Publications
Displaying Items 1 - 25 of 102
2022
- (2022). Assimilation of airborne gamma observations provides utility for snow estimation in forested environments. Hydrology and Earth System Sciences Discussions, 1-26.
- (2022). Evaluating the Utility of Active Microwave Observations as a Snow Mission Concept Using Observing System Simulation Experiments. The Cryosphere Discussions, 1-24.
- (2022). Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent. Hydrology and Earth System Sciences, 1-22.
- (2022). A western United States snow reanalysis dataset over the Landsat era from water years 1985 to 2021. Scientific Data, 9 (1), 1-17.
- (2022). Forest impacts on snow accumulation and melt in a semi-arid environment. Frontiers in Water, 207.
- (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.
- (2022). Development of a “nature run” for observing system simulation experiments (OSSEs) for snow mission development. Journal of Hydrometeorology, 23 (3), 351-375.
- (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.
2021
- (2021). Spatiotemporal Variations in Liquid Water Content in a Seasonal Snowpack: Implications for Radar Remote Sensing. Remote Sens., 13, 4223. https://doi.org/10.3390/rs13214223.
- (2021). Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning. The Cryosphere, 15 (5), 2187-2209.
- (2021). Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling. The Cryosphere, 15 (2), 771-791.
- (2021). Quantifying the observational requirements of a space-borne LiDAR snow mission. Journal of Hydrology, 601, p126709.
- (2021). The retrieval of snow properties from SLSTR Sentinel-3 – Part 2: Results and validation. The Cryosphere, 15, 2781–2802. https://doi.org/10.5194/tc-15-2781-2021.
- (2021). In Situ Determination of Dry and Wet Snow Permittivity: Improving Equations for Low Frequency Radar Applications. Remote Sens., 13, 4617. https://doi.org/10.3390/rs13224617.
2020
- (2020). Weather-Dependent Nonlinear Microwave Behavior of Seasonal High-Elevation Snowpacks. Remote Sens., 12, 3422. https://doi.org/10.3390/rs12203422.
- (2020). Parsing synthetic aperture radar measurements of snow in complex terrain: scaling behaviour and sensitivity to snow wetness and land cover. Remote Sensing, 12 (3), 483.
- (2020). Within‐stand boundary effects on snow water equivalent distribution in forested areas. Water Resources Research, 56 (10), e2019WR024905.
2019
- (2019). Comparing aerial lidar observations with terrestrial lidar and snow‐probe transects from NASA's 2017 SnowEx campaign. Water Resources Research, 55 (7), 6285-6294.
- (2019). Revisiting snow cover variability and canopy structure within forest stands: Insights from airborne lidar data. Water Resources Research, 55 (7), 6198-6216.
- (2019). Spatially extensive ground‐penetrating radar snow depth observations during NASA's 2017 SnowEx campaign: Comparison with In situ, airborne, and satellite observations. Water Resources Research, 55 (11), 10026-10036.
- (2019). Assessing the ability of Structure from Motion to map high‐resolution snow surface elevations in complex terrain: A case study from Senator Beck Basin, CO. Water Resources Research, 55 (8), 6596-6605.
- (2019). Observations of a coniferous forest at 9.6 and 17.2 GHz: Implications for SWE retrievals. Remote Sensing, 11 (1), 6.
2018
- (2018). A multilayer IST – albedo product of Greenland from MODIS. Remote Sensing [Special Issue: Remote Sensing of Essential Climate Variables and their Applications], 10 (4), 555. 10.3390/rs10040555.
- (2018). On the frequency of lake-effect snowfall in the Catskill Mountains. Physical Geography, 1-17. 10.1080/02723646.2018.1440827.
- (2018). How Can We Find Out How Much Snow Is in the World?. Eos, 99,