Commit 3a75fd36 authored by Woude, Auke van der's avatar Woude, Auke van der
Browse files

different time profiles for different countries

parent 5bb47dd1
......@@ -49,31 +49,11 @@ categories = {
'CO2.uncertainty': 'n',
'CO': -7.52,
'CO.uncertainty': 'l'},
'cars highway': {'name': 'cars highway',
'cars': {'name': 'cars',
'model': 1,
'spatial': 'Road transport',
'temporal': 't_carhw',
'fraction_of_total': 0.47,
'emission_factors': 36200000,
'CO2' : 1,
'CO2.uncertainty': 'n',
'CO': -4.32,
'CO.uncertainty': 'l'},
'cars middle road': {'name': 'cars middle road',
'model': 1,
'spatial': 'Road transport',
'temporal': 't_carmr',
'fraction_of_total': 0.28,
'emission_factors': 36200000,
'CO2' : 1,
'CO2.uncertainty': 'n',
'CO': -4.32,
'CO.uncertainty': 'l'},
'cars urban road': {'name': 'cars urban road',
'model': 1,
'spatial': 'Road transport',
'temporal': 't_carur',
'fraction_of_total': 0.25,
'temporal': 't_road',
'fraction_of_total': 1,
'emission_factors': 36200000,
'CO2' : 1,
'CO2.uncertainty': 'n',
......@@ -82,7 +62,7 @@ categories = {
'heavy duty highway': {'name': 'heavy duty highway',
'model': 1,
'spatial': 'Road transport',
'temporal': 't_hdvhw',
'temporal': 't_road',
'fraction_of_total': 0.56,
'emission_factors': 36650000,
'CO2' : 1,
......@@ -92,7 +72,7 @@ categories = {
'heavy duty middle road': {'name': 'heavy duty middle road',
'model': 1,
'spatial': 'Road transport',
'temporal': 't_hdvmr',
'temporal': 't_road',
'fraction_of_total': 0.24,
'emission_factors': 36650000,
'CO2' : 1,
......@@ -102,7 +82,7 @@ categories = {
'heavy duty urban': {'name': 'heavy duty urban',
'model': 1,
'spatial': 'Road transport',
'temporal': 't_hdvur',
'temporal': 't_road',
'fraction_of_total': 0.2,
'emission_factors': 36650000,
'CO2' : 1,
......
This diff is collapsed.
energy_use_per_country = {
'AUS': {
'Public power': 161.01,
'Public power ratio gas': 0.78,
'Industry': 158.02,
'Other stationary combustion': 120.04,
'Road transport': 150.8,
......@@ -8,6 +9,7 @@ energy_use_per_country = {
},
'BEL': {
'Public power': 254.82,
'Public power ratio gas': 0.72,
'Industry': 203.68,
'Other stationary combustion': 383.16,
'Road transport': 172.455,
......@@ -15,12 +17,14 @@ energy_use_per_country = {
},
'CZE': {
'Public power': 582.9,
'Public power ratio gas': 0.10,
'Industry': 140.13,
'Other stationary combustion': 178.46,
'Road transport': 121.935,
'Shipping': 0.17},
'FRA': {
'Public power': 585.52,
'Public power ratio gas': 0.56,
'Industry': 731.9,
'Other stationary combustion': 1262.1,
'Road transport': 845.07,
......@@ -28,6 +32,7 @@ energy_use_per_country = {
},
'DEU': {
'Public power': 3515.68,
'Public power ratio gas': 0.19,
'Industry': 1516.34,
'Other stationary combustion': 2069.16,
'Road transport': 1066.98,
......@@ -35,6 +40,7 @@ energy_use_per_country = {
},
'LUX': {
'Public power': 3.75,
'Public power ratio gas': 0.99,
'Industry': 15.23,
'Other stationary combustion': 25.22,
'Road transport': 37.045,
......@@ -42,6 +48,7 @@ energy_use_per_country = {
},
'NED': {
'Public power': 868.96,
'Public power ratio gas': 0.47,
'Industry': 427.43,
'Other stationary combustion': 599.52,
'Road transport': 199.74,
......@@ -49,6 +56,7 @@ energy_use_per_country = {
},
'POL': {
'Public power': 1702.42,
'Public power ratio gas': 0.05,
'Industry': 338.92,
'Other stationary combustion': 618.77,
'Road transport': 362.94,
......@@ -56,6 +64,7 @@ energy_use_per_country = {
},
'CHE': {
'Public power': 43.41,
'Public power ratio gas': 0.53,
'Industry': 66.5,
'Other stationary combustion': 194.77,
'Road transport': 100.28,
......@@ -63,6 +72,7 @@ energy_use_per_country = {
},
'GBR': {
'Public power': 1716.77,
'Public power ratio gas': 0.76,
'Industry': 620.58,
'Other stationary combustion': 1485.23,
'Road transport': 787.845,
......
......@@ -207,10 +207,11 @@ class STILTObservationOperator(ObservationOperator):
self.paramdict = rc.read(dacycle.dasystem['paramdict'])
self.pftfile = dacycle.dasystem['file.pft']
with rasterio.Env(logging.getLogger().setLevel(logging.DEBUG)):
with rasterio.Env(logging.getLogger().setLevel(logging.INFO)):
with rasterio.open(self.pftfile) as dataset:
self.pft_shape_orig = dataset.read().shape[-2:]
logging.getLogger().setLevel(logging.DEBUG)
self.lon_start = float(dacycle.dasystem['domain.lon.start'])
self.lon_end = float(dacycle.dasystem['domain.lon.end'])
self.lat_start = float(dacycle.dasystem['domain.lat.start'])
......@@ -353,11 +354,12 @@ class STILTObservationOperator(ObservationOperator):
for i in range(2)])
logging.debug('Shape for paint-by-number: {}'.format(new_shape))
with rasterio.Env(logging.getLogger().setLevel(logging.DEBUG)):
with rasterio.Env(logging.getLogger().setLevel(logging.INFO)):
with rasterio.open(self.pftfile) as dataset:
pftdata = dataset.read(out_shape=new_shape,
resampling=Resampling.mode)
pftdata = pftdata.reshape(pftdata.shape[1:])
logging.getLogger().setLevel(logging.DEBUG)
scaling_factors = np.array(np.array(new_shape) / np.array(self.lu_pref[0].shape), dtype=int)
......@@ -388,7 +390,9 @@ class STILTObservationOperator(ObservationOperator):
for mem, values in enumerate(all_param_values):
param_values = all_param_values[mem]
index_in_state = find_in_state(param_values, 'BIO', str(lutype), return_index=True)
if index_in_state: param_value = param_values[index_in_state]
if index_in_state:
param_value = param_values[index_in_state]
print(param_value)
else: param_value = 1
nee_lut_mem = (nee_lut.sum(axis=0) * mask) * param_value
nee_lut_mem_scaled = average2d(nee_lut_mem, domain_shape)
......
......@@ -17,16 +17,17 @@ do.c14integrated: 0
do.c14targeted: 0
obs.spec.name : CO2
! number of emission categories defined in the emission model
obs.cat.nr : 14
obs.cat.nr : 12
! For Rdam obs
obs.sites.rc : ${datadir}/sites_weights2.rc
! number of parameters
! In the covmatrix and statevector, the ff parameters are first, then the bio parameters!
nffparameters : 24
nbioparameters : 6
nbioparameters : 8
nparameters : ${nffparameters} + ${nbioparameters}
file.pft : /projects/0/ctdas/RINGO/inversions/Data/SiBPFTs.nc
file.pft : ${datadir}/SiBPFTs.nc
file.timeprofs : ${datadir}/CAMS_TEMPO_Tprof_subset.nc
! Settings for the domain:
domain.lon.start : -5.95
......@@ -36,7 +37,7 @@ domain.lat.end : 54.975
domain.lon.num : 260
domain.lat.num : 240
paramdict : ${datadir}/paramdict.rc
paramdict : ${datadir}/paramdict_sib.rc
! set fixed seed for random number generator, or use 0 if you want to use any random seed
random.seed : 4385
!file with prior estimate of scaling factors (statevector) and covariances
......
......@@ -28,7 +28,7 @@
!
! The time for which to start and end the data assimilation experiment in format YYYY-MM-DD HH:MM:SS
time.start : 2016-01-04 00:00:00
time.start : 2016-01-06 00:00:00
time.finish : 2016-01-20 00:00:00
time.fxstart : 2016-01-01 00:00:00
......
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