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Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

Journal of climate, 2011-12, Vol.24 (24), p.6322-6338

2011

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Prediction of Active Microwave Backscatter Over Snow-Covered Terrain Across Western Colorado Using a Land Surface Model and Support Vector Machine Regression

IEEE journal of selected topics in applied earth observations and remote sensing, 2021, Vol.14, p.2403-2417

2021

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Exploring the Spatiotemporal Coverage of Terrestrial Snow Mass Using a Suite of Satellite Constellation Configurations

Remote sensing (Basel, Switzerland), 2022-02, Vol.14 (3), p.633

2022

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Assimilation of MODIS Snow Cover Fraction Observations into the NASA Catchment Land Surface Model

Remote sensing (Basel, Switzerland), 2018-01, Vol.10 (2), p.316-316

2018

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Permafrost variability over the Northern Hemisphere based on the MERRA-2 reanalysis

The cryosphere, 2019-08, Vol.13 (8), p.2087-2110

2019

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Evaluating the Uncertainty of Terrestrial Water Budget Components over High Mountain Asia

Frontiers in earth science (Lausanne), 2019-05, Vol.7

2019

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Evaluation of GEOS-Simulated L-Band Microwave Brightness Temperature using Aquarius Observations over Non-Frozen Land across North America

Remote sensing (Basel, Switzerland), 2020-09, Vol.12 (18), p.3098

2020

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Quantifying the observational requirements of a space-borne LiDAR snow mission

Journal of hydrology (Amsterdam), 2021-10, Vol.601, p.126709, Article 126709

2021

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Estimating Terrestrial Snow Mass via Multi-sensor Assimilation of Synthetic AMSR-E Brightness Temperature Spectral Differences and Synthetic GRACE Terrestrial Water Storage Retrievals

Water resources research, 2021-09, Vol.57 (9), p.n/a

2021

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Snowfall Replenishes Groundwater Loss in the Great Basin of the Western United States, but Cannot Compensate for Increasing Aridification

Geophysical research letters, 2024-03, Vol.51 (6), p.n/a

2024

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Soil Moisture Estimation in South Asia via Assimilation of SMAP Retrievals

Hydrology and earth system sciences, 2022-04, Vol.26 (8), p.2221-2243

2022

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Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia

Remote sensing (Basel, Switzerland), 2019-09, Vol.11 (19), p.2265

2019

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Estimating snow mass in North America through assimilation of AMSR-E brightness temperature observations using the Catchment land surface model and support vector machines

Water resources research, 2018-09, Vol.54 (9), p.6488-6509

2018

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Estimation of Snow Mass Information via Assimilation of C-Band Synthetic Aperture Radar Backscatter Observations Into an Advanced Land Surface Model

IEEE journal of selected topics in applied earth observations and remote sensing, 2022, Vol.15, p.862-875

2022

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Estimating Passive Microwave Brightness Temperature Over Snow-Covered Land in North America Using a Land Surface Model and an Artificial Neural Network

IEEE transactions on geoscience and remote sensing, 2014-01, Vol.52 (1), p.235-248

2014

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Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling

The cryosphere, 2021-02, Vol.15 (2), p.771-791

2021

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Analyzing Machine Learning Predictions of Passive Microwave Brightness Temperature Spectral Difference Over Snow-Covered Terrain in High Mountain Asia

Frontiers in earth science (Lausanne), 2019-08, Vol.7

2019

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Passive Microwave Brightness Temperature Assimilation to Improve Snow Mass Estimation Across Complex Terrain in Pakistan, Afghanistan, and Tajikistan

IEEE journal of selected topics in applied earth observations and remote sensing, 2021-01, Vol.14, p.8849-8863

2021

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Connecting Satellite Observations with Water Cycle Variables Through Land Data Assimilation: Examples Using the NASA GEOS-5 LDAS

Surveys in geophysics, 2014-05, Vol.35 (3), p.577-606

2014

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Achieving Breakthroughs in Global Hydrologic Science by Unlocking the Power of Multisensor, Multidisciplinary Earth Observations

AGU advances, 2021-12, Vol.2 (4), p.n/a

2021

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Evaluation of ensemble-based distributed hydrologic model response with disaggregated precipitation products

Water resources research, 2008-12, Vol.44 (12), p.W12409-n/a

2008

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Assimilation of Ground‐Based GPS Observations of Vertical Displacement into a Land Surface Model to Improve Terrestrial Water Storage Estimates

Water resources research, 2021-02, Vol.57 (2), p.n/a

2021

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Exploration of Synthetic Terrestrial Snow Mass Estimation via Assimilation of AMSR‐E Brightness Temperature Spectral Differences Using the Catchment Land Surface Model and Support Vector Machine Regression

Water resources research, 2021-02, Vol.57 (2), p.n/a

2021

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Estimating Snow Mass in North America Through Assimilation of Advanced Microwave Scanning Radiometer Brightness Temperature Observations Using the Catchment Land Surface Model and Support Vector Machines

Water resources research, 2018-09, Vol.54 (9), p.6488-6509

2018

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Machine learning predictions of passive microwave brightness temperature over snow-covered land using the special sensor microwave imager (SSM/I)

Physical geography, 2017-03, Vol.38 (2), p.176-196

2017

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Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

Prediction of Active Microwave Backscatter Over Snow-Covered Terrain Across Western Colorado Using a Land Surface Model and Support Vector Machine Regression

Exploring the Spatiotemporal Coverage of Terrestrial Snow Mass Using a Suite of Satellite Constellation Configurations

Assimilation of MODIS Snow Cover Fraction Observations into the NASA Catchment Land Surface Model

Permafrost variability over the Northern Hemisphere based on the MERRA-2 reanalysis

Evaluating the Uncertainty of Terrestrial Water Budget Components over High Mountain Asia

Evaluation of GEOS-Simulated L-Band Microwave Brightness Temperature using Aquarius Observations over Non-Frozen Land across North America

Quantifying the observational requirements of a space-borne LiDAR snow mission

Estimating Terrestrial Snow Mass via Multi-sensor Assimilation of Synthetic AMSR-E Brightness Temperature Spectral Differences and Synthetic GRACE Terrestrial Water Storage Retrievals

Snowfall Replenishes Groundwater Loss in the Great Basin of the Western United States, but Cannot Compensate for Increasing Aridification

Soil Moisture Estimation in South Asia via Assimilation of SMAP Retrievals

Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia

Estimating snow mass in North America through assimilation of AMSR-E brightness temperature observations using the Catchment land surface model and support vector machines

Estimation of Snow Mass Information via Assimilation of C-Band Synthetic Aperture Radar Backscatter Observations Into an Advanced Land Surface Model

Estimating Passive Microwave Brightness Temperature Over Snow-Covered Land in North America Using a Land Surface Model and an Artificial Neural Network

Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling

Analyzing Machine Learning Predictions of Passive Microwave Brightness Temperature Spectral Difference Over Snow-Covered Terrain in High Mountain Asia

Passive Microwave Brightness Temperature Assimilation to Improve Snow Mass Estimation Across Complex Terrain in Pakistan, Afghanistan, and Tajikistan

Connecting Satellite Observations with Water Cycle Variables Through Land Data Assimilation: Examples Using the NASA GEOS-5 LDAS

Achieving Breakthroughs in Global Hydrologic Science by Unlocking the Power of Multisensor, Multidisciplinary Earth Observations

Evaluation of ensemble-based distributed hydrologic model response with disaggregated precipitation products

Assimilation of Ground‐Based GPS Observations of Vertical Displacement into a Land Surface Model to Improve Terrestrial Water Storage Estimates

Exploration of Synthetic Terrestrial Snow Mass Estimation via Assimilation of AMSR‐E Brightness Temperature Spectral Differences Using the Catchment Land Surface Model and Support Vector Machine Regression

Estimating Snow Mass in North America Through Assimilation of Advanced Microwave Scanning Radiometer Brightness Temperature Observations Using the Catchment Land Surface Model and Support Vector Machines

Machine learning predictions of passive microwave brightness temperature over snow-covered land using the special sensor microwave imager (SSM/I)

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