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AbstractUnderstanding the roles of land surface conditions and atmospheric circulation on continental daily temperature variance is key to improving predictions of temperature extremes. Evaporative resistance (rs, hereafter), a function of the land cover type, reflects the ease with which water can be evaporated or transpired and is a strong control on land–atmosphere interactions. This study explores the effects of rs perturbations on summer daily temperature variance using the Simple Land Interface Model (SLIM) by mimicking, for rs only, a global land cover conversion from forest to crop/grassland. Decreasing rs causes a global cooling. The cooling is larger in wetter areas and weaker in drier areas, and primarily results from perturbations in shortwave radiation (SW) and latent heat flux (LH). Decreasing rs enhances cloud cover due to greater land surface evaporation and thus reduces incoming SW over most land areas. When rs decreases, wetter areas experience strong evaporative cooling, while drier areas become more moisture-limited and thus experience less cooling. Thermal advection further shapes the temperature response by damping the combined impacts of SW and LH. Temperature variance increases in drier areas and decreases in wetter areas as rs decreases. The temperature variance changes can be largely explained from changes in the combined variance of SW and LH, including an important contribution of changes in the covariance of SW and LH. In contrast, the effects of changes in thermal advection variance mainly affect the Northern Hemisphere midlatitudes.Significance StatementThis study aims to better understand processes governing daily near-surface air temperature variance over land. We use an idealized modeling framework to explore the effects of land surface evaporative resistance (a parameter that controls how hard it is to evaporate water from the surface) on summer daily temperature variance. We find that a uniform decrease of evaporative resistance across the global land surface causes changes in the temperature variance that can be predicted from changes in the combined variance of shortwave radiation and latent heat flux. The variance of horizontal advection is important in altering the temperature variance in the Northern Hemisphere midlatitudes. Our findings shed light on predicting the characteristics of temperature variability as a function of surface conditions.

The accuracy of the simulation of carbon and water processes largely relies on the selection of atmospheric forcing datasets when driving land surface models (LSM). Particularly in high-altitude regions, choosing appropriate atmospheric forcing datasets can effectively reduce uncertainties in the LSM simulations. Therefore, this study conducted four offline LSM simulations over the Tibetan Plateau (TP) using the Community Land Model version 4.5 (CLM4.5) driven by four state-of-the-art atmospheric forcing datasets. The performances of CRUNCEP (CLM4.5 model default) and three other reanalysis-based atmospheric forcing datasets (i.e. ITPCAS, GSWP3 and WFDEI) in simulating the net primary productivity (NPP) and actual evapotranspiration (ET) were evaluated based on in situ and gridded reference datasets. Compared with in situ observations, simulated results exhibited determination coefficients (R 2) ranging from 0.58 to 0.84 and 0.59 to 0.87 for observed NPP and ET, respectively, among which GSWP3 and ITPCAS showed superior performance. At the plateau level, CRUNCEP-based simulations displayed the largest bias compared with the reference NPP and ET. GSWP3-based simulations demonstrated the best performance when comprehensively considering both the magnitudes and change trends of TP-averaged NPP and ET. The simulated ET increase over the TP during 1982–2010 based on ITPCAS was significantly greater than in the other three simulations and reference ET, suggesting that ITPCAS may not be appropriate for studying long-term ET changes over the TP. These results suggest that GSWP3 is recommended for driving CLM4.5 in conducting long-term carbon and water processes simulations over the TP. This study contributes to enhancing the accuracy of LSM in water–carbon simulations over alpine regions. [ABSTRACT FROM AUTHOR]

The hydrologic flows across the river–aquifer interface play an important role in groundwater dynamics and biogeochemical reactions within the subsurface; however, little is known about the effects of river–aquifer interactions on land surface processes. In this study, we developed a fully coupled three‐dimensional (3D) land surface and subsurface model at a high resolution (~1 km) that accounts for high‐frequency hydrologic exchange flow conditions to investigate how river–aquifer interactions modulate surface water budgets in the Upper Columbia‐Priest Rapids watershed, a typical semiarid watershed located in the northwestern United States where river stage fluctuates in response to reservoir releases changing. Our results show that the spatiotemporal dynamics of river–aquifer interactions are highly heterogeneous, driven mainly by river‐stage fluctuations. Adding 6.64 × 106 m3 year−1 of water over the watershed from the river to groundwater owing to the lateral flow, river–aquifer interactions led to an increase in soil evaporation and transpiration supplied by higher soil moisture content, particularly in deeper subsurface. In a hypothetic future scenarios where a 5‐m rise in river stage was assumed, the hydrologic flow exchange rates were intensified, resulting in higher surface water over the entire watershed. Overall, lateral flow induced by river–aquifer exchanges leads to an increase in evapotranspiration of ~75% in the historical period and of ~83% in the hypothetical future scenario. Our study demonstrates the potential of coupled model as an effective tool for understanding river–aquifer–land surface interactions, and indicates that river–aquifer interactions fundamentally alter the water balance of the riparian zone for the semiarid watershed and will likely become more frequent and intense in the future under the effects of climate change. [ABSTRACT FROM AUTHOR]

The Tigris–Euphrates dryland river basin has experienced a declining trend in terrestrial water storage (TWS) from April 2002 to June 2017. Using satellite observations and a process-based land surface model, we find that climate variations and direct human interventions explain ∼61% (−0.57 mm month−1) and ∼39% (−0.36 mm month−1) of the negative trend, respectively. We further disaggregate the effects of climate variations and find that interannual climate variability contributes substantially (−0.27 mm month−1) to the negative TWS trend, slightly greater than the decadal climate change (−0.25 mm month−1). Interannual climate variability affects TWS mainly through the nonlinear relationship between monthly TWS dynamics and aridity. Slow recovery of TWS during short wetting periods does not compensate for rapid depletion of TWS through transpiration during prolonged drying periods. Despite enhanced water stress, the dryland ecosystems show slightly enhanced resilience to water stress through greater partitioning of evapotranspiration into transpiration and weak surface "greening" effects. However, the dryland ecosystems are vulnerable to drought impacts. The basin shows straining ecosystem functioning after experiencing a severe drought event. In addition, after the onset of the drought, the dryland ecosystem becomes more sensitive to variations in climate conditions. Significance Statement: The purpose of the research is to better understand climate impacts on terrestrial water storage over dryland regions with declining water storage. In our study, we disaggregate three components of climate impacts, namely, decadal climate change, interannual variability, and intra-annual variability. We then use observational datasets and a process-based model to quantify their individual effects on water storage. We find that interannual variability is the most significant climatic contributor to the declining water storage, mainly caused by prolonged drought periods and corresponding quick drying rates due to plant transpiration. We also find that the dryland ecosystem is sensitive and vulnerable to severe drought events. This study is important because 1) it provides a framework to investigate climate impacts on water fluxes and storages, 2) it highlights the importance of vegetation dynamics on dryland hydrology, and 3) it emphasizes the negative impacts of extreme hydroclimatological events on ecosystem functioning. [ABSTRACT FROM AUTHOR]

This study assesses the impact of irrigation on terrestrial fluxes through incorporation of satellite-derived irrigation scheme and crop datasets into the NOAH Land Surface Model in Punjab. NOAH 3.3 LSM was run at 0.05-degree resolution for three years from 2013 to 2015.The results show that the evapotranspiration (ET) and latent heat flux (LE) have increased significantly in the Northwestern and Central Punjab region while soil temperature has reduced in the area. The increase in LE is by about 32% for the growing seasons, DJFM (December January February March)and ASON (August September October November), which is balanced by the increase in ET by 26%. The soil temperature also witnesses cooling by 0.6 degrees at most locations. Besides, successfully demonstrating the effects of irrigation, the present study can also be relevant to water and energy cycles studies of an area that still lacks proper quantification of agricultural practices utilizing irrigation. [ABSTRACT FROM AUTHOR]

Past work has shown that a land surface model's (LSM) implicit (not explicitly coded) relationships between soil moisture and both evapotranspiration (ET) and runoff largely determine the LSM's hydrological behavior. Here we estimate the relationships that appear to be operating in the real world and compare them to those of the LSM component of a state-of-the-art Earth system model (ESM). The two sets of relationships are determined by calibrating them within a simple water balance model (WBM): once using stream gauge observations from small, unregulated rivers over the eastern half of the United States, and once using the runoffs generated by the LSM as part of a state-of-the-art atmospheric reanalysis. Hydrological simulations and subseasonal hydrological forecasts performed with the two calibrated versions of the WBM provide two key results. First, the version calibrated to the LSM-generated runoffs does successfully reproduce, to first order, the hydrological behavior of the full LSM within its ESM environment. Second, of the two WBM versions, the one calibrated to the observations reproduces more accurately a broad collection of fully independent streamflow observations as well as a similarly broad collection of in situ soil moisture measurements. Taken together, the two results suggest that the observations-calibrated ET and runoff efficiency functions do successfully represent, at least to some degree, soil moisture controls over hydrological variability in nature and can serve as potentially useful targets for further LSM development. Significance Statement: For all their complexity, and for all the work that underlies their development, the land surface model components of Earth system models may be suboptimal in fundamental yet unstudied ways. Here we estimate how the joint control of soil moisture over evapotranspiration and runoff processes in nature differs from that built implicitly into a state-of-the-art land model. Validation exercises demonstrate how this difference appears to lead to reduced accuracy in the land model's simulation and forecasting of such hydrological variables as streamflow and soil moisture. Our results indicate that the relationships estimated for nature could serve as a potentially valuable target for further land model development. [ABSTRACT FROM AUTHOR]

Fog plays a vital role in maintaining ecosystems in montane cloud forests. In these forests, a large amount of water on the surface of leaves and canopy (hereafter canopy water) evaporates during the morning. This biophysical process plays a critical factor in regulating afternoon fog formation. Recent studies have found that alterations in precipitation, temperature, humidity, and CO2 concentrations associated with future climate changes may affect terrestrial hydroclimatology, but the responses in cloud forests remain unclear. Utilizing numerical experiments with the Community Land Model, we explored changes in surface evaporative fluxes in Chi-Lan Mountain cloud forests in northeastern Taiwan under the RCP8.5 scenario with changes in the aforementioned various atmospheric variables. The results showed that increased rainfall intensity in climate change runs decreased the accumulation of canopy water, while larger water vapor concentrations led to more nighttime condensation on leaves. Elevated CO2 concentrations did not greatly impact canopy water amounts, but photosynthesis was enhanced, while transpiration was reduced and contributed to decreased latent heat fluxes, implying the importance of forest plant physiology in modulating land evaporative fluxes. Evapotranspiration decreased in Chi-Lan due to multiple combined factors, in contrast to the expected intensification in the global water cycle under global warming. The study, however, is restricted to an offline land surface model without land–atmosphere interactions and the interactions with adjacent grids, which deserves further analyses for the water cycle changes in the montane cloud forest regions. [ABSTRACT FROM AUTHOR]

To investigate the simulation performance of the Community Land Model version 5 (CLM5) in simulating terrestrial evapotranspiration,this paper simulated the surface processes in the Pearl River Basin (PRB) from 1989 to 2018 with CLM5.For validation,the remote sensing-based GLEAM ET products were used as reference for the evaluation of the model's simulation performance.The evaluation was based on temporal variability analysis and spatial pattern analysis.The results show that CLM5 underestimates the evapotranspiration in the PRB to varying degrees,with the relative error of average annual evapotranspiration being -16.07% in the basin.The underestimation is mainly attributed to the underestimation of low evapotranspiration in the cold season. By contrast,CLM5 performs better in the simulation of high evapotranspiration in the warm season.Spatially,CLM5 has good performance in the southeast,south,and west of PRB,while poor performance in the northern PRB.This study can provide a guideline for the development of the evapotranspiration module in CLM5.

Several urban canopy models now incorporate urban vegetation to represent local urban cooling related to natural soil and plant evapotranspiration. Nevertheless, little is known about the realism of simulating these processes and turbulent exchanges within the urban canopy. Here, the coupled modeling of thermal and hydrological exchanges was investigated for a lawn located in an urban environment and for which soil temperature and water content measurements were available. The ISBA diffusive (ISBA-DF) surface–vegetation–atmosphere transfer model is inline coupled to the Town Energy Balance urban canopy model to model mixed urban environments. For the present case study, ISBA-DF was applied to the lawn and first evaluated in its default configuration. Particular attention was then paid to the parameterization of turbulent exchanges above the lawn and to the description of soil characteristics. The results highlighted the importance of taking into account local roughness related to surrounding obstacles for computing the turbulent exchanges over the lawn and simulating realistic surface and soil temperatures. The soil nature and texture vertical heterogeneity are also key properties for simulating the soil water content evolution and water exchanges. [ABSTRACT FROM AUTHOR]

Future projections of precipitation change over tropical land are often enhanced by vegetation responses to CO2 forcing in Earth system models. Projected decreases in rainfall over the Amazon basin and increases over the Maritime Continent are both stronger when plant physiological changes are modeled than if these changes are neglected, but the reasons for this amplification remain unclear. The responses of vegetation to increasing CO2 levels are complex and uncertain, including possible decreases in stomatal conductance and increases in leaf area index due to CO2 fertilization. Our results from an idealized atmospheric general circulation model show that the amplification of rainfall changes occurs even when we use a simplified vegetation parameterization based solely on CO2-driven decreases in stomatal conductance, indicating that this mechanism plays a key role in complex model projections. Based on simulations with rectangular continents we find that reducing terrestrial evaporation to zero with increasing CO2 notably leads to enhanced rainfall over a narrow island. Strong heating and ascent over the island trigger moisture advection from the surrounding ocean. In contrast, over larger continents rainfall depends on continental evaporation. Simulations with two rectangular continents representing South America and Africa reveal that the stronger decrease in rainfall over the Amazon basin seen in Earth system models is due to a combination of local and remote effects, which are fundamentally connected to South America's size and its location with respect to Africa. The response of tropical rainfall to changes in evapotranspiration is thus connected to size and configuration of the continents. [ABSTRACT FROM AUTHOR]

Arctic precipitation (PG) that occurs as rainfall (Prain) or snowfall (Psnow) depending on the prevailing climatic conditions results in seasonally specific hydrological events. Climate change can affect the PG‐ and permafrost‐originated water (Pice) regimes, resulting in change to ecohydrological processes. However, the relative influences of source waters (i.e., Prain, Psnow, and Pice) on terrestrial hydrological processes have not yet been fully established. Here, we report the development and implementation of a numerical water tracer model designed to quantify changes in the storages and fluxes of the source waters and the hydrogen and oxygen isotopic tracers associated with hydrometeorological events. The presented tracer model was used to illustrate the spatiotemporal variability of the tracers in the surface–subsurface system of a deciduous needleleaf boreal forest and to separate the contribution rates of the tracer waters to evapotranspiration (ET). Although Psnow accounted for 22%–57% of ET and the subcomponents, the contribution rates to soil evaporation and transpiration were significant only during spring. The major source water for soil moisture was Prain, which accounted for 69.2% of ET and showed an increasing trend during 1980–2016. Additionally, Prain also accounted for 77.2% of transpiration. Under the present conditions of warming permafrost, Pice demonstrated negligibly low impact on ET. The tracer model was shown capable of quantifying the contribution rates of tracer waters to ET, highlighting the advantages of the tracer model for a similar quantitative separation regarding future climate change. Plain Language Summary: Although snowfall and rainfall are seasonally different processes, their influence on hydrological processes (i.e., evapotranspiration and river discharge) occurs mainly during the growing season. Quantification of their contributions to hydrological processes is an ongoing scientific problem in the field of Arctic hydrology. Thus, we developed a tracer model, which includes isotopic processes, to separate the contributions of snowfall, rainfall, and permafrost‐originated water to evapotranspiration and applied it to a boreal forest. The model simulation suggested that summer rainfall has the greatest impact on evapotranspiration, while water from snowfall is strongly implicated in springtime evaporation. Permafrost‐originated water is not connected directly to evapotranspiration at the study site. However, future warming climate could potentially increase the role of permafrost‐related water in ecohydrological processes. Thus, the presented water tracer model could potentially provide a quantitative assessment of the changes in the physics of water dynamics caused by climate change. Key Points: Tracer model separates contributions of precipitation‐ and permafrost‐originated waters to evapotranspiration in deciduous boreal forestRainfall is the primary contributor to seasonal and interannual variability of evapotranspirationPermafrost‐originated water has negligibly low impact on evapotranspiration [ABSTRACT FROM AUTHOR]

Rising temperatures in the southern Arctic region are leading to shrub expansion and permafrost degradation. The objective of this study is to analyze the surface energy budget (SEB) of a subarctic shrub tundra site that is subject to these changes, on the east coast of Hudson Bay in eastern Canada. We focus on the turbulent heat fluxes, as they have been poorly quantified in this region. This study is based on data collected by a flux tower using the eddy covariance approach and focused on snow-free periods. Furthermore, we compare our results with those from six Fluxnet sites in the Arctic region and analyze the performance of two land surface models, SVS and ISBA, in simulating soil moisture and turbulent heat fluxes. We found that 23% of the net radiation was converted into latent heat flux at our site, 35% was used for sensible heat flux, and about 15% for ground heat flux. These results were surprising considering our site was by far the wettest site among those studied, and most of the net radiation at the other Arctic sites was consumed by the latent heat flux. We attribute this behavior to the high hydraulic conductivity of the soil (littoral and intertidal sediments), typical of what is found in the coastal regions of the eastern Canadian Arctic. Land surface models overestimated the surface water content of those soils but were able to accurately simulate the turbulent heat flux, particularly the sensible heat flux and, to a lesser extent, the latent heat flux. Significance Statement: Isostatic uplift after the last deglaciation led to the emergence of beaches, which represent a large area in the Canadian Arctic. We studied the surface energy budget of such a beach that emerged 6000 years ago in northeastern Canada. Results suggest that evaporation is up to 20% less than at previously studied sites, which is explained by sandy soils retaining little moisture despite abundant precipitation. Deployed numerical models showed difficulties in simulating the soil conditions but proved successful in simulating the surface energy budget after manual adjustments of the soil conditions. These simulation difficulties probably apply to other parts of the Canadian Arctic, possibly leading to errors in meteorological and climate forecasting. [ABSTRACT FROM AUTHOR]

• New phenology module embedded into CoLM enhances carbon and water flux modeling. • The improved CoLM outperforms CoLM-MODIS in GPP and ET accuracy on a site scale. • Globally, the improved CoLM could captures spatiotemporal of GPP and ET. Land surface models (LSMs) are essential tools for simulating the energy and momentum exchange between the land surface and the atmosphere. The vegetation phenology module, a pivotal component of LSMs, reflects the feedback of vegetation to climate variations. However, the vegetation phenology module in several LSMs, such as the Common Land Model (CoLM), face challenges concerning its rationality. Currently, the original satellite phenology mode in CoLM, which uses satellite-based leaf area index (LAI) data directly and statically, constrains the model's ability to accurately represent complex and dynamic ecosystem processes. In this study, we embedded a dynamic vegetation phenology model into CoLM, serving as a novel phenology module. We conducted an extensive comparison of the effects of various phenology modules on CoLM, focusing on their performance in the modeling of gross primary productivity (GPP) and evapotranspiration (ET) at both site and global scales. Results demonstrate an improvement in CoLM for modeling GPP and ET following the integration of the novel phenology module. Specifically, the Pearson's correlation coefficient for GPP increased by 1.29 % to 33.74 %, and for ET by 0.32 % to 7.47 % on a site scale. Furthermore, on a global scale, when compared with global reference datasets, the CoLM embedded with the novel phenology module successfully captures the spatiotemporal distribution of GPP and ET, and its performance is closer to the reference data than that of the CoLM with the original satellite phenology mode. This study highlights the importance of vegetation phenology in LSMs and its potential to improve the modeling of dynamic interactions between vegetation processes and environmental changes within LSMs. [ABSTRACT FROM AUTHOR]

A meteorological drought in 2018 led to senescence of the C3 grass at Cardington, Bedfordshire, United Kingdom. Observations of near-surface atmospheric variables and soil moisture are compared to simulations by the JULES land surface model (LSM) as used for Met Office forecasts. In years without drought, JULES provides better standalone simulations of evapotranspiration (ET) and soil moisture when the canopy height and rooting depth are reduced to match local conditions. During drought with the adjusted configuration, JULES correctly estimates total ET, but the components are in the wrong proportions. Several factors affect the estimation of ET including modeled skin temperatures, dewfall, and bare-soil evaporation. A diurnal range of skin temperatures close to observed is produced via the adjusted configuration and doubling the optical extinction coefficient. Although modeled ET during drought matches observed ET, this includes simulation of transpiration but in reality the grass was senescent. Excluding transpiration, the modeled bare-soil evaporation underestimates the observed midday latent heat flux. Part of the missing latent heat may relate to inappropriate parameterization of hydraulic properties of dry soils and part may be due to insufficient evaporation of dew. Dew meters indicate dewfall of up to 20 W m−2 during drought when the surface is cooling radiatively and turbulence is minimal. These data demonstrate that eddy-covariance techniques fail to reliably record the times, intensity, and variations in negative latent heat flux. Furthermore, the parameterization of atmospheric turbulence as used in LSMs fails to represent accurately dewfall during calm conditions when the surface is radiatively cooled. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) and evapotranspiration (ET) are key variables of the terrestrial water cycle with a strong relationship. This study examines remotely sensed soil moisture and evapotranspiration data assimilation (DA) with the aim of improving drought monitoring. Although numerous efforts have gone into assimilating satellite soil moisture observations into land surface models to improve their predictive skills, little attention has been given to the combined use of soil moisture and evapotranspiration to better characterize hydrologic fluxes. In this study, we assimilate two remotely sensed datasets, namely, Soil Moisture Operational Product System (SMOPS) and MODIS evapotranspiration (MODIS16 ET), at 1-km spatial resolution, into the VIC land surface model by means of an evolutionary particle filter method. To achieve this, a fully parallelized framework based on model and domain decomposition using a parallel divide-and-conquer algorithm was implemented. The findings show improvement in soil moisture predictions by multivariate assimilation of both ET and SM as compared to univariate scenarios. In addition, monthly and weekly drought maps are produced using the updated root-zone soil moisture percentiles over the Apalachicola-Chattahoochee-Flint basin in the southeastern United States. The model-based estimates are then compared against the corresponding U.S. Drought Monitor (USDM) archive maps. The results are consistent with the USDM maps during the winter and spring season considering the drought extents; however, the drought severity was found to be slightly higher according to DA method. Comparing different assimilation scenarios showed that ET assimilation results in wetter conditions comparing to open-loop and univariate SM DA. The multivariate DA then combines the effects of the two variables and provides an in-between condition. [ABSTRACT FROM AUTHOR]

Surface temperature is one of the key parameters for estimating regional evapotranspiration (ET) based on the Surface Energy Balance System (SEBS) model using remote sensing data. However, continuous daily remote sensing surface temperature data are often not available due to the weather and environmental conditions. This paper proposed a scheme to obtain reliable ET that estimating ET using WRF-simulated surface skin temperature (TSK) and then modifying the deviation using the normalized difference vegetation index (NDVI). This study aims to explore whether the model data can be a viable option when the continuous-time-series remote sensing surface temperature is missing for estimating ET. Comparison results show that the correlation between WRF TSK and the measured temperature of the 2-cm soil (Ts) is better than MODIS land surface temperature (LST) in the study area, while the correlation between MODIS LST and the measured surface radiation temperature (IRT) is better than WRF TSK. The MODIS LST is significantly higher than Ts, and the WRF TSK is closer to Ts than MODIS LST. However, the ET calculated using WRF TSK was not good, exhibiting relatively high ET in the whole area and a poor correlation with the measurements, whereby R2, RMSE, and the percent bias (PBIAS) were equal to 0.1256, 5.2783 mm, and −202.17%, respectively. According to the principle of land surface process simulation in WRF, this paper proposes using NDVI to modify ET calculated using TSK. The comparison between the modified ET and the measurements exhibited a relatively good correlation, with R2 = 0.7532, RMSE = 1.0993 mm, and PBIAS = −17.9%. Therefore, the model surface temperature data can be used to estimate continuous-time-series regional ET when NDVI is used to modify the deviation, which indicates the surface temperature data simulated by the WRF Model can become the optional data for estimating ET and compensate for the shortcoming of poor time continuity of remote sensing data, further expanding the application prospects of meteorological model data in the remote sensing field. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) plays a key role in linking water, energy, and carbon cycles. However, at regional scales, variations and controls of ET are still not well understood, due to the substantial uncertainties in ET estimates. Here, the variations in ET over China during the last three decades and their drivers and controls were analysed at monthly, seasonal, and annual scales, using well‐evaluated land surface model simulations. The results suggested that (a) the spatially averaged ET over China increased during 1979–2012 at each temporal scale. Overall, the ET significantly increased (p <.05) in most of western China and decreased in several regions in eastern China during most months and seasons. (a) The increases in spatially averaged ET during the nongrowing season were mainly determined by warming. The increased annual ET, seasonal ET, and monthly ET within the growing season were jointly caused by vegetation greening and climate warming. (c) During November–March, ET was primarily determined by temperature in most of central China and was determined by water availability in the remaining regions. The annual ET and the monthly ET within April–October were mainly controlled by water availability in most of northern and western China, and several regions in central China, by solar radiation in most of central and southern China and by temperature in some regions in the Tibetan Plateau. The study highlights the large effects of warming and greening on ET over China during the last three decades. The results may benefit water resource management under climate change. [ABSTRACT FROM AUTHOR]

Accurate estimation of irrigation-induced evapotranspiration (ET) is critical for understanding the terrestrial water cycle. However, current estimation has large uncertainties due to the model limitations and the lack of accurate water use data. In this study, a water-energy balanced irrigation scheme is incorporated into the Conjunctive Surface-Subsurface Process version 2 (CSSPv2) model to improve the hydrological simulations over the Yellow River basin (YRB) where irrigation is extensive. The coupled model (CSSPv2-IRR) is calibrated against long-term water use data from provincial survey, and it is used to perform a 6-km resolution simulation over the YRB during 1991–2017. The results show that the coupled model can well reproduce hydrological processes within the basin, and the simulated irrigation amount, ET and surface soil moisture largely agree with the validation datasets. Specifically, the annual irrigation amount and irrigation-induced ET changes from the CSSPv2-IRR are more reasonable than ISIMIP2a and reanalysis products, with a reduction in bias by 79.5–97.3 % and 81.2–98.8 % respectively. The CSSPv2-IRR model simulation suggests that irrigation-induced annual ET change is 26.4 mm/year during 1991–2017, contributing to an 8.9 % increase in annual ET over the YRB, and the increase can reach 44.3 % over major irrigation districts. In addition, the contribution of irrigation to long-term increasing trend in ET over the irrigation districts in the upper reach is greater than the contribution of climate change. This study suggests a growing control of irrigation on the ET over the YRB, which has implications for regional water cycle and water resources management. [ABSTRACT FROM AUTHOR]

Shortfalls in regular evapotranspiration (ET) monitoring and evaluation pose a huge challenge to agricultural water resource distribution in arid Central Asia (CA). In this study, a first detailed regional assessment of GLEAM, ERA5, MERRA2, CLSM and NOAH ET products in CA was performed by systematically implementing the triple collocation (TC) method, in which about 36,936 grid cells for each ET data (within a six-triplet design) were collocated, at 0.25° and with monthly resolutions during 2003–2020. The reliability of the strategy adopted was confirmed in four arid biomes using standard evaluation metrics (R, RMSE and BIAS), and by spatiotemporal cross-validation of the six ET triplets across CA. Results show that the systematic TC method produced more robust ET product assessment metrics with reduced RMSEs compared to the initial ET product validation using in-situ, which showed weak-positive correlation and high negative bias-range (i.e., −21.02 ≤ BIAS < 16 mm) in the four arid biomes of CA. The spatial cross-validation by TC showed that the magnitude of ET random errors significantly varies, and confirms the systematic biases with site-scale measurements. The highest ET uncertainties by CLSM (27.43%), NOAH (29.16%), MERRA2 (38.28%), ERA5 (36.75), and GLEAM (41%) were more evident in the shrubland, cropland, grassland, cropland again, and desert biomes, respectively. Moreover, error magnitudes in high altitudes (Tianshan Mountain range) are generally lower than in plain-desert areas. All ET products spatially captured ET dynamics over CA, but none simultaneously outperformed the other. These findings are invaluable in the utilization of the assessed ET products in supporting regional water resource management, particularly in CA.

In a warming climate, the water budget of the land is subject to varying forces such as increasing evaporative demand, mainly through the increased temperature, and changes to the precipitation, which might go up or down. Using a verified, physically based model with 55 years of observation-based meteorological forcing, an analysis of the water budget demonstrates that Great Britain is getting warmer and wetter. Increases in precipitation (2.96.0 ± 2.03 mm yr–1 yr–1) and air temperature (0.20 ± 0.13 K decade–1) are driving increases in runoff (2.18 ± 1.84 mm yr–1 yr–1) and evapotranspiration (0.87 ± 0.55 mm yr–1 yr–1), with no significant trend in the soil moisture. The change in evapotranspiration is roughly constant across the regions, whereas runoff varies greatly between regions: the biggest change is seen in Scotland (4.56 ± 2.82 mm yr–1 yr–1), where precipitation increases were also the greatest (5.4 ± 3.0 mm yr–1 yr–1), and the smallest trend (0.33 ± 1.50 mm yr–1 yr–1, not statistically significant) is seen in the English Lowlands (East Anglia and Midlands), where the increase in rainfall is not statistically significant (1.07 ± 1.76 mm yr–1 yr–1). Relative to its contribution to the evapotranspiration budget, the increase in interception is higher than the other components. This is due to the fact that it correlates strongly with precipitation, which is seeing a greater increase than the potential evapotranspiration. This leads to a higher increase in actual evapotranspiration than the potential evapotranspiration, and a negligible increase in soil moisture or groundwater store. [ABSTRACT FROM AUTHOR]

• Evapotranspiration (ET) change from land cover changes was quantified in study area. • Substantial increased ET from crop expansion largely intensifies water crisis. • Water consumed by crop expansion can recover 10 times area of desert ecosystem. Evapotranspiration (ET) plays an important role in determining the available water resources of a basin. In past decades, the Heihe River basin (HRB) in Northwest China has suffered severe water crisis and ecological problems due to large land cover changes (LCCs), especially oases expansion for irrigation agriculture. This study quantifies the ET variations due to LCCs in the HRB from 2000 to 2015 using the Ecological Assimilation of Land and Climate Observations (EALCO) model and detailed LCC measurements. Large variations in ET with land cover type is seen in the HRB. In the past fifteen years, crop expansion from bare soil or desert grass caused most of the increase in ET, while the conversion of alpine grass to desert grass caused most of the decrease in ET. As a result, a net 1.03 billion m3 of increased water consumption per year resulted from the overall LCCs in the HRB. This increased water use for ET largely intensified the water crisis in the HRB and deteriorated the health of the downstream ecosystems. Our results show that the water consumed in crop expansion can be used to recover almost ten times the area of the degraded desert grass ecosystem. A stricter policy that limits agriculture expansion is recommended in land use planning for a sustainable ecosystem development in the basin. This study also helps to better understand ET changes from LCCs and manage the limited water resources for sustainable ecosystem development in other arid regions of the world. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a key process affecting terrestrial hydroclimate, as it modulates the land surface carbon, energy, and water budgets. Evapotranspiration mainly consists of the sum of three components: plant transpiration, soil evaporation, and canopy interception. Here we investigate how the partitioning of ET into these three main components is represented in CMIP5 model simulations of present and future climate. A large spread exists between models in the simulated mean present-day partitioning; even the ranking of the different components in the global mean differs between models. Differences in the simulation of the vegetation leaf area index appear to be an important cause of this spread. Although ET partitioning is not accurately known globally, existing global estimates suggest that CMIP5 models generally underestimate the relative contribution of transpiration. Differences in ET partitioning lead to differences in climate characteristics over land, such as land–atmosphere fluxes and near-surface air temperature. On the other hand, CMIP5 models simulate robust patterns of future changes in ET partitioning under global warming, notably a marked contrast between decreased transpiration and increased soil evaporation in the tropics, whereas transpiration and evaporation both increase at higher latitudes and both decrease in the dry subtropics. Idealized CMIP5 simulations from a subset of models show that the decrease in transpiration in the tropics largely reflects the stomatal closure effect of increased atmospheric CO2 on plants (despite increased vegetation from CO2 fertilization), whereas changes at higher latitudes are dominated by radiative CO2 effects, with warming and increased precipitation leading to vegetation increase and simultaneous (absolute) increases in all three ET components. [ABSTRACT FROM AUTHOR]

This study examines the evolution of soil moisture, evapotranspiration, vegetation, and atmospheric conditions during an unusual flash drought–flash recovery sequence that occurred across the south-central United States during 2015. This event was characterized by a period of rapid drought intensification (flash drought) during late summer that was terminated by heavy rainfall at the end of October that eliminated the extreme drought conditions over a 2-week period (flash recovery). A detailed analysis was performed using time series of environmental variables derived from meteorological, remote sensing, and land surface modeling datasets. Though the analysis revealed a similar progression of cascading effects in each region, characteristics of the flash drought such as its onset time, rate of intensification, and vegetation impacts differed between regions due to variations in the antecedent conditions and the atmospheric anomalies during its growth. Overall, flash drought signals initially appeared in the near-surface soil moisture, followed closely by reductions in evapotranspiration. Total column soil moisture deficits took longer to develop, especially in the western part of the region where heavy rainfall during the spring and early summer led to large moisture surpluses. Large differences were noted in how land surface models in the North American Land Data Assimilation System depicted soil moisture evolution during the flash drought; however, the models were more similar in their assessment of conditions during the flash recovery period. This study illustrates the need to use multiple datasets to track the evolution and impacts of rapidly evolving flash drought and flash recovery events. [ABSTRACT FROM AUTHOR]

In distributed land surface modeling (LSM) studies, uncertainty in the rainfields that are used to force models is a major source of error in predicted land surface response variables. This is particularly true for applications in the African Sahel region, where weak knowledge of highly time/space-variable convective rainfall in a poorly monitored region is a considerable obstacle to such developments. In this study, we used a field-based stochastic rainfield generator to analyze the propagation of the rainfall uncertainty through a distributed land surface model simulating water and energy fluxes in Sahelian ecosystems. Ensemble time/space rainfields were generated from field observations of the local AMMA-CATCH-Niger recording raingauge network. The rainfields were then used to force the SEtHyS-Savannah LSM, yielding an ensemble of time/space simulated fluxes. Through informative graphical representations and innovative diagnosis metrics, these outputs were analyzed to separate the different components of flux variability, among which was the uncertainty represented by ensemble-wise variability. Scale dependence was analyzed for each flux type in the water and energy budgets, producing a comprehensive picture of uncertainty propagation for the various flux types, with its relationship to intrinsic space/time flux variability. The study was performed over a 2530 km2 domain over six months, covering an entire monsoon season and the subsequent dry-down, using a kilometer/daily base resolution of analysis. The newly introduced dimensionless uncertainty measure, called the uncertainty coefficient, proved to be more effective in describing uncertainty patterns and relationships than a more classical measure based on variance fractions. Results show a clear scaling relationship in uncertainty coefficients between rainfall and the dependent fluxes, specific to each flux type. These results suggest a higher sensitivity to rainfall uncertainty for hydrological than for agro-ecological or meteorological applications, even though eddy fluxes do receive a substantial part of that source uncertainty.

Earth system models (ESMs) rely on the calculation of canopy conductance in land surface models (LSMs) to quantify the partitioning of land surface energy, water, and CO2 fluxes. This is achieved by scaling stomatal conductance, gw, determined from physiological models developed for leaves. Traditionally, models for gw have been semi‐empirical, combining physiological functions with empirically determined calibration constants. More recently, optimization theory has been applied to model gw in LSMs under the premise that it has a stronger grounding in physiological theory and might ultimately lead to improved predictive accuracy. However, this premise has not been thoroughly tested. Using original field data from contrasting forest systems, we compare a widely used empirical type and a more recently developed optimization‐type gw model, termed BB and MED, respectively. Overall, we find no difference between the two models when used to simulate gw from photosynthesis data, or leaf gas exchange from a coupled photosynthesis‐conductance model, or gross primary productivity and evapotranspiration for a FLUXNET tower site with the CLM5 community LSM. Field measurements reveal that the key fitted parameters for BB and MED, g1B and g1M, exhibit strong species specificity in magnitude and sensitivity to CO2, and CLM5 simulations reveal that failure to include this sensitivity can result in significant overestimates of evapotranspiration for high‐CO2 scenarios. Further, we show that g1B and g1M can be determined from mean ci/ca (ratio of leaf intercellular to ambient CO2 concentration). Applying this relationship with ci/ca values derived from a leaf δ13C database, we obtain a global distribution of g1B and g1M, and these values correlate significantly with mean annual precipitation. This provides a new methodology for global parameterization of the BB and MED models in LSMs, tied directly to leaf physiology but unconstrained by spatial boundaries separating designated biomes or plant functional types. We show that current optimization and empirical methods to determine stomatal conductance in Earth system models (ESMs) yield similar results and exhibit similar species‐specific sensitivities to environmental variables, including CO2. Failure to account for different stomatal sensitivities across species or vegetation types will lead to significant errors in ESM simulations, particularly for terrestrial water fluxes. The key fitted parameter calibrating optimization or empirical stomatal conductance models to different global vegetation types may be determined from mean annual precipitation, as shown here for the empirical Ball‐Berry slope, overcoming constraints imposed by inflexibilities in current global calibration methods. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is one of the most important fluxes in terrestrial ecosystems that regulate atmosphere–hydrosphere–biosphere interactions. Several studies have suggested that global ET has significantly increased in the past several decades, and that such increase has exhibited big spatial variability, but there are few detailed studies on the spatio-temporal change in ET over China. Here, we developed a high-resolution data-oriented monthly ET product in China between 1982 and 2015 by integrating remote-sensing and the eddy covariance technique observed ET data in a machine learning approach (model tree ensemble, MTE). We showed that the mean annual ET over China is 552 ± 14 mm yr −1 , which is comparable to the estimate from a MTE-derived product based on water balance, but is larger than that from both previous MTE-derived global product and process-based land surface models. ET in China significantly increased with a rate of 10.7 mm yr −1 per decade over the past 30 years ( p  < 0.05). The largest increases in ET (>60 mm yr −1 per decade) occurred in the eastern periphery of Sichuan, southern Taiwan, and central China, which was attributed to the increases in temperature and solar radiation, as well as the enhanced vegetation productivity. About 22% of the area showed a decreasing trend in ET, mainly in parts of southeastern, southwestern, and northeastern China. The regional decrease in ET was likely due to decreasing precipitation and/or vegetation browning. Although our finding of the significant increase in China’s ET at the country scale is supported by five different ET products, there are still less agreement on the change in ET at the regional scale among different ET products. [ABSTRACT FROM AUTHOR]

The maximum entropy production (MEP) model based on nonequilibrium thermodynamics and the theory of Bayesian probabilities was recently developed to model land surface fluxes, including soil evaporation and vegetation transpiration. This model requires few input data and ensures the closure of the surface energy balance. This study aims to test the capability of such a model to realistically simulate evapotranspiration (ET) over a wide range of climates and vegetation covers. A weighting coefficient is introduced to calculate total ET from soil evaporation and vegetation transpiration over partially vegetated land surfaces, resulting in the MEP-ET model. Using this coefficient, the model outputs are compared with in situ observations of ET at eight FLUXNET sites across the continental United States. Results confirm the close agreement between the MEP-ET predicted daily ET and the corresponding observations at sites characterized by moderately limited water availability. Poor ET results were obtained under high water stress conditions. A regulation parameter was therefore introduced in the MEP-ET model to properly take into account the effects of soil water stress on stomata, yielding the generalized MEP-ET model. This parameter considerably reduced model biases under water stress conditions for various heterogeneous land surface sites. The generalized MEP-ET model outperforms several popular ET models, including Penman-Monteith (PM), modified Priestley-Taylor-Jet Propulsion Laboratory (PT-JPL), and air-relative-humidity-based two-source model (ARTS) at all test sites. [ABSTRACT FROM AUTHOR]

We develop and implement a novel numerical water tracer model within the Noah LSM with multiparameterization options (WT-Noah-MP) that is specifically designed to track individual hydrometeorological events. This approach provides a more complete representation of the physical processes beyond the standard land surface model output. Unlike isotope-enabled LSMs, WT-Noah-MP does not simulate the concentration of oxygen or hydrogen isotopes, or require isotope information to drive it. WT-Noah-MP provides stores, fluxes, and transit time estimates of tagged water in the surface-subsurface system. The new tracer tool can account for the horizontal and vertical heterogeneity of tracer transport in the subsurface by allowing partial mixing in each soil layer. We compared model-estimated transit times at the H. J. Andrews Experimental Watershed in Oregon with those derived from isotope observations. Our results show that including partial mixing in the soil results in a more realistic transit time distribution than the basic well-mixed assumption. We then used WT-Noah-MP to investigate the regional response to an extreme precipitation event in the U.S. Pacific Northwest. The model differentiated the flood response due to direct precipitation from indirect thermal effects and showed that a large portion of this event water was retained in the soil after 6 months. The water tracer addition in Noah-MP can help us quantify the long-term memory in the hydrologic system that can impact seasonal hydroclimate variability through evapotranspiration and groundwater recharge. [ABSTRACT FROM AUTHOR]

Water and carbon fluxes simulated by 12 Earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) over several recent decades were evaluated using three functional constraints that are derived from both model simulations, or four global datasets, and 736 site-year measurements. Three functional constraints are ecosystem water-use efficiency (WUE), light-use efficiency (LUE), and the partitioning of precipitation P into evapotranspiration (ET) and runoff based on the Budyko framework. Although values of these three constraints varied significantly with time scale and should be quite conservative if being averaged over multiple decades, the results showed that both WUE and LUE simulated by the ensemble mean of 12 ESMs were generally lower than the site measurements. Simulations by the ESMs were generally consistent with the broad pattern of energy-controlled ET under wet conditions and soil water-controlled ET under dry conditions, as described by the Budyko framework. However, the value of the parameter in the Budyko framework ω, obtained from fitting the Budyko curve to the ensemble model simulation (1.74), was larger than the best-fit value of ω to the observed data (1.28). Globally, the ensemble mean of multiple models, although performing better than any individual model simulations, still underestimated the observed WUE and LUE, and overestimated the ratio of ET to P, as a result of overestimation in ET and underestimation in gross primary production (GPP). The results suggest that future model development should focus on improving the algorithms of the partitioning of precipitation into ecosystem ET and runoff, and the coupling of water and carbon cycles for different land- use types. [ABSTRACT FROM AUTHOR]

Abstract: Achieving higher canopy photosynthesis rates is one of the keys to increasing future crop production; however, this typically requires additional water inputs because of increased water loss through the stomata. Lowland rice canopies presently consume a large amount of water, and any further increase in water usage may significantly impact local water resources. This situation is further complicated by changing the environmental conditions such as rising atmospheric CO2 concentration ([CO2]). Here, we modeled and compared evapotranspiration of fully developed rice canopies of a high‐yielding rice cultivar (Oryza sativa L. cv. Takanari) with a common cultivar (cv. Koshihikari) under ambient and elevated [CO2] (A‐CO2 and E‐CO2, respectively) via leaf ecophysiological parameters derived from a free‐air CO2 enrichment (FACE) experiment. Takanari had 4%–5% higher evapotranspiration than Koshihikari under both A‐CO2 and E‐CO2, and E‐CO2 decreased evapotranspiration of both varieties by 4%–6%. Therefore, if Takanari was cultivated under future [CO2] conditions, the cost for water could be maintained at the same level as for cultivating Koshihikari at current [CO2] with an increase in canopy photosynthesis by 36%. Sensitivity analyses determined that stomatal conductance was a significant physiological factor responsible for the greater canopy photosynthesis in Takanari over Koshihikari. Takanari had 30%–40% higher stomatal conductance than Koshihikari; however, the presence of high aerodynamic resistance in the natural field and lower canopy temperature of Takanari than Koshihikari resulted in the small difference in evapotranspiration. Despite the small difference in evapotranspiration between varieties, the model simulations showed that Takanari clearly decreased canopy and air temperatures within the planetary boundary layer compared to Koshihikari. Our results indicate that lowland rice varieties characterized by high‐stomatal conductance can play a key role in enhancing productivity and moderating heat‐induced damage to grain quality in the coming decades, without significantly increasing crop water use. [ABSTRACT FROM AUTHOR]

To address certain limitations with their current operational model, Environment and Climate Change Canada recently developed the Soil, Vegetation, and Snow (SVS) land surface model and the representation of subsurface hydrological processes was targeted as an area for improvement. The objective of this study is to evaluate the ability of HydroSVS, the component of SVS responsible for the vertical redistribution of water, to simulate soil moisture under snow-free conditions when using flux-tower observations of evapotranspiration as forcing data. We assessed (1) model fidelity by comparing soil moisture modelled with HydroSVS to point-scale measurements of volumetric soil water content and (2) model complexity by comparing the performance of HydroSVS to that of HydroGeoSphere, a state-of-the-art integrated surface and subsurface hydrologic model. To do this, we performed one-dimensional soil column simulations at four sites of the AmeriFlux network. Results indicate that under Mediterranean and temperate climates, HydroSVS satisfactorily simulated soil moisture (Nash-Sutcliffe efficiency between 0.26 and 0.70; R 2  ≥ 0.80), with a performance comparable to HydroGeoSphere (Nash-Sutcliffe efficiency ≥0.60; R 2  ≥ 0.80). However, HydroSVS performed weakly under a semiarid climate while HydroGeoSphere performed relatively well. By decoupling the magnitude and sourcing of evapotranspiration, this study proposes a powerful diagnostic tool to evaluate the representation of subsurface hydrological processes in land surface models. Overall, this study highlights the potential of SVS for hydrological applications. [ABSTRACT FROM AUTHOR]

The estimation of evapotranspiration of blue water (ETb) from farmlands, due to irrigation, is crucial to improve water management, especially in regions where water resources are scarce. Large scale ETb was previously obtained, based on the differences between remote sensing derived actual ET and values simulated from the Global Land Data Assimilation System (GLDAS). In this paper, we improve on the previous approach by enhancing the classification scheme employed so that it represents regions with common hydrometeorological conditions. Bias between the two data sets for reference areas (non-irrigated croplands) were identified per class, and used to adjust the remote sensing products. Different classifiers were compared and evaluated based on the generated bias curves per class and their variability. The results in Europe show that the k-means classifier was better suited to identify the bias curves per class, capturing the dynamic range of these curves and minimizing their variability within each corresponding class. The method was applied in Africa and the classification and bias results were consistent with the findings in Europe. The ETb results were compared with existing literature and provided differences up to 50 mm/year in Europe, while the comparison in Africa was found to be highly influenced by the assigned cover type and the heterogeneity of the pixel. Although further research is needed to fully understand the ETb values found, this paper shows a more robust approach to classify and characterize the bias between the two sets of ET data.

An evapotranspiration (ET) ensemble composed of 36 land surface model (LSM) experiments and four diagnostic datasets (GLEAM, ALEXI, MOD16, and FLUXNET) is used to investigate uncertainties in ET estimate over five climate regions in West Africa. Diagnostic ET datasets show lower uncertainty estimates and smaller seasonal variations than the LSM-based ET values, particularly in the humid climate regions. Overall, the impact of the choice of LSMs and meteorological forcing datasets on the modeled ET rates increases from north to south. The LSM formulations and parameters have the largest impact on ET in humid regions, contributing to 90% of the ET uncertainty estimates. Precipitation contributes to the ET uncertainty primarily in arid regions. The LSM-based ET estimates are sensitive to the uncertainty of net radiation in arid region and precipitation in humid region. This study serves as support for better determining water availability for agriculture and livelihoods in Africa with earth observations and land surface models.

This paper presents a comparison of two water transfer schemes implemented in land surface models: a three-layer bulk reservoir model based on the force-restore scheme (FR) and a multilayer soil diffusion scheme (DIF) relying on explicit mass-diffusive equations and a root profile. The performances of each model at simulating evapotranspiration (ET) over a 14-yr Mediterranean crop succession are compared when the standard pedotransfer estimates versus the in situ values of the soil parameters are used. The Interactions between Soil, Biosphere, and Atmosphere (ISBA) generic land surface model is employed. When the pedotransfer estimates of the soil parameters are used, the best performance scores are obtained with DIF. DIF provides more accurate simulations of soil evaporation and gravitational drainage. It is less sensitive to errors in the soil parameters compared to FR, which is strongly driven by the soil moisture at field capacity. When the in situ soil parameters are used, the performance of the FR simulations surpasses those of DIF. The use of the proper maximum available water content for the plant removes the bias in ET and soil moisture over the crop cycle with FR, while soil water stress is simulated too early and the transpiration is underestimated with DIF. Increasing the values of the root extinction coefficient and the proportion of homogeneous root distribution slightly improves the DIF performance scores. Spatiotemporal uncertainties in the soil parameters generate smaller uncertainties in ET simulated with DIF compared to FR, which highlights the robustness of DIF for large-scale applications. [ABSTRACT FROM AUTHOR]

The spatial distribution and fractional cover of plant functional types (PFTs) is a key uncertainty in land surface models (LSMs) that is closely linked to uncertainties in global carbon, hydrology and energy budgets. Land cover is considered to be an Essential Climate Variable because changes in it can result in local, regional or global scale impacts on climate. In LSMs, land cover (LC) class maps are converted to PFT fractional maps using a cross-walking (CW) table by prescribing the fraction of each PFT that occurs within each LC class. In this study we assess the largest plausible range of PFT uncertainty derived from remotely sensed LC maps produced under the European Space Agency Land Cover Climate Change Initiative on simulations of land surface fluxes using 3 leading LSMs. We evaluate the impact of uncertainty due to both LC classification algorithms, and CW procedure, on energy, moisture and carbon fluxes in LSMs. We investigate the maximum plausible range of uncertainty deriving from both LC and CW within the context of a potential biomass scale (bare ground-grass-shrub-tree), representing a gradient from low to high biomass PFTs. More specifically, plausible alternative land cover maps and associated PFT fractional distributions were produced to prioritise low or high biomass vegetation in the LC classification (uncertainty in LC), and subsequently in the assignment of PFT fractions for each LC class (uncertainty in CW), relative to a reference PFT distribution. We examined the impact of PFT uncertainty on 3 key variables in the carbon, water and energy cycles (gross primary production (GPP), evapo-transpiration (ET), and albedo), for 3 LSMs (JSBACH, JULES and ORCHIDEE) at global scale. Results showed a greater uncertainty in PFT fraction due to CW as opposed to LC uncertainty, for all three variables. CW uncertainty in tree fraction was found to be particularly important in the northern boreal forests for simulated LSM albedo. Uncertainty in the balance between grass and bare soil fraction in arid parts of Africa, central Asia, and central Australia was also found to influence albedo and ET in all models. The spread due to PFT uncertainty for albedo was between 30 and 105% of inter-model uncertainty, for GPP between 20 and 90%, and for ET 0–30%. Each model had a different sensitivity to PFT uncertainty, for example, GPP in JSBACH was found to have a much higher sensitivity to PFT uncertainty in the tropics than JULES and ORCHIDEE, whereas the inverse was true for ET. These results show that inter-model uncertainty for key variables in LSMs can be reduced by more accurate representation of PFT distributions. Future efforts in land cover mapping should therefore be focused on reducing CW uncertainty through better understanding of the fractional cover of PFTs within a land cover class. Efforts to reduce LC uncertainty should particularly be focused on more accurate mapping of grass and bare soil fractions in arid areas. In the context of Land Surface Models, these results demonstrate that prescribed vegetation distribution in models is a key source of uncertainty that is comparable to the spread between models for key model state variables. [ABSTRACT FROM AUTHOR]

Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region. [ABSTRACT FROM AUTHOR]

Climate models project significant twenty-first-century declines in water availability over the American West from anthropogenic warming. However, the physical mechanisms underpinning this response are poorly characterized, as are the uncertainties from vegetation's modulation of evaporative losses. To understand the drivers and uncertainties of future hydroclimate in the American West, a 35-member single model ensemble is used to examine the response of summer soil moisture and runoff to anthropogenic forcing. Widespread dry season soil moisture declines occur across the region despite increases in total water-year precipitation and ubiquitous increases in plant water-use efficiency. These modeled soil moisture declines are initially forced by significant snowpack losses that directly diminish summer soil water, even in regions where water-year precipitation increases. When snowpack priming is coupled with a warming- and CO2-induced shift in phenology and increased primary production, widespread increases in leaf area further reduces summer soil moisture and runoff by outpacing decreased stomatal conductance from high CO2. The net effects lead to the co-occurrence of both a 'greener' and 'drier' future across the western United States. Because simulated vegetation exerts a large influence on predicted changes in water availability in the American West, these findings highlight the importance of reducing the substantial uncertainties in the ecological processes increasingly incorporated into numerical Earth system models. [ABSTRACT FROM AUTHOR]

The central Amazon forest is projected to experience larger interannual precipitation variability, with uncertain impacts on terrestrial hydrologic fluxes. How surface runoff, groundwater, and evapotranspiration (ET) change as a function of annual precipitation (AP) has large climate and biogeochemical implications. A process-based hydrological model is used to examine the sensitivity of hydrologic budgets and stream discharge Q s generation to AP in an upland Amazon catchment. The authors find that AP strongly controls infiltration, base flow, and surface runoff, but not ET. Hence, AP alone can predict interannual changes in these fluxes except ET. Experiments with perturbed rainfall show the strong control derives from the predominant groundwater component that varies linearly with AP but is insensitive to seasonal rainfall fluctuations. Most rainfall from large storms infiltrates and becomes base flow rather than runoff or ET. Annual baseflow index (BFI; the fraction of stream discharge from base flow) is nearly constant (~0.8) when AP is below ~2500 mm yr−1 and decreases with AP above this value, which represents an inflection point for increased storage-dependent saturation excess. These results indicate that the system is energy limited and groundwater dominated in dry seasons, which implies some resilience of ET to moderate droughts. The results suggest AP is a good predictor for interannual changes in infiltration. Both the seasonal near-surface soil moisture and surface runoff are correlated more strongly to the subsurface fluxes than to precipitation over monthly and annual time scales. Finally, the results confirm the importance of central Amazon groundwater flow and its buffering effect on storms and droughts, implying needed model development in regional to global models. [ABSTRACT FROM AUTHOR]

This study examines the dynamics and robustness of large-scale evapotranspiration products in water-limited environments. Four types of ET products are tested against rainfall in two large semi-arid to arid Australian basins from 2003 to 2010: two energy balance ET methods which are forced by optical satellite retrievals from MODIS; a newly developed land surface model (AWRA); and one approach based on observations from the Gravity Recovery and Climate Experiment (GRACE) and rainfall data. The two basins are quasi (Murray-Darling Basin: 1.06 million km²) and completely (Lake Eyre Basin: 1.14 million km²) endorheic. During the study period, two extreme climatic events--the Millennium drought and the strongest La Niña event--were recorded in the basins and are used in our assessment. The two remotely-sensed ET products constrained by the energy balance tended to overestimate ET flux over water-stressed regions. They had low sensitivity to climatic extremes and poor capability to close the water balance. However, these two remotely-sensed and energy balance products demonstrated their superiority in capturing spatial features including over small-scale and complicated landscapes. AWRA and GRACE formulated in the water balance framework were more sensitive to rainfall variability and yielded more realistic ET estimates during climate extremes. GRACE demonstrated its ability to account for seasonal and inter-annual change in water storage for ET evaluation. [ABSTRACT FROM AUTHOR]

Land surface processes play an important role in the West African monsoon variability. In addition, the evolution of hydrological systems in this region, and particularly the increase of surface water and runoff coefficients observed since the 1950s, has had a strong impact on water resources and on the occurrence of floods events. This study addresses results from phase 2 of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project (ALMIP2), carried out to evaluate the capability of different state-of-the-art land surface models to reproduce surface processes at the mesoscale. Evaluation of runoff and water fluxes over the Mali site is carried out through comparison with runoff estimations over endorheic watersheds as well as evapotranspiration (ET) measurements. Three remote-sensing-based ET products [ALEXI, MODIS, and Global Land Evaporation Amsterdam Model (GLEAM)] are also analyzed. It is found that, over deep sandy soils, surface runoff is generally overestimated, but the ALMIP2 multimodel mean reproduces in situ measurements of ET and water stress events rather well. However, ALMIP2 models are generally unable to distinguish among the two contrasted hydrological systems typical of the study area. Employing as input a soil map that explicitly represents shallow soils improves the representation of water fluxes for the models that can account for their representation. Shallow soils are shown to be also quite challenging for remote-sensing-based ET products, even if their effect on evaporative loss was captured by the diagnostic thermal-based ALEXI. A better representation of these soils, in soil databases, model parameterizations, and remote sensing algorithms, is fundamental to improve the estimation of water fluxes in this part of the Sahel. [ABSTRACT FROM AUTHOR]

A new, high-resolution (4 km), gridded land surface dataset produced with the Land Information System (LIS) is introduced, and the first set of synthesis of key hydroclimatic variables is reported. The dataset is produced over a 33-yr time period (1980-2012) for the U.S. Midwest with the intent to aid the agricultural community in understanding hydroclimatic impacts on crop production and decision-making in operational practices. While approximately 20 hydroclimatic variables are available through the LIS dataset, the focus here is on soil water content, soil temperature, and evapotranspiration. To assess the performance of the model, the LIS dataset is compared with in situ hydrometeorological observations across the study domain and with coarse-resolution reanalysis products [NARR, MERRA, and NLDAS-2 (phase 2 of the North American Land Data Assimilation System)]. In agricultural regions such as the U.S. Midwest, finescale hydroclimatic mapping that links the regional scale to the field scale is necessary. The new dataset provides this link as an intermediate-scale product that links point observations and coarse gridded datasets. In general, the LIS dataset compares well with in situ observations and coarser gridded products in terms of both temporal and spatial patterns, but cases of strong disagreement exist particularly in areas with sandy soils. The dataset is made available to the broader research community as an effort to fill the gap in spatial hydroclimatic data availability. [ABSTRACT FROM AUTHOR]

Distributed hydrological models simulate states and fluxes of water and energy in the terrestrial hydrosphere at each cell. The predicted spatial patterns result from complex nonlinear relationships and feedbacks. Spatial patterns are often neglected during the modeling process, and therefore a spatial sensitivity analysis framework that highlights their importance is proposed. This study features a comprehensive analysis of spatial patterns of actual evapotranspiration (ET) and land surface temperature (LST), with the aim of quantifying the extent to which forcing data and model parameters drive these patterns. This framework is applied on a distributed model [MIKE Système Hydrologique Européen (MIKE SHE)] coupled to a land surface model [Shuttleworth and Wallace-Evapotranspiration (SW-ET)] of a catchment in Denmark. Twenty-two scenarios are defined, each having a simplified representation of a potential driver of spatial variability. A baseline model that incorporates full spatial detail is used to assess sensitivity. High sensitivity can be attested in scenarios where the simulated spatial patterns differ significantly from the baseline. The core novelty of this study is that the analysis is based on a set of innovative spatial performance metrics that enable a reliable spatial pattern comparison. Overall, LST is very sensitive to air temperature and wind speed whereas ET is rather driven by vegetation. Both are sensitive to groundwater coupling and precipitation. The conclusions may be limited to the selected catchment and to the applied modeling system, but the suggested framework is generically relevant for the modeling community. While the applied metrics focus on specific spatial information, they partly exhibit redundant information. Thus, a combination of metrics is the ideal approach to evaluate spatial patterns in models outputs. [ABSTRACT FROM AUTHOR]

Land surface models (LSMs) are useful tools to estimate land evapotranspiration at a grid scale and for long-term applications. Here, the Community Land Model, version 4.0 (CLM4.0); Dynamic Land Model (DLM); and Variable Infiltration Capacity model (VIC) were driven with observation-based forcing datasets, and a multiple-LSM ensemble-averaged evapotranspiration (ET) product (LSMs-ET) was developed and its spatial-temporal variations were analyzed for the China landmass over the period 1979-2012. Evaluations against measurements from nine flux towers at site scale and surface water budget-based ET at regional scale showed that the LSMs-ET had good performance in most areas of China's landmass. The intercomparisons between the ET estimates and the independent ET products from remote sensing and upscaling methods suggested that there were fairly consistent patterns between each dataset. The LSMs-ET produced a mean annual ET of 351.24 ± 10.7 mm yr−1 over 1979-2012, and its spatial-temporal variation analyses showed that (i) there was an overall significant ET increasing trend, with a value of 0.72 mm yr−1 ( p < 0.01), and (ii) 36.01% of Chinese land had significant increasing trends, ranging from 1 to 9 mm yr−1, while only 6.41% of the area showed significant decreasing trends, ranging from −6.28 to −0.08 mm yr−1. Analyses of ET variations in each climate region clearly showed that the Tibetan Plateau areas were the main contributors to the overall increasing ET trends of China. [ABSTRACT FROM AUTHOR]

The Community Atmosphere Biosphere Land Exchange (CABLE) land surface model overestimates evapotranspiration ( E) at numerous flux tower sites during boreal spring. The overestimation of E is not eliminated when the nonlinear dependence of soil evaporation on soil moisture or a simple litter layer is introduced into the model. New resistance terms, previously developed from a pore-scale model of soil evaporation, are incorporated into the treatment of under canopy water vapor transfer in CABLE. The new resistance terms reduce the large positive bias in spring time E at multiple flux tower sites and also improve the simulation of daily sensible heat flux. The reduction in the spring E bias allows the soil to retain water into the summer, improving the seasonality of E. The simulation of daily E is largely insensitive to the details of the implementation of the pore model resistance scheme. The more physically based treatment of soil evaporation presented here eliminates the need for empirical functions that reduce evaporation as a function of soil moisture that are included in many land surface models. [ABSTRACT FROM AUTHOR]

Imperfect land physics introduce significant levels of uncertainty into current land surface models (LSMs) and can cause bias in their representation of land-atmosphere coupling strength (ρ). When LSMs are coupled with atmospheric prediction models, such errors will eventually degrade the accuracy of lower atmosphere forecasts. Here, we investigate the potential of two remote sensing (RS)-based ρ references for addressing LSM ρ bias. To minimize meteorological uncertainty and maximally attribute LSM ρ bias to land sources, we focus specifically on off-line LSM calibration forced using high-quality, observation-based meteorological data. Both ρ references are based on a newly proposed two-system approach for eliminating the impact of random errors in RS retrievals and quantified using the temporal correlations of soil moisture (SM) versus both evapotranspiration (ET) and the diurnal amplitude of surface temperature (dT). Experiments are conducted to calibrate an off-line LSM individually against each resulting ρ reference and using a combination of both dT- and ET-represented ρ references. The resulting calibrated LSM is further evaluated using independent ground-based ET observations and RS dT retrievals. Results show that although dT- and ET-represented ρ references are physically consistent across space, model calibration results based on them are quite different. Specifically, the calibration experiment targeting ET-represented ρ outperforms that targeting dT-represented ρ in ET and dT modeling. Diagnostic results indicate that the failure of dT-based calibration experiments is due to the confounding impacts of transpiration/evapotranspiration partitioning error and large dT uncertainties in LSM. However, results also confirm the potential of both dT- and ET-represented ρ references for jointly diagnosing and understanding LSM ρ bias. As a result, we suggest diagnosing LSM ρ bias using both ET- and dT-represented ρ references – but calibrating LSM using only ET-represented ρ reference data. • A new approach is proposed for estimating land-atmosphere coupling strength (ρ). • Remotely sensed surface temperature- and ET-based ρ are estimated. • They are physically consistent and complementary in understanding LSM ρ bias. • ET-based ρ is more applicable for LSM calibration than temperature-based ρ. [ABSTRACT FROM AUTHOR]

During the industrial period, many regions experienced a reduction in forest cover and an expansion of agricultural areas, in particular North America, northern Eurasia, and South Asia. Here, results from the Land-Use and Climate, Identification of Robust Impacts (LUCID) and CMIP5 model intercomparison projects are compared in order to investigate how land-cover changes (LCC) in these regions have locally impacted the biophysical land surface properties, like albedo and evapotranspiration, and how this has affected seasonal mean temperature as well as its diurnal cycle. The impact of LCC is extracted from climate simulations, including all historical forcings, using a method that is shown to capture well the sign and the seasonal cycle of the impacts diagnosed from single-forcing experiments in most cases. The model comparison reveals that both the LUCID and CMIP5 models agree on the albedo-induced reduction of mean winter temperatures over midlatitudes. In contrast, there is less agreement concerning the response of the latent heat flux and, subsequently, mean temperature during summer, when evaporative cooling plays a more important role. Overall, a majority of models exhibit a local warming effect of LCC during this season, contrasting with results from the LUCID studies. A striking result is that none of the analyzed models reproduce well the changes in the diurnal cycle identified in present-day observations of the effect of deforestation. However, overall the CMIP5 models better simulate the observed summer daytime warming effect compared to the LUCID models, as well as the winter nighttime cooling effect. [ABSTRACT FROM AUTHOR]

The effects of groundwater dynamics on the representation of water storage and evapotranspiration (ET) over southern South America are studied from simulations with the Noah-MP land surface model. The model is run with three different configurations: one including the Miguez-Macho and Fan groundwater scheme, another with the Simple Groundwater Model (SIMGM), and the other with free drainage at the bottom of the soil column. The first objective is to assess the effects of the groundwater schemes using a grid size typical of regional climate model simulations at the continental scale (20 km). The phase and amplitude of the fluctuations in the terrestrial water storage over the southern Amazon are improved with one of the groundwater schemes. An increase in the moisture in the top 2 m of the soil is found in those regions where the water table is closer to the land surface, including the western and southern Amazon and the La Plata basin. This induces an increase in ET over the southern La Plata basin, where ET is water limited. There is also a seasonal increase in ET during the dry season over parts of the southern Amazon. The second objective is to assess the role of the horizontal resolution on the effects induced by the Miguez-Macho and Fan groundwater scheme using simulations with grid sizes of 5 and 20 km. Over the La Plata basin, the effect of groundwater on ET is amplified at the 5-km resolution. Notably, over parts of the Amazon, the groundwater scheme increases ET only at the higher 5-km resolution. [ABSTRACT FROM AUTHOR]

A sensitivity study of the impact of a groundwater scheme on hydrometeorological variables in coupled land-atmosphere simulations over southern South America is presented. It is found that shallow water tables in the groundwater scheme lead to reduced drainage and even upward capillary fluxes over parts of the central and southern La Plata basin. This leads to an increase in the simulated moisture in the root zone, which in turn produces an increase in evapotranspiration (ET) over the southern part of the domain, where ET is water limited. There is also a decrease in the near-surface temperature, in the range 0.5°-1.0°C. During the dry season, the increases in ET and relative humidity over the central La Plata coincide with an increase in precipitation downstream. Including groundwater leads to an increase in precipitation over parts of the central and southern La Plata basin during the early rainy season (October-December). The overall increase in ET and precipitation over the southern La Plata basin during the early rainy season is 13% and 10%, respectively. The additional precipitation comes from both an increase in the availability of atmospheric moisture when the groundwater scheme is used and its effect on the atmospheric instability. In the La Plata basin, including a representation of groundwater increases simulated precipitation and partially alleviates a warm and dry bias present in simulations without realistic subsurface hydrology. [ABSTRACT FROM AUTHOR]

Inclusion of vegetation is critical for urban land surface models (ULSM) to represent reasonably the turbulent sensible and latent heat flux densities in an urban environment. Here the Joint UK Land Environment Simulator (JULES), a ULSM, is used to simulate the Bowen ratio at a number of urban and rural sites with vegetation cover varying between 1% and 98%. The results show that JULES is able to represent the observed Bowen ratios, but only when the additional anthropogenic water supplied into the urban ecosystem is considered. The impact of the external water use (e.g., through irrigation or street cleaning) on the surface energy flux partitioning can be as substantial as that of the anthropogenic heat flux on the sensible and latent heat fluxes. The Bowen ratio varies from 1 to 2 when the plan area vegetation fraction is between 30% and 70%. However, when the vegetation fraction is less than 20%, the Bowen ratios increase substantially (2-10) and have greater sensitivity to assumptions about external water use. As there are few long-term observational sites with vegetation cover less than 30%, there is a clear need for more measurement studies in such environments. [ABSTRACT FROM AUTHOR]

A method for projecting the water levels of the Laurentian Great Lakes under scenarios of human-caused climate change, used almost to the exclusion of other methods in the past, relies very heavily on the large basin runoff model (LBRM) as a component for determining the water budget for the lake system. This model uses near-surface air temperature as a primary predictor of evapotranspiration (ET); as in previous published work, it is shown here that the model's very high sensitivity to temperature causes it to overestimate ET in a way that is greatly at variance with the fundamental principle of conservation of energy at the land surface. The traditional formulation is characterized here as being equivalent to having several suns in the virtual sky created by LBRM. More physically based methods show, relative to the traditional method, often astoundingly less potential ET and less ET, more runoff from the land and net basin supply for the lake basins, and higher lake water levels in the future. Using various methods of estimating the statistical significance, it is found that, at minimum, these discrepancies in results are significant at the 99.998% level. The lesson for the larger climate impact community is to use caution about whether an impact is forced directly by air temperature itself or is significantly forced by season or latitude independently of temperature. The results here apply only to the water levels of the Great Lakes and the hydrology of its basin and do not affect larger questions of climate change. [ABSTRACT FROM AUTHOR]