PT-jpl Publications

2021

Gu C., Tang Q., Zhu G., Ma J., Gu C., Zhang K., Sun S., et al., 2021, Discrepant responses between evapotranspiration- and transpiration-based ecosystem water use efficiency to interannual precipitation fluctuations, Ag. For. Met., 303:108385, 2021. doi:10.1016/j.agrformet.2021.108385  

Lan X, Li Y, Shao R, Chen X, Lin K, Cheng L, Gao H, Liu Z, Vegetation controls on surface energy partitioning and water budget over China, J. Hydrol., 600:125646, 2021.  

Lan, X; Liu, ZY; Chen, XH; Lin, KR; Cheng, LY, Trade-off between carbon sequestration and water loss for vegetation greening in China. AGRICULTURE ECOSYSTEMS & ENVIRONMENT, 319, 107522, 2021.  

Liu N, Oishi AC, Ford Miniat, Bolstad P, An evaluation of ECOSTRESS products of a temperate montane humid forest in a complex terrain environment, Remote Sensing of Environment, 265: 112662, 2021.  

Mobe NT, Dzikiti S, Dube T, Mazvimavi D, Ntshidi Z, Modelling water utilization patterns in apple orchards with varying canopy sizes and different growth stages in semi-arid environments, Scientia Horticulturae, 283:110051, 2021.  

Shang K, Liang S, Zhang Y, Fisher JB, Chen J, Liu S, Xu Z, Zhang Y, Jia K, Zhang X, Yang J, Bei X, Guo X, Yu R, Xie Z, Zhang L, DNN-MET: A Deep Neural Networks method to integrate satellite-derived evapotranspiration products, eddy covariance observations and ancillary information, Ag. For. Met., 2021. 308-309:108582  

Stisen, S, Soltani M, Mendiguren G, Langkilde H, Garcia M, Koch J, Spatial Patterns in Actual Evapotranspiration Climatologies for Europe. Remote Sens., 13, 2410, 2021. https://doi.org/10.3390/rs13122410  

Wang X, Zhang B, Li F, Li X, Li Xl, Wang Y, Shao R, Tian J, Vegetation Restoration Projects Intensify Intraregional Water Recycling Processes in the Agro-Pastoral Ecotone of Northern China, J. Hydromet., 22(6):1385–1403, 2021. DOI:https://doi.org/10.1175/JHM-D-20-0125.1  

Xing W, Wang W, Shao Q, Song L, Cao M, Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture Data. Remote Sens. 13, 3118, 2021. https://doi.org/10.3390/rs13163118  

Xiao, J., Fisher, J.B., Hashimoto, H., Ichii, K., Parazoo, N.C., Emerging satellite observations for diurnal cycling of ecosystem processes. Nature Plants, 2021. https://doi.org/10.1038/s41477-021-00952-8  

Yao, Y., Liang, S., Fisher, J.B., Zhang, Y., Chen, J., Jia, K., Zhang, X., Bei, X., Shang, K., Guo, X., Yang, J., A novel NIR-Red spectral domain evapotranspiration model from the Chinese GF-1 satellite: application to the Huailai agricultural region of China. IEEE Transactions on Geoscience and Remote Sensing 59(5): 4105-4119, 2021.  

Zhang, L, M Marshall, A Nelson, A Vrieling, A global assessment of PT-JPL soil evaporation in agroecosystems with optical, thermal, and microwave satellite data, Ag. For. Met., 306:108455, 2021.  

2020  

Athira KV, E Rajasekaran and G Boulet, Comparison of Three Remote Sensing Based Multi-Source Evapotranspiration Models, IEEE India Geoscience and Remote Sensing Symposium (InGARSS), 2020, pp. 50-53, doi: 10.1109/InGARSS48198.2020.9358935.  

Chen H, Zhu G, Zhang K, Bi J, Jia X, Ding B, Zhang Y, Shang S, Zhao N, Qin W. Evaluation of Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017. Remote Sensing. 2020; 12(15):2473.  

Fisher, J. B. et al. ECOSTRESS: NASA’s next generation mission to measure evapotranspiration from the international space station. Water Resour. Res. 56, 50. https://doi.org/10.1029/2019wr026058, 2020.  

Li S, Zhang L, Ma R, Yan M, & Tian X., Improved ET assimilation through incorporating SMAP soil moisture observations using a coupled process model: A study of US arid and semiarid regions. Journal of Hydrology, 854 590, 125402, 2020.  

Marshall, M., Tu, K. & Andreo, V. On parameterizing soil evaporation in a direct remote sensing model of ET: PT-JPL. Water Resour. Res. 56, 160. https://doi.org/10.1029/2019WR026290, 2020.  

Niu, Z., He, H., Zhu, G. et al. A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981–2015. Sci. Data, 7, 369, 2020. https://doi.org/10.1038/s41597-020-00693-x  

Wu G, X Cai, F. K Trevor, S Li, X Luo, J B Fisher, R Cao, et al., Evaluating Three Evapotranspiration Estimates from Model of Different Complexity over China Using the ILAMB Benchmarking System. Journal of Hydrology 590, 2020. doi:https://doi.org/10.1016/j.jhydrol.2020.125553  

Xue B, Wang G, Xiao J, Tan Q, Shrestha S, Sun W, Liu T, Global evapotranspiration hiatus explained by vegetation structural and physiological controls. Ecological Engineering, 158, 106046, 2020. https://doi.org/10.1016/j.ecoleng.2020.106046.  

Zhang J, Y Bai, H Yan, H Guo, S Yang, J Wang, Linking observation, modelling and satellite-based estimation of global land evapotranspiration, Big Earth Data, 4:2, 94-127, 2020. DOI: 10.1080/20964471.2020.1743612  

Zhang B, Y Xia, B Long, M Hobbins, X Zhao, C Hain, Y Li, and M Anderson, Evaluation and comparison of multiple evapotranspiration data models over the contiguous United States: Implications for the next phase of NLDAS (NLDAS-Testbed) development, Agricultural and Forest Meteorology 280, 2020, 107810. doi: 10.1016/j.agrformet.2019.107810  

Zhuang Q, H Wang, Y Xu, Comparison of Remote Sensing based Multi-Source ET Models over Cropland in a Semi-Humid Region of China, Atmosphere, 11(4):325, 2020. DOI: 10.3390/atmos11040325  

2019  

Cooley, S.S., Williams, C.A, Fisher, J.B., Halverson, G.H, Perret, J., Lee, C.M., Assessing regional drought impacts on vegetation and evapotranspiration: a case study in Guanacaste, Costa Rica. Ecological Applications 29(2): 1-21, 2019.  

Dzikiti, S., Jovanovic, N.Z., Bugan, R.D. et al. Comparison of two remote sensing models for estimating evapotranspiration: algorithm evaluation and application in seasonally arid ecosystems in South Africa. J. Arid Land 11, 495–512 (2019).  

Gomis-Cebolla, J., Jimenez, J. C., Sobrino, J. A., Corbari, C., & Mancini, M, Intercomparison of remote-sensing based evapotranspiration algorithms over amazonian forests. International Journal of Applied Earth Observation and Geoinformation, 80, 280–294, 2019.  

Hao, Y., Baik, J., Choi, M., Developing a soil water index-based Priestley–Taylor algorithm for estimating evapotranspiration over East Asia and Australia. Agric. For. Meteorol. 279, 107760, 2019.  

McCabe, M.F., Miralles, D.G., Holmes, T.R.H., Fisher, J.B., Advances in the remote sensing of terrestrial evaporation. Remote Sensing 11(9): 1-8, 2019.  

Niu, Z. et al., An increasing trend in the ratio of transpiration to total terrestrial evapotranspiration in China from 1982 to 2015 caused by greening and warming. Agric. For. Meteorol. 279, 107701, 2019.  

Shao, R., et al., Estimating the increase in regional evaporative water consumption as a result of vegetation restoration over the Loess Plateau, China. J. Geophys. Res.: Atmos. 124 (22), 11783–11802, 2019.  

Stoy, P., El-Madany, T., Fisher, J.B., Gentine, P., Gerken, T., Good, S., Liu, S., Miralles, D., Perez-Priego, O., Skaggs, T., Wohlfahrt, G., Anderson, R., Jung, M., Maes, W., Mammarella, I., Mauder, M., Migliavacca, M., Nelson, J., Poyatos, R., Reichstein, M., Scott, R., Wolf, S., Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities. Biogeosciences 16(19): 3747-3775, 2019.  

Yao, Y., et al., Evaluation of a satellite-derived model parameterized by three soil moisture constraints to estimate terrestrial latent heat flux in the Heihe River basin of Northwest China. Sci. Total Environ. 695, 133787, 2019.  

2018  

Aragon B, R Houborg, K Tu, JB Fisher, M McCabe, CubeSats Enable High Spatiotemporal Retrievals of Crop-Water Use for Precision Agriculture, Remote Sensing, 10 (10): 1867, 2018.  

Chang Y, Qin D, Ding Y, Zhao Q, Zhang S, A modified MOD16 algorithm to estimate evapotranspiration over alpine meadow on the Tibetan Plateau, China, Journal of Hydrology, 561:16-30, 2018.  

Gu C, Ma J, Zhu G, Yang H, Zhang K, Wang Y, Gu C, Partitioning evapotranspiration using an optimized satellite-based ET model across biomes, Ag. For. Met., 259: 355-363, 2018.  

Hajji, I., D. F. Nadeau, B. Music, F. Anctil, and J. Wang (2018): Application of the maximum entropy production model of evapotranspiration over partially vegetated water-limited land surfaces. Journal of Hydrometeorology 19: 989-1005.  

Jiménez, C., Martens, B., Gonzalez Miralles, D., Fisher, J. B., Beck, H. E., & Fernández-Prieto, D., Exploring the merging of the global land evaporation WACMOS-ET products based on local tower measurements. Hydrology and Earth System Sciences, 22(8), 4513–4533, 2018.  

Lu C, Zhao T, Shi X, Cao S, Ecological restoration by afforestation may increase groundwater depth and create potentially large ecological and water opportunity costs in arid and semiarid China, Journal of Cleaner Production, 176:1213-1222, 2018.  

Moyano, M., et al., Vegetation water use based on a thermal and optical remote sensing model in the mediterranean region of donana. Remote Sens. 10 (7), 1105, 2018.  

Purdy AJ, JB Fisher, ML Goulden, A Colliander, G Halverson, K Tu, JS Famiglietti, SMAP soil moisture improves global evapotranspiration, Remote Sensing of Environment, 219: 1-14, 2018.  

Singh, A., Behrangi, A., Fisher, J.B., Reager, J.T., 2018. On the desiccation of the South Aral Sea observed from spaceborne missions. Remote Sensing 10(793): doi:10.3390/rs10050793.  

Talsma, C. J., Good, S. P., Jimenez, C., Martens, B., Fisher, J. B., Miralles, D. G., McCabe, M. F., & Purdy, A. J., Partitioning of evapotranspiration in remote sensing-based models. Agricultural and Forest Meteorology, 260, 131–143, 2018.  

Wang S, Ibrom A, Bauer-Gottwein P, Garcia M, Incorporating diffuse radiation into a light use efficiency and evapotranspiration model - An 11-year study in a high latitude deciduous forest, Agricultural and Forest Meteorology, 248:479-493, 2018.  

Yao Y, Liang S, Cao B, Liu S, Yu G, Jia K, Zhang X, Zhang Y, Chen J, Fisher JB (2018). Satellite detection of water stress effects on terrestrial latent heat flux with MODIS shortwave infrared reflectance data. Journal of Geophysical Research: Atmospheres, 123. https://doi.org/10.1029/2018JD029011  

2017  

Feng F, Li X, Yao Y, Liu M, Long-term spatial distributions and trends of the latent heat fluxes over the global cropland ecosystem using multiple satellite-based models. PLoS ONE, 12(8): e0183771, 2017.  

Fisher JB, F Melton, E Middleton, C Hain, M Anderson, R Allen, MF McCabe, S Hook, D Baldocchi, PA Townsend, A Kilic, K Tu, DD Miralles, J Perret, J-P Lagouarde, D Waliser, AJ Purdy, A French, D Schimel, JS Famiglietti, G Stephens, EF Wood. (2017), The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources, Water Resources Research, 53, 2618–2626, doi:10.1002/2016WR020175.  

Li Y, CHuanga, J Houa, J Gud, G Zhud, X Li. 2017. Mapping daily evapotranspiration based on spatiotemporal fusion of ASTER and MODIS images over irrigated agricultural areas in the Heihe River Basin, Northwest China, Agricultural and Forest Meteorology, 244-245:82-97.  

McCabe MF, Aragon B, Houborg R, Mascaro J, CubeSats in hydrology: Ultrahigh-resolution insights into vegetation dynamics and terrestrial evaporation. Water Resources Research, 53, 10,017–10,024. https://doi.org/10.1002/2017WR022240, 2017.  

Wang S, A Ibrom, K Pilegaard, P Bauer-Gottwein, and M Garcia, Effects of diffuse radiation on carbon and water fluxes of a high latitude temperate deciduous forest, Geophysical Research Abstracts, Vol. 19, EGU2017-12865-2, 2017.  Webster E, Ramp D, Kingsford R, Incorporating an iterative energy restraint for the Surface Energy Balance System (SEBS), Remote Sensing of Environment, 198:267-285, 2017.  

Yao, Y., Liang, S., Li, X., Chen, J., Liu, S., Jia, K., Zhang, X., Xiao, Z., Fisher, J.B., Mu, Q., Pan, M., Liu, M., Cheng, J., Jiang, B., Xie, X., Grünwald, T., Bernhofer, C., Roupsard, O., 2017. Improving global terrestrial evapotranspiration estimation using support vector machine by merging three process-based algorithms. Agricultural and Forest Meteorology, 242: 55-74.  

Yao Y, S Liang, Xianglan Li, Y Zhang, J Chen, K Jia, X Zhang, JB Fisher, X Wang, L Zhang, J Xu, C Shao, G Posse, Y Li, V Magliulo, A Varlagin, EJ Moors, J Boike, C Macfarlane, T Kato, N Buchmann, DP Billesbach, J Beringer, S Wolf, SA Papuga, G Wohlfahrt, L Montagnani, J Ardö, E Paul-Limoges, C Emmel, L Hörtnagl, T Sachs, C Gruening, B Gioli, A López-Ballesteros, R Steinbrecher, B Gielen, Estimation of high-resolution terrestrial evapotranspiration from Landsat data using a simple Taylor skill fusion method, Journal of Hydrology, 553: 508-526, 2017.  

Yao Y, S Liang, J Yu, J Chen, S Liu, Y Lin, JB Fisher, TR McVicar, J Cheng, KJia, X Zhang, X Xie, B Jiang, L Sun, A simple temperature domain two-source model for estimating agricultural field surface energy fluxes from Landsat images, Journal of Geophysical Research - Atmospheres, 122, 5211-5236, doi:10.1002/2016JD026370, 2017.  

Yao Y, S Liang, J Yu, J, Zhao S, Lin Y, Jia K, Zhang X, Cheng J, Xie X, Sun L, Wang X, Zhang L, Differences in estimating terrestrial water flux from three satellite-based Priestley-Taylor algorithms, International Journal of Applied Earth Observation and Geoinformation, 56:1–12, 2017.  

Zhang, K., et al., Parameter sensitivity analysis and optimization for a satellite based evapotranspiration model across multiple sites using moderate resolution imaging spectroradiometer and flux data. J. Geophys. Res.: Atmos. 122 (1), 230–245, 2017a.  

Zhang, L., et al., Satellite-derived spatiotemporal variations in evapotranspiration over Northeast China during 1982–2010. Remote Sens. 9 (11), 1140, 2017b.  

2016  

Feng F, Li X, Yao Y, Liang S, Chen J, Zhao X, et al. (2016) An Empirical Orthogonal Function Based Algorithm for Estimating Terrestrial Latent Heat Flux from Eddy Covariance, Meteorological and Satellite Observations. PLoS ONE 11(7): e0160150. doi:10.1371/journal.pone.0160150  

Gao, Y., Gan, G., Liu, M., Wang, J. (2016) Evaluating soil evaporation parameterizations at near-instantaneous scales using surface dryness indices, Journal of Hydrology, 541, pp. 1199-1211.  

McCabe, M. F., Ershadi, A., Jimenez, C., Miralles, D. G., , and Wood, E. F. 2016. The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally-gridded forcing data, Geoscientific Model Development, 9, 283–305.  

Michel D., C. Jiménez, D. M. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto, The WACMOS-ET project – Part 1: Tower-scale performance of four observation-based evapotranspiration algorithms, Hydrology and Earth System Sciences, 20, 803-822, doi:10.5194/hess-20-803-2016, doi:10.5194/hess-20-823-2016, 2016.  

Miralles D. G, C. Jiménez, M. Jung, D. Miche, A. Ershadi, M. F. McCabe, M. Hirschi, A. J. Dolman, J. B. Fisher, B. Martens, Q. Mu, S. I. Seneviratne, U. Weber, E. F. Wood and D.Fernández-Prieto, The WACMOS-ET project – Part 2: Evaluation of global land evaporation data sets, Hydrology and Earth System Sciences, 20, 823-842, 2016.  

Yang, Z., Zhang, Q., Yang, Y., Hao, X., and Zhang, H., Evaluation of evapotranspiration models over semi-arid and semi-humid areas of China. Hydrological Processes, 30: 4292–4313. doi: 10.1002/hyp.10824, 2016.  

Zhang K, Kimbal JS and Running SW. A review of remote sensing based actual evapotranspiration estimation, WIREs Water 3:834–853. doi: 10.1002/wat2.1168, 2016.  

Zhang, K., J. Ma, G. Zhu, T. Ma, T. Han, and L. L. Feng (2016), Parameter sensitivity analysis and optimization for a satellite-based evapotranspiration model across multiple sites using Moderate Resolution Imaging Spectroradiometer and flux data, J. Geophys. Res. Atmos., 122, doi:10.1002/2016JD025768.  

Zhu, G., Li, X., Zhang, K., Ding, Z., Han, T., Ma, J., Huang, C., He, J., and Ma, T., Multi-model ensemble prediction of terrestrial evapotranspiration across north China using Bayesian model averaging. Hydrological Processes, 30: 2861–2879. doi: 10.1002/hyp.10832, 2016.  

2015  

Badgley, G., Fisher, J.B., Jiménez, C., Tu, K.P., Vinukollu, R., 2015. On uncertainty in global terrestrial evapotranspiration estimates from choice of input forcing datasets. Journal of Hydrometeorology 16(4): 1449-1455.  

Cao S and Zhang J, Political risks arising from the impacts of large-scale afforestation on water resources of the Tibetan Plateau, Gondwana Research, 28(2):898-903, 2015.  

Feng F, J Chen, X Li, Y Yao, S Liang, M Liu, N Zhang, Y Guo, J Yu and M Sun. 2015. Validity of five satellite-based latent heat flux algorithms for semi-arid ecosystems, Remote Sensing, 7, 16733–16755; doi:10.3390/rs71215853.  

Mao, J., Fu, W., Shi, X., Ricciuto, D., Fisher, J.B., Dickinson, R., Wei, Y., Shem, W., Piao, S., Wang, K., Schwalm, C., Tian, H., Mu, M., Arain, A., Ciais, P., Cook, R., Dai, Y., Hayes, D., Hoffman, F., Huang, M., Huang, S., Huntzinger, D., Ito, A., Jain, A., King, A., Lei, H., Lu, C., Michalak, A., Parazoo, N., Peng, C., Peng, S., Poulter, B., Schaefer, K., Jafarov, E., Thornton, P., Wang, W., Zeng, N., Zhenzhong, Z., Fang, Z., Zhu, Q., Zhu, Z., 2015. Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends. Environmental Research Letters 10: 094008.  

Parr, D.; Wang, G.; Bjerklie, D.; Parr, D.; Wang, G.; Bjerklie, D. Integrating Remote Sensing Data on Evapotranspiration and Leaf Area Index with Hydrological Modeling: Impacts on Model Performance and Future Predictions. J. Hydrometeorol. 2015, 16, 2086–2100.  

Yao, Yunjun; Shunlin Liang, Xianglan Li, Jiquan Chen, Kaicun Wang, Kun Jia, Jie Cheng, Bo Jiang, Joshua B. Fisher, Qiaozhen Mu, Thomas Grünwald, Christian Bernhofer, Olivier Roupsard. A satellite-based hybrid algorithm to determine the Priestley–Taylor parameter for global terrestrial latent heat flux estimation across multiple biomes, Remote Sensing of Environment. 165 (2015) 216–233.  

Zhuang, Q. and Wu, B. (2015). Estimating Evapotranspiration from an Improved Two-Source Energy Balance Model Using ASTER Satellite Imagery. Water 7:6673–6688; doi:10.3390/w7126653.  

2014  

Armanios, D., Fisher, J.B., 2014. Measuring water availability with limited ground data: An entirely remote sensing-based hydrologic budget model of the Rufiji Basin, Tanzania using TRMM, GRACE, MODIS, SRB and AIRS. Hydrological Processes, 28(3): 853-867.  

Behrangi, A., Wong, S., Mallick, K., Fisher, J.B., 2014. On the net surface water exchange rate estimated from remote sensing observation and reanalysis. International Journal of Remote Sensing, 35(6): 2170-2185.  

Chen, Y., Xia, J., Liang, S., Feng, J., Fisher, J.B., Li, X., Li, X., Liu, S., Ma, Z., Miyata, A., Mu, Q., Sun, L., Tang, J., Wang, K., Wen, J., Xue, Y., Yu, G., Zha, T., Zhang, L., Zhang, Q., Zhao, T., Zhao, L., Zhou, G., Yuan, W., 2014. Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China. Remote Sensing of Environment, 140: 279-293.  

Christoffersen, B.O., Restrepo-Coupe, N., Arain, M.A., Baker, I.T., Cestaro, B.P., Ciais, P., Fisher, J.B., et al., 2014. Mechanisms of water supply and vegetation demand govern the seasonality and magnitude of evapotranspiration in Amazonia and Cerrado. Agricultural and Forest Meteorology, 191: 33-50.  

Clark, K.E., Torres, M.A., West, A.J., Hilton, R.G., New, M., Horwath, A.B., Fisher, J.B., Rapp, J.M., Robles Caceres, A., Malhi, Y., 2014. The hydrological regime of a forested tropical Andean valley. Hydrology and Earth System Sciences, 18: 5377-5397.  

Ershadi, A., McCabe, M., Evans, J., Chaney, N., & Wood, E. (2014). Multi-site evaluation of terrestrial evaporation models using FLUXNET data. Agricultural and Forest Meteorology, 187,46–61.  

Marshall MT, Funk C, Michaelsen J., 2014. Agricultural Drought Monitoring in Kenya Using Evapotranspiration Derived from Remote Sensing and Reanalysis Data, in Remote Sensing of Drought: Innovative Monitoring Approaches, Taylor and Francis, Editors: M. Anderson, J.Verdin, pp.270.  

Morillas L, Villagarcía L, Domingo F, Nieto H, Uclés O, M Garcia. 2014. Environmental factors affecting the accuracy of surface fluxes from a two-source model in Mediterranean drylands: Upscaling instantaneous to daytime estimates Agricultural and Forest Meteorology, 189: 140-158.  

Yao, Y., Liang, S., Li, X., Hong, Y., Fisher, J.B., Zhang, N., Chen, J., Cheng, J., Zhao, S., Zhang, X., Jiang, B., Sun, L., Jia, K., Wang, K., Chen, Y., Mu, Q., Feng, F., 2014. Bayesian multimodel estimation of global terrestrial latent heat flux from eddy covariance, meteorological, and satellite observations. Journal of Geophysical Research, 119(8): 4521-4545.  

Yao Y, S Liang, S Zhao, Y Zhang, Q Qin, J Cheng, K Jia, X Xie, N Zhang and M Liu. 2014. Validation and application of the modified satellite-based Priestley-Taylor algorithm for mapping terrestrial evapotranspiration. Remote Sensing, 6, 880-904; doi:10.3390/rs6010880.  

2013  

Garcia M, Sandholt I, Ceccato P, Ridler M, Mougin E, Kergoat L, Morillas L, Timouk F, Fensholt R, Domingo F. 2013. Actual evapotranspiration in drylands derived from in-situ and satellite data-assessing biophysical constraints. Remote Sensing of Environment, 131: 103-118.  

Guzinski R., M. C. Anderson, W. P. Kustas, H. Nieto1, and I. Sandholt, Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day–night MODIS observations, Hydrol. Earth Syst. Sci., 17, 2809–2825, 2013.  

Mallick, K., Jarvis, A.J, Boegh, E., Fisher, J.B., Drewry, D.T., Tu, K.P., Hook, S.J., Hulley, G., Ardö, J., Beringer, J., Arain, A., Niyogi, D., 2013. A Surface Temperature Initiated Closure (STIC) for surface energy balance fluxes. Remote Sensing of Environment 141: 243-261.  

Mallick K, Jarvis A, Fisher JB, Tu KP, Boegh E, Niyogi D. 2013. Latent heat flux and canopy conductance based on Penman-Monteith, Priestley-Taylor equation and Bouchet’s complementary hypothesis: validation over multiple biomes. Journal of Hydrometeorology.  

McCabe, M., Miralles, D., Jimenez, C., Ershadi, A., Fisher, J., Mu, Z., Liang, M., Mueller, B., Sheffield, J., Seneviratne, S., Wood, E., 2013. Global-scale estimation of land surface heat fluxes from space: product assessment and intercomparison. In: Remote Sensing of Energy Fluxes and Soil Moisture Content, Ed. Petropoulos, G.P. CRC Press, Taylor & Francis Group. 538 pp.  

Marshall, M., K. Tu, C. Funk, J. Michaelsen, P. Williams, C. Williams, J. Ardö, B. Marie, B. Cappelaere, A. Grandcourt, A. Nickless, Y. Nouvellon, R. Scholes, and W. Kutsch. 2013. Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach. Hydrology and Earth System Sciences,  17, 1079-1091, doi:10.5194/hess-17-1079-2013.  

Mueller, B., Hirschi, M., Jimenez, C., Ciais, P., Dirmeyer, P.A., Dolman, A.J., Fisher, J.B., Jung, M., Ludwig, F., Maignan, F., Miralles, D.G., McCabe, M.F., Reichstein, M., Sheffield, J., Wang, K., Wood, E.F., Zhang, Y., Seneviratne, S.I., 2013. Benchmark products for land evapotranspiration: LandFlux-EVAL multi-dataset synthesis. Hydrology and Earth System Sciences 17: 3707-3720.  

Polhamus A, Fisher JB, Tu KP. 2013. What controls the error structure in evapotranspiration models? Agriculture and Forest Meteorology, 169: 12-24.  

Yao Y, Liang S, Chenga J, Liu S, Fisher JB, Zhang X, Jia K, Zhao X, Qing Q, Zhaoh B, Hani S,  Zhouj G, Zhouk G, Li Y, Zhao S. 2013. MODIS-driven estimation of terrestrial latent heat flux in China based on a modified Priestley–Taylor algorithm. Agriculture and Forest Meteorology, 171-172: 187-202.  

2012  

Boroon, M.H.R., Fisher, J.B., 2012. Linking groundwater quality and quantity: an assessment of satellite-based groundwater storage anomalies from GRACE against ground measurements of contaminants in California. Journal of Environmental Science and Engineering B 1: 1271-1284.  

Fisher, J. B., G. Badgley, and E. Blyth (2012), Global nutrient limitation in terrestrial vegetation, Global Biogeochemical Cycles, 26, GB3007, doi:10.1029/2011GB004252.  

Moore, S., Fisher, J.B., 2012. Challenges and opportunities in GRACE-based groundwater storage assessment and management: an example from Yemen. Water Resources Management 26: 1425-1453.  

2011  

Fisher, J.B., Whittaker, R., Malhi, Y., 2011. ET Come Home: Potential evapotranspiration in geographical ecology. Global Ecology and Biogeography 20: 1-18.  

Mueller, B., Seneviratne, S.I., Jiménez, C., Corti, T., Hirschi, M., Balsamo, G., Ciais, P., Dirmeyer, P., Fisher, J.B., Guo, Z., Jung, M., Maignan, F., McCabe, M.F., Reichle, R., Reichstein, M., Rodell, M., Sheffield, J., Teuling, A.J., Wang, K., Wood, E.F., Zhang, Y., 2011. Evaluation of global observations-based evapotranspiration datasets and IPCC AR4 simulations. Geophysical Research Letters 38: L06402, doi:10.1029/2010GL046230.  

Jiménez, C., Prigent, C., Mueller, B., Seneviratne, S.I., McCabe, M.F., Wood, E.F., Rossow, W.B., Balsamo, G., Betts, A.K., Dirmeyer, P.A., Fisher, J.B., Jung, M., Kanamitsu, M., Reichle, R.H., Reichstein, M., Rodell, M., Sheffield, J., Tu, K., Wang, K., 2011. Global intercomparison of 12 land surface heat flux estimates. Journal of Geophysical Research 116: D02102, doi:10.1029/2010JD014545.  

Vinukollu, R.K., Meynadier, R., Sheffield, J., & Wood, E. F. (2011). Multi-model, multisensor estimates of global evapotranspiration: Climatology, uncertainties and trends. Hydrological Processes, 25,3993–4010.  

Vinukollu, R.K., Wood, E.F., Ferguson, C.R., Fisher, J.B., 2011. Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches. Remote Sensing of Environment 115: 801-823.  

Zelazowski, P., Malhi, Y., Huntingford, C., Sitch, S., Fisher, J.B., 2011. Changes in the potential distribution of humid tropical forests on a warmer planet. Philosophical Transactions of the Royal Society A - Mathematical, Physical & Engineering Sciences 369: 137-160.  

2010  

Glenn EP, Nagler PL, Huete AR. 2010. Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing, Surv Geophys, 31:531–555.  

Chen, Y., J. T. Randerson, G. van der Werf, D. Morton, M. Mu, P. Kasibhatla. 2010. Nitrogen deposition in tropical forests from savanna and deforestation fires, Global Change Biology, 16(7): 2024-2038.  

2009  

Phillips, O.L., Aragão, L., Lewis, S.L., Fisher, J.B., et al., 2009. Drought sensitivity of the Amazon rainforest. Science, 323(5919): 1344-1347.  

Fisher, J.B., Malhi, Y., de Araújo, A.C., Bonal, D., Gamo, M., Goulden, M.L., Hirano, T., Huete, A.R., Kondo, H., Kumagai, T., Loescher, H., Miller, S., Nobre, A.D., Nouvellon, Y., Oberbauer, S.F., Panuthai, S., von Randow, C., da Rocha, H.R., Roupsard, O., Saleska, S., Tanaka, K., Tanaka, N., Tu, K.P., 2009.  The land-atmosphere water flux in the tropics. Global Change Biology 15: 2694-2714.  

2008  

Leuning R., Y. Q. Zhang, A. Rajaud, H. Cleugh, K. Tu (2008), A simple surface conductance model to estimate regional evaporation using MODIS leaf area index and the Penman-Monteith equation, Water Resour. Res., 44, W10419, doi:10.1029/2007WR006562. (pdf) (correction)  

Fisher JB and Tu KP, Baldocchi DD. 2008. Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites. Remote Sensing of Environment 112(3): 909-919. (pdf)  

2004    

Tu KP and Fisher JB. 2004. Remote sensing of plant transpiration and soil evaporation using MODIS data, MODIS Vegetation Workshop II, Missoula, Montana.     

ABSTRACTS & REPORTS  

2020  

Tu K, Parry C, Zhang R, Patel R, Reyes A, Rotundo J, Messina CD. 2020. Validation of High Resolution Satellite ET Using Canopy Temperature Measurements at Sub-Field Scales, ASA, CSSA and SSSA International Annual Meeting, Virtual.  

2017  

Aragon B, R Houborg, KP Tu, J Fisher, M McCabe. 2017. Evaporation Using Planet Cubesats and the PT-JPL Model: A Precision Agriculture Application, AGU Fall Meeting, New Orleans, Louisiana, USA.  

2016  

Fisher JB, Middleton E, Melton F, Anderson M, Hook S, Hain C, Allen R, McCabe M, Lagouarde J-P, Tu K, Baldocchi D, Townsend PA, Kilic A, Perret J, Miralles D, Waliser D, French A, Famiglietti J, Schimel D. 2016. Evapotranspiration: A critical variable linking ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources. NASA Decadal Survey. US National Academy of Sciences.  

Marshall, M.T., Tu, K.P., Thenkabail, P.S. and Brown, J.F. (2016). Recent decline in crop water productivity in the United States: a call to grow “more crop per drop”, American Geophysical Union, Fall Meeting, San Francisco, California, USA.  

Marshall, M.T. and Tu, K.P. (2016). Simulating macro-scale crop yield using an optimized light-use efficiency model, American Geophysical Union, Fall Meeting, San Francisco, California, USA.Geophysical Union, Fall Meeting, San Francisco, California, USA  

2015  

Marshall M and Tu K, 2015. Light- and water-use efficiency model synergy: a revised look at crop yield estimation for agricultural decision-making, American Geophysical Union, Fall Meeting, San Francisco, California, USA  

Moyano C, M Garcia, L Tornos, L Recuero, A Palacios-Orueta, and L de Juana, 2015, Assessing regional crop water demand using a satellite-based combination equation with a land surface temperature component, Geophysical Research Abstracts, Vol. 17, EGU2015-15503-1.  

2014  

Verma, M.; Fisher, J. B.; Mallick, K.; Ryu, Y.; Tu, K. P.; Kobayashi, H.; Guillaume, A.; Moore, G.; Ramakrishnan, L.; Hendrix, V. 2014. Evaluating ET and Its Components from the CMIP5 Models with New, Global Remote Sensing-Based Estimates, American Geophysical Union, Fall Meeting, San Francisco, California, USA. 

2013  

Garcia, M, Q Mu, P Ceccato, J Ardö, E Mougin, Lt Kergoat, F Timouk, I Sandholt, and J Fisher, Satellite-based drought monitoring in the Sahel: Evaluation of two global physically-based evapotranspiration algorithms, Geophysical Research Abstracts, Vol. 15, EGU2013-13379-1, 2013. 

2010  

Marshall MT, Tu K, Funk C, Michaelsen J., 2010. A Historical Record of Actual Evapotranspiration in Sub-Saharan Africa using Climate Reanalysis and Remote Sensing Data, 24th Conference on Hydrology, American Meteorological Society.   

2009  

Fisher, J.B., Armanios, D., Tu, K.P., 2009. Global evapotranspiration from remote sensing driven by SRB, AIRS and MODIS, validated at 36 FLUXNET sites, American Geophysical Union, Fall Meeting, San Francisco, California, USA.  

Fisher, J.B., Tu, K., Armanios, D., 2009. Global evapotranspiration from remote sensing. Joint 6th International GEWEX and 2nd iLEAPS Science Conference; iLEAPS ECSW Meeting; LandFlux Meeting. Melbourne, Australia.  

Marshall, M. T.; Funk, C.; Tu, K. P.; Michaelsen, J. 2009. Combining Remote Sensing and Climate Reanalysis Data to Estimate Evapotranspiration in sub-Saharan Africa, American Geophysical Union, Fall Meeting, San Francisco, California, USA. 

2008  

Tu KP. 2008. Using Optimality Principles to Predict Spatio-Temporal Patterns of Vegetation-Atmosphere Fluxes at Leaf to Global Scales, American Geophysical Union, Fall Meeting, San Francisco, California, USA.  

Tu KP, Knohl A, Mambelli S, Ma S, Baldocchi D, Dawson T. 2008. Observations and scaling of water use efficiency from leaf to globe. Geophysical Research Abstracts, Vol. 10, EGU2008-A-07012.

2007   

Fisher, J.B., Malhi, Y., de Araújo, A.C., Bonal, D., da Rocha, H.R., Goulden, M.L., Hirano, T., Kumagai, T., Loescher, H., Miller, S.,Nobre, A.D., Oberbauer, S., Saleska, S., von Randow, C., Tu, K.P., 2007. The tropical land-atmosphere water flux: Measurements, models and controls for evapotranspiration in the Amazon. LBA-ECO 11th Science Team Meeting, Salvador, Bahia, Brazil.  

Tu KP, Knohl A, Mambelli S, Ma S, Baldocchi D, DawsonT (2007), Global remote sensing of water use efficiency: Initial test and application of a synergistic approach. Eos Trans. AGU, 88(52), Fall Meet. Suppl., Abstract B33D-1597.  

Fisher, JB, Tu KP (2007), Global trends in potential and actual evapotranspiration based on 20 years of satellite observations. Eos Trans. AGU, 88(52), Fall Meet. Suppl., Abstract H34D-08. 

2006  

Tu KP and Fisher JB. 2006. Remote sensing of the land-atmosphere water flux: Global validation using FLUXNET data.Proceedings of the 1st iLEAPS Science Conference, Boulder, Colorado,USA.   

Tu KP, Massman WJ and Ham JM. 2006. Partitioning ET between plant and soil components using surface temperature and fractional vegetation cover. AmeriFlux Annual Meeting, Boulder, Colorado, US. 

2005  

Fisher JB and Tu KP. 2005. New global estimates of the land-atmosphere water flux: A fully remote sensing driven, flux site-validated ecophysiological model of evapotranspiration, 9th International Symposium on Physical Measurements and Signatures in Remote Sensing (ISPMSRS), Beijing, China, October.  

Tu KP. 2005. Towards global estimates of the d18O-evapotranspiration flux: Implications of non-steady state isotopic enrichment of leaf water, presented at the BASIN Workshop, San Francisco, CA, USA.  

Wood EF, MF McCabe, H Su, K Tu, (2005) Globally Distributed Evapotranspiration using Remote Sensing and CEOP Data. CEOP Phase 1 Achievements -- Presentations at CEOP/IGWCO Joint Meeting, Tokyo. 

2004  

Fisher, J.B., 2004. Estimation of Evapotranspiration Across Multiple Scales: Sap Flow, Flux Measurement, Remote Sensing, and Sociology.  NASA Earth System Science Network Symposium, Washington, D.C., USA.  

Fisher, J.B., Tu, KP., 2004.  Validation of MODIS-Derived Parameters with FLUXNET Measurements: Surface Temperature, AirTemperature, Fraction of Photosynthetically Absorbed Radiation, and Albedo. MODIS Vegetation Workshop II, Missoula, Montana, USA.  

Su H, Wood EF, McCabe M and Tu KP, (2004), Model intercomparison of evapotranspiration estimation based on CEOP dataset, Eos Trans. AGU, 85(47), Fall Meet. Suppl., Abstract H13C-0440.   

Tu KP and Fisher JB. 2004. Remote sensing of plant transpiration and soil evaporation using MODIS data, MODIS Vegetation Workshop II, Missoula, Montana.