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dc.creatorHong, Sungwook
dc.date.accessioned2012-06-07T23:14:45Z
dc.date.available2012-06-07T23:14:45Z
dc.date.created2002
dc.date.issued2002
dc.identifier.urihttps://hdl.handle.net/1969.1/ETD-TAMU-2002-THESIS-H665
dc.descriptionDue to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item.en
dc.descriptionIncludes bibliographical references (leaves 81-83).en
dc.descriptionIssued also on microfiche from Lange Micrographics.en
dc.description.abstractTRMM Microwave Imager(TMI)-based passive microwave retrieval techniques result in biased estimates of the freezing level and rainfall over the east Pacific in the Inter Tropical Convergence Zone (ITCZ). Passive microwave rainfall estimates are usually based on microwave absorption, emission, and scattering, that is, the brightness temperatures measured with a microwave radiometer. For this study, the Wilheit el al. (1977) model is used as a starting point. The freezing level (FL), which is calculated from 19 and 21 GHz brightness temperature channels, serves as an important intermediate product within the above model. Atmospheric water vapor and surface temperature are determined by the FL in the passive microwave rainfall retrieval. Therefore, the FL, a rough estimate of the height of the liquid water column, is a crucial parameter to this rainfall estimation. For a raining cloud with a FL height of 5 km, an underestimation (overestimation) of FL by 0.5 km, for example, will result in a 10% overestimation (underestimation) of the rain rate. Thus, the correct FL retrieval is very important to determine whether or not a rainfall retrieval algorithm is reasonable. There may be two causes for this bias over the east Pacific. One is an extrinsic cause, such as different meteorological conditions from the model. If meteorological conditions differ from the models in a meaningful way, then the models will yield an erroneous FL. In this case, we may consider that the atmosphere is not in the standard condition. The other is an intrinsic cause in the model itself. For heavy rainfall (high brightness temperatures), the current algorithm may lead to a wrong FL retrieval due to increased non-uniformity of rainfall across the beam, and increased scattering effects. This is because the current algorithm assumes horizontal uniformity of rainfall across the beam, and strong scattering makes it more difficult to measure the rainfall accurately. An improved FL retrieval method may provide a clue to clarify a cause of bias over the east Pacific.en
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherTexas A&M University
dc.rightsThis thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries in 2008. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use.en
dc.subjectatmospheric sciences.en
dc.subjectMajor atmospheric sciences.en
dc.titleImproved freezing level retrievalen
dc.typeThesisen
thesis.degree.disciplineatmospheric sciencesen
thesis.degree.nameM.S.en
thesis.degree.levelMastersen
dc.type.genrethesisen
dc.type.materialtexten
dc.format.digitalOriginreformatted digitalen


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