Articles | Volume 20, issue 6
Hydrol. Earth Syst. Sci., 20, 2403–2419, 2016
https://doi.org/10.5194/hess-20-2403-2016
Hydrol. Earth Syst. Sci., 20, 2403–2419, 2016
https://doi.org/10.5194/hess-20-2403-2016
Research article
21 Jun 2016
Research article | 21 Jun 2016

Modelling evapotranspiration during precipitation deficits: identifying critical processes in a land surface model

Anna M. Ukkola et al.

Related authors

Opening Pandora's box: How to constrain regional projections of the carbon cycle
Lina Teckentrup, Martin Gerard De Kauwe, Gab Abramowitz, Andrew John Pitman, Anna Maria Ukkola, Sanaa Hobeichi, Bastien François, and Benjamin Smith
EGUsphere, https://doi.org/10.5194/egusphere-2022-623,https://doi.org/10.5194/egusphere-2022-623, 2022
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
Declining water resources in response to global warming and changes in atmospheric circulation patterns over southern Mediterranean France
Camille Labrousse, Wolfgang Ludwig, Sébastien Pinel, Mahrez Sadaoui, Andrea Toreti, and Guillaume Lacquement
Hydrol. Earth Syst. Sci., 26, 6055–6071, https://doi.org/10.5194/hess-26-6055-2022,https://doi.org/10.5194/hess-26-6055-2022, 2022
Short summary
Linking the complementary evaporation relationship with the Budyko framework for ungauged areas in Australia
Daeha Kim, Minha Choi, and Jong Ahn Chun
Hydrol. Earth Syst. Sci., 26, 5955–5969, https://doi.org/10.5194/hess-26-5955-2022,https://doi.org/10.5194/hess-26-5955-2022, 2022
Short summary
Risks of seasonal extreme rainfall events in Bangladesh under 1.5 and 2.0 °C warmer worlds – how anthropogenic aerosols change the story
Ruksana H. Rimi, Karsten Haustein, Emily J. Barbour, Sarah N. Sparrow, Sihan Li, David C. H. Wallom, and Myles R. Allen
Hydrol. Earth Syst. Sci., 26, 5737–5756, https://doi.org/10.5194/hess-26-5737-2022,https://doi.org/10.5194/hess-26-5737-2022, 2022
Short summary
Pan evaporation is increased by submerged macrophytes
Brigitta Simon-Gáspár, Gábor Soós, and Angela Anda
Hydrol. Earth Syst. Sci., 26, 4741–4756, https://doi.org/10.5194/hess-26-4741-2022,https://doi.org/10.5194/hess-26-4741-2022, 2022
Short summary
Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis
Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 26, 4603–4618, https://doi.org/10.5194/hess-26-4603-2022,https://doi.org/10.5194/hess-26-4603-2022, 2022
Short summary

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.
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.
Abramowitz, G., Leuning, R., Clark, M., and Pitman, A.: Evaluating the performance of land surface Models, J. Climate, 21, 5468–5481, https://doi.org/10.1175/2008JCLI2378.1, 2008.
Allen, C. D., Macalady, A. K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D. D., Hogg, E. H. (Ted), Gonzalez, P., Fensham, R., Zhang, Z., Castro, J., Demidova, N., Lim, J. H., Allard, G., Running, S. W., Semerci, A., and Cobb, N.: A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests, Forest Ecol. Manage., 259, 660–684, https://doi.org/10.1016/j.foreco.2009.09.001, 2010.
Ball, T., Woodrow, I., and Berry, J.: A model predicting stomatal conductance and its contribution to the control of photosynthesis under different environmental conditions, in Progress in Photosynthesis Research, edited by: Biggins, J., Martinus Nijhoff, Leiden, the Netherlands, 221–224, 1987.
Download