Computational Tools for Chemical Data Assimilation with CMAQ

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dc.contributor.authorGou, Tianyien
dc.contributor.committeechairSandu, Adrianen
dc.contributor.committeememberCao, Yangen
dc.contributor.committeememberMarr, Linsey C.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2014-03-14T20:31:00Zen
dc.date.adate2010-02-15en
dc.date.available2014-03-14T20:31:00Zen
dc.date.issued2010-01-11en
dc.date.rdate2010-02-15en
dc.date.sdate2010-01-21en
dc.description.abstractThe Community Multiscale Air Quality (CMAQ) system is the Environmental Protection Agency's main modeling tool for atmospheric pollution studies. CMAQ-ADJ, the adjoint model of CMAQ, offers new analysis capabilities such as receptor-oriented sensitivity analysis and chemical data assimilation. This thesis presents the construction, validation, and properties of new adjoint modules in CMAQ, and illustrates their use in sensitivity analyses and data assimilation experiments. The new module of discrete adjoint of advection is implemented with the aid of automatic differentiation tool (TAMC) and is fully validated by comparing the adjoint sensitivities with finite difference values. In addition, adjoint sensitivity with respect to boundary conditions and boundary condition scaling factors are developed and validated in CMAQ. To investigate numerically the impact of the continuous and discrete advection adjoints on data assimilation, various four dimensional variational (4D-Var) data assimilation experiments are carried out with the 1D advection PDE, and with CMAQ advection using synthetic and real observation data. The results show that optimization procedure gives better estimates of the reference initial condition and converges faster when using gradients computed by the continuous adjoint approach. This counter-intuitive result is explained using the nonlinearity properties of the piecewise parabolic method (the numerical discretization of advection in CMAQ). Data assimilation experiments are carried out using real observation data. The simulation domain encompasses Texas and the simulation period is August 30 to September 1, 2006. Data assimilation is used to improve both initial and boundary conditions. These experiments further validate the tools developed in this thesis.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-01212010-174148en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-01212010-174148/en
dc.identifier.urihttp://hdl.handle.net/10919/31017en
dc.publisherVirginia Techen
dc.relation.haspartGou_TY_T_2010.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectData Assimilationen
dc.subjectChemical Transport Modelsen
dc.subjectAdjoint Sensitivity Analysisen
dc.titleComputational Tools for Chemical Data Assimilation with CMAQen
dc.typeThesisen
thesis.degree.disciplineComputer Scienceen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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