Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH
<p>We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the boreal zone. The parameter posterior distributions were generated by the adaptive population importance sampler (APIS); then the optimal v...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-09-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://www.geosci-model-dev.net/12/4075/2019/gmd-12-4075-2019.pdf |
| _version_ | 1828482449139564544 |
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| author | J. Mäkelä J. Knauer M. Aurela A. Black M. Heimann H. Kobayashi A. Lohila A. Lohila I. Mammarella H. Margolis T. Markkanen J. Susiluoto J. Susiluoto T. Thum T. Viskari S. Zaehle T. Aalto |
| author_facet | J. Mäkelä J. Knauer M. Aurela A. Black M. Heimann H. Kobayashi A. Lohila A. Lohila I. Mammarella H. Margolis T. Markkanen J. Susiluoto J. Susiluoto T. Thum T. Viskari S. Zaehle T. Aalto |
| author_sort | J. Mäkelä |
| collection | DOAJ |
| description | <p>We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the boreal zone. The parameter posterior distributions were generated by the adaptive population importance sampler (APIS); then the optimal values were estimated by a simple stochastic optimisation algorithm. The model was constrained with in situ observations of evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation.</p>
<p>The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity in spring. This modification enabled the model to correctly reproduce the springtime increase in GPP for all conifer sites used in this study. Overall, the calibration and model modifications improved the coefficient of determination and the model bias for GPP with all stomatal conductance formulations. However, only the coefficient of determination was clearly improved for ET. The optimisation resulted in best performance by the Bethy, Ball–Berry, and the Friend and Kiang stomatal conductance models.</p>
<p>We also optimised the model during a drought event at a Finnish Scots pine forest site. This optimisation improved the model behaviour but resulted in significant changes to the parameter values except for the unified stomatal optimisation model (USO). Interestingly, the USO demonstrated the best performance during this event.</p> |
| first_indexed | 2024-12-11T08:14:44Z |
| format | Article |
| id | doaj.art-62f11bf2acd84306a4e3a4e8e1b9e13a |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-12-11T08:14:44Z |
| publishDate | 2019-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-62f11bf2acd84306a4e3a4e8e1b9e13a2022-12-22T01:14:47ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032019-09-01124075409810.5194/gmd-12-4075-2019Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACHJ. Mäkelä0J. Knauer1M. Aurela2A. Black3M. Heimann4H. Kobayashi5A. Lohila6A. Lohila7I. Mammarella8H. Margolis9T. Markkanen10J. Susiluoto11J. Susiluoto12T. Thum13T. Viskari14S. Zaehle15T. Aalto16Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, FinlandMax Planck Institute for Biogeochemistry, 07745 Jena, GermanyFinnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, FinlandUniversity of British Columbia, Vancouver, CanadaMax Planck Institute for Biogeochemistry, 07745 Jena, GermanyInstitute of Arctic Climate and Environment Change Research, Japan Agency for Marine-Earth Science and Technology, Yokohama, JapanFinnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, FinlandInstitute for Atmospheric and Earth System Research/Physics, P.O. Box 48, Faculty of Science, 00014 University of Helsinki, Helsinki, FinlandInstitute for Atmospheric and Earth System Research/Physics, P.O. Box 48, Faculty of Science, 00014 University of Helsinki, Helsinki, FinlandDepartment of Forest Sciences, Laval University, Québec city, CanadaFinnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, FinlandFinnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, FinlandSchool of Engineering Science, Lappeenranta-Lahti University of Technology, P.O. Box 20, 53851 Lappeenranta, FinlandMax Planck Institute for Biogeochemistry, 07745 Jena, GermanyFinnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, FinlandMax Planck Institute for Biogeochemistry, 07745 Jena, GermanyFinnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland<p>We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the boreal zone. The parameter posterior distributions were generated by the adaptive population importance sampler (APIS); then the optimal values were estimated by a simple stochastic optimisation algorithm. The model was constrained with in situ observations of evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation.</p> <p>The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity in spring. This modification enabled the model to correctly reproduce the springtime increase in GPP for all conifer sites used in this study. Overall, the calibration and model modifications improved the coefficient of determination and the model bias for GPP with all stomatal conductance formulations. However, only the coefficient of determination was clearly improved for ET. The optimisation resulted in best performance by the Bethy, Ball–Berry, and the Friend and Kiang stomatal conductance models.</p> <p>We also optimised the model during a drought event at a Finnish Scots pine forest site. This optimisation improved the model behaviour but resulted in significant changes to the parameter values except for the unified stomatal optimisation model (USO). Interestingly, the USO demonstrated the best performance during this event.</p>https://www.geosci-model-dev.net/12/4075/2019/gmd-12-4075-2019.pdf |
| spellingShingle | J. Mäkelä J. Knauer M. Aurela A. Black M. Heimann H. Kobayashi A. Lohila A. Lohila I. Mammarella H. Margolis T. Markkanen J. Susiluoto J. Susiluoto T. Thum T. Viskari S. Zaehle T. Aalto Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH Geoscientific Model Development |
| title | Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH |
| title_full | Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH |
| title_fullStr | Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH |
| title_full_unstemmed | Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH |
| title_short | Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH |
| title_sort | parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model jsbach |
| url | https://www.geosci-model-dev.net/12/4075/2019/gmd-12-4075-2019.pdf |
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