Changes between Version 80 and Version 81 of DevelopmentActivities/ORCHIDEE-CNP
- Timestamp:
- 2016-03-08T13:46:23+01:00 (8 years ago)
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DevelopmentActivities/ORCHIDEE-CNP
v80 v81 11 11 12 12 13 == 1. Technical notes : the modularisation of code used by nitrogen and phosphorus routines ==13 == 1. Technical notes A: the modularisation of code used by nitrogen and phosphorus routines == 14 14 There are aspects which the nutrient cycles have in common, for example root uptake kinetics, stoichiometric considerations, etc. To avoid the risks of introducing inconsistencies and reduce redundant code, I introduced the following subroutines. All subroutines are in stomate_phosphorus.f90. 15 15 … … 19 19 === 1.2 f_XY_plant === 20 20 This subroutine calculates the scaling functions based on the stoichiometric ratio of labile plant tissue (reserve, labile and leaf) which are used to scale root uptake, biological N2 fixation, and biochemical mineralization. It currently supports scaling functions based on the P-to-N ratio, N-to-C ratio and P-to-C ratio. All other combinations will cause a 'STOP', but could be easily implemented if needed. 21 22 == 2. Technical notes B: the analytical spinup of the biogeochemical cycles == 23 24 === 2.1 avoid that immobilisation demand exceeds mineral nutrient supply === 25 Directly, after an analytic spinup cycle the immobilisation demand can exceed the mineral nutrient supply (soil_n_min or soil_p_min). 26 In such a case, we have to add artificially the needed amount of nutrients to the supply. The flag ok_spunup controls that only in the timestep after the analytical solution is derived nutrients can be added. 27 28 === 2.2 prescribed N inputs from BNF during the spinup === 29 The biological fixation of N2 from the atmosphere is computed as a function of NPP and plant C:N:P stoichiometry. During the spinup large amounts of organic matter accumulate which is connected with a high immobilisation flux. We thus must ensure that the N inputs are rather high and constant in time. Therefore we read BNF rates in from a file rather than computing them dynamically. 30 31 TODO: It would be good to have an automatized test if the mineral N & P cycles are in equilibrium comparable like it is done with the C pools. 32 21 33 22 == 2. Conceptual modifications to the nitrogen cycle ==23 24 === 2.1 soil mineral N concentration in soil solution ===34 == 3. Conceptual modifications to the nitrogen cycle == 35 36 === 3.1 soil mineral N concentration in soil solution === 25 37 Following Smith et al (2014), I introduced the use of the maximum water holding capacity of soils (max_var_eau) to approximate pore space which to derive the average soil mineral N concentration in solution. The use of the actual water volume can not be recommended as we this would lead to high N concentration in soil water when soil water is very low. As we do not account for the inhibition of replenishment of mineral N in the soil solution around roots when soil water is scarce. 26 38 27 === 2.2 Biological N2 fixation (BNF) ===39 === 3.2 Biological N2 fixation (BNF) === 28 40 We introduce a module which computes BNF as a function of NPP, tissue C:N, and tissue & N:P. This approach is based on Cleveland et al (1999), Thornton et al. (2007), and Goll et al. (2012). 29 41 When using the analytical spinup the BNF must be read in from a file to speed up the spin up. The file should contain the reference BNF rates for the respective climatic conditions. 30 42 Such files are currently missing, but should be generated as soon as the model is ready. 31 43 32 == 3. New input files ==33 === 3.1 USDA soil orders ===44 == 4. New input files == 45 === 4.1 USDA soil orders === 34 46 We use the USDA soil order map of Sun et al. (in revision) with the dominant soil order per pixel. The gap filling of the missing values was done like this 35 47 (see script /home/users/dgoll/ORC_data/USDA_soilorders/try_2_fill/fill_deserts.ksh): … … 43 55 Figure 1: USDA soil orders: Alfisols(1), Andisols(2), Aridisols(3), Entisols(4), Gelisols(5), Histosols(6), Inceptisols(7), Mollisols(8), Oxisols(9), Spodosols(10),Ultisols(11), Vertisols(12) 44 56 45 === 3.2 GliM lithology ===57 === 4.2 GliM lithology === 46 58 We use the GliM lithology map by Hartmann & Moosdorf (2012). We account for subgrid scale heterogeneity by reading the fractional coverage of each of the 16 classes. 47 59 … … 66 78 ! ! 16 - water bodies 67 79 68 === 3.4 Soil shielding (Hartmann et al. (2014) ===80 === 4.4 Soil shielding (Hartmann et al. (2014) === 69 81 The factor corrects the weathering flux where the active zone in the soil is disconnected from the bedrock. 70 82 … … 74 86 75 87 76 == 4.0 unresolved Issues ==88 == 5.0 unresolved Issues == 77 89 78 90 === Reading in N inputs ===
