Earth and Atmospheric Sciences, Department of

 

First Advisor

Dr. Matthew Van Den Broeke

Date of this Version

11-2016

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska in Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Earth and Atmospheric Sciences, Under the Supervision of Professor Matthew Van Den Broeke. Lincoln, Nebraska: November 2016

Copyright (c) 2016 Andrew J. Kalin

Abstract

In this study, the validity of 3 LSMs (Community Land Model version 4.0, Noah-MP and the Budyko Bucket Hydrology model [henceforth referred to as ‘Bucket model’]) coupled with the Weather Research and Forecasting model version 3.6 (WRF3.6), was examined in an effort to show the associated strengths and weaknesses of each LSM. This objective was completed by first, developing expected results based on a simple surface energy budget calculation, and by later comparing model output to Parameter-elevation Relationships on Independent Slopes Model (PRISM) data, which serve as gridded observed values of mean monthly temperature and total monthly precipitation. Model output temperature, precipitation, sensible heat (SH), latent heat (LH), downward solar radiation, and soil water content (SWC) are also compared to observations from several Atmospheric Radiation Measurement (ARM) and AmeriFlux sites across the Central and Southern Great Plains. The LSM output analysis revealed an overall warm bias in CLM4.0 and Noah-MP, with a cool bias of larger magnitude in the Bucket model. All 3 LSMs produced similar patterns of wet and dry biases when compared to each other across identical time periods, but no overall bias for any particular LSM emerged. Biases in model output of SWC, SH, LH, and downward solar radiation compared to observations, were consistent with what would be expected based on results from the surface energy budget component of the study. While many factors should be considered when choosing a LSM, both sophisticated LSMs seem to be viable options for simulating the effects of land use change in the Southern Great Plains region, while the limitations of the Bucket model with detailed surface energy calculations make it less suitable for such a detailed study.

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