HR: 0800h
AN: C21A-1080    [Abstracts]
TI: Evaluation of the NOAA/NWS National Snow Analyses Snow Model: Internal Physical Properties of a Snowpack
AU: * Li, L
EM: long.li@noaa.gov
AF: National Weather Service, NOAA, 1375 Lake Street, West, Chanhassen, MN 55317 United States
AU: Cline, D W
EM: Donald.Cline@noaa.gov
AF: National Weather Service, NOAA, 1375 Lake Street, West, Chanhassen, MN 55317 United States
AU: Rutter, N
EM: nick.rutter@aber.ac.uk
AF: Centre for Glaciology, University of Wales, Aberystwyth, SY23 3DB United Kingdom
AB: Abstract The NOAA/NWS National Snow Analyses Snow Model (NSM) is a distributed multi-layer snow energy and mass balance model developed for high-resolution large-region land-surface modeling. The model is used operationally by the National Weather Service's National Operational Hydrologic Remote Sensing Center (NOHRSC) in its snow data assimilation system (www.nohrsc.noaa.gov). Operationally, the model is forced by downscaled mesoscale weather analyses and model states are updated regularly with all available ground, airborne and satellite observations of snow water equivalent, snow depth, and snow cover. To evaluate the physical formulations and skill of the NSM, we have conducted a series of tests of the model in 1D-mode over the 2002-2003 snow season using in situ observed forcings and intensive snow observations at five sites of the NASA Cold Land Processes Experiment (CLPX). For an additional point of reference, we have conducted the same tests using a well-known 1D snow energy and mass balance model, SNTHERM.89. Previous tests demonstrated that the NSM (and SNTHERM) simulates the evolution of snow water equivalent and depth over the course of the season with high accuracy. This is of first-order importance for the NOHRSC's operational hydrology needs. Here, we present the results of further tests that examine the ability of the NSM to simulate the internal vertical distribution of temperature and density. A goal for models like NSM is to use them for forward estimation of microwave radiative transfer for snow-covered regions to improve assimilation of microwave remote sensing data. For this objective grain size and other internal snowpack parameters must be estimated accurately. The first-order driver for grain size is the internal temperature gradient and its effect on snow metamorphism and snowpack structure, therefore it is critical that the models are able to correctly simulate the vertical temperature and density profiles. The test results indicated that during the accumulation season (when the snowpack temperatures were typically less than 0 degree C), the NSM consistently underestimated the average snowpack temperature by 2-3 K, and the internal temperature profile was distorted. Warming of the snowpacks to isothermal conditions at 0 degree C occurred at the appropriate time, however, and thereafter the model agreed well with observations. The cold-season deficiency was traced to the formulation of downward longwave radiation. This was confirmed using observed longwave data to drive the NSM. Further improvements in the temperature profile simulations were gained by implementing new formulations for sub-surface penetration of incident solar radiation into the snowpack and for heat transfer by windpumping, i.e. the movement of air within the snowpack near the upper surface.
DE: 1827 Glaciology (0736, 0776, 1863)
DE: 1863 Snow and ice (0736, 0738, 0776, 1827)
SC: Cryosphere [C]
MN: Fall Meeting 2005