by a systematic overestimation. In general, all four algorithms produce the best results in wet and moderately wet climate regimes. In dry regimes, the correlation and the absolute agreement to the reference tower ET observations were consistently lower. While ET derived with in situ forcing data agrees best with the tower measurements (R² =0.67), the agreement of the satellite-based ET estimates is only marginally lower (R² =0.58). Results also show similar model performance at daily and sub-daily (3-hourly) resolutions. Overall, our validation experiments against in situ measurements indicate that there is no single best-performing algorithm across all biome and forcing types. An extension of the evaluation to a larger selection of 85 towers (model inputs re-sampled to a common grid to facilitate global estimates) confirmed the original findings. [ABSTRACT FROM AUTHOR]

The WACMOS-ET project aims to advance the development of land evaporation estimates at global and regional scales. Its main objective is the derivation, validation and inter-comparison of a group of existing evaporation retrieval algorithms driven by a common forcing data set. Three commonly used process-based evaporation methodologies are evaluated: the Penman-Monteith algorithm behind the oficial Moderate Resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Global Land Evaporation Amsterdam Model (GLEAM), and the Priestley and Taylor Jet Propulsion Laboratory model (PT-JPL). The resulting global spatiotemporal variability of evaporation, the closure of regional water budgets and the discrete estimation of land evaporation components or sources (i.e. transpiration, interception loss and direct soil evaporation) are investigated using river discharge data, independent global evaporation data sets and results from previous studies. In a companion article (Part 1), Michel et al. (2015) inspect the performance of these three models at local scales using measurements from eddy-covariance towers, and include the assessment the Surface Energy Balance System (SEBS) model. In agreement with Part 1, our results here indicate that the Priestley and Taylor based products (PT-JPL and GLEAM) perform overall best for most ecosystems and climate regimes. While all three products adequately represent the expected average geographical patterns and seasonality, there is a ten dency from PM-MOD to underestimate the flux in the tropics and subtropics. Overall, results from GLEAM and PT-JPL appear more realistic when compared against surface water balances from 837 globally-distributed catchments, and against separate evaporation estimates from ERA-Interim and the Model Tree Ensemble (MTE). Nonetheless, all products manifest large dissimilarities during conditions of water stress and drought, and deficiencies in the way evaporation is partitioned into its different components. This observed inter-product variability, even when common forcing is used, implies caution in applying a single data set for large-scale studies in isolation. A general finding that different models perform better under different conditions highlights the potential for considering biome- or climate-specific composites of models. Yet, the generation of a multi-product ensemble, with weighting based on validation analyses and uncertainty assessments, is proposed as the best way forward in our long-term goal to develop a robust observational benchmark data set of continental evaporation. [ABSTRACT FROM AUTHOR]

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the GEWEX LandFlux project, four commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman-Monteith based Mu model (PMMu) and the Global Land Evaporation: the Amsterdam Methodology (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multimodel response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale gridbased forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance. Using surface flux observations from forty-five globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overally statistical performance (0.72; 61Wm-2; 0.65), followed closely by GLEAM (0.68; 64Wm-2; 0.62), with values in parenthesis representing the R2, RMSD and Nash-Sutclifie Effciency (NSE) and respectively. PM-Mu (0.51; 78Wm-2; 0.45) tended to underestimate fluxes, while SEBS (0.72; 101Wm-2; 0.24) overestimated values relative to observations. A focused analysis across specific biome types and climate zones showed considerable variability in the performance of all models, with no single model consistently able to outperform any other. Results also indicated that the global gridded data tended to reduce the performance for all of the studied models when compared to the tower data, likely a response to scale mismatch and issues related to forcing quality. Rather than relying on any single model simulation, the spatial and temporal variability at both the towerand grid-scale highlighted the potential benefits of developing an ensemble or blended evaporation product for global scale LandFlux applications. Challenges related to the robust assessment of the LandFlux product are also discussed. [ABSTRACT FROM AUTHOR]

Stomatal conductance (gs) affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model (LSM). In common with many LSMs, CABLE does not differentiate between gs model parameters in relation to plant functional type (PFT), but instead only in relation to photosynthetic pathway. We therefore constrained the key model parameter "g1" which represents a plants water use strategy by PFT based on a global synthesis of stomatal behaviour. As proof of concept, we also demonstrate that the g1 parameter can be estimated using two long-term average (1960-1990) bioclimatic variables: (i) temperature and (ii) an indirect estimate of annual plant water availability. The new stomatal models in conjunction with PFT parameterisations resulted in a large reduction in annual fluxes of transpiration (~ 30% compared to the standard CABLE simulations) across evergreen needleleaf, tundra and C4 grass regions. Differences in other regions of the globe were typically small. Model performance when compared to upscaled data products was not degraded, though the new stomatal conductance scheme did not noticeably change existing model-data biases. We conclude that optimisation theory can yield a simple and tractable approach to predicting stomatal conductance in LSMs. [ABSTRACT FROM AUTHOR]

A physics-based methodology is applied to estimate global land-surface evaporation from multi-satellite observations. GLEAM (Global Land-surface Evaporation: the Amsterdam Methodology) combines a wide range of remotely sensed observations within a Priestley and Taylor-based framework. Daily actual evaporation is derived at quarter degree resolution over the world's land surface. A running water balance of the vertical profile of soil moisture in the root zone is used to estimate the effect of soil water stress on transpiration. Forest rainfall interception, evaporation from bare soil, transpiration and snow sublimation are calculated independently. The inclusion of soil moisture deficit and forest rainfall interception -- by means of the Gash analytical model -- leads to an improved representation of the magnitude and distribution of the latent heat flux over semiarid and forested regions. Analyses of the global results show that interception loss plays an important role in the partition of the precipitation into evaporation and water available for runoff at a continental scale. The global distribution of evaporation and its different components is analysed to understand the relative magnitude of each component over different ecosystems. This study gives new insights into the relative importance of precipitation and net radiation in driving evaporation, and how the seasonal influence of these controls varies over the different regions of the world. Precipitation is recognised as an important factor driving evaporation, not only in areas that have limited soil water availability, but also in areas of high rainfall interception and low available energy. [ABSTRACT FROM AUTHOR]

The article discusses the monitoring of land evaporation which essential in air temperature, air humidity and photosynthesis. Among the global datasets used in observing evaporation include the European Union Water and global Change (WATCH), LandFlux initiative of the Global Energy and Watercycle Exchanges (GEWEX), and European Space Agency (ESA) Water Cycle Multi-mission Observation Strategy (WACMOS)-ET project.