Mesoscale fluxes over heterogeneous flat landscapes for use in larger scale models

Roger A. Pielke; Xubin Zeng; Tsengdar J. Lee; Giovanni A. Dalu

doi:10.1016/S0022-1694(96)03132-0

Mesoscale fluxes over heterogeneous flat landscapes for use in larger scale models

Roger A. Pielke, Xubin Zeng, Tsengdar J. Lee, Giovanni A. Dalu

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

We have developed a framework to parameterize mesoscale fluxes of heat, moisture, and momentum, in a cloud-free environment, which result from heterogeneous heating of flat land surfaces. The importance and parameterizability of these mesoscale fluxes is demonstrated using the mathematical concept of predictability. This methodology is used to estimate the relative importance of mesoscale, as contrasted with turbulent fluxes, in the Konza Prairie of Kansas during the FIFE field experiment.

Original language	English (US)
Pages (from-to)	317-336
Number of pages	20
Journal	Journal of Hydrology
Volume	190
Issue number	3-4
DOIs	https://doi.org/10.1016/S0022-1694(96)03132-0
State	Published - Mar 15 1997
Externally published	Yes

ASJC Scopus subject areas

Water Science and Technology

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10.1016/S0022-1694(96)03132-0

Cite this

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title = "Mesoscale fluxes over heterogeneous flat landscapes for use in larger scale models",

abstract = "We have developed a framework to parameterize mesoscale fluxes of heat, moisture, and momentum, in a cloud-free environment, which result from heterogeneous heating of flat land surfaces. The importance and parameterizability of these mesoscale fluxes is demonstrated using the mathematical concept of predictability. This methodology is used to estimate the relative importance of mesoscale, as contrasted with turbulent fluxes, in the Konza Prairie of Kansas during the FIFE field experiment.",

author = "Pielke, {Roger A.} and Xubin Zeng and Lee, {Tsengdar J.} and Dalu, {Giovanni A.}",

note = "Funding Information: This work was supported by the National Science Foundation under grant no. ATM-8915265 and ATM-9306754, the National Aeronautics and Space Administration under grant no. NAG 5-2078, S-01, and the Climate System Modeling Program through subcontract no. UCAR S9361. The review of this paper by Roni Avissar was very much appreciated. The paper was ably edited by Dallas McDonald.",

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doi = "10.1016/S0022-1694(96)03132-0",

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T1 - Mesoscale fluxes over heterogeneous flat landscapes for use in larger scale models

AU - Pielke, Roger A.

AU - Zeng, Xubin

AU - Lee, Tsengdar J.

AU - Dalu, Giovanni A.

N1 - Funding Information: This work was supported by the National Science Foundation under grant no. ATM-8915265 and ATM-9306754, the National Aeronautics and Space Administration under grant no. NAG 5-2078, S-01, and the Climate System Modeling Program through subcontract no. UCAR S9361. The review of this paper by Roni Avissar was very much appreciated. The paper was ably edited by Dallas McDonald.

PY - 1997/3/15

Y1 - 1997/3/15

N2 - We have developed a framework to parameterize mesoscale fluxes of heat, moisture, and momentum, in a cloud-free environment, which result from heterogeneous heating of flat land surfaces. The importance and parameterizability of these mesoscale fluxes is demonstrated using the mathematical concept of predictability. This methodology is used to estimate the relative importance of mesoscale, as contrasted with turbulent fluxes, in the Konza Prairie of Kansas during the FIFE field experiment.

AB - We have developed a framework to parameterize mesoscale fluxes of heat, moisture, and momentum, in a cloud-free environment, which result from heterogeneous heating of flat land surfaces. The importance and parameterizability of these mesoscale fluxes is demonstrated using the mathematical concept of predictability. This methodology is used to estimate the relative importance of mesoscale, as contrasted with turbulent fluxes, in the Konza Prairie of Kansas during the FIFE field experiment.

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Mesoscale fluxes over heterogeneous flat landscapes for use in larger scale models

Abstract

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