MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Undergraduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Undergraduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

An observing system simulation experiment for soil moisture measurements from the SMAP radiometer

Author(s)
Konings, Alexandra Georges
Thumbnail
DownloadFull printable version (5.660Mb)
Other Contributors
Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.
Advisor
Dara Entekhabi.
Terms of use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
The Soil Moisture Active Passive (SMAP) satellite, to be launched in 2013, will use both radiometer and radar data to estimate soil moisture. Improved soil moisture knowledge has many applications in hydroclimatology, numerical weather prediction, flood forecasting, and human health. In this thesis, an observing system simulation experiment (OSSE) was used to study the error structure of radiometer measurements using two different retrieval algorithms. In an OSSE, geophysical fields are used to create a model of surface emission, which is coupled to an orbital sampling module and proposed retrieval algorithms. Comparing output from the retrieval algorithm to the starting soil moisture values demonstrates retrieval error. Significant uncertainty remains about the optimal representation of the effect of dielectric mixing, soil roughness, and vegetation opacity on radiometric emissions at a given soil moisture. The effect of this uncertainty on retrieval algorithms is studied by using different representations for each term in the forward and retrieval modules of the OSSE. Uncertainty due to roughness causes less error than errors in dielectric mixing and vegetation opacity treatment. In both algorithms, the retrieval shows a spatially variable bias, which is particularly large when using a single-polarization retrieval algorithm. The spatial and temporal variation of the bias, and the implications for characterization and removal of this bias as a possible error reduction strategy, are discussed.
Description
Thesis (S.B. in Environmental Engineering Science)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2009.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (p. 57-61).
 
Date issued
2009
URI
http://hdl.handle.net/1721.1/70758
Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Publisher
Massachusetts Institute of Technology
Keywords
Civil and Environmental Engineering.

Collections
  • Undergraduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.