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dc.contributor.authorRen, Diandong
dc.contributor.authorXue, M.
dc.date.accessioned2017-01-30T11:10:57Z
dc.date.available2017-01-30T11:10:57Z
dc.date.created2016-09-20T19:30:20Z
dc.date.issued2016
dc.date.submitted2016-09-21
dc.identifier.citationRen, D. and Xue, M. 2016. Retrieval of Land Surface Model State Variables through Assimilating Screen Level Humidity and Temperature Measurements. Advances in Meteorology. 1905076.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/9170
dc.identifier.doi10.1155/2016/1905076
dc.description.abstract

© 2016 Diandong Ren and Ming Xue. This study demonstrates successful variational retrieval of land surface states by assimilating screen level atmospheric measurements of specific humidity and air temperature. To this end, the land surface scheme is first validated against the Oklahoma Atmospheric Surface Layer Instrumentation System measurements with necessary refinements to the forward model implemented. The retrieval scheme involves a 1D land surface-Atmosphere model, the corresponding adjoint codes, and a cost function that measures residuals between observed and modeled screen level atmospheric temperature and specific humidity. The retrieval scheme is robust when subjected to observational errors with magnitudes comparable to instrument accuracy and for initial guess errors larger than typical model forecast errors. Using varying assimilation window lengths centered on different periods of a day, the sampling strategy is assessed. The daytime observations are more informative compared to nocturnal observations. An assimilation window as narrow as four hours, if centered on local noon, contains comparable information to an expanded window covering the whole day. There exists an optimal assimilation window length resulting from the contest between degrading forecast accuracy and increasing information content. For an assimilation window less than two days, the "optimal" assimilation window length is inversely proportional to the data ingesting frequency.

dc.titleRetrieval of Land Surface Model State Variables through Assimilating Screen Level Humidity and Temperature Measurements
dc.typeJournal Article
dcterms.dateSubmitted2016-09-21
dcterms.source.volume2016
dcterms.source.issn1687-9309
dcterms.source.titleAdvances in Meteorology
curtin.digitool.pid244478
curtin.pubStatusPublished
curtin.refereedTRUE
curtin.departmentDepartment of Physics and Astronomy
curtin.identifier.scriptidPUB-VC-ORD-SA-06015
curtin.identifier.elementsidELEMENTS-134230
curtin.accessStatusOpen access via publisher


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