Articles | Volume 27, issue 21
https://doi.org/10.5194/hess-27-4039-2023
https://doi.org/10.5194/hess-27-4039-2023
Research article
 | 
10 Nov 2023
Research article |  | 10 Nov 2023

Assimilation of airborne gamma observations provides utility for snow estimation in forested environments

Eunsang Cho, Yonghwan Kwon, Sujay V. Kumar, and Carrie M. Vuyovich

Data sets

Airborne Gamma Radiation Snow Survey Program: A User's Guide, Version 5.0, National Operational Hydrologic Remote Sensing Center (NOHRSC) T. R. Carroll Airborne Gamma Radiation Snow Survey Program: A User's Guide, Version 5.0, National Operational Hydrologic Remote Sensing Center (NOHRSC)

Data for ``Assimilation of airborne gamma observations provides utility for snow estimation in forested environments'' E. Cho, Y. Kwon, S. V. Kumar, and C. M. Vuyovich http://www.hydroshare.org/resource/fc5c757899fb49a5869e597451120a33

Snowpack change from 1982 to 2016 over conterminous United States (https://nsidc.org/data/nsidc-0719) X. Zeng, P. Broxton, and N. Dawson https://doi.org/10.1029/2018GL079621

The AMSR-E snow depth algorithm: description and initial results (https://www.eorc.jaxa.jp/AMSR/datacatalog/land/#snd) R. Kelly https://doi.org/10.11440/rssj.29.307

The Modern-Era Retrospective Analysis for Research and Applications (https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/data_access/) R. Gelaro, W. McCarty, M. J. Suárez, R. Todling, A. Molod, L. Takacs, C. A. Randles, A. Darmenov, M. G. Bosilovich, R. Reichle, K. Wargan, L. Coy, R. Cullather, C. Draper, S. Akella, V. Buchard, A. Conaty, A. M. da Silva, W. Gu, G.-K. Kim, R. Koster, R. Lucchesi, D. Merkova, J. E. Nielsen, G. Partyka, S. Pawson, W. Putman, M. Rienecker, S. D. Schubert, M. Sienkiewicz, and B. Zhao https://doi.org/10.1175/JCLI-D-16-0758.1

Land information system: An interoperable framework for high resolution land surface modeling (https://github.com/NASA-LIS/LISF) S. V. Kumar, C. D. Peters-Lidard, Y. Tian, P. R. Houser, J. Geiger, S. Olden, L. Lighty, J. L. Eastman, B. Doty, P. Dirmeyer, J. Adams, K. Mitchell, E. F. Wood, and J. Sheffield https://doi.org/10.1016/j.envsoft.2005.07.004

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Short summary
An airborne gamma-ray remote-sensing technique provides reliable snow water equivalent (SWE) in a forested area where remote-sensing techniques (e.g., passive microwave) typically have large uncertainties. Here, we explore the utility of assimilating the gamma snow data into a land surface model to improve the modeled SWE estimates in the northeastern US. Results provide new insights into utilizing the gamma SWE data for enhanced land surface model simulations in forested environments.