Snow quenches our thirst, cools our planet

Publications

Displaying Items 1 - 25 of 119

2023

Bonnell, R. McGrath, D. Hedrick, A. Trujillo, E. Meehan, T.G. Marshall, H.P Sexton, G. Fulton, J. Ronayne, M. Fassnacht, S.R. Webb, R. Hale, K.
(2023). Snowpack relative permittivity and density derived from near-coincident lidar and ground-penetrating radar. Hydrological Processes, 37 (10), https://doi.org/10.1002/hyp.14996.
Borah, F. Tsang, L. Kim, E.
(2023). SWE Retrieval Algorithms Based on the Parameterized BI-Continuous DMRT Model Without Priors on Grain Size OR Scattering Albedo. Progress In Electromagnetics Research, 178, 129-147. http://dx.doi.org/10.2528/PIER23071101.
Cho, E. Vuyovich, C. Kumar, S. Wrzesien, M.L. Kim, R.S.
(2023). Evaluating the utility of active microwave observations as a snow mission concept using observing system simulation experiments. The Cryosphere, 17 (9), 3915-3931. https://doi.org/10.5194/tc-17-3915-2023.
Gao, S. Li, Z. Zhang, P. Chen, Q. Huang, L. Zhou, J. Zhao, C. Qiao, H. Zheng, Z.
(2023). A novel global snow depth retrieval method considering snow metamorphism and forest influence. Remote Sensing of Environment, 295, https://doi.org/10.1016/j.rse.2023.113712.
Hojatimalekshah, A. Gongora, J. Enterkine, J. Glenn, N. Caughlin, T. Marshall, H.P Hiemstra, C.
(2023). Lidar and deep learning reveal forest structural controls on snowpack. Frontiers in Ecology and the Environment. Frontiers in Ecology and the Environment, 21 (1), 49-54. https://doi.org/10.1002/fee.2584.
Hu, J.M. Shean, D. Bhushan, S.
(2023). Six consecutive seasons of high-resolution mountain snow depth maps from satellite stereo imagery. Geophysical Research Letters, 50 (24), https://doi.org/10.1029/2023GL104871.
McGrath, D. Zeller, L. Bonnell, R. Reis, W. Kampf, S. Williams, K.
(2023). Declines in peak snow water equivalent and elevated snowmelt rates following the 2020 Cameron Peak wildfire in Northern Colorado. Geophysical Research Letters, 50 (6), https://doi.org/10.1029/2022GL101294.
Palomaki, R. Sproles, E.
(2023). Assessment of L-band InSAR snow estimation techniques over a shallow, heterogeneous prairie snowpack. Remote Sensing of Environment, 296, https://doi.org/10.1016/j.rse.2023.113744.
Tarricone, J. Webb, R. Marshall, H.P Nolin, A. Meyer, F.J.
(2023). Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR). The Cryosphere, 17 (5), 1997-2019. https://doi.org/10.5194/tc-17-1997-2023.

2022

Cho, E. Kwon, Y. Kumar, S.V. Vuyovich, C.M.
(2022). Assimilation of airborne gamma observations provides utility for snow estimation in forested environments. Hydrology and Earth System Sciences Discussions, 1-26.
Cho, E. Vuyovich, C.M. Kumar, S.V. Wrzesien, M.L. Kim, R.S.
(2022). Evaluating the Utility of Active Microwave Observations as a Snow Mission Concept Using Observing System Simulation Experiments. The Cryosphere Discussions, 1-24.
Cho, E. Vuyovich, C.M. Kumar, S.V. Wrzesien, M.L. Kim, R.S. Jacobs, J.M.
(2022). Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent. Hydrology and Earth System Sciences, 1-22.
Enterkine, J. Campbell, B. Kohl, H. Glenn, N. Weaver, K. Overoye, D. Danke, D.
(2022). The potential of citizen science data to complement satellite and airborne lidar tree height measurements: lessons from The GLOBE Program. Environmental Research Letters, 17 (7), 075003. https://doi.org/10.1088/1748-9326/ac77a2.
Fang, Y. Liu, Y. Margulis, S.A.
(2022). A western United States snow reanalysis dataset over the Landsat era from water years 1985 to 2021. Scientific Data, 9 (1), 1-17.
Kang, D.H. Lee, K. Kim, E.
(2022). Improvement of springtime streamflow prediction using a snow hydrology model aided with USDA SNOTEL and in-situ snowpit observations. Hydrology Research, 53 (12), 1510-1528. https://doi.org/10.2166/nh.2022.180 .
Kraft, M. McNamara, J.P. Marshall, H.P. Glenn, N.F.
(2022). Forest impacts on snow accumulation and melt in a semi-arid environment. Frontiers in Water, 207. https://doi.org/10.3389/frwa.2022.1004123.
Lahmers, T.M. Kumar, S.V. Rosen, D. Dugger, A. Gochis, D.J. Santanello, J.A. Gangodagamage, C. Dunlap, R.
(2022). Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF‐Hydro System. Water Resources Research, 58 (3), e2021WR029867.
Liu, C. Li, Z. Zhang, P. Wu, Z.
(2022). Seasonal snow cover classification based on SAR imagery and topographic data. Remote Sensing Letters, 13 (3), 269-278. https://doi.org/10.1080/2150704X.2021.2018145.
Lumbrazo, C. Bennett, A. Currier, W.R. Nijssen, B. Lundquist, J.
(2022). Evaluating multiple canopy-snow unloading parameterizations in SUMMA with time-lapse photography characterized by citizen scientists. Water Resources Research, 58, https://doi.org/10.1029/2021WR030852.
Lund, J. Forster, R. Deeb, E. Liston, G. Skiles, S.M. Marshall, H.P
(2022). Interpreting Sentinel-1 SAR Backscatter Signals of Snowpack Surface Melt/Freeze, Warming, and Ripening, through Field Measurements and Physically-Based SnowModel. Remote Sensing, 14 (16), https://doi.org/10.3390/rs14164002 .
McGrath, D. Bonnell, R. Zeller, L. Olsen-Mikitowicz, A. Bump, E. Webb, R. Marshall, H.P
(2022). A time series of snow density and snow water equivalent observations derived from the integration of GPR and UAV SfM observations. Frontiers in Remote Sensing, 3, https://doi.org/10.3389/frsen.2022.886747.
Skiles, S.M. Clark, S. Ragar, D.
(2022). Hourly snow energy and mass balance at Atwater Study Plot, Alta, Utah. Hydrological Processes, 36 (3), https://doi.org/10.1002/hyp.14558SKILESET AL.5of5.
Smyth, E. Raleigh, M.S. Small, E.E.
(2022). The challenges of simulating SWE beneath forest canopies are reduced by data assimilation of snow depth.. Water Resources Research, 58 (3), https://doi.org/10.1029/2021WR030563.
Wrzesien, M.L. Kumar, S. Vuyovich, C. Gutmann, E.D. Kim, R.S. Forman, B.A. Durand, M. Raleigh, M.S. Webb, R. Houser, P.
(2022). Development of a “nature run” for observing system simulation experiments (OSSEs) for snow mission development. Journal of Hydrometeorology, 23 (3), 351-375. https://doi.org/10.1175/JHM-D-21-0071.1.
Yatheendradas, S. Kumar, S.
(2022). A Novel Machine Learning–Based Gap-Filling of Fine-Resolution Remotely Sensed Snow Cover Fraction Data by Combining Downscaling and Regression. Journal of Hydrometeorology, 23 (5), 637-658.

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