Articles | Volume 25, issue 7
https://doi.org/10.5194/hess-25-4209-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-4209-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Jul 2021
Research article |
| 30 Jul 2021
| 30 Jul 2021
Comprehensive evaluation of satellite-based and reanalysis soil moisture products using in situ observations over China
Xiaolu Ling
Jiangsu Key Laboratory of Coal-based Greenhouse Gas Control and Utilization, China University of Mining and Technology, Xuzhou 221008, Jiangsu, China
School of Environment and Spatial Informatics, China University of
Mining and Technology, Xuzhou 221000, China
Ying Huang
CORRESPONDING AUTHOR
Institute for Climate and Global Change Research, School of
Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth
System Sciences, Nanjing University, Nanjing 210023, China
Weidong Guo
Institute for Climate and Global Change Research, School of
Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth
System Sciences, Nanjing University, Nanjing 210023, China
Yixin Wang
Institute for Climate and Global Change Research, School of
Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Chaorong Chen
Institute for Climate and Global Change Research, School of
Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Bo Qiu
Institute for Climate and Global Change Research, School of
Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth
System Sciences, Nanjing University, Nanjing 210023, China
Institute for Climate and Global Change Research, School of
Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Joint International Research Laboratory of Atmospheric and Earth
System Sciences, Nanjing University, Nanjing 210023, China
Jiangsu Key Laboratory of Coal-based Greenhouse Gas Control and Utilization, China University of Mining and Technology, Xuzhou 221008, Jiangsu, China
School of Environment and Spatial Informatics, China University of
Mining and Technology, Xuzhou 221000, China
Yong Xue
Jiangsu Key Laboratory of Coal-based Greenhouse Gas Control and Utilization, China University of Mining and Technology, Xuzhou 221008, Jiangsu, China
School of Environment and Spatial Informatics, China University of
Mining and Technology, Xuzhou 221000, China
Jian Peng
Department of Remote Sensing, Helmholtz Centre for Environmental
Research – UFZ, Permoserstraße 15, 04318 Leipzig, Germany
Remote Sensing Centre for Earth System Research, Leipzig University, 04103 Leipzig, Germany
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Atmos. Meas. Tech., 16, 2237–2262, https://doi.org/10.5194/amt-16-2237-2023, https://doi.org/10.5194/amt-16-2237-2023, 2023
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Meng-Zhuo Zhang, Zhongfeng Xu, Ying Han, and Weidong Guo
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Hydrol. Earth Syst. Sci., 25, 1617–1641, https://doi.org/10.5194/hess-25-1617-2021, https://doi.org/10.5194/hess-25-1617-2021, 2021
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Wenkai Li, Shuzhen Hu, Pang-Chi Hsu, Weidong Guo, and Jiangfeng Wei
The Cryosphere, 14, 3565–3579, https://doi.org/10.5194/tc-14-3565-2020, https://doi.org/10.5194/tc-14-3565-2020, 2020
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Understanding the forecasting skills of the subseasonal-to-seasonal (S2S) model on Tibetan Plateau snow cover (TPSC) is the first step to applying the S2S model to hydrological forecasts over the Tibetan Plateau. This study conducted a multimodel comparison of the TPSC prediction skill to learn about their performance in capturing TPSC variability. S2S models can skillfully forecast TPSC within a lead time of 2 weeks but show limited skill beyond 3 weeks. Systematic biases of TPSC were found.
Mengyao Liu, Jintai Lin, Hao Kong, K. Folkert Boersma, Henk Eskes, Yugo Kanaya, Qin He, Xin Tian, Kai Qin, Pinhua Xie, Robert Spurr, Ruijing Ni, Yingying Yan, Hongjian Weng, and Jingxu Wang
Atmos. Meas. Tech., 13, 4247–4259, https://doi.org/10.5194/amt-13-4247-2020, https://doi.org/10.5194/amt-13-4247-2020, 2020
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Nicholas C. Parazoo, Troy Magney, Alex Norton, Brett Raczka, Cédric Bacour, Fabienne Maignan, Ian Baker, Yongguang Zhang, Bo Qiu, Mingjie Shi, Natasha MacBean, Dave R. Bowling, Sean P. Burns, Peter D. Blanken, Jochen Stutz, Katja Grossmann, and Christian Frankenberg
Biogeosciences, 17, 3733–3755, https://doi.org/10.5194/bg-17-3733-2020, https://doi.org/10.5194/bg-17-3733-2020, 2020
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Jian Peng, Simon Dadson, Feyera Hirpa, Ellen Dyer, Thomas Lees, Diego G. Miralles, Sergio M. Vicente-Serrano, and Chris Funk
Earth Syst. Sci. Data, 12, 753–769, https://doi.org/10.5194/essd-12-753-2020, https://doi.org/10.5194/essd-12-753-2020, 2020
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Jun Ge, Andrew J. Pitman, Weidong Guo, Beilei Zan, and Congbin Fu
Hydrol. Earth Syst. Sci., 24, 515–533, https://doi.org/10.5194/hess-24-515-2020, https://doi.org/10.5194/hess-24-515-2020, 2020
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Pradeep Khatri, Hironobu Iwabuchi, Tadahiro Hayasaka, Hitoshi Irie, Tamio Takamura, Akihiro Yamazaki, Alessandro Damiani, Husi Letu, and Qin Kai
Atmos. Meas. Tech., 12, 6037–6047, https://doi.org/10.5194/amt-12-6037-2019, https://doi.org/10.5194/amt-12-6037-2019, 2019
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In an attempt to make cloud retrievals from the surface more common and convenient, we developed a cloud retrieval algorithm applicable for sky radiometers. It is based on an optimum method by fitting measured transmittances with modeled values. Further, a cost-effective and easy-to-use calibration procedure is proposed and validated using data obtained from the standard method. A detailed error analysis and quality assessment are also performed.
Xiao-Lu Ling, Cong-Bin Fu, Zong-Liang Yang, and Wei-Dong Guo
Geosci. Model Dev., 12, 3119–3133, https://doi.org/10.5194/gmd-12-3119-2019, https://doi.org/10.5194/gmd-12-3119-2019, 2019
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Observation and simulation can provide the temporal and spatial variation of vegetation characteristics, while they are not satisfactory for understanding the mechanism of the exchange between ecosystems and atmosphere. Data assimilation (DA) can combine the observation and models via mathematical statistical analysis. Results show that the ensemble adjust Kalman filter (EAKF) is the optimal algorithm. In addition, models perform better when the DA accepts a higher proportion of observations.
X. Han, G. Tana, K. Qin, and H. Letu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W5, 9–15, https://doi.org/10.5194/isprs-archives-XLII-3-W5-9-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W5-9-2018, 2018
X. Shi, C. Zhao, K. Qin, Y. Yang, K. Zhang, and H. Fan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W5, 73–76, https://doi.org/10.5194/isprs-archives-XLII-3-W5-73-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W5-73-2018, 2018
J. Zou, K. Qin, J. Xu, and X. Han
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W5, 83–88, https://doi.org/10.5194/isprs-archives-XLII-3-W5-83-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W5-83-2018, 2018
K. L. Chan and K. Qin
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 29–36, https://doi.org/10.5194/isprs-archives-XLII-2-W7-29-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-29-2017, 2017
Xueqian Wang, Weidong Guo, Bo Qiu, Ye Liu, Jianning Sun, and Aijun Ding
Atmos. Chem. Phys., 17, 4989–4996, https://doi.org/10.5194/acp-17-4989-2017, https://doi.org/10.5194/acp-17-4989-2017, 2017
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Land use or cover change is a fundamental anthropogenic forcing for climate change. Based on field observations, we quantified the contributions of different factors to surface temperature change and deepened the understanding of its mechanisms. We found evaporative cooling plays the most important role in the temperature change, while radiative forcing, which is traditionally emphasized, is not significant. This study provided firsthand evidence to verify the model results in IPCC AR5.
Zhongfeng Xu, Zhaolu Hou, Ying Han, and Weidong Guo
Geosci. Model Dev., 9, 4365–4380, https://doi.org/10.5194/gmd-9-4365-2016, https://doi.org/10.5194/gmd-9-4365-2016, 2016
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This paper devises a new diagram called the vector field evaluation (VFE) diagram. The VFE diagram is a generalized Taylor diagram and is able to provide a concise evaluation of model performance in simulating vector fields (e.g., vector winds) in terms of three statistical variables. The VFE diagram can be applied to the evaluation of full vector fields or anomaly fields as needed. Some potential applications of the VFE diagram in model evaluation are also presented in the paper.
Lixin Wu, Shuo Zheng, Angelo De Santis, Kai Qin, Rosa Di Mauro, Shanjun Liu, and Mario Luigi Rainone
Nat. Hazards Earth Syst. Sci., 16, 1859–1880, https://doi.org/10.5194/nhess-16-1859-2016, https://doi.org/10.5194/nhess-16-1859-2016, 2016
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Many anomalies before the 2009 L'Aquila earthquake were reported but not synergically analyzed referring to geosystem coupling. We investigated changes of multiple hydrothermal parameters in coversphere and atmosphere and studied 3-D evolution of b value in lithosphere. Quasi-synchronism of pre-earthquake anomalies georelating to particular thrusts and local topography are revealed. A geosphere coupling mode is proposed interpreting the function of CO2-rich crust fluids on local LCA coupling.
Xin Huang, Aijun Ding, Lixia Liu, Qiang Liu, Ke Ding, Xiaorui Niu, Wei Nie, Zheng Xu, Xuguang Chi, Minghuai Wang, Jianning Sun, Weidong Guo, and Congbin Fu
Atmos. Chem. Phys., 16, 10063–10082, https://doi.org/10.5194/acp-16-10063-2016, https://doi.org/10.5194/acp-16-10063-2016, 2016
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We conducted a comprehensive modelling work to understand the impact of biomass burning on synoptic weather during agricultural burning season in East China. We demonstrated that the numerical model with fire emission, chemical processes, and aerosol–meteorology online coupled could reproduce the change of air temperature and precipitation induced by air pollution during this event. This study highlights the importance of including human activities in numerical-model-based weather forecast.
Jian Peng, Alexander Loew, Xuelong Chen, Yaoming Ma, and Zhongbo Su
Hydrol. Earth Syst. Sci., 20, 3167–3182, https://doi.org/10.5194/hess-20-3167-2016, https://doi.org/10.5194/hess-20-3167-2016, 2016
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The Tibetan Plateau plays a major role in regional and global climate. The knowledge of latent heat flux can help to better describe the complex interactions between land and atmosphere. The purpose of this paper is to provide a detailed cross-comparison of existing latent heat flux products over the TP. The results highlight the recently developed latent heat product – High Resolution Land Surface Parameters from Space (HOLAPS).
Weidong Guo, Xueqian Wang, Jianning Sun, Aijun Ding, and Jun Zou
Atmos. Chem. Phys., 16, 9875–9890, https://doi.org/10.5194/acp-16-9875-2016, https://doi.org/10.5194/acp-16-9875-2016, 2016
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Basic characteristics of land–atmosphere interactions at four neighboring sites with different underlying surfaces in southern China, a typical monsoon region, are analyzed systematically. Despite the same climate background, the differences in land surface characteristics like albedo and aerodynamic roughness length due to land use/cover change exert distinct influences on the surface radiative budget and energy allocation and result in differences of near-surface micrometeorological elements.
Alexander Loew, Jian Peng, and Michael Borsche
Geosci. Model Dev., 9, 2499–2532, https://doi.org/10.5194/gmd-9-2499-2016, https://doi.org/10.5194/gmd-9-2499-2016, 2016
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Surface water and energy fluxes are essential components of the Earth system. The present paper introduces a new framework for the estimation of surface energy and water fluxes at the land surface, which allows for temporally and spatially high resolved flux estimates at the global scale. The framework maximizes the usage of existing long-term satellite data records. Overall the results indicate very good agreement with in situ observations when compared against 49 FLUXNET stations worldwide.
J. Peng, J. Niesel, and A. Loew
Hydrol. Earth Syst. Sci., 19, 4765–4782, https://doi.org/10.5194/hess-19-4765-2015, https://doi.org/10.5194/hess-19-4765-2015, 2015
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This paper gives a comprehensive evaluation of a simple newly developed downscaling scheme using in situ measurements from REMEDHUS network, a first cross-comparison of the performance of the downscaled soil moisture from MODIS and MSG SEVIRI, an evaluation of the performance of the downscaled soil moisture at different spatial resolutions, and an exploration of the influence of LST, vegetation index, terrain, clouds, and land cover heterogeneity on the performance of VTCI.
J. Peng, M. Borsche, Y. Liu, and A. Loew
Hydrol. Earth Syst. Sci., 17, 3913–3919, https://doi.org/10.5194/hess-17-3913-2013, https://doi.org/10.5194/hess-17-3913-2013, 2013
K. Qin, L. X. Wu, X. Y. Ouyang, X. H. Shen, and S. Zheng
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-1-2439-2013, https://doi.org/10.5194/nhessd-1-2439-2013, 2013
Revised manuscript has not been submitted
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Remote Sensing and GIS
A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze–Atbara Basin
Improved soil evaporation remote sensing retrieval algorithms and associated uncertainty analysis on the Tibetan Plateau
SMPD: a soil moisture-based precipitation downscaling method for high-resolution daily satellite precipitation estimation
Evaluating the accuracy of gridded water resources reanalysis and evapotranspiration products for assessing water security in poorly gauged basins
Attribution of global evapotranspiration trends based on the Budyko framework
The influence of vegetation water dynamics on the ASCAT backscatter–incidence angle relationship in the Amazon
Extrapolating continuous vegetation water content to understand sub-daily backscatter variations
Variations in surface roughness of heterogeneous surfaces in the Nagqu area of the Tibetan Plateau
Evapotranspiration in the Amazon: spatial patterns, seasonality, and recent trends in observations, reanalysis, and climate models
The benefit of brightness temperature assimilation for the SMAP Level-4 surface and root-zone soil moisture analysis
Evaluation of the dual-polarization weather radar quantitative precipitation estimation using long-term datasets
Validation of SMAP L2 passive-only soil moisture products using upscaled in situ measurements collected in Twente, the Netherlands
Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa
Data-driven estimates of evapotranspiration and its controls in the Congo Basin
Ability of an Australian reanalysis dataset to characterise sub-daily precipitation
A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products
Evaluation of soil moisture from CCAM-CABLE simulation, satellite-based models estimates and satellite observations: a case study of Skukuza and Malopeni flux towers
Statistical characteristics of raindrop size distribution during rainy seasons in the Beijing urban area and implications for radar rainfall estimation
An evaluation of daily precipitation from a regional atmospheric reanalysis over Australia
Performance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River basin
The El Niño event of 2015–2016: climate anomalies and their impact on groundwater resources in East and Southern Africa
Consistency of satellite-based precipitation products in space and over time compared with gauge observations and snow- hydrological modelling in the Lake Titicaca region
Using phase lags to evaluate model biases in simulating the diurnal cycle of evapotranspiration: a case study in Luxembourg
Integrating multiple satellite observations into a coherent dataset to monitor the full water cycle – application to the Mediterranean region
An improved perspective in the spatial representation of soil moisture: potential added value of SMOS disaggregated 1 km resolution “all weather” product
Temporal- and spatial-scale and positional effects on rain erosivity derived from point-scale and contiguous rain data
The PERSIANN family of global satellite precipitation data: a review and evaluation of products
Exploring seasonal and regional relationships between the Evaporative Stress Index and surface weather and soil moisture anomalies across the United States
Development of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United States
Evaluation of multiple climate data sources for managing environmental resources in East Africa
Precipitation downscaling using a probability-matching approach and geostationary infrared data: an evaluation over six climate regions
Regional co-variability of spatial and temporal soil moisture–precipitation coupling in North Africa: an observational perspective
Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US
Regional frequency analysis of extreme rainfall in Belgium based on radar estimates
An assessment of the performance of global rainfall estimates without ground-based observations
Water–food–energy nexus with changing agricultural scenarios in India during recent decades
Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean
The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France
Reservoir storage and hydrologic responses to droughts in the Paraná River basin, south-eastern Brazil
Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels
Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau
Evaluation of soil moisture downscaling using a simple thermal-based proxy – the REMEDHUS network (Spain) example
The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat
Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002–2012)
Scoping a field experiment: error diagnostics of TRMM precipitation radar estimates in complex terrain as a basis for IPHEx2014
Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in Ethiopia
Downscaling of seasonal soil moisture forecasts using satellite data
Long term soil moisture mapping over the Tibetan plateau using Special Sensor Microwave/Imager
Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate
Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France
Mohammed Abdallah, Ke Zhang, Lijun Chao, Abubaker Omer, Khalid Hassaballah, Kidane Welde Reda, Linxin Liu, Tolossa Lemma Tola, and Omar M. Nour
Hydrol. Earth Syst. Sci., 28, 1147–1172, https://doi.org/10.5194/hess-28-1147-2024, https://doi.org/10.5194/hess-28-1147-2024, 2024
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A D-vine copula-based quantile regression (DVQR) model is used to merge satellite precipitation products. The performance of the DVQR model is compared with the simple model average and one-outlier-removed average methods. The nonlinear DVQR model outperforms the quantile-regression-based multivariate linear and Bayesian model averaging methods.
Jin Feng, Ke Zhang, Huijie Zhan, and Lijun Chao
Hydrol. Earth Syst. Sci., 27, 363–383, https://doi.org/10.5194/hess-27-363-2023, https://doi.org/10.5194/hess-27-363-2023, 2023
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Here we improved a satellite-driven evaporation algorithm by introducing the modified versions of the two constraint schemes. The two moisture constraint schemes largely improved the evaporation estimation on two barren-dominated basins of the Tibetan Plateau. Investigation of moisture constraint uncertainty showed that high-quality soil moisture can optimally represent moisture, and more accessible precipitation data generally help improve the estimation of barren evaporation.
Kunlong He, Wei Zhao, Luca Brocca, and Pere Quintana-Seguí
Hydrol. Earth Syst. Sci., 27, 169–190, https://doi.org/10.5194/hess-27-169-2023, https://doi.org/10.5194/hess-27-169-2023, 2023
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In this study, we developed a soil moisture-based precipitation downscaling (SMPD) method for spatially downscaling the GPM daily precipitation product by exploiting the connection between surface soil moisture and precipitation according to the soil water balance equation. Based on this physical method, the spatial resolution of the daily precipitation product was downscaled to 1 km and the SMPD method shows good potential for the development of the high-resolution precipitation product.
Elias Nkiaka, Robert G. Bryant, Joshua Ntajal, and Eliézer I. Biao
Hydrol. Earth Syst. Sci., 26, 5899–5916, https://doi.org/10.5194/hess-26-5899-2022, https://doi.org/10.5194/hess-26-5899-2022, 2022
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Achieving water security in poorly gauged regions is hindered by a lack of in situ hydrometeorological data. In this study, we validated nine existing gridded water resource reanalyses and eight evapotranspiration products in eight representative gauged basins in Central–West Africa. Our results show the strengths and and weaknesses of the existing products and that these products can be used to assess water security in ungauged basins. However, it is imperative to validate these products.
Shijie Li, Guojie Wang, Chenxia Zhu, Jiao Lu, Waheed Ullah, Daniel Fiifi Tawia Hagan, Giri Kattel, and Jian Peng
Hydrol. Earth Syst. Sci., 26, 3691–3707, https://doi.org/10.5194/hess-26-3691-2022, https://doi.org/10.5194/hess-26-3691-2022, 2022
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We found that the precipitation variability dominantly controls global evapotranspiration (ET) in dry climates, while the net radiation has substantial control over ET in the tropical regions, and vapor pressure deficit (VPD) impacts ET trends in boreal mid-latitude climate. The critical role of VPD in controlling ET trends is particularly emphasized due to its influence in controlling the carbon–water–energy cycle.
Ashwini Petchiappan, Susan C. Steele-Dunne, Mariette Vreugdenhil, Sebastian Hahn, Wolfgang Wagner, and Rafael Oliveira
Hydrol. Earth Syst. Sci., 26, 2997–3019, https://doi.org/10.5194/hess-26-2997-2022, https://doi.org/10.5194/hess-26-2997-2022, 2022
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This study investigates spatial and temporal patterns in the incidence angle dependence of backscatter from the ASCAT C-band scatterometer and relates those to precipitation, humidity, and radiation data and GRACE equivalent water thickness in ecoregions in the Amazon. The results show that the ASCAT data record offers a unique perspective on vegetation water dynamics exhibiting sensitivity to moisture availability and demand and phenological change at interannual, seasonal, and diurnal scales.
Paul C. Vermunt, Susan C. Steele-Dunne, Saeed Khabbazan, Jasmeet Judge, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 26, 1223–1241, https://doi.org/10.5194/hess-26-1223-2022, https://doi.org/10.5194/hess-26-1223-2022, 2022
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This study investigates the use of hydrometeorological sensors to reconstruct variations in internal vegetation water content of corn and relates these variations to the sub-daily behaviour of polarimetric L-band backscatter. The results show significant sensitivity of backscatter to the daily cycles of vegetation water content and dew, particularly on dry days and for vertical and cross-polarizations, which demonstrates the potential for using radar for studies on vegetation water dynamics.
Maoshan Li, Xiaoran Liu, Lei Shu, Shucheng Yin, Lingzhi Wang, Wei Fu, Yaoming Ma, Yaoxian Yang, and Fanglin Sun
Hydrol. Earth Syst. Sci., 25, 2915–2930, https://doi.org/10.5194/hess-25-2915-2021, https://doi.org/10.5194/hess-25-2915-2021, 2021
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In this study, using MODIS satellite data and site atmospheric turbulence observation data in the Nagqu area of the northern Tibetan Plateau, with the Massman-retrieved model and a single height observation to determine aerodynamic surface roughness, temporal and spatial variation characteristics of the surface roughness were analyzed. The result is feasible, and it can be applied to improve the model parameters of the land surface model and the accuracy of model simulation in future work.
Jessica C. A. Baker, Luis Garcia-Carreras, Manuel Gloor, John H. Marsham, Wolfgang Buermann, Humberto R. da Rocha, Antonio D. Nobre, Alessandro Carioca de Araujo, and Dominick V. Spracklen
Hydrol. Earth Syst. Sci., 25, 2279–2300, https://doi.org/10.5194/hess-25-2279-2021, https://doi.org/10.5194/hess-25-2279-2021, 2021
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Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to measure over large areas. In this study, we compare spatial patterns, seasonality, and recent trends in Amazon ET from a water-budget analysis with estimates from satellites, reanalysis, and global climate models. We find large differences between products, showing that many widely used datasets and climate models may not provide a reliable representation of this crucial variable over the Amazon.
Jianxiu Qiu, Jianzhi Dong, Wade T. Crow, Xiaohu Zhang, Rolf H. Reichle, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 1569–1586, https://doi.org/10.5194/hess-25-1569-2021, https://doi.org/10.5194/hess-25-1569-2021, 2021
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The SMAP L4 dataset has been extensively used in hydrological applications. We innovatively use a machine learning method to analyze how the efficiency of the L4 data assimilation (DA) system is determined. It shows that DA efficiency is mainly related to Tb innovation, followed by error in precipitation forcing and microwave soil roughness. Since the L4 system can effectively filter out precipitation error, future development should focus on correctly specifying the SSM–RZSM coupling strength.
Tanel Voormansik, Roberto Cremonini, Piia Post, and Dmitri Moisseev
Hydrol. Earth Syst. Sci., 25, 1245–1258, https://doi.org/10.5194/hess-25-1245-2021, https://doi.org/10.5194/hess-25-1245-2021, 2021
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A long set of operational polarimetric weather radar rainfall accumulations from Estonia and Italy are generated and investigated. Results show that the combined product of specific differential phase and horizontal reflectivity yields the best results when compared to rain gauge measurements. The specific differential-phase-based product overestimates weak precipitation, and the horizontal-reflectivity-based product underestimates heavy rainfall in all analysed accumulation periods.
Rogier van der Velde, Andreas Colliander, Michiel Pezij, Harm-Jan F. Benninga, Rajat Bindlish, Steven K. Chan, Thomas J. Jackson, Dimmie M. D. Hendriks, Denie C. M. Augustijn, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 473–495, https://doi.org/10.5194/hess-25-473-2021, https://doi.org/10.5194/hess-25-473-2021, 2021
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NASA’s SMAP satellite provides estimates of the amount of water in the soil. With measurements from a network of 20 monitoring stations, the accuracy of these estimates has been studied for a 4-year period. We found an agreement between satellite and in situ estimates in line with the mission requirements once the large mismatches associated with rapidly changing water contents, e.g. soil freezing and rainfall, are excluded.
Moctar Dembélé, Bettina Schaefli, Nick van de Giesen, and Grégoire Mariéthoz
Hydrol. Earth Syst. Sci., 24, 5379–5406, https://doi.org/10.5194/hess-24-5379-2020, https://doi.org/10.5194/hess-24-5379-2020, 2020
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This study evaluates 102 combinations of rainfall and temperature datasets from satellite and reanalysis sources as input to a fully distributed hydrological model. The model is recalibrated for each input dataset, and the outputs are evaluated with streamflow, evaporation, soil moisture and terrestrial water storage data. Results show that no single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes.
Michael W. Burnett, Gregory R. Quetin, and Alexandra G. Konings
Hydrol. Earth Syst. Sci., 24, 4189–4211, https://doi.org/10.5194/hess-24-4189-2020, https://doi.org/10.5194/hess-24-4189-2020, 2020
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Water that evaporates from Africa's tropical forests provides rainfall throughout the continent. However, there are few sources of meteorological data in central Africa, so we use observations from satellites to estimate evaporation from the Congo Basin at different times of the year. We find that existing evaporation estimates in tropical Africa do not accurately capture seasonal variations in evaporation and that fluctuations in soil moisture and solar radiation drive evaporation rates.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 24, 2951–2962, https://doi.org/10.5194/hess-24-2951-2020, https://doi.org/10.5194/hess-24-2951-2020, 2020
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BARRA is a high-resolution reanalysis dataset over the Oceania region. This study evaluates the performance of sub-daily BARRA precipitation at point and spatial scales over Australia. We find that the dataset reproduces some of the sub-daily characteristics of precipitation well, although it exhibits some spatial displacement errors, and it performs better in temperate than in tropical regions. The product is well suited to complement other estimates derived from remote sensing and rain gauges.
Christian Massari, Luca Brocca, Thierry Pellarin, Gab Abramowitz, Paolo Filippucci, Luca Ciabatta, Viviana Maggioni, Yann Kerr, and Diego Fernandez Prieto
Hydrol. Earth Syst. Sci., 24, 2687–2710, https://doi.org/10.5194/hess-24-2687-2020, https://doi.org/10.5194/hess-24-2687-2020, 2020
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Rain gauges are unevenly spaced around the world with extremely low gauge density over places like Africa and South America. Here, water-related problems like floods, drought and famine are particularly severe and able to cause fatalities, migration and diseases. We have developed a rainfall dataset that exploits the synergies between rainfall and soil moisture to provide accurate rainfall observations which can be used to face these problems.
Floyd Vukosi Khosa, Mohau Jacob Mateyisi, Martina Reynita van der Merwe, Gregor Timothy Feig, Francois Alwyn Engelbrecht, and Michael John Savage
Hydrol. Earth Syst. Sci., 24, 1587–1609, https://doi.org/10.5194/hess-24-1587-2020, https://doi.org/10.5194/hess-24-1587-2020, 2020
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The paper evaluates soil moisture outputs from three structurally distinct models against in situ data. Our goal is to find how representative the model outputs are for site and region. This is a question of interest as some of the models have a specific regional focus on their inceptions. Much focus is placed on how the models capture the soil moisture signal. We find that there is agreement on seasonal patterns between the models and observations with a tolerable level of model uncertainty.
Yu Ma, Guangheng Ni, Chandrasekar V. Chandra, Fuqiang Tian, and Haonan Chen
Hydrol. Earth Syst. Sci., 23, 4153–4170, https://doi.org/10.5194/hess-23-4153-2019, https://doi.org/10.5194/hess-23-4153-2019, 2019
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Raindrop size distribution (DSD) information is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation. This study extensively investigates the DSD characteristics during rainy seasons in the Beijing urban area using 5-year DSD observations from a Parsivel2 disdrometer. The statistical distributions of DSD parameters are examined and the polarimetric radar rainfall algorithms are derived to support the ongoing development of an X-band radar network.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 23, 3387–3403, https://doi.org/10.5194/hess-23-3387-2019, https://doi.org/10.5194/hess-23-3387-2019, 2019
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BARRA is a novel regional reanalysis for Australia. Our research demonstrates that it is able to characterize a rich spatial variation in daily precipitation behaviour. In addition, its ability to represent large rainfalls is valuable for the analysis of extremes. It is a useful complement to existing precipitation datasets for Australia, especially in sparsely gauged regions.
Webster Gumindoga, Tom H. M. Rientjes, Alemseged Tamiru Haile, Hodson Makurira, and Paolo Reggiani
Hydrol. Earth Syst. Sci., 23, 2915–2938, https://doi.org/10.5194/hess-23-2915-2019, https://doi.org/10.5194/hess-23-2915-2019, 2019
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We evaluate the influence of elevation and distance from large-scale open water bodies on bias for CMORPH satellite rainfall in the Zambezi basin. Effects of distance > 10 km from water bodies are minimal, whereas the effects at shorter distances are indicated but are not conclusive for lack of rain gauges. Taylor diagrams show station elevation influencing CMORPH performance. The
spatio-temporaland newly developed
elevation zonebias schemes proved more effective in removing CMORPH bias.
Seshagiri Rao Kolusu, Mohammad Shamsudduha, Martin C. Todd, Richard G. Taylor, David Seddon, Japhet J. Kashaigili, Girma Y. Ebrahim, Mark O. Cuthbert, James P. R. Sorensen, Karen G. Villholth, Alan M. MacDonald, and Dave A. MacLeod
Hydrol. Earth Syst. Sci., 23, 1751–1762, https://doi.org/10.5194/hess-23-1751-2019, https://doi.org/10.5194/hess-23-1751-2019, 2019
Frédéric Satgé, Denis Ruelland, Marie-Paule Bonnet, Jorge Molina, and Ramiro Pillco
Hydrol. Earth Syst. Sci., 23, 595–619, https://doi.org/10.5194/hess-23-595-2019, https://doi.org/10.5194/hess-23-595-2019, 2019
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This paper assesses the potential of satellite precipitation estimates (SPEs) for precipitation measurement and hydrological and snow modelling. A total of 12 SPEs is considered to provide a global overview of available SPE accuracy for users interested in such datasets. Results show that, over poorly monitored regions, SPEs represent a very efficient alternative to traditional precipitation gauges to follow precipitation in time and space and for hydrological and snow modelling.
Maik Renner, Claire Brenner, Kaniska Mallick, Hans-Dieter Wizemann, Luigi Conte, Ivonne Trebs, Jianhui Wei, Volker Wulfmeyer, Karsten Schulz, and Axel Kleidon
Hydrol. Earth Syst. Sci., 23, 515–535, https://doi.org/10.5194/hess-23-515-2019, https://doi.org/10.5194/hess-23-515-2019, 2019
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We estimate the phase lag of surface states and heat fluxes to incoming solar radiation at the sub-daily timescale. While evapotranspiration reveals a minor phase lag, the vapor pressure deficit used as input by Penman–Monteith approaches shows a large phase lag. The surface-to-air temperature gradient used by energy balance residual approaches shows a small phase shift in agreement with the sensible heat flux and thus explains the better correlation of these models at the sub-daily timescale.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
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This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Samiro Khodayar, Amparo Coll, and Ernesto Lopez-Baeza
Hydrol. Earth Syst. Sci., 23, 255–275, https://doi.org/10.5194/hess-23-255-2019, https://doi.org/10.5194/hess-23-255-2019, 2019
Franziska K. Fischer, Tanja Winterrath, and Karl Auerswald
Hydrol. Earth Syst. Sci., 22, 6505–6518, https://doi.org/10.5194/hess-22-6505-2018, https://doi.org/10.5194/hess-22-6505-2018, 2018
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The potential of rain to cause soil erosion by runoff is called rain erosivity. Rain erosivity is highly variable in space and time even over distances of less than 1 km. Contiguously measured radar rain data depict for the first time this spatio-temporal variation, but scaling factors are required to account for differences in spatial and temporal resolution compared to rain gauge data. These scaling factors were obtained from more than 2 million erosive events.
Phu Nguyen, Mohammed Ombadi, Soroosh Sorooshian, Kuolin Hsu, Amir AghaKouchak, Dan Braithwaite, Hamed Ashouri, and Andrea Rose Thorstensen
Hydrol. Earth Syst. Sci., 22, 5801–5816, https://doi.org/10.5194/hess-22-5801-2018, https://doi.org/10.5194/hess-22-5801-2018, 2018
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The goal of this article is to first provide an overview of the available PERSIANN precipitation retrieval algorithms and their differences. We evaluate the products over CONUS at different spatial and temporal scales using CPC data. Daily scale is the finest temporal scale used for the evaluation over CONUS. We provide a comparison of the available products at a quasi-global scale. We highlight the strengths and limitations of the PERSIANN products.
Jason A. Otkin, Yafang Zhong, David Lorenz, Martha C. Anderson, and Christopher Hain
Hydrol. Earth Syst. Sci., 22, 5373–5386, https://doi.org/10.5194/hess-22-5373-2018, https://doi.org/10.5194/hess-22-5373-2018, 2018
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Correlation analyses were used to explore relationships between the Evaporative Stress Index (ESI) – which depicts anomalies in evapotranspiration (ET) – and various land and atmospheric variables that impact ET. The results revealed that the ESI is more strongly correlated to anomalies in soil moisture and near-surface vapor pressure deficit than to precipitation and temperature anomalies. Large regional and seasonal dependencies in the strengths of the correlations were also observed.
Vikalp Mishra, James F. Cruise, Christopher R. Hain, John R. Mecikalski, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 22, 4935–4957, https://doi.org/10.5194/hess-22-4935-2018, https://doi.org/10.5194/hess-22-4935-2018, 2018
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Multiple satellite observations can be used for surface and subsurface soil moisture estimations. In this study, satellite observations along with a mathematical model were used to distribute and develop multiyear soil moisture profiles over the southeastern US. Such remotely sensed profiles become particularly useful at large spatiotemporal scales, can be a significant tool in data-scarce regions of the world, can complement various land and crop models, and can act as drought indicators etc.
Solomon Hailu Gebrechorkos, Stephan Hülsmann, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 22, 4547–4564, https://doi.org/10.5194/hess-22-4547-2018, https://doi.org/10.5194/hess-22-4547-2018, 2018
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In Africa field-based meteorological data are scarce; therefore global data sources based on remote sensing and climate models are often used as alternatives. To assess their suitability for a large and topographically complex area in East Africa, we evaluated multiple climate data products with available ground station data at multiple timescales over 21 regions. The comprehensive evaluation resulted in identification of preferential data sources to be used for climate and hydrological studies.
Ruifang Guo, Yuanbo Liu, Han Zhou, and Yaqiao Zhu
Hydrol. Earth Syst. Sci., 22, 3685–3699, https://doi.org/10.5194/hess-22-3685-2018, https://doi.org/10.5194/hess-22-3685-2018, 2018
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Existing satellite products are often insufficient for use in small-scale (< 10 km) hydrological and meteorological studies. We propose a new approach based on the cumulative distribution of frequency to downscale satellite precipitation products with geostationary (GEO) data. This paper uses CMORPH and FY2-E GEO data to examine the approach in six different climate regions. The downscaled precipitation performed better for convective systems.
Irina Y. Petrova, Chiel C. van Heerwaarden, Cathy Hohenegger, and Françoise Guichard
Hydrol. Earth Syst. Sci., 22, 3275–3294, https://doi.org/10.5194/hess-22-3275-2018, https://doi.org/10.5194/hess-22-3275-2018, 2018
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In North Africa rain storms can be as vital as they are devastating. The present study uses multi-year satellite data to better understand how and where soil moisture conditions affect development of rainfall in the area. Our results reveal two major regions in the southwest and southeast, where drier soils show higher potential to cause rainfall development. This knowledge is essential for the hydrological sector, and can be further used by models to improve prediction of rainfall and droughts.
Nishan Bhattarai, Kaniska Mallick, Nathaniel A. Brunsell, Ge Sun, and Meha Jain
Hydrol. Earth Syst. Sci., 22, 2311–2341, https://doi.org/10.5194/hess-22-2311-2018, https://doi.org/10.5194/hess-22-2311-2018, 2018
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We report the first ever regional-scale implementation of the Surface Temperature Initiated Closure (STIC1.2) model for mapping evapotranspiration (ET) using MODIS land surface and gridded climate datasets to overcome the existing uncertainties in aerodynamic temperature and conductance estimation in global ET models. Validation and intercomparison with SEBS and MOD16 products across an aridity gradient in the US manifested better ET mapping potential of STIC1.2 in different climates and biomes.
Edouard Goudenhoofdt, Laurent Delobbe, and Patrick Willems
Hydrol. Earth Syst. Sci., 21, 5385–5399, https://doi.org/10.5194/hess-21-5385-2017, https://doi.org/10.5194/hess-21-5385-2017, 2017
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Knowing the characteristics of extreme precipitation is useful for flood management applications like sewer system design. The potential of a 12-year high-quality weather radar precipitation dataset is investigated by comparison with rain gauges. Despite known limitations, a good agreement is found between the radar and the rain gauges. Using the radar data allow us to reduce the uncertainty of the extreme value analysis, especially for short duration extremes related to thunderstorms.
Christian Massari, Wade Crow, and Luca Brocca
Hydrol. Earth Syst. Sci., 21, 4347–4361, https://doi.org/10.5194/hess-21-4347-2017, https://doi.org/10.5194/hess-21-4347-2017, 2017
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The paper explores a method for the assessment of the performance of global rainfall estimates without relying on ground-based observations. Thanks to this method, different global correlation maps are obtained (for the first time without relying on a benchmark dataset) for some of the most used globally available rainfall products. This is central for hydroclimatic studies within data-scarce regions, where ground observations are scarce to evaluate the relative quality of a rainfall product
Beas Barik, Subimal Ghosh, A. Saheer Sahana, Amey Pathak, and Muddu Sekhar
Hydrol. Earth Syst. Sci., 21, 3041–3060, https://doi.org/10.5194/hess-21-3041-2017, https://doi.org/10.5194/hess-21-3041-2017, 2017
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The article summarises changing patterns of the water-food-energy nexus in India during recent decades. The work first analyses satellite data of water storage with a validation using the observed well data. Northern India shows a declining trend of water storage and western-central India shows an increasing trend of the same. Major droughts result in a drop in water storage which is not recovered due to uncontrolled ground water irrigation for agricultural activities even in good monsoon years.
Francesco Marra, Efrat Morin, Nadav Peleg, Yiwen Mei, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 21, 2389–2404, https://doi.org/10.5194/hess-21-2389-2017, https://doi.org/10.5194/hess-21-2389-2017, 2017
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Rainfall frequency analyses from radar and satellite estimates over the eastern Mediterranean are compared examining different climatic conditions. Correlation between radar and satellite results is high for frequent events and decreases with return period. The uncertainty related to record length is larger for drier climates. The agreement between different sensors instills confidence on their use for rainfall frequency analysis in ungauged areas of the Earth.
David Fairbairn, Alina Lavinia Barbu, Adrien Napoly, Clément Albergel, Jean-François Mahfouf, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 2015–2033, https://doi.org/10.5194/hess-21-2015-2017, https://doi.org/10.5194/hess-21-2015-2017, 2017
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This study assesses the impact on river discharge simulations over France of assimilating ASCAT-derived surface soil moisture (SSM) and leaf area index (LAI) observations into the ISBA land surface model. Wintertime LAI has a notable impact on river discharge. SSM assimilation degrades river discharge simulations. This is caused by limitations in the simplified versions of the Kalman filter and ISBA model used in this study. Implementing an observation operator for ASCAT is needed.
Davi de C. D. Melo, Bridget R. Scanlon, Zizhan Zhang, Edson Wendland, and Lei Yin
Hydrol. Earth Syst. Sci., 20, 4673–4688, https://doi.org/10.5194/hess-20-4673-2016, https://doi.org/10.5194/hess-20-4673-2016, 2016
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Drought propagation from rainfall deficits to reservoir depletion was studied based on remote sensing, monitoring and modelling data. Regional droughts were shown by widespread depletion in total water storage that reduced soil moisture storage and runoff, greatly reducing reservoir storage. The multidisciplinary approach to drought assessment shows the linkages between meteorological and hydrological droughts that are essential for managing water resources subjected to climate extremes.
Zhi Qing Peng, Xiaozhou Xin, Jin Jun Jiao, Ti Zhou, and Qinhuo Liu
Hydrol. Earth Syst. Sci., 20, 4409–4438, https://doi.org/10.5194/hess-20-4409-2016, https://doi.org/10.5194/hess-20-4409-2016, 2016
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A remote sensing algorithm named temperature sharpening and flux aggregation (TSFA) was applied to HJ-1B satellite data to estimate evapotranspiration over heterogeneous surface considering landscape and statistical effects on mixed pixels. Footprint validation results showed TSFA was more accurate and less uncertain than other two upscaling methods. Additional analysis and comparison showed TSFA can capture land surface heterogeneities and integrate the effect of landscapes within mixed pixels.
Jian Peng, Alexander Loew, Xuelong Chen, Yaoming Ma, and Zhongbo Su
Hydrol. Earth Syst. Sci., 20, 3167–3182, https://doi.org/10.5194/hess-20-3167-2016, https://doi.org/10.5194/hess-20-3167-2016, 2016
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The Tibetan Plateau plays a major role in regional and global climate. The knowledge of latent heat flux can help to better describe the complex interactions between land and atmosphere. The purpose of this paper is to provide a detailed cross-comparison of existing latent heat flux products over the TP. The results highlight the recently developed latent heat product – High Resolution Land Surface Parameters from Space (HOLAPS).
J. Peng, J. Niesel, and A. Loew
Hydrol. Earth Syst. Sci., 19, 4765–4782, https://doi.org/10.5194/hess-19-4765-2015, https://doi.org/10.5194/hess-19-4765-2015, 2015
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This paper gives a comprehensive evaluation of a simple newly developed downscaling scheme using in situ measurements from REMEDHUS network, a first cross-comparison of the performance of the downscaled soil moisture from MODIS and MSG SEVIRI, an evaluation of the performance of the downscaled soil moisture at different spatial resolutions, and an exploration of the influence of LST, vegetation index, terrain, clouds, and land cover heterogeneity on the performance of VTCI.
G. Boulet, B. Mougenot, J.-P. Lhomme, P. Fanise, Z. Lili-Chabaane, A. Olioso, M. Bahir, V. Rivalland, L. Jarlan, O. Merlin, B. Coudert, S. Er-Raki, and J.-P. Lagouarde
Hydrol. Earth Syst. Sci., 19, 4653–4672, https://doi.org/10.5194/hess-19-4653-2015, https://doi.org/10.5194/hess-19-4653-2015, 2015
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The paper presents a new model (SPARSE) to estimate total evapotranspiration as well as its components (evaporation and transpiration) from remote-sensing data in the thermal infra-red domain. The limits of computing two unknowns (evaporation and transpiration) out of one piece of information (one surface temperature) are assessed theoretically. The model performance in retrieving the components as well as the water stress is assessed for two wheat crops (one irrigated and one rainfed).
O. P. Prat and B. R. Nelson
Hydrol. Earth Syst. Sci., 19, 2037–2056, https://doi.org/10.5194/hess-19-2037-2015, https://doi.org/10.5194/hess-19-2037-2015, 2015
Y. Duan, A. M. Wilson, and A. P. Barros
Hydrol. Earth Syst. Sci., 19, 1501–1520, https://doi.org/10.5194/hess-19-1501-2015, https://doi.org/10.5194/hess-19-1501-2015, 2015
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A diagnostic analysis of the space-time structure of error in quantitative precipitation estimates (QPEs) from the precipitation radar on the Tropical Rainfall Measurement Mission satellite is presented here in preparation for the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014. A high-density raingauge network over the southern Appalachians allows for direct comparison between ground-based measurements and satellite-based QPE (PR 2A25 Version 7 with 5 years of data 2008-2013).
A. W. Worqlul, B. Maathuis, A. A. Adem, S. S. Demissie, S. Langan, and T. S. Steenhuis
Hydrol. Earth Syst. Sci., 18, 4871–4881, https://doi.org/10.5194/hess-18-4871-2014, https://doi.org/10.5194/hess-18-4871-2014, 2014
S. Schneider, A. Jann, and T. Schellander-Gorgas
Hydrol. Earth Syst. Sci., 18, 2899–2905, https://doi.org/10.5194/hess-18-2899-2014, https://doi.org/10.5194/hess-18-2899-2014, 2014
R. van der Velde, M. S. Salama, T. Pellarin, M. Ofwono, Y. Ma, and Z. Su
Hydrol. Earth Syst. Sci., 18, 1323–1337, https://doi.org/10.5194/hess-18-1323-2014, https://doi.org/10.5194/hess-18-1323-2014, 2014
J. Chirouze, G. Boulet, L. Jarlan, R. Fieuzal, J. C. Rodriguez, J. Ezzahar, S. Er-Raki, G. Bigeard, O. Merlin, J. Garatuza-Payan, C. Watts, and G. Chehbouni
Hydrol. Earth Syst. Sci., 18, 1165–1188, https://doi.org/10.5194/hess-18-1165-2014, https://doi.org/10.5194/hess-18-1165-2014, 2014
A. L. Barbu, J.-C. Calvet, J.-F. Mahfouf, and S. Lafont
Hydrol. Earth Syst. Sci., 18, 173–192, https://doi.org/10.5194/hess-18-173-2014, https://doi.org/10.5194/hess-18-173-2014, 2014
Cited articles
AghaKouchak, A., Farahmand, A., Melton, F. S., Teixeira, J., Anderson, M.
C., Wardlow, B. D., and Hain, C. R.: Remote sensing of drought: progress,
challenges and opportunities, Rev. Geophys., 53, 452–480,
https://doi.org/10.1002/2014rg000456, 2015.
Akbar, R., Gianotti, D. J. S., McColl, K. A., Haghighi, E., Salvucci, G. D.,
and Entekhabi, D.: Estimation of landscape soil water losses from satellite
observations of soil moisture, J. Hydrometeorol., 19, 871–889,
https://doi.org/10.1175/jhm-d-17-0200.1, 2018.
Albergel, C., Rosnay, P., Gruhier, C., Munoz-Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y., and Wagner, W.: Evaluation of remotely sensed and
modelled soil moisture products using global ground-based in situ observations, Remote Sens. Environ., 118, 215–226,
https://doi.org/10.1016/j.rse.2011.11.017, 2012.
Albergel, C., Dutra, E., Munier, S., Calvet, J. C., Munoz-Sabater, J., de
Rosnay, P., and Balsamo, G.: ERA-5 and ERA-interim driven ISBA land surface
model simulations: which one performs better?, Hydrol. Earth Syst. Sci., 22,
3515–3532, https://doi.org/10.5194/hess-22-3515-2018, 2018.
An, R., Zhang, L., Wang, Z., Quaye-Ballard, J. A., You, J., Shen, X., Gao, W., Huang, L., Zhao, Y., and Ke, Z.: Validation of the ESA CCI soil moisture product in China, Int. J. Appl. Earth Obs. Geoinf., 48, 28–36,
https://doi.org/10.1016/j.jag.2015.09.009, 2016.
Anderson, M. C., Norman, J. M., Mecikalski, J. R., Otkin, J. A., and Kustas,
W. P.: A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 2. Surface moisture climatology, J. Geophys. Res., 112, D11112,
https://doi.org/10.1029/2006jd007507, 2007.
Balenzano, A., Mattia, F., Satalino, G., and Davidson, M. W. J.: Dense temporal series of C- and L-band SAR data for soil moisture retrieval over
agricultural crops, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 4, 439–450, https://doi.org/10.1109/jstars.2010.2052916, 2011.
Bárdossy, A. and Lehmann, W.: Spatial distribution of soil moisture in a small catchment. Part 1: geostatistical analysis, J. Hydrol., 206, 1–15,
https://doi.org/10.1016/s0022-1694(97)00152-2, 1998.
Bastiaanssen, W. G. M., Molden, D. J., and Makin, I. W.: Remote sensing for
irrigated agriculture: examples from research and possible applications, Agric. Water Manage., 46, 137–155, https://doi.org/10.1016/s0378-3774(00)00080-9, 2000.
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.
Berg, A. A., Famiglietti, J. S., Walker, J. P., and Houser, P. R.: Impact of
bias correction to reanalysis products on simulations of North American soil
moisture and hydrological fluxes, J. Geophys. Res., 108, 4490, https://doi.org/10.1029/2002jd003334, 2003.
Berrisford, P., Dee, D., Poli, P., Brugge, R., Fielding, K., Fuentes, M., Kallberg, P., Kobayashi, S., Uppala, S., and Simmons, A.: The ERA-Interim archive, version 2.0, ERA report series, 1. Technical Report, ECMWF, Shinfield Park, Reading, 23 pp., 2011.
Bogena, H. R., Huisman, J. A., Oberdörster, C., and Vereecken, H.: Evaluation of a low-cost soil water content sensor for wireless network
applications, J. Hydrol., 344, 32–42, https://doi.org/10.1016/j.jhydrol.2007.06.032, 2007.
Busch, F. A., Niemann, J. D., and Coleman, M.: Evaluation of an empirical
orthogonal function-based method to downscale soil moisture patterns based
on topographical attributes, Hydrol. Process., 26, 2696–2709,
https://doi.org/10.1002/hyp.8363, 2012.
Chakravorty, A., Chahar, B. R., Sharma, O. P., and Dhanya, C. T.: A regional
scale performance evaluation of SMOS and ESA-CCI soil moisture products over
India with simulated soil moisture from MERRA-Land, Remote Sens. Environ.,
186, 514–527, https://doi.org/10.1016/j.rse.2016.09.011, 2016.
Chauhan, N. S., Miller, S., and Ardanuy, P.: Spaceborne soil moisture estimation at high resolution: a microwave-optical/IR synergistic approach,
Int. J. Remote Sens., 24, 4599–4622, https://doi.org/10.1080/0143116031000156837, 2003.
Chen, Y. and Yuan, H.: Evaluation of nine sub-daily soil moisture model products over China using high-resolution in situ observations, J. Hydrol.,
588, 125054, https://doi.org/10.1016/j.jhydrol.2020.125054, 2020.
Choi, M. and Hur, Y.: A microwave-optical/infrared disaggregation for improving spatial representation of soil moisture using AMSR-E and MODIS
products, Remote Sens. Environ., 124, 259–269, https://doi.org/10.1016/j.rse.2012.05.009, 2012.
Climate research unit: Drought indices, available at: https://crudata.uea.ac.uk/cru/data/drought/#global/, last access: 12 January 2020.
Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J.,
Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P.,
Brönnimann, S., Brunet, M., Crouthamel, R. I., Grant, A. N., Groisman,
P. Y., Jones, P. D., Kruk, M. C., Kruger, A. C., Marshall, G. J., Maugeri, M., Mok, H. Y., Nordli, Ø., Ross, T. F., Trigo, R. M., Wang, X. L., Woodruff, S. D., and Worley, S. J.: The twentieth century reanalysis
project, Q. J. Roy. Meteorol. Soc., 137, 1–28, https://doi.org/10.1002/qj.776, 2011.
Crow, W. and Van den Berg, M.: An improved approach for estimating observation and model error parameters in soil moisture data assimilation,
Water Resour. Res., 46, W12519, https://doi.org/10.1029/2010WR009402, 2010.
Crow, W. T. and Ryu, D.: A new data assimilation approach for improving runoff prediction using remotely-sensed soil moisture retrievals, Hydrol.
Earth Syst. Sci., 13, 1–16, https://doi.org/10.5194/hess-13-1-2009, 2009.
Crow, W. T. and Wood, E. F.: Multi-scale dynamics of soil moisture variability observed during SGP'97, Geophys. Res. Lett., 26, 3485–3488,
https://doi.org/10.1029/1999gl010880, 1999.
Crow, W. T., Berg, A. A., Cosh, M. H., Loew, A., Mohanty, B. P., Panciera, R., de Rosnay, P., Ryu, D., and Walker, J. P.: Upscaling sparse ground-based
soil moisture observations for the validation of coarse-resolution satellite
soil moisture products, Rev. Geophys., 50, RG2002, https://doi.org/10.1029/2011rg000372, 2012.
C3S: ERA5: fifth generation of ECMWF atmospheric reanalyses of the global
climate, available at: https://cds.climate.copernicus.eu/cdsapp#!/home (last access: 12 July 2018), 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.
Das, N. N., Entekhabi, D., and Njoku, E. G.: An algorithm for merging SMAP
radiometer and radar data for high-resolution soil-moisture retrieval, IEEE
T. Geosci. Remote, 49, 1504–1512, https://doi.org/10.1109/tgrs.2010.2089526, 2011.
Decker, M., Brunke, M. A., Wang, Z., Sakaguchi, K., Zeng, X., and Bosilovich, M. G.: Evaluation of the reanalysis products from GSFC, NCEP, and ECMWF using flux tower observations, J. Climate, 25, 1916–1944, https://doi.org/10.1175/jcli-d-11-00004.1, 2012.
de Jeu, R. A. M., Wagner, W., Holmes, T. R. H., Dolman, A. J., van de Giesen, N. C., and Friesen, J.: Global soil moisture patterns observed by space borne microwave radiometers and scatterometers, Surv. Geophys., 29, 399–420, https://doi.org/10.1007/s10712-008-9044-0, 2008.
Deng, Y., Wang, S., Bai, X., Wu, L., Cao, Y., Li, H., Wang, M., Li, C., Yang, Y., Hu, Z., Tian, S., and Lu, Q.: Comparison of soil moisture products from microwave remote sensing, land model, and reanalysis using global ground observations, Hydrol. Process., 34, 836–851, https://doi.org/10.1002/hyp.13636, 2020.
Dirmeyer, P. A.: The terrestrial segment of soil moisture-climate coupling,
Geophys. Res. Lett., 38, L16702, https://doi.org/10.1029/2011gl048268, 2011.
Dobriyal, P., Qureshi, A., Badola, R., and Hussain, S. A.: A review of the
methods available for estimating soil moisture and its implications for water resource management, J. Hydrol., 458–459, 110–117, https://doi.org/10.1016/j.jhydrol.2012.06.021, 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., Wagner, W., Gruber, A., Scanlon, T., Hahn, S., Kidd, R., Paulik,
C., Reimer, C., van der Schalie, R., and de Jeu, R.: ESA soil moisture
climate change initiative (soil_moisture_cci): version 04.2 data collection, Cent. Environ. Data Anal., https://doi.org/10.5285/3a8a94c3fa464d68b6d70df291afd457, 2018.
Dorigo, W. A., Scipal, K., Parinussa, R. M., Liu, Y. Y., Wagner, W., de Jeu,
R. A. M., and Naeimi, V.: Error characterisation of global active and
passive microwave soil moisture datasets, Hydrol. Earth Syst. Sci., 14,
2605–2616, https://doi.org/10.5194/hess-14-2605-2010, 2010.
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., Gruber, A., De Jeu, R. A. M., Wagner, W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., Parinussa, R. M., and Kidd, R.:
Evaluation of the ESA CCI soil moisture product using ground-based observations, Remote Sens. Environ., 162, 380–395, https://doi.org/10.1016/j.rse.2014.07.023, 2015.
ECMWF: European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis Interim (ERA-Interim) Model Data, NCAS British Atmospheric Data Centre, Oxford, UK, 2009.
ECMWF: ERA5 Catalogue, available at: https://apps.ecmwf.int/data-catalogues/era5/?class=ea, last access: 27 November 2017.
ECMWF: ERA Interim, Daily, available at:
https://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/, last access: 5 June 2018.
Engman, E. T.: Applications of microwave remote sensing of soil moisture for
water resources and agriculture, Remote Sens. Environ., 35, 213–226,
https://doi.org/10.1016/0034-4257(91)90013-v, 1991.
Entekhabi, D., Yueh, S., O'Neill, P., Kellogg, K., Allen, A., Bindlish, R., Brown, M., Chan, S., Colliander, A., Crow, W., Das, N., De Lannoy, G., Dunbar, R., Edelstein, W., Entin, J., Escobar, V., Goodman, S., Jackson, T., Jai, B., Johnson, J., Kim, E., Kim, S., Kimball, J., Koster, R., Leon, A., McDonald, K., Moghaddam, M., Mohammed, P., Moran, S., Njoku, E., Piepmeier, J., Reichle, R., Rogez, F., Shi, J., Spencer, M., Thurman, S., Tsang, L., Van Zyl, J., Weiss, B., and West, R.: SMAP Handbook Soil Moisture Active Passive, Mapping Soil Moisture Freeze/Thaw From Space, Nat. Aeronaut. Space Admin., Jet Propul. Lab., Pasadena, California, 180 pp., 2014.
ESA: v05.2 release: ESA CCI SM now including SMAP data!, available at:
https://www.esa-soilmoisture-cci.org/ (last access: 7 September 2018), 2018.
GCOS: Essential Climate Variables-Land, available at:
https://public.wmo.int/en/programmes/global-climate-observing-system/essential-climate-variables
(last access: 12 July 2019), 2010.
González-Zamora, Á., Sánchez, N., Pablos, M., and
Martínez-Fernández, J.: CCI soil moisture assessment with SMOS soil
moisture and in situ data under different environmental conditions and
spatial scales in Spain, Remote Sens. Environ., 225, 469–482,
https://doi.org/10.1016/j.rse.2018.02.010, 2019.
Gottschalck, J., Meng, J., Rodell, M., and Houser, P.: Analysis of multiple
precipitation products and preliminary assessment of their impact on Global
Land Data Assimilation System land surface states, J. Hydrometeorol., 6,
573–598, 2005.
Gruber, A., Dorigo, W. A., Crow, W., and Wagner, W.: Triple collocation-based merging of satellite soil moisture retrievals, IEEE T. Geosci. Remote, 55, 6780–6792, https://doi.org/10.1109/tgrs.2017.2734070, 2017.
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W.:
Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739,
https://doi.org/10.5194/essd-11-717-2019, 2019.
Gupta, H., Kling, H., Yilmaz, K., and Martinez, G. F.: Decomposition of the
mean squared error and NSE performance criteria: Implications for improved
hydrological modeling, J. Hydrol., 377, 80–91, 2009.
Hagan, D. F. T., Parinussa, R. M., Wang, G., and Draper, C. S.: An evaluation of soil moisture anomalies from global model-based datasets over the people's republic of China, Water, 12, 117, https://doi.org/10.3390/w12010117, 2020.
Harmsen, E. W., Norman, L. M., Nicole, J. S., and Gonzalez, J. E.: Seasonal climate change impacts on evapotranspiration, precipitation deficit and crop yield in Puerto Rico, Agr. Water Manage., 96, 1085–1095, 2009.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horanyi, A., Munoz-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. D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Holm, E., Janiskova, M., Keeley, S., Laloyaux, P., Lopez, P., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thepaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Ikonen, J., Smolander, T., Rautiainen, K., Cohen, J., Lemmetyinen, J., Salminen, M., and Pulliainen, J.: Spatially distributed evaluation of ESA
CCI soil moisture products in a northern boreal forest environment, Geosciences, 8, 51, https://doi.org/10.3390/geosciences8020051, 2018.
ISMN: Welcome to the International Soil Moisture Network, available at: https://ismn.geo.tuwien.ac.at/en/, last access: 15 June 2020.
Jackson, T., Cosh, M., Bindlish, R., Starks, P., Bosch, D., Seyfried, M.,
Goodrich, D., Moran, S., and Du, J.: Validation of Advanced Microwave Scanning Radiometer soil moisture products, IEEE T. Geosci. Remote, 48, 4256–4272, https://doi.org/10.1109/TGRS.2010.2051035, 2010.
Jackson, T., Bindlish, R., Cosh, M., Zhao, T., Starks, P., Bosch, D., Seyfried, M., Moran, M., Goodrich, D., Kerr, Y., and Leroux, D.: Validation of Soil Moisture and Ocean Salinity (SMOS) soil moisture over watershed networks in the U.S., IEEE T. Geosci. Remote, 50, 1530–1543, https://doi.org/10.1109/TGRS.2011.2168533, 2012.
Jasper, K., Calanca, P., and Fuhrer, J.: Changes in summertime soil water patterns in complex terrain due to climatic change, J. Hydrol., 327, 550–563, 2006.
Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S. K., Hnilo, J. J., Fiorino, M., and Potter, G. L.: NCEP-DOE AMIP-II reanalysis (R-2), B. Am. Meteorol. Soc., 83, 1631–1643, https://doi.org/10.1175/BAMS-83-11-1631, 2002.
Kim, J. E. and Hong, S. Y.: Impact of soil moisture anomalies on summer rainfall over east Asia: a regional climate model study, J. Climate, 20,
5732–5743, https://doi.org/10.1175/2006jcli1358.1, 2007.
Komma, J., Blöschl, G., and Reszler, C.: Soil moisture updating by Ensemble Kalman Filtering in real-time flood forecasting, J. Hydrol., 357,
228–242, https://doi.org/10.1016/j.jhydrol.2008.05.020, 2008.
Lai, X., Wen, J., Ceng, S. X., Song, H. Q., Tian, H., Shi, X. K., He, Y., and Huang, X.: Numerical simulation and evaluation study of soil moisture over China by using CLM4.0 model, J. Atmos. Sci., 38, 499–512, 2014.
Li, H. Y., Robock, A., Liu, S., Mo, X., and Viterbo, P.: Evaluation of reanalysis soil moisture simulations using updated Chinese soil moisture
observations, J. Hydrometeorol., 6, 180–193, https://doi.org/10.1175/jhm416.1, 2009.
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, 2020.
Li, Y., Li, Y., Yuan, X., Zhang, L., and Sha, S.: Evaluation of model-based
soil moisture drought monitoring over three key regions in China, J. Appl.
Meteorol. Clim., 57, 1989–2004, https://doi.org/10.1175/jamc-d-17-0118.1, 2018.
Liu, L., Zhang, R., and Zuo, Z.: Intercomparison of spring soil moisture among multiple reanalysis data sets over eastern China, J. Geophys. Res., 119, 54–64, https://doi.org/10.1002/2013jd020940, 2014.
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.
Luo, L., Tang, W., Lin, Z., and Wood, E.: Evaluation of summer temperature and precipitation predictions from NCEP CFSv2 retrospective forecast over China, Clim. Dynam., 41, 2213–2230, 2013.
Ma, H. , Zeng, J. , Chen, N. , Zhang, X. , and Wang, W.: Satellite surface soil moisture from SMAP, SMOS, AMSR2 and ESA CCI: a comprehensive assessment using global ground-based observations, Remote Sens. Environ., 231, 111215, https://doi.org/10.1016/j.rse.2019.111215, 2019.
Ma, S., Zhu, K., Li, M., and Ma, Z.: A comparative study of multi-source soil moisture data for China's regions, Clim. Environ. Res., 21, 121–133, 2016.
Mall, R., Gupta, A., Singh, R., Singh, R., and Rathore, L.: Water resources and climate change: an Indian perspective, Curr. Sci., 90, 1610–1626, 2006.
Markewitz, D., Devine, S., Davidson, E. A., Brando, P., and Nepstad, D. C.:
Soil moisture depletion under simulated drought in the Amazon: impacts on
deep root uptake, New Phytol., 187, 592–607, https://doi.org/10.1111/j.1469-8137.2010.03391.x, 2010.
McColl, K. A., Wang, W., Peng, B., Akbar, R., Gianotti, D. J. S., Lu, H., Pan, M., and Entekhabi, D.: Global characterization of surface soil moisture
drydowns, Geophys. Res. Lett., 44, 3682–3690, https://doi.org/10.1002/2017gl072819, 2017.
Murphy, A.: Skill scores based on the mean square error and their relationships to the correlation coefficient, Mon. Weather Rev., 116, 2417–2424, 1988.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through. Part I. A
conceptual models discussion of principles, J. Hydrol., 10, 282–290, 1970.
Nie, S., Luo, Y., and Zhu, J.: Trends and scales of observed soil moisture
variation in China, Adv. Atmos. Sci., 25, 43–58, 2008.
NMIC: Data set of crop growth and soil moisture in China (AGME_AB2_CHN_TEN): http://data.cma.cn/data/cdcdetail/dataCode/AGME_AB2_CHN_TEN.html (last access: 27 November 2017), 2006.
NorBiasto, D., Borga, M., Esposti, S. D., Gaume, E., and Anquetin, S.: Flash
flood warning based on rainfall thresholds and soil moisture conditions: an
assessment for gauged and ungauged basins, J. Hydrol., 362, 274–290,
https://doi.org/10.1016/j.jhydrol.2008.08.023, 2008.
Ochsner, T. E., Cosh, M. H., Cuenca, R. H., Dorigo, W. A., Draper, C. S.,
Hagimoto, Y., Kerr, Y. H., Larson, K. M., Njoku, E. G., Small, E. E., and Zreda, M.: State of the art in large-scale soil moisture monitoring, Soil Sci. Soc. Am. J., 77, 1888–1919, https://doi.org/10.2136/sssaj2013.03.0093, 2013.
Pasik, A., Scanlon, T., Dorigo, W., de Jeu, R. A. M., Hahn, S., van der
Schalie, R., Wagner, W., Kidd, R., Gruber, A., Moesinger, L., and Preimesberger, W.: ESA Climate Change Initiative Plus – Soil Moisture: Algorithm Theoretical Baseline Document (ATBD) Supporting Product Version v05.2, Earth Observation Data Centre for Water Resources Monitoring (EODC) GmbH, TU Wien, VanderSat, CESBIO and ETH, Zürich, 71 pp., 2020.
Peng, J. and Loew, A.: Recent advances in soil moisture estimation from remote sensing, Water, 9, 530, https://doi.org/10.3390/w9070530, 2017.
Peng, J., Niesel, J., Loew, A., Zhang, S., and Wang, J.: Evaluation of
satellite and reanalysis soil moisture products over southwest China using
ground-based measurements, Remote Sens., 7, 15729–15747, https://doi.org/10.3390/rs71115729, 2015.
Peng, J., Loew, A., Merlin, O., and Verhoest, N. E. C.: A review of spatial
downscaling of satellite remotely sensed soil moisture, Rev. Geophys., 55,
341–366, https://doi.org/10.1002/2016RG000543, 2017.
Petropoulos, G. P., Ireland, G., and Barrett, B.: Surface soil moisture
retrievals from remote sensing: current status, products & future trends,
Phys. Chem. Earth Pt. A/B/C, 83–84, 36–56, https://doi.org/10.1016/j.pce.2015.02.009, 2015.
Qiu, B., Xue, Y., Fisher, J. B., Guo, W., Berry, J. A., and Zhang, Y.: Satellite chlorophyll fluorescence and soil moisture observations lead to
advances in the predictive understanding of global terrestrial coupled
carbon-water cycles, Global Biogeochem. Cy., 32, 360–375, https://doi.org/10.1002/2017gb005744, 2018.
Robock, A., Vinnikov, K. Y., Srinivasan, G., Entin, J. K., Hollinger, S. E.,
Speranskaya, N. A., Liu, S., and Namkhai, A.: The global soil moisture data
bank, B. Am. Meteorol. Soc., 81, 1281–1299,
https://doi.org/10.1175/1520-0477(2000)081<1281:tgsmdb>2.3.co;2, 2000.
Schellekens, J., Dutra, E., Martínez-de la Torre, A., Balsamo, G., van Dijk, A., Weiland, F. S., Minvielle, M., Calvet, J.-C., Decharme, B.,
Eisner, S., Fink, G., Flörke, M., Peßenteiner, S., van Beek, R.,
Polcher, J., Beck, H., Orth, R., Calton, B., Burke, S., Dorigo, W., and Weedon, G. P.: A global water resources ensemble of hydrological models: the
eartH2Observe Tier-1 dataset, Earth Syst. Sci. Data, 9, 389–413,
https://doi.org/10.5194/essd-9-389-2017, 2017.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B.,
Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture–climate interactions in a changing climate: a review, Earth Sci.
Rev., 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004, 2010.
Sevanto, S., McDowell, N. G., Dickman, L. T., Pangle, R., and Pockman, W. T.: How do trees die? A test of the hydraulic failure and carbon starvation hypotheses, Plant Cell Environ., 37, 153–161, https://doi.org/10.1111/pce.12141, 2014.
Shangguan, W., Dai, Y., Liu, B., Ye, A., and Yuan, H.: A soil particle-size distribution dataset for regional land and climate modelling in China, Geoderma, 171–172, 85–91, https://doi.org/10.1016/j.geoderma.2011.01.013, 2012.
Shrivastava, S., Kar, S. C., and Sharma, A. R.: Soil moisture variations in
remotely sensed and reanalysis datasets during weak monsoon conditions over
central India and central Myanmar, Theor. Appl. Climatol., 129, 305–320,
https://doi.org/10.1007/s00704-016-1792-z, 2017.
Taylor, C. M., De Jeu, R. A. M., Guichard, F., Harris, P. P., and Dorigo, W.
A.: Afternoon rain more likely over drier soils, Nature, 489, 282–286, 2012.
Wells, N., Goddard, S., and Hayes, M. J.: A self-calibrating palmer drought
severity index, J. Climate, 17, 2335–2351,
https://doi.org/10.1175/1520-0442(2004)017<2335:aspdsi>2.0.co;2, 2004.
Western, A. W. and Blöschl, G.: On the spatial scaling of soil moisture, J. Hydrol., 217, 203–224, https://doi.org/10.1016/s0022-1694(98)00232-7, 1999.
Wu, J. and Gao, X. J.: A gridded daily observation dataset over China region
and comparison with the other datasets, Chinese J. Geophys., 56, 1102–1111, https://doi.org/10.6038/cjg20130406, 2013.
Yun, Y., Liu, C., Luo, Y., Liang, X., Huang, L., Chen, F., and Rasmmusen, R.: Convection-permitting regional climate simulation of warm-season precipitation over Eastern China, Clim. Dynam., 54, 1469–1489, https://doi.org/10.1007/s00382-019-05070-y, 2020.
Zeng, J., Li, Z., Chen, Q., Bi, H., Qiu, J., and Zou, P.: Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan plateau using in-situ observations, Remote Sens. Environ., 163, 91–110, 2015.
Zhang, W., Zhou, T., and Zhi, H.: Numerical test of soil moisture affecting
summer climate in China, J. Meteorol., 70, 78–90, https://doi.org/10.1007/s11783-011-0280-z, 2012.
Zhu, Z., Shi, C., Zhang, T., and Wang, J.: Applicability analysis of four
reanalysis soil moisture datasets in China, Plateau Meteorol., 37, 240–252,
https://doi.org/10.7522/j.issn.1000-0534.2017.00033, 2018.
Zuo, Z. and Zhang, R.: Soil Moisture and its Impact on the East Asian Summer Monsoon, American Geophysical Union, Washington, DC, 2016.
Short summary
Soil moisture (SM) plays a critical role in the water and energy cycles of the Earth system, for which a long-term SM product with high quality is urgently needed. In situ observations are generally treated as the true value to systematically evaluate five SM products, including one remote sensing product and four reanalysis data sets during 1981–2013. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.
Soil moisture (SM) plays a critical role in the water and energy cycles of the Earth system, for...
