Articles | Volume 14, issue 8
https://doi.org/10.5194/essd-14-3673-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-3673-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
12 Aug 2022
Data description paper |
| 12 Aug 2022
| 12 Aug 2022
A global terrestrial evapotranspiration product based on the three-temperature model with fewer input parameters and no calibration requirement
Leiyu Yu
School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
Guo Yu Qiu
School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
Chunhua Yan
School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
Wenli Zhao
Department of Earth and Environmental Engineering, Columbia University, New York, NY 10027, USA
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10,
Jena 07745, Germany
Zhendong Zou
Shenzhen Investment Holdings Co., LTD, Shenzhen, 518048, China
Jinshan Ding
School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
Longjun Qin
School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
School of Civil Engineering, Sun Yat-Sen University, Guangzhou,
510275, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai),
Zhuhai, 519082, China
Related authors
No articles found.
Wen Li Zhao, Yu Jiu Xiong, Kyaw Tha Paw U, Pierre Gentine, Baoyu Chen, and Guo Yu Qiu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-160, https://doi.org/10.5194/hess-2019-160, 2019
Manuscript not accepted for further review
Short summary
Short summary
Accurate evapotranspiration (ET) estimation requires an in-depth identification of uncertainty sources. Using high density eddy covariance observations, we evaluated the effects of resistances on ET estimation and discussed possible solutions. The results show that more complex resistance parameterizations leads to more uncertainty, although prior calibration can improve the ET estimates and that a new model without resistance parameterization introduces less uncertainty into the ET estimation.
Jing Yin, Fan He, Yu Jiu Xiong, and Guo Yu Qiu
Hydrol. Earth Syst. Sci., 21, 183–196, https://doi.org/10.5194/hess-21-183-2017, https://doi.org/10.5194/hess-21-183-2017, 2017
Short summary
Short summary
Conflicting results on the effect of the land use/land cover (LULC) and climate changes on runoff have been reported for relatively large basins. After quantifying the impacts of LULC and climate changes on surface runoff using the Soil and Water Assessment Tool, we concluded that large-scale LULC has had an important effect on the water cycle and that the conflicting findings on the effect of the LULC and climate changes on runoff are likely caused by uncertainty in hydrological simulations.
Related subject area
Domain: ESSD – Land | Subject: Hydrology
Hydro-PE: gridded datasets of historical and future Penman–Monteith potential evaporation for the United Kingdom
A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022)
Soil water retention and hydraulic conductivity measured in a wide saturation range
A high-frequency, long-term data set of hydrology and sediment yield: the alpine badland catchments of Draix-Bléone Observatory
Geospatial dataset for hydrologic analyses in India (GHI): a quality-controlled dataset on river gauges, catchment boundaries and hydrometeorological time series
Lake-TopoCat: a global lake drainage topology and catchment database
Three years of soil moisture observations by a dense cosmic-ray neutron sensing cluster at an agricultural research site in north-east Germany
A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015
A global database of historic glacier lake outburst floods
Past and future discharge and stream temperature at high spatial resolution in a large European basin (Loire basin, France)
Res-CN (Reservoir dataset in China): hydrometeorological time series and landscape attributes across 3254 Chinese reservoirs
An ensemble of 48 physically perturbed model estimates of the 1∕8° terrestrial water budget over the conterminous United States, 1980–2015
The UKSCAPE-G2G river flow and soil moisture datasets: Grid-to-Grid model estimates for the UK for historical and potential future climates
The enhanced future Flows and Groundwater dataset: development and evaluation of nationally consistent hydrological projections based on UKCP18
RC4USCoast: a river chemistry dataset for regional ocean model applications in the US East Coast, Gulf of Mexico, and US West Coast
Generation of global 1 km daily soil moisture product from 2000 to 2020 using ensemble learning
Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts
Twelve years of profile soil moisture and temperature measurements in Twente, the Netherlands
Shallow-groundwater-level time series and a groundwater chemistry survey from a boreal headwater catchment, Krycklan, Sweden
Weekly high-resolution multi-spectral and thermal uncrewed-aerial-system mapping of an alpine catchment during summer snowmelt, Niwot Ridge, Colorado
Nunataryuk field campaigns: understanding the origin and fate of terrestrial organic matter in the coastal waters of the Mackenzie Delta region
A gridded dataset of consumptive water footprints, evaporation, transpiration, and associated benchmarks related to crop production in China during 2000–2018
Integrated ecohydrological hydrometric and stable water isotope data of a drought-sensitive mixed land use lowland catchment
Regional data sets of high-resolution (1 and 6 km) irrigation estimates from space
Lake surface temperature retrieved from Landsat satellite series (1984 to 2021) for the North Slave Region
A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth-Wallace model
Global hourly, 5 km, all-sky land surface temperature data from 2011 to 2021 based on integrating geostationary and polar-orbiting satellite data
Flood detection using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage and extreme precipitation data
The pan-Arctic catchment database (ARCADE)
Multi-hazard susceptibility mapping of cryospheric hazards in a high-Arctic environment: Svalbard Archipelago
High-resolution water level and storage variation datasets for 338 reservoirs in China during 2010–2021
WaterBench-Iowa: a large-scale benchmark dataset for data-driven streamflow forecasting
A dataset of 10-year regional-scale soil moisture and soil temperature measurements at multiple depths on the Tibetan Plateau
OpenMRG: Open data from Microwave links, Radar, and Gauges for rainfall quantification in Gothenburg, Sweden
A 1 km daily soil moisture dataset over China using in situ measurement and machine learning
Downscaled hyper-resolution (400 m) gridded datasets of daily precipitation and temperature (2008–2019) for the East–Taylor subbasin (western United States)
HRLT: a high-resolution (1 d, 1 km) and long-term (1961–2019) gridded dataset for surface temperature and precipitation across China
The Surface Water Chemistry (SWatCh) database: a standardized global database of water chemistry to facilitate large-sample hydrological research
Hydrography90m: a new high-resolution global hydrographic dataset
GLOBMAP SWF: a global annual surface water cover frequency dataset during 2000–2020
Streamflow data availability in Europe: a detailed dataset of interpolated flow-duration curves
High-resolution streamflow and weather data (2013–2019) for seven small coastal watersheds in the northeast Pacific coastal temperate rainforest, Canada
A 500-year annual runoff reconstruction for 14 selected European catchments
A comprehensive geospatial database of nearly 100 000 reservoirs in China
Stable water isotope monitoring network of different water bodies in Shiyang River basin, a typical arid river in China
A dataset of lake-catchment characteristics for the Tibetan Plateau
QUADICA: water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany
A new snow depth data set over northern China derived using GNSS interferometric reflectometry from a continuously operating network (GSnow-CHINA v1.0, 2013–2022)
Microwave radiometry experiment for snow in Altay, China: time series of in situ data for electromagnetic and physical features of snowpack
An integrated dataset of daily lake surface water temperature over the Tibetan Plateau
Emma L. Robinson, Matthew J. Brown, Alison L. Kay, Rosanna A. Lane, Rhian Chapman, Victoria A. Bell, and Eleanor M. Blyth
Earth Syst. Sci. Data, 15, 4433–4461, https://doi.org/10.5194/essd-15-4433-2023, https://doi.org/10.5194/essd-15-4433-2023, 2023
Short summary
Short summary
This work presents two new Penman–Monteith potential evaporation datasets for the UK, calculated with the same methodology applied to historical climate data (Hydro-PE HadUK-Grid) and an ensemble of future climate projections (Hydro-PE UKCP18 RCM). Both include an optional correction for evaporation of rain that lands on the surface of vegetation. The historical data are consistent with existing PE datasets, and the future projections include effects of rising atmospheric CO2 on vegetation.
Xinyu Chen, Liguang Jiang, Yuning Luo, and Junguo Liu
Earth Syst. Sci. Data, 15, 4463–4479, https://doi.org/10.5194/essd-15-4463-2023, https://doi.org/10.5194/essd-15-4463-2023, 2023
Short summary
Short summary
River flow is experiencing changes under the impacts of climate change and human activities. For example, flood events are occurring more often and are more destructive in many places worldwide. To deal with such issues, hydrologists endeavor to understand the features of extreme events as well as other hydrological changes. One key approach is analyzing flow characteristics, represented by hydrological indices. Building such a comprehensive global large-sample dataset is essential.
Tobias L. Hohenbrink, Conrad Jackisch, Wolfgang Durner, Kai Germer, Sascha C. Iden, Janis Kreiselmeier, Frederic Leuther, Johanna C. Metzger, Mahyar Naseri, and Andre Peters
Earth Syst. Sci. Data, 15, 4417–4432, https://doi.org/10.5194/essd-15-4417-2023, https://doi.org/10.5194/essd-15-4417-2023, 2023
Short summary
Short summary
The article describes a collection of 572 data sets of soil water retention and unsaturated hydraulic conductivity data measured with state-of-the-art laboratory methods. Furthermore, the data collection contains basic soil properties such as soil texture and organic carbon content. We expect that the data will be useful for various important purposes, for example, the development of soil hydraulic property models and related pedotransfer functions.
Sebastien Klotz, Caroline Le Bouteiller, Nicolle Mathys, Firmin Fontaine, Xavier Ravanat, Jean-Emmanuel Olivier, Frédéric Liébault, Hugo Jantzi, Patrick Coulmeau, Didier Richard, Jean-Pierre Cambon, and Maurice Meunier
Earth Syst. Sci. Data, 15, 4371–4388, https://doi.org/10.5194/essd-15-4371-2023, https://doi.org/10.5194/essd-15-4371-2023, 2023
Short summary
Short summary
Mountain badlands are places of intense erosion. They deliver large amounts of sediment to river systems, with consequences for hydropower sustainability, habitat quality and biodiversity, and flood hazard and river management. Draix-Bleone Observatory was created in 1983 to understand and quantify sediment delivery from such badland areas. Our paper describes how water and sediment fluxes have been monitored for almost 40 years in the small mountain catchments of this observatory.
Gopi Goteti
Earth Syst. Sci. Data, 15, 4389–4415, https://doi.org/10.5194/essd-15-4389-2023, https://doi.org/10.5194/essd-15-4389-2023, 2023
Short summary
Short summary
Data on river gauging stations, river basin boundaries and river flow paths are critical for hydrological analyses, but existing data for India's river basins have limited availability and reliability. This work fills the gap by building a new dataset. Data for 645 stations in 15 basins of India were compiled and checked against global data sources; data were supplemented with additional information where needed. This dataset will serve as a reliable building block in hydrological analyses.
Md Safat Sikder, Jida Wang, George H. Allen, Yongwei Sheng, Dai Yamazaki, Chunqiao Song, Meng Ding, Jean-François Crétaux, and Tamlin M. Pavelsky
Earth Syst. Sci. Data, 15, 3483–3511, https://doi.org/10.5194/essd-15-3483-2023, https://doi.org/10.5194/essd-15-3483-2023, 2023
Short summary
Short summary
We introduce Lake-TopoCat to reveal detailed lake hydrography information. It contains the location of lake outlets, the boundary of lake catchments, and a wide suite of attributes that depict detailed lake drainage relationships. It was constructed using lake boundaries from a global lake dataset, with the help of high-resolution hydrography data. This database may facilitate a variety of applications including water quality, agriculture and fisheries, and integrated lake–river modeling.
Maik Heistermann, Till Francke, Lena Scheiffele, Katya Dimitrova Petrova, Christian Budach, Martin Schrön, Benjamin Trost, Daniel Rasche, Andreas Güntner, Veronika Döpper, Michael Förster, Markus Köhli, Lisa Angermann, Nikolaos Antonoglou, Manuela Zude-Sasse, and Sascha E. Oswald
Earth Syst. Sci. Data, 15, 3243–3262, https://doi.org/10.5194/essd-15-3243-2023, https://doi.org/10.5194/essd-15-3243-2023, 2023
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of root-zone soil water content (SWC). The signal observed by a single CRNS sensor is influenced by the SWC in a radius of around 150 m (the footprint). Here, we have put together a cluster of eight CRNS sensors with overlapping footprints at an agricultural research site in north-east Germany. That way, we hope to represent spatial SWC heterogeneity instead of retrieving just one average SWC estimate from a single sensor.
Benjamin M. Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Frederic Frappart, Stephane Calmant, Omid Elmi, Ayan Santos Fleischmann, Melanie Becker, Mohammad J. Tourian, Rômulo A. Jucá Oliveira, and Sly Wongchuig
Earth Syst. Sci. Data, 15, 2957–2982, https://doi.org/10.5194/essd-15-2957-2023, https://doi.org/10.5194/essd-15-2957-2023, 2023
Short summary
Short summary
The surface water storage (SWS) in the Congo River basin (CB) remains unknown. In this study, the multi-satellite and hypsometric curve approaches are used to estimate SWS in the CB over 1992–2015. The results provide monthly SWS characterized by strong variability with an annual mean amplitude of ~101 ± 23 km3. The evaluation of SWS against independent datasets performed well. This SWS dataset contributes to the better understanding of the Congo basin’s surface hydrology using remote sensing.
Natalie Lützow, Georg Veh, and Oliver Korup
Earth Syst. Sci. Data, 15, 2983–3000, https://doi.org/10.5194/essd-15-2983-2023, https://doi.org/10.5194/essd-15-2983-2023, 2023
Short summary
Short summary
Glacier lake outburst floods (GLOFs) are a prominent natural hazard, and climate change may change their magnitude, frequency, and impacts. A global, literature-based GLOF inventory is introduced, entailing 3151 reported GLOFs. The reporting density varies temporally and regionally, with most cases occurring in NW North America. Since 1900, the number of yearly documented GLOFs has increased 6-fold. However, many GLOFs have incomplete records, and we call for a systematic reporting protocol.
Hanieh Seyedhashemi, Florentina Moatar, Jean-Philippe Vidal, and Dominique Thiéry
Earth Syst. Sci. Data, 15, 2827–2839, https://doi.org/10.5194/essd-15-2827-2023, https://doi.org/10.5194/essd-15-2827-2023, 2023
Short summary
Short summary
This paper presents a past and future dataset of daily time series of discharge and stream temperature for 52 278 reaches over the Loire River basin (100 000 km2) in France, using thermal and hydrological models. Past data are provided over 1963–2019. Future data are available over the 1976–2100 period under different future climate change models (warm and wet, intermediate, and hot and dry) and scenarios (optimistic, intermediate, and pessimistic).
Youjiang Shen, Karina Nielsen, Menaka Revel, Dedi Liu, and Dai Yamazaki
Earth Syst. Sci. Data, 15, 2781–2808, https://doi.org/10.5194/essd-15-2781-2023, https://doi.org/10.5194/essd-15-2781-2023, 2023
Short summary
Short summary
Res-CN fills a gap in a comprehensive and extensive dataset of reservoir-catchment characteristics for 3254 Chinese reservoirs with 512 catchment-level attributes and significantly enhanced spatial and temporal coverage (e.g., 67 % increase in water level and 225 % in storage anomaly) of time series of reservoir water level (data available for 20 % of 3254 reservoirs), water area (99 %), storage anomaly (92 %), and evaporation (98 %), supporting a wide range of applications and disciplines.
Hui Zheng, Wenli Fei, Zong-Liang Yang, Jiangfeng Wei, Long Zhao, Lingcheng Li, and Shu Wang
Earth Syst. Sci. Data, 15, 2755–2780, https://doi.org/10.5194/essd-15-2755-2023, https://doi.org/10.5194/essd-15-2755-2023, 2023
Short summary
Short summary
An ensemble of evapotranspiration, runoff, and water storage is estimated here using the Noah-MP land surface model by perturbing model parameterization schemes. The data could be beneficial for monitoring and understanding the variability of water resources. Model developers could also gain insights by intercomparing the ensemble members.
Alison L. Kay, Victoria A. Bell, Helen N. Davies, Rosanna A. Lane, and Alison C. Rudd
Earth Syst. Sci. Data, 15, 2533–2546, https://doi.org/10.5194/essd-15-2533-2023, https://doi.org/10.5194/essd-15-2533-2023, 2023
Short summary
Short summary
Climate change will affect the water cycle, including river flows and soil moisture. We have used both observational data (1980–2011) and the latest UK climate projections (1980–2080) to drive a national-scale grid-based hydrological model. The data, covering Great Britain and Northern Ireland, suggest potential future decreases in summer flows, low flows, and summer/autumn soil moisture, and possible future increases in winter and high flows. Society must plan how to adapt to such impacts.
Jamie Hannaford, Jonathan D. Mackay, Matthew Ascott, Victoria A. Bell, Thomas Chitson, Steven Cole, Christian Counsell, Mason Durant, Christopher R. Jackson, Alison L. Kay, Rosanna A. Lane, Majdi Mansour, Robert Moore, Simon Parry, Alison C. Rudd, Michael Simpson, Katie Facer-Childs, Stephen Turner, John R. Wallbank, Steven Wells, and Amy Wilcox
Earth Syst. Sci. Data, 15, 2391–2415, https://doi.org/10.5194/essd-15-2391-2023, https://doi.org/10.5194/essd-15-2391-2023, 2023
Short summary
Short summary
The eFLaG dataset is a nationally consistent set of projections of future climate change impacts on hydrology. eFLaG uses the latest available UK climate projections (UKCP18) run through a series of computer simulation models which enable us to produce future projections of river flows, groundwater levels and groundwater recharge. These simulations are designed for use by water resource planners and managers but could also be used for a wide range of other purposes.
Fabian A. Gomez, Sang-Ki Lee, Charles A. Stock, Andrew C. Ross, Laure Resplandy, Samantha A. Siedlecki, Filippos Tagklis, and Joseph E. Salisbury
Earth Syst. Sci. Data, 15, 2223–2234, https://doi.org/10.5194/essd-15-2223-2023, https://doi.org/10.5194/essd-15-2223-2023, 2023
Short summary
Short summary
We present a river chemistry and discharge dataset for 140 rivers in the United States, which integrates information from the Water Quality Database of the US Geological Survey (USGS), the USGS’s Surface-Water Monthly Statistics for the Nation, and the U.S. Army Corps of Engineers. This dataset includes dissolved inorganic carbon and alkalinity, two key properties to characterize the carbonate system, as well as nutrient concentrations, such as nitrate, phosphate, and silica.
Yufang Zhang, Shunlin Liang, Han Ma, Tao He, Qian Wang, Bing Li, Jianglei Xu, Guodong Zhang, Xiaobang Liu, and Changhao Xiong
Earth Syst. Sci. Data, 15, 2055–2079, https://doi.org/10.5194/essd-15-2055-2023, https://doi.org/10.5194/essd-15-2055-2023, 2023
Short summary
Short summary
Soil moisture observations are important for a range of earth system applications. This study generated a long-term (2000–2020) global seamless soil moisture product with both high spatial and temporal resolutions (1 km, daily) using an XGBoost model and multisource datasets. Evaluation of this product against dense in situ soil moisture datasets and microwave soil moisture products showed that this product has reliable accuracy and more complete spatial coverage.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
Short summary
Short summary
As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Rogier van der Velde, Harm-Jan F. Benninga, Bas Retsios, Paul C. Vermunt, and M. Suhyb Salama
Earth Syst. Sci. Data, 15, 1889–1910, https://doi.org/10.5194/essd-15-1889-2023, https://doi.org/10.5194/essd-15-1889-2023, 2023
Short summary
Short summary
From 2009, a network of 20 profile soil moisture and temperature monitoring stations has been operational in the Twente region, east of the Netherlands. In addition, field campaigns have been conducted covering four growing seasons during which soil moisture was measured near 12 monitoring stations. We describe the monitoring network and field campaigns, and we provide an overview of open third-party datasets that may support the use of the Twente datasets.
Jana Erdbrügger, Ilja van Meerveld, Jan Seibert, and Kevin Bishop
Earth Syst. Sci. Data, 15, 1779–1800, https://doi.org/10.5194/essd-15-1779-2023, https://doi.org/10.5194/essd-15-1779-2023, 2023
Short summary
Short summary
Groundwater can respond quickly to precipitation and is the main source of streamflow in most catchments in humid, temperate climates. To better understand shallow groundwater dynamics, we installed a network of groundwater wells in two boreal headwater catchments in Sweden. We recorded groundwater levels in 75 wells for 2 years and sampled the water and analyzed its chemical composition in one summer. This paper describes these datasets.
Oliver Wigmore and Noah P. Molotch
Earth Syst. Sci. Data, 15, 1733–1747, https://doi.org/10.5194/essd-15-1733-2023, https://doi.org/10.5194/essd-15-1733-2023, 2023
Short summary
Short summary
We flew a custom-built drone fitted with visible, near-infrared and thermal cameras every week over a summer season at Niwot Ridge in Colorado's alpine tundra. We processed these images into seamless orthomosaics that record changes in snow cover, vegetation health and the movement of water over the land surface. These novel datasets provide a unique centimetre resolution snapshot of ecohydrologic processes, connectivity and spatial and temporal heterogeneity in the alpine zone.
Martine Lizotte, Bennet Juhls, Atsushi Matsuoka, Philippe Massicotte, Gaëlle Mével, David Obie James Anikina, Sofia Antonova, Guislain Bécu, Marine Béguin, Simon Bélanger, Thomas Bossé-Demers, Lisa Bröder, Flavienne Bruyant, Gwénaëlle Chaillou, Jérôme Comte, Raoul-Marie Couture, Emmanuel Devred, Gabrièle Deslongchamps, Thibaud Dezutter, Miles Dillon, David Doxaran, Aude Flamand, Frank Fell, Joannie Ferland, Marie-Hélène Forget, Michael Fritz, Thomas J. Gordon, Caroline Guilmette, Andrea Hilborn, Rachel Hussherr, Charlotte Irish, Fabien Joux, Lauren Kipp, Audrey Laberge-Carignan, Hugues Lantuit, Edouard Leymarie, Antonio Mannino, Juliette Maury, Paul Overduin, Laurent Oziel, Colin Stedmon, Crystal Thomas, Lucas Tisserand, Jean-Éric Tremblay, Jorien Vonk, Dustin Whalen, and Marcel Babin
Earth Syst. Sci. Data, 15, 1617–1653, https://doi.org/10.5194/essd-15-1617-2023, https://doi.org/10.5194/essd-15-1617-2023, 2023
Short summary
Short summary
Permafrost thaw in the Mackenzie Delta region results in the release of organic matter into the coastal marine environment. What happens to this carbon-rich organic matter as it transits along the fresh to salty aquatic environments is still underdocumented. Four expeditions were conducted from April to September 2019 in the coastal area of the Beaufort Sea to study the fate of organic matter. This paper describes a rich set of data characterizing the composition and sources of organic matter.
Wei Wang, La Zhuo, Xiangxiang Ji, Zhiwei Yue, Zhibin Li, Meng Li, Huimin Zhang, Rong Gao, Chenjian Yan, Ping Zhang, and Pute Wu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-102, https://doi.org/10.5194/essd-2023-102, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
The consumptive water footprint of crop production (WFCP) measures blue and green evapotranspiration of either irrigated or rainfed crops in time and space. A gridded monthly WFCP dataset for China is established. There are four improvements from existing datasets: (i) distinguishing water supply modes and irrigation techniques; (ii) distinguishing evaporation and transpiration; (iii) consisting of both total and unit WFCP, and (iv) providing benchmarks for unit WFCP by climatic zones.
Doerthe Tetzlaff, Aaron Smith, Lukas Kleine, Hauke Daempfling, Jonas Freymueller, and Chris Soulsby
Earth Syst. Sci. Data, 15, 1543–1554, https://doi.org/10.5194/essd-15-1543-2023, https://doi.org/10.5194/essd-15-1543-2023, 2023
Short summary
Short summary
We present a comprehensive set of ecohydrological hydrometric and stable water isotope data of 2 years of data. The data set is unique as the different compartments of the landscape were sampled and the effects of a prolonged drought (2018–2020) captured by a marked negative rainfall anomaly (the most severe regional drought of the 21st century). Thus, the data allow the drought effects on water storage, flux and age dynamics, and persistence of lowland landscapes to be investigated.
Jacopo Dari, Luca Brocca, Sara Modanesi, Christian Massari, Angelica Tarpanelli, Silvia Barbetta, Raphael Quast, Mariette Vreugdenhil, Vahid Freeman, Anaïs Barella-Ortiz, Pere Quintana-Seguí, David Bretreger, and Espen Volden
Earth Syst. Sci. Data, 15, 1555–1575, https://doi.org/10.5194/essd-15-1555-2023, https://doi.org/10.5194/essd-15-1555-2023, 2023
Short summary
Short summary
Irrigation is the main source of global freshwater consumption. Despite this, a detailed knowledge of irrigation dynamics (i.e., timing, extent of irrigated areas, and amounts of water used) are generally lacking worldwide. Satellites represent a useful tool to fill this knowledge gap and monitor irrigation water from space. In this study, three regional-scale and high-resolution (1 and 6 km) products of irrigation amounts estimated by inverting the satellite soil moisture signals are presented.
Gifty Attiah, Homa Kheyrollah Pour, and K. Andrea Scott
Earth Syst. Sci. Data, 15, 1329–1355, https://doi.org/10.5194/essd-15-1329-2023, https://doi.org/10.5194/essd-15-1329-2023, 2023
Short summary
Short summary
Lake surface temperature (LST) is a significant indicator of climate change and influences local weather and climate. This study developed a LST dataset retrieved from Landsat archives for 535 lakes across the North Slave Region, NWT, Canada. The data consist of individual NetCDF files for all observed days for each lake. The North Slave LST dataset will provide communities, scientists, and stakeholders with the changing spatiotemporal trends of LST for the past 38 years (1984–2021).
Shanlei Sun, Zaoying Bi, Jingfeng Xiao, Yi Liu, Ge Sun, Weimin Ju, Chunwei Liu, Mengyuan Mu, Jinjian Li, Yang Zhou, Xiaoyuan Li, Yibo Liu, and Haishan Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-38, https://doi.org/10.5194/essd-2023-38, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
Based on various existing datasets, we comprehensively considered spatio-temporal differences in land surfaces and CO2 effects on plant stomatal resistance to parameterize the Shuttleworth-Wallace model, and generated a global 5 km ensemble mean monthly potential evapotranspiration (PET) dataset (including potential transpiration (PT) and soil evaporation (PE)) during 1982–2015. The new dataset may be used by academic communities and various agencies to conduct various studies.
Aolin Jia, Shunlin Liang, Dongdong Wang, Lei Ma, Zhihao Wang, and Shuo Xu
Earth Syst. Sci. Data, 15, 869–895, https://doi.org/10.5194/essd-15-869-2023, https://doi.org/10.5194/essd-15-869-2023, 2023
Short summary
Short summary
Satellites are now producing multiple global land surface temperature (LST) products; however, they suffer from data gaps caused by cloud cover, seriously restricting the applications, and few products provide gap-free global hourly LST. We produced global hourly, 5 km, all-sky LST data from 2011 to 2021 using geostationary and polar-orbiting satellite data. Based on the assessment, it has high accuracy and can be used to estimate evapotranspiration, drought, etc.
Jianxin Zhang, Kai Liu, and Ming Wang
Earth Syst. Sci. Data, 15, 521–540, https://doi.org/10.5194/essd-15-521-2023, https://doi.org/10.5194/essd-15-521-2023, 2023
Short summary
Short summary
This study successfully extracted global flood days based on gravity satellite and precipitation data between 60° S and 60° N from 1 April 2002 to 31 August 2016. Our flood days data performed well compared with current available observations. This provides an important data foundation for analyzing the spatiotemporal distribution of large-scale floods and exploring the impact of ocean–atmosphere oscillations on floods in different regions.
Niek Jesse Speetjens, Gustaf Hugelius, Thomas Gumbricht, Hugues Lantuit, Wouter R. Berghuijs, Philip A. Pika, Amanda Poste, and Jorien E. Vonk
Earth Syst. Sci. Data, 15, 541–554, https://doi.org/10.5194/essd-15-541-2023, https://doi.org/10.5194/essd-15-541-2023, 2023
Short summary
Short summary
The Arctic is rapidly changing. Outside the Arctic, large databases changed how researchers look at river systems and land-to-ocean processes. We present the first integrated pan-ARctic CAtchments summary DatabasE (ARCADE) (> 40 000 river catchments draining into the Arctic Ocean). It incorporates information about the drainage area with 103 geospatial, environmental, climatic, and physiographic properties and covers small watersheds , which are especially subject to change, at a high resolution
Ionut Cristi Nicu, Letizia Elia, Lena Rubensdotter, Hakan Tanyaş, and Luigi Lombardo
Earth Syst. Sci. Data, 15, 447–464, https://doi.org/10.5194/essd-15-447-2023, https://doi.org/10.5194/essd-15-447-2023, 2023
Short summary
Short summary
Thaw slumps and thermo-erosion gullies are cryospheric hazards that are widely encountered in Nordenskiöld Land, the largest and most compact ice-free area of the Svalbard Archipelago. By statistically analysing the landscape characteristics of locations where these processes occurred, we can estimate where they may occur in the future. We mapped 562 thaw slumps and 908 thermo-erosion gullies and used them to create the first multi-hazard susceptibility map in a high-Arctic environment.
Youjiang Shen, Dedi Liu, Liguang Jiang, Karina Nielsen, Jiabo Yin, Jun Liu, and Peter Bauer-Gottwein
Earth Syst. Sci. Data, 14, 5671–5694, https://doi.org/10.5194/essd-14-5671-2022, https://doi.org/10.5194/essd-14-5671-2022, 2022
Short summary
Short summary
A data gap of 338 Chinese reservoirs with their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) during 2010–2021. Validation against the in situ observations of 93 reservoirs indicates the relatively high accuracy and reliability of the datasets. The unique and novel remotely sensed dataset would benefit studies involving many aspects (e.g., hydrological models, water resources related studies, and more).
Ibrahim Demir, Zhongrun Xiang, Bekir Demiray, and Muhammed Sit
Earth Syst. Sci. Data, 14, 5605–5616, https://doi.org/10.5194/essd-14-5605-2022, https://doi.org/10.5194/essd-14-5605-2022, 2022
Short summary
Short summary
We provide a large benchmark dataset, WaterBench-Iowa, with valuable features for hydrological modeling. This dataset is designed to support cutting-edge deep learning studies for a more accurate streamflow forecast model. We also propose a modeling task for comparative model studies and provide sample models with codes and results as the benchmark for reference. This makes up for the lack of benchmarks in earth science research.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yaoming Ma, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 14, 5513–5542, https://doi.org/10.5194/essd-14-5513-2022, https://doi.org/10.5194/essd-14-5513-2022, 2022
Short summary
Short summary
Soil moisture and soil temperature (SMST) are important state variables for quantifying the heat–water exchange between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements at multiple depths are scarce on the Tibetan Plateau (TP). The presented dataset would be valuable for the evaluation and improvement of long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change.
Jafet C. M. Andersson, Jonas Olsson, Remco (C. Z.) van de Beek, and Jonas Hansryd
Earth Syst. Sci. Data, 14, 5411–5426, https://doi.org/10.5194/essd-14-5411-2022, https://doi.org/10.5194/essd-14-5411-2022, 2022
Short summary
Short summary
This article presents data from three types of sensors for rain measurement, i.e. commercial microwave links (CMLs), gauges, and weather radar. Access to CML data is typically restricted, which limits research and applications. We openly share a large CML database (364 CMLs at 10 s resolution with true coordinates), along with 11 gauges and one radar composite. This opens up new opportunities to study CMLs, to benchmark algorithms, and to investigate how multiple sensors can best be combined.
Qingliang Li, Gaosong Shi, Wei Shangguan, Vahid Nourani, Jianduo Li, Lu Li, Feini Huang, Ye Zhang, Chunyan Wang, Dagang Wang, Jianxiu Qiu, Xingjie Lu, and Yongjiu Dai
Earth Syst. Sci. Data, 14, 5267–5286, https://doi.org/10.5194/essd-14-5267-2022, https://doi.org/10.5194/essd-14-5267-2022, 2022
Short summary
Short summary
SMCI1.0 is a 1 km resolution dataset of daily soil moisture over China for 2000–2020 derived through machine learning trained with in situ measurements of 1789 stations, meteorological forcings, and land surface variables. It contains 10 soil layers with 10 cm intervals up to 100 cm deep. Evaluated by in situ data, the error (ubRMSE) ranges from 0.045 to 0.051, and the correlation (R) range is 0.866-0.893. Compared with ERA5-Land, SMAP-L4, and SoMo.ml, SIMI1.0 has higher accuracy and resolution.
Utkarsh Mital, Dipankar Dwivedi, James B. Brown, and Carl I. Steefel
Earth Syst. Sci. Data, 14, 4949–4966, https://doi.org/10.5194/essd-14-4949-2022, https://doi.org/10.5194/essd-14-4949-2022, 2022
Short summary
Short summary
We present a new dataset that estimates small-scale variations in precipitation and temperature in mountainous terrain. The dataset is generated using a new machine learning framework that extracts relationships between climate and topography from existing coarse-scale datasets. The generated dataset is shown to capture small-scale variations more reliably than existing datasets and constitutes a valuable resource to model the water cycle in the mountains of Colorado, western United States.
Rongzhu Qin, Zeyu Zhao, Jia Xu, Jian-Sheng Ye, Feng-Min Li, and Feng Zhang
Earth Syst. Sci. Data, 14, 4793–4810, https://doi.org/10.5194/essd-14-4793-2022, https://doi.org/10.5194/essd-14-4793-2022, 2022
Short summary
Short summary
This work presents a new high-resolution daily gridded maximum temperature, minimum temperature, and precipitation dataset for China (HRLT) with a spatial resolution of 1 × 1 km for the period 1961 to 2019. This dataset is valuable for crop modelers and climate change studies. We created the HRLT dataset using comprehensive statistical analyses, which included machine learning, the generalized additive model, and thin-plate splines.
Lobke Rotteveel, Franz Heubach, and Shannon M. Sterling
Earth Syst. Sci. Data, 14, 4667–4680, https://doi.org/10.5194/essd-14-4667-2022, https://doi.org/10.5194/essd-14-4667-2022, 2022
Short summary
Short summary
Data are needed to detect environmental problems, find their solutions, and identify knowledge gaps. Existing datasets have limited availability, sample size and/or frequency, or geographic scope. Here, we begin to address these limitations by collecting, cleaning, standardizing, and compiling the Surface Water Chemistry (SWatCh) database. SWatCh contains global surface water chemistry data for seven continents, 24 variables, 33 722 sites, and > 5 million samples collected between 1960 and 2022.
Giuseppe Amatulli, Jaime Garcia Marquez, Tushar Sethi, Jens Kiesel, Afroditi Grigoropoulou, Maria M. Üblacker, Longzhu Q. Shen, and Sami Domisch
Earth Syst. Sci. Data, 14, 4525–4550, https://doi.org/10.5194/essd-14-4525-2022, https://doi.org/10.5194/essd-14-4525-2022, 2022
Short summary
Short summary
Streams and rivers drive several processes in hydrology, geomorphology, geography, and ecology. A hydrographic network that accurately delineates streams and rivers, along with their topographic and topological properties, is needed for environmental applications. Using the MERIT Hydro Digital Elevation Model at 90 m resolution, we derived a globally seamless, standardised hydrographic network: Hydrography90m. The validation demonstrates improved accuracy compared to other datasets.
Yang Liu, Ronggao Liu, and Rong Shang
Earth Syst. Sci. Data, 14, 4505–4523, https://doi.org/10.5194/essd-14-4505-2022, https://doi.org/10.5194/essd-14-4505-2022, 2022
Short summary
Short summary
Surface water has been changing significantly with high seasonal variation and abrupt change, making it hard to capture its interannual trend. Here we generated a global annual surface water cover frequency dataset during 2000–2020. The percentage of the time period when a pixel is covered by water in a year was estimated to describe the seasonal dynamics of surface water. This dataset can be used to analyze the interannual variation and change trend of highly dynamic inland water extent.
Simone Persiano, Alessio Pugliese, Alberto Aloe, Jon Olav Skøien, Attilio Castellarin, and Alberto Pistocchi
Earth Syst. Sci. Data, 14, 4435–4443, https://doi.org/10.5194/essd-14-4435-2022, https://doi.org/10.5194/essd-14-4435-2022, 2022
Short summary
Short summary
For about 24000 river basins across Europe, this study provides a continuous representation of the streamflow regime in terms of empirical flow–duration curves (FDCs), which are key signatures of the hydrological behaviour of a catchment and are widely used for supporting decisions on water resource management as well as for assessing hydrologic change. FDCs at ungauged sites are estimated by means of a geostatistical procedure starting from data observed at about 3000 sites across Europe.
Maartje C. Korver, Emily Haughton, William C. Floyd, and Ian J. W. Giesbrecht
Earth Syst. Sci. Data, 14, 4231–4250, https://doi.org/10.5194/essd-14-4231-2022, https://doi.org/10.5194/essd-14-4231-2022, 2022
Short summary
Short summary
The central coastline of the northeast Pacific coastal temperate rainforest contains many small streams that are important for the ecology of the region but are sparsely monitored. Here we present the first 5 years (2013–2019) of streamflow and weather data from seven small streams, using novel automated methods with estimations of measurement uncertainties. These observations support regional climate change monitoring and provide a scientific basis for environmental management decisions.
Sadaf Nasreen, Markéta Součková, Mijael Rodrigo Vargas Godoy, Ujjwal Singh, Yannis Markonis, Rohini Kumar, Oldrich Rakovec, and Martin Hanel
Earth Syst. Sci. Data, 14, 4035–4056, https://doi.org/10.5194/essd-14-4035-2022, https://doi.org/10.5194/essd-14-4035-2022, 2022
Short summary
Short summary
This article presents a 500-year reconstructed annual runoff dataset for several European catchments. Several data-driven and hydrological models were used to derive the runoff series using reconstructed precipitation and temperature and a set of proxy data. The simulated runoff was validated using independent observed runoff data and documentary evidence. The validation revealed a good fit between the observed and reconstructed series for 14 catchments, which are available for further analysis.
Chunqiao Song, Chenyu Fan, Jingying Zhu, Jida Wang, Yongwei Sheng, Kai Liu, Tan Chen, Pengfei Zhan, Shuangxiao Luo, Chunyu Yuan, and Linghong Ke
Earth Syst. Sci. Data, 14, 4017–4034, https://doi.org/10.5194/essd-14-4017-2022, https://doi.org/10.5194/essd-14-4017-2022, 2022
Short summary
Short summary
Over the last century, many dams/reservoirs have been built globally to meet various needs. The official statistics reported more than 98 000 dams/reservoirs in China. Despite the availability of several global-scale dam/reservoir databases, these databases have insufficient coverage in China. Therefore, we present the China Reservoir Dataset (CRD), which contains 97 435 reservoir polygons. The CRD reservoirs have a total area of 50 085.21 km2 and total storage of about 979.62 Gt.
Guofeng Zhu, Yuwei Liu, Peiji Shi, Wenxiong Jia, Junju Zhou, Yuanfeng Liu, Xinggang Ma, Hanxiong Pan, Yu Zhang, Zhiyuan Zhang, Zhigang Sun, Leilei Yong, and Kailiang Zhao
Earth Syst. Sci. Data, 14, 3773–3789, https://doi.org/10.5194/essd-14-3773-2022, https://doi.org/10.5194/essd-14-3773-2022, 2022
Short summary
Short summary
From 2015 to 2020, we studied the Shiyang River basin, which has the highest utilization rate of water resources and the most prominent contradiction of water use, as a typical demonstration basin to establish and improve the isotope hydrology observation system, including river source region, oasis region, reservoir channel system region, oasis farmland region, ecological engineering construction region, and salinization process region.
Junzhi Liu, Pengcheng Fang, Yefeng Que, Liang-Jun Zhu, Zheng Duan, Guoan Tang, Pengfei Liu, Mukan Ji, and Yongqin Liu
Earth Syst. Sci. Data, 14, 3791–3805, https://doi.org/10.5194/essd-14-3791-2022, https://doi.org/10.5194/essd-14-3791-2022, 2022
Short summary
Short summary
The management and conservation of lakes should be conducted in the context of catchments because lakes collect water and materials from their upstream catchments. This study constructed the first dataset of lake-catchment characteristics for 1525 lakes with an area from 0.2 to 4503 km2 on the Tibetan Plateau (TP), which provides exciting opportunities for lake studies in a spatially explicit context and promotes the development of landscape limnology on the TP.
Pia Ebeling, Rohini Kumar, Stefanie R. Lutz, Tam Nguyen, Fanny Sarrazin, Michael Weber, Olaf Büttner, Sabine Attinger, and Andreas Musolff
Earth Syst. Sci. Data, 14, 3715–3741, https://doi.org/10.5194/essd-14-3715-2022, https://doi.org/10.5194/essd-14-3715-2022, 2022
Short summary
Short summary
Environmental data are critical for understanding and managing ecosystems, including the mitigation of water quality degradation. To increase data availability, we present the first large-sample water quality data set (QUADICA) of riverine macronutrient concentrations combined with water quantity, meteorological, and nutrient forcing data as well as catchment attributes. QUADICA covers 1386 German catchments to facilitate large-sample data-driven and modeling water quality assessments.
Wei Wan, Jie Zhang, Liyun Dai, Hong Liang, Ting Yang, Baojian Liu, Zhizhou Guo, Heng Hu, and Limin Zhao
Earth Syst. Sci. Data, 14, 3549–3571, https://doi.org/10.5194/essd-14-3549-2022, https://doi.org/10.5194/essd-14-3549-2022, 2022
Short summary
Short summary
The GSnow-CHINA data set is a snow depth data set developed using the two Global Navigation Satellite System station networks in China. It includes snow depth of 24, 12, and 2/3/6 h records, if possible, for 80 sites from 2013–2022 over northern China (25–55° N, 70–140° E). The footprint of the data set is ~ 1000 m2, and it can be used as an independent data source for validation purposes. It is also useful for regional climate research and other meteorological and hydrological applications.
Liyun Dai, Tao Che, Yang Zhang, Zhiguo Ren, Junlei Tan, Meerzhan Akynbekkyzy, Lin Xiao, Shengnan Zhou, Yuna Yan, Yan Liu, Hongyi Li, and Lifu Wang
Earth Syst. Sci. Data, 14, 3509–3530, https://doi.org/10.5194/essd-14-3509-2022, https://doi.org/10.5194/essd-14-3509-2022, 2022
Short summary
Short summary
An Integrated Microwave Radiometry Campaign for Snow (IMCS) was conducted to collect ground-based passive microwave and optical remote-sensing data, snow pit and underlying soil data, and meteorological parameters. The dataset is unique in continuously providing electromagnetic and physical features of snowpack and environment. The dataset is expected to serve the evaluation and development of microwave radiative transfer models and snow process models, along with land surface process models.
Linan Guo, Hongxing Zheng, Yanhong Wu, Lanxin Fan, Mengxuan Wen, Junsheng Li, Fangfang Zhang, Liping Zhu, and Bing Zhang
Earth Syst. Sci. Data, 14, 3411–3422, https://doi.org/10.5194/essd-14-3411-2022, https://doi.org/10.5194/essd-14-3411-2022, 2022
Short summary
Short summary
Lake surface water temperature (LSWT) is a critical physical property of the aquatic ecosystem and an indicator of climate change. By combining the strengths of satellites and models, we produced an integrated dataset on daily LSWT of 160 large lakes across the Tibetan Plateau (TP) for the period 1978–2017. LSWT increased significantly at a rate of 0.01–0.47° per 10 years. The dataset can contribute to research on water and heat balance changes and their ecological effects in the TP.
Cited articles
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.
Bao, X. and Zhang, F.: Evaluation of NCEP–CFSR, NCEP–NCAR, ERA-Interim,
and ERA-40 reanalysis datasets against independent sounding observations
over the Tibetan Plateau, J. Climate, 26, 206–214,
https://doi.org/10.1175/JCLI-D-12-00056.1, 2013.
Beaudoing, H. and Rodell, M.: GLDAS Noah Land Surface Model L4 3 hourly 0.25 × 0.25 degree V2.1, Goddard Earth Sciences Data and Information Services
Center (GES DISC) [data set], https://doi.org/10.5067/E7TYRXPJKWOQ, 2020.
Bengtsson, L. and Shukla, J.: Integration of space and in situ observations
to study global climate change, B. Am. Meteorol. Soc., 69, 1130–1143,
https://doi.org/10.1175/1520-0477(1988)069<1130:IOSAIS>2.0.CO;2, 1988.
Bonan, G. B., Patton, E. G., Finnigan, J. J., Baldocchi, D. D., and Harman,
I. N.: Moving beyond the incorrect but useful paradigm: reevaluating
big-leaf and multilayer plant canopies to model biosphere-atmosphere
fluxes – a review, Agric. For. Meteorol., 306, 108435,
https://doi.org/10.1017/aju.2017.9, 2021.
Cao, M., Wang, W., Xing, W., Wei, J., Chen, X., Li, J., and Shao, Q.:
Multiple sources of uncertainties in satellite retrieval of terrestrial
actual evapotranspiration, J. Hydrol., 601, 126642,
https://doi.org/10.1016/j.jhydrol.2021.126642, 2021.
Cao, Q., Liu, Y., Sun, X., and Yang, L.: Country-level evaluation of solar
radiation data sets using ground measurements in China, Energy, 241, 122938,
https://doi.org/10.1016/j.energy.2021.122938, 2022.
Carter, C. and Liang, S.: Comprehensive evaluation of empirical algorithms
for estimating land surface evapotranspiration, Agric. For. Meteorol., 256,
334–345, https://doi.org/10.1016/j.agrformet.2018.03.027, 2018.
Chen, M., Senay, G. B., Singh, R. K., and Verdin, J. P.: Uncertainty
analysis of the Operational Simplified Surface Energy Balance (SSEBop) model
at multiple flux tower sites, J. Hydrol., 536, 384–399,
https://doi.org/10.1016/j.jhydrol.2016.02.026, 2016.
Chen, X., Su, Z., Ma, Y., Trigo, I., and Gentine, P.: Remote Sensing of
Global Daily Evapotranspiration based on a Surface Energy Balance Method and
Reanalysis Data, J. Geophys. Res.-Atmos., 126, e2020JD032873,
https://doi.org/10.1029/2020JD032873, 2021.
Cheng, M., Jiao, X., Li, B., Yu, X., Shao, M., and Jin, X.: Long time series of daily evapotranspiration in China based on the SEBAL model and multisource images and validation, Earth Syst. Sci. Data, 13, 3995–4017, https://doi.org/10.5194/essd-13-3995-2021, 2021.
Cleugh, H. A., Leuning, R., Mu, Q., and Running, S. W.: Regional evaporation
estimates from flux tower and MODIS satellite data, Remote Sens. Environ.,
106, 285–304, https://doi.org/10.1016/j.rse.2006.07.007, 2007.
Didan, K.: MOD13C2 MODIS/Terra Vegetation Indices Monthly L3 Global 0.05Deg
CMG V006. NASA EOSDIS Land Processes DAAC [data set],
https://doi.org/10.5067/MODIS/MOD13C2.006, 2015.
Elnashar, A., Wang, L., Wu, B., Zhu, W., and Zeng, H.: Synthesis of global actual evapotranspiration from 1982 to 2019, Earth Syst. Sci. Data, 13, 447–480, https://doi.org/10.5194/essd-13-447-2021, 2021.
Ershadi, A., McCabe, M., Evans, J., and Wood, E. F.: Impact of model
structure and parameterization on Penman–Monteith type evaporation models,
J. Hydrol., 525, 521–535, https://doi.org/10.1016/j.jhydrol.2015.04.008,
2015.
Fisher, J. B., Melton, F., Middleton, E., Hain, C., Anderson, M., Allen, R.,
McCabe, M. F., Hook, S., Baldocchi, D., and Townsend, P. A.: The future of
evapotranspiration: Global requirements for ecosystem functioning, carbon
and climate feedbacks, agricultural management, and water resources, Water
Resour. Res., 53, 2618–2626, https://doi.org/10.1002/2016WR020175, 2017.
Fu, X. and Wang, B.: Reliability evaluation of soil moisture and land
surface temperature simulated by Global Land Data Assimilation System
(GLDAS) using AMSR-E data, Remote Sensing and Modeling of the Atmosphere,
Oceans, and Interactions V, 92650O, https://doi.org/10.1117/12.2074566,
2014.
Guo, H., Liang, D., Chen, F., and Shirazi, Z.: Innovative approaches to the
Sustainable Development Goals using Big Earth Data, Big Earth Data, 5,
263–276, https://doi.org/10.1080/20964471.2021.1939989, 2021.
Guo, X., Liu, H., and Yang, K.: On the application of the Priestley–Taylor
relation on sub-daily time scales, Bound.-Lay. Meteorol., 156, 489–499,
https://doi.org/10.1007/s10546-015-0031-y, 2015.
Han, C., Ma, Y., Wang, B., Zhong, L., Ma, W., Chen, X., and Su, Z.: Long-term variations in actual evapotranspiration over the Tibetan Plateau, Earth Syst. Sci. Data, 13, 3513–3524, https://doi.org/10.5194/essd-13-3513-2021, 2021.
He, M., Kimball, J. S., Yi, Y., Running, S. W., Guan, K., Moreno, A., Wu,
X., and Maneta, M.: Satellite data-driven modeling of field scale
evapotranspiration in croplands using the MOD16 algorithm framework, Remote
Sens. Environ., 230, 111201, https://doi.org/10.1016/j.rse.2019.05.020,
2019.
IPCC: Summary for Policymakers, in: Climate Change 2022: Impacts,
Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth
Assessment Report of the Intergovernmental Panel on Climate Change, edited
by: Pörtner, H.-O., Roberts, D. C., Tignor, M., Poloczanska, E. S.,
Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S.,
Möller, V., Okem, A., and Rama, B., Cambridge University Press, 3–33, https://doi.org/10.1017/9781009325844.001, 2022.
Ji, L., Senay, G. B., and Verdin, J. P.: Evaluation of the Global Land Data
Assimilation System (GLDAS) air temperature data products, J.
Hydrometeorol., 16, 2463–2480, https://doi.org/10.1175/JHM-D-14-0230.1,
2015.
Jiang, C. and Ryu, Y.: Multi-scale evaluation of global gross primary
productivity and evapotranspiration products derived from Breathing Earth
System Simulator (BESS), Remote Sens. Environ., 186, 528–547,
https://doi.org/10.1016/j.rse.2016.08.030, 2016.
Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., Camps-Valls, G.,
Papale, D., Schwalm, C., Tramontana, G., and Reichstein, M.: The FLUXCOM
ensemble of global land-atmosphere energy fluxes, Sci. Data, 6, 1–14,
https://doi.org/10.1038/s41597-019-0076-8, 2019.
Khan, M. S., Liaqat, U. W., Baik, J., and Choi, M.: Stand-alone uncertainty
characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using
an extended triple collocation approach, Agric. For. Meteorol., 252,
256–268, https://doi.org/10.1016/j.agrformet.2018.01.022, 2018.
Kim, S., Anabalón, A., and Sharma, A.: An assessment of concurrency in
evapotranspiration trends across multiple global datasets, J.
Hydrometeorol., 22, 231–244, https://doi.org/10.1175/JHM-D-20-0059.1, 2021.
Komatsu, H.: Forest categorization according to dry-canopy evaporation rates
in the growing season: comparison of the Priestley–Taylor coefficient
values from various observation sites, Hydrol. Process., 19, 3873–3896,
https://doi.org/10.1002/hyp.5987, 2005.
Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World map of
the Köppen-Geiger climate classification updated, Meteorol. Z., 15,
259–263, https://doi.org/10.1127/0941-2948/2006/0130, 2006.
Lhomme, J.-P., Monteny, B., and Amadou, M.: Estimating sensible heat flux
from radiometric temperature over sparse millet, Agric. For. Meteorol., 68,
77–91, https://doi.org/10.1016/0168-1923(94)90070-1, 1994.
Liu, W., Wang, L., Zhou, J., Li, Y., Sun, F., Fu, G., Li, X., and Sang,
Y.-F.: A worldwide evaluation of basin-scale evapotranspiration estimates
against the water balance method, J. Hydrol., 538, 82–95,
https://doi.org/10.1016/j.jhydrol.2016.04.006, 2016.
Liu, Y., Liu, Y., and Wang, W.: Inter-comparison of satellite-retrieved and
Global Land Data Assimilation System-simulated soil moisture datasets for
global drought analysis, Remote Sens. Environ., 220, 1–18,
https://doi.org/10.1016/j.rse.2018.10.026, 2019.
Liu, Y., Qiu, G. Y., Zhang, H., Yang, Y., Zhang, Y., Wang, Q., Zhao, W.,
Jia, L., Ji, X., Xiong, Y., Yan, C., Ma, N., Han, S., and Cui, Y.: Shifting
from homogeneous to heterogeneous surfaces in estimating terrestrial
evapotranspiration: Review and perspectives, Sci. China Earth Sci., 65,
197–214, https://doi.org/10.1007/s11430-020-9834-y, 2022.
Ma, N., Szilagyi, J., and Zhang, Y.: Calibration-free complementary
relationship estimates terrestrial evapotranspiration globally, Water
Resour. Res., 57, e2021WR029691, https://doi.org/10.1029/2021WR029691, 2021.
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017.
Medici, C., Wade, A. J., and Frances, F.: Does increased hydrochemical model
complexity decrease robustness?, J. Hydrol., 440, 1–13,
https://doi.org/10.1016/j.jhydrol.2012.02.047, 2012.
Melton, F. S., Huntington, J., Grimm, R., Herring, J., Hall, M., Rollison, D., Erickson, T., Allen, R., Anderson, M., Fisher, J. B., Kilic, A., Senay, G. B., Volk, J., Hain, C., Johnson, L., Ruhoff, A., Blankenau, P., Bromley, M., Carrara, W., Daudert, B., Doherty, C., Dunkerly, C., Friedrichs, M., Guzman, A., Halverson, G., Hansen, J., Harding, J., Kang, Y., Ketchum, D., Minor, B., Morton, C., Ortega-Salazar, S., Ott, T., Ozdogan, M., ReVelle, P. M., Schull, M., Wang, C., Yang, Y., and Anderson, R. G.: OpenET: Filling a critical data gap in water management for the western United States, JAWRA J. Am. Water Resour. Assoc., 1–24, https://doi.org/10.1111/1752-1688.12956, 2021.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
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 Fernández-Prieto, D.: The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets, Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, 2016.
Mu, Q., Zhao, M., and Running, S. W.: Improvements to a MODIS global
terrestrial evapotranspiration algorithm, Remote Sens. Environ., 115,
1781–1800, https://doi.org/10.1016/j.rse.2011.02.019, 2011.
Mu, Q., Heinsch, F. A., Zhao, M., and Running, S. W.: Development of a
global evapotranspiration algorithm based on MODIS and global meteorology
data, Remote Sens. Environ., 111, 519–536,
https://doi.org/10.1016/j.rse.2007.04.015, 2007.
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.
Peng, X., She, J., Zhang, S., Tan, J., and Li, Y.: Evaluation of
multi-reanalysis solar radiation products using global surface observations,
Atmosphere, 10, 42, https://doi.org/10.3390/atmos10020042, 2019.
Peng, Z., Tang, R., Jiang, Y., and Liu, M.: Global Daily 500-M
Evapotranspiration Estimation Over Vegetated Areas Using Rnadom Forest from
MODIS Data, 2021 IEEE International Geoscience and Remote Sensing Symposium
IGARSS, 3733–3736, https://doi.org/10.1109/IGARSS47720.2021.9554153, 2021.
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, https://doi.org/10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2, 1972.
Qiu, G. Y.: A new method for estimation of evapotranspiration, PhD thesis,
The united graduate school of agricultural sciences, Tottori University,
Japan, 1996.
Qiu, G. Y., Ben-Asher, J., Yano, T., and Momii, K.: Estimation of soil
evaporation using the differential temperature method, Soil Sci. Soc. Am.
J., 63, 1608–1614, https://doi.org/10.2136/sssaj1999.6361608x, 1999.
Qiu, G. Y., Yu, X., Wen, H., and Yan, C.: An advanced approach for measuring
the transpiration rate of individual urban trees by the 3D three-temperature
model and thermal infrared remote sensing, J. Hydrol., 587, 125034,
https://doi.org/10.1016/j.jhydrol.2020.125034, 2020.
Raupach, M. R. and Finnigan, J.: Single-layer models of evaporation from
plant canopies are incorrect but useful, whereas multilayer models are
correct but useless: discuss, Aust. J. Plant Physiol., 15, 705–716,
https://doi.org/10.1071/PP9880705, 1988.
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J.,
Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L., and Kim, G.-K.:
MERRA: NASA's modern-era retrospective analysis for research and
applications, J. Climate, 24, 3624–3648,
https://doi.org/10.1175/JCLI-D-11-00015.1, 2011.
Rodell, M., Houser, P., Jambor, U., Gottschalck, J., Mitchell, K., Meng,
C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., and Bosilovich, M.: The
global land data assimilation system, B. Am. Meteorol. Soc., 85, 381–394,
https://doi.org/10.1175/BAMS-85-3-381, 2004.
Schneider, U., Becker, A., Finger, P., Rustemeier, E., and Ziese, M.: GPCC
Full Data Monthly Product Version 2020 at 0.25∘: Monthly Land-Surface
Precipitation from Rain-Gauges Built on GTS-Based and Historical Data,
Global Precipitation Climatology Centre (GPCC) at Deutscher Wetterdienst
[data set], https://doi.org/10.5676/DWD_GPCC/FD_M_V2020_025, 2020.
Senay, G. B., Kagone, S., and Velpuri, N. M.: Operational global actual
evapotranspiration: development, evaluation, and dissemination, Sensors, 20,
1915, https://doi.org/10.3390/s20071915, 2020.
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.
Tian, F., Qiu, G. Y., Yang, Y., Lü, Y., and Xiong, Y.: Estimation of
evapotranspiration and its partition based on an extended three-temperature
model and MODIS products, J. Hydrol., 498, 210–220,
https://doi.org/10.1016/j.jhydrol.2013.06.038, 2013.
Trenberth, K. E., Fasullo, J. T., and Kiehl, J.: Earth's global energy
budget, B. Am. Meteorol. Soc., 90, 311–324,
https://doi.org/10.1175/2008BAMS2634.1, 2009.
Trenberth, K. E., Smith, L., Qian, T., Dai, A., and Fasullo, J.: Estimates
of the global water budget and its annual cycle using observational and
model data, J. Hydrometeorol., 8, 758–769, https://doi.org/10.1175/JHM600.1,
2007.
UNEP (United Nations Environment Programme): World Atlas of Desertification: Second Edition, Arnold Publications, Great Britain, https://wedocs.unep.org/20.500.11822/30300 (last access: 27 September 2021), 1997.
Vinukollu, R. K., Wood, E. F., Ferguson, C. R., and Fisher, J. B.: Global
estimates of evapotranspiration for climate studies using multi-sensor
remote sensing data: Evaluation of three process-based approaches, Remote
Sens. Environ., 115, 801–823, https://doi.org/10.1016/j.rse.2010.11.006,
2011.
Wang, Y., Xiong, Y., Qiu, G. Y., and Zhang, Q.: Is scale really a challenge
in evapotranspiration estimation? A multi-scale study in the Heihe oasis
using thermal remote sensing and the three-temperature model, Agric. For.
Meteorol., 230, 128–141, https://doi.org/10.1016/j.agrformet.2016.03.012,
2016.
Watkins, M. M., Wiese, D. N., Yuan, D. N., Boening, C., and Landerer, F. W.:
Improved methods for observing Earth's time variable mass distribution with
GRACE using spherical cap mascons, J. Geophys. Res.-Sol. Ea., 120,
2648–2671, https://doi.org/10.1002/2014JB011547, 2015.
Wu, G., Cai, X., Keenan, T. F., Li, S., Luo, X., Fisher, J. B., Cao, R., Li,
F., Purdy, A. J., and Zhao, W.: Evaluating three evapotranspiration
estimates from model of different complexity over China using the ILAMB
benchmarking system, J. Hydrol., 590, 125553,
https://doi.org/10.1016/j.jhydrol.2020.125553, 2020.
Xia, Y., Fu, C., Wu, H., Wu, H., Zhang, H., Cao, Y., and Zhu, Z.: Influences
of Extreme Events on Water and Carbon Cycles of Cropland Ecosystems: A
Comprehensive Exploration Combining Site and Global Modeling, Water Resour.
Res., 57, e2021WR029884, https://doi.org/10.1029/2021WR029884, 2021.
Xiong, Y. and Qiu, G. Y.: Estimation of evapotranspiration using remotely
sensed land surface temperature and the revised three-temperature model,
Int. J. Remote Sens., 32, 5853–5874,
https://doi.org/10.1080/01431161.2010.507791, 2011.
Xiong, Y. and Qiu, G. Y.: Simplifying the revised three-temperature model
for remotely estimating regional evapotranspiration and its application to a
semi-arid steppe, Int. J. Remote Sens., 35, 2003–2027,
https://doi.org/10.1080/01431161.2014.885149, 2014.
Xiong, Y., Yu, L., Qiu, G. Y., Yan, C., Zhao, W., Zou, Z., Ding, J., and Qin, L.: A global terrestrial evapotranspiration product based on
three-temperature model from 2001 to 2020 (Version V2), Science Data Bank
[data set], https://doi.org/10.57760/sciencedb.o00014.00001, 2022.
Xiong, Y., Zhao, S., Tian, F., and Qiu, G. Y.: An evapotranspiration product
for arid regions based on the three-temperature model and thermal remote
sensing, J. Hydrol., 530, 392–404,
https://doi.org/10.1016/j.jhydrol.2015.09.050, 2015.
Xiong, Y., Zhao, W., Wang, P., Paw U, K. T., and Qiu, G. Y.: Simple and
applicable method for estimating evapotranspiration and its components in
arid regions, J. Geophys. Res.: Atmos., 124, 9963–9982,
https://doi.org/10.1029/2019JD030774, 2019.
Xu, W., Sun, C., Zuo, J., Ma, Z., Li, W., and Yang, S.: Homogenization of
monthly ground surface temperature in China during 1961–2016 and
performances of GLDAS reanalysis products, J. Climate, 32, 1121–1135,
https://doi.org/10.1175/JCLI-D-18-0275.1, 2019.
Yang, Y., Liu, Y., Li, M., Hu, Z., and Ding, Z.: Assessment of reanalysis
flux products based on eddy covariance observations over the Tibetan
Plateau, Theor. Appl. Climatol., 138, 275–292,
https://doi.org/10.1007/s00704-019-02811-1, 2019.
Yao, Y., Liang, S., Cheng, J., Liu, S., Fisher, J. B., Zhang, X., Jia, K.,
Zhao, X., Qin, Q., Zhao, B., Han, S., Zhou, G., Zhou, G., Li, Y., and Zhao,
S.: MODIS-driven estimation of terrestrial latent heat flux in China based
on a modified Priestley–Taylor algorithm, Agric. For. Meteorol., 171–172,
187–202, https://doi.org/10.1016/j.agrformet.2012.11.016,
2013.
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,
https://doi.org/10.1002/2013JD020864, 2014.
Yao, Y., Liang, S., Li, X., Chen, J., Wang, K., Jia, K., Cheng, J., Jiang,
B., Fisher, J. B., Mu, Q., Grünwald, T., Bernhofer, C., and Roupsard,
O.: A satellite-based hybrid algorithm to determine the Priestley–Taylor
parameter for global terrestrial latent heat flux estimation across multiple
biomes, Remote Sens. Environ., 165, 216–233,
https://doi.org/10.1016/j.rse.2015.05.013, 2015.
Yao, Y., Liang, S., Li, X., Zhang, Y., Chen, J., Jia, K., Zhang, X., Fisher,
J. B., Wang, X., and Zhang, L.: Estimation of high-resolution terrestrial
evapotranspiration from Landsat data using a simple Taylor skill fusion
method, J. Hydrol., 553, 508–526,
https://doi.org/10.1016/j.jhydrol.2017.08.013, 2017.
Zeng, Z., Wang, T., Zhou, F., Ciais, P., Mao, J., Shi, X., and Piao, S.: A
worldwide analysis of spatiotemporal changes in water balance-based
evapotranspiration from 1982 to 2009, J. Geophys. Res.-Atmos., 119,
1186–1202, https://doi.org/10.1002/2013JD020941, 2014.
Zhang, K., Kimball, J. S., Nemani, R. R., Running, S. W., Hong, Y., Gourley,
J. J., and Yu, Z.: Vegetation greening and climate change promote
multidecadal rises of global land evapotranspiration, Sci. Rep.-UK, 5, 1–9,
https://doi.org/10.1038/srep15956, 2015.
Zhang, K., Kimball, J. S., and Running, S. W.: A review of remote sensing
based actual evapotranspiration estimation, Wiley Interdisciplinary
Reviews-Water, 3, 834–853, https://doi.org/10.1002/wat2.1168, 2016.
Zhang, X., Liang, S., Wang, G., Yao, Y., Jiang, B., and Cheng, J.:
Evaluation of the reanalysis surface incident shortwave radiation products
from NCEP, ECMWF, GSFC, and JMA using satellite and surface observations,
Remote Sens., 8, 225, https://doi.org/10.3390/rs8030225, 2016.
Zhang, Y., Kong, D., Gan, R., Chiew, F. H., McVicar, T. R., Zhang, Q., and
Yang, Y.: Coupled estimation of 500 m and 8-day resolution global
evapotranspiration and gross primary production in 2002–2017, Remote Sens.
Environ., 222, 165–182, https://doi.org/10.1016/j.rse.2018.12.031, 2019.
Zhao, W., Qiu, G. Y., Xiong, Y., Paw U, K. T., Gentine, P., and Chen, B.:
Uncertainties caused by resistances in evapotranspiration estimation using
high-density eddy covariance measurements, J. Hydrometeorol., 21, 1349–1365,
https://doi.org/10.1175/JHM-D-19-0191.1, 2020.
Zhou, C., Wang, K., and Ma, Q.: Evaluation of eight current reanalyses in
simulating land surface temperature from 1979 to 2003 in China, J. Climate,
30, 7379–7398, https://doi.org/10.1175/JCLI-D-16-0903.1, 2017.
Short summary
Accurate evapotranspiration (ET) estimation is essential to better understand Earth’s energy and water cycles. We estimate global terrestrial ET with a simple three-temperature model, without calibration and resistance parameterization requirements. Results show the ET estimates agree well with FLUXNET EC data, water balance ET, and other global ET products. The proposed daily and 0.25° ET product from 2001 to 2020 could provide large-scale information to support water-cycle-related studies.
Accurate evapotranspiration (ET) estimation is essential to better understand Earth’s energy...
Altmetrics
Final-revised paper
Preprint