ORCHIDEE-CN optimization

Optimization

Algorithm : genetic (Monte Carlo)
Observations : FLUXNET data (78 sites), Net Ecosystem Exchange (NEEt) and Latent Heat Flux (Qle)
Optimization : multi-site for each PFT
Number of iterations : 20
Population (number of parameter sets retained during optimization) : 30

Virtal Optimized Parameters

K_LATOSA_MIN = K_LATOSA_MAX * RATIO_KLATOSA
K_ROOT = (K_LATOSA_MAX_PRIOR / K_LATOSA_MAX)**2 * PARAM_KROOT
CN_LEAF_MIN = CN_LEAF_MAX * RATIO_CNLEAF
CN_LEAF_INIT = CN_LEAF_MIN + (CN_LEAF_MAX - CN_LEAF_MIN) / 2.

Outputs

PFT2      PFT5      PFT6      PFT8     

PFT2

PARAMETER	prior	min	max	post
CN_LEAF_MAX__00002	45.5	30	60	59.483
EXT_COEFF_N__00002	0.15	0.1	0.3	0.291
FCN_ROOT__00002	0.86	0.6	1.2	0.679
FCN_WOOD__00002	0.087	0.06	0.12	0.12
K_LATOSA_MAX__00002	17000	12000	22000	16184.656
K_N_min__00001	30	20	40	20.017
K_N_min__00002	30	20	40	22.448
LOW_K_N_min__00001	0.0002	0.00014	0.00025	2.153e-4
LOW_K_N_min__00002	0.0002	0.00014	0.00025	2.204e-4
NUE_OPT__00002	22	15	29	28.264
PARAM_KROOT__00002	1.0E-8	7.0E-9	1.3E-8	9.672e-9
RATIO_CNLEAF__00002	0.35165	0.25	0.5	0.472
RATIO_KLATOSA__00002	0.97059	0.7	1	0.78
SLAINIT__00002	0.026	0.018	0.034	0.022
VMAX_UPTAKE__00001	3	2	4	3.889
VMAX_UPTAKE__00002	3	2	4	3.322
K_LATOSA_MIN__00002	16500.03	8400	22000	12618.188
K_ROOT__00002	1.000e-8	1.405e-8	7.762e-9	1.067e-8
CN_LEAF_MIN__00002	16	7.5	30	28.095
CN_LEAF_INIT__00002	30.75	18.75	45	43.789
Cost function reduction	1			0.867

PFT5

PARAMETER	prior	min	max	post
CN_LEAF_MAX__00005	45.5	30	60	57.729
EXT_COEFF_N__00005	0.15	0.1	0.3	0.15
FCN_ROOT__00005	0.86	0.6	1.2	1.017
FCN_WOOD__00005	0.087	0.06	0.12	0.114
K_LATOSA_MAX__00005	41053	30000	50000	30102.155
K_N_min__00001	30	20	40	24.803
K_N_min__00002	30	20	40	27.945
LOW_K_N_min__00001	0.0002	0.00014	0.00025	2.210e-4
LOW_K_N_min__00002	0.0002	0.00014	0.00025	1.734e-4
NUE_OPT__00005	33	23	43	23.497
PARAM_KROOT__00005	1.6E-9	1.1E-9	2.1E-9	2.074e-9
RATIO_CNLEAF__00005	0.35165	0.25	0.5	0.32
RATIO_KLATOSA__00005	0.21923	0.15	0.3	0.284
SLAINIT__00005	0.03	0.021	0.039	0.037
VMAX_UPTAKE__00001	3	2	4	3.41
VMAX_UPTAKE__00002	3	2	4	2.728
K_LATOSA_MIN__00005	9000.04919	4500	15000	8557.203
K_ROOT__00005	1.600e-9	2.060e-9	1.416e-9	3.858e-9
CN_LEAF_MIN__00005	16	7.5	30	18.449
CN_LEAF_INIT__00005	30.75	18.75	45	38.089
Cost function reduction	1			0.553

PFT6

PARAMETER	prior	min	max	post
CN_LEAF_MAX__00006	45.5	30	60	52.384
EXT_COEFF_N__00006	0.15	0.1	0.3	0.152
FCN_ROOT__00006	0.86	0.6	1.2	0.63
FCN_WOOD__00006	0.087	0.06	0.12	0.072
K_LATOSA_MAX__00006	8000	5500	10500	5618.018
K_N_min__00001	30	20	40	36.358
K_N_min__00002	30	20	40	24.2
LOW_K_N_min__00001	0.0002	0.00014	0.00025	1.977e-4
LOW_K_N_min__00002	0.0002	0.00014	0.00025	1.426e-4
NUE_OPT__00006	33	23	43	29.014
PARAM_KROOT__00006	6.27E-8	4.4E-8	8.2E-8	8.078e-8
RATIO_CNLEAF__00006	0.35165	0.25	0.5	0.452
RATIO_KLATOSA__00006	0.75	0.5	1	0.86
SLAINIT__00006	0.039	0.027	0.051	0.049
VMAX_UPTAKE__00001	3	2	4	2.543
VMAX_UPTAKE__00002	3	2	4	3.448
K_LATOSA_MIN__00006	6000	2750	10500	4834.103
K_ROOT__00006	6.270e-8	9.309e-8	4.760e-8	1.638e-7
CN_LEAF_MIN__00006	16	7.5	30	23.675
CN_LEAF_INIT__00006	30.75	18.75	45	38.03
Cost function reduction	1			0.838

PFT8

PARAMETER	prior	min	max	post
CN_LEAF_MAX__00008	45.5	30	60	50.91
EXT_COEFF_N__00008	0.15	0.1	0.3	0.179
FCN_ROOT__00008	0.86	0.6	1.2	0.786
FCN_WOOD__00008	0.087	0.06	0.12	0.091
K_LATOSA_MAX__00008	30000	20000	40000	20058.271
K_N_min__00001	30	20	40	36.721
K_N_min__00002	30	20	40	35.475
LOW_K_N_min__00001	0.0002	0.00014	0.00025	2.029e-4
LOW_K_N_min__00002	0.0002	0.00014	0.00025	1.965e-4
NUE_OPT__00008	33	23	43	29.236
PARAM_KROOT__00008	2.8E-8	2.0E-8	3.6E-8	3.316e-8
RATIO_CNLEAF__00008	0.35165	0.25	0.5	0.465
RATIO_KLATOSA__00008	0.96	0.7	1	0.788
SLAINIT__00008	0.037	0.026	0.048	0.04
VMAX_UPTAKE__00001	3	2	4	2.098
VMAX_UPTAKE__00002	3	2	4	2.87
K_LATOSA_MIN__00008	28800	14000	40000	15810.709
K_ROOT__00008	2.800e-8	4.500e-8	2.025e-8	7.417e-8
CN_LEAF_MIN__00008	16	7.5	30	23.653
CN_LEAF_INIT__00008	30.75	18.75	45	37.281
Cost function reduction	1			0.853