Article
Engineering, Electrical & Electronic
Jiaxin Tian, Hui Lu, Kun Yang, Jun Qin, Long Zhao, Yaozhi Jiang, Pengfei Shi, Xiaogang Ma, Jianhong Zhou
Summary: Soil moisture plays a vital role in the global terrestrial water, energy, and carbon cycles. This article develops a novel land surface temperature assimilation scheme, which improves soil moisture estimation accuracy by linking simulated ensembles of soil moisture with remote sensing land surface temperature.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Engineering, Electrical & Electronic
Asif Mahmood, Leila Farhadi
Summary: This study develops a variational data assimilation framework to couple estimation of evapotranspiration and recharge fluxes by assimilating land surface soil moisture and temperature observations into a coupled water and energy balance model. The results demonstrate the success of the framework in estimating evaporative and recharge fluxes from implicit information contained in the observations, and the feasibility test results show promise in extending the framework to large scale using remotely sensed observations.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Zhen Zhang, Abhishek Chatterjee, Lesley Ott, Rolf Reichle, Andrew F. Feldman, Benjamin Poulter
Summary: Soil moisture plays a crucial role in the carbon-water coupling process in terrestrial ecosystems. Utilizing soil moisture data from the SMAP satellite mission can improve model simulations of carbon fluxes and enhance predictions under extreme events.
Article
Environmental Sciences
Xinlei He, Tongren Xu, Sayed M. Bateni, Seo Jin Ki, Jingfeng Xiao, Shaomin Liu, Lisheng Song, Xiangping He
Summary: In this study, a variational data assimilation (VDA) system is used to merge land surface temperature (LST) and leaf area index (LAI) observations with a coupled two-source surface energy budget-vegetation dynamic model (TSEB-VDM) to predict turbulent heat fluxes and gross primary productivity (GPP). The VDA approach, evaluated at six AmeriFlux sites, shows good agreement between modeled and measured sensible (H) and latent (LE) heat fluxes, and GPP under different environmental conditions. Results suggest that the VDA method can effectively estimate H, LE, and GPP by utilizing implicit information in LST and LAI measurements.
WATER RESOURCES RESEARCH
(2021)
Article
Water Resources
Andrew M. Ireson, Ines Sanchez-Rodriguez, Sujan Basnet, Haley Brauner, Talia Bobenic, Rosa Brannen, Mennatullah Elrashidy, Morgan Braaten, Seth K. Amankwah, Alan Barr
Summary: This study uses soil moisture data from five long-term field sites and tests two configurations to constrain modelled hydrological fluxes. The results show that the calibration based on hydraulic properties outperforms the texture-based calibration in reproducing changes in soil moisture storage. However, both methods perform reasonably well, especially in the summer months. The predicted hydrological fluxes, when constrained by soil moisture observations, have large uncertainties associated with equifinality. The uncertainty is larger for the hydraulic properties-based calibration, despite its better performance. Therefore, additional sources of information are recommended to reduce uncertainties.
HYDROLOGICAL PROCESSES
(2022)
Article
Engineering, Civil
Jun Qin, Jiaxin Tian, Kun Yang, Hui Lu, Xin Li, Ling Yao, Jiancheng Shi
Summary: Soil moisture plays a critical role in land surface energy and water cycles and is considered an essential climate variable. Microwave remote sensing offers the potential to estimate soil moisture in real-time on a large scale. In this study, a dual-cycle assimilation algorithm is proposed to correct bias in satellite soil moisture products. Numerical experiments show that the presented algorithm outperforms existing correction schemes.
JOURNAL OF HYDROLOGY
(2022)
Article
Geosciences, Multidisciplinary
Tasnuva Rouf, Manuela Girotto, Paul Houser, Viviana Maggioni
Summary: This article focuses on developing a data assimilation system that combines modeled surface moisture estimates with satellite observations, showing that assimilating SMAP soil moisture retrievals improves model performance. Using higher resolution atmospheric forcings leads to higher correlations and smaller errors in soil moisture simulations, highlighting the importance of data resolution in improving accuracy.
JOURNAL OF HYDROLOGY X
(2021)
Article
Meteorology & Atmospheric Sciences
Nina Raoult, Catherine Ottle, Philippe Peylin, Vladislav Bastrikov, Pascal Maugis
Summary: Investigating the rate at which land surface soils dry after rain events is crucial for terrestrial models. By using observation-based estimates of decay time scale τ, the representation of surface soil moisture (SSM) can be improved, leading to better calibration of the model's drydown processes.
JOURNAL OF HYDROMETEOROLOGY
(2021)
Article
Meteorology & Atmospheric Sciences
Yamin Qing, Shuo Wang, Zong-Liang Yang, Pierre Gentine, Boen Zhang, Jagger Alexander
Summary: The study reveals that there has been a significant increase in soil drying rate in wet regions over the past four decades, with an average increase of 6.01% to 9.90% per decade, while there is no consistent trend in dry regions. Atmospheric aridity and high temperatures are identified as the main factors leading to the increase in soil drying rate in wet regions.
NPJ CLIMATE AND ATMOSPHERIC SCIENCE
(2023)
Article
Meteorology & Atmospheric Sciences
Tongren Xu, Fei Chen, Xinlei He, Michael Barlage, Zhe Zhang, Shaomin Liu, Xiangping He
Summary: The proposed multipass land data assimilation scheme (MLDAS) based on the Noah-MP-Crop model effectively constrains model state variables and optimizes key crop-model parameters by jointly assimilating multiple observations. The MLDAS demonstrates good agreement with observed sensible heat, latent heat, and gross primary productivity, indicating that physical models can greatly benefit from assimilating multi-source observations within MLDAS.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2021)
Article
Geochemistry & Geophysics
Long Zhao, Kun Yang, Jie He, Hui Zheng, Donghai Zheng
Summary: This study explores the feasibility of mapping global soil type and texture using satellite data, demonstrating that the proposed scheme can accurately map soil types compared to existing models. This is particularly crucial for remote areas with limited soil samples.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Civil
Jacopo Dari, Pere Quintana-Segui, Maria Jose Escorihuela, Vivien Stefan, Luca Brocca, Renato Morbidelli
Summary: This study investigates the capability of remotely sensed soil moisture products to detect irrigation signals in an intensively irrigated area in North East Spain, proposing a method to map actually irrigated areas using the K-means clustering algorithm. The data sets used in this study include SMOS, SMAP, Sentinel-1, and ASCAT, with downscaled versions obtained by the DISPATCH algorithm. L-band passive microwave downscaling products, particularly SMAP at 1 km, show the best performance in detecting irrigation signals in the study area.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
Leqiang Sun, Stephane Belair, Marco L. Carrera, Bernard Bilodeau, Mohammed Dabboor
Summary: This paper presents the assimilation of synthetic surface soil moisture retrievals and C-band backscatter signal using EnKF filter to reduce the impact of nonlinear errors. Results show that assimilating backscatter is as effective as soil moisture retrievals assimilation, with some advantage in temporal statistics. Both methods significantly improved the analysis of surface and root zone soil moisture.
WATER RESOURCES RESEARCH
(2021)
Article
Environmental Sciences
Jiaxin Tian, Jun Qin, Kun Yang, Long Zhao, Yingying Chen, Hui Lu, Xin Li, Jiancheng Shi
Summary: Soil moisture is crucial for land surface processes. Data assimilation can merge satellite observations and land surface models to improve soil moisture estimation. In this study, a dual-cycle assimilation algorithm is proposed, which can simultaneously estimate model parameters, observation operator parameters, model error, and observation error, and outperforms traditional algorithms.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Meteorology & Atmospheric Sciences
Zdenko Heyvaert, Samuel Scherrer, Michel Bechtold, Alexander Gruber, Wouter Dorigo, Sujay Kumar, Gabrielle De Lannoy
Summary: In this study, the combination of active-passive ESA Climate Change Initiative soil moisture product with the Noah-MP land surface model is evaluated over Europe. The impact of different design choices on the performance of the data assimilation system is explored. The choice of observation errors, observation bias correction method, and atmospheric reanalysis dataset all affect the skill improvements.
JOURNAL OF HYDROMETEOROLOGY
(2023)