Articles | Volume 19, issue 7
https://doi.org/10.5194/bg-19-1913-2022
https://doi.org/10.5194/bg-19-1913-2022
Research article
 | 
05 Apr 2022
Research article |  | 05 Apr 2022

Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems

Jon Cranko Page, Martin G. De Kauwe, Gab Abramowitz, Jamie Cleverly, Nina Hinko-Najera, Mark J. Hovenden, Yao Liu, Andy J. Pitman, and Kiona Ogle

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Cited articles

Abramowitz, G.: Towards a public, standardized, diagnostic benchmarking system for land surface models, Geosci. Model Dev., 5, 819–827, https://doi.org/10.5194/gmd-5-819-2012, 2012. a, b
Abramowitz, G., Pitman, A., Gupta, H., Kowalczyk, E., and Wang, Y.: Systematic Bias in Land Surface Models, J. Hydrometeorol., 8, 989–1001, https://doi.org/10.1175/JHM628.1, 2007. a
Abramowitz, G., Leuning, R., Clark, M., and Pitman, A.: Evaluating the Performance of Land Surface Models, J. Clim., 21, 5468–5481, https://doi.org/10.1175/2008JCLI2378.1, 2008. a
Anderegg, W. R. L., Schwalm, C., Biondi, F., Camarero, J. J., Koch, G., Litvak, M., Ogle, K., Shaw, J. D., Shevliakova, E., Williams, A. P., Wolf, A., Ziaco, E., and Pacala, S.: Pervasive Drought Legacies in Forest Ecosystems and Their Implications for Carbon Cycle Models, Science, 349, 528–532, https://doi.org/10.1126/science.aab1833, 2015. a, b, c, d
Arndt, S., Hinko-Najera, N., and Griebel, A.: Wombat Wombat State Forest Flux Data Collection Level 6, Terrestrial Ecosystem Research Network (TERN) [data set], https://hdl.handle.net/102.100.100/14237 (last access: 21 September 2021), 2013. a
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Although vegetation responds to climate at a wide range of timescales, models of the land carbon sink often ignore responses that do not occur instantly. In this study, we explore the timescales at which Australian ecosystems respond to climate. We identified that carbon and water fluxes can be modelled more accurately if we include environmental drivers from up to a year in the past. The importance of antecedent conditions is related to ecosystem aridity but is also influenced by other factors.
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