Submitted to: Journal of Geophysical Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/25/1999
Publication Date: N/A
Citation: N/A Interpretive Summary: The ETA model is one of the principal computer models used by the National Weather Service for weather prediction. One of its limitations has been that it does not simulate freezing and thawing of soil and melting of snow, and this has affected its accuracy in forecasting weather during late winter and early spring. In this project, a new portion of the model was developed to address this deficiency. The new component of the model divides the soil profile into four layers and simulates freezing and thawing based on thermodynamic principles. It was tested by comparing model results against field measurements of snow depth, soil temperature, and soil water and ice contents that were made in a farm field at the University of Minnesota's Rosemount Agricultural Experiment Station. We found that the model matched the experimental data reasonably well, whereas if the previous approach was used there were substantial errors in the prediction of soil temperature and water content. These additions to the model should result in improved weather forecasting in regions of the country where snow and frozen soil occur.
Technical Abstract: Extensions to the land surface scheme (LSS) in the NCEP, regional, coupled, land-atmosphere weather prediction model, known as the mesoscale Eta model, are proposed and tested off-line in uncoupled mode to account for seasonal freezing and thawing of soils, and snow accumulation-ablation processes. An original model assumption that there is no significant heat transfer during gredistribution of liquid water was relaxed by including a source/sink term in the heat transfer equation to account for latent heat during phase transitions of soil moisture. The parameterization uses the layer- integrated form of heat and water diffusion equations adopted by the original Eta-LSS. Therefore it simulates the total ice content of each selected soil layer. Infiltration reduction under frozen ground conditions was estimated by probabilistic averaging of spatially variable ice content of the soil profile. Off-line uncoupled tests of the new and original Eta- LSS were performed using experimental data from Rosemount, Minnesota. Simulated soil temperature and unfrozen water content matched observed data reasonably well. Neglecting frozen ground processes leads to significant underestimation/overestimation of soil temperature during soil freezing/thawing periods and underestimates total soil moisture content after extensive periods of soil freezing.