preparing ECHAM data for INT2LM
Hey, I want to force my
CCLM
simulation with output from the
ECHAM
model
[ https://fesom.de/models/awi-cm/ ]
Has anyone experience concering the preprocessing [ECHAM output —-compatiblity—-> INT2LM input]
So far we have found that:
[T] 3D
cdo -sp2gp echam6.nc output.nc
transforms the spectral temperature to lat/lon grid
[U,V] 3D
cdo -dv2uv echam6.nc output.nc
transforms the spectral divergence/vorticity to u/v-winds on lat/lon grid
[QV,QC,QI] 3D
specific humidity, cloud water, cloud ice are already on lat/lon grid
[W_SNOW, FR_LAND,T_SKIN,T_SNOW,FIS,PS,FR_SEA_ICE] 2D
seem all to exist and are already on lat/lon grid
[W_SO_REL,T_SO] 3D
(multi layer) soil moisture content and soil temperature are difficult.
We havn´t found the temperature, but a soil moisture content (in meter).
Is is possible to run INT2LM with: lmulti_layer_lm=TRUE ; lmulti_layer_in=FALSE
(If yes, is this a good idea?)
Any other advice or suggestion that comes to mind?
Cheers
Rolf
There is a very old version of a converter under https://redc.clm-community.eu/projects/int2lm/wiki/Pre-Processor_Programs
In the tape archive
/hpss/doku/ik0555/DKRZ_LTA_555_ds00001/cordex/MPI-ESM-LR
at
DKRZ
you find examples how the files should look like. Below is a “ncdump -h” listing as an example
T_SO is not needed for
COSMO
_CLM. INT2LM calculates an exponential profile using T_S or T_SKIN (or even T(ke) in the worst case, if the latter are not available).
W_SO_REL: I cannot remember if a conversion factor is needed. Anyway, you can also initialise with an artificial soil moisture by setting
in CONTRL
itype_w_so_rel = 0
and in LMGRID
czvw_so_lm= 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75,
Setting
lmulti_layer_in=FALSE
is probably not a good idea.
netcdf caf2090010100 {
dimensions:
lat = 96 ;
lon = 192 ;
time = UNLIMITED ; // (1 currently)
level = 47 ;
soil1 = 5 ;
nhyi = 48 ;
nhym = 47 ;
level1 = 48 ;
bnds = 2 ;
variables:
float FR_LAND(lat, lon) ;
FR_LAND:long_name = "sea_land_mask" ;
FR_LAND:units = "0,1" ;
FR_LAND:code = 172 ;
FR_LAND:grid_type = "gaussian" ;
float FR_SEA_ICE(time, lat, lon) ;
FR_SEA_ICE:long_name = "sea_ice_area_fraction" ;
FR_SEA_ICE:units = "fraction" ;
FR_SEA_ICE:code = 210 ;
FR_SEA_ICE:grid_type = "gaussian" ;
FR_SEA_ICE:_FillValue = -1.e+20f ;
float PS(time, lat, lon) ;
PS:long_name = "surface_air_pressure" ;
PS:units = "Pa" ;
PS:code = 134 ;
PS:table = 128 ;
PS:grid_type = "gaussian" ;
PS:_FillValue = -1.e+20f ;
float QC(time, level, lat, lon) ;
QC:long_name = "mass_fraction_of_cloud_liquid_water_in_air" ;
QC:units = "kg/kg" ;
QC:code = 153 ;
QC:table = 128 ;
QC:grid_type = "gaussian" ;
QC:_FillValue = -1.e+20f ;
float QI(time, level, lat, lon) ;
QI:long_name = "mass_fraction_of_cloud_ice_in_air" ;
QI:units = "kg/kg" ;
QI:code = 154 ;
QI:table = 128 ;
QI:grid_type = "gaussian" ;
QI:_FillValue = -1.e+20f ;
float QV(time, level, lat, lon) ;
QV:long_name = "specific_humidity" ;
QV:units = "kg/kg" ;
QV:code = 133 ;
QV:table = 128 ;
QV:grid_type = "gaussian" ;
QV:_FillValue = -1.e+20f ;
float T(time, level, lat, lon) ;
T:long_name = "air_temperature" ;
T:units = "K" ;
T:code = 130 ;
T:table = 128 ;
T:grid_type = "gaussian" ;
T:_FillValue = -1.e+20f ;
float T_S(time, lat, lon) ;
T_S:long_name = "soil_surface_temperature" ;
T_S:units = "K" ;
T_S:code = 1 ;
T_S:table = 128 ;
T_S:grid_type = "gaussian" ;
T_S:_FillValue = -1.e+20f ;
float T_SO(time, soil1, lat, lon) ;
T_SO:long_name = "soil_temperature" ;
T_SO:units = "K" ;
T_SO:code = 68 ;
T_SO:table = 180 ;
T_SO:grid_type = "gaussian" ;
T_SO:_FillValue = -1.e+20f ;
float U(time, level, lat, lon) ;
U:long_name = "eastward_wind" ;
U:units = "m/s" ;
U:code = 131 ;
U:table = 128 ;
U:grid_type = "gaussian" ;
U:_FillValue = -1.e+20f ;
float V(time, level, lat, lon) ;
V:long_name = "northward_wind" ;
V:units = "m/s" ;
V:code = 132 ;
V:table = 128 ;
V:grid_type = "gaussian" ;
V:_FillValue = -1.e+20f ;
float W_I(time, lat, lon) ;
W_I:long_name = "canopy_water_amount" ;
W_I:units = "kg/m2" ;
W_I:code = 193 ;
W_I:table = 128 ;
W_I:grid_type = "gaussian" ;
W_I:_FillValue = -1.e+20f ;
float W_SNOW(time, lat, lon) ;
W_SNOW:long_name = "lwe_thickness_of_surface_snow_amount" ;
W_SNOW:units = "m" ;
W_SNOW:code = 141 ;
W_SNOW:table = 128 ;
W_SNOW:grid_type = "gaussian" ;
W_SNOW:_FillValue = -1.e+20f ;
float W_SO_REL(time, soil1, lat, lon) ;
W_SO_REL:long_name = "volume_fraction_of_soil_moisture scaled to max. field capacity" ;
W_SO_REL:units = "m/m" ;
W_SO_REL:code = 2 ;
W_SO_REL:table = 255 ;
W_SO_REL:grid_type = "gaussian" ;
W_SO_REL:_FillValue = -1.e+20f ;
float ak(nhyi) ;
ak:long_name = "hybrid A coefficient at layer interfaces" ;
ak:units = "Pa" ;
float bk(nhyi) ;
bk:long_name = "hybrid B coefficient at layer interfaces" ;
bk:units = "1" ;
double hyam(nhym) ;
hyam:long_name = "hybrid A coefficient at layer midpoints" ;
hyam:units = "Pa" ;
double hybm(nhym) ;
hybm:long_name = "hybrid B coefficient at layer midpoints" ;
hybm:units = "1" ;
float lat(lat) ;
lat:axis = "Y" ;
lat:long_name = "latitude" ;
lat:standard_name = "latitude" ;
lat:units = "degrees_north" ;
float level(level) ;
level:formula = "hyam hybm (mlev=hyam+hybm*aps)" ;
level:formula_terms = "ap: hyam b: hybm ps: aps" ;
level:long_name = "hybrid level at layer midpoints" ;
level:positive = "down" ;
level:standard_name = "hybrid_sigma_pressure" ;
level:units = "level" ;
float level1(level1) ;
float lon(lon) ;
lon:axis = "X" ;
lon:long_name = "longitude" ;
lon:standard_name = "longitude" ;
lon:units = "degrees_east" ;
float soil1(soil1) ;
soil1:axis = "Z" ;
soil1:long_name = "depth of soil layers" ;
soil1:positive = "down" ;
soil1:units = "m" ;
float soil1_bnds(soil1, bnds) ;
double time(time) ;
time:units = "days since 2090-01-01 00:00:00" ;
time:calendar = "proleptic_gregorian" ;
float FIS(lat, lon) ;
FIS:long_name = "surface geopotential" ;
FIS:units = "m2/s2" ;
FIS:code = 129 ;
FIS:grid_type = "gaussian" ;
There is a very old version of a converter under https://redc.clm-community.eu/projects/int2lm/wiki/Pre-Processor_Programs
In the tape archive
/hpss/doku/ik0555/DKRZ_LTA_555_ds00001/cordex/MPI-ESM-LRat DKRZ you find examples how the files should look like. Below is a “ncdump -h” listing as an exampleT_SO is not needed for COSMO _CLM. INT2LM calculates an exponential profile using T_S or T_SKIN (or even T(ke) in the worst case, if the latter are not available).
W_SO_REL: I cannot remember if a conversion factor is needed. Anyway, you can also initialise with an artificial soil moisture by setting
in CONTRL
itype_w_so_rel = 0
and in LMGRID
czvw_so_lm= 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75,Setting
lmulti_layer_in=FALSEis probably not a good idea.netcdf caf2090010100 { dimensions: lat = 96 ; lon = 192 ; time = UNLIMITED ; // (1 currently) level = 47 ; soil1 = 5 ; nhyi = 48 ; nhym = 47 ; level1 = 48 ; bnds = 2 ; variables: float FR_LAND(lat, lon) ; FR_LAND:long_name = "sea_land_mask" ; FR_LAND:units = "0,1" ; FR_LAND:code = 172 ; FR_LAND:grid_type = "gaussian" ; float FR_SEA_ICE(time, lat, lon) ; FR_SEA_ICE:long_name = "sea_ice_area_fraction" ; FR_SEA_ICE:units = "fraction" ; FR_SEA_ICE:code = 210 ; FR_SEA_ICE:grid_type = "gaussian" ; FR_SEA_ICE:_FillValue = -1.e+20f ; float PS(time, lat, lon) ; PS:long_name = "surface_air_pressure" ; PS:units = "Pa" ; PS:code = 134 ; PS:table = 128 ; PS:grid_type = "gaussian" ; PS:_FillValue = -1.e+20f ; float QC(time, level, lat, lon) ; QC:long_name = "mass_fraction_of_cloud_liquid_water_in_air" ; QC:units = "kg/kg" ; QC:code = 153 ; QC:table = 128 ; QC:grid_type = "gaussian" ; QC:_FillValue = -1.e+20f ; float QI(time, level, lat, lon) ; QI:long_name = "mass_fraction_of_cloud_ice_in_air" ; QI:units = "kg/kg" ; QI:code = 154 ; QI:table = 128 ; QI:grid_type = "gaussian" ; QI:_FillValue = -1.e+20f ; float QV(time, level, lat, lon) ; QV:long_name = "specific_humidity" ; QV:units = "kg/kg" ; QV:code = 133 ; QV:table = 128 ; QV:grid_type = "gaussian" ; QV:_FillValue = -1.e+20f ; float T(time, level, lat, lon) ; T:long_name = "air_temperature" ; T:units = "K" ; T:code = 130 ; T:table = 128 ; T:grid_type = "gaussian" ; T:_FillValue = -1.e+20f ; float T_S(time, lat, lon) ; T_S:long_name = "soil_surface_temperature" ; T_S:units = "K" ; T_S:code = 1 ; T_S:table = 128 ; T_S:grid_type = "gaussian" ; T_S:_FillValue = -1.e+20f ; float T_SO(time, soil1, lat, lon) ; T_SO:long_name = "soil_temperature" ; T_SO:units = "K" ; T_SO:code = 68 ; T_SO:table = 180 ; T_SO:grid_type = "gaussian" ; T_SO:_FillValue = -1.e+20f ; float U(time, level, lat, lon) ; U:long_name = "eastward_wind" ; U:units = "m/s" ; U:code = 131 ; U:table = 128 ; U:grid_type = "gaussian" ; U:_FillValue = -1.e+20f ; float V(time, level, lat, lon) ; V:long_name = "northward_wind" ; V:units = "m/s" ; V:code = 132 ; V:table = 128 ; V:grid_type = "gaussian" ; V:_FillValue = -1.e+20f ; float W_I(time, lat, lon) ; W_I:long_name = "canopy_water_amount" ; W_I:units = "kg/m2" ; W_I:code = 193 ; W_I:table = 128 ; W_I:grid_type = "gaussian" ; W_I:_FillValue = -1.e+20f ; float W_SNOW(time, lat, lon) ; W_SNOW:long_name = "lwe_thickness_of_surface_snow_amount" ; W_SNOW:units = "m" ; W_SNOW:code = 141 ; W_SNOW:table = 128 ; W_SNOW:grid_type = "gaussian" ; W_SNOW:_FillValue = -1.e+20f ; float W_SO_REL(time, soil1, lat, lon) ; W_SO_REL:long_name = "volume_fraction_of_soil_moisture scaled to max. field capacity" ; W_SO_REL:units = "m/m" ; W_SO_REL:code = 2 ; W_SO_REL:table = 255 ; W_SO_REL:grid_type = "gaussian" ; W_SO_REL:_FillValue = -1.e+20f ; float ak(nhyi) ; ak:long_name = "hybrid A coefficient at layer interfaces" ; ak:units = "Pa" ; float bk(nhyi) ; bk:long_name = "hybrid B coefficient at layer interfaces" ; bk:units = "1" ; double hyam(nhym) ; hyam:long_name = "hybrid A coefficient at layer midpoints" ; hyam:units = "Pa" ; double hybm(nhym) ; hybm:long_name = "hybrid B coefficient at layer midpoints" ; hybm:units = "1" ; float lat(lat) ; lat:axis = "Y" ; lat:long_name = "latitude" ; lat:standard_name = "latitude" ; lat:units = "degrees_north" ; float level(level) ; level:formula = "hyam hybm (mlev=hyam+hybm*aps)" ; level:formula_terms = "ap: hyam b: hybm ps: aps" ; level:long_name = "hybrid level at layer midpoints" ; level:positive = "down" ; level:standard_name = "hybrid_sigma_pressure" ; level:units = "level" ; float level1(level1) ; float lon(lon) ; lon:axis = "X" ; lon:long_name = "longitude" ; lon:standard_name = "longitude" ; lon:units = "degrees_east" ; float soil1(soil1) ; soil1:axis = "Z" ; soil1:long_name = "depth of soil layers" ; soil1:positive = "down" ; soil1:units = "m" ; float soil1_bnds(soil1, bnds) ; double time(time) ; time:units = "days since 2090-01-01 00:00:00" ; time:calendar = "proleptic_gregorian" ; float FIS(lat, lon) ; FIS:long_name = "surface geopotential" ; FIS:units = "m2/s2" ; FIS:code = 129 ; FIS:grid_type = "gaussian" ;
There is a very old version of a converter under https://redc.clm-community.eu/projects/int2lm/wiki/Pre-Processor_Programs
In the tape archive
/hpss/doku/ik0555/DKRZ_LTA_555_ds00001/cordex/MPI-ESM-LR
at
DKRZ
you find examples how the files should look like. Below is a “ncdump -h” listing as an example
T_SO is not needed for
COSMO
_CLM. INT2LM calculates an exponential profile using T_S or T_SKIN (or even T(ke) in the worst case, if the latter are not available).
W_SO_REL: I cannot remember if a conversion factor is needed. Anyway, you can also initialise with an artificial soil moisture by setting
in CONTRL
itype_w_so_rel = 0
and in LMGRID
czvw_so_lm= 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75,
Setting
lmulti_layer_in=FALSE
is probably not a good idea.
netcdf caf2090010100 {
dimensions:
lat = 96 ;
lon = 192 ;
time = UNLIMITED ; // (1 currently)
level = 47 ;
soil1 = 5 ;
nhyi = 48 ;
nhym = 47 ;
level1 = 48 ;
bnds = 2 ;
variables:
float FR_LAND(lat, lon) ;
FR_LAND:long_name = "sea_land_mask" ;
FR_LAND:units = "0,1" ;
FR_LAND:code = 172 ;
FR_LAND:grid_type = "gaussian" ;
float FR_SEA_ICE(time, lat, lon) ;
FR_SEA_ICE:long_name = "sea_ice_area_fraction" ;
FR_SEA_ICE:units = "fraction" ;
FR_SEA_ICE:code = 210 ;
FR_SEA_ICE:grid_type = "gaussian" ;
FR_SEA_ICE:_FillValue = -1.e+20f ;
float PS(time, lat, lon) ;
PS:long_name = "surface_air_pressure" ;
PS:units = "Pa" ;
PS:code = 134 ;
PS:table = 128 ;
PS:grid_type = "gaussian" ;
PS:_FillValue = -1.e+20f ;
float QC(time, level, lat, lon) ;
QC:long_name = "mass_fraction_of_cloud_liquid_water_in_air" ;
QC:units = "kg/kg" ;
QC:code = 153 ;
QC:table = 128 ;
QC:grid_type = "gaussian" ;
QC:_FillValue = -1.e+20f ;
float QI(time, level, lat, lon) ;
QI:long_name = "mass_fraction_of_cloud_ice_in_air" ;
QI:units = "kg/kg" ;
QI:code = 154 ;
QI:table = 128 ;
QI:grid_type = "gaussian" ;
QI:_FillValue = -1.e+20f ;
float QV(time, level, lat, lon) ;
QV:long_name = "specific_humidity" ;
QV:units = "kg/kg" ;
QV:code = 133 ;
QV:table = 128 ;
QV:grid_type = "gaussian" ;
QV:_FillValue = -1.e+20f ;
float T(time, level, lat, lon) ;
T:long_name = "air_temperature" ;
T:units = "K" ;
T:code = 130 ;
T:table = 128 ;
T:grid_type = "gaussian" ;
T:_FillValue = -1.e+20f ;
float T_S(time, lat, lon) ;
T_S:long_name = "soil_surface_temperature" ;
T_S:units = "K" ;
T_S:code = 1 ;
T_S:table = 128 ;
T_S:grid_type = "gaussian" ;
T_S:_FillValue = -1.e+20f ;
float T_SO(time, soil1, lat, lon) ;
T_SO:long_name = "soil_temperature" ;
T_SO:units = "K" ;
T_SO:code = 68 ;
T_SO:table = 180 ;
T_SO:grid_type = "gaussian" ;
T_SO:_FillValue = -1.e+20f ;
float U(time, level, lat, lon) ;
U:long_name = "eastward_wind" ;
U:units = "m/s" ;
U:code = 131 ;
U:table = 128 ;
U:grid_type = "gaussian" ;
U:_FillValue = -1.e+20f ;
float V(time, level, lat, lon) ;
V:long_name = "northward_wind" ;
V:units = "m/s" ;
V:code = 132 ;
V:table = 128 ;
V:grid_type = "gaussian" ;
V:_FillValue = -1.e+20f ;
float W_I(time, lat, lon) ;
W_I:long_name = "canopy_water_amount" ;
W_I:units = "kg/m2" ;
W_I:code = 193 ;
W_I:table = 128 ;
W_I:grid_type = "gaussian" ;
W_I:_FillValue = -1.e+20f ;
float W_SNOW(time, lat, lon) ;
W_SNOW:long_name = "lwe_thickness_of_surface_snow_amount" ;
W_SNOW:units = "m" ;
W_SNOW:code = 141 ;
W_SNOW:table = 128 ;
W_SNOW:grid_type = "gaussian" ;
W_SNOW:_FillValue = -1.e+20f ;
float W_SO_REL(time, soil1, lat, lon) ;
W_SO_REL:long_name = "volume_fraction_of_soil_moisture scaled to max. field capacity" ;
W_SO_REL:units = "m/m" ;
W_SO_REL:code = 2 ;
W_SO_REL:table = 255 ;
W_SO_REL:grid_type = "gaussian" ;
W_SO_REL:_FillValue = -1.e+20f ;
float ak(nhyi) ;
ak:long_name = "hybrid A coefficient at layer interfaces" ;
ak:units = "Pa" ;
float bk(nhyi) ;
bk:long_name = "hybrid B coefficient at layer interfaces" ;
bk:units = "1" ;
double hyam(nhym) ;
hyam:long_name = "hybrid A coefficient at layer midpoints" ;
hyam:units = "Pa" ;
double hybm(nhym) ;
hybm:long_name = "hybrid B coefficient at layer midpoints" ;
hybm:units = "1" ;
float lat(lat) ;
lat:axis = "Y" ;
lat:long_name = "latitude" ;
lat:standard_name = "latitude" ;
lat:units = "degrees_north" ;
float level(level) ;
level:formula = "hyam hybm (mlev=hyam+hybm*aps)" ;
level:formula_terms = "ap: hyam b: hybm ps: aps" ;
level:long_name = "hybrid level at layer midpoints" ;
level:positive = "down" ;
level:standard_name = "hybrid_sigma_pressure" ;
level:units = "level" ;
float level1(level1) ;
float lon(lon) ;
lon:axis = "X" ;
lon:long_name = "longitude" ;
lon:standard_name = "longitude" ;
lon:units = "degrees_east" ;
float soil1(soil1) ;
soil1:axis = "Z" ;
soil1:long_name = "depth of soil layers" ;
soil1:positive = "down" ;
soil1:units = "m" ;
float soil1_bnds(soil1, bnds) ;
double time(time) ;
time:units = "days since 2090-01-01 00:00:00" ;
time:calendar = "proleptic_gregorian" ;
float FIS(lat, lon) ;
FIS:long_name = "surface geopotential" ;
FIS:units = "m2/s2" ;
FIS:code = 129 ;
FIS:grid_type = "gaussian" ;
Hey, I want to force my CCLM simulation with output from the ECHAM model
[ https://fesom.de/models/awi-cm/ ]
Has anyone experience concering the preprocessing [ECHAM output —-compatiblity—-> INT2LM input]
So far we have found that:
[T] 3D
cdo -sp2gp echam6.nc output.nc
transforms the spectral temperature to lat/lon grid
[U,V] 3D
cdo -dv2uv echam6.nc output.nc
transforms the spectral divergence/vorticity to u/v-winds on lat/lon grid
[QV,QC,QI] 3D
specific humidity, cloud water, cloud ice are already on lat/lon grid
[W_SNOW, FR_LAND,T_SKIN,T_SNOW,FIS,PS,FR_SEA_ICE] 2D
seem all to exist and are already on lat/lon grid
[W_SO_REL,T_SO] 3D
(multi layer) soil moisture content and soil temperature are difficult.
We havn´t found the temperature, but a soil moisture content (in meter).
Is is possible to run INT2LM with: lmulti_layer_lm=TRUE ; lmulti_layer_in=FALSE
(If yes, is this a good idea?)
Any other advice or suggestion that comes to mind?
Cheers
Rolf