Interpolation of surface radiative temperature measured from polar orbiting satellites to a diurnal cycle

Persistent Link:
http://hdl.handle.net/10150/282883
Title:
Interpolation of surface radiative temperature measured from polar orbiting satellites to a diurnal cycle
Author:
Jin, Menglin
Issue Date:
1999
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
The land surface skin temperature diurnal cycle (LSTD) is very important for the understanding of surface climate and for evaluating climate models. This variable, however, cannot be obtained globally from polar-orbiting satellites because the satellites usually pass a given area twice per day and because their infrared channels cannot observe the surface when the sky is cloudy. In order to more optimally use the satellite data, this research is designed, for the first time, to solve the above two problems by advance use of remote sensing techniques and climate modeling. Specifically, this work is divided into two parts. Part one deals with obtaining the skin temperature diurnal cycle for cloud-free cases. We have developed a "cloud-free algorithm" to combine model results with satellite and surface-based observations, thus interpolating satellite twice-daily observations to the diurnal cycle. Part two studies the cloudy cases. The "cloudy-pixel treatment" presented here is a hybrid technique of "neighboring-pixel" and "surface air temperature" approaches. The whole algorithm has been tested against field experiments and climate model CCM3/BATS in global and single column mode simulations. It shows that this proposed algorithm can obtain skin temperature diurnal cycles with an accuracy of 1-2 K at the monthly pixel level.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Physics, Atmospheric Science.; Environmental Sciences.; Remote Sensing.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Atmospheric Sciences
Degree Grantor:
University of Arizona
Advisor:
Dickinson, Robert E.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleInterpolation of surface radiative temperature measured from polar orbiting satellites to a diurnal cycleen_US
dc.creatorJin, Menglinen_US
dc.contributor.authorJin, Menglinen_US
dc.date.issued1999en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThe land surface skin temperature diurnal cycle (LSTD) is very important for the understanding of surface climate and for evaluating climate models. This variable, however, cannot be obtained globally from polar-orbiting satellites because the satellites usually pass a given area twice per day and because their infrared channels cannot observe the surface when the sky is cloudy. In order to more optimally use the satellite data, this research is designed, for the first time, to solve the above two problems by advance use of remote sensing techniques and climate modeling. Specifically, this work is divided into two parts. Part one deals with obtaining the skin temperature diurnal cycle for cloud-free cases. We have developed a "cloud-free algorithm" to combine model results with satellite and surface-based observations, thus interpolating satellite twice-daily observations to the diurnal cycle. Part two studies the cloudy cases. The "cloudy-pixel treatment" presented here is a hybrid technique of "neighboring-pixel" and "surface air temperature" approaches. The whole algorithm has been tested against field experiments and climate model CCM3/BATS in global and single column mode simulations. It shows that this proposed algorithm can obtain skin temperature diurnal cycles with an accuracy of 1-2 K at the monthly pixel level.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectPhysics, Atmospheric Science.en_US
dc.subjectEnvironmental Sciences.en_US
dc.subjectRemote Sensing.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineAtmospheric Sciencesen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorDickinson, Robert E.en_US
dc.identifier.proquest9923351en_US
dc.identifier.bibrecord.b39471147en_US
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