Articles | Volume 13, issue 9
Data description paper
07 Sep 2021
Data description paper | 07 Sep 2021
Development of observation-based global multilayer soil moisture products for 1970 to 2016
Yaoping Wang et al.
No articles found.
Rachael E. McCaully, Carli A. Arendt, Brent D. Newman, Verity G. Salmon, Jeffrey M. Heikoop, Cathy J. Wilson, Sanna Sevanto, Nathan A. Wales, George B. Perkins, Oana C. Marina, and Stan D. Wullschleger
The Cryosphere, 16, 1889–1901,Short summary
Degrading permafrost and shrub expansion are critically important to tundra biogeochemistry. We observed significant variability in soil pore water NO3-N in an alder-dominated permafrost hillslope in Alaska. Proximity to alder shrubs and the presence or absence of topographic gradients and precipitation events strongly influence NO3-N availability and mobility. The highly dynamic nature of labile N on small spatiotemporal scales has implications for nutrient responses to a warming Arctic.
Nathan Alec Conroy, Jeffrey Heikoop, Emma Lathrop, Dea Musa, Brent Newman, Chonggang Xu, Rachael McCaully, Carli Arendt, Verity Salmon, Amy Breen, Vladimir Romanovsky, Katrina Bennett, Cathy Wilson, and Stan Wullschleger
This study combines field observations, non-parametric statistical analyses, and thermodynamic modeling to characterize the environmental causes of the spatial variability in soil pore water solute concentrations across two Arctic catchments with varying extents of permafrost. Vegetation type, soil moisture and redox conditions, weathering and hydrologic transport, and mineral solubility were all found to be the primary drivers of the existing spatial variability of some soil pore water solutes.
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P. M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Earth Syst. Sci. Data, 13, 2607–2649,Short summary
Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
sapfluxnetrwill facilitate new data syntheses on the ecological factors driving water use and drought responses of trees and forests.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293,Short summary
We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Xiaoying Shi, Daniel M. Ricciuto, Peter E. Thornton, Xiaofeng Xu, Fengming Yuan, Richard J. Norby, Anthony P. Walker, Jeffrey M. Warren, Jiafu Mao, Paul J. Hanson, Lin Meng, David Weston, and Natalie A. Griffiths
Biogeosciences, 18, 467–486,Short summary
The Sphagnum mosses are the important species of a wetland ecosystem. To better represent the peatland ecosystem, we introduced the moss species to the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. We tested the model against field observations and used the model to make projections of the site's carbon cycle under warming and atmospheric CO2 concentration scenarios.
Nathan A. Wales, Jesus D. Gomez-Velez, Brent D. Newman, Cathy J. Wilson, Baptiste Dafflon, Timothy J. Kneafsey, Florian Soom, and Stan D. Wullschleger
Hydrol. Earth Syst. Sci., 24, 1109–1129,Short summary
Rapid warming in the Arctic is causing increased permafrost temperatures and ground ice degradation. To study the effects of ice degradation on water distribution, tracer was applied to two end members of ice-wedge polygons – a ubiquitous landform in the Arctic. End member type was found to significantly affect water distribution as lower flux was observed with ice-wedge degradation. Results suggest ice degradation can influence partitioning of sequestered carbon as carbon dioxide or methane.
Binghao Jia, Xin Luo, Ximing Cai, Atul Jain, Deborah N. Huntzinger, Zhenghui Xie, Ning Zeng, Jiafu Mao, Xiaoying Shi, Akihiko Ito, Yaxing Wei, Hanqin Tian, Benjamin Poulter, Dan Hayes, and Kevin Schaefer
Earth Syst. Dynam., 11, 235–249,Short summary
We quantitatively examined the relative contributions of climate change, land use and land cover change, and elevated CO2 to interannual variations and seasonal cycle amplitude of gross primary productivity (GPP) in China based on multi-model ensemble simulations. The contributions of major subregions to the temporal change in China's total GPP are also presented. This work may help us better understand GPP spatiotemporal patterns and their responses to regional changes and human activities.
Yongjiu Dai, Wei Shangguan, Nan Wei, Qinchuan Xin, Hua Yuan, Shupeng Zhang, Shaofeng Liu, Xingjie Lu, Dagang Wang, and Fapeng Yan
SOIL, 5, 137–158,Short summary
Soil data are widely used in various Earth science fields. We reviewed soil property maps for Earth system models, which can also offer insights to soil data developers and users. Old soil datasets are often based on limited observations and have various uncertainties. Updated and comprehensive soil data are made available to the public and can benefit related research. Good-quality soil data are identified and suggestions on how to improve and use them are provided.
Jianqiu Zheng, Peter E. Thornton, Scott L. Painter, Baohua Gu, Stan D. Wullschleger, and David E. Graham
Biogeosciences, 16, 663–680,Short summary
Arctic warming exposes soil carbon to increased degradation, increasing CO2 and CH4 emissions. Models underrepresent anaerobic decomposition that predominates wet soils. We simulated microbial growth, pH regulation, and anaerobic carbon decomposition in a new model, parameterized and validated with prior soil incubation data. The model accurately simulated CO2 production and strong influences of water content, pH, methanogen biomass, and competing electron acceptors on CH4 production.
Qinchuan Xin, Yongjiu Dai, and Xiaoping Liu
Biogeosciences, 16, 467–484,Short summary
Terrestrial biosphere models that simulate both leaf dynamics and canopy photosynthesis are required to understand vegetation–climate interactions. A time-stepping scheme is proposed to simulate leaf area index, phenology, and gross primary production via climate variables. The method performs well on simulating deciduous broadleaf forests across the eastern United States; it provides a simplified and improved version of the growing production day model for use in land surface modeling.
Donghai Wu, Philippe Ciais, Nicolas Viovy, Alan K. Knapp, Kevin Wilcox, Michael Bahn, Melinda D. Smith, Sara Vicca, Simone Fatichi, Jakob Zscheischler, Yue He, Xiangyi Li, Akihiko Ito, Almut Arneth, Anna Harper, Anna Ukkola, Athanasios Paschalis, Benjamin Poulter, Changhui Peng, Daniel Ricciuto, David Reinthaler, Guangsheng Chen, Hanqin Tian, Hélène Genet, Jiafu Mao, Johannes Ingrisch, Julia E. S. M. Nabel, Julia Pongratz, Lena R. Boysen, Markus Kautz, Michael Schmitt, Patrick Meir, Qiuan Zhu, Roland Hasibeder, Sebastian Sippel, Shree R. S. Dangal, Stephen Sitch, Xiaoying Shi, Yingping Wang, Yiqi Luo, Yongwen Liu, and Shilong Piao
Biogeosciences, 15, 3421–3437,Short summary
Our results indicate that most ecosystem models do not capture the observed asymmetric responses under normal precipitation conditions, suggesting an overestimate of the drought effects and/or underestimate of the watering impacts on primary productivity, which may be the result of inadequate representation of key eco-hydrological processes. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.
Reindert J. Haarsma, Malcolm J. Roberts, Pier Luigi Vidale, Catherine A. Senior, Alessio Bellucci, Qing Bao, Ping Chang, Susanna Corti, Neven S. Fučkar, Virginie Guemas, Jost von Hardenberg, Wilco Hazeleger, Chihiro Kodama, Torben Koenigk, L. Ruby Leung, Jian Lu, Jing-Jia Luo, Jiafu Mao, Matthew S. Mizielinski, Ryo Mizuta, Paulo Nobre, Masaki Satoh, Enrico Scoccimarro, Tido Semmler, Justin Small, and Jin-Song von Storch
Geosci. Model Dev., 9, 4185–4208,Short summary
Recent progress in computing power has enabled climate models to simulate more processes in detail and on a smaller scale. Here we present a common protocol for these high-resolution runs that will foster the analysis and understanding of the impact of model resolution on the simulated climate. These runs will also serve as a more reliable source for assessing climate risks that are associated with small-scale weather phenomena such as tropical cyclones.
Bart van den Hurk, Hyungjun Kim, Gerhard Krinner, Sonia I. Seneviratne, Chris Derksen, Taikan Oki, Hervé Douville, Jeanne Colin, Agnès Ducharne, Frederique Cheruy, Nicholas Viovy, Michael J. Puma, Yoshihide Wada, Weiping Li, Binghao Jia, Andrea Alessandri, Dave M. Lawrence, Graham P. Weedon, Richard Ellis, Stefan Hagemann, Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, and Justin Sheffield
Geosci. Model Dev., 9, 2809–2832,Short summary
This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
J. Mao, D. M. Ricciuto, P. E. Thornton, J. M. Warren, A. W. King, X. Shi, C. M. Iversen, and R. J. Norby
Biogeosciences, 13, 641–657,Short summary
The aim of this study is to implement, calibrate and evaluate the CLM4 against carbon and hydrology observations from a shading and labeling experiment in a stand of young loblolly pines. We found a combination of parameters measured on-site and calibration targeting biomass, transpiration, and 13C discrimination gave good agreement with pretreatment measurements. We also used observations from the experiment to develop a conceptual model of short-term photosynthate storage and transport.
X. Shi, P. E. Thornton, D. M. Ricciuto, P. J. Hanson, J. Mao, S. D. Sebestyen, N. A. Griffiths, and G. Bisht
Biogeosciences, 12, 6463–6477,
W. D. Collins, A. P. Craig, J. E. Truesdale, A. V. Di Vittorio, A. D. Jones, B. Bond-Lamberty, K. V. Calvin, J. A. Edmonds, S. H. Kim, A. M. Thomson, P. Patel, Y. Zhou, J. Mao, X. Shi, P. E. Thornton, L. P. Chini, and G. C. Hurtt
Geosci. Model Dev., 8, 2203–2219,Short summary
The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human-climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. By introducing heretofore-omitted feedbacks between natural and societal drivers in iESM, we can improve scientific understanding of the human-Earth system dynamics.
Y. Wei, S. Liu, D. N. Huntzinger, A. M. Michalak, N. Viovy, W. M. Post, C. R. Schwalm, K. Schaefer, A. R. Jacobson, C. Lu, H. Tian, D. M. Ricciuto, R. B. Cook, J. Mao, and X. Shi
Geosci. Model Dev., 7, 2875–2893,
A. V. Di Vittorio, L. P. Chini, B. Bond-Lamberty, J. Mao, X. Shi, J. Truesdale, A. Craig, K. Calvin, A. Jones, W. D. Collins, J. Edmonds, G. C. Hurtt, P. Thornton, and A. Thomson
Biogeosciences, 11, 6435–6450,Short summary
Economic models provide scenarios of land use and greenhouse gas emissions to earth system models to project global change. We found, and partially addressed, inconsistencies in land cover between an economic and an earth system model that effectively alter a prescribed scenario, causing significant differences in projected terrestrial carbon and atmospheric CO2 between prescribed and altered scenarios. We outline a solution to this current problem in scenario-based global change projections.
B. Bond-Lamberty, K. Calvin, A. D. Jones, J. Mao, P. Patel, X. Y. Shi, A. Thomson, P. Thornton, and Y. Zhou
Geosci. Model Dev., 7, 2545–2555,
D. N. Huntzinger, C. Schwalm, A. M. Michalak, K. Schaefer, A. W. King, Y. Wei, A. Jacobson, S. Liu, R. B. Cook, W. M. Post, G. Berthier, D. Hayes, M. Huang, A. Ito, H. Lei, C. Lu, J. Mao, C. H. Peng, S. Peng, B. Poulter, D. Riccuito, X. Shi, H. Tian, W. Wang, N. Zeng, F. Zhao, and Q. Zhu
Geosci. Model Dev., 6, 2121–2133,
Related subject area
Hydrology and Soil Science – HydrologyConcentrations and fluxes of suspended particulate matter and associated contaminants in the Rhône River from Lake Geneva to the Mediterranean SeaA global drought dataset of standardized moisture anomaly index incorporating snow dynamics (SZIsnow) and its application in identifying large-scale drought eventsRiver network and hydro-geomorphological parameters at 1∕12° resolution for global hydrological and climate studiesIntegrated hydrogeological and hydrogeochemical dataset of an alpine catchment in the northern Qinghai–Tibet PlateauGeoDAR: georeferenced global dams and reservoirs dataset for bridging attributes and geolocationsSpatial and seasonal patterns of water isotopes in northeastern German lakesA new dataset of river flood hazard maps for Europe and the Mediterranean BasinCOSMOS-Europe: a European network of cosmic-ray neutron soil moisture sensorsDistribution and characteristics of wastewater treatment plants within the global river networkCorrecting Thornthwaite potential evapotranspiration using a global grid of local coefficients to support temperature-based estimations of reference evapotranspiration and aridity indicesA 1-km daily surface soil moisture dataset of enhanced coverage under all-weather conditions over China in 2003–2019Soil moisture observation in a forested headwater catchment: combining a dense cosmic-ray neutron sensor network with roving and hydrogravimetry at the TERENO site WüstebachCCAM: China Catchment Attributes and Meteorology datasetA high-accuracy rainfall dataset by merging multiple satellites and dense gauges over the southern Tibetan Plateau for 2014–2019 warm seasonsBaseline data for monitoring geomorphological effects of glacier lake outburst flood: a very-high-resolution image and GIS datasets of the distal part of the Zackenberg River, northeast GreenlandMineral, thermal and deep groundwater of Hesse, GermanyLamaH-CE: LArge-SaMple DAta for Hydrology and Environmental Sciences for Central EuropeA year of attenuation data from a commercial dual-polarized duplex microwave link with concurrent disdrometer, rain gauge, and weather observationsRosalia: an experimental research site to study hydrological processes in a forest catchmentLong time series of daily evapotranspiration in China based on the SEBAL model and multisource images and validationCAMELS-AUS: hydrometeorological time series and landscape attributes for 222 catchments in AustraliaA multi-source 120-year US flood database with a unified common format and public accessC-band radar data and in situ measurements for the monitoring of wheat crops in a semi-arid area (center of Morocco)The three-dimensional groundwater salinity distribution and fresh groundwater volumes in the Mekong Delta, Vietnam, inferred from geostatistical analysesA national topographic dataset for hydrological modeling over the contiguous United StatesStatus of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009–2019) surface soil moisture datasetCLIGEN parameter regionalization for mainland ChinaYear-long, broad-band, microwave backscatter observations of an alpine meadow over the Tibetan Plateau with a ground-based scatterometerSTH-net: a soil monitoring network for process-based hydrological modelling from the pedon to the hillslope scaleComprehensive bathymetry and intertidal topography of the Amazon estuaryVirtual water trade and water footprint of agricultural goods: the 1961–2016 CWASI databaseHistorical cartographic and topo-bathymetric database on the French Rhône River (17th–20th century)COSMOS-UK: national soil moisture and hydrometeorology data for environmental science researchSoilKsatDB: global database of soil saturated hydraulic conductivity measurements for geoscience applicationsADHI: the African Database of Hydrometric Indices (1950–2018)Dynamics of shallow wakes on gravel-bed floodplains: dataset from field experimentsTwo decades of distributed global radiation time series across a mountainous semiarid area (Sierra Nevada, Spain)Inventory of dams in GermanyCountry-level and gridded estimates of wastewater production, collection, treatment and reuseDataset of Georeferenced Dams in South America (DDSA)The impact of landscape evolution on soil physics: evolution of soil physical and hydraulic properties along two chronosequences of proglacial morainesThe CH-IRP data set: a decade of fortnightly data on δ2H and δ18O in streamflow and precipitation in SwitzerlandCAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great BritainA dense network of cosmic-ray neutron sensors for soil moisture observation in a highly instrumented pre-Alpine headwater catchment in GermanyCAMELS-BR: hydrometeorological time series and landscape attributes for 897 catchments in BrazilGloFAS-ERA5 operational global river discharge reanalysis 1979–presentA Canadian River Ice Database from the National Hydrometric Program ArchivesAn integration of gauge, satellite, and reanalysis precipitation datasets for the largest river basin of the Tibetan PlateauTowards harmonisation of image velocimetry techniques for river surface velocity observationsAIMERG: a new Asian precipitation dataset (0.1°/half-hourly, 2000–2015) by calibrating the GPM-era IMERG at a daily scale using APHRODITE
Hugo Lepage, Alexandra Gruat, Fabien Thollet, Jérôme Le Coz, Marina Coquery, Matthieu Masson, Aymeric Dabrin, Olivier Radakovitch, Jérôme Labille, Jean-Paul Ambrosi, Doriane Delanghe, and Patrick Raimbault
Earth Syst. Sci. Data, 14, 2369–2384,Short summary
The dataset contains concentrations and fluxes of suspended particle matter (SPM) and several particle-bound contaminants along the Rhône River downstream of Lake Geneva. These data allow us to understand the dynamics and origins. They show the impact of flood events which mainly contribute to a decrease in the contaminant concentrations while fluxes are significant. On the contrary, concentrations are higher during low flow periods probably due to the increase of organic matter.
Lei Tian, Baoqing Zhang, and Pute Wu
Earth Syst. Sci. Data, 14, 2259–2278,Short summary
We propose a global monthly drought dataset with a resolution of 0.25° from 1948 to 2010 based on a multitype and multiscalar drought index, the standardized moisture anomaly index adding snow processes (SZIsnow). The consideration of snow processes improved its capability, and the improvement is prominent over snow-covered high-latitude and high-altitude areas. This new dataset is well suited to monitoring, assessing, and characterizing drought and is a valuable resource for drought studies.
Simon Munier and Bertrand Decharme
Earth Syst. Sci. Data, 14, 2239–2258,Short summary
This paper presents a new global-scale river network at 1/12°, generated automatically and assessed over the 69 largest basins of the world. A set of hydro-geomorphological parameters are derived at the same spatial resolution, including a description of river stretches (length, slope, width, roughness, bankfull depth), floodplains (roughness, sub-grid topography) and aquifers (transmissivity, porosity, sub-grid topography). The dataset may be useful for hydrology modelling or climate studies.
Zhao Pan, Rui Ma, Ziyong Sun, Yalu Hu, Qixin Chang, Mengyan Ge, Shuo Wang, Jianwei Bu, Xiang Long, Yanxi Pan, and Lusong Zhao
Earth Syst. Sci. Data, 14, 2147–2165,Short summary
We drilled four sets of cluster wells and monitored groundwater level and temperature at different depths in an alpine catchment, northern Tibet plateau. The chemical and isotopic compositions of different waters, including stream water, glacier/snow meltwater, soil water, spring, and groundwater from boreholes, were measured for 6 years. The data can be used to study the impact of soil freeze-thaw process and permafrost degradation on the groundwater flow and its interaction with surface water.
Jida Wang, Blake A. Walter, Fangfang Yao, Chunqiao Song, Meng Ding, Abu Sayeed Maroof, Jingying Zhu, Chenyu Fan, Jordan M. McAlister, Safat Sikder, Yongwei Sheng, George H. Allen, Jean-François Crétaux, and Yoshihide Wada
Earth Syst. Sci. Data, 14, 1869–1899,Short summary
Improved water infrastructure data on dams and reservoirs remain to be critical to hydrologic modeling, energy planning, and environmental conservation. We present a new global dataset, GeoDAR, that includes nearly 25 000 georeferenced dam points and their associated reservoir boundaries. A majority of these features can be linked to the register of the International Commission on Large Dams, extending the potential of registered attribute information for spatially explicit applications.
Bernhard Aichner, David Dubbert, Christine Kiel, Katrin Kohnert, Igor Ogashawara, Andreas Jechow, Sarah-Faye Harpenslager, Franz Hölker, Jens Christian Nejstgaard, Hans-Peter Grossart, Gabriel Singer, Sabine Wollrab, and Stella Angela Berger
Earth Syst. Sci. Data, 14, 1857–1867,Short summary
Water isotopes were measured along transects and in the form of time series in northeastern German lakes. The spatial patterns within the data and their seasonal variability are related to morphological and hydrological properties of the studied lake systems. They are further useful for the understanding of biogeochemical and ecological characteristics of these lakes.
Francesco Dottori, Lorenzo Alfieri, Alessandra Bianchi, Jon Skoien, and Peter Salamon
Earth Syst. Sci. Data, 14, 1549–1569,Short summary
We present a set of hazard maps for river flooding for Europe and the Mediterranean basin. The maps depict inundation extent and depth for flood probabilities for up to 1-in-500-year flood hazards and are based on hydrological and hydrodynamic models driven by observed climatology. The maps can identify two-thirds of the flood extent reported by official flood maps, with increasing skill for higher-magnitude floods. The maps are used for evaluating present and future impacts of river floods.
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151,Short summary
Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, Günther Grill, Jing Li, Antonio Limtong, and Ranish Shakya
Earth Syst. Sci. Data, 14, 559–577,Short summary
We introduce HydroWASTE, a spatially explicit global database of 58 502 wastewater treatment plants (WWTPs) and their characteristics to understand the impact of discharges from such facilities. HydroWASTE was developed by compiling regional datasets and using auxiliary information to complete missing characteristics. The location of the outfall of the WWTPs into the river system is also included, allowing for the identification of the waterbodies most likely affected.
Vassilis Aschonitis, Dimos Touloumidis, Marie-Claire ten Veldhuis, and Miriam Coenders-Gerrits
Earth Syst. Sci. Data, 14, 163–177,Short summary
This work provides a global database of correction coefficients for improving the performance of the temperature-based Thornthwaite potential evapotranspiration formula and aridity indices (e.g., UNEP, Thornthwaite) that make use of this formula. The coefficients were produced using as a benchmark the ASCE-standardized reference evapotranspiration formula (formerly FAO-56) that requires temperature, solar radiation, wind speed, and relative humidity data.
Peilin Song, Yongqiang Zhang, Jianping Guo, Jiancheng Shi, Tianjie Zhao, and Bing Tong
Earth Syst. Sci. Data Discuss.,
Revised manuscript accepted for ESSDShort summary
Soil moisture information is cruicial for understanding the earth surface, but currently available satellite-based soil moisture datasets are imperfect either in their spatio-temporal resolutions or in esnuring image completeness from cloudy weather. In this study, therefore, we developed one soil moisture data product over China that has tackled most of the above problems. This data product has great potential to promote investigation on earth hydrology and to be extended to the global scale.
Maik Heistermann, Heye Bogena, Till Francke, Andreas Güntner, Jannis Jakobi, Daniel Rasche, Martin Schrön, Veronika Döpper, Benjamin Fersch, Jannis Groh, Amol Patil, Thomas Pütz, Marvin Reich, Steffen Zacharias, Carmen Zengerle, and Sascha Oswald
Earth Syst. Sci. Data Discuss.,
Revised manuscript accepted for ESSDShort summary
This paper presents a dense network of Cosmic Ray Neutron Sensors (CRNS) to measure spatiotemporal soil moisture patterns during a two month campaign in the Wüstebach headwater catchment in Germany. Stationary, mobile, and airborne CRNS technology monitored the root-zone water dynamics as well as spatial heterogeneity in the 0.4 km2 area. The 15 CRNS stations were supported by a hydrogravimeter, extensive biomass sampling, and a dense TDT network to facilitate holistic hydrological analysis.
Zhen Hao, Jin Jin, Runliang Xia, Shimin Tian, Wushuang Yang, Qixing Liu, Min Zhu, Tao Ma, Chengran Jing, and Yanning Zhang
Earth Syst. Sci. Data, 13, 5591–5616,Short summary
CCAM is proposed to promote large-sample hydrological research in China. The first catchment attribute dataset and catchment-scale meteorological time series dataset in China are built. We also built HydroMLYR, a hydrological dataset with standardized streamflow observations supporting machine learning modeling. The open-source code producing CCAM supports the calculation of custom watersheds.
Kunbiao Li, Fuqiang Tian, Mohd Yawar Ali Khan, Ran Xu, Zhihua He, Long Yang, Hui Lu, and Yingzhao Ma
Earth Syst. Sci. Data, 13, 5455–5467,Short summary
Due to complex climate and topography, there is still a lack of a high-quality rainfall dataset for hydrological modeling over the Tibetan Plateau. This study aims to establish a high-accuracy daily rainfall product over the southern Tibetan Plateau through merging satellite rainfall estimates based on a high-density rainfall gauge network. Statistical and hydrological evaluation indicated that the new dataset outperforms the raw satellite estimates and several other products of similar types.
Aleksandra M. Tomczyk and Marek W. Ewertowski
Earth Syst. Sci. Data, 13, 5293–5309,Short summary
We collected detailed (cm-scale) topographical data to illustrate how a single flood event can modify river landscape in the high-Arctic setting of Zackenberg Valley, NE Greenland. The studied flood was a result of an outburst from a glacier-dammed lake. We used drones to capture images immediately before, during, and after the flood for the 2 km long section of the river. Data can be used for monitoring and modelling of flood events and assessment of geohazards for Zackenberg Research Station.
Rafael Schäffer, Kristian Bär, Sebastian Fischer, Johann-Gerhard Fritsche, and Ingo Sass
Earth Syst. Sci. Data, 13, 4847–4860,Short summary
Knowledge of groundwater properties is relevant, e.g. for drinking-water supply, spas or geothermal energy. We compiled 1035 groundwater datasets from 560 springs or wells sampled since 1810, using mainly publications, supplemented by personal communication and our own measurements. The data can help address spatial–temporal variation in groundwater composition, uncertainties in groundwater property prediction, deep groundwater movement, or groundwater characteristics like temperature and age.
Christoph Klingler, Karsten Schulz, and Mathew Herrnegger
Earth Syst. Sci. Data, 13, 4529–4565,Short summary
LamaH-CE is a large-sample catchment hydrology dataset for Central Europe. The dataset contains hydrometeorological time series (daily and hourly resolution) and various attributes for 859 gauged basins. Sticking closely to the CAMELS datasets, LamaH includes additional basin delineations and attributes for describing a large interconnected river network. LamaH further contains outputs of a conceptual hydrological baseline model for plausibility checking of the inputs and for benchmarking.
Anna Špačková, Vojtěch Bareš, Martin Fencl, Marc Schleiss, Joël Jaffrain, Alexis Berne, and Jörg Rieckermann
Earth Syst. Sci. Data, 13, 4219–4240,Short summary
An original dataset of microwave signal attenuation and rainfall variables was collected during 1-year-long field campaign. The monitored 38 GHz dual-polarized commercial microwave link with a short sampling resolution (4 s) was accompanied by five disdrometers and three rain gauges along its path. Antenna radomes were temporarily shielded for approximately half of the campaign period to investigate antenna wetting impacts.
Josef Fürst, Hans Peter Nachtnebel, Josef Gasch, Reinhard Nolz, Michael Paul Stockinger, Christine Stumpp, and Karsten Schulz
Earth Syst. Sci. Data, 13, 4019–4034,Short summary
Rosalia is a 222 ha forested research watershed in eastern Austria to study water, energy and solute transport processes. The paper describes the site, monitoring network, instrumentation and the datasets: high-resolution (10 min interval) time series starting in 2015 of four discharge gauging stations, seven rain gauges, and observations of air and water temperature, relative humidity, and conductivity, as well as soil water content and temperature, at different depths at four profiles.
Minghan Cheng, Xiyun Jiao, Binbin Li, Xun Yu, Mingchao Shao, and Xiuliang Jin
Earth Syst. Sci. Data, 13, 3995–4017,Short summary
Evapotranspiration (ET) is a key node linking surface water and energy balance. Satellite observations of ET have been widely used for water resources management in China. In this study, an ET product with high spatiotemporal resolution was generated using a surface energy balance algorithm and multisource remote sensing data. The generated ET product can be used for geoscience studies, especially global change, water resources management, and agricultural drought monitoring, for example.
Keirnan J. A. Fowler, Suwash Chandra Acharya, Nans Addor, Chihchung Chou, and Murray C. Peel
Earth Syst. Sci. Data, 13, 3847–3867,Short summary
This paper presents the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS comprises data for 222 unregulated catchments with long-term monitoring, combining hydrometeorological time series (streamflow and 18 climatic variables) with 134 attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. It is freely downloadable from https://doi.pangaea.de/10.1594/PANGAEA.921850.
Zhi Li, Mengye Chen, Shang Gao, Jonathan J. Gourley, Tiantian Yang, Xinyi Shen, Randall Kolar, and Yang Hong
Earth Syst. Sci. Data, 13, 3755–3766,Short summary
This dataset is a compilation of multi-sourced flood records, retrieved from official reports, instruments, and crowdsourcing data since 1900. This study utilizes the flood database to analyze flood seasonality within major basins and socioeconomic impacts over time. It is anticipated that this dataset can support a variety of flood-related research, such as validation resources for hydrologic models, hydroclimatic studies, and flood vulnerability analysis across the United States.
Nadia Ouaadi, Jamal Ezzahar, Saïd Khabba, Salah Er-Raki, Adnane Chakir, Bouchra Ait Hssaine, Valérie Le Dantec, Zoubair Rafi, Antoine Beaumont, Mohamed Kasbani, and Lionel Jarlan
Earth Syst. Sci. Data, 13, 3707–3731,Short summary
In this paper, a radar remote sensing database composed of processed Sentinel-1 products and field measurements of soil and vegetation characteristics, weather data, and irrigation water inputs is described. The data set was collected over 3 years (2016–2019) in three drip-irrigated wheat fields in the center of Morocco. It is dedicated to radar data analysis over vegetated surface including the retrieval of soil and vegetation characteristics.
Jan L. Gunnink, Hung Van Pham, Gualbert H. P. Oude Essink, and Marc F. P. Bierkens
Earth Syst. Sci. Data, 13, 3297–3319,Short summary
In the Mekong Delta (Vietnam) groundwater is important for domestic, agricultural and industrial use. Increased pumping of groundwater has caused land subsidence and increased the risk of salinization, thereby endangering the livelihood of the population in the delta. We made a model of the salinity of the groundwater by integrating different sources of information and determined fresh groundwater volumes. The resulting model can be used by researchers and policymakers.
Jun Zhang, Laura E. Condon, Hoang Tran, and Reed M. Maxwell
Earth Syst. Sci. Data, 13, 3263–3279,Short summary
Existing national topographic datasets for the US may not be compatible with gridded hydrologic models. A national topographic dataset developed to support physically based hydrologic models at 1 km and 250 m over the contiguous US is provided. We used a Priority Flood algorithm to ensure hydrologically consistent drainage networks and evaluated the performance with an integrated hydrologic model. Datasets and scripts are available for direct data usage or modification of processing as desired.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 13, 3075–3102,Short summary
This paper reports on the status of the Tibet-Obs and presents a 10-year (2009–2019) surface soil moisture (SM) dataset produced based on in situ measurements taken at a depth of 5 cm collected from the Tibet-Obs. This surface SM dataset includes the original 15 min in situ measurements collected by multiple SM monitoring sites of three networks (i.e. the Maqu, Naqu, and Ngari networks) and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks.
Wenting Wang, Shuiqing Yin, Bofu Yu, and Shaodong Wang
Earth Syst. Sci. Data, 13, 2945–2962,Short summary
A gridded input dataset at a 10 km resolution of a weather generator, CLIGEN, was established for mainland China. Based on this, CLIGEN can generate a series of daily temperature, solar radiation, precipitation data, and rainfall intensity information. In each grid, the input file contains 13 groups of parameters. All parameters were first calculated based on long-term observations and then interpolated by universal kriging. The accuracy of the gridded input dataset has been fully assessed.
Jan G. Hofste, Rogier van der Velde, Jun Wen, Xin Wang, Zuoliang Wang, Donghai Zheng, Christiaan van der Tol, and Zhongbo Su
Earth Syst. Sci. Data, 13, 2819–2856,Short summary
The dataset reported in this paper concerns the measurement of microwave reflections from an alpine meadow over the Tibetan Plateau. These microwave reflections were measured continuously over 1 year. With it, variations in soil water content due to evaporation, precipitation, drainage, and soil freezing/thawing can be seen. A better understanding of the effects aforementioned processes have on microwave reflections may improve methods for estimating soil water content used by satellites.
Edoardo Martini, Matteo Bauckholt, Simon Kögler, Manuel Kreck, Kurt Roth, Ulrike Werban, Ute Wollschläger, and Steffen Zacharias
Earth Syst. Sci. Data, 13, 2529–2539,Short summary
We present the in situ data available from the soil monitoring network
STH-net, recently implemented at the Schäfertal Hillslope site (Germany). The STH-net provides data (soil water content, soil temperature, water level, and meteorological variables – measured at a 10 min interval since 1 January 2019) for developing and testing modelling approaches in the context of vadose zone hydrology at spatial scales ranging from the pedon to the hillslope.
Alice César Fassoni-Andrade, Fabien Durand, Daniel Moreira, Alberto Azevedo, Valdenira Ferreira dos Santos, Claudia Funi, and Alain Laraque
Earth Syst. Sci. Data, 13, 2275–2291,Short summary
We present a seamless dataset of river, land, and ocean topography of the Amazon River estuary with a 30 m spatial resolution. An innovative remote sensing approach was used to estimate the topography of the intertidal flats, riverbanks, and adjacent floodplains. Amazon River bathymetry was generated from digitized nautical charts. The novel dataset opens up a broad range of opportunities, providing the poorly known underwater digital topography required for environmental sciences.
Stefania Tamea, Marta Tuninetti, Irene Soligno, and Francesco Laio
Earth Syst. Sci. Data, 13, 2025–2051,Short summary
The database includes water footprint and virtual water trade data for 370 agricultural goods in all countries, starting from 1961 and 1986, respectively. Data improve upon earlier datasets because of the annual variability of data and the tracing of goods’ origin within the international trade. The CWASI database aims at supporting national and global assessments of water use in agriculture and food production/consumption and welcomes contributions from the research community.
Fanny Arnaud, Lalandy Sehen Chanu, Jules Grillot, Jérémie Riquier, Hervé Piégay, Dad Roux-Michollet, Georges Carrel, and Jean-Michel Olivier
Earth Syst. Sci. Data, 13, 1939–1955,Short summary
This article provides a database of 350 cartographic and topographic resources on the 530-km-long French Rhône River, compiled from the 17th to mid-20th century in 14 national, regional, and departmental archive services. The database has several potential applications in geomorphology, retrospective hydraulic modelling, historical ecology, and sustainable river management and restoration, as well as permitting comparisons of channel changes with other human-impacted rivers worldwide.
Hollie M. Cooper, Emma Bennett, James Blake, Eleanor Blyth, David Boorman, Elizabeth Cooper, Jonathan Evans, Matthew Fry, Alan Jenkins, Ross Morrison, Daniel Rylett, Simon Stanley, Magdalena Szczykulska, Emily Trill, Vasileios Antoniou, Anne Askquith-Ellis, Lucy Ball, Milo Brooks, Michael A. Clarke, Nicholas Cowan, Alexander Cumming, Philip Farrand, Olivia Hitt, William Lord, Peter Scarlett, Oliver Swain, Jenna Thornton, Alan Warwick, and Ben Winterbourn
Earth Syst. Sci. Data, 13, 1737–1757,Short summary
COSMOS-UK is a UK network of environmental monitoring sites, with a focus on measuring field-scale soil moisture. Each site includes soil and hydrometeorological sensors providing data including air temperature, humidity, net radiation, neutron counts, snow water equivalent, and potential evaporation. These data can provide information for science, industry, and agriculture by improving existing understanding and data products in fields such as water resources, space sciences, and biodiversity.
Surya Gupta, Tomislav Hengl, Peter Lehmann, Sara Bonetti, and Dani Or
Earth Syst. Sci. Data, 13, 1593–1612,
Yves Tramblay, Nathalie Rouché, Jean-Emmanuel Paturel, Gil Mahé, Jean-François Boyer, Ernest Amoussou, Ansoumana Bodian, Honoré Dacosta, Hamouda Dakhlaoui, Alain Dezetter, Denis Hughes, Lahoucine Hanich, Christophe Peugeot, Raphael Tshimanga, and Patrick Lachassagne
Earth Syst. Sci. Data, 13, 1547–1560,Short summary
This dataset provides a set of hydrometric indices for about 1500 stations across Africa with daily discharge data. These indices represent mean flow characteristics and extremes (low flows and floods), allowing us to study the long-term evolution of hydrology in Africa and support the modeling efforts that aim at reducing the vulnerability of African countries to hydro-climatic variability.
Oleksandra O. Shumilova, Alexander N. Sukhodolov, George S. Constantinescu, and Bruce J. MacVicar
Earth Syst. Sci. Data, 13, 1519–1529,Short summary
Obstructions (vegetation and/or boulders) located on a riverbed alter flow structure and affect riverbed morphology and biodiversity. We studied flow dynamics around obstructions by carrying out experiments in a gravel-bed river. Flow rates, size, submergence and solid fractions of the obstructions were varied in a set of 30 experimental runs, in which high-resolution patterns of mean and turbulent flow were obtained. For an introduction to the experiments see: https://youtu.be/5wXjvzqxONI.
Cristina Aguilar, Rafael Pimentel, and María J. Polo
Earth Syst. Sci. Data, 13, 1335–1359,Short summary
This work presents the reconstruction of 19 years of daily, monthly, and annual global radiation maps in Sierra Nevada (Spain) derived using daily historical records from weather stations in the area and a modeling scheme that captures the topographic effects that constitute the main sources of the spatial and temporal variability of solar radiation. The generated datasets are valuable in different fields, such as hydrology, ecology, or energy production systems downstream.
Gustavo Andrei Speckhann, Heidi Kreibich, and Bruno Merz
Earth Syst. Sci. Data, 13, 731–740,Short summary
Dams are an important element of water resources management. Data about dams are crucial for practitioners, scientists, and policymakers. We present the most comprehensive open-access dam inventory for Germany to date. The inventory combines multiple sources of information. It comprises 530 dams with information on name, location, river, start year of construction and operation, crest length, dam height, lake area, lake volume, purpose, dam structure, and building characteristics.
Edward R. Jones, Michelle T. H. van Vliet, Manzoor Qadir, and Marc F. P. Bierkens
Earth Syst. Sci. Data, 13, 237–254,Short summary
Continually improving and affordable wastewater management provides opportunities for both pollution reduction and clean water supply augmentation. This study provides a global outlook on the state of domestic and industrial wastewater production, collection, treatment and reuse. Our results can serve as a baseline in evaluating progress towards policy goals (e.g. Sustainable Development Goals) and as input data in large-scale water resource assessments (e.g. water quality modelling).
Bolivar Paredes-Beltran, Alvaro Sordo-Ward, and Luis Garrote
Earth Syst. Sci. Data, 13, 213–229,Short summary
We present a dataset of 1010 entries of dams in South America describing several attributes such as the dams' names, characteristics, purposes, georeferenced locations and also relevant data on the dams' catchments. Information was obtained from extensive research through numerous sources and then validated individually. With this work we expect to contribute to the development of new research in the region, which to date has been limited to certain basins due to the absence of information.
Anne Hartmann, Markus Weiler, and Theresa Blume
Earth Syst. Sci. Data, 12, 3189–3204,Short summary
Our analysis of soil physical and hydraulic properties across two soil chronosequences of 10 millennia in the Swiss Alps provides important observation of the evolution of soil hydraulic behavior. A strong co-evolution of soil physical and hydraulic properties was revealed by the observed change of fast-draining coarse-textured soils to slow-draining soils with a high water-holding capacity in correlation with a distinct change in structural properties and organic matter content.
Maria Staudinger, Stefan Seeger, Barbara Herbstritt, Michael Stoelzle, Jan Seibert, Kerstin Stahl, and Markus Weiler
Earth Syst. Sci. Data, 12, 3057–3066,Short summary
The data set CH-IRP provides isotope composition in precipitation and streamflow from 23 Swiss catchments, being unique regarding its long-term multi-catchment coverage along an alpine–pre-alpine gradient. CH-IRP contains fortnightly time series of stable water isotopes from streamflow grab samples complemented by time series in precipitation. Sampling conditions, catchment and climate information, lab standards and errors are provided together with areal precipitation and catchment boundaries.
Gemma Coxon, Nans Addor, John P. Bloomfield, Jim Freer, Matt Fry, Jamie Hannaford, Nicholas J. K. Howden, Rosanna Lane, Melinda Lewis, Emma L. Robinson, Thorsten Wagener, and Ross Woods
Earth Syst. Sci. Data, 12, 2459–2483,Short summary
We present the first large-sample catchment hydrology dataset for Great Britain. The dataset collates river flows, catchment attributes, and catchment boundaries for 671 catchments across Great Britain. We characterise the topography, climate, streamflow, land cover, soils, hydrogeology, human influence, and discharge uncertainty of each catchment. The dataset is publicly available for the community to use in a wide range of environmental and modelling analyses.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309,
Vinícius B. P. Chagas, Pedro L. B. Chaffe, Nans Addor, Fernando M. Fan, Ayan S. Fleischmann, Rodrigo C. D. Paiva, and Vinícius A. Siqueira
Earth Syst. Sci. Data, 12, 2075–2096,Short summary
We present a new dataset for large-sample hydrological studies in Brazil. The dataset encompasses daily observed streamflow from 3679 gauges, as well as meteorological forcing for 897 selected catchments. It also includes 65 attributes covering topographic, climatic, hydrologic, land cover, geologic, soil, and human intervention variables. CAMELS-BR is publicly available and will enable new insights into the hydrological behavior of catchments in Brazil.
Shaun Harrigan, Ervin Zsoter, Lorenzo Alfieri, Christel Prudhomme, Peter Salamon, Fredrik Wetterhall, Christopher Barnard, Hannah Cloke, and Florian Pappenberger
Earth Syst. Sci. Data, 12, 2043–2060,Short summary
A new river discharge reanalysis dataset is produced operationally by coupling ECMWF's latest global atmospheric reanalysis, ERA5, with the hydrological modelling component of the Global Flood Awareness System (GloFAS). The GloFAS-ERA5 reanalysis is a global gridded dataset with a horizontal resolution of 0.1° at a daily time step and is freely available from 1979 until near real time. The evaluation against observations shows that the GloFAS-ERA5 reanalysis was skilful in 86 % of catchments.
Laurent de Rham, Yonas Dibike, Spyros Beltaos, Daniel Peters, Barrie Bonsal, and Terry Prowse
Earth Syst. Sci. Data, 12, 1835–1860,Short summary
This paper describes the Canadian River Ice Database. Water level recordings at a network of 196 National Hydrometric Program gauging sites over the period 1894–2015 were reviewed. This database, of nearly 73 000 recorded variables and over 460 000 data entries, includes the timing and magnitude of fall freeze-up, midwinter break-up, winter minimum, ice thickness, spring break-up and maximum open-water levels. These data cover the range of river types and climate regions for Canada.
Yuanwei Wang, Lei Wang, Xiuping Li, Jing Zhou, and Zhidan Hu
Earth Syst. Sci. Data, 12, 1789–1803,Short summary
This article is to provide a better precipitation product for the largest river basin of the Tibetan Plateau, the upper Brahmaputra River basin, suitable for use in hydrological simulations and other climate change studies. We integrate gauge, satellite, and reanalysis precipitation datasets to generate a new dataset. The new product has been rigorously validated at various temporal and spatial scales with gauge precipitation observations as well as in cryosphere hydrological simulations.
Matthew T. Perks, Silvano Fortunato Dal Sasso, Alexandre Hauet, Elizabeth Jamieson, Jérôme Le Coz, Sophie Pearce, Salvador Peña-Haro, Alonso Pizarro, Dariia Strelnikova, Flavia Tauro, James Bomhof, Salvatore Grimaldi, Alain Goulet, Borbála Hortobágyi, Magali Jodeau, Sabine Käfer, Robert Ljubičić, Ian Maddock, Peter Mayr, Gernot Paulus, Lionel Pénard, Leigh Sinclair, and Salvatore Manfreda
Earth Syst. Sci. Data, 12, 1545–1559,Short summary
We present datasets acquired from seven countries across Europe and North America consisting of image sequences. These have been subjected to a range of pre-processing methods in preparation for image velocimetry analysis. These datasets and accompanying reference data are a resource that may be used for conducting benchmarking experiments, assessing algorithm performances, and focusing future software development.
Ziqiang Ma, Jintao Xu, Siyu Zhu, Jun Yang, Guoqiang Tang, Yuanjian Yang, Zhou Shi, and Yang Hong
Earth Syst. Sci. Data, 12, 1525–1544,Short summary
Focusing on the potential drawbacks in generating the state-of-the-art IMERG data in both the TRMM and GPM era, a new daily calibration algorithm on IMERG was proposed, as well as a new AIMERG precipitation dataset (0.1°/half-hourly, 2000–2015, Asia) with better quality than IMERG for Asian scientific research and applications. The proposed daily calibration algorithm for GPM is promising and applicable in generating the future IMERG in either an operational scheme or a retrospective manner.
Al Bitar, A., Kerr, Y. H., Merlin, O., Cabot, F., Wigneron, J.-P., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: Global drought index from SMOS soil moisture, in: IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Melbourne, Australia, 2013.
Al Bitar, A., Mialon, A., Kerr, Y. H., Cabot, F., Richaume, P., Jacquette, E., Quesney, A., Mahmoodi, A., Tarot, S., Parrens, M., Al-Yaari, A., Pellarin, T., Rodriguez-Fernandez, N., and Wigneron, J.-P.: The global SMOS Level 3 daily soil moisture and brightness temperature maps, Earth Syst. Sci. Data, 9, 293–315, https://doi.org/10.5194/essd-9-293-2017, 2017.
Andresen, C. G., Lawrence, D. M., Wilson, C. J., McGuire, A. D., Koven, C., Schaefer, K., Jafarov, E., Peng, S., Chen, X., Gouttevin, I., Burke, E., Chadburn, S., Ji, D., Chen, G., Hayes, D., and Zhang, W.: Soil moisture and hydrology projections of the permafrost region – a model intercomparison, The Cryosphere, 14, 445–459, https://doi.org/10.5194/tc-14-445-2020, 2020.
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi, M., and Betts, A. K.: A revised hydrology for the ECMWF model: Verification from field site to terrestrial water storage and impact in the integrated forecast system, J. Hydrometeorol., 10, 623–643, https://doi.org/10.1175/2008JHM1068.1, 2009.
Balsamo, G., Albergel, C., Beljaars, A., Boussetta, S., Brun, E., Cloke, H., Dee, D., Dutra, E., Muñoz-Sabater, J., Pappenberger, F., de Rosnay, P., Stockdale, T., and Vitart, F.: ERA-Interim/Land: a global land surface reanalysis data set, Hydrol. Earth Syst. Sci., 19, 389–407, https://doi.org/10.5194/hess-19-389-2015, 2015.
Beaudoing, H., Rodell, M., and NASA/GSFC/HSL: GLDAS Noah Land Surface Model L4 3 hourly 0.25 x 0.25 degree V2.0, Goddard Earth Sciences Data and Information Services Center (GES DISC), Greenbelt, MD, USA, 2019.
Beck, H. E., Pan, M., Miralles, D. G., Reichle, R. H., Dorigo, W. A., Hahn, S., Sheffield, J., Karthikeyan, L., Balsamo, G., Parinussa, R. M., van Dijk, A. I. J. M., Du, J., Kimball, J. S., Vergopolan, N., and Wood, E. F.: Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors, Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, 2021.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Bishop, C. H. and Abramowitz, G.: Climate model dependence and the replicate Earth paradigm, Clim. Dynam., 41, 885–900, https://doi.org/10.1007/s00382-012-1610-y, 2013.
Dai, A. and Zhao, T.: Uncertainties in historical changes and future projections of drought. Part I: estimates of historical drought changes, Clim. Change, 144, 519–533, https://doi.org/10.1007/s10584-016-1705-2, 2017.
Dai, A., Trenberth, K. E., and Qian, T.: A global dataset of Palmer Drought Severity Index for 1870–2002: Relationship with soil moisture and effects of surface warming, J. Hydrometeorol., 5, 1117–1130, https://doi.org/10.1175/jhm-386.1, 2004.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, I., Biblot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Greer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M., Matricardi, M., McNally, A. P., Mong-Sanz, B. M., Morcette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
de Rosnay, P., Drusch, M., Vasiljevic, D., Balsamo, G., Albergel, C., and Isaksen, L.: A simplified Extended Kalman Filter for the global operational soil moisture analysis at ECMWF, Q. J. Roy. Meteor. Soc., 139, 1199–1213, https://doi.org/10.1002/qj.2023, 2013.
Dirmeyer, P. A., Gao, X., Zhao, M., Guo, Z., Oki, T., and Hanasaki, N.: GSWP-2: Multimodel analysis and implications for our perception of the land surface, B. Am. Meteorol. Soc., 87, 1381–1398, https://doi.org/10.1175/bams-87-10-1381, 2006.
Dorigo, W., de Jeu, R., Chung, D., Parinussa, R., Liu, Y., Wagner, W., and Fernández-Prieto, D.: Evaluating global trends (1988–2010) in harmonized multi-satellite surface soil moisture, Geophys. Res. Lett., 39, L18405, https://doi.org/10.1029/2012GL052988, 2012.
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, P. D., Hirschi, M., Ikonen, J., de Jeu, R., Kidd, R., Lahoz, W., Liu, Y. Y., Miralles, D., Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C., Reimer, C., van der Schalie, R., Seneviratne, S. I., Smolander, T., and Lecomte, P.: ESA CCI soil moisture for improved Earth system understanding: State-of-the art and future directions, Remote Sens. Environ., 203, 185–215, https://doi.org/10.1016/j.rse.2017.07.001, 2017.
Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A., Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., and Jackson, T.: The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements, Hydrol. Earth Syst. Sci., 15, 1675–1698, https://doi.org/10.5194/hess-15-1675-2011, 2011.
Dorigo, W. A., Xaver, A., Vreugdenhil, M., Gruber, A., Hegyiová, A., Sanchis-Dufau, A. D., Zamojski, D., Cordes, C., Wagner, W., and Drusch, M.: Global automated quality control of in situ soil moisture data from the International Soil Moisture Network, Vadose Zone J., 12, vzj2012.0097, https://doi.org/10.2136/vzj2012.0097, 2013.
EODC (Earth Observation Data Centre for Water Resources Monitoring GmbH): Algorithm theoretical baseline document (ATBD) supporting product version 06.1 – D2.1 version 2, Earth Observation Data Centre for Water Resources Monitoring GmbH, available at: https://climate.esa.int/media/documents/ESA_CCI_SM_RD_D2.1_v1_ATBD_v05.2.pdf, last access: 30 July 2021.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Field, C. B., Barros, V., Stocker, T. F., and Dahe, Q. (Eds.): Managing the risks of extreme events and disasters to advance climate change adaptation: Special report of the intergovernmental panel on climate change, Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9781139177245, 2012.
Friedl, M. and Sulla-Menashe, D.: MCD12C1 MODIS/Terra+Aqua land cover type L3 global 0.05Deg CMG V006, LP DAAC [Data set], https://doi.org/10.5067/MODIS/MCD12C1.006, 2015.
Giorgi, F. and Mearns, L. O.: Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the “reliability ensemble averaging” (REA) method, J. Climate, 15, 1141–1158, https://doi.org/10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2, 2002.
Green, J. K., Seneviratne, S. I., Berg, A. M., Findell, K. L., Hagemann, S., Lawrence, D. M., and Gentine, P.: Large influence of soil moisture on long-term terrestrial carbon uptake, Nature, 565, 476–479, https://doi.org/10.1038/s41586-018-0848-x, 2019.
Gruber, A., Su, C.-H., Crow, W. T., Zwieback, S., Dorigo, W. A., and Wagner, W.: Estimating error cross-correlations in soil moisture data sets using extended collocation analysis, J. Geophys. Res.-Atmos., 121, 1208–1219, https://doi.org/10.1002/2015JD024027, 2016.
Gruber, A., Crow, W. T., and Dorigo, W. A.: Assimilation of spatially sparse in situ soil moisture networks into a continuous model domain, Water Resour. Res., 54, 1353–1367, https://doi.org/10.1002/2017WR021277, 2018.
Gruber, A., De Lannoy, G., Albergel, C., Al-Yaari, A., Brocca, L., Calvet, J.-C., Colliander, A., Cosh, M., Crow, W., Dorigo, W., Draper, C., Hirschi, M., Kerr, Y., Konings, A., Lahoz, W., McColl, K., Montzka, C., Muñoz-Sabater, J., Peng, J., Reichle, R., Richaume, P., Rüdiger, C., Scanlon, T., van der Schalie, R., Wigneron, J.-P., and Wagner, W.: Validation practices for satellite soil moisture retrievals: What are (the) errors?, Remote Sensing of Environment, 244, 111806, https://doi.org/10.1016/j.rse.2020.111806, 2020.
Gu, X., Li, J., Chen, Y. D., Kong, D., and Liu, J.: Consistency and discrepancy of global surface soil moisture changes from multiple model-based data sets against satellite observations, J. Geophys. Res.-Atmos., 124, 1474–1495, https://doi.org/10.1029/2018JD029304, 2019.
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated high-resolution grids of monthly climatic observations – the CRU TS3.10 dataset, Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014.
Hauser, M.: Regionmask: plotting and creation of masks of spatial regions, Zenodo, https://doi.org/10.5281/zenodo.3585543, 2019.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hobeichi, S., Abramowitz, G., Evans, J., and Ukkola, A.: Derived Optimal Linear Combination Evapotranspiration (DOLCE): a global gridded synthesis ET estimate, Hydrol. Earth Syst. Sci., 22, 1317–1336, https://doi.org/10.5194/hess-22-1317-2018, 2018.
Hobeichi, S., Abramowitz, G., Evans, J., and Beck, H. E.: Linear Optimal Runoff Aggregate (LORA): a global gridded synthesis runoff product, Hydrol. Earth Syst. Sci., 23, 851–870, https://doi.org/10.5194/hess-23-851-2019, 2019.
Hollander, M., Wolfe, D. A., and Chicken, E.: Nonparametric statistical methods, 3rd ed., Wiley, 2013.
Huntzinger, D. N., Schwalm, C. R., Wei, Y., Cook, R. B., Michalak, a M., Schaefer, K., Jacobson, a R., Arain, M. a, Ciais, P., Fisher, J. B., Hayes, D. J., Huang, M., Huang, S., Ito, A., Jain, a K., Lei, H., Lu, C., Maignan, F., Mao, J., Parazoo, N. C., Peng, C., Peng, S., Poulter, B., Ricciuto, D. M., Tian, H., Shi, X., Wang, W., Zeng, N., Zhao, F., Zhu, Q., Yang, J., and Tao, B.: NACP MsTMIP: Global 0.5-degree model outputs in standard format, Version 1.0, ORNL Distributed Active Archive Center, https://doi.org/10.3334/ornldaac/1225, 2018.
Karthikeyan, L., Pan, M., Wanders, N., Kumar, D. N., and Wood, E. F.: Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons, Adv. Water Resour., 109, 236–252, https://doi.org/10.1016/j.advwatres.2017.09.010, 2017.
Knoben, W. J. M., Woods, R. A., and Freer, J. E.: Global bimodal precipitation seasonality: A systematic overview, Int. J. Climatol., 39, 558–567, https://doi.org/10.1002/joc.5786, 2019.
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Takahashi, K.: The JRA-55 Reanalysis: General specifications and basic characteristics, J. Meteor. Soc. Jpn., 93, 5–48, https://doi.org/10.2151/jmsj.2015-001, 2015.
Kumar, S., Newman, M., Wang, Y., and Livneh, B.: Potential reemergence of seasonal soil moisture anomalies in North America, J. Climate, 32, 2707–2734, https://doi.org/10.1175/JCLI-D-18-0540.1, 2019.
Laloyaux, P., de Boisseson, E., and Dahlgren, P.: CERA-20C: An Earth system approach to climate reanalysis, ECMWF Newsl., 150, 25–30, https://doi.org/10.21957/FFS36BIRJ2, 2017.
Li, L., Shangguan, W., Deng, Y., Mao, J., Pan, J., Wei, N., Yuan, H., Zhang, S., Zhang, Y., and Dai, Y.: A causal inference model based on random forests to identify the effect of soil moisture on precipitation, J. Hydrometeorol., 21, 1115–1131, https://doi.org/10.1175/JHM-D-19-0209.1, 2020a.
Li, M., Wu, P., and Ma, Z.: A comprehensive evaluation of soil moisture and soil temperature from third-generation atmospheric and land reanalysis data sets, Int. J. Climatol., 40, 5744–5766, https://doi.org/10.1002/joc.6549, 2020b.
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. 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, 2011.
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, https://doi.org/10.1016/j.rse.2012.03.014, 2012.
Loew, A., Stacke, T., Dorigo, W., de Jeu, R., and Hagemann, S.: Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies, Hydrol. Earth Syst. Sci., 17, 3523–3542, https://doi.org/10.5194/hess-17-3523-2013, 2013.
Lu, J., Carbone, G. J., and Grego, J. M.: Uncertainty and hotspots in 21st century projections of agricultural drought from CMIP5 models, Sci. Rep., 9, 4922, https://doi.org/10.1038/s41598-019-41196-z, 2019.
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.
McCarty, W., Coy, L., Gelaro, R., Huang, A., Merkova, D., Smith, E. B., Sienkiewicz, M., and Wargan, K.: MERRA-2 input observations: summary and assessment, Goddard Space Flight Center, Greenbelt, MD, USA, 2016.
Melton, J. R., Verseghy, D. L., Sospedra-Alfonso, R., and Gruber, S.: Improving permafrost physics in the coupled Canadian Land Surface Scheme (v.3.6.2) and Canadian Terrestrial Ecosystem Model (v.2.1) (CLASS-CTEM), Geosci. Model Dev., 12, 4443–4467, https://doi.org/10.5194/gmd-12-4443-2019, 2019.
Molero, B., Leroux, D. J., Richaume, P., Kerr, Y. H., Merlin, O., Cosh, M. H., and Bindlish, R.: Multi-timescale analysis of the spatial representativeness of in situ soil moisture data within satellite footprints: Soil moisture time and spatial scales, J. Geophys. Res.-Atmos., 123, 3–21, https://doi.org/10.1002/2017JD027478, 2018.
O, S. and Orth, R.: Global soil moisture data derived through machine learning trained with in-situ measurements, Sci. Data, 8, 170, https://doi.org/10.1038/s41597-021-00964-1, 2021.
Padrón, R. S., Gudmundsson, L., and Seneviratne, S. I.: Observational constraints reduce likelihood of extreme changes in multidecadal land water availability, Geophys. Res. Lett., 46, 736–744, https://doi.org/10.1029/2018GL080521, 2019.
Pan, S., Pan, N., Tian, H., Friedlingstein, P., Sitch, S., Shi, H., Arora, V. K., Haverd, V., Jain, A. K., Kato, E., Lienert, S., Lombardozzi, D., Nabel, J. E. M. S., Ottlé, C., Poulter, B., Zaehle, S., and Running, S. W.: Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling, Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, 2020.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.: Scikit-learn: machine learning in Python, J. Mach. Learn. Res., 12, 2825–2830, 2011.
Piles, M., Ballabrera-Poy, J., and Muñoz-Sabater, J.: Dominant features of global surface soil moisture variability observed by the SMOS satellite, Remote Sens., 11, 95, https://doi.org/10.3390/rs11010095, 2019.
Poli, P., Hersbach, H., Dee, D. P., Berrisford, P., Simmons, A. J., Vitart, F., Laloyaux, P., Tan, D. G. H., Peubey, C., Thépaut, J.-N., Trémolet, Y., Hólm, E. V., Bonavita, M., Isaksen, L., and Fisher, M.: ERA-20C: An atmospheric reanalysis of the twentieth century, J. Climate, 29, 4083–4097, https://doi.org/10.1175/JCLI-D-15-0556.1, 2016.
Rui, H. and Beaudoing, H.: README document for NASA GLDAS version 2 data products, NASA Goddard Space Flight Center (GES DISC), Greenbelt, MD, USA, available at: https://disc.gsfc.nasa.gov/information/documents?title=Hydrology Documentation (last access: 30 July 2021), 2020.
Seabold, S. and Perktold, J.: Statsmodels: Econometric and statistical modeling with Python, in: 9th Python in Science Conference, Austin, Texas, 28 June–3 July 2010 https://doi.org/10.25080/majora-92bf1922-011, 2010.
Sitch, S., Huntingford, C., Gedney, N., Levy, P. E., Lomas, M., Piao, S. L., Betts, R., Ciais, P., Cox, P., Friedlingstein, P., Jones, C. D., Prentice, I. C., and Woodward, F. I.: Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs), Glob. Change Biol., 14, 2015–2039, https://doi.org/10.1111/j.1365-2486.2008.01626.x, 2008.
Sospedra-Alfonso, R. and Merryfield, W. J.: Initialization and potential predictability of soil moisture in the Canadian Seasonal to Interannual Prediction System, J. Climate, 31, 5205–5224, https://doi.org/10.1175/JCLI-D-17-0707.1, 2018.
Su, C.-H., Ryu, D., Dorigo, W., Zwieback, S., Gruber, A., Albergel, C., Reichle, R. H., and Wagner, W.: Homogeneity of a global multisatellite soil moisture climate data record, Geophys. Res. Lett., 43, 11245–11252, https://doi.org/10.1002/2016GL070458, 2016.
Spinoni, J., Barbosa, P., De Jager, A., McCormick, N., Naumann, G., Vogt, J. V., Magni, D., Masante, D., and Mazzeschi, M.: A new global database of meteorological drought events from 1951 to 2016, J. Hydrol. Reg. Stud., 22, 100593, https://doi.org/10.1016/j.ejrh.2019.100593, 2019.
Su, C.-H., Ryu, D., Dorigo, W., Zwieback, S., Gruber, A., Albergel, C., Reichle, R. H., and Wagner, W.: Homogeneity of a global multisatellite soil moisture climate data record, Geophys. Res. Lett., 43, 11245–11252, https://doi.org/10.1002/2016GL070458, 2016.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and the experiment design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012.
Tobin, K. J., Torres, R., Crow, W. T., and Bennett, M. E.: Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS, Hydrol. Earth Syst. Sci., 21, 4403–4417, https://doi.org/10.5194/hess-21-4403-2017, 2017.
UCAR/NCAR/CISL/TDD: The NCAR Comannd Language (Version 6.6.2) [Software], Boulder, CO, USA, https://doi.org/10.5065/D6WD3XH5, 2019.
Wang, G., Garcia, D., Liu, Y., de Jeu, R., and Johannes Dolman, A.: A three-dimensional gap filling method for large geophysical datasets: Application to global satellite soil moisture observations, Environ. Model. Softw., 30, 139–142, https://doi.org/10.1016/j.envsoft.2011.10.015, 2012.
Wang, Y.: soil_moisture_merge, Bitbucket repository [code], https://bitbucket.org/ywang11/soil_moisture_merge/src/master/ (last access: 30 July 2021), 2020.
Wang, Y. and Mao, J.: Global multi-layer soil moisture products, https://doi.org/10.6084/m9.figshare.13661312.v1, 2021.
Wang, Y., Leng, P., Peng, J., Marzahn, P., and Ludwig, R.: Global assessments of two blended microwave soil moisture products CCI and SMOPS with in-situ measurements and reanalysis data, Int. J. Appl. Earth Obs., 94, 102234, https://doi.org/10.1016/j.jag.2020.102234, 2021a.
Wang, Z., Zhan, C., Ning, L., and Guo, H.: Evaluation of global terrestrial evapotranspiration in CMIP6 models, Theor. Appl. Climatol., 143, 521–531, https://doi.org/10.1007/s00704-020-03437-4, 2021b.
Wu, Z., Zhou, J., He, H., Lin, Q., Wu, X., and Xu, Z.: An advanced error correction methodology for merging in-situ observed and model-based soil moisture, J. Hydrol., 566, 150–163, https://doi.org/10.1016/j.jhydrol.2018.09.018, 2018.
Yuan, S. and Quiring, S. M.: Evaluation of soil moisture in CMIP5 simulations over the contiguous United States using in situ and satellite observations, Hydrol. Earth Syst. Sci., 21, 2203–2218, https://doi.org/10.5194/hess-21-2203-2017, 2017.
Zeng, Y., Su, Z., van der Velde, R., Wang, L., Xu, K., Wang, X., and Wen, J.: Blending satellite observed, model simulated, and in situ measured soil moisture over Tibetan plateau, Remote Sens., 8, 268, https://doi.org/10.3390/rs8030268, 2016.
Zhang, G. and Cook, K. H.: West African monsoon demise: Climatology, interannual variations, and relationship to seasonal rainfall, J. Geophys. Res.-Atmos., 119, 10175–10193, https://doi.org/10.1002/2014JD022043, 2014.
We developed seven global soil moisture datasets (1970–2016, monthly, half-degree, and multilayer) by merging a wide range of data sources, including in situ and satellite observations, reanalysis, offline land surface model simulations, and Earth system model simulations. Given the great value of long-term, multilayer, gap-free soil moisture products to climate research and applications, we believe this paper and the presented datasets would be of interest to many different communities.
We developed seven global soil moisture datasets (1970–2016, monthly, half-degree, and...