Articles | Volume 22, issue 2
https://doi.org/10.5194/hess-22-1317-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-22-1317-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
21 Feb 2018
Research article |
| 21 Feb 2018
Derived Optimal Linear Combination Evapotranspiration (DOLCE): a global gridded synthesis ET estimate
Sanaa Hobeichi
CORRESPONDING AUTHOR
Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, NSW 2052, Australia
Gab Abramowitz
Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
ARC Centre of Excellence for Climate Extremes, University of New South Wales, Sydney, NSW 2052, Australia
Jason Evans
Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
ARC Centre of Excellence for Climate Extremes, University of New South Wales, Sydney, NSW 2052, Australia
Anna Ukkola
Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, NSW 2052, Australia
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Hoori Ajami, Ashish Sharma, Lawrence E. Band, Jason P. Evans, Narendra K. Tuteja, Gnanathikkam E. Amirthanathan, and Mohammed A. Bari
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Hydrol. Earth Syst. Sci., 20, 2403–2419, https://doi.org/10.5194/hess-20-2403-2016, https://doi.org/10.5194/hess-20-2403-2016, 2016
J. Kala, M. G. De Kauwe, A. J. Pitman, R. Lorenz, B. E. Medlyn, Y.-P Wang, Y.-S Lin, and G. Abramowitz
Geosci. Model Dev., 8, 3877–3889, https://doi.org/10.5194/gmd-8-3877-2015, https://doi.org/10.5194/gmd-8-3877-2015, 2015
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Hydrol. Earth Syst. Sci., 19, 3433–3447, https://doi.org/10.5194/hess-19-3433-2015, https://doi.org/10.5194/hess-19-3433-2015, 2015
M. G. De Kauwe, J. Kala, Y.-S. Lin, A. J. Pitman, B. E. Medlyn, R. A. Duursma, G. Abramowitz, Y.-P. Wang, and D. G. Miralles
Geosci. Model Dev., 8, 431–452, https://doi.org/10.5194/gmd-8-431-2015, https://doi.org/10.5194/gmd-8-431-2015, 2015
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J. Teng, N. J. Potter, F. H. S. Chiew, L. Zhang, B. Wang, J. Vaze, and J. P. Evans
Hydrol. Earth Syst. Sci., 19, 711–728, https://doi.org/10.5194/hess-19-711-2015, https://doi.org/10.5194/hess-19-711-2015, 2015
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H. Ajami, J. P. Evans, M. F. McCabe, and S. Stisen
Hydrol. Earth Syst. Sci., 18, 5169–5179, https://doi.org/10.5194/hess-18-5169-2014, https://doi.org/10.5194/hess-18-5169-2014, 2014
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Pre-industrial soil organic carbon (SOC) stocks vary 6-fold in models used in the 5th IPCC Assessment Report. This paper shows that this range is largely determined by model-specific responses of microbal decomposition during the equilibration procedure. As SOC stocks are maintained through the present and to 2100 almost unchanged, we propose that current SOC observations could be used to constrain this equilibration procedure and thereby reduce the uncertainty in climate change projections.
J. Kala, J. P. Evans, A. J. Pitman, C. B. Schaaf, M. Decker, C. Carouge, D. Mocko, and Q. Sun
Geosci. Model Dev., 7, 2121–2140, https://doi.org/10.5194/gmd-7-2121-2014, https://doi.org/10.5194/gmd-7-2121-2014, 2014
J. P. Evans, F. Ji, C. Lee, P. Smith, D. Argüeso, and L. Fita
Geosci. Model Dev., 7, 621–629, https://doi.org/10.5194/gmd-7-621-2014, https://doi.org/10.5194/gmd-7-621-2014, 2014
J.-F. Exbrayat, A. J. Pitman, Q. Zhang, G. Abramowitz, and Y.-P. Wang
Biogeosciences, 10, 7095–7108, https://doi.org/10.5194/bg-10-7095-2013, https://doi.org/10.5194/bg-10-7095-2013, 2013
D. Argüeso, J. P. Evans, and L. Fita
Hydrol. Earth Syst. Sci., 17, 4379–4388, https://doi.org/10.5194/hess-17-4379-2013, https://doi.org/10.5194/hess-17-4379-2013, 2013
A. M. Ukkola and I. C. Prentice
Hydrol. Earth Syst. Sci., 17, 4177–4187, https://doi.org/10.5194/hess-17-4177-2013, https://doi.org/10.5194/hess-17-4177-2013, 2013
Related subject area
Subject: Global hydrology | Techniques and Approaches: Mathematical applications
Projecting end-of-century climate extremes and their impacts on the hydrology of a representative California watershed
Integrating process-related information into an artificial neural network for root-zone soil moisture prediction
Coherence of global hydroclimate classification systems
Design flood estimation for global river networks based on machine learning models
Attributing correlation skill of dynamical GCM precipitation forecasts to statistical ENSO teleconnection using a set-theory-based approach
The spatial extent of hydrological and landscape changes across the mountains and prairies of Canada in the Mackenzie and Nelson River basins based on data from a warm-season time window
Averaging over spatiotemporal heterogeneity substantially biases evapotranspiration rates in a mechanistic large-scale land evaporation model
Rainfall Estimates on a Gridded Network (REGEN) – a global land-based gridded dataset of daily precipitation from 1950 to 2016
A framework for deriving drought indicators from the Gravity Recovery and Climate Experiment (GRACE)
Hydrological effects of climate variability and vegetation dynamics on annual fluvial water balance in global large river basins
Spatial patterns and characteristics of flood seasonality in Europe
Effects of different reference periods on drought index (SPEI) estimations from 1901 to 2014
The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis
Global trends in extreme precipitation: climate models versus observations
A global water cycle reanalysis (2003–2012) merging satellite gravimetry and altimetry observations with a hydrological multi-model ensemble
A generic method for hydrological drought identification across different climate regions
Simplifying a hydrological ensemble prediction system with a backward greedy selection of members – Part 1: Optimization criteria
Simplifying a hydrological ensemble prediction system with a backward greedy selection of members – Part 2: Generalization in time and space
Fadji Z. Maina, Alan Rhoades, Erica R. Siirila-Woodburn, and Peter-James Dennedy-Frank
Hydrol. Earth Syst. Sci., 26, 3589–3609, https://doi.org/10.5194/hess-26-3589-2022, https://doi.org/10.5194/hess-26-3589-2022, 2022
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In this work, we assess the effects of end-of-century extreme dry and wet conditions on the hydrology of California. Our results, derived from cutting-edge and high-resolution climate and hydrologic models, highlight that (1) water storage will be larger and increase earlier in the year, yet the summer streamflow will decrease as a result of high evapotranspiration rates, and that (2) groundwater and lower-order streams are very sensitive to decreases in snowmelt and higher evapotranspiration.
Roiya Souissi, Mehrez Zribi, Chiara Corbari, Marco Mancini, Sekhar Muddu, Sat Kumar Tomer, Deepti B. Upadhyaya, and Ahmad Al Bitar
Hydrol. Earth Syst. Sci., 26, 3263–3297, https://doi.org/10.5194/hess-26-3263-2022, https://doi.org/10.5194/hess-26-3263-2022, 2022
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In this study, we investigate the combination of surface soil moisture information with process-related features, namely, evaporation efficiency, soil water index and normalized difference vegetation index, using artificial neural networks to predict root-zone soil moisture. The joint use of process-related features yielded more accurate predictions in the case of arid and semiarid conditions. However, they have no to little added value in temperate to tropical conditions.
Kathryn L. McCurley Pisarello and James W. Jawitz
Hydrol. Earth Syst. Sci., 25, 6173–6183, https://doi.org/10.5194/hess-25-6173-2021, https://doi.org/10.5194/hess-25-6173-2021, 2021
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Climate classification systems divide the Earth into zones of similar climates. We compared the within-zone hydroclimate similarity and zone shape complexity of a suite of climate classification systems, including new ones formed in this study. The most frequently used system had high similarity but high complexity. We propose the Water-Energy Clustering framework, which also had high similarity but lower complexity. This new system is therefore proposed for future hydroclimate assessments.
Gang Zhao, Paul Bates, Jeffrey Neal, and Bo Pang
Hydrol. Earth Syst. Sci., 25, 5981–5999, https://doi.org/10.5194/hess-25-5981-2021, https://doi.org/10.5194/hess-25-5981-2021, 2021
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Design flood estimation is a fundamental task in hydrology. We propose a machine- learning-based approach to estimate design floods anywhere on the global river network. This approach shows considerable improvement over the index-flood-based method, and the average bias in estimation is less than 18 % for 10-, 20-, 50- and 100-year design floods. This approach is a valid method to estimate design floods globally, improving our prediction of flood hazard, especially in ungauged areas.
Tongtiegang Zhao, Haoling Chen, Quanxi Shao, Tongbi Tu, Yu Tian, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 25, 5717–5732, https://doi.org/10.5194/hess-25-5717-2021, https://doi.org/10.5194/hess-25-5717-2021, 2021
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This paper develops a novel approach to attributing correlation skill of dynamical GCM forecasts to statistical El Niño–Southern Oscillation (ENSO) teleconnection using the coefficient of determination. Three cases of attribution are effectively facilitated, which are significantly positive anomaly correlation attributable to positive ENSO teleconnection, attributable to negative ENSO teleconnection and not attributable to ENSO teleconnection.
Paul H. Whitfield, Philip D. A. Kraaijenbrink, Kevin R. Shook, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 25, 2513–2541, https://doi.org/10.5194/hess-25-2513-2021, https://doi.org/10.5194/hess-25-2513-2021, 2021
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Using only warm season streamflow records, regime and change classifications were produced for ~ 400 watersheds in the Nelson and Mackenzie River basins, and trends in water storage and vegetation were detected from satellite imagery. Three areas show consistent changes: north of 60° (increased streamflow and basin greenness), in the western Boreal Plains (decreased streamflow and basin greenness), and across the Prairies (three different patterns of increased streamflow and basin wetness).
Elham Rouholahnejad Freund, Massimiliano Zappa, and James W. Kirchner
Hydrol. Earth Syst. Sci., 24, 5015–5025, https://doi.org/10.5194/hess-24-5015-2020, https://doi.org/10.5194/hess-24-5015-2020, 2020
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Evapotranspiration (ET) is the largest flux from the land to the atmosphere and thus contributes to Earth's energy and water balance. Due to its impact on atmospheric dynamics, ET is a key driver of droughts and heatwaves. In this paper, we demonstrate how averaging over land surface heterogeneity contributes to substantial overestimates of ET fluxes. We also demonstrate how one can correct for the effects of small-scale heterogeneity without explicitly representing it in land surface models.
Steefan Contractor, Markus G. Donat, Lisa V. Alexander, Markus Ziese, Anja Meyer-Christoffer, Udo Schneider, Elke Rustemeier, Andreas Becker, Imke Durre, and Russell S. Vose
Hydrol. Earth Syst. Sci., 24, 919–943, https://doi.org/10.5194/hess-24-919-2020, https://doi.org/10.5194/hess-24-919-2020, 2020
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This paper provides the documentation of the REGEN dataset, a global land-based daily observational precipitation dataset from 1950 to 2016 at a gridded resolution of 1° × 1°. REGEN is currently the longest-running global dataset of daily precipitation and is expected to facilitate studies looking at changes and variability in several aspects of daily precipitation distributions, extremes and measures of hydrological intensity.
Helena Gerdener, Olga Engels, and Jürgen Kusche
Hydrol. Earth Syst. Sci., 24, 227–248, https://doi.org/10.5194/hess-24-227-2020, https://doi.org/10.5194/hess-24-227-2020, 2020
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GRACE-derived drought indicators enable us to detect hydrological droughts based on changes observed in all storages. By performing synthetic experiments, we find that droughts identified by existing and modified indicators are biased by trends and GRACE-based spatial noise. A modified version of the Zhao et al. (2017) indicator is found to be particularly robust against spatial noise and is therefore applied to real GRACE data over South Africa.
Jianyu Liu, Qiang Zhang, Vijay P. Singh, Changqing Song, Yongqiang Zhang, Peng Sun, and Xihui Gu
Hydrol. Earth Syst. Sci., 22, 4047–4060, https://doi.org/10.5194/hess-22-4047-2018, https://doi.org/10.5194/hess-22-4047-2018, 2018
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Considering effective precipitation (Pe), the Budyko framework was extended to the annual water balance analysis. To reflect the mismatch between water supply (precipitation, P) and energy (potential evapotranspiration,
E0), a climate seasonality and asynchrony index (SAI) were proposed in terms of both phase and amplitude mismatch between P and E0.
Julia Hall and Günter Blöschl
Hydrol. Earth Syst. Sci., 22, 3883–3901, https://doi.org/10.5194/hess-22-3883-2018, https://doi.org/10.5194/hess-22-3883-2018, 2018
Myoung-Jin Um, Yeonjoo Kim, Daeryong Park, and Jeongbin Kim
Hydrol. Earth Syst. Sci., 21, 4989–5007, https://doi.org/10.5194/hess-21-4989-2017, https://doi.org/10.5194/hess-21-4989-2017, 2017
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This study aims to understand how different reference periods (i.e., calibration periods) of climate data for estimating the drought index influence regional drought assessments. Specifically, we investigate the influence of different reference periods on historical drought characteristics such as trends, frequency, intensity and spatial extents using the Standard Precipitation Evapotranspiration Index (SPEI) estimated from the two widely used global datasets.
Lorenzo Mentaschi, Michalis Vousdoukas, Evangelos Voukouvalas, Ludovica Sartini, Luc Feyen, Giovanni Besio, and Lorenzo Alfieri
Hydrol. Earth Syst. Sci., 20, 3527–3547, https://doi.org/10.5194/hess-20-3527-2016, https://doi.org/10.5194/hess-20-3527-2016, 2016
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The climate is subject to variations which must be considered
studying the intensity and frequency of extreme events.
We introduce in this paper a new methodology
for the study of variable extremes, which consists in detecting
the pattern of variability of a time series, and applying these patterns
to the analysis of the extreme events.
This technique comes with advantages with respect to the previous ones
in terms of accuracy, simplicity, and robustness.
B. Asadieh and N. Y. Krakauer
Hydrol. Earth Syst. Sci., 19, 877–891, https://doi.org/10.5194/hess-19-877-2015, https://doi.org/10.5194/hess-19-877-2015, 2015
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We present a systematic comparison of changes in historical extreme precipitation in station observations (HadEX2) and 15 climate models from the CMIP5 (as the largest and most recent sets of available observational and modeled data sets), on global and continental scales for 1901-2010, using both parametric (linear regression) and non-parametric (the Mann-Kendall as well as Sen’s slope estimator) methods, taking care to sample observations and models spatially and temporally in comparable ways.
A. I. J. M. van Dijk, L. J. Renzullo, Y. Wada, and P. Tregoning
Hydrol. Earth Syst. Sci., 18, 2955–2973, https://doi.org/10.5194/hess-18-2955-2014, https://doi.org/10.5194/hess-18-2955-2014, 2014
M. H. J. van Huijgevoort, P. Hazenberg, H. A. J. van Lanen, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 16, 2437–2451, https://doi.org/10.5194/hess-16-2437-2012, https://doi.org/10.5194/hess-16-2437-2012, 2012
D. Brochero, F. Anctil, and C. Gagné
Hydrol. Earth Syst. Sci., 15, 3307–3325, https://doi.org/10.5194/hess-15-3307-2011, https://doi.org/10.5194/hess-15-3307-2011, 2011
D. Brochero, F. Anctil, and C. Gagné
Hydrol. Earth Syst. Sci., 15, 3327–3341, https://doi.org/10.5194/hess-15-3327-2011, https://doi.org/10.5194/hess-15-3327-2011, 2011
Cited articles
Abramowitz, G.: Towards a benchmark for land surface models, Geophys. Res.
Lett., 32, L22702, https://doi.org/10.1029/2005GL024419, 2005.
Abramowitz, G.: Towards a public, standardized, diagnostic benchmarking
system for land surface models, Geosci. Model Dev., 5, 819–827,
https://doi.org/10.5194/gmd-5-819-2012, 2012.
Abramowitz, G. and Bishop, C. H.: Climate model dependence and the ensemble
dependence transformation of CMIP projections, J. Climate, 28, 2332–2348,
https://doi.org/10.1175/JCLI-D-14-00364.1, 2015.
Alemohammad, S. H., Fang, B., Konings, A. G., Aires, F., Green, J. K.,
Kolassa, J., Miralles, D., Prigent, C., and Gentine, P.: Water, Energy, and
Carbon with Artificial Neural Networks (WECANN): a statistically based
estimate of global surface turbulent fluxes and gross primary productivity
using solar-induced fluorescence, Biogeosciences, 14, 4101–4124,
https://doi.org/10.5194/bg-14-4101-2017, 2017.
Annan, J. D. and Hargreaves, J. C.: Reliability of the CMIP3 ensemble,
Geophys. Res. Lett., 37, L02703, https://doi.org/10.1029/2009GL041994, 2010.
Badgley, G., Fisher, J. B., Jiménez, C., Tu, K. P., and Vinukollu, R.: On
uncertainty in global terrestrial evapotranspiration estimates from choice of
input forcing datasets, J. Hydrometeorol., 16, 1449–1455,
https://doi.org/10.1175/JHM-D-14-0040.1, 2015.
Baldocchi, D.: “Breathing” of the terrestrial biosphere: lessons learned
from a global network of carbon dioxide flux measurement systems, Aust. J.
Bot., 56, 1, https://doi.org/10.1071/BT07151, 2008.
Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S.,
Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein, A.,
Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, W., Oechel, W.,
Paw, K. T., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S.,
Vesala, T., Wilson, K., and Wofsy, S.:
FLUXNET: a new tool to study the temporal and spatial variability of
ecosystem–scale carbon dioxide, water vapor, and energy flux densities, B.
Am. Meteorol. Soc., 82, 2415–2434,
https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2,
2001.
Best, M. J., Abramowitz, G., Johnson, H. R., Pitman, A. J., Balsamo, G.,
Boone, A., Cuntz, M., Decharme, B., Dirmeyer, P. A., Dong, J., Ek, M.,
Guo, Z., Haverd, V., van den Hurk, B. J. J., Nearing, G. S., Pak, B.,
Peters-Lidard, C., Santanello Jr., J. A., Stevens, L., and
Vuichard, N.: The plumbing of land surface
models: benchmarking model performance, J. Hydrometeorol., 16, 1425–1442,
https://doi.org/10.1175/JHM-D-14-0158.1, 2015.
Bishop, C. H. and Abramowitz, G.: Climate model dependence and the replicate
Earth paradigm, Clim. Dynam., 41, 885–900, https://doi.org/10.1007/s00382-012-1610-y,
2013.
Bowen, I. S.: The ratio of heat losses by conduction and by evaporation from
any water surface, Phys. Rev., 27, 779–787, https://doi.org/10.1103/PhysRev.27.779,
1926.
Brutsaert, W. and Stricker, H.: An advection-aridity approach to estimate
actual regional evapotranspiration, Water Resour. Res., 15, 443–450,
https://doi.org/10.1029/WR015i002p00443, 1979.
Burba, G. and Anderson, D.: A Brief Practical Guide to Eddy Covariance Flux
Measurements: Principles and Workflow Examples for Scientific and Industrial
Applications, LI-COR Biosciences, Lincoln, Nebraska, USA, 2010.
Chen, T. H., Henderson-Sellers, A., Milly, P. C. D., Pitman, A. J.,
Beljaars, A. C. M., Polcher, J., Abramopoulos, F., Boone, A., Chang, S.,
Chen, F., Dai, Y., Desborough, C. E., Dickinson, R. E., Dümenil, L.,
Ek, M., Garratt, J. R., Gedney, N., Gusev, Y. M., Kim, J., Koster, R.,
Kowalczyk, E. A., Laval, K., Lean, J., Lettenmaier, D., Liang, X.,
Mahfouf, J.-F., Mengelkamp, H.-T., Mitchell, K., Nasonova, O. N.,
Noilhan, J., Robock, A., Rosenzweig, C., Schaake, J., Schlosser, C. A.,
Schulz, J.-P., Shao, Y., Shmakin, A. B., Verseghy, D. L., Wetzel, P.,
Wood, E. F., Xue, Y., Yang, Z.-L., and Zeng, Q.: Cabauw experimental results from the project for intercomparison of
land-surface parameterization schemes, J. Climate, 10, 1194–1215,
https://doi.org/10.1175/1520-0442(1997)010<1194:CERFTP>2.0.CO;2,
1997.
Cheng, Y., Sayde, C., Li, Q., Basara, J., Selker, J., Tanner, E., and
Gentine, P.: Failure of Taylor's hypothesis in the atmospheric surface layer
and its correction for eddy-covariance measurements, Geophys. Res. Lett., 44,
4287–4295, https://doi.org/10.1002/2017GL073499, 2017.
Dirmeyer, P. A., Wu, J., Norton, H. E., Dorigo, W. A., Quiring, S. M.,
Ford, T. W., Santanello, J. A., Bosilovich, M. G., Ek, M. B., Koster, R. D.,
Balsamo, G., and Lawrence, D. M.: Confronting weather and climate models with
observational data from soil moisture networks over the United States,
J. Hydrometeorol., 17, 1049–1067, https://doi.org/10.1175/JHM-D-15-0196.1, 2016.
Ershadi, A., McCabe, M. F., Evans, J. P., Chaney, N. W., and Wood, E. F.:
Multi-site evaluation of terrestrial evaporation models using FLUXNET data,
Agr. Forest Meteorol., 187, 46–61, https://doi.org/10.1016/j.agrformet.2013.11.008,
2014.
Fisher, J. B., Tu, K. P., and Baldocchi, D. D.: Global estimates of the
land–atmosphere water flux based on monthly AVHRR and ISLSCP-II data,
validated at 16 FLUXNET sites, Remote Sens. Environ., 112, 901–919,
https://doi.org/10.1016/j.rse.2007.06.025, 2008.
FluxData: FLUXNET 2015 Dataset, available at:
https://fluxnet.fluxdata.org, last access: 21 December 2016.
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N.,
Sibley, A., and Huang, X.: MODIS Collection 5 global land cover: algorithm
refinements and characterization of new datasets, Remote Sens. Environ., 114,
168–182, https://doi.org/10.1016/j.rse.2009.08.016, 2010.
Göckede, M., Foken, T., Aubinet, M., Aurela, M., Banza, J., Bernhofer,
C., Bonnefond, J. M., Brunet, Y., Carrara, A., Clement, R., Dellwik, E.,
Elbers, J., Eugster, W., Fuhrer, J., Granier, A., Grünwald, T., Heinesch,
B., Janssens, I. A., Knohl, A., Koeble, R., Laurila, T., Longdoz, B., Manca,
G., Marek, M., Markkanen, T., Mateus, J., Matteucci, G., Mauder, M.,
Migliavacca, M., Minerbi, S., Moncrieff, J., Montagnani, L., Moors, E.,
Ourcival, J.-M., Papale, D., Pereira, J., Pilegaard, K., Pita, G., Rambal,
S., Rebmann, C., Rodrigues, A., Rotenberg, E., Sanz, M. J., Sedlak, P.,
Seufert, G., Siebicke, L., Soussana, J. F., Valentini, R., Vesala, T.,
Verbeeck, H., and Yakir, D.: Quality control of CarboEurope flux data – Part
1: Coupling footprint analyses with flux data quality assessment to evaluate
sites in forest ecosystems, Biogeosciences, 5, 433–450,
https://doi.org/10.5194/bg-5-433-2008, 2008.
Haughton, N., Abramowitz, G., Pitman, A. J., Or, D., Best, M. J.,
Johnson, H. R., Balsamo, G., Boone, A., Cuntz, M., Decharme, B.,
Dirmeyer, P. A., Dong, J., Ek, M., Guo, Z., Haverd, V., van den
Hurk, B. J. J., Nearing, G. S., Pak, B., Santanello, J. A.,
Stevens Jr., L. E., and Vuichard, N.: The
plumbing of land surface models: is poor performance a result of methodology
or data quality?, J. Hydrometeorol., 17, 1705–1723,
https://doi.org/10.1175/JHM-D-15-0171.1, 2016.
Hobeichi, S., Abramowitz, G., Evans, J., and Ukkola, A.: Derived Optimal
Linear Combination Evapotranspiration v 1.0, NCI Catalogue,
https://doi.org/10.4225/41/58980b55b0495, 2017.
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., and Wang, K.: Global intercomparison of
12 land surface heat flux estimates, J. Geophys. Res.-Atmos., 116, D02102,
https://doi.org/10.1029/2010JD014545, 2011.
Jung, M., Reichstein, M., Margolis, H. A., Cescatti, A., Richardson, A. D.,
Arain, M. A., Arneth, A., Bernhofer, C., Bonal, D., Chen, J., Gianelle, D.,
Gobron, N., Kiely, G., Kutsch, W., Lasslop, G., Law, B. E., Lindroth, A.,
Merbold, L., Montagnani, L., Moors, E. J., Papale, D., Sottocornola, M.,
Vaccari, F., and Williams, C.: Global patterns of land–atmosphere fluxes of
carbon dioxide, latent heat, and sensible heat derived from eddy covariance,
satellite, and meteorological observations, J. Geophys. Res., 116, G00J07,
https://doi.org/10.1029/2010JG001566, 2011.
Loew, A., Peng, J., and Borsche, M.: High-resolution land surface fluxes from
satellite and reanalysis data (HOLAPS v1.0): evaluation and uncertainty
assessment, Geosci. Model Dev., 9, 2499–2532, https://doi.org/10.5194/gmd-9-2499-2016,
2016.
Martens, B., Miralles, D., Lievens, H., Van Der Schalie, R., De Jeu, R.,
Fernández-Prieto, D., and Verhoest, N.: GLEAM v3: updated land
evaporation and root-zone soil moisture datasets, Geophys. Res. Abstr. EGU
Gen. Assem., 18, 2016–4253,
2016.
McCabe, M. F., Ershadi, A., Jimenez, C., Miralles, D. G., Michel, D., and
Wood, E. F.: The GEWEX LandFlux project: evaluation of model evaporation
using tower-based and globally gridded forcing data, Geosci. Model Dev., 9,
283–305, https://doi.org/10.5194/gmd-9-283-2016, 2016.
Michel, D., Jiménez, C., Miralles, D. G., Jung, M., Hirschi, M., Ershadi,
A., Martens, B., McCabe, M. F., Fisher, J. B., Mu, Q., Seneviratne, S. I.,
Wood, E. F., and Fernández-Prieto, D.: The WACMOS-ET project – Part 1:
Tower-scale evaluation of four remote-sensing-based evapotranspiration
algorithms, Hydrol. Earth Syst. Sci., 20, 803–822,
https://doi.org/10.5194/hess-20-803-2016, 2016.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters,
A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated
from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469,
https://doi.org/10.5194/hess-15-453-2011, 2011.
Monteith, J. L.: Evaporation and envrionment, Symp. Soc. Exp.
Biol., 19, 205–223, 1965.
Mu, Q., Heinsch, F. A., Zhao, M., and Running, S. W.: Development of a global
evapotranspiration algorithm based on MODIS and global meteorology data,
Remote Sens. Environ., 111, 519–536, https://doi.org/10.1016/j.rse.2007.04.015, 2007.
Mu, Q., Zhao, M., and Running, S. W.: Improvements to a MODIS global
terrestrial evapotranspiration algorithm, Remote Sens. Environ., 115,
1781–1800, https://doi.org/10.1016/j.rse.2011.02.019, 2011.
Mueller, B., Seneviratne, S. I., Jimenez, 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., and Zhang, Y.:
Evaluation of global observations-based evapotranspiration datasets and IPCC
AR4 simulations, Geophys. Res. Lett., 38, L06402, https://doi.org/10.1029/2010GL046230,
2011.
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., and Seneviratne, S. I.: Benchmark products for land evapotranspiration:
LandFlux-EVAL multi-data set synthesis, Hydrol. Earth Syst. Sci., 17,
3707–3720, https://doi.org/10.5194/hess-17-3707-2013, 2013.
Papale, D., Agarwal, D. A., Baldocchi, D., Cook, R. B., Fisher, J. B., and
van Ingen, C.: Database maintenance, data sharing policy, collaboration, in:
Eddy Covariance, Springer Netherlands, Dordrecht, 399–424, 2012.
Richardson, A. D., Hollinger, D. Y., Burba, G. G., Davis, K. J.,
Flanagan, L. B., Katul, G. G., Munger, J. W., Ricciuto, D. M., Stoy, P. C.,
Suyker, A. E., Verma, S. B., and Wofsy, S. C.: A multi-site analysis of
random error in tower-based measurements of carbon and energy fluxes, Agr.
Forest Meteorol., 136, 1–18, https://doi.org/10.1016/j.agrformet.2006.01.007, 2006.
Stöckli, R., Lawrence, D. M., Niu, G.-Y., Oleson, K. W., Thornton, P. E.,
Yang, Z.-L., Bonan, G. B., Denning, A. S., and Running, S. W.: Use of FLUXNET
in the Community Land Model development, J. Geophys. Res.-Biogeo., 113,
G01025, https://doi.org/10.1029/2007JG000562, 2008.
Su, Z.: The Surface Energy Balance System (SEBS) for estimation of turbulent
heat fluxes, Hydrol. Earth Syst. Sci., 6, 85–100,
https://doi.org/10.5194/hess-6-85-2002, 2002.
Sumner, D. M. and Jacobs, J. M.: Utility of Penman–Monteith,
Priestley–Taylor, reference evapotranspiration, and pan evaporation methods
to estimate pasture evapotranspiration, J. Hydrol., 308, 81–104,
https://doi.org/10.1016/j.jhydrol.2004.10.023, 2005.
Twine, T. E., Kustas, W. P., Norman, J. M., Cook, D. R., Houser, P. R.,
Meyers, T. P., Prueger, J. H., Starks, P. J., and Wesley, M. L.: Correcting
eddy-covariance flux underestimates over a grassland, Agr. Forest Meteorol.,
103, 279–300, 2000.
Vinukollu, R. K., Wood, E. F., Ferguson, C. R., and Fisher, J. B.: Global
estimates of evapotranspiration for climate studies using multi-sensor remote
sensing data: evaluation of three process-based approaches, Remote Sens.
Environ., 115, 801–823, https://doi.org/10.1016/j.rse.2010.11.006, 2011.
Wang, K. and Dickinson, R. E.: A review of global terrestrial
evapotranspiration: Observation, modeling, climatology, and climatic
variability, Rev Geophys, 50, RG2005, https://doi.org/10.1029/2011RG000373, 2012.
Wang, Y. P., Baldocchi, D., Leuning, R., Falge, E., and Vesala, T.:
Estimating parameters in a land-surface model by applying nonlinear inversion
to eddy covariance flux measurements from eight FLUXNET sites, Glob. Change
Biol., 13, 652–670, https://doi.org/10.1111/j.1365-2486.2006.01225.x, 2007.
Zeller, K. and Hehn, T.: Measurements of upward turbulent ozone fluxes above
a subalpine spruce-fir forest, Geophys. Res. Lett., 23, 841–844,
https://doi.org/10.1029/96GL00786, 1996.
Zhang, K., Kimball, J. S., Nemani, R. R., and Running, S. W.: A continuous
satellite-derived global record of land surface evapotranspiration from 1983
to 2006, Water Resour. Res., 46, W09522, https://doi.org/10.1029/2009WR008800, 2010.
Zhang, K., Kimball, J. S., and Running, S. W.: A review of remote sensing
based actual evapotranspiration estimation, Wiley Interdiscip. Rev. Water, 3,
834–853, https://doi.org/10.1002/wat2.1168, 2016.
Zhang, Y., Leuning, R., Hutley, L. B., Beringer, J., McHugh, I., and
Walker, J. P.: Using long-term water balances to parameterize surface
conductances and calculate evaporation at 0.05∘ spatial resolution,
Water Resour. Res., 46, W05512, https://doi.org/10.1029/2009WR008716, 2010.
Zhang, Y., Peña-Arancibia, J. L., Mcvicar, T. R., Chiew, F. H. S.,
Vaze, J., Liu, C., Lu, X., Zheng, H., Wang, Y., Liu, Y. Y., Miralles, D. G.,
and Pan, M.: Multi-decadal trends in global terrestrial evapotranspiration
and its components, Nat. Publ. Gr., 6, 19124, https://doi.org/10.1038/srep19124, 2015.
Short summary
We present a new global ET dataset and associated uncertainty with monthly temporal resolution for 2000–2009 and 0.5 grid cell size. Six existing gridded ET products are combined using a weighting approach trained by observational datasets from 159 FLUXNET sites. We confirm that point-based estimates of flux towers provide information at the grid scale of these products. We also show that the weighted product performs better than 10 different existing global ET datasets in a range of metrics.
We present a new global ET dataset and associated uncertainty with monthly temporal resolution...
