| 485 | | Process Parameter(s) Tool |
| 486 | | Onset of growing season and start of senescence thresholds for phenology FLUXNET |
| 487 | | NPP/GPP ratio coeff for maintenance respiration FLUXNET + Campioli |
| 488 | | Magnitude of LAI k_latosa_min and k_latosa_max NFI + Luyssaert et al 2007 |
| 489 | | Magnitude of GPP LL_alpha, Vcmax, J_max FLUXNET |
| 490 | | Magnitude of NPP Implicit through NPP/GPP and GPP Luyssaert et al 2007 |
| 491 | | Evapotranspiration LAI_top, water stress FLUXNET |
| 492 | | Water stress To be discovered FLUXNET |
| 493 | | Magnitude of Rh To be checked - Rh Luyssaert et al 2007 |
| 494 | | Magnitude of TER To be checked - Rh FLUXNET |
| 495 | | Diameter, height, and biomass form factor NFI + Luyssaert et al 2007 |
| 496 | | density and biomass self-thinning parameters NFI + Luyssaert et al 2007 |
| 497 | | Harvest and biomass Self-thinning and RDI parameters NFI + ??? |
| 498 | | Albedo Implicit through LAI and forest structure FLUXNET? |
| 499 | | Tree ring width Self-thinning, recruitment ITRDB or VERIFY Fig 4 |
| | 486 | || '''Process''' || '''Parameter(s)''' || '''Tool''' || |
| | 487 | || Onset of growing season and start of senescence || thresholds for phenology || FLUXNET || |
| | 488 | || NPP/GPP ratio || coeff for maintenance respiration || FLUXNET + Campioli || |
| | 489 | || Magnitude of LAI || k_latosa_min and k_latosa_max || NFI + Luyssaert et al 2007 || |
| | 490 | || Magnitude of GPP || LL_alpha, Vcmax, J_max || FLUXNET || |
| | 491 | || Magnitude of NPP || Implicit through NPP/GPP and GPP || Luyssaert et al 2007 || |
| | 492 | || Evapotranspiration || LAI_top, water stress || FLUXNET || |
| | 493 | || Water stress || To be discovered || FLUXNET || |
| | 494 | || Magnitude of Rh || To be checked - Rh || Luyssaert et al 2007 || |
| | 495 | || Magnitude of TER || To be checked - Rh || FLUXNET || |
| | 496 | || Diameter, height, and biomass || form factor || NFI + Luyssaert et al 2007 || |
| | 497 | || Density and biomass || self-thinning parameters || NFI + Luyssaert et al 2007 || |
| | 498 | || Harvest and biomass || Self-thinning and RDI parameters || NFI + ??? || |
| | 499 | || Albedo || Implicit through LAI and forest structure || FLUXNET? || |
| | 500 | || Tree ring width || Self-thinning, recruitment || ITRDB or VERIFY Fig 4 || |
| 540 | | Table 4. Observational data products to evaluate European control simulation |
| 541 | | Observations Tool |
| 542 | | EU-wide NFI data (Fig. 3) through the VERIFY project ??? |
| 543 | | Jung GPP – relies on FLUXNET thus partly circular XXX |
| 544 | | Jung evapotranspiration – relies on FLUXNET thus partly circular XXX |
| 545 | | MODIS albedo NIR & VIS XXX |
| 546 | | Remote sensing tree height XXX |
| 547 | | Extract effective LAI from MODIS XXX |
| 548 | | BA from JRC – relies on NFI thus partly circular XXX |
| 549 | | Biomass from JRC – relies on NFI thus partly circular ??? |
| 550 | | Biomass from Turner – Remote sensing? ??? |
| 551 | | Harvest from Schelhaas - data through the VERIFY project ??? |
| 552 | | LCC – Luyssaert et al 2014 XXX |
| 553 | | LCC – Duveiller et al 2018 ??? |
| 554 | | |
| | 540 | Table 5. Observational data products to evaluate European control simulation |
| | 541 | || '''Observations''' || '''Tool''' || |
| | 542 | || EU-wide NFI data (Fig. 3) through the VERIFY project || ??? || |
| | 543 | || Jung GPP – relies on FLUXNET thus partly circular || XXX || |
| | 544 | || Jung evapotranspiration – relies on FLUXNET thus partly circular || XXX || |
| | 545 | || MODIS albedo NIR & VIS || XXX || |
| | 546 | || Remote sensing tree height || XXX || |
| | 547 | || Extract effective LAI from MODIS || XXX || |
| | 548 | || BA from JRC – relies on NFI thus partly circular || XXX || |
| | 549 | || Biomass from JRC – relies on NFI thus partly circular || ??? || |
| | 550 | || Biomass from Turner – Remote sensing? || ??? || |
| | 551 | || Harvest from Schelhaas - data through the VERIFY project || ??? || |
| | 552 | || LCC – Luyssaert et al 2014 || XXX || |
| | 553 | || LCC – Duveiller et al 2018 || ??? || |
| 559 | | • Identify the variables that are targeted by the spin-up (such as NEP, heterotrophic respiration, decomposition etc). The spin-up will reveal whether parameters affecting these variables need to be tuned. The spin-up itself is also an interesting test case that could be loosely compared against data. |
| 560 | | • We could compare the spin-ups to maps of soil carbon stocks to check the order of magnitude. Soil carbon maps should only be formally compared with the control run (spin-up + transient simulation) for the year 2000 because that run includes the simulated effects of N-deposition, management, litter raking and land cover change. The more simple configurations of the spin-up do not account for these processes or do not account for the right sequence of processes |
| | 558 | * Identify the variables that are targeted by the spin-up (such as NEP, heterotrophic respiration, decomposition etc). The spin-up will reveal whether parameters affecting these variables need to be tuned. The spin-up itself is also an interesting test case that could be loosely compared against data. |
| | 559 | * We could compare the spin-ups to maps of soil carbon stocks to check the order of magnitude. Soil carbon maps should only be formally compared with the control run (spin-up + transient simulation) for the year 2000 because that run includes the simulated effects of N-deposition, management, litter raking and land cover change. The more simple configurations of the spin-up do not account for these processes or do not account for the right sequence of processes |
