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Amending soils with biochar, a pyrolyzed organic material, is an emerging practice to potentially increase plant available water and reduce the risks associated with climatic variability in traditionally-rainfed tropical agricultural systems. To investigate the impacts of biochar amendment on soil water storage relative to non-amended soils, we performed an upland rice field experiment in a tropical seasonally dry region of Costa Rica consisting of plots with two different biochar amendments and a control plot. Across all plots, we collected hydrometric and isotopic data (delta O-18 and delta H-2 of rain, mobile soil, ground and rice xylem water). We observed that the soil water retention curves for biochar treated soils shifted, indicating that rice plants had 2% to 7% more water available throughout the growing season relative to the control plots and thus could withstand dry spells up to seven extra days. Furthermore, the isotopic composition of plant water in biochar and control treatments were rather similar, indicating that rice plants in different treatments likely consumed similar water. Hence, we observed that biochar amendments can stabilize water supplies for the rice plants; however, still supplemental irrigation was required to facilitate plant growth during extended dry periods. Ultimately, our findings indicate, that biochar amendments can complement, but not necessarily replace, other water management strategies to help reduce the threat of rainfall variability to rainfed agriculture in tropical regions.

Biochar has been put forward as a potential technology that could help achieve sustainable water management in agriculture through its ability to increase water holding capacity in soils. Despite this opportunity, there are still a limited number of studies, especially in vulnerable regions like the tropics, quantifying the impacts of biochar on soil water storage and characterizing the impacts of biochar additions on plant water composition. To address this critical gap, we present a case study using stable water isotopes and hydrometric data from melon production in tropical agriculture to explore the hydrological impacts of biochar as a soil amendment. Results from our 10-week growing season experiment in Costa Rica under drip irrigation demonstrated an average increase in volumetric soil moisture content of about 10% with an average moisture content of 25.4 cm(3) cm(-3) versus 23.1 cm(3) cm(-3), respectively, for biochar amended plots compared with control plots. Further, there was a reduction in the variability of soil matric potential for biochar amended plots compared with control plots. Our isotopic investigation demonstrated that for both biochar and control plots, there was a consistent increase (or enrichment) in isotopic composition for plant materials moving from the roots, where the average delta O-18 was -8.1 parts per thousand and the average delta H-2 was -58.5 parts per thousand across all plots and samples, up through the leaves, where the average delta O-18 was 4.3 parts per thousand and the average delta H-2 was 0.1 parts per thousand across all plots and samples. However, as there was no discernible difference in isotopic composition for plant water samples when comparing across biochar and control plots, we find that biochar did not alter the composition of water found in the melon plant material, indicating that biochar and plants are not competing for the same water sources. In addition, and through the holistic lens of sustainability, biochar additions allowed locally sourced feedstock carbon to be directly sequestered into the soil while improving soil water availability without jeopardizing production for the melon crop. Given that most of the expansion and intensification of global agricultural production over the next several decades will take place in the tropics and that the variability of tropical water cycling is expected to increase due to climate change, biochar amendments could offer a pathway forward towards sustainable tropical agricultural water management.

Low-cost miniature hyperspectral and thermal cameras onboard lightweight unmanned aerial vehicles (UAV) bring new opportunities for monitoring land surface variables at unprecedented fine spatial resolution with acceptable accuracy. This research applies hyperspectral and thermal imagery from a drone to quantify upland rice growth and water use efficiency (WUE) after biochar application in a Costa Rican dry region. The field flights were conducted over two experimental groups with bamboo biochar and sugarcane biochar amendments and one control group without biochar application. Rice canopy biophysical variables were estimated by inversion of a canopy radiative transfer model on hyperspectral reflectance. Variations in gross primary production (GPP) and WUE across treatments were estimated from the normalized difference vegetation index (NDVI), canopy chlorophyll content (CCC), and evapotranspiration. We found that GPP was increased by 41.9±3.4 % when using bamboo biochar and 17.5±3.4 % when using sugarcane biochar, which was probably due to higher soil moisture in the biochar-amended plots and led to significantly higher WUE by 40.8±3.5 % in bamboo biochar and 13.4±3.5 % in sugarcane biochar. This study demonstrated the use of hyperspectral and thermal imagery from drone to provide indicators for quantifying biochar effects on tropical dry cropland by integrating with ground point samples and physical models.

Amending soils with biochar, a pyrolyzed organic material, is an emerging practice to potentially increase plant available water. However, it is not clear (1) to what extent biochar amendments increase soil water storage relative to non-amended soils and (2) whether plants grown in biochar amended soils access different pools of water compared to those grown in non-amended soils. To investigate these questions, we set up an upland rice field experiment in a tropical seasonally dry region in Costa Rica, with plots treated with two different biochar amendments and control plots, from where we collected hydrometric and isotopic data (δ18O and δ2H from rain, soil, groundwater and rice plants). Our results show that the soil water retention curves for biochar treated soils shifted, indicating that rice plants had 2 % to 7 % more water available throughout the growing season relative to the control plots. In addition, we observed a within treatment variability in the soil water retention curves which was in the same order of magnitude as one would expect from responses due to differences in biochar application rates or due to differences in biochar typologies. The stable water isotope composition of plant water showed that the rice plants across all plots preferentially utilized the more variable soil water from the top 20 cm of the soil instead of using the deeper and less variable sources of water. Our results indicated that rice plants in biochar amended soils could access larger stores of water more consistently and thus could withstand dry spells of seven extra days relative to rice grown in non-treated soils. Though supplemental irrigation was required to facilitate plant growth during extended dry periods. Therefore, biochar amendments can complement, but not necessarily replace, other water management strategies.

The ECOsystem Space Thermal Radiometer Experiment on the Space Station (ECOSTRESS) was launched to the International Space Station on June 29, 2018 by the National Aeronautics and Space Administration (NASA). The primary scientific focus of ECOSTRESS is on evapotranspiration (ET), which occurs as Level 3 (L3) latent heat flux (LE) data products. This data is generated from the Level 2 Earth Surface Temperature and Emissivity Product (L2_LSTE), along with the atmospheric and ancillary surface data. Here, we provide the first validation (Stage 1, preliminary) of the global product ECOSTRESS clear - sky ET (L3_ET_PT - JPL, Version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against site measurements (instant clear sky / flyover time: r 2 = 0.88; overall bias = 8%; normalized root mean square error, RMSE = 6%) . ET uncertainty was generally constant across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), although temperate sites are over-represented. ECOSTRESS 70 m high spatial resolution improved correlations by 85% and RMSE by 62%, relative to 1 km pixels. This document serves as a reference for the accuracy of ECOSTRESS L3 ET and the Stage 1 validation status for subsequent science that continues to use this data. Fil: Fisher, Joshua B. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Lee, Brian. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Purdy, Adam J. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Halverson, Gregory H. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Dohlen, Matthew B. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Cawse - Nicholson, Kerry. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Wang, Audrey. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Anderson, Ray G. U.S. Department of Agriculture; Estados Unidos Fil: Aragon, Bruno. King Abdullah University of Science and Technology. Division of Biological and Environmental Science and Engineering. Hydrology, Agriculture and Land Observation Group (HALO); Arabia Saudita Fil: Arain, M. Alfat. McMaster University. School of Geography and Earth Sciences; Canadá Fil: Baldocchi, Dennis D. University of California, Berkeley. Department of Environmental Science, Policy and Management; Estados Unidos Fil: Baker, John M. U.S. Department of Agriculture; Estados Unidos Fil: Barral, Helene. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Bernacchi, Carl J. University of Illinois Urbana‐Champaign. Institute for Sustainability, Energy, and Environment and Carl R. Woese Institute for Genomic Biology. Center for Advanced Bioenergy and Bioproducts Innovation; Estados Unidos. U.S. Department of Agriculture, Global Change and Photosynthesis Research Unit; Estados Unidos Fil: Bernhofer, Christian. Technische Universität Dresden, Institute of Hydrology and Meteorology; Alemania Fil: Biraud, Sebastien C. Lawrence Berkeley National Laboratory; Estados Unidos Fil: Bohrer, Gil. Ohio State University. Department of Civil, Environmental and Geodetic Engineering; Estados Unidos Fil: Brunsell, Nathaniel. University of Kansas. Department of Geography and Atmospheric Science; Estados Unidos Fil: Cappelaere, Bernard. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Castro - Contreras, Saulo. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Chum, Junghwa. National Institute of Forest Science; Corea del Sur Fil: Conrad, Bryan. University of Kansas. Department of Geography and Atmospheric Science; Estados Unidos Fil: Cremonese, Edoardo. Environmental Protection Agency of Aosta Valley; Italia Fil: Demarty, Jerome. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Desai, Ankur R. University of Wisconsin‐Madison. Department of Atmospheric and Oceanic Sciences; Estados Unidos Fil: De Ligne, Anne. University of Liege. TERRA Teaching and Research Centre. Gembloux Agro‐Bio Tech; Bélgica Fil: Foltynova, Lenka. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Goulden, Michael L. University of California Irvine. Department of Earth System Science; Estados Unidos Fil: Griffis, Timothy J. University of Minnesota. Department of Soil, Water, and Climate; Estados Unidos Fil: Grunwald, Thomas. Technische Universität Dresden, Institute of Hydrology and Meteorology; Alemania Fil: Johnson, Mark S. University of British Columbia. Department of Earth, Ocean, and Atmospheric Sciences; Canadá Fil: Kang, Minseok. National Center for AgroMeteorology; Corea del Sur Fil: Kelbe, Dave. Xerra Earth Observation Institute; Nueva Zelanda Fil: Kowalska, Natalia. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Jong - Hwan, Lim. National Institute of Forest Science; Corea del Sur Fil: Mainassara, Ibrahim. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: McCabe, Matthew F. King Abdullah University of Science and Technology. Division of Biological and Environmental Science and Engineering. Hydrology, Agriculture and Land Observation Group (HALO); Arabia Saudita Fil: Missik, Justine E.C. Washington State University. Department of Civil and Environmental Engineering. Laboratory for Atmospheric Research; Estados Unidos Fil: Mohanty, Binayak P. Texas A&M University. Texas Water Observatory; Estados Unidos Fil: Moore, Caitlin E. University of Illinois Urbana‐Champaign. Institute for Sustainability, Energy, and Environment and Carl R. Woese Institute for Genomic Biology. Center for Advanced Bioenergy and Bioproducts Innovation; Estados Unidos Fil: Morillas, Laura. University of British Columbia. Department of Earth, Ocean, and Atmospheric Sciences; Canadá Fil: Morrison, Ross. Centre for Ecology and Hydrology; Reino Unido Fil: Munger, J. Willians. Harvard University. School of Engineering and Applied Sciences; Estados Unidos Fil: Posse, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina Fil: Richardson, Andrew D. Northern Arizona University Center for Ecosystem Science and Society; Estados Unidos Fil: Russell, Eric. S. Washington State University. Department of Civil and Environmental Engineering. Laboratory for Atmospheric Research; Estados Unidos Fil: Ryu, Youngryel. Seoul National University . Department of Landscape Architecture and Rural Systems Engineering; Corea del Sur Fil: Sanchez - Azofeifa, Arturo. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Schmidt, Marius. IInstitute of Bio‐ and Geosciences: Agrosphere (IBG‐3) Forschungszentrum Jülich IBG‐3; Alemania Fil: Schwartz, Efrat. Weizmann Institute of Science. Department of Earth and Planetary Sciences, ; Israel Fil: Sharp, Iain. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Sigut, Ladislav. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Tang, Yao. Georgia Institute of Technology. School of Civil and Environmental Engineering; Estados Unidos Fil: Hulley, Glynn. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Anderson, Martha. U.S. Department of Agriculture‐Agricultural Research Service; Estados Unidos Fil: Hain, Christopher. NASA Marshall Space Flight Center; Estados Unidos Fil: French, Andrew. U.S. Department of Agriculture; Estados Unidos Fil: Wood, Eric. Princeton University. Department of Civil and Environmental Engineering; Estados Unidos Fil: Hook, Simón. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos

Communities in regions with seasonal rainfall face annual dry seasons, during which water shortages and conflicts between different water use sectors may erupt. These difficulties increase following wet seasons with low rainfall, such as in relation to El Nino events in the wet-dry tropics of Central America. Hydrologic data are typically scarce in this region, making the development of drought adaptation strategies challenging. Many communities in the region depend on groundwater as their primary water source. For instance in the Province of Guanacaste in Costa Rica, groundwater supplied 78% of the total domestic water demand in 2015 and groundwater recharge from the wet season provides the primary water supply for the subsequent dry season. In this research we present a ‘groundwater recharge indicator’ that can support water managers in preparing for seasonal droughts. We developed this tool for an aquifer in northwestern Costa Rica where we conducted hydrological monitoring of streams and groundwater levels for 2.5 years, obtained further hydrological data (groundwater levels from 2005 to 2016), and worked with communities to assemble water use data. We combined these datasets in a hydrologic model (the Water Evaluation And Planning system, WEAP) and modelled groundwater recharge from 2005 to 2016, permitting a characterization of the relationship between rainfall and groundwater recharge. The groundwater recharge indicator is based on this relationship, and allows estimating total groundwater recharge for a wet season from cumulative rainfall measured to date. The indicator permits water managers to assess if the current year will likely fall into a low recharge category prior to the end of the wet season. This information can then be used to trigger short-term adaptation strategies with the goal to ‘bank’ groundwater while surface water sources are still available in the wet season. This indicator-based tool was refined through feedback provided in local stakeholder workshops. We also assessed the overall accuracy of predicting end-of-wet-season groundwater recharge with cumulative rainfall to date, and found that after the first 2–3 months of the wet season, prediction accuracies are high, leaving 5–6 months of wet season to respond adaptively to the prediction. The indicator can help water managers to plan ahead, and communicate the need for water conservation (demand management) and consideration of other water sources such as rain and surface water (supply management). This idea is transferable to other communities in regions with seasonal rainfall, and can support decision makers in increasing the socio-hydrological resilience of communities to seasonal droughts.

DOE Office of Science TES [SC DE-SC0008088]; NSF Ecosystems [NSF-DEB-1557176]; Pacific Northwest National Lab's LDRD program; Los Alamos National Lab; College of Arts and Sciences at the University of New Mexico

The recent paper by Morillas et al. [Morillas, L. et al. Using radiometric surface temperature for surface energy flux estimation in Mediterranean drylands from a two-source perspective, Remote Sens. Environ. 136, 234–246, 2013] evaluates the two-source model (TSM) of Norman et al. (1995) with revisions by Kustas and Norman (1999) over a semiarid tussock grassland site in southeastern Spain. The TSM - in its current incarnation, the two-source energy balance model (TSEB) - was applied to this landscape using ground-based infrared radiometer sensors to estimate both the composite surface radiometric temperature and component soil and canopy temperatures. Morillas et al. (2013) found the TSEB model substantially underestimated the sensible H (and overestimated the latent heat LE) fluxes. Using the same data set from Morillas et al. (2013), we were able to confirm their results. We also found energy transport and exchange behavior derived from primarily the observations themselves to differ significantly from a number of prior studies using land surface temperature for estimating heat fluxes with one-source modeling approaches in semi-arid landscapes. However, revisions to key vegetation inputs to TSEB and the soil resistance formulation resulted in a significant reduction in the bias and root mean square error (RMSE) between model output of H and LE and the measurements compared to the prior results from Morillas et al. (2013). These included more representative ground-based vegetation greenness and local leaf area index values as well as modifications to the coefficients of the soil resistance formulation to account for the very rough (rocky) soil surface conditions with a clumped canopy. This indicates that both limitations in remote estimates of biophysical indicators of the canopy at the site and the lack of adjustment in soil resistance formulation to account for site specific characteristics, contributed to the earlier findings of Morillas et al. (2013). This suggests further studies need to be conducted to reduce the uncertainties in the vegetation and land surface temperature input data in order to more accurately assess the effects of the transport exchange processes of this Mediterranean landscape on TSEB formulations.

Activation of NK cells depends on a balance between activating and inhibitory signals. Class Ia PI3K are heterodimeric proteins with a catalytic and a regulatory subunit and have a central role in cell signaling by associating with tyrosine kinase receptors to trigger signaling cascades. The regulatory p85 subunit participates in signaling through NKG2D, one of the main activating receptors on NK cells, via its interaction with the adaptor protein DAP10. Although the effects of inhibiting catalytic subunits or deleting the regulatory p85α subunit have been studied, little attention has focused on the role of the p85β subunit in NK cells. Using p85β knockout mice, we found that p85β deficiency does not alter NK cell differentiation and maturation in spleen or bone marrow. NK cells from p85β−/− mice nonetheless produced more IFN-γ and degranulated more effectively when stimulated with anti-NKG2D antibody. These cells also degranulated and killed NKG2D ligand-expressing target cells more efficiently. We show that p85β deficiency impaired NKG2D internalization, which could contribute to the activated phenotype. Decreasing p85β subunit protein levels might thus constitute a therapeutic target to promote NK cell activity toward NKG2D ligand-expressing cells.

The temperature-based two-source model (TSM) of Norman et al. (1995) has not been properly evaluated under the water stress conditions that are typical in natural Mediterranean drylands. In such areas, the asynchrony between precipitation and energy supply strongly reduces evapotranspiration, E (or latent heat flux, LE , if expressed in energy terms), making sensible heat flux ( H ) the dominant turbulent heat flux. In this study, we present a detailed analysis of the main environmental factors affecting the TSM effectiveness under such challenging conditions. The accuracy of the TSM, evaluated via errors in 15-min H estimates, was shown to have a diurnal variation. Accuracy was clearly reduced for solar elevation angles lower than 25° and during marginal hours of daytime, before 10 am and after 3 pm. The surface to air temperature difference ( T R − T a ) and the wind speed were the two environmental factors showing the strongest effect on the TSM accuracy. In contrast with results observed in other ecosystems, in this Mediterranean tussock grassland the TSM accuracy was not clearly reduced by cloudiness and it was improved under highly stressed vegetation conditions. The parallel resistances scheme of the TSM ( TSM P ) showed overall lower errors and a lower tendency to underestimate at high H values, but the series resistances scheme of the TSM ( TSM S ) increased the model accuracy under some specific circumstances such as low energy supply and atmospheric neutral conditions. Finally, two extrapolation methods to obtain daytime ( Rn > 55 W m −2 ) turbulent fluxes from the 15-min estimates of TSM were compared: (i) assuming the self-preservation of the evaporative and the non-evaporative fraction ( EF and NEF method ) and (ii) averaging the total daytime instantaneous fluxes ( Averaging method ). Despite the assumption of daytime self-preservation of EF and NEF was showed consistent, this method retrieved less accurate daytime estimates of H , and E than the Averaging method as a result of inaccuracies affecting estimates of EF and NEF from the TSM at our site. Moreover, better daytime estimates of H and E were obtained when using instantaneous fluxes from the TSM P than from the TSM S . Thus, reliable daytime estimates of H were obtained from the TSM P in a Mediterranean dryland, with mean errors of 20% and high correlations ( R 2 = 0.85). However, daytime E was strongly overestimated (125%) using the TSM by both methods, although a good correlation with eddy covariance measurements was found ( R 2 = 0.84).

[1] An adaptation of a simple model for evapotranspiration (E) estimations in drylands based on remotely sensed leaf area index and the Penman-Monteith equation (PML model) (Leuning et al., 2008) is presented. Three methods for improving the consideration of soil evaporation influence in total evapotranspiration estimates for these ecosystems are proposed. The original PML model considered evaporation as a constant fraction (f) of soil equilibrium evaporation. We propose an adaptation that considers f as a variable primarily related to soil water availability. In order to estimate daily f values, the first proposed method (fSWC) uses rescaled soil water content measurements, the second (fZhang) uses the ratio of 16 days antecedent precipitation and soil equilibrium evaporation, and the third (fdrying), includes a soil drying simulation factor for periods after a rainfall event. E estimates were validated using E measurements from eddy covariance systems located in two functionally different sparsely vegetated drylands sites: a littoral Mediterranean semiarid steppe and a dry-subhumid Mediterranean montane site. The method providing the best results in both areas was fdrying (mean absolute error of 0.17 mm day−1) which was capable of reproducing the pulse-behavior characteristic of soil evaporation in drylands strongly linked to water availability. This proposed model adaptation, fdrying, improved the PML model performance in sparsely vegetated drylands where a more accurate consideration of soil evaporation is necessary.

A two-source model (TSM) for surface energy balance, considering explicitly soil and vegetation components, was tested under water stress conditions. The TSM evaluated estimates the sensible heat flux (H) using the surface-air thermal gradient and the latent heat flux (LE) as a residual from the surface energy balance equation. The analysis was performed in a semiarid Mediterranean tussock grassland in southeast Spain, where H is the dominant flux and LE rates are low, challenging conditions under which the TSM has not been validated before. We evaluated two different resistance schemes: series and parallel; as well as the iterative algorithm included in the TSM to disaggregate the soil-surface composite temperature into its separate components. Continuous field measurements of composite soil-vegetation surface temperature (TR) and bare soil temperature (Ts) from thermal infrared sensors were used for model testing along with canopy temperature estimates (T'c), derived from TR and Ts.Comparisons with Eddy covariance and field data showed that the TSM produced reliable estimates of net radiation (Rn) and H fluxes, with errors of ~30% and ~10%, respectively, but not for LE, with errors ~90%. Despite of lower errors (~10%) in estimating H using parallel resistance, the series scheme was more robust showing slightly higher correlations (r2=0.78-0.80 vs. r2=0.75-0.77) and allowing a better disaggregation of soil and canopy fluxes. Differences between model runs using the iterative algorithm to disaggregate TR and the simplified version that uses separate inputs of Ts and T'c were minor. This demonstrates the robustness of the iterative procedure to disaggregate a composite soil-vegetation temperature into separate soil and vegetation components in semiarid environments with good prospects for image applications. © 2013 Elsevier Inc., This research was funded by Andalusia Regional Government projects AQUASEM (P06-RNM-01732), GEOCARBO (P08-RNM-3721), and GLOCHARID, European Union ERDF funds, with support from the Spanish Ministry of Science and Innovation CARBORAD Projects (CGL2011-27493), the Danish Council for Independent Research and Technology and Production Sciences (FTP) Grant 09-070382, and the research project RNM-6685 financed by the Regional Andalucian Government (Spain). L. Morillas received a Ph.D. research grant and funding from the Andalusia Regional Government for visiting the Institute of Geography and Geology, University of Copenhagen, in Denmark.

Improving regional estimates of actual evapotranspiration ( λE ) in water-limited regions located at climatic transition zones is critical. This study assesses an λE model (PT-JPL model) based on downscaling potential evapotranspiration according to multiple stresses at daily time-scale in two of these regions using MSG–SEVIRI (surface temperature and albedo) and MODIS products ( NDVI , LAI and f PAR ). An open woody savanna in the Sahel (Mali) and a Mediterranean grassland (Spain) were selected as test sites with Eddy Covariance data used for evaluation. The PT-JPL model was modified to run at a daily time step and the outputs from eight algorithms differing in the input variables and also in the formulation of the biophysical constraints (stresses) were compared with the λE from the Eddy Covariance. Model outputs were also compared with other modeling studies at similar global dryland ecosystems. The novelty of this paper is the computation of a key model parameter, the soil moisture constraint, relying on the concept of apparent thermal inertia ( f SM-ATI ) computed with surface temperature and albedo observations. Our results showed that f SM-ATI from both in-situ and satellite data produced satisfactory results for λE at the Sahelian savanna, comparable to parameterizations using field-measured Soil Water Content ( SWC ) with r 2 greater than 0.80. In the Mediterranean grasslands however, with much lower daily λE values, model results were not as good as in the Sahel (r 2 = 0.57–0.31) but still better than reported values from more complex models applied at the site such as the Two Source Model (TSM) or the Penman–Monteith Leuning model (PML). PT-JPL-daily model with a soil moisture constraint based on apparent thermal inertia, f SM-ATI offers great potential for regionalization as no field-calibrations are required and water vapor deficit estimates, required in the original version, are not necessary, being air temperature and the available energy ( Rn-G ) the only input variables required, apart from routinely available satellite products.