Assimilating earth observation data into land surface models

T. Quaife*, P. Lewis, M. De Kauwe

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

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Abstract

Data assimilation techniques such as the ensemble Kalman filter and the sequential Metropolis-Hastings algorithm provide ameans of integrating satellite data with ecosystemmodels to optimally adjust their temporal trajectory. To some extent thesemethods can compensate for poor model parameterisations but a preferable scenario is to calibrate themodelwell in the first instance. This paper explores how a site specific model calibration can be adapted to a different site using only MODIS reflectance data. Results show that, using reflectance data only, estimates of the net carbon budget of a field site can be extended to a nearby site, but that this best facilitated by re-calibration rather than sequential data assimilation.

Original languageEnglish
Title of host publication2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
PagesV445-V448
Number of pages4
Volume5
Edition1
ISBN (Print)9781424428083
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings - Boston, MA, United States
Duration: 6 Jul 200811 Jul 2008

Other

Other2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
CountryUnited States
CityBoston, MA
Period6/07/0811/07/08

Bibliographical note

Copyright 2008 IEEE. Reprinted from 2008 IEEE International Geoscience & Remote Sensing Symposium : proceedings : July 6-11, 2008, John B. Hynes Veterans Memorial Convention Center, Boston, Massachusetts, U.S.A. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

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