| 588 | | The parameterization starts with several 1-pixel test cases coinciding with long-term flux-net sites to test whether the model captures the growth dynamics such as phenology, max LAI, GPP, etc. These tests require a spin-up. The 1-pixel test cases will allow for both parameter tuning and changes in the code to improve the model behaviour. The majority of the data represent mature forests, hence, the modelled forests should be mature as well. The model will be run for 80 years, before any output will be compared to the FLUXNET measurements. An iterative process is be planned: |
| 589 | | * 80 years to reach mature forest → parameterize |
| 590 | | * Re-run the 80 years to reach mature forest with the new parameters → parameterize |
| 591 | | * Re-run spin-up and 80 year simulation to reach mature forest with the new parameters → parameterize |
| | 588 | The parameterization starts with several 1-pixel test cases coinciding with long-term flux-net sites to test whether the model captures the growth dynamics such as phenology, max LAI, GPP, etc. These tests require a spin-up. The 1-pixel test cases will allow for both parameter tuning and changes in the code to improve the model behaviour. The majority of the data represent mature forests, hence, the modelled forests should be mature as well. The ENSEMBLE runs consists of several steps of which the last step is a clear cut after which the forest is replanted in the same year as the observations. This procedure is not exact because we have to cycle over the fluxnet climate drivers. Simulation and data will thus come from forest of approximately the same age. An iterative process is be planned: |
| | 589 | * Spin-up, clearcut, run to match the observed age → parameterize |
| | 590 | * Re-run to match the observed age with the new parameters → parameterize |
| | 591 | * Re-run spin-up clearcut, run to match the observed age with the new parameters → parameterize |
| 594 | | The current scripts for FLUXNET evaluation are broken down into three parts. 1) An initial looping over the driver file (1-10 years, depending on the file), 2) 500 years of spinup (regardless of the length of driver file), 3) one final loop over the driver file, for production. Tests for the grassland and cropland sites can easily use the existing setup. Given the temporal evolution of forest structure and their fluxes, testing now needs 80 years from planting after spinup as a production run over the forcing file to avoid trees dying and biasing our results. The FLUXNET script will need to be adjusted to do this. Possible issues with age classes (i.e., changes in the PFT of interest) will be avoided by using a run.def without age classes. |
| 595 | | |
| 596 | | Only if we experience too many difficulties with manual tuning (if there are too many non-linearities in the model), we will use the multi-site optimization tool developed by Vlad . When the simulated growth dynamics are satisfying, 140 years long tests will be performed to check cumulative variables such as basal area, tree height, tree diameter, stand density, standing biomass, and harvest. To evaluate net ecosystem exchange of carbon and soil carbon and nitrogen pools a spin-up is required. Note that the spin-up depends on the parameters used in ORCHIDEE and that the sensitivity of parameters in ORCHIDEE depends on the spin-up. There is no easy way to break this dependency. We should avoid to ‘over-tune’ the 1-pixel FLUXNET comparisons. Instead, we will continue evaluating the model over longitudinal bands. |
| | 594 | Only if we experience too many difficulties with manual tuning (if there are too many non-linearities in the model), we will use the multi-site optimization tool developed by Vlad. When the simulated growth dynamics are satisfying, 140 years long tests will be performed to check cumulative variables such as basal area, tree height, tree diameter, stand density, standing biomass, and harvest. To evaluate net ecosystem exchange of carbon and soil carbon and nitrogen pools a spin-up is required. Note that the spin-up depends on the parameters used in ORCHIDEE and that the sensitivity of parameters in ORCHIDEE depends on the spin-up. There is no easy way to break this dependency. We should avoid to ‘over-tune’ the 1-pixel FLUXNET comparisons. Instead, we will continue evaluating the model over longitudinal bands or geographical regions, e.g., Siberia. |
