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dc.contributor.authorJankov, Mihailo
dc.date.accessioned2015-09-02T01:24:34Z
dc.date.available2015-09-02T01:24:34Z
dc.date.issued2005-08
dc.identifier.urihttp://hdl.handle.net/11122/5911
dc.descriptionThesis (M.S.) University of Alaska Fairbanks, 2005en_US
dc.description.abstractLand surface models (LSMs) serve to describe the atmosphere-land surface exchange in numerical weather prediction models (NWPMs) and global circulation models (GCMs). The use of empirical soil and vegetation parameters in LSMs introduces uncertainty that propagates and affects predictions of the lower boundary conditions. To statistically assess that uncertainty in predicted evapotranspiration (water transport by direct evaporation from bare ground and canopy and transpiration by the canopy) and ground heat flux for natural ranges of atmospheric soil and vegetation conditions, the Gaussian Error Propagation method is utilized. The assessed uncertainties in direct and canopy water evaporation, transpiration and ground heat flux display prominent diurnal cycles. Prediction of evapotranspiration in desert areas is limited by the uncertainty in the evaporation of water collected on the canopy and transpiration. To improve predictions of evapotranspiration the maximal canopy storage and shielding factor should be determined with higher accuracy. It is found that uncertainty in ground heat flux is particularly great in dry and warm areas covered with sandy clay loam. A better prediction of ground heat flux requires a better parameterization of thermal conductivity and a higher degree of accuracy of the pore size distribution index.en_US
dc.description.tableofcontentsIntroduction -- Uncertainty of predicted evapotranspiration caused by empiracal soil and vegetation parameters -- Uncertainty of predicted ground heat flux density -- References -- Conclusions.en_US
dc.language.isoen_USen_US
dc.titleAnalysis of uncertainty in simulated exchange of heat and moisture at the land-atmosphere interfaceen_US
dc.typeThesisen_US
dc.type.degreemsen_US
dc.identifier.departmentProgram in Atmospheric Sciencesen_US
refterms.dateFOA2020-03-13T01:27:05Z


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