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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 23, issue 6
Nonlin. Processes Geophys., 23, 447–465, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Nonlin. Processes Geophys., 23, 447–465, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 09 Dec 2016

Research article | 09 Dec 2016

Constraining ecosystem model with adaptive Metropolis algorithm using boreal forest site eddy covariance measurements

Jarmo Mäkelä et al.

Related authors

Soil carbon estimates by Yasso15 model improved with state data assimilation
Toni Viskari, Maisa Laine, Liisa Kulmala, Jarmo Mäkela, Istem Fer, and Jari Liski
Geosci. Model Dev. Discuss.,,, 2020
Revised manuscript accepted for GMD
Short summary
Sensitivity of 21st century simulated ecosystem indicators to model parameters, prescribed climate drivers, RCP scenarios and forest management actions for two Finnish boreal forest sites
Jarmo Mäkelä, Francesco Minunno, Tuula Aalto, Annikki Mäkelä, Tiina Markkanen, and Mikko Peltoniemi
Biogeosciences, 17, 2681–2700,,, 2020
Short summary
Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH
Jarmo Mäkelä, Jürgen Knauer, Mika Aurela, Andrew Black, Martin Heimann, Hideki Kobayashi, Annalea Lohila, Ivan Mammarella, Hank Margolis, Tiina Markkanen, Jouni Susiluoto, Tea Thum, Toni Viskari, Sönke Zaehle, and Tuula Aalto
Geosci. Model Dev., 12, 4075–4098,,, 2019
Short summary
Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC
Jouni Susiluoto, Maarit Raivonen, Leif Backman, Marko Laine, Jarmo Makela, Olli Peltola, Timo Vesala, and Tuula Aalto
Geosci. Model Dev., 11, 1199–1228,,, 2018
Short summary
Process-level improvements in CMIP5 models and their impact on tropical variability, the Southern Ocean, and monsoons
Axel Lauer, Colin Jones, Veronika Eyring, Martin Evaldsson, Stefan Hagemann, Jarmo Mäkelä, Gill Martin, Romain Roehrig, and Shiyu Wang
Earth Syst. Dynam., 9, 33–67,,, 2018

Related subject area

Subject: Predictability, probabilistic forecasts, data assimilation, inverse problems | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere
A method for predicting the uncompleted climate transition process
Pengcheng Yan, Guolin Feng, Wei Hou, and Ping Yang
Nonlin. Processes Geophys., 27, 489–500,,, 2020
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Statistical postprocessing of ensemble forecasts for severe weather at Deutscher Wetterdienst
Reinhold Hess
Nonlin. Processes Geophys., 27, 473–487,,, 2020
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Data-driven predictions of a multiscale Lorenz 96 chaotic system using machine-learning methods: reservoir computing, artificial neural network, and long short-term memory network
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Application of ensemble transform data assimilation methods for parameter estimation in nonlinear problems
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Nonlin. Processes Geophys. Discuss.,,, 2020
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Short summary
From research to applications – examples of operational ensemble post-processing in France using machine learning
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Cited articles

Aalto, T., Ciais, P., Chevillard, A., and Moulin, C.: Optimal determination of the parameters controlling biospheric CO2 fluxes over Europe using eddy covariance fluxes and satellite NDVI measurements, Tellus B, 56, 93–104,, 2004.
Abramowitz, G., Pitman, A., Gupta, H., Kowalczyk, E., and Wang, Y.: Systematic Bias in Land Surface Models, J. Hydrol., 8, 989–1001,, 2007.
Aurela, M.: Carbon dioxide exchange in subarctic ecosystems measured by a micrometeorological technique, Finnish Meteorol. Inst. Contr., 51, 1–39, 2005.
Aurela, M., Lohila, A., Tuovinen, J., Hatakka, J., Riutta, T., and Laurila, T.: Carbon dioxide exchange on a northern boreal fen, Boreal Environ. Res., 14, 699–710, 2009.
Baldocchi, D.: Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future, Global Change Biol., 9, 479–492,, 2003.
Publications Copernicus
Short summary
The land-based hydrological cycle is one of the key processes controlling the growth and wilting of plants and the amount of carbon vegetation can assimilate. Recent studies have shown that many land surface models have biases in this area. We optimized parameters in one such model (JSBACH) and were able to enhance the model performance in many respects, but the response to drought remained unaffected. Further studies into this aspect should include alternative stomatal conductance formulations.
The land-based hydrological cycle is one of the key processes controlling the growth and wilting...