Affiliation
Univ Arizona, Dept Hydrol & Atmospher SciIssue Date
2017-01
Metadata
Show full item recordPublisher
AMER METEOROLOGICAL SOCCitation
A New Snow Density Parameterization for Land Data Initialization 2017, 18 (1):197 Journal of HydrometeorologyJournal
Journal of HydrometeorologyRights
© 2017 American Meteorological SocietyCollection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Snow initialization is crucial for weather and seasonal prediction, but the National Centers for Environmental Prediction (NCEP) operational models have been found to produce too little snow water equivalent, partly because they assume a constant and unrealistically low snow density for the snowpack. One possible solution is to use the snow density formulation from the Noah land model used in NCEP operational forecast models. While this solution is better than the constant density assumption, the seasonal evolution of snow density in Noah is still found to be unrealistic, through the evaluation of both the offline Noah model output and the Noah snow density formulation itself. A physically based snow density parameterization is then developed, which performs considerably better than the Noah parameterization based on the measurements from the SNOTEL network over the western United States and Alaska. It also performs better than the snow density schemes used in three other models. This parameterization could be easily implemented in NCEP operational snow initialization. With the consideration of up to 10 snow layers, this parameterization can also be applied to multilayer snowpack initiation or to estimate snow water equivalent from in situ and airborne snow depth measurements.Note
6 month embargo; published online 10 January 2017.ISSN
1525-755X1525-7541
Version
Final published versionAdditional Links
http://journals.ametsoc.org/doi/10.1175/JHM-D-16-0166.1ae974a485f413a2113503eed53cd6c53
10.1175/JHM-D-16-0166.1