Articles | Volume 9, issue 1
https://doi.org/10.5194/gmd-9-283-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-283-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Methods for assessment of models
| 
26 Jan 2016
Methods for assessment of models |
| 26 Jan 2016
The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally gridded forcing data
Division of Biological and Environmental Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
A. Ershadi
Division of Biological and Environmental Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
C. Jimenez
Estellus, Paris, France
D. G. Miralles
Department of Earth Sciences, VU University Amsterdam, Amsterdam, the Netherlands
D. Michel
Institute for Atmospheric and Climate Sciences, ETH Zurich, Zurich, Switzerland
E. F. Wood
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
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Preprint archived
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Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
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Jian Peng, Simon Dadson, Feyera Hirpa, Ellen Dyer, Thomas Lees, Diego G. Miralles, Sergio M. Vicente-Serrano, and Chris Funk
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Christopher Krich, Jakob Runge, Diego G. Miralles, Mirco Migliavacca, Oscar Perez-Priego, Tarek El-Madany, Arnaud Carrara, and Miguel D. Mahecha
Biogeosciences, 17, 1033–1061, https://doi.org/10.5194/bg-17-1033-2020, https://doi.org/10.5194/bg-17-1033-2020, 2020
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We focus on the net exchange of water between land and air via evapotranspiration and dew during the night. We provide, for the first time, an overview of the magnitude and variability of this flux across the globe from observations and climate models. Nocturnal water loss from land is 7 % of total evapotranspiration on average and can be greater than 15 % locally. Our results highlight the relevance of this often overlooked flux, with implications for water resources and climate studies.
Colby K. Fisher, Ming Pan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 24, 293–305, https://doi.org/10.5194/hess-24-293-2020, https://doi.org/10.5194/hess-24-293-2020, 2020
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Poorly monitored river flows in many regions of the world have been hindering our ability to accurately estimate global water usage. In this paper we present a method to derive continuous records of streamflow from a set of in situ gauges. Applying this method to the Ohio River basin, we found that we could reliably generate estimates of streamflow throughout the basin using only a small set of streamflow gauges, which can be useful for global river basins where we do not have good observations.
Jeroen Claessen, Annalisa Molini, Brecht Martens, Matteo Detto, Matthias Demuzere, and Diego G. Miralles
Biogeosciences, 16, 4851–4874, https://doi.org/10.5194/bg-16-4851-2019, https://doi.org/10.5194/bg-16-4851-2019, 2019
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Bidirectional interactions between vegetation and climate are unraveled over short (monthly) and long (inter-annual) temporal scales. Analyses use a novel causal inference method based on wavelet theory. The performance of climate models at representing these interactions is benchmarked against satellite data. Climate models can reproduce the overall climate controls on vegetation at all temporal scales, while their performance at representing biophysical feedbacks on climate is less adequate.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
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Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
K. Johansen, M. J. L. Morton, Y. Malbeteau, B. Aragon, S. Al-Mashharawi, M. Ziliani, Y. Angel, G. Fiene, S. Negrao, M. A. A. Mousa, M. A. Tester, and M. F. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 407–411, https://doi.org/10.5194/isprs-archives-XLII-2-W13-407-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-407-2019, 2019
Hendrik Wouters, Irina Y. Petrova, Chiel C. van Heerwaarden, Jordi Vilà-Guerau de Arellano, Adriaan J. Teuling, Vicky Meulenberg, Joseph A. Santanello, and Diego G. Miralles
Geosci. Model Dev., 12, 2139–2153, https://doi.org/10.5194/gmd-12-2139-2019, https://doi.org/10.5194/gmd-12-2139-2019, 2019
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The free software CLASS4GL (http://class4gl.eu) is designed to investigate the dynamic atmospheric boundary layer (ABL) with weather balloons. It mines observational data from global radio soundings, satellite and reanalysis data from the last 40 years to constrain and initialize an ABL model and automizes multiple experiments in parallel. CLASS4GL aims at fostering a better understanding of land–atmosphere feedbacks and the drivers of extreme weather.
Samuel Favrichon, Catherine Prigent, Carlos Jimenez, and Filipe Aires
Atmos. Meas. Tech., 12, 1531–1543, https://doi.org/10.5194/amt-12-1531-2019, https://doi.org/10.5194/amt-12-1531-2019, 2019
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Land surface parameters (such as temperature) can be extracted from passive microwave satellite observations, with less cloud contamination than in the infrared. A cloud contamination index is proposed to detect cloud contamination for multiple frequency ranges (from 10 to 190 GHz), to be applicable to the successive generations of MW instruments. Even with a reduced number of low-frequency channels over land, the index reaches an accuracy of ≥ 70 % in detecting contaminated observations.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 23, 925–948, https://doi.org/10.5194/hess-23-925-2019, https://doi.org/10.5194/hess-23-925-2019, 2019
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Potential evaporation (Ep) is the amount of water an ecosystem would consume if it were not limited by water availability or other stress factors. In this study, we compared several methods to estimate Ep using a global dataset of 107 FLUXNET sites. A simple radiation-driven method calibrated per biome consistently outperformed more complex approaches and makes a suitable tool to investigate the impact of water use and demand, drought severity and biome productivity.
Hylke E. Beck, Ming Pan, Tirthankar Roy, Graham P. Weedon, Florian Pappenberger, Albert I. J. M. van Dijk, George J. Huffman, Robert F. Adler, and Eric F. Wood
Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, https://doi.org/10.5194/hess-23-207-2019, 2019
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We conducted a comprehensive evaluation of 26 precipitation datasets for the US using the Stage-IV gauge-radar dataset as a reference. The best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for reporting times. Our findings can be used as a guide to choose the most suitable precipitation dataset for a particular application.
Sara Sadri, Eric F. Wood, and Ming Pan
Hydrol. Earth Syst. Sci., 22, 6611–6626, https://doi.org/10.5194/hess-22-6611-2018, https://doi.org/10.5194/hess-22-6611-2018, 2018
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Of particular interest to NASA's SMAP-based agricultural applications is a monitoring product that assesses near-surface soil moisture in terms of probability percentiles for dry and wet conditions. However, the short SMAP record length poses a statistical challenge for the meaningful assessment of its indices. This study presents initial insights about using SMAP Level 3 and Level 4 for monitoring drought and pluvial regions with a first application over the contiguous United States (CONUS).
Christina Papagiannopoulou, Diego G. Miralles, Matthias Demuzere, Niko E. C. Verhoest, and Willem Waegeman
Geosci. Model Dev., 11, 4139–4153, https://doi.org/10.5194/gmd-11-4139-2018, https://doi.org/10.5194/gmd-11-4139-2018, 2018
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Common global land cover and climate classifications are based on vegetation–climatic characteristics derived from observational data, ignoring the interaction between the local climate and biome. Here, we model the interplay between vegetation and local climate by discovering spatial relationships among different locations. The resulting global
hydro-climatic biomescorrespond to regions of coherent climate–vegetation interactions that agree well with traditional global land cover maps.
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533, https://doi.org/10.5194/hess-22-4513-2018, https://doi.org/10.5194/hess-22-4513-2018, 2018
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Observing the amount of water evaporated in nature is not easy, and we need to combine accurate local measurements with estimates from satellites, more uncertain but covering larger areas. This is the main topic of our paper, in which local observations are compared with global land evaporation estimates, followed by a weighting of the global observations based on this comparison to attempt derive a more accurate evaporation product.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-682, https://doi.org/10.5194/hess-2017-682, 2018
Revised manuscript not accepted
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Potential evaporation is a key parameter in numerous models used for assessing water use and drought severity. Yet, multiple incompatible methods have been proposed, thus estimates of potential evaporation remain uncertain. Based on the largest available dataset of FLUXNET data, we identify the best method to calculate potential evaporation globally. A simple radiation-driven method calibrated per biome consistently performed best; more complex models did not perform as good.
Andreas Marx, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Niko Wanders, Matthias Zink, Eric F. Wood, Ming Pan, Justin Sheffield, and Luis Samaniego
Hydrol. Earth Syst. Sci., 22, 1017–1032, https://doi.org/10.5194/hess-22-1017-2018, https://doi.org/10.5194/hess-22-1017-2018, 2018
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Hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K). The multi-model ensemble results show that the change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean, while they increase in the Alpine and Northern regions. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. Adaptation should make use of change and uncertainty information.
Yu Zhang, Ming Pan, Justin Sheffield, Amanda L. Siemann, Colby K. Fisher, Miaoling Liang, Hylke E. Beck, Niko Wanders, Rosalyn F. MacCracken, Paul R. Houser, Tian Zhou, Dennis P. Lettenmaier, Rachel T. Pinker, Janice Bytheway, Christian D. Kummerow, and Eric F. Wood
Hydrol. Earth Syst. Sci., 22, 241–263, https://doi.org/10.5194/hess-22-241-2018, https://doi.org/10.5194/hess-22-241-2018, 2018
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A global data record for all four terrestrial water budget variables (precipitation, evapotranspiration, runoff, and total water storage change) at 0.5° resolution and monthly scale for the period of 1984–2010 is developed by optimally merging a series of remote sensing products, in situ measurements, land surface model outputs, and atmospheric reanalysis estimates and enforcing the mass balance of water. Initial validations show the data record is reliable for climate related analysis.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
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This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
Khan Zaib Jadoon, Muhammad Umer Altaf, Matthew Francis McCabe, Ibrahim Hoteit, Nisar Muhammad, Davood Moghadas, and Lutz Weihermüller
Hydrol. Earth Syst. Sci., 21, 5375–5383, https://doi.org/10.5194/hess-21-5375-2017, https://doi.org/10.5194/hess-21-5375-2017, 2017
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In this study electromagnetic induction (EMI) measurements were used to estimate soil salinity in an agriculture field irrigated with a drip irrigation system. Electromagnetic model parameters and uncertainty were estimated using adaptive Bayesian Markov chain Monte Carlo (MCMC). Application of the MCMC-based inversion to the synthetic and field measurements demonstrates that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil.
Seyed Hamed Alemohammad, Bin Fang, Alexandra G. Konings, Filipe Aires, Julia K. Green, Jana Kolassa, Diego Miralles, Catherine Prigent, and Pierre Gentine
Biogeosciences, 14, 4101–4124, https://doi.org/10.5194/bg-14-4101-2017, https://doi.org/10.5194/bg-14-4101-2017, 2017
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Water, Energy, and Carbon with Artificial Neural Networks (WECANN) is a statistically based estimate of global surface latent and sensible heat fluxes and gross primary productivity. The retrieval uses six remotely sensed observations as input, including the solar-induced fluorescence. WECANN provides estimates on a 1° × 1° geographic grid and on a monthly time scale and outperforms other global products in capturing the seasonality of the fluxes when compared to eddy covariance tower data.
D. Turner, A. Lucieer, M. McCabe, S. Parkes, and I. Clarke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 379–384, https://doi.org/10.5194/isprs-archives-XLII-2-W6-379-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-379-2017, 2017
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017, https://doi.org/10.5194/hess-21-3879-2017, 2017
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We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
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Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
Christina Papagiannopoulou, Diego G. Miralles, Stijn Decubber, Matthias Demuzere, Niko E. C. Verhoest, Wouter A. Dorigo, and Willem Waegeman
Geosci. Model Dev., 10, 1945–1960, https://doi.org/10.5194/gmd-10-1945-2017, https://doi.org/10.5194/gmd-10-1945-2017, 2017
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Global satellite observations provide a means to unravel the influence of climate on vegetation. Common statistical methods used to study the relationships between climate and vegetation are often too simplistic to capture the complexity of these relationships. Here, we present a novel causality framework that includes data fusion from various databases, time series decomposition, and machine learning techniques. Results highlight the highly non-linear nature of climate–vegetation interactions.
Martin Hirschi, Dominik Michel, Irene Lehner, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 21, 1809–1825, https://doi.org/10.5194/hess-21-1809-2017, https://doi.org/10.5194/hess-21-1809-2017, 2017
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We compare lysimeter and eddy covariance (EC) flux measurements of evapotranspiration at a research catchment in Switzerland. The measurements are compared on various timescales, and with respect to a 40-year long-term lysimeter time series. Overall, the lysimeter and EC measurements agree well, especially on the annual timescale. Furthermore, we identify that lack of reliable EC data during/after rainfall events significantly contributes to an underestimation of EC evapotranspiration.
Di Tian, Eric F. Wood, and Xing Yuan
Hydrol. Earth Syst. Sci., 21, 1477–1490, https://doi.org/10.5194/hess-21-1477-2017, https://doi.org/10.5194/hess-21-1477-2017, 2017
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This study evaluated dynamic climate model sub-seasonal forecasts for important precipitation and temperature indices over the contiguous United States. The presence of active Madden-Julian Oscillation (MJO) events improved weekly mean precipitation forecast skill over most regions. Sub-seasonal forecast indices calculated from the daily forecast showed higher skill than temporally downscaled forecasts, suggesting the usefulness of the daily forecast for sub-seasonal hydrological forecasting.
Stephen D. Parkes, Matthew F. McCabe, Alan D. Griffiths, Lixin Wang, Scott Chambers, Ali Ershadi, Alastair G. Williams, Josiah Strauss, and Adrian Element
Hydrol. Earth Syst. Sci., 21, 533–548, https://doi.org/10.5194/hess-21-533-2017, https://doi.org/10.5194/hess-21-533-2017, 2017
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Determining atmospheric moisture sources is required for understanding the water cycle. The role of land surface fluxes is a particular source of uncertainty for moisture budgets. Water vapour isotopes have the potential to improve constraints on moisture sources. In this work relationships between water vapour isotopes and land–atmosphere exchange are studied. Results show that land surface evaporative fluxes play a minor role in the daytime water and isotope budgets in semi-arid environments.
Jason P. Evans, Xianhong Meng, and Matthew F. McCabe
Hydrol. Earth Syst. Sci., 21, 409–422, https://doi.org/10.5194/hess-21-409-2017, https://doi.org/10.5194/hess-21-409-2017, 2017
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This work demonstrates that changes in surface albedo and vegetation, caused by the millennium drought in south-east Australia, affected the atmosphere in a way that decreased precipitation further. This land–surface feedback increased the severity of the drought by 10 %. This suggests that climate models need to simulate changes in surface characteristics (other than soil moisture) in response to a developing drought if they are to capture this kind of multi-year drought.
Oliver López, Rasmus Houborg, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 21, 323–343, https://doi.org/10.5194/hess-21-323-2017, https://doi.org/10.5194/hess-21-323-2017, 2017
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The study evaluated the spatial and temporal consistency of satellite-based hydrological products based on the water budget equation, including three global evaporation products. The products were spatially matched using spherical harmonics analysis. The results highlighted the difficulty in obtaining agreement between independent satellite products, even over regions with simple water budgets. However, imposing a time lag on water storage data improved results considerably.
Raghavendra B. Jana, Ali Ershadi, and Matthew F. McCabe
Hydrol. Earth Syst. Sci., 20, 3987–4004, https://doi.org/10.5194/hess-20-3987-2016, https://doi.org/10.5194/hess-20-3987-2016, 2016
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Interactions between soil moisture and terrestrial evaporation affect responses between land surface and the atmosphere across scales. We present an analysis of the link between soil moisture and evaporation estimates from three distinct models. The relationships were examined over nearly 2 years of observation data. Results show that while direct correlations of raw data were mostly not useful, the root-zone soil moisture and the modelled evaporation estimates reflect similar distributions.
D. G. Miralles, C. Jiménez, M. Jung, D. Michel, A. Ershadi, M. F. McCabe, M. Hirschi, B. Martens, A. J. Dolman, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, https://doi.org/10.5194/hess-20-823-2016, 2016
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The WACMOS-ET project aims to advance the development of land evaporation estimates on global and regional scales. Evaluation of current evaporation data sets on the global scale showed that they manifest large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into several components. Different models perform better under different conditions, highlighting the potential for considering biome- or climate-specific model ensembles.
D. Michel, C. Jiménez, D. G. 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
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
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In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
W. Zhan, M. Pan, N. Wanders, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 4275–4291, https://doi.org/10.5194/hess-19-4275-2015, https://doi.org/10.5194/hess-19-4275-2015, 2015
A. I. Stegehuis, R. Vautard, P. Ciais, A. J. Teuling, D. G. Miralles, and M. Wild
Geosci. Model Dev., 8, 2285–2298, https://doi.org/10.5194/gmd-8-2285-2015, https://doi.org/10.5194/gmd-8-2285-2015, 2015
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Many climate models have difficulties in properly reproducing climate extremes such as heat wave conditions. We use a regional climate model with different atmospheric physics schemes to simulate the heat wave events of 2003 in western Europe and 2010 in Russia. The five best-performing and diverse physics scheme combinations may be used in the future to perform heat wave analysis and to investigate the impact of climate change in summer in Europe.
N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015, https://doi.org/10.5194/hess-19-3239-2015, 2015
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Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.
V. S. Galligani, C. Prigent, E. Defer, C. Jimenez, P. Eriksson, J.-P. Pinty, and J.-P. Chaboureau
Atmos. Meas. Tech., 8, 1605–1616, https://doi.org/10.5194/amt-8-1605-2015, https://doi.org/10.5194/amt-8-1605-2015, 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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Stomatal conductance affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the CABLE land surface model (LSM). The new implementation resulted in a large reduction in the annual fluxes of transpiration across evergreen needleleaf, tundra and C4 grass regions. We conclude that optimisation theory can yield a tractable approach to predicting stomatal conductance in LSMs.
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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A new hybrid approach was developed to reduce the computational burden of the spin-up procedure by using a combination of model simulations and an empirical depth-to-water table function. Results illustrate that the hybrid approach reduced the spin-up period required for an integrated groundwater--surface water--land surface model (ParFlow.CLM) by up to 50%. The methodology is applicable to other coupled or integrated modeling frameworks when initialization from an equilibrium state is required.
K. Guan, S. P. Good, K. K. Caylor, H. Sato, E. F. Wood, and H. Li
Biogeosciences, 11, 6939–6954, https://doi.org/10.5194/bg-11-6939-2014, https://doi.org/10.5194/bg-11-6939-2014, 2014
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Climate change is expected to modify the way that rainfall arrives, namely the frequency and intensity of rainfall events and rainy season length. Yet, the quantification of the impact of these possible rainfall changes across large biomes is lacking. Our study fills this gap by developing a new modeling framework, applying it to continental Africa. We show that African ecosystems are highly sensitive to these rainfall variabilities, with esp. large sensitivity to changes in rainy season length.
B. P. Guillod, B. Orlowsky, D. Miralles, A. J. Teuling, P. D. Blanken, N. Buchmann, P. Ciais, M. Ek, K. L. Findell, P. Gentine, B. R. Lintner, R. L. Scott, B. Van den Hurk, and S. I. Seneviratne
Atmos. Chem. Phys., 14, 8343–8367, https://doi.org/10.5194/acp-14-8343-2014, https://doi.org/10.5194/acp-14-8343-2014, 2014
M. Pan and E. F. Wood
Hydrol. Earth Syst. Sci., 17, 4577–4588, https://doi.org/10.5194/hess-17-4577-2013, https://doi.org/10.5194/hess-17-4577-2013, 2013
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
S. Shukla, J. Sheffield, E. F. Wood, and D. P. Lettenmaier
Hydrol. Earth Syst. Sci., 17, 2781–2796, https://doi.org/10.5194/hess-17-2781-2013, https://doi.org/10.5194/hess-17-2781-2013, 2013
A. D. Griffiths, S. D. Parkes, S. D. Chambers, M. F. McCabe, and A. G. Williams
Atmos. Meas. Tech., 6, 207–218, https://doi.org/10.5194/amt-6-207-2013, https://doi.org/10.5194/amt-6-207-2013, 2013
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rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model
Development of inter-grid-cell lateral unsaturated and saturated flow model in the E3SM Land Model (v2.0)
pyESDv1.0.1: an open-source Python framework for empirical-statistical downscaling of climate information
Representing the impact of Rhizophora mangroves on flow in a hydrodynamic model (COAWST_rh v1.0): the importance of three-dimensional root system structures
Dynamically weighted ensemble of geoscientific models via automated machine-learning-based classification
Deep Dive into Global Hydrologic Simulations: Harnessing the Power of Deep Learning and Physics-informed Differentiable Models (δHBV-globe1.0-hydroDL)
Enhancing the representation of water management in global hydrological models
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
DynQual v1.0: a high-resolution global surface water quality model
Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model
Simulation of crop yield using the global hydrological model H08 (crp.v1)
How is a global sensitivity analysis of a catchment-scale, distributed pesticide transfer model performed? Application to the PESHMELBA model
iHydroSlide3D v1.0: an advanced hydrological–geotechnical model for hydrological simulation and three-dimensional landslide prediction
GEB v0.1: a large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model
Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation (within CAESAR-Lisflood version 1.9j-WS)
Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe
Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats
SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)
Customized deep learning for precipitation bias correction and downscaling
Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain
Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data
Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments
Prediction of algal blooms via data-driven machine learning models: an evaluation using data from a well-monitored mesotrophic lake
UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python
Basin-scale gyres and mesoscale eddies in large lakes: a novel procedure for their detection and characterization, assessed in Lake Geneva
SIMO v1.0: simplified model of the vertical temperature profile in a small, warm, monomictic lake
Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model
Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality
Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale
RavenR v2.1.4: an open-source R package to support flexible hydrologic modelling
Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest
Manuel F. Rios Gaona, Katerina Michaelides, and Michael Bliss Singer
Geosci. Model Dev., 17, 5387–5412, https://doi.org/10.5194/gmd-17-5387-2024, https://doi.org/10.5194/gmd-17-5387-2024, 2024
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STORM v.2 (short for STOchastic Rainfall Model version 2.0) is an open-source and user-friendly modelling framework for simulating rainfall fields over a basin. It also allows simulating the impact of plausible climate change either on the total seasonal rainfall or the storm’s maximum intensity.
Lukas Riedel, Thomas Röösli, Thomas Vogt, and David N. Bresch
Geosci. Model Dev., 17, 5291–5308, https://doi.org/10.5194/gmd-17-5291-2024, https://doi.org/10.5194/gmd-17-5291-2024, 2024
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River floods are among the most devastating natural hazards. We propose a flood model with a statistical approach based on openly available data. The model is integrated in a framework for estimating impacts of physical hazards. Although the model only agrees moderately with satellite-detected flood extents, we show that it can be used for forecasting the magnitude of flood events in terms of socio-economic impacts and for comparing these with past events.
Robin Schwemmle, Hannes Leistert, Andreas Steinbrich, and Markus Weiler
Geosci. Model Dev., 17, 5249–5262, https://doi.org/10.5194/gmd-17-5249-2024, https://doi.org/10.5194/gmd-17-5249-2024, 2024
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The new process-based hydrological toolbox model, RoGeR (https://roger.readthedocs.io/), can be used to estimate the components of the hydrological cycle and the related travel times of pollutants through parts of the hydrological cycle. These estimations may contribute to effective water resources management. This paper presents the toolbox concept and provides a simple example of providing estimations to water resources management.
Sarah Hanus, Lilian Schuster, Peter Burek, Fabien Maussion, Yoshihide Wada, and Daniel Viviroli
Geosci. Model Dev., 17, 5123–5144, https://doi.org/10.5194/gmd-17-5123-2024, https://doi.org/10.5194/gmd-17-5123-2024, 2024
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This study presents a coupling of the large-scale glacier model OGGM and the hydrological model CWatM. Projected future increase in discharge is less strong while future decrease in discharge is stronger when glacier runoff is explicitly included in the large-scale hydrological model. This is because glacier runoff is projected to decrease in nearly all basins. We conclude that an improved glacier representation can prevent underestimating future discharge changes in large river basins.
M. Graham Clark and Sean K. Carey
Geosci. Model Dev., 17, 4911–4922, https://doi.org/10.5194/gmd-17-4911-2024, https://doi.org/10.5194/gmd-17-4911-2024, 2024
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This paper provides validation of the Canadian Small Lakes Model (CSLM) for estimating evaporation rates from reservoirs and a refactoring of the original FORTRAN code into MATLAB and Python, which are now stored in GitHub repositories. Here we provide direct observations of the surface energy exchange obtained with an eddy covariance system to validate the CSLM. There was good agreement between observations and estimations except under specific atmospheric conditions when evaporation is low.
Thibault Hallouin, François Bourgin, Charles Perrin, Maria-Helena Ramos, and Vazken Andréassian
Geosci. Model Dev., 17, 4561–4578, https://doi.org/10.5194/gmd-17-4561-2024, https://doi.org/10.5194/gmd-17-4561-2024, 2024
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The evaluation of the quality of hydrological model outputs against streamflow observations is widespread in the hydrological literature. In order to improve on the reproducibility of published studies, a new evaluation tool dedicated to hydrological applications is presented. It is open source and usable in a variety of programming languages to make it as accessible as possible to the community. Thus, authors and readers alike can use the same tool to produce and reproduce the results.
Barnaby Dobson, Leyang Liu, and Ana Mijic
Geosci. Model Dev., 17, 4495–4513, https://doi.org/10.5194/gmd-17-4495-2024, https://doi.org/10.5194/gmd-17-4495-2024, 2024
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Water management is challenging when models don't capture the entire water cycle. We propose that using integrated models facilitates management and improves understanding. We introduce a software tool designed for this task. We discuss its foundation, how it simulates water system components and their interactions, and its customisation. We provide a flexible way to represent water systems, and we hope it will inspire more research and practical applications for sustainable water management.
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Geosci. Model Dev., 17, 3559–3578, https://doi.org/10.5194/gmd-17-3559-2024, https://doi.org/10.5194/gmd-17-3559-2024, 2024
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We have developed a new data assimilation framework by coupling an integrated hydrological model HydroGeoSphere with the data assimilation software PDAF. Compared to existing hydrological data assimilation systems, the advantage of our newly developed framework lies in its consideration of the physically based model; its large selection of different assimilation algorithms; and its modularity with respect to the combination of different types of observations, states and parameters.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev., 17, 3199–3234, https://doi.org/10.5194/gmd-17-3199-2024, https://doi.org/10.5194/gmd-17-3199-2024, 2024
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We present the wflow_sbm distributed hydrological model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast runtime, making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev., 17, 3137–3156, https://doi.org/10.5194/gmd-17-3137-2024, https://doi.org/10.5194/gmd-17-3137-2024, 2024
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The Reservoir Assessment Tool (RAT) merges satellite data with hydrological models, enabling robust estimation of reservoir parameters like inflow, outflow, surface area, and storage changes around the world. Version 3.0 of RAT lowers the barrier of entry for new users and achieves scalability and computational efficiency. RAT 3.0 also facilitates open-source development of functions for continuous improvement to mobilize and empower the global water management community.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, and Günther Grill
Geosci. Model Dev., 17, 2877–2899, https://doi.org/10.5194/gmd-17-2877-2024, https://doi.org/10.5194/gmd-17-2877-2024, 2024
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Treated and untreated wastewaters are sources of contaminants of emerging concern. HydroFATE, a new global model, estimates their concentrations in surface waters, identifying streams that are most at risk and guiding monitoring/mitigation efforts to safeguard aquatic ecosystems and human health. Model predictions were validated against field measurements of the antibiotic sulfamethoxazole, with predicted concentrations exceeding ecological thresholds in more than 400 000 km of rivers worldwide.
Pedro Felipe Arboleda-Obando, Agnès Ducharne, Zun Yin, and Philippe Ciais
Geosci. Model Dev., 17, 2141–2164, https://doi.org/10.5194/gmd-17-2141-2024, https://doi.org/10.5194/gmd-17-2141-2024, 2024
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We show a new irrigation scheme included in the ORCHIDEE land surface model. The new irrigation scheme restrains irrigation due to water shortage, includes water adduction, and represents environmental limits and facilities to access water, due to representing infrastructure in a simple way. Our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, even if there are difficulties due to shortcomings and limited information.
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024, https://doi.org/10.5194/gmd-17-1153-2024, 2024
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Ensemble geophysical datasets are crucial for understanding uncertainties and supporting probabilistic estimation/prediction. However, open-access tools for creating these datasets are limited. We have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP). Through several experiments, we demonstrate GPEP's ability to estimate precipitation, temperature, and snow water equivalent. GPEP will be a useful tool to support uncertainty analysis in Earth science applications.
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024, https://doi.org/10.5194/gmd-17-911-2024, 2024
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We present a parsimonious snow model which simulates snow mass without the need for extensive calibration. The model is based on a machine learning algorithm that has been trained on diverse set of daily observations of snow accumulation or melt, along with corresponding climate and topography data. We validated the model using in situ data from numerous new locations. The model provides a promising solution for accurate snow mass estimation across regions where in situ data are limited.
Ciaran J. Harman and Esther Xu Fei
Geosci. Model Dev., 17, 477–495, https://doi.org/10.5194/gmd-17-477-2024, https://doi.org/10.5194/gmd-17-477-2024, 2024
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Over the last 10 years, scientists have developed StorAge Selection: a new way of modeling how material is transported through complex systems. Here, we present some new, easy-to-use, flexible, and very accurate code for implementing this method. We show that, in cases where we know exactly what the answer should be, our code gets the right answer. We also show that our code is closer than some other codes to the right answer in an important way: it conserves mass.
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024, https://doi.org/10.5194/gmd-17-497-2024, 2024
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Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating water movement in the environment. We demonstrated its effectiveness in two watersheds, one in the USA and one in China. The toolkit also facilitated the creation of the Global Hydrological Data Cloud, a platform for automatic data processing and model deployment, marking a significant advancement in hydrological research.
Jarno Verkaik, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens
Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024, https://doi.org/10.5194/gmd-17-275-2024, 2024
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This paper presents the parallel PCR-GLOBWB global-scale groundwater model at 30 arcsec resolution (~1 km at the Equator). Named GLOBGM v1.0, this model is a follow-up of the 5 arcmin (~10 km) model, aiming for a higher-resolution simulation of worldwide fresh groundwater reserves under climate change and excessive pumping. For a long transient simulation using a parallel prototype of MODFLOW 6, we show that our implementation is efficient for a relatively low number of processor cores.
Han Qiu, Gautam Bisht, Lingcheng Li, Dalei Hao, and Donghui Xu
Geosci. Model Dev., 17, 143–167, https://doi.org/10.5194/gmd-17-143-2024, https://doi.org/10.5194/gmd-17-143-2024, 2024
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We developed and validated an inter-grid-cell lateral groundwater flow model for both saturated and unsaturated zone in the ELMv2.0 framework. The developed model was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model and showed comparable performance with PFLOTRAN. The developed model was also applied to the Little Washita experimental watershed. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset.
Daniel Boateng and Sebastian G. Mutz
Geosci. Model Dev., 16, 6479–6514, https://doi.org/10.5194/gmd-16-6479-2023, https://doi.org/10.5194/gmd-16-6479-2023, 2023
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We present an open-source Python framework for performing empirical-statistical downscaling of climate information, such as precipitation. The user-friendly package comprises all the downscaling cycles including data preparation, model selection, training, and evaluation, designed in an efficient and flexible manner, allowing for quick and reproducible downscaling products. The framework would contribute to climate change impact assessments by generating accurate high-resolution climate data.
Masaya Yoshikai, Takashi Nakamura, Eugene C. Herrera, Rempei Suwa, Rene Rollon, Raghab Ray, Keita Furukawa, and Kazuo Nadaoka
Geosci. Model Dev., 16, 5847–5863, https://doi.org/10.5194/gmd-16-5847-2023, https://doi.org/10.5194/gmd-16-5847-2023, 2023
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Due to complex root system structures, representing the impacts of Rhizophora mangroves on flow in hydrodynamic models has been challenging. This study presents a new drag and turbulence model that leverages an empirical model for root systems. The model can be applied without rigorous measurements of root structures and showed high performance in flow simulations; this may provide a better understanding of hydrodynamics and related transport processes in Rhizophora mangrove forests.
Hao Chen, Tiejun Wang, Yonggen Zhang, Yun Bai, and Xi Chen
Geosci. Model Dev., 16, 5685–5701, https://doi.org/10.5194/gmd-16-5685-2023, https://doi.org/10.5194/gmd-16-5685-2023, 2023
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Effectively assembling multiple models for approaching a benchmark solution remains a long-standing issue for various geoscience domains. We here propose an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this challenge. Results demonstrate the great potential of AutoML-Ens for improving estimations due to its two unique features, i.e., assigning dynamic weights for candidate models and taking full advantage of AutoML-assisted workflow.
Dapeng Feng, Hylke Beck, Jens de Bruijn, Reetik Kumar Sahu, Yusuke Satoh, Yoshihide Wada, Jiangtao Liu, Ming Pan, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-190, https://doi.org/10.5194/gmd-2023-190, 2023
Revised manuscript accepted for GMD
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Accurate hydrological modeling is vital to characterizing water cycle responses to climate change. For the first time at this scale, we use differentiable physics-informed machine learning hydrologic models to simulate rainfall-runoff processes for 3753 basins around the world and compare them with purely data-driven and traditional approaches. This sets a benchmark for hydrologic estimates around the world and builds foundations for improving global hydrologic simulations.
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472, https://doi.org/10.5194/gmd-16-5449-2023, https://doi.org/10.5194/gmd-16-5449-2023, 2023
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Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023, https://doi.org/10.5194/gmd-16-5035-2023, 2023
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NEOPRENE is an open-source, freely available library allowing scientists and practitioners to generate synthetic time series and maps of rainfall. These outputs will help to explore plausible events that were never observed in the past but may occur in the near future and to generate possible future events under climate change conditions. The paper shows how to use the library to downscale daily precipitation and how to use synthetic generation to improve our characterization of extreme events.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
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We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791, https://doi.org/10.5194/gmd-16-4767-2023, https://doi.org/10.5194/gmd-16-4767-2023, 2023
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Water in natural environments consists of many ions. Ions are electrically charged and exert electric forces on each other. We discuss whether the electric forces are relevant in describing mixing and reaction processes in natural environments. By comparing our computer simulations to lab experiments in literature, we show that the electric interactions between ions can play an essential role in mixing and reaction processes, in which case they should not be neglected in numerical modeling.
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, https://doi.org/10.5194/gmd-16-4481-2023, 2023
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DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic pollution and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has the potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.
Hugo Delottier, John Doherty, and Philip Brunner
Geosci. Model Dev., 16, 4213–4231, https://doi.org/10.5194/gmd-16-4213-2023, https://doi.org/10.5194/gmd-16-4213-2023, 2023
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Long run times are usually a barrier to the quantification and reduction of predictive uncertainty with complex hydrological models. Data space inversion (DSI) provides an alternative and highly model-run-efficient method for uncertainty quantification. This paper demonstrates DSI's ability to robustly quantify predictive uncertainty and extend the methodology to provide practical metrics that can guide data acquisition and analysis to achieve goals of decision-support modelling.
Zhipin Ai and Naota Hanasaki
Geosci. Model Dev., 16, 3275–3290, https://doi.org/10.5194/gmd-16-3275-2023, https://doi.org/10.5194/gmd-16-3275-2023, 2023
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Simultaneously simulating food production and the requirements and availability of water resources in a spatially explicit manner within a single framework remains challenging on a global scale. Here, we successfully enhanced the global hydrological model H08 that considers human water use and management to simulate the yields of four major staple crops: maize, wheat, rice, and soybean. Our improved model will be beneficial for advancing global food–water nexus studies in the future.
Emilie Rouzies, Claire Lauvernet, Bruno Sudret, and Arthur Vidard
Geosci. Model Dev., 16, 3137–3163, https://doi.org/10.5194/gmd-16-3137-2023, https://doi.org/10.5194/gmd-16-3137-2023, 2023
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Water and pesticide transfer models are complex and should be simplified to be used in decision support. Indeed, these models simulate many spatial processes in interaction, involving a large number of parameters. Sensitivity analysis allows us to select the most influential input parameters, but it has to be adapted to spatial modelling. This study will identify relevant methods that can be transposed to any hydrological and water quality model and improve the fate of pesticide knowledge.
Guoding Chen, Ke Zhang, Sheng Wang, Yi Xia, and Lijun Chao
Geosci. Model Dev., 16, 2915–2937, https://doi.org/10.5194/gmd-16-2915-2023, https://doi.org/10.5194/gmd-16-2915-2023, 2023
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In this study, we developed a novel modeling system called iHydroSlide3D v1.0 by coupling a modified a 3D landslide model with a distributed hydrology model. The model is able to apply flexibly different simulating resolutions for hydrological and slope stability submodules and gain a high computational efficiency through parallel computation. The test results in the Yuehe River basin, China, show a good predicative capability for cascading flood–landslide events.
Jens A. de Bruijn, Mikhail Smilovic, Peter Burek, Luca Guillaumot, Yoshihide Wada, and Jeroen C. J. H. Aerts
Geosci. Model Dev., 16, 2437–2454, https://doi.org/10.5194/gmd-16-2437-2023, https://doi.org/10.5194/gmd-16-2437-2023, 2023
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We present a computer simulation model of the hydrological system and human system, which can simulate the behaviour of individual farmers and their interactions with the water system at basin scale to assess how the systems have evolved and are projected to evolve in the future. For example, we can simulate the effect of subsidies provided on investment in adaptation measures and subsequent effects in the hydrological system, such as a lowering of the groundwater table or reservoir level.
Matthew D. Wilson and Thomas J. Coulthard
Geosci. Model Dev., 16, 2415–2436, https://doi.org/10.5194/gmd-16-2415-2023, https://doi.org/10.5194/gmd-16-2415-2023, 2023
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During flooding, the sources of water that inundate a location can influence impacts such as pollution. However, methods to trace water sources in flood events are currently only available in complex, computationally expensive hydraulic models. We propose a simplified method which can be added to efficient, reduced-complexity model codes, enabling an improved understanding of flood dynamics and its impacts. We demonstrate its application for three sites at a range of spatial and temporal scales.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-2023, https://doi.org/10.5194/gmd-16-1617-2023, 2023
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It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 16, 1553–1567, https://doi.org/10.5194/gmd-16-1553-2023, https://doi.org/10.5194/gmd-16-1553-2023, 2023
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Under-monitored regions like Africa need high-quality soil moisture predictions to help with food production, but it is not clear if soil moisture processes are similar enough around the world for data-driven models to maintain accuracy. We present a deep-learning-based soil moisture model that learns from both in situ data and satellite data and performs better than satellite products at the global scale. These results help us apply our model globally while better understanding its limitations.
Daniel Caviedes-Voullième, Mario Morales-Hernández, Matthew R. Norman, and Ilhan Özgen-Xian
Geosci. Model Dev., 16, 977–1008, https://doi.org/10.5194/gmd-16-977-2023, https://doi.org/10.5194/gmd-16-977-2023, 2023
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This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
Andrew M. Ireson, Raymond J. Spiteri, Martyn P. Clark, and Simon A. Mathias
Geosci. Model Dev., 16, 659–677, https://doi.org/10.5194/gmd-16-659-2023, https://doi.org/10.5194/gmd-16-659-2023, 2023
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Richards' equation (RE) is used to describe the movement and storage of water in a soil profile and is a component of many hydrological and earth-system models. Solving RE numerically is challenging due to the non-linearities in the properties. Here, we present a simple but effective and mass-conservative solution to solving RE, which is ideal for teaching/learning purposes but also useful in prototype models that are used to explore alternative process representations.
Fang Wang, Di Tian, and Mark Carroll
Geosci. Model Dev., 16, 535–556, https://doi.org/10.5194/gmd-16-535-2023, https://doi.org/10.5194/gmd-16-535-2023, 2023
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Gridded precipitation datasets suffer from biases and coarse resolutions. We developed a customized deep learning (DL) model to bias-correct and downscale gridded precipitation data using radar observations. The results showed that the customized DL model can generate improved precipitation at fine resolutions where regular DL and statistical methods experience challenges. The new model can be used to improve precipitation estimates, especially for capturing extremes at smaller scales.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
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Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Nicolas Flipo, Nicolas Gallois, and Jonathan Schuite
Geosci. Model Dev., 16, 353–381, https://doi.org/10.5194/gmd-16-353-2023, https://doi.org/10.5194/gmd-16-353-2023, 2023
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A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
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Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
Shuqi Lin, Donald C. Pierson, and Jorrit P. Mesman
Geosci. Model Dev., 16, 35–46, https://doi.org/10.5194/gmd-16-35-2023, https://doi.org/10.5194/gmd-16-35-2023, 2023
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The risks brought by the proliferation of algal blooms motivate the improvement of bloom forecasting tools, but algal blooms are complexly controlled and difficult to predict. Given rapid growth of monitoring data and advances in computation, machine learning offers an alternative prediction methodology. This study tested various machine learning workflows in a dimictic mesotrophic lake and gave promising predictions of the seasonal variations and the timing of algal blooms.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
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A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
Seyed Mahmood Hamze-Ziabari, Ulrich Lemmin, Frédéric Soulignac, Mehrshad Foroughan, and David Andrew Barry
Geosci. Model Dev., 15, 8785–8807, https://doi.org/10.5194/gmd-15-8785-2022, https://doi.org/10.5194/gmd-15-8785-2022, 2022
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A procedure combining numerical simulations, remote sensing, and statistical analyses is developed to detect large-scale current systems in large lakes. By applying this novel procedure in Lake Geneva, strategies for detailed transect field studies of the gyres and eddies were developed. Unambiguous field evidence of 3D gyre/eddy structures in full agreement with predictions confirmed the robustness of the proposed procedure.
Kristina Šarović, Melita Burić, and Zvjezdana B. Klaić
Geosci. Model Dev., 15, 8349–8375, https://doi.org/10.5194/gmd-15-8349-2022, https://doi.org/10.5194/gmd-15-8349-2022, 2022
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We develop a simple 1-D model for the prediction of the vertical temperature profiles in small, warm lakes. The model uses routinely measured meteorological variables as well as UVB radiation and yearly mean temperature data. It can be used for the assessment of the onset and duration of lake stratification periods when water temperature data are unavailable, which can be useful for various lake studies performed in other scientific fields, such as biology, geochemistry, and sedimentology.
Jason A. Clark, Elchin E. Jafarov, Ken D. Tape, Benjamin M. Jones, and Victor Stepanenko
Geosci. Model Dev., 15, 7421–7448, https://doi.org/10.5194/gmd-15-7421-2022, https://doi.org/10.5194/gmd-15-7421-2022, 2022
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Lakes in the Arctic are important reservoirs of heat. Under climate warming scenarios, we expect Arctic lakes to warm the surrounding frozen ground. We simulate water temperatures in three Arctic lakes in northern Alaska over several years. Our results show that snow depth and lake ice strongly affect water temperatures during the frozen season and that more heat storage by lakes would enhance thawing of frozen ground.
Danielle S. Grogan, Shan Zuidema, Alex Prusevich, Wilfred M. Wollheim, Stanley Glidden, and Richard B. Lammers
Geosci. Model Dev., 15, 7287–7323, https://doi.org/10.5194/gmd-15-7287-2022, https://doi.org/10.5194/gmd-15-7287-2022, 2022
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This paper describes the University of New Hampshire's water balance model (WBM). This model simulates the land surface components of the global water cycle and includes water extractions for use by humans for agricultural, domestic, and industrial purposes. A new feature is described that permits water source tracking through the water cycle, which has implications for water resource management. This paper was written to describe a long-used model and presents its first open-source version.
Luca Guillaumot, Mikhail Smilovic, Peter Burek, Jens de Bruijn, Peter Greve, Taher Kahil, and Yoshihide Wada
Geosci. Model Dev., 15, 7099–7120, https://doi.org/10.5194/gmd-15-7099-2022, https://doi.org/10.5194/gmd-15-7099-2022, 2022
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We develop and test the first large-scale hydrological model at regional scale with a very high spatial resolution that includes a water management and groundwater flow model. This study infers the impact of surface and groundwater-based irrigation on groundwater recharge and on evapotranspiration in both irrigated and non-irrigated areas. We argue that water table recorded in boreholes can be used as validation data if water management is well implemented and spatial resolution is ≤ 100 m.
Robert Chlumsky, James R. Craig, Simon G. M. Lin, Sarah Grass, Leland Scantlebury, Genevieve Brown, and Rezgar Arabzadeh
Geosci. Model Dev., 15, 7017–7030, https://doi.org/10.5194/gmd-15-7017-2022, https://doi.org/10.5194/gmd-15-7017-2022, 2022
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We introduce the open-source RavenR package, which has been built to support the use of the hydrologic modelling framework Raven. The R package contains many functions that may be useful in each step of the model-building process, including preparing model input files, running the model, and analyzing the outputs. We present six reproducible use cases of the RavenR package for the Liard River basin in Canada to demonstrate how it may be deployed.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
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Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
Cited articles
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P. P., Janowiak,
J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind,
J., Arkin, P., and Nelkin, E.: The version-2 global precipitation climatology
project (GPCP) monthly precipitation analysis (1979–present), J.
Hydrometeorol., 4, 1147–1167, 2003.
Allen, R. G.: Using the FAO-56 dual crop coefficient method over an irrigated
region as part of an evapotranspiration intercomparison study, J. Hydrol.,
229, 27–41, 2000.
Allen, R. G., Tasumi, M., and Trezza, R.: Satellite-Based Energy Balance for
Mapping Evapotranspiration with Internalized Calibration (METRIC)-Model, J.
Irrig. Drain. E., 133, 380–394, 2007.
Armstrong, R. L., Brodzik, M. J., Knowles, K., and Savoie, M.: Global monthly
EASE-Grid snow water equivalent climatology, National Snow and Ice Data
Center, Digital media, Boulder, CO, USA, 2005.
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., 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, 2001.
Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., and Holtslag, A. A. M.: A
remote sensing surface energy balance algorithm for land (SEBAL). 1.
Formulation, J. Hydrol., 212–213, 198–212, 1998.
Bos, M. G., Kselik, R. A. L., Allen, R. G., and Molden, D. J.: Water
Requirements for Irrigation and the Environment, Springer, Dordrecht, the
Netherlands, 2008.
Bouchet, R. J.: Evapotranspiration réelle et potentielle, signification
climatique. General Assembly Berkeley, International Association for
Hydrological Sciences, Gentbrugge, Belgium, 62, 134–142, 1963.
Brutsaert, W.: Evaporation Into the Atmosphere: theory, history, and
applications, Reidel Publishing, Dordrecht, the Netherlands, 1982.
Brutsaert, W.: Hydrology : An Introduction, Cambridge University Press,
Cambridge, UK, 2005.
Brutsaert, W. and Stricker, H.: An advection-aridity approach to estimate
actual regional evapotranspiration, Water Resour. Res., 15, 443–450, 1979.
Carvalhais, N., Reichstein, M., Collatz, G. J., Mahecha, M. D., Migliavacca,
M., Neigh, C. S. R., Tomelleri, E., Benali, A. A., Papale, D., and Seixas,
J.: Deciphering the components of regional net ecosystem fluxes following a
bottom-up approach for the Iberian Peninsula, Biogeosciences, 7, 3707–3729,
https://doi.org/10.5194/bg-7-3707-2010, 2010.
Cavanaugh, M. L., Kurc, S. A., and Scott, R. L.: Evapotranspiration
partitioning in semiarid shrubland ecosystems: a two-site evaluation of soil
moisture control on transpiration, Ecohydrology, 4, 671–681, 2011.
Chahine, M. T.: The hydrological cycle and its influence on climate, Nature,
359, 373–380, 1992.
Chen, X., Su, Z., Ma, Y., Yang, K., Wen, J., and Zhang, Y.: An Improvement of
Roughness Height Parameterization of the Surface Energy Balance System (SEBS)
over the Tibetan Plateau, J. Appl. Meteorol. Clim., 52, 607–622, 2012.
Chiti, T., Papale, D., Smith, P., Dalmonech, D., Matteucci, G., Yeluripati,
J., Rodeghiero, M., and Valentini, R.: Predicting changes in soil organic
carbon in mediterranean and alpine forests during the Kyoto Protocol
commitment periods using the CENTURY model, Soil Use Manage., 26, 475–484,
2010.
Coccia, G., Siemann, A., Pan, M., and Wood, E. F.: Creating consistent
datasets by combining remotely-sensed data and land surface model estimates
through Bayesian uncertainty post-processing: the case of Land Surface
Temperature from HIRS, Remote Sens. Environ., 170, 290–305,
https://doi.org/10.1016/j.rse.2015.09.010, 2015.
Curtis, P. S., Hanson, P. J., Bolstad, P., Barford, C., Randolph, J. C.,
Schmid, H. P., and Wilson, K. B.: Biometric and eddy-covariance based
estimates of annual carbon storage in five eastern North American deciduous
forests, Agr. Forest Meteorol., 113, 3–19, 2002.
Delpierre, N., Soudani, K., Francois, C., Köstner, B., Pontailler, J. Y.,
Nikinmaa, E., Misson, L., Aubinet, M., Bernhofer, C., and Granier, A.:
Exceptional carbon uptake in European forests during the warm spring of 2007:
a data–model analysis, Glob. Change Biol., 15, 1455–1474, 2009.
Don, A., Rebmann, C., Kolle, O., Scherer-Lorenzen, M., and Schulze, E. D.:
Impact of afforestation-associated management changes on the carbon balance
of grassland, Glob. Change Biol., 15, 1990–2002, 2009.
Douville, H., Ribes, A., Decharme, B., Alkama, R., and Sheffield, J.:
Anthropogenic influence on multidecadal changes in reconstructed global
evapotranspiration, Nature Clim. Change, 3, 59–62, 2013.
Dragoni, D., Schmid, H. P., Wayson, C. A., Potter, H., Grimmond, C. S. B.,
and Randolph, J. C.: Evidence of increased net ecosystem productivity
associated with a longer vegetated season in a deciduous forest in
south-central Indiana, USA, Glob. Change Biol., 17, 886–897, 2011.
Ershadi, A., McCabe, M. F., Evans, J. P., Mariethoz, G., and Kavetski, D.: A
Bayesian analysis of sensible heat flux estimation: Quantifying uncertainty
in meteorological forcing to improve model prediction, Water Resour. Res.,
49, 2343–2358, 2013.
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, 2014.
Ershadi, A., McCabe, M. F., Evans, J. P., and Wood, E. F.: Impact of model
structure and parameterization on Penman–Monteith type evaporation models,
J. Hydrol., 525, 521–535, 2015.
Famiglietti, J. S., Lo, M., Ho, S. L., Bethune, J., Anderson, K. J., Syed, T.
H., Swenson, S. C., de Linage, C. R., and Rodell, M.: Satellites measure
recent rates of groundwater depletion in California's Central Valley,
Geophys. Res. Lett., 38, L03403, https://doi.org/10.1029/2010GL046442, 2011.
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, 2008.
Flanagan, L. B., Cai, T., Black, T. A., Barr, A. G., McCaughey, J. H., and
Margolis, H. A.: Measuring and modeling ecosystem photosynthesis and the
carbon isotope composition of ecosystem-respired CO2 in three boreal
coniferous forests, Agr. Forest Meteorol., 153, 165–176, 2012.
Fu, D., Chen, B., Zhang, H., Wang, J., Black, T. A., Amiro, B. D., Bohrer,
G., Bolstad, P., Coulter, R., and Rahman, A. F.: Estimating landscape net
ecosystem exchange at high spatial–temporal resolution based on Landsat
data, an improved upscaling model framework, and eddy covariance flux
measurements, Remote Sens. Environ., 141, 90–104, 2014.
Gamon, J. A., Coburn, C., Flanagan, L. B., Huemmrich, K. F., Kiddle, C.,
Sanchez-Azofeifa, G. A., Thayer, D. R., Vescovo, L., Gianelle, D., and Sims,
D. A.: SpecNet revisited: bridging flux and remote sensing communities, Can.
J. Remote Sens., 36, S376–S390, 2010.
Gash, J. H.: An analytical model of rainfall interception by forests
quarterly, Q. J. Roy. Meteor. Soc., 105, 43–45, 1979.
Gilmanov, T., Soussana, J., Aires, L., Allard, V., Ammann, C., Balzarolo, M.,
Barcza, Z., Bernhofer, C., Campbell, C., Cernusca, A., Cescatti, A.,
Clifton-Brown, J., Dirks, B., Dore, S., Eugster, W., Fuhrer, J., Gimeno, C.,
Gruenwald, T., Haszpra, L., Hensen, A., Ibrom, A., Jacobs, A., Jones, M.,
Lanigan, G., Laurila, T., Lohila, A., Manca, G., Marcolla, B., Nagy, Z.,
Pilegaard, K., Pinter, K., Pio, C., Raschi, A., Rogiers, N., Sanz, M.,
Stefani, P., Sutton, M., Tuba, Z., Valentini, R., Williams, M., and
Wohlfahrt, G.: Partitioning European grassland net ecosystem CO2
exchange into gross primary productivity and ecosystem respiration using
light response function analysis, Agr. Ecosyst. Environ., 121, 93–120, 2007.
Gioli, B., Miglietta, F., De Martino, B., Hutjes, R. W. A., Dolman, H. A. J.,
Lindroth, A., Schumacher, M., Sanz, M. J., Manca, G., and Peressotti, A.:
Comparison between tower and aircraft-based eddy covariance fluxes in five
European regions, Agr. Forest Meteorol., 127, 1–16, 2004.
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.
Granger, R. J.: Satellite-derived estimates of evapotranspiration in the
Gediz basin, J. Hydrol., 229, 70–76, 2000.
Greve, P., Orlowsky, B., Mueller, B., Sheffield, J., Reichstein, M., and
Seneviratne, S. I.: Global assessment of trends in wetting and drying over
land, Nat. Geosci., 7, 716–721, 2014.
Guillod, B. P., Orlowsky, B., Miralles, D. G., Teuling, A. J., and
Seneviratne, S. I.: Reconciling spatial and temporal soil moisture effects on
afternoon rainfall, Nat. Commun., 6, 6443, https://doi.org/10.1038/ncomms7443, 2015.
Hansen, M. C., Townshend, J. R. G., DeFries, R. S., and Carroll, M.:
Estimation of tree cover using MODIS data at global, continental and
regional/local scales, Int. J. Remote Sens., 26, 4359–4380, 2005.
Harman, I.: The Role of Roughness Sublayer Dynamics Within Surface Exchange
Schemes, Bound.-Lay. Meteorol., 142, 1–20, 2012.
Hilton, T. W., Davis, K. J., and Keller, K.: Evaluating terrestrial CO2
flux diagnoses and uncertainties from a simple land surface model and its
residuals, Biogeosciences, 11, 217–235, https://doi.org/10.5194/bg-11-217-2014, 2014.
Hirschi, M., Seneviratne, S. I., Alexandrov, V., Boberg, F., Boroneant, C.,
Christensen, O. B., Formayer, H., Orlowsky, B., and Stepanek, P.:
Observational evidence for soil-moisture impact on hot extremes in
southeastern Europe, Nat. Geosci., 4, 17–21, 2011.
Hoeting, J. A., Madigan, D., Raftery, A. E., and Volinsky, C. T.: Bayesian
Model Averaging: A Tutorial, Stat. Sci., 14, 382–401, 1999.
Hollinger, D. Y., Ollinger, S. V., Richardson, A. D., Meyers, T. P., Dail, D.
B., Martin, M. E., Scott, N. A., Arkebauer, T. J., Baldocchi, D. D., and
Clark, K. L.: Albedo estimates for land surface models and support for a new
paradigm based on foliage nitrogen concentration, Glob. Change Biol., 16,
696–710, 2010.
Horn, J. E. and Schulz, K.: Identification of a general light use efficiency
model for gross primary production, Biogeosciences, 8, 999–1021,
https://doi.org/10.5194/bg-8-999-2011, 2011.
Houborg, R., McCabe, M. F., and Gao, F.: A Spatio-Temporal Enhancement Method
for medium resolution LAI (STEM-LAI), Int. J. Appl. Earth Obs., 47, 15–29,
2016.
Huffman, G. J., Adler, R. F., Rudolph, B., Schneider, U., and Keehn, P.:
Global precipitation estimates based on a technique for combining
satellite-based estimates, rain gauge analysis, and NWP model precipitation
information, J. Climate, 8, 1284–1295, 1995.
Humphreys, E. R., Black, T. A., Morgenstern, K., Cai, T., Drewitt, G. B.,
Nesic, Z., and Trofymow, J. A.: Carbon dioxide fluxes in coastal Douglas-fir
stands at different stages of development after clearcut harvesting, Agr.
Forest Meteorol., 140, 6–22, 2006.
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., 116, D02102, https://doi.org/10.1029/2010JD014545,
2011.
Jiménez-Muñoz, J., Sobrino, J., Plaza, A., Guanter, L., Moreno, J.,
and Martinez, P.: Comparison Between Fractional Vegetation Cover Retrievals
from Vegetation Indices and Spectral Mixture Analysis: Case Study of
PROBA/CHRIS Data Over an Agricultural Area, Sensors, 9, 768–793, 2009.
Jung, M., Reichstein, M., Ciais, P., Seneviratne, S. I., Sheffield, J.,
Goulden, M. L., Bonan, G., Cescatti, A., Chen, J., and de Jeu, R.: Recent
decline in the global land evapotranspiration trend due to limited moisture
supply, Nature, 467, 951–954, 2010.
Kross, A., Seaquist, J. W., Roulet, N. T., Fernandes, R., and Sonnentag, O.:
Estimating carbon dioxide exchange rates at contrasting northern peatlands
using MODIS satellite data, Remote Sens. Environ., 137, 234–243, 2013.
Kustas, W. P., Perry, E. M., Doraiswamy, P. C., and Moran, M. S.: Using
satellite remote sensing to extrapolate evapotranspiration in time and space
over a semiarid rangeland, Remote Sens. Environ., 49, 275–286, 1994.
Liu, Y. Y., de Jeu, R. A. M., McCabe, M. F., Evans, J. P., and van Dijk, A.
I. J. M.: Global long-term passive microwave satellite-based retrievals of
vegetation optical depth, Geophys. Res. Lett., 38, L18402, https://doi.org/10.1029/2011GL048684,
2011a.
Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W.,
van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P.: Developing an
improved soil moisture dataset by blending passive and active microwave
satellite-based retrievals, Hydrol. Earth Syst. Sci., 15, 425–436,
https://doi.org/10.5194/hess-15-425-2011, 2011b.
Liu, Y. Y., Dorigo, W. A., Parinussa, R. M., De Jeu, R. A. M., Wagner, W.,
McCabe, M. F., Evans, J. P., and Van Dijk, A. I. J. M.: Trend-preserving
blending of passive and active microwave soil moisture retrievals, Remote
Sens. Environ., 123, 280–297, 2012.
Liu, Y. Y., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P., and de Jeu,
R. A. M.: Global vegetation biomass change (1988–2008) and attribution to
environmental and human drivers, Global Ecol. Biogeogr., 22, 692–705, 2013.
Lokupitiya, E., Denning, S., Paustian, K., Baker, I., Schaefer, K., Verma,
S., Meyers, T., Bernacchi, C. J., Suyker, A., and Fischer, M.: Incorporation
of crop phenology in Simple Biosphere Model (SiBcrop) to improve
land-atmosphere carbon exchanges from croplands, Biogeosciences, 6, 969–986,
https://doi.org/10.5194/bg-6-969-2009, 2009.
Luojus, K., Pulliainen, J., Takala, M., Lemmetyinen, J., Derksen, C., and
Wang, L.: Snow water equivalent (SWE) product guide, Global Snow Monitoring
for Climate Research, European Space Agency Study Contract Report Esrin
Contract 21703/08/I-EC), available at:
http://www.globsnow.info/docs/GlobSnow_2_Final_Report_release.pdf (last
access: 25 January 2016), 2010.
Mach, D. M., Christian, H. J., Blakeslee, R. J., Boccippio, D. J., Goodman,
S. J., and Boeck, W. L.: Performance assessment of the optical transient
detector and lightning imaging sensor, J. Geophys. Res.-Atmos. (1984–2012),
112, D09210, https://doi.org/10.1029/2006JD007787, 2007.
McCabe, M. F. and Wood, E. F.: Scale influences on the remote estimation of
evapotranspiration using multiple satellite sensors, Remote Sens. Environ.,
105, 271–285, 2006.
McCabe, M. F., Wood, E. F., Wójcik, R., Pan, M., Sheffield, J., Gao, H.,
and Su, H.: Hydrological consistency using multi-sensor remote sensing data
for water and energy cycle studies, Remote Sens. Environ., 112, 430–444,
2008.
Merlin, O., Al Bitar, A., Rivalland, V., Béziat, P., Ceschia, E., and
Dedieu, G.: An analytical model of evaporation efficiency for unsaturated
soil surfaces with an arbitrary thickness, J. Appl. Meteorol. Clim., 50,
457–471, 2011.
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. Discuss., 12, 10739–10787,
https://doi.org/10.5194/hessd-12-10739-2015, 2015.
Miralles, D. G., Gash, J. H., Holmes, T. R. H., de Jeu, R. A. M., and Dolman,
A.: Global canopy interception from satellite observations, J. Geophys. Res.,
115, D16122, https://doi.org/10.1029/2009JD013530, 2010.
Miralles, D. G., De Jeu, R. A. M., Gash, J. H., Holmes, T. R. H., and Dolman,
A. J.: Magnitude and variability of land evaporation and its components at
the global scale, Hydrol. Earth Syst. Sci., 15, 967–981,
https://doi.org/10.5194/hess-15-967-2011, 2011a.
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, 2011b.
Miralles, D. G., Teuling, A. J., van Heerwaarden, C. C., and de Arellano, J.
V.-G.: Mega-heatwave temperatures due to combined soil desiccation and
atmospheric heat accumulation, Nat. Geosci., 7, 345–349, 2014a.
Miralles, D. G., van den Berg, M. J., Gash, J. H., Parinussa, R. M., de Jeu,
R. A. M., Beck, H. E., Holmes, T. R. H., Jiménez, C., Verhoest, N. E. C.,
and Dorigo, W. A.: El Niño–La Niña cycle and recent trends in
continental evaporation, Nature Climate Change, 4, 122–126, 2014b.
Miralles, D. G., Jiménez, C., Jung, M., Michel, D., Ershadi, A., McCabe,
M. F., Hirschi, M., Martens, B., Dolman, A. J., Fisher, J. B., Mu, Q.,
Seneviratne, S. I., Wood, E. F., and Fernaìndez-Prieto, D.: The
WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation
data sets, Hydrol. Earth Syst. Sci. Discuss., 12, 10651–10700,
https://doi.org/10.5194/hessd-12-10651-2015, 2015.
Monteith, J. L.: Evaporation and environment, Symp. Soc. Exp. Biol., 19,
205–234, 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, 2007.
Mu, Q., Zhao, M., and Running, S. W.: Improvements to a MODIS global
terrestrial evapotranspiration algorithm, Remote Sens. Environ., 115,
1781–1800, 2011.
Mu, Q., Zhao, M., Kimball, J. S., McDowell, N. G., and Running, S. W.: A
Remotely Sensed Global Terrestrial Drought Severity Index, B. Am. Meteorol.
Soc., 94, 83–98, 2012.
Mu, Q., Zhao, M., and Running, S. W.: MODIS Global Terrestrial
Evapotranspiration (ET) Product (NASA MOD16A2/A3), Algorithm Theoretical
Basis Document, Collection, 5, The University of Montana, Missoula, MT, USA,
available at: http://www.ntsg.umt.edu/node/801 (last access: 25 January
2016), 2013.
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.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual
models: Part I – a discussion of principles, J. Hydrol., 10, 282–290, 1970.
Nesbitt, S. W., Zipser, E. J., and Kummerow, C. D.: An examination of
version-5 rainfall estimates from the TRMM Microwave Imager, precipitation
radar, and rain gauges on global, regional, and storm scales, J. Appl.
Meteorol., 43, 1016–1036, 2004.
Norman, J. M., Kustas, W. P., and Humes, K. S.: Source approach for
estimating soil and vegetation energy fluxes in observations of directional
radiometric surface temperature, Agr. Forest Meteorol., 77, 263–293, 1995.
Otkin, J. A., Anderson, M. C., Hain, C., and Svoboda, M.: Examining the
Relationship between Drought Development and Rapid Changes in the Evaporative
Stress Index, J. Hydrometeorol., 15, 938–956, 2014.
Penman, H. L.: Natural Evaporation from Open Water, Bare Soil and Grass, P.
Roy. Soc. Lond. A Mat., 193, 120–145, 1948.
Potter, C. S., Randerson, J. T., Field, C. B., Matson, P. A., Vitousek, P.
M., Mooney, H. A., and Klooster, S. A.: Terrestrial ecosystem production: a
process model based on global satellite and surface data, Global Biogeochem.
Cy., 7, 811–841, 1993.
Priestley, C. H. B. and Taylor, R. J.: On the Assessment of Surface Heat Flux
and Evaporation Using Large-Scale Parameters, Mon. Weather Rev., 100, 81–92,
1972.
Rebmann, C., Göckede, M., Foken, T., Aubinet, M., Aurela, M., Berbigier,
P., Bernhofer, C., Buchmann, N., Carrara, A., and Cescatti, A.: Quality
analysis applied on eddy covariance measurements at complex forest sites
using footprint modelling, Theor. Appl. Climatol., 80, 121–141, 2005.
Reichstein, M., Rey, A., Freibauer, A., Tenhunen, J., Valentini, R., Banza,
J., Casals, P., Cheng, Y., Grünzweig, J. M., and Irvine, J.: Modeling
temporal and large-scale spatial variability of soil respiration from soil
water availability, temperature and vegetation productivity indices, Global
Biogeochem. Cy., 17, 1104, https://doi.org/10.1029/2003GB002035, 2003.
Richardson, A. D., Black, T. A., Ciais, P., Delbart, N., Friedl, M. A.,
Gobron, N., Hollinger, D. Y., Kutsch, W. L., Longdoz, B., and Luyssaert, S.:
Influence of spring and autumn phenological transitions on forest ecosystem
productivity, Philos. T. R. Soc. B, 365, 3227–3246, 2010.
Richey, A. S., Thomas, B. F., Lo, M.-H., Reager, J. T., Famiglietti, J. S.,
Voss, K., Swenson, S., and Rodell, M.: Quantifying renewable groundwater
stress with GRACE, Water Resour. Res., 51, 5217–5238,
https://doi.org/10.1002/2015WR017349, 2015.
Rubel, F. and Kottek, M.: Observed and projected climate shifts 1901–2100
depicted by world maps of the Köppen-Geiger climate classification,
Meteorol. Z., 19, 135–141, 2010.
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P.,
Kistler, R., Woollen, J., and Behringer, D.: The NCEP climate forecast system
reanalysis, B. Am. Meteorol. Soc., 91, 1015–1057, 2010.
Sahoo, A. K., Pan, M., Troy, T. J., Vinukollu, R. K., Sheffield, J., and
Wood, E. F.: Reconciling the global terrestrial water budget using satellite
remote sensing, Remote Sens. Environ., 115, 1850–1865, 2011.
Saigusa, N., Ichii, K., Murakami, H., Hirata, R., Asanuma, J., Den, H., Han,
S.-J., Ide, R., Li, S.-G., Ohta, T., Sasai, T., Wang, S.-Q., and Yu, G.-R.:
Impact of meteorological anomalies in the 2003 summer on Gross Primary
Productivity in East Asia, Biogeosciences, 7, 641–655,
https://doi.org/10.5194/bg-7-641-2010, 2010.
Scott, R. L.: Using watershed water balance to evaluate the accuracy of eddy
covariance evaporation measurements for three semiarid ecosystems, Agr.
Forest Meteorol., 150, 219–225, 2010.
Sheffield, J., Ferguson, C. R., Troy, T. J., Wood, E. F., and McCabe, M. F.:
Closing the terrestrial water budget from satellite remote sensing, Geophys.
Res. Lett., 36, L07403, https://doi.org/10.1029/2009GL037338, 2009.
Sheffield, J., Wood, E. F., and Munoz-Arriola, F.: Long-term regional
estimates of evapotranspiration for Mexico based on downscaled ISCCP data, J.
Hydrometeorol., 11, 253–275, 2010.
Shuttleworth, W. J. and Wallace, J. S.: Evaporation from sparse crops-an
energy combination theory, Q. J. Roy. Meteorol. Soc., 111, 839–855, 1985.
Simard, M., Pinto, N., Fisher, J. B., and Baccini, A.: Mapping forest canopy
height globally with spaceborne lidar, J. Geophys. Res.-Biogeo., 116, G04021,
https://doi.org/10.1029/2011JG001708, 2011.
Smith, P., Lanigan, G., Kutsch, W. L., Buchmann, N., Eugster, W., Aubinet,
M., Ceschia, E., Béziat, P., Yeluripati, J. B., and Osborne, B.:
Measurements necessary for assessing the net ecosystem carbon budget of
croplands, Agr. Ecosyst. Environ., 139, 302–315, 2010.
Sobrino, J. A., Jiménez-Muñoz, J. C., and Paolini, L.: Land surface
temperature retrieval from LANDSAT TM 5, Remote Sens. Environ., 90, 434–440,
2004.
Soudani, K., Hmimina, G., Dufrêne, E., Berveiller, D., Delpierre, N.,
Ourcival, J.-M., Rambal, S., and Joffre, R.: Relationships between
photochemical reflectance index and light-use efficiency in deciduous and
evergreen broadleaf forests, Remote Sens. Environ., 144, 73–84, 2014.
Sprintsin, M., Cohen, S., Maseyk, K., Rotenberg, E., Grünzweig, J.,
Karnieli, A., Berliner, P., and Yakir, D.: Long term and seasonal courses of
leaf area index in a semi-arid forest plantation, Agr. Forest Meteorol., 151,
565–574, 2011.
Stackhouse, P. W., Gupta, S. K., Cox, S. J., Zhang, T., Mikovitz, J. C., and
Hinkelman, L. M.: The NASA/GEWEX surface radiation budget release 3.0:
24.5-year dataset, GEWEX News, 21, 10–12, 2011.
Stoy, P. C., Mauder, M., Foken, T., Marcolla, B., Boegh, E., Ibrom, A.,
Arain, M. A., Arneth, A., Aurela, M., and Bernhofer, C.: A data-driven
analysis of energy balance closure across FLUXNET research sites: The role of
landscape scale heterogeneity, Agr. Forest Meteorol., 171, 137–152, 2013.
Su, H., McCabe, M. F., Wood, E. F., Su, Z., and Prueger, J. H.: Modeling
evapotranspiration during SMACEX: Comparing two approaches for local- and
regional-scale prediction, J. Hydrometeorol., 6, 910–922, 2005.
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.
Sulkava, M., Luyssaert, S., Zhehle, S., and Papale, D.: Assessing and
improving the representativeness of monitoring networks: The European flux
tower network example, J. Geophys. Res., 116, G00J04,
https://doi.org/10.1029/2010JG001562, 2011.
Tucker, C. J., Pinzon, J. E., Brown, M. E., Slayback, D. A., Pak, E. W.,
Mahoney, R., Vermote, E. F., and El Saleous, N.: An extended AVHRR 8-km NDVI
dataset compatible with MODIS and SPOT vegetation NDVI data, Int. J. Remote
Sens., 26, 4485–4498, 2005.
van der Kwast, J., Timmermans, W., Gieske, A., Su, Z., Olioso, A., Jia, L.,
Elbers, J., Karssenberg, D., and de Jong, S.: Evaluation of the Surface
Energy Balance System (SEBS) applied to ASTER imagery with flux-measurements
at the SPARC 2004 site (Barrax, Spain), Hydrol. Earth Syst. Sci., 13,
1337–1347, https://doi.org/10.5194/hess-13-1337-2009, 2009.
Veenendaal, M., Kolle, O., and Lloyd, J.: Seasonal variation in energy fluxes
and carbon dioxide exchange for a broad leaved semi-arid savanna (Mopane
woodland) in Southern Africa, Glob. Change Biol., 10, 318–328, 2004.
Vinukollu, R. K., Sheffield, J., Wood, E. F., Bosilovich, M. G., and Mocko,
D.: Multimodel Analysis of Energy and Water Fluxes: Intercomparisons between
Operational Analyses, a Land Surface Model, and Remote Sensing, J.
Hydrometeorol., 13, 3–26, 2011a.
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, 2011b.
Weligepolage, K., Gieske, A. S. M., van der Tol, C., Timmermans, J., and Su,
Z.: Effect of sub-layer corrections on the roughness parameterization of a
Douglas fir forest, Agr. Forest Meteorol., 162–163, 115–126, 2012.
Wharton, S., Schroeder, M., Paw U, K. T., Falk, M., and Bible, K.: Turbulence
considerations for comparing ecosystem exchange over old-growth and clear-cut
stands for limited fetch and complex canopy flow conditions, Agr. Forest
Meteorol., 149, 1477–1490, 2009.
Wohl, E., Barros, A., Brunsell, N., Chappell, N. A., Coe, M., Giambelluca,
T., Goldsmith, S., Harmon, R., Hendrickx, J. M. H., Juvik, J., McDonnell, J.,
and Ogden, F.: The hydrology of the humid tropics, Nature Clim. Change, 2,
655–662, 2012.
Yan, Y., Zhao, B., Chen, J., Guo, H., Gu, Y., Wu, Q., and Li, B.: Closing the
carbon budget of estuarine wetlands with tower-based measurements and MODIS
time series, Glob. Change Biol., 14, 1690–1702, 2008.
Yao, Y., Liang, S., Li, X., Hong, Y., Fisher, J. B., Zhang, N., Chen, J.,
Cheng, J., Zhao, S., and Zhang, X.: Bayesian multimodel estimation of global
terrestrial latent heat flux from eddy covariance, meteorological, and
satellite observations, J. Geophys. Res.-Atmos., 119, 4521–4545, 2014.
Zhu, Z., Bi, J., Pan, Y., Ganguly, S., Anav, A., Xu, L., Samanta, A., Piao,
S., Nemani, R. R., and Myneni, R. B.: Global data sets of vegetation leaf
area index (LAI) 3 g and Fraction of Photosynthetically Active Radiation
(FPAR) 3 g derived from Global Inventory Modeling and Mapping Studies
(GIMMS) Normalized Difference Vegetation Index (NDVI3g) for the period 1981
to 2011, Remote Sensing, 5, 927–948, 2013.
Zierl, B., Bugmann, H., and Tague, C. L.: Water and carbon fluxes of European
ecosystems: An evaluation of the ecohydrological model RHESSys, Hydrol.
Process., 21, 3328–3339, 2007.
Short summary
In an effort to develop a global terrestrial evaporation product, four models were forced using both a tower and grid-based data set. Comparisons against flux-tower observations from different biome and land cover types show considerable inter-model variability and sensitivity to forcing type. Results suggest that no single model is able to capture expected flux patterns and response. It is suggested that a multi-model ensemble is likely to provide a more stable long-term flux estimate.
In an effort to develop a global terrestrial evaporation product, four models were forced using...
