This page lists the most recently-uploaded publications that have been added to the ESD Publications database. Select one or more Research Program(s) to filter the list.

Publication Citation Research Program(s) Updated date
Smith, J. B., et al. (2017), A case study of convectively sourced water vapor observed in the overworld stratosphere over the United States, J. Geophys. Res., 122, 9529-9554, doi:10.1002/2017JD026831. TCP 8/20/2020
Punge, H. J., et al. (2017), Hail frequency estimation across Europe based on a combination of overshooting top detections and the ERA-Interim reanalysis, Atmos. Res., 198, 34-43. 8/20/2020
Apke, J. M., et al. (2018), Relationships between Deep Convection Updraft Characteristics and Satellite-Based Super Rapid Scan Mesoscale Atmospheric Motion Vector-Derived Flow, Mon. Wea. Rev., 146, 3461-3480, doi:10.1175/MWR-D-18-0119.1. 8/20/2020
Bedka, K., et al. (2018), The Above-Anvil Cirrus Plume: An Important Severe Weather Indicator in Visible and Infrared Satellite Imagery, Wea. Forecasting, 33, 1159-1181, doi:10.1175/WAF-D-18-0040.1. 8/20/2020
Sandmæl, T. N., et al. (2020), Evaluating the Ability of Remote Sensing Observations to Identify Significantly Severe and Potentially Tornadic Storms, J. Appl. Meteor. Climat., doi:10.1175/JAMC-D-18-0241.1. 8/20/2020
Clapp, C., et al. (2019), Identifying source regions and the distribution of cross‐tropopause convective outflow over North America during the warm season, J. Geophys. Res., 124, 13750-, doi:10.1029/2019JD031382. 8/20/2020
Bedka, K., et al. (2019), Analysis and Automated Detection of Ice Crystal Icing Conditions Using Geostationary Satellite Datasets and In Situ Ice Water Content Measurements, SAE Technical Paper, 2019-01-1953, 2019, doi:10.4271/2019-01-1953. ADP 8/20/2020
Bedka, K., et al. (2019), Analysis and Automated Detection of Ice Crystal Icing Conditions Using Geostationary Satellite Datasets and In Situ Ice Water Content Measurements, SAE Technical Paper, 2019-01-1953, 2019, doi:10.4271/2019-01-1953. ADP 8/20/2020
Ghobadi‐Far, K., et al. (2020), GRACE Follow‐On Laser Ranging Interferometer Measurements Uniquely Distinguish Short‐Wavelength Gravitational Perturbations, Geophys. Res. Lett., 47, e2020GL089445, doi:10.1029/2020GL089445. ESI 8/13/2020
Molan, Y. E., Z. Lu, and J. W. Kim (2020), Influence of the Statistical Properties of Phase and Intensity on Closure Phase, IEEE Trans. Geosci. Remote Sens., 58, doi:10.1109/TGRS.2020.2982062. ESI 8/9/2020
Molan, Y. E., and Z. Lu (2020), Modeling InSAR Phase and SAR Intensity Changes Induced by Soil Moisture, IEEE Trans. Geosci. Remote Sens., 1-9, doi:10.1109/TGRS.2020.2970841. ESI 8/9/2020
Molan, Y. E., and Z. Lu (2020), Can InSAR Coherence and Closure Phase Be Used to Estimate Soil Moisture Changes?, Remote Sensing, doi:10.3390/rs12091511. ESI 8/9/2020
DeGrandpre, K. G., et al. (2020), All Rights Reserved. High Rates of Inflation During a Noneruptive Episode of Seismic Unrest at Semisopochnoi Volcano, Alaska in 2014–2015, Geochem., Geophys., Geosyst., 20. ESI 8/9/2020
Xue, X., J. Freymueller, and Z. Lu (2020), Modeling the Posteruptive Deformation at Okmok Based on the GPS and InSAR Time Series: Changes in the Shallow Magma Storage System, J. Geophys. Res., 125, e2019JB017801, doi:10.1029/2019JB017801. ESI 8/9/2020
Xu, Y., et al. (2019), Characterizing Seasonally Rainfall-Driven Movement of a Translational Landslide using SAR Imagery and SMAP Soil Moisture, Remote Sensing, doi:10.3390/rs11202347. IDS 8/9/2020
Zheng, W. Y., et al. (2019), Wastewater leakage in West Texas revealed by satellite radar imagery and numerical modeling, Scientific Reports, 9, 14601, doi:10.1038/s41598-019-51138-4. ESI 8/9/2020
Albright, J., et al. (2020), Hindcasting Magma Reservoir Stability Preceding the 2008 Eruption of Okmok, Alaska, Geophys. Res. Lett., 46, doi:10.1029/2019GL083395. ESI 8/9/2020
Qu, F., et al. (2020), Identify and Monitor Growth Faulting Using InSAR over Northern Greater Houston, Texas, USA, Remote Sensing, doi:10.3390/rs11121498. ESI 8/9/2020
Chirayath, Dr. V., and Instrella (2019), Fluid Lensing and Machine Learning for Automated Centimeter-Resolution Airborne Assessment of Coral Reefs in American Samoa without Ocean Wave Distortion, Remote Sensing of Environment, 235, 111475, doi:10.1016/j.rse.2019.111475. 8/7/2020
Chirayath, Dr. V., and Li (2020), Next-Generation Optical Sensing Technologies for Exploring Ocean Worlds - NASA FluidCam, MiDAR, and NeMO-Net, Frontiers in Marine Science, 6, 521, doi:doi.org/10.3389/fmars.2019.005. 8/7/2020

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