Articles | Volume 8, issue 11
Geosci. Model Dev., 8, 3695–3713, 2015
https://doi.org/10.5194/gmd-8-3695-2015
Geosci. Model Dev., 8, 3695–3713, 2015
https://doi.org/10.5194/gmd-8-3695-2015

Development and technical paper 17 Nov 2015

Development and technical paper | 17 Nov 2015

A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP)

N. Kljun et al.

Related authors

Field-scale CH4 emission at a sub-arctic mire with heterogeneous permafrost thaw status
Patryk Łakomiec, Jutta Holst, Thomas Friborg, Patrick Crill, Niklas Rakos, Natascha Kljun, Per-Ola Olsson, Lars Eklundh, and Janne Rinne
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-81,https://doi.org/10.5194/bg-2021-81, 2021
Revised manuscript accepted for BG
Short summary
Methane efflux from an American bison herd
Paul C. Stoy, Adam A. Cook, John E. Dore, Natascha Kljun, William Kleindl, E. N. Jack Brookshire, and Tobias Gerken
Biogeosciences, 18, 961–975, https://doi.org/10.5194/bg-18-961-2021,https://doi.org/10.5194/bg-18-961-2021, 2021
Short summary
Technical note: Dynamic INtegrated Gap-filling and partitioning for OzFlux (DINGO)
Jason Beringer, Ian McHugh, Lindsay B. Hutley, Peter Isaac, and Natascha Kljun
Biogeosciences, 14, 1457–1460, https://doi.org/10.5194/bg-14-1457-2017,https://doi.org/10.5194/bg-14-1457-2017, 2017
Short summary
Carbon uptake and water use in woodlands and forests in southern Australia during an extreme heat wave event in the “Angry Summer” of 2012/2013
Eva van Gorsel, Sebastian Wolf, James Cleverly, Peter Isaac, Vanessa Haverd, Cäcilia Ewenz, Stefan Arndt, Jason Beringer, Víctor Resco de Dios, Bradley J. Evans, Anne Griebel, Lindsay B. Hutley, Trevor Keenan, Natascha Kljun, Craig Macfarlane, Wayne S. Meyer, Ian McHugh, Elise Pendall, Suzanne M. Prober, and Richard Silberstein
Biogeosciences, 13, 5947–5964, https://doi.org/10.5194/bg-13-5947-2016,https://doi.org/10.5194/bg-13-5947-2016, 2016
Short summary

Related subject area

Biogeosciences
Accounting for forest management in the estimation of forest carbon balance using the dynamic vegetation model LPJ-GUESS (v4.0, r9710): implementation and evaluation of simulations for Europe
Mats Lindeskog, Benjamin Smith, Fredrik Lagergren, Ekaterina Sycheva, Andrej Ficko, Hans Pretzsch, and Anja Rammig
Geosci. Model Dev., 14, 6071–6112, https://doi.org/10.5194/gmd-14-6071-2021,https://doi.org/10.5194/gmd-14-6071-2021, 2021
Short summary
FABM-NflexPD 1.0: assessing an instantaneous acclimation approach for modeling phytoplankton growth
Onur Kerimoglu, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 14, 6025–6047, https://doi.org/10.5194/gmd-14-6025-2021,https://doi.org/10.5194/gmd-14-6025-2021, 2021
Short summary
A model for marine sedimentary carbonate diagenesis and paleoclimate proxy signal tracking: IMP v1.0
Yoshiki Kanzaki, Dominik Hülse, Sandra Kirtland Turner, and Andy Ridgwell
Geosci. Model Dev., 14, 5999–6023, https://doi.org/10.5194/gmd-14-5999-2021,https://doi.org/10.5194/gmd-14-5999-2021, 2021
Short summary
Using the International Tree-Ring Data Bank (ITRDB) records as century-long benchmarks for global land-surface models
Jina Jeong, Jonathan Barichivich, Philippe Peylin, Vanessa Haverd, Matthew Joseph McGrath, Nicolas Vuichard, Michael Neil Evans, Flurin Babst, and Sebastiaan Luyssaert
Geosci. Model Dev., 14, 5891–5913, https://doi.org/10.5194/gmd-14-5891-2021,https://doi.org/10.5194/gmd-14-5891-2021, 2021
Short summary
A model-independent data assimilation (MIDA) module and its applications in ecology
Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021,https://doi.org/10.5194/gmd-14-5217-2021, 2021
Short summary

Cited articles

Aubinet, M., Chermanne, B., Vandenhaute, M., Longdoz, B., Yernaux, M., and Laitat, E.: Long Term Carbon Dioxide Exchange Above a Mixed Forest in the Belgian Ardennes, Agr. Forest Meteorol., 108, 293–315, 2001.
Baldocchi, D.: Flux Footprints Within and Over Forest Canopies, Bound.-Lay. Meteorol., 85, 273–292, 1997.
Barcza, Z., Kern, A., Haszpra, L., and Kljun, N.: Spatial Representativeness of Tall Tower Eddy Covariance Measurements Using Remote Sensing and Footprint Analysis, Agr. Forest Meteorol., 149, 795–807, 2009.
Batchvarova, E. and Gryning, S.-E.: Applied Model for the Growth of the Daytime Mixed Layer, Bound.-Lay. Meteorol., 56, 261–274, 1991.
Chang, J. C. and Hanna, S. R.: Air Quality Model Performance Evaluation, Meteorol. Atmos. Phys., 87, 167–196, 2004.
Download
Short summary
Flux footprint models describe the surface area of influence of a flux measurement. They are used for designing flux tower sites, and for interpretation of flux measurements. The two-dimensional footprint parameterisation (FFP) presented here is suitable for processing large data sets, and, unlike other fast footprint models, FFP is applicable to daytime or night-time measurements, fluxes from short masts over grassland to tall towers over mature forests, and even to airborne flux measurements.