RRTMColumn
The RRTM radiation column that WRF builds from a model column (SUBROUTINE MM5ATM and the column-amount part of SETCOEF in phys/module_ra_rrtm.F, WRF 4.8): the NLEV model layers plus NBUF buffer layers above the model top, on the index sets `rlay` (RRTM layers, 1 = lowest, NLEV + NBUF members) and `rlev` (RRTM levels, 1 = surface, NLEV + NBUF + 1 members). MM5ATM: (1) the model part is a plain copy in the bottom-up order shared by this grid (PZ(L) = Pw(kte+1-L) undoes the top-down order of the wrapper's 1-D arrays): pz = p_e/100 hPa, tz = T_e, pavel = p/100, tavel = T for the model layers; (2) the buffer part continues the column to p = 0 in steps of deltap = 4 hPa (pz[j] = p_top - deltap (j - NLEV - 1) for the NBUF - 1 full buffer levels, then pz[NLEV+NBUF+1] = 0, so the top buffer layer is thinner) with layer pressures the level means; (3) buffer temperatures follow the MM5 standard atmosphere T_std(p) (the 60-point PPROF/TPROF table, linear in pressure, clamped to its 0.10 hPa end; template standard_atmosphere_temperature) shifted so that it is continuous at the model top, tz = T_std(pz) + (T_e[top] - T_std(p_top)), and tavel the level means; (4) the dry-air column of every layer coldry = (dp/g)(N_A/amm)/(1 + w) in molecules/cm^2 with w the water-vapour volume mixing ratio (qv amdw, floored at 1e-12 kg/kg, in the model layers; the constant 5e-6 above the model top) and amm = (1 - w) amd + w amw the moist molecular weight; (5) the scaled molecular column amounts of SETCOEF, col_x = 1e-20 coldry vmr_x for H2O, CO2 (co2vmr), N2O (n2ovmr) and CH4 (ch4vmr), all uniform above the model top except H2O (the O2 column COLO2 is identically 0, because MM5ATM never fills WKL(7), and RRTM's longwave bands do not read it); (6) the longwave cloud optical depth of the model layers, taucloud = abcw CLWP + abice CIWP + abrn PLWP + absn PIWP with the paths in g/m^2 (CLWP = rho qc dz, the ice path likewise, and the (rho q)^0.75 rain and snow paths), 0 above the model top, and the layer cloud fraction cldfrac = cldfra forced to 1 where taucloud > 0.01 and 0 above the model top; (7) the surface boundary temperature tbound = tsk capped at 339.99 K (the Planck table limit) and the 16-band surface emissivity semiss = emiss. NOT in this component: the ozone column colo3, which MM5ATM takes from the O3DATA annual-mean climatology (31-bin layer-mean average of the summer/winter tables, INIRAD) evaluated on the EXTENDED column PZR -- a pressure-weighted mean of a piecewise-constant profile that will be written as an `integral` over pressure in the next pass (the dumped o3prof is the same climatology on the model column only and is not what colo3 uses; they differ by 33 %); the 1e-32 floors of SETCOEF on zero CO2/N2O/CH4 columns (never active with the WRF trace-gas inputs); and the cross-section species WX (all zero in WRF). NBUF is a metaparameter because RRTMINIT fixes it once from the model top, NLAYERS = kme + nint(p_top/(100 deltap)) - 1, i.e. NBUF = nint(p_top/(100 deltap)); 44 for the reference column with p_top = 177.6 hPa. Inputs are REWRITE-TARGET ops `input_<name>` that the consumer lowers (in the inline tests through a per-test expression_template_imports library extracted from the WRF dumps). Ozone (added 2026-09-06): the annual-mean O3DATA climatology of MM5ATM/O3PROF2 as the layer integral of a piecewise-constant profile, including WRF's one-layer shift (EqWeFiC FORTRAN_BUGS.md B5), and colo3. EqWeFiC, cited here for FORTRAN_BUGS.md, couplings/ and components/atmospheric_dynamics/wrf_arw/, is https://github.com/EarthSciML/EqWeFiC, where these components were developed and are coupled into a WRF column.
Description
The RRTM radiation column that WRF builds from a model column (SUBROUTINE MM5ATM and the column-amount part of SETCOEF in phys/module_ra_rrtm.F, WRF 4.8): the NLEV model layers plus NBUF buffer layers above the model top, on the index sets rlay (RRTM layers, 1 = lowest, NLEV + NBUF members) and rlev (RRTM levels, 1 = surface, NLEV + NBUF + 1 members). MM5ATM: (1) the model part is a plain copy in the bottom-up order shared by this grid (PZ(L) = Pw(kte+1-L) undoes the top-down order of the wrapper’s 1-D arrays): pz = p_e/100 hPa, tz = T_e, pavel = p/100, tavel = T for the model layers; (2) the buffer part continues the column to p = 0 in steps of deltap = 4 hPa (pz[j] = p_top - deltap (j - NLEV - 1) for the NBUF - 1 full buffer levels, then pz[NLEV+NBUF+1] = 0, so the top buffer layer is thinner) with layer pressures the level means; (3) buffer temperatures follow the MM5 standard atmosphere T_std(p) (the 60-point PPROF/TPROF table, linear in pressure, clamped to its 0.10 hPa end; template standard_atmosphere_temperature) shifted so that it is continuous at the model top, tz = T_std(pz) + (T_e[top] - T_std(p_top)), and tavel the level means; (4) the dry-air column of every layer coldry = (dp/g)(N_A/amm)/(1 + w) in molecules/cm^2 with w the water-vapour volume mixing ratio (qv amdw, floored at 1e-12 kg/kg, in the model layers; the constant 5e-6 above the model top) and amm = (1 - w) amd + w amw the moist molecular weight; (5) the scaled molecular column amounts of SETCOEF, col_x = 1e-20 coldry vmr_x for H2O, CO2 (co2vmr), N2O (n2ovmr) and CH4 (ch4vmr), all uniform above the model top except H2O (the O2 column COLO2 is identically 0, because MM5ATM never fills WKL(7), and RRTM’s longwave bands do not read it); (6) the longwave cloud optical depth of the model layers, taucloud = abcw CLWP + abice CIWP + abrn PLWP + absn PIWP with the paths in g/m^2 (CLWP = rho qc dz, the ice path likewise, and the (rho q)^0.75 rain and snow paths), 0 above the model top, and the layer cloud fraction cldfrac = cldfra forced to 1 where taucloud > 0.01 and 0 above the model top; (7) the surface boundary temperature tbound = tsk capped at 339.99 K (the Planck table limit) and the 16-band surface emissivity semiss = emiss. NOT in this component: the ozone column colo3, which MM5ATM takes from the O3DATA annual-mean climatology (31-bin layer-mean average of the summer/winter tables, INIRAD) evaluated on the EXTENDED column PZR – a pressure-weighted mean of a piecewise-constant profile that will be written as an integral over pressure in the next pass (the dumped o3prof is the same climatology on the model column only and is not what colo3 uses; they differ by 33 %); the 1e-32 floors of SETCOEF on zero CO2/N2O/CH4 columns (never active with the WRF trace-gas inputs); and the cross-section species WX (all zero in WRF). NBUF is a metaparameter because RRTMINIT fixes it once from the model top, NLAYERS = kme + nint(p_top/(100 deltap)) - 1, i.e. NBUF = nint(p_top/(100 deltap)); 44 for the reference column with p_top = 177.6 hPa. Inputs are REWRITE-TARGET ops input_<name> that the consumer lowers (in the inline tests through a per-test expression_template_imports library extracted from the WRF dumps). Ozone (added 2026-09-06): the annual-mean O3DATA climatology of MM5ATM/O3PROF2 as the layer integral of a piecewise-constant profile, including WRF’s one-layer shift (EqWeFiC FORTRAN_BUGS.md B5), and colo3. EqWeFiC, cited here for FORTRAN_BUGS.md, couplings/ and components/atmospheric_dynamics/wrf_arw/, is https://github.com/EarthSciML/EqWeFiC
, where these components were developed and are coupled into a WRF column.
Reference
- Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough (1997). Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102(D14), 16663-16682.
- WRF 4.8 phys/module_ra_rrtm.F: MM5ATM (lines 3739-4246: model layers 4094-4103, buffer layers 4128-4147, column amounts 4148-4160 and 4177-4185, clouds 4195-4207), SETCOEF (lines 4386-4391, COLxxx = 1.E-20*WKL), RRTMINIT line 6850 (NLAYERS).
Parameters
| Name | Units | Default | Description |
|---|---|---|---|
p_in | Pa | 0.0 | Coupling target (assembly input path): a shaped parameter that receives the model layer pressure (WRF p3d) from the column geometry (EqWeFiC components/atmospheric_dynamics/wrf_arw/column_geometry.esm, output p) through a document-level coupling.variable_map (param_to_var); a mount-edge template library lowers this component’s input_p rewrite target to it (esm-spec 9.7.10, 10.4). Unused by this component’s own inline tests, which lower input_p to dumped constants instead. |
p_e_in | Pa | 0.0 | Coupling target (assembly input path): a shaped parameter that receives the model interface pressure (WRF p8w, bottom-up) from the column geometry (EqWeFiC components/atmospheric_dynamics/wrf_arw/column_geometry.esm, output p_hyd_w, the hydrostatic interface pressure (p_top at the model top, the surface pressure at the ground), which is what WRF passes here rather than the extrapolated p8w) through a document-level coupling.variable_map (param_to_var); a mount-edge template library lowers this component’s input_p_e rewrite target to it (esm-spec 9.7.10, 10.4). Unused by this component’s own inline tests, which lower input_p_e to dumped constants instead. |
T_in | K | 0.0 | Coupling target (assembly input path): a shaped parameter that receives the model layer temperature (WRF t3d) from the column geometry (EqWeFiC components/atmospheric_dynamics/wrf_arw/column_geometry.esm, output T) through a document-level coupling.variable_map (param_to_var); a mount-edge template library lowers this component’s input_T rewrite target to it (esm-spec 9.7.10, 10.4). Unused by this component’s own inline tests, which lower input_T to dumped constants instead. |
T_e_in | K | 0.0 | Coupling target (assembly input path): a shaped parameter that receives the model interface temperature (WRF t8w) from the column geometry (EqWeFiC components/atmospheric_dynamics/wrf_arw/column_geometry.esm, output t8w) through a document-level coupling.variable_map (param_to_var); a mount-edge template library lowers this component’s input_T_e rewrite target to it (esm-spec 9.7.10, 10.4). Unused by this component’s own inline tests, which lower input_T_e to dumped constants instead. |
dz_m_in | m | 0.0 | Coupling target (assembly input path): a shaped parameter that receives the model layer thickness (WRF dz8w) from the column geometry (EqWeFiC components/atmospheric_dynamics/wrf_arw/column_geometry.esm, output dz8w) through a document-level coupling.variable_map (param_to_var); a mount-edge template library lowers this component’s input_dz_m rewrite target to it (esm-spec 9.7.10, 10.4). Unused by this component’s own inline tests, which lower input_dz_m to dumped constants instead. |
co2vmr | 1 | 0.000379 | CO2 volume mixing ratio (WRF co2vmr from the trace-gas time series; 379 ppmv in the reference run). |
n2ovmr | 1 | 3.19e-07 | N2O volume mixing ratio (WRF n2ovmr). |
ch4vmr | 1 | 1.774e-06 | CH4 volume mixing ratio (WRF ch4vmr). |
tsk | K | 288.0 | Surface skin temperature (WRF tsk). |
emiss | 1 | 0.92 | Broadband surface emissivity (WRF emiss), applied to every RRTM band. |
Observed
| Name | Units | Default | Description |
|---|---|---|---|
p_e | Pa | Model interface pressure (WRF p8w, bottom-up), consumer-supplied through input_p_e. | |
T_e | K | Model interface temperature (WRF t8w), consumer-supplied through input_T_e. | |
p | Pa | Model layer pressure (WRF p3d), consumer-supplied through input_p. | |
T | K | Model layer temperature (WRF t3d), consumer-supplied through input_T. | |
qv | kg/kg | Water-vapour mixing ratio (WRF qv3d), consumer-supplied through input_qv. | |
qc | kg/kg | Cloud-water mixing ratio (WRF qc3d), consumer-supplied through input_qc. | |
qr | kg/kg | Rain mixing ratio (WRF qr3d), consumer-supplied through input_qr. | |
qi | kg/kg | Cloud-ice mixing ratio (WRF qi3d), consumer-supplied through input_qi. | |
qs | kg/kg | Snow mixing ratio (WRF qs3d), consumer-supplied through input_qs. | |
cldfra | 1 | Model cloud fraction (WRF cldfra3d), consumer-supplied through input_cldfra. | |
dz_m | m | Model layer thickness (WRF dz8w), consumer-supplied through input_dz_m. | |
rho | kg/m^3 | Dry-air density p/(r_d T) of the model layers (MM5ATM RO). | |
clwp | g/m^2 | Cloud liquid water path of the model layer, rho qc dz (MM5ATM CLWP). | |
ciwp | g/m^2 | Cloud ice path rho qi dz (MM5ATM CIWP). | |
plwp | g/m^2 | Rain path (rho qr)^0.75 dz (MM5ATM PLWP). | |
piwp | g/m^2 | Snow path (rho qs)^0.75 dz (MM5ATM PIWP). | |
tau_model | 1 | Longwave cloud optical depth of the model layer, abcw clwp + abice ciwp + abrn plwp + absn piwp (MM5ATM TAUCLOUD before the buffer extension). | |
pz | hPa | RRTM level pressure (MM5ATM PZ(0..NLAYERS)): the model interfaces p_e/100, then buffer levels descending by deltap, then 0 at the top of the column. | |
tz | K | RRTM level temperature (MM5ATM TZ): the model interface temperatures, then the shifted standard atmosphere T_std(pz) + (T_e[NLEV+1] - T_std(p_top)). | |
pavel | hPa | RRTM layer pressure (MM5ATM PAVEL): the model layer pressures p/100, then the buffer level means. | |
tavel | K | RRTM layer temperature (MM5ATM TAVEL): the model layer temperatures, then the buffer level means. | |
w_h2o | 1 | Water-vapour volume mixing ratio relative to dry air (MM5ATM WKL(1,L) before the COLDRY scaling): max(qv, qv_min) amdw in the model layers, h2ovmr_top above. | |
amm | g/mol | Molecular weight of the moist air of the layer, (1 - w_h2o) amd + w_h2o amw (MM5ATM amm). | |
coldry | 1/cm^2 | Dry-air molecular column of the layer, (dp/g)(N_A/amm)/(1 + w_h2o) in molecules/cm^2 (MM5ATM COLDRY = (PZ(L-1)-PZ(L))1.E3avgdro/(gravitamm(1+WKL(1,L))). | |
colh2o | 1/cm^2 | Scaled water-vapour column 1e-20 coldry w_h2o (SETCOEF COLH2O). | |
colco2 | 1/cm^2 | Scaled CO2 column 1e-20 coldry co2vmr (SETCOEF COLCO2). | |
coln2o | 1/cm^2 | Scaled N2O column 1e-20 coldry n2ovmr (SETCOEF COLN2O; MM5ATM multiplies by amdn and divides it out again). | |
colch4 | 1/cm^2 | Scaled CH4 column 1e-20 coldry ch4vmr (SETCOEF COLCH4). | |
taucloud | 1 | Longwave cloud optical depth of the RRTM layer: tau_model in the model layers, 0 above the model top (MM5ATM TAUCLOUD). | |
cldfrac | 1 | Cloud fraction of the RRTM layer: the model cloud fraction, forced to 1 where taucloud > tau_overcast, 0 above the model top (MM5ATM CLDFRAC). | |
tbound | K | Surface boundary temperature for the Planck emission, tsk capped at tbound_reset when it reaches tbound_limit (MM5ATM TBOUND). WRF tests TBOUND .GT. 340., so a skin temperature of exactly 340 K passes uncapped and RTRN’s linear interpolation reads TOTPLNK one node past the end of the table (with a zero weight); the test here is >= so that 340 K is capped too and the lookup stays inside the 160..340 K table. | |
semiss | 1 | Surface emissivity of each of the 16 RRTM bands, all equal to emiss (MM5ATM SEMISS(N) = EMISS). | |
pp_sum | hPa | Pressure nodes of the summer ozone climatology (O3DATA PPSUM), also the nodes of the annual mean (PPANN = PPSUM). | |
o3_sum | kg/kg | Summer ozone mass mixing ratio at pp_sum (O3DATA O3SUM). | |
pp_win | hPa | Pressure nodes of the winter ozone climatology (O3DATA PPWIN). | |
o3_win | kg/kg | Winter ozone mass mixing ratio at pp_win (O3DATA O3WIN). | |
o3_ann | kg/kg | Annual-mean ozone climatology at pp_sum (O3DATA O3ANN): the mean of the summer value and the winter profile interpolated linearly in pressure onto the summer node (for node 1 the plain mean of the two first values), exactly as O3DATA blends the two seasons. | |
pp_half | hPa | Bin edges of the piecewise-constant annual climatology (O3DATA PPWRKH): 1100 hPa, the midpoints between successive nodes, and 0 hPa. | |
o3_clim_integral | hPa*kg/kg | The pressure integral of the annual ozone climatology over the interval MM5ATM passes to O3DATA for layer L (see o3_clim): the sum over the 31 climatology bins of climatology_layer_mean. The top layer’s interval is empty, so its integral is 0 (o3_clim takes the constant o3_top there). | |
o3_clim | kg/kg | Ozone mass mixing ratio of the RRTM layer as MM5ATM assigns it (O3PROF2): the pressure-weighted mean of the piecewise-constant annual climatology, (1/dp) integral of o3_ann(p) dp, over the pressure interval MM5ATM passes to O3DATA. That interval is NOT the layer’s own: MM5ATM reverses PZ(1..NLAYERS) without PZ(0) into the array O3DATA reads, so layer L receives the mean over [PZ(L+1), PZ(L)] = [pz[L+2], pz[L+1]] – the layer above it – and the top layer receives the constant 6.135e-6 (EqWeFiC FORTRAN_BUGS.md B5). The integral is evaluated exactly as the sum over climatology bins of the overlap of the interval with each bin times the bin value (O3DATA’s PB/PT bookkeeping). | |
colo3 | 1/cm^2 | Scaled ozone column 1e-20 coldry o3_clim amdo (SETCOEF COLO3 from MM5ATM WKL(3,L) = O3PROF2(L) amdo COLDRY). | |
nbuf_wrf | 1 | The buffer-layer count WRF would use for this column, nint(p_top / deltap) with p_top = p_e[NLEV+1] in hPa (RRTMINIT: NLAYERS = kme + nint(p_top*0.01/deltap) - 1, so NLAYERS - kte buffer layers). | |
nbuf_mismatch | 1 | nbuf_wrf - NBUF: 0 when the NBUF metaparameter this component was loaded with is the one WRF derives from the column’s p_top, so that the buffer levels pz = p_top - deltap k stay in (0, p_top). Nonzero means the column is mis-sized for its model top (see the NBUF metaparameter); every inline test asserts that it is 0. |
Observed expressions
$$ p_{e} = \mathrm{input_p_e}\left(\right) $$Model interface pressure (WRF p8w, bottom-up), consumer-supplied through input_p_e.
Model interface temperature (WRF t8w), consumer-supplied through input_T_e.
Model layer pressure (WRF p3d), consumer-supplied through input_p.
Model layer temperature (WRF t3d), consumer-supplied through input_T.
Water-vapour mixing ratio (WRF qv3d), consumer-supplied through input_qv.
Cloud-water mixing ratio (WRF qc3d), consumer-supplied through input_qc.
Rain mixing ratio (WRF qr3d), consumer-supplied through input_qr.
Cloud-ice mixing ratio (WRF qi3d), consumer-supplied through input_qi.
Snow mixing ratio (WRF qs3d), consumer-supplied through input_qs.
Model cloud fraction (WRF cldfra3d), consumer-supplied through input_cldfra.
Model layer thickness (WRF dz8w), consumer-supplied through input_dz_m.
Dry-air density p/(r_d T) of the model layers (MM5ATM RO).
$$ clwp = \mathrm{condensate_path}\left(rho=rho, q=qc, dz=dz_{m}, g_{per\,kg}=par.g_{per\,kg}\right) $$Cloud liquid water path of the model layer, rho qc dz (MM5ATM CLWP).
$$ ciwp = \mathrm{condensate_path}\left(rho=rho, q=qi, dz=dz_{m}, g_{per\,kg}=par.g_{per\,kg}\right) $$Cloud ice path rho qi dz (MM5ATM CIWP).
$$ plwp = \mathrm{precipitation_path}\left(rho=rho, q=qr, dz=dz_{m}, rho_{ref}=par.rho_{ref}, g_{per\,kg}=par.g_{per\,kg}\right) $$Rain path (rho qr)^0.75 dz (MM5ATM PLWP).
$$ piwp = \mathrm{precipitation_path}\left(rho=rho, q=qs, dz=dz_{m}, rho_{ref}=par.rho_{ref}, g_{per\,kg}=par.g_{per\,kg}\right) $$Snow path (rho qs)^0.75 dz (MM5ATM PIWP).
$$ tau_{model} = par.abcw \cdot clwp + par.abice \cdot ciwp + par.abrn \cdot plwp + par.absn \cdot piwp $$Longwave cloud optical depth of the model layer, abcw clwp + abice ciwp + abrn plwp + absn piwp (MM5ATM TAUCLOUD before the buffer extension).
$$ pz = \mathrm{aggregate}\left(p_{e}\right) $$RRTM level pressure (MM5ATM PZ(0..NLAYERS)): the model interfaces p_e/100, then buffer levels descending by deltap, then 0 at the top of the column.
$$ tz = \mathrm{aggregate}\left(T_{e}, pz\right) $$RRTM level temperature (MM5ATM TZ): the model interface temperatures, then the shifted standard atmosphere T_std(pz) + (T_e[NLEV+1] - T_std(p_top)).
$$ pavel = \mathrm{aggregate}\left(p, pz\right) $$RRTM layer pressure (MM5ATM PAVEL): the model layer pressures p/100, then the buffer level means.
$$ tavel = \mathrm{aggregate}\left(T, tz\right) $$RRTM layer temperature (MM5ATM TAVEL): the model layer temperatures, then the buffer level means.
$$ w_{h2o} = \mathrm{aggregate}\left(qv\right) $$Water-vapour volume mixing ratio relative to dry air (MM5ATM WKL(1,L) before the COLDRY scaling): max(qv, qv_min) amdw in the model layers, h2ovmr_top above.
$$ amm = \left(1.0 - w_{h2o}\right) \cdot par.amd + w_{h2o} \cdot par.amw $$Molecular weight of the moist air of the layer, (1 - w_h2o) amd + w_h2o amw (MM5ATM amm).
$$ coldry = \mathrm{aggregate}\left(pz, amm, w_{h2o}\right) $$Dry-air molecular column of the layer, (dp/g)(N_A/amm)/(1 + w_h2o) in molecules/cm^2 (MM5ATM COLDRY = (PZ(L-1)-PZ(L))1.E3avgdro/(gravitamm(1+WKL(1,L))).
$$ colh2o = par.col_{scale} \cdot coldry \cdot w_{h2o} $$Scaled water-vapour column 1e-20 coldry w_h2o (SETCOEF COLH2O).
$$ colco2 = par.col_{scale} \cdot coldry \cdot co2vmr $$Scaled CO2 column 1e-20 coldry co2vmr (SETCOEF COLCO2).
$$ coln2o = par.col_{scale} \cdot coldry \cdot n2ovmr $$Scaled N2O column 1e-20 coldry n2ovmr (SETCOEF COLN2O; MM5ATM multiplies by amdn and divides it out again).
$$ colch4 = par.col_{scale} \cdot coldry \cdot ch4vmr $$Scaled CH4 column 1e-20 coldry ch4vmr (SETCOEF COLCH4).
$$ taucloud = \mathrm{aggregate}\left(tau_{model}\right) $$Longwave cloud optical depth of the RRTM layer: tau_model in the model layers, 0 above the model top (MM5ATM TAUCLOUD).
$$ cldfrac = \mathrm{aggregate}\left(cldfra, taucloud\right) $$Cloud fraction of the RRTM layer: the model cloud fraction, forced to 1 where taucloud > tau_overcast, 0 above the model top (MM5ATM CLDFRAC).
$$ tbound = \mathrm{ifelse}\left(\mathrm{>=}\left(tsk, par.tbound_{limit}\right), par.tbound_{reset}, tsk\right) $$Surface boundary temperature for the Planck emission, tsk capped at tbound_reset when it reaches tbound_limit (MM5ATM TBOUND). WRF tests TBOUND .GT. 340., so a skin temperature of exactly 340 K passes uncapped and RTRN’s linear interpolation reads TOTPLNK one node past the end of the table (with a zero weight); the test here is >= so that 340 K is capped too and the lookup stays inside the 160..340 K table.
$$ semiss = \mathrm{aggregate}\left(\right) $$Surface emissivity of each of the 16 RRTM bands, all equal to emiss (MM5ATM SEMISS(N) = EMISS).
$$ pp_{sum} = par.unit_{hpa} \cdot \mathrm{aggregate}\left(\right) $$Pressure nodes of the summer ozone climatology (O3DATA PPSUM), also the nodes of the annual mean (PPANN = PPSUM).
$$ o3_{sum} = \mathrm{aggregate}\left(\right) $$Summer ozone mass mixing ratio at pp_sum (O3DATA O3SUM).
$$ pp_{win} = par.unit_{hpa} \cdot \mathrm{aggregate}\left(\right) $$Pressure nodes of the winter ozone climatology (O3DATA PPWIN).
$$ o3_{win} = \mathrm{aggregate}\left(\right) $$Winter ozone mass mixing ratio at pp_win (O3DATA O3WIN).
$$ o3_{ann} = \mathrm{aggregate}\left(\right) $$Annual-mean ozone climatology at pp_sum (O3DATA O3ANN): the mean of the summer value and the winter profile interpolated linearly in pressure onto the summer node (for node 1 the plain mean of the two first values), exactly as O3DATA blends the two seasons.
$$ pp_{half} = \mathrm{aggregate}\left(\right) $$Bin edges of the piecewise-constant annual climatology (O3DATA PPWRKH): 1100 hPa, the midpoints between successive nodes, and 0 hPa.
$$ o3_{clim\,integral} = \mathrm{aggregate}\left(\right) $$The pressure integral of the annual ozone climatology over the interval MM5ATM passes to O3DATA for layer L (see o3_clim): the sum over the 31 climatology bins of climatology_layer_mean. The top layer’s interval is empty, so its integral is 0 (o3_clim takes the constant o3_top there).
$$ o3_{clim} = \mathrm{aggregate}\left(\right) $$Ozone mass mixing ratio of the RRTM layer as MM5ATM assigns it (O3PROF2): the pressure-weighted mean of the piecewise-constant annual climatology, (1/dp) integral of o3_ann(p) dp, over the pressure interval MM5ATM passes to O3DATA. That interval is NOT the layer’s own: MM5ATM reverses PZ(1..NLAYERS) without PZ(0) into the array O3DATA reads, so layer L receives the mean over [PZ(L+1), PZ(L)] = [pz[L+2], pz[L+1]] – the layer above it – and the top layer receives the constant 6.135e-6 (EqWeFiC FORTRAN_BUGS.md B5). The integral is evaluated exactly as the sum over climatology bins of the overlap of the interval with each bin times the bin value (O3DATA’s PB/PT bookkeeping).
$$ colo3 = par.col_{scale} \cdot coldry \cdot o3_{clim} \cdot par.amdo $$Scaled ozone column 1e-20 coldry o3_clim amdo (SETCOEF COLO3 from MM5ATM WKL(3,L) = O3PROF2(L) amdo COLDRY).
$$ nbuf_{wrf} = \mathrm{floor}\left(\frac{\mathrm{index}\left(p_{e}, NLEV + 1\right)}{par.pa_{per\,hpa} \cdot par.deltap} + 0.5\right) $$The buffer-layer count WRF would use for this column, nint(p_top / deltap) with p_top = p_e[NLEV+1] in hPa (RRTMINIT: NLAYERS = kme + nint(p_top*0.01/deltap) - 1, so NLAYERS - kte buffer layers).
$$ nbuf_{mismatch} = nbuf_{wrf} - NBUF $$nbuf_wrf - NBUF: 0 when the NBUF metaparameter this component was loaded with is the one WRF derives from the column’s p_top, so that the buffer levels pz = p_top - deltap k stay in (0, p_top). Nonzero means the column is mis-sized for its model top (see the NBUF metaparameter); every inline test asserts that it is 0.
Expression Templates
condensate_path
Parameters: rho, q, dz, g_per_kg
precipitation_path
Parameters: rho, q, dz, rho_ref, g_per_kg
model_or_buffer_layer
Parameters: L, model_value, buffer_value
model_layer_index
Parameters: L
model_level_index
Parameters: j
level_mean
Parameters: x, L
standard_atmosphere_temperature
Parameters: p
climatology_layer_mean
Parameters: p_bottom, p_top, j
Raw .esm
Raw .esm JSON (this component)
{
"expression_template_imports": [
{
"ref": "${ESD_ROOT}/grids/column_nonuniform_1d/grid.esm",
"bindings": {
"NLEV": "NLEV"
}
},
{
"ref": "../../../lib/wrf_thermo.esm"
},
{
"ref": "./rrtm_ozone_climatology.esm"
}
],
"subsystems": {
"wrf": {
"ref": "../../../lib/wrf_constants.esm"
},
"par": {
"ref": "./rrtm_parameters.esm"
}
},
"expression_templates": {
"condensate_path": {
"params": [
"rho",
"q",
"dz",
"g_per_kg"
],
"description": "Condensate path of a layer in g/m^2, rho q dz (MM5ATM CLWP, CIWP).",
"body": {
"op": "*",
"args": [
"rho",
"q",
"dz",
"g_per_kg"
]
}
},
"precipitation_path": {
"params": [
"rho",
"q",
"dz",
"rho_ref",
"g_per_kg"
],
"description": "Precipitation path of a layer in g/m^2 with MM5ATM's 0.75 power of the water content, ((rho q)/rho_ref)^0.75 rho_ref dz (PLWP, PIWP; rho_ref = 1 kg/m^3 makes the Fortran's implicit SI power law dimensionally explicit).",
"body": {
"op": "*",
"args": [
{
"op": "^",
"args": [
{
"op": "/",
"args": [
{
"op": "*",
"args": [
"rho",
"q"
]
},
"rho_ref"
]
},
0.75
]
},
"rho_ref",
"dz",
"g_per_kg"
]
}
},
"model_or_buffer_layer": {
"params": [
"L",
"model_value",
"buffer_value"
],
"description": "Case split of an RRTM-layer quantity between the model layers (L <= NLEV) and the buffer layers above the model top.",
"body": {
"op": "ifelse",
"args": [
{
"op": "<=",
"args": [
"L",
"NLEV"
]
},
"model_value",
"buffer_value"
]
}
},
"model_layer_index": {
"params": [
"L"
],
"description": "The model-layer index of RRTM layer L, clamped to NLEV so that a model-column gather stays in bounds when it is evaluated on a buffer layer (where the case split discards it).",
"body": {
"op": "min",
"args": [
"L",
"NLEV"
]
}
},
"model_level_index": {
"params": [
"j"
],
"description": "The model-interface index of RRTM level j, clamped to NLEV + 1 for the same reason as model_layer_index.",
"body": {
"op": "min",
"args": [
"j",
{
"op": "+",
"args": [
"NLEV",
1
]
}
]
}
},
"level_mean": {
"params": [
"x",
"L"
],
"description": "Mean of a level quantity over the two levels bounding layer L, (x[L] + x[L+1])/2 (MM5ATM PAVEL/TAVEL of the buffer layers).",
"body": {
"op": "*",
"args": [
0.5,
{
"op": "+",
"args": [
{
"op": "index",
"args": [
"x",
"L"
]
},
{
"op": "index",
"args": [
"x",
{
"op": "+",
"args": [
"L",
1
]
}
]
}
]
}
]
}
},
"standard_atmosphere_temperature": {
"params": [
"p"
],
"description": "MM5ATM's standard-atmosphere temperature T_std(p): linear interpolation in pressure of the 60-point TPROF (K) vs PPROF (hPa) table (1000 hPa .. 0.10 hPa, stored with the pressure axis ascending), clamped beyond the ends -- the Fortran clamps at 0.10 hPa, the only end the buffer layers reach (above 1000 hPa it would extrapolate linearly, impossible above the model top). Spelled as the esm-spec 9.5.3 lowered form interp.linear(data, axis, p) rather than as a `function_tables` entry with `table_lookup`, because the Rust array interpreter of EarthSciAST (inline-test path) does not lower table_lookup (unevaluable_operator).",
"body": {
"op": "fn",
"name": "interp.linear",
"args": [
{
"op": "const",
"args": [],
"value": [
237.53,
239.87,
242.77,
245.46,
248.23,
251.07,
254.02,
256.49,
258.78,
260.85,
262.76,
264.45,
265.34,
265.42,
264.67,
263.38,
261.88,
259.84,
257.02,
254.04,
251.08,
248.13,
245.21,
242.3,
239.5,
236.82,
234.22,
231.88,
229.73,
227.78,
226.04,
224.39,
222.84,
221.31,
219.92,
218.89,
218.11,
217.42,
216.73,
215.96,
214.95,
213.81,
212.71,
211.73,
211.45,
211.63,
213.48,
215.21,
217.31,
220.52,
224.02,
228.78,
234.91,
241.97,
249.28,
256.71,
264.14,
270.73,
276.16,
279.94
]
},
{
"op": "const",
"args": [],
"value": [
0.1,
0.12,
0.14,
0.16,
0.19,
0.22,
0.26,
0.3,
0.35,
0.41,
0.48,
0.56,
0.65,
0.76,
0.89,
1.04,
1.22,
1.42,
1.66,
1.94,
2.27,
2.65,
3.1,
3.63,
4.24,
4.95,
5.79,
6.77,
7.91,
9.25,
10.81,
12.64,
14.77,
17.27,
20.19,
23.6,
27.59,
32.25,
37.69,
44.06,
51.51,
60.21,
70.38,
82.27,
96.17,
112.42,
131.41,
153.62,
179.57,
209.91,
245.38,
286.83,
335.29,
391.94,
458.16,
535.57,
626.05,
731.82,
855.47,
1000.0
]
},
"p"
]
}
},
"climatology_layer_mean": {
"params": [
"p_bottom",
"p_top",
"j"
],
"description": "One climatology bin's share of the pressure integral of the piecewise-constant annual ozone climatology over the interval [p_top, p_bottom] (p_bottom > p_top): the overlap length max(0, min(p_bottom, pp_half[j]) - max(p_top, pp_half[j+1])) of the interval with bin j = [pp_half[j+1], pp_half[j]], times the bin value o3_ann[j] (O3DATA loop 25: PB2 - PB1 - PT2 + PT1 is that overlap). Summed over the 31 bins and divided by p_bottom - p_top it is the exact pressure-weighted mean (o3_clim_integral, o3_clim).",
"body": {
"op": "*",
"args": [
{
"op": "max",
"args": [
{
"op": "*",
"args": [
0.0,
"par.unit_hpa"
]
},
{
"op": "-",
"args": [
{
"op": "min",
"args": [
"p_bottom",
{
"op": "index",
"args": [
"pp_half",
"j"
]
}
]
},
{
"op": "max",
"args": [
"p_top",
{
"op": "index",
"args": [
"pp_half",
{
"op": "+",
"args": [
"j",
1
]
}
]
}
]
}
]
}
]
},
{
"op": "index",
"args": [
"o3_ann",
"j"
]
}
]
}
}
},
"variables": {
"p_in": {
"type": "parameter",
"shape": [
"lev"
],
"units": "Pa",
"default": 0.0,
"description": "Coupling target (assembly input path): a shaped parameter that receives the model layer pressure (WRF p3d) from the column geometry (EqWeFiC components/atmospheric_dynamics/wrf_arw/column_geometry.esm, output `p`) through a document-level `coupling.variable_map` (param_to_var); a mount-edge template library lowers this component's `input_p` rewrite target to it (esm-spec 9.7.10, 10.4). Unused by this component's own inline tests, which lower `input_p` to dumped constants instead."
},
"p_e_in": {
"type": "parameter",
"shape": [
"lev_nodes"
],
"units": "Pa",
"default": 0.0,
"description": "Coupling target (assembly input path): a shaped parameter that receives the model interface pressure (WRF p8w, bottom-up) from the column geometry (EqWeFiC components/atmospheric_dynamics/wrf_arw/column_geometry.esm, output `p_hyd_w`, the hydrostatic interface pressure (p_top at the model top, the surface pressure at the ground), which is what WRF passes here rather than the extrapolated p8w) through a document-level `coupling.variable_map` (param_to_var); a mount-edge template library lowers this component's `input_p_e` rewrite target to it (esm-spec 9.7.10, 10.4). Unused by this component's own inline tests, which lower `input_p_e` to dumped constants instead."
},
"T_in": {
"type": "parameter",
"shape": [
"lev"
],
"units": "K",
"default": 0.0,
"description": "Coupling target (assembly input path): a shaped parameter that receives the model layer temperature (WRF t3d) from the column geometry (EqWeFiC components/atmospheric_dynamics/wrf_arw/column_geometry.esm, output `T`) through a document-level `coupling.variable_map` (param_to_var); a mount-edge template library lowers this component's `input_T` rewrite target to it (esm-spec 9.7.10, 10.4). Unused by this component's own inline tests, which lower `input_T` to dumped constants instead."
},
"T_e_in": {
"type": "parameter",
"shape": [
"lev_nodes"
],
"units": "K",
"default": 0.0,
"description": "Coupling target (assembly input path): a shaped parameter that receives the model interface temperature (WRF t8w) from the column geometry (EqWeFiC components/atmospheric_dynamics/wrf_arw/column_geometry.esm, output `t8w`) through a document-level `coupling.variable_map` (param_to_var); a mount-edge template library lowers this component's `input_T_e` rewrite target to it (esm-spec 9.7.10, 10.4). Unused by this component's own inline tests, which lower `input_T_e` to dumped constants instead."
},
"dz_m_in": {
"type": "parameter",
"shape": [
"lev"
],
"units": "m",
"default": 0.0,
"description": "Coupling target (assembly input path): a shaped parameter that receives the model layer thickness (WRF dz8w) from the column geometry (EqWeFiC components/atmospheric_dynamics/wrf_arw/column_geometry.esm, output `dz8w`) through a document-level `coupling.variable_map` (param_to_var); a mount-edge template library lowers this component's `input_dz_m` rewrite target to it (esm-spec 9.7.10, 10.4). Unused by this component's own inline tests, which lower `input_dz_m` to dumped constants instead."
},
"co2vmr": {
"type": "parameter",
"units": "1",
"default": 0.000379,
"description": "CO2 volume mixing ratio (WRF co2vmr from the trace-gas time series; 379 ppmv in the reference run)."
},
"n2ovmr": {
"type": "parameter",
"units": "1",
"default": 3.19e-07,
"description": "N2O volume mixing ratio (WRF n2ovmr)."
},
"ch4vmr": {
"type": "parameter",
"units": "1",
"default": 1.774e-06,
"description": "CH4 volume mixing ratio (WRF ch4vmr)."
},
"tsk": {
"type": "parameter",
"units": "K",
"default": 288.0,
"description": "Surface skin temperature (WRF tsk)."
},
"emiss": {
"type": "parameter",
"units": "1",
"default": 0.92,
"description": "Broadband surface emissivity (WRF emiss), applied to every RRTM band."
},
"p_e": {
"type": "unknown",
"units": "Pa",
"shape": [
"lev_nodes"
],
"description": "Model interface pressure (WRF p8w, bottom-up), consumer-supplied through `input_p_e`."
},
"T_e": {
"type": "unknown",
"units": "K",
"shape": [
"lev_nodes"
],
"description": "Model interface temperature (WRF t8w), consumer-supplied through `input_T_e`."
},
"p": {
"type": "unknown",
"units": "Pa",
"shape": [
"lev"
],
"description": "Model layer pressure (WRF p3d), consumer-supplied through `input_p`."
},
"T": {
"type": "unknown",
"units": "K",
"shape": [
"lev"
],
"description": "Model layer temperature (WRF t3d), consumer-supplied through `input_T`."
},
"qv": {
"type": "unknown",
"units": "kg/kg",
"shape": [
"lev"
],
"description": "Water-vapour mixing ratio (WRF qv3d), consumer-supplied through `input_qv`."
},
"qc": {
"type": "unknown",
"units": "kg/kg",
"shape": [
"lev"
],
"description": "Cloud-water mixing ratio (WRF qc3d), consumer-supplied through `input_qc`."
},
"qr": {
"type": "unknown",
"units": "kg/kg",
"shape": [
"lev"
],
"description": "Rain mixing ratio (WRF qr3d), consumer-supplied through `input_qr`."
},
"qi": {
"type": "unknown",
"units": "kg/kg",
"shape": [
"lev"
],
"description": "Cloud-ice mixing ratio (WRF qi3d), consumer-supplied through `input_qi`."
},
"qs": {
"type": "unknown",
"units": "kg/kg",
"shape": [
"lev"
],
"description": "Snow mixing ratio (WRF qs3d), consumer-supplied through `input_qs`."
},
"cldfra": {
"type": "unknown",
"units": "1",
"shape": [
"lev"
],
"description": "Model cloud fraction (WRF cldfra3d), consumer-supplied through `input_cldfra`."
},
"dz_m": {
"type": "unknown",
"units": "m",
"shape": [
"lev"
],
"description": "Model layer thickness (WRF dz8w), consumer-supplied through `input_dz_m`."
},
"rho": {
"type": "unknown",
"units": "kg/m^3",
"shape": [
"lev"
],
"description": "Dry-air density p/(r_d T) of the model layers (MM5ATM RO)."
},
"clwp": {
"type": "unknown",
"units": "g/m^2",
"shape": [
"lev"
],
"description": "Cloud liquid water path of the model layer, rho qc dz (MM5ATM CLWP)."
},
"ciwp": {
"type": "unknown",
"units": "g/m^2",
"shape": [
"lev"
],
"description": "Cloud ice path rho qi dz (MM5ATM CIWP)."
},
"plwp": {
"type": "unknown",
"units": "g/m^2",
"shape": [
"lev"
],
"description": "Rain path (rho qr)^0.75 dz (MM5ATM PLWP)."
},
"piwp": {
"type": "unknown",
"units": "g/m^2",
"shape": [
"lev"
],
"description": "Snow path (rho qs)^0.75 dz (MM5ATM PIWP)."
},
"tau_model": {
"type": "unknown",
"units": "1",
"shape": [
"lev"
],
"description": "Longwave cloud optical depth of the model layer, abcw clwp + abice ciwp + abrn plwp + absn piwp (MM5ATM TAUCLOUD before the buffer extension)."
},
"pz": {
"type": "unknown",
"units": "hPa",
"shape": [
"rlev"
],
"description": "RRTM level pressure (MM5ATM PZ(0..NLAYERS)): the model interfaces p_e/100, then buffer levels descending by deltap, then 0 at the top of the column."
},
"tz": {
"type": "unknown",
"units": "K",
"shape": [
"rlev"
],
"description": "RRTM level temperature (MM5ATM TZ): the model interface temperatures, then the shifted standard atmosphere T_std(pz) + (T_e[NLEV+1] - T_std(p_top))."
},
"pavel": {
"type": "unknown",
"units": "hPa",
"shape": [
"rlay"
],
"description": "RRTM layer pressure (MM5ATM PAVEL): the model layer pressures p/100, then the buffer level means."
},
"tavel": {
"type": "unknown",
"units": "K",
"shape": [
"rlay"
],
"description": "RRTM layer temperature (MM5ATM TAVEL): the model layer temperatures, then the buffer level means."
},
"w_h2o": {
"type": "unknown",
"units": "1",
"shape": [
"rlay"
],
"description": "Water-vapour volume mixing ratio relative to dry air (MM5ATM WKL(1,L) before the COLDRY scaling): max(qv, qv_min) amdw in the model layers, h2ovmr_top above."
},
"amm": {
"type": "unknown",
"units": "g/mol",
"shape": [
"rlay"
],
"description": "Molecular weight of the moist air of the layer, (1 - w_h2o) amd + w_h2o amw (MM5ATM amm)."
},
"coldry": {
"type": "unknown",
"units": "1/cm^2",
"shape": [
"rlay"
],
"description": "Dry-air molecular column of the layer, (dp/g)(N_A/amm)/(1 + w_h2o) in molecules/cm^2 (MM5ATM COLDRY = (PZ(L-1)-PZ(L))*1.E3*avgdro/(gravit*amm*(1+WKL(1,L)))."
},
"colh2o": {
"type": "unknown",
"units": "1/cm^2",
"shape": [
"rlay"
],
"description": "Scaled water-vapour column 1e-20 coldry w_h2o (SETCOEF COLH2O)."
},
"colco2": {
"type": "unknown",
"units": "1/cm^2",
"shape": [
"rlay"
],
"description": "Scaled CO2 column 1e-20 coldry co2vmr (SETCOEF COLCO2)."
},
"coln2o": {
"type": "unknown",
"units": "1/cm^2",
"shape": [
"rlay"
],
"description": "Scaled N2O column 1e-20 coldry n2ovmr (SETCOEF COLN2O; MM5ATM multiplies by amdn and divides it out again)."
},
"colch4": {
"type": "unknown",
"units": "1/cm^2",
"shape": [
"rlay"
],
"description": "Scaled CH4 column 1e-20 coldry ch4vmr (SETCOEF COLCH4)."
},
"taucloud": {
"type": "unknown",
"units": "1",
"shape": [
"rlay"
],
"description": "Longwave cloud optical depth of the RRTM layer: tau_model in the model layers, 0 above the model top (MM5ATM TAUCLOUD)."
},
"cldfrac": {
"type": "unknown",
"units": "1",
"shape": [
"rlay"
],
"description": "Cloud fraction of the RRTM layer: the model cloud fraction, forced to 1 where taucloud > tau_overcast, 0 above the model top (MM5ATM CLDFRAC)."
},
"tbound": {
"type": "unknown",
"units": "K",
"description": "Surface boundary temperature for the Planck emission, tsk capped at tbound_reset when it reaches tbound_limit (MM5ATM TBOUND). WRF tests TBOUND .GT. 340., so a skin temperature of exactly 340 K passes uncapped and RTRN's linear interpolation reads TOTPLNK one node past the end of the table (with a zero weight); the test here is >= so that 340 K is capped too and the lookup stays inside the 160..340 K table."
},
"semiss": {
"type": "unknown",
"units": "1",
"shape": [
"bands"
],
"description": "Surface emissivity of each of the 16 RRTM bands, all equal to emiss (MM5ATM SEMISS(N) = EMISS)."
},
"pp_sum": {
"type": "unknown",
"units": "hPa",
"shape": [
"o3nodes"
],
"description": "Pressure nodes of the summer ozone climatology (O3DATA PPSUM), also the nodes of the annual mean (PPANN = PPSUM)."
},
"o3_sum": {
"type": "unknown",
"units": "kg/kg",
"shape": [
"o3nodes"
],
"description": "Summer ozone mass mixing ratio at pp_sum (O3DATA O3SUM)."
},
"pp_win": {
"type": "unknown",
"units": "hPa",
"shape": [
"o3nodes"
],
"description": "Pressure nodes of the winter ozone climatology (O3DATA PPWIN)."
},
"o3_win": {
"type": "unknown",
"units": "kg/kg",
"shape": [
"o3nodes"
],
"description": "Winter ozone mass mixing ratio at pp_win (O3DATA O3WIN)."
},
"o3_ann": {
"type": "unknown",
"units": "kg/kg",
"shape": [
"o3nodes"
],
"description": "Annual-mean ozone climatology at pp_sum (O3DATA O3ANN): the mean of the summer value and the winter profile interpolated linearly in pressure onto the summer node (for node 1 the plain mean of the two first values), exactly as O3DATA blends the two seasons."
},
"pp_half": {
"type": "unknown",
"units": "hPa",
"shape": [
"o3edges"
],
"description": "Bin edges of the piecewise-constant annual climatology (O3DATA PPWRKH): 1100 hPa, the midpoints between successive nodes, and 0 hPa."
},
"o3_clim_integral": {
"type": "unknown",
"units": "hPa*kg/kg",
"shape": [
"rlay"
],
"description": "The pressure integral of the annual ozone climatology over the interval MM5ATM passes to O3DATA for layer L (see o3_clim): the sum over the 31 climatology bins of climatology_layer_mean. The top layer's interval is empty, so its integral is 0 (o3_clim takes the constant o3_top there)."
},
"o3_clim": {
"type": "unknown",
"units": "kg/kg",
"shape": [
"rlay"
],
"description": "Ozone mass mixing ratio of the RRTM layer as MM5ATM assigns it (O3PROF2): the pressure-weighted mean of the piecewise-constant annual climatology, (1/dp) integral of o3_ann(p) dp, over the pressure interval MM5ATM passes to O3DATA. That interval is NOT the layer's own: MM5ATM reverses PZ(1..NLAYERS) without PZ(0) into the array O3DATA reads, so layer L receives the mean over [PZ(L+1), PZ(L)] = [pz[L+2], pz[L+1]] -- the layer above it -- and the top layer receives the constant 6.135e-6 (EqWeFiC FORTRAN_BUGS.md B5). The integral is evaluated exactly as the sum over climatology bins of the overlap of the interval with each bin times the bin value (O3DATA's PB/PT bookkeeping)."
},
"colo3": {
"type": "unknown",
"units": "1/cm^2",
"shape": [
"rlay"
],
"description": "Scaled ozone column 1e-20 coldry o3_clim amdo (SETCOEF COLO3 from MM5ATM WKL(3,L) = O3PROF2(L) amdo COLDRY)."
},
"nbuf_wrf": {
"type": "unknown",
"units": "1",
"description": "The buffer-layer count WRF would use for this column, nint(p_top / deltap) with p_top = p_e[NLEV+1] in hPa (RRTMINIT: NLAYERS = kme + nint(p_top*0.01/deltap) - 1, so NLAYERS - kte buffer layers)."
},
"nbuf_mismatch": {
"type": "unknown",
"units": "1",
"description": "nbuf_wrf - NBUF: 0 when the NBUF metaparameter this component was loaded with is the one WRF derives from the column's p_top, so that the buffer levels pz = p_top - deltap k stay in (0, p_top). Nonzero means the column is mis-sized for its model top (see the NBUF metaparameter); every inline test asserts that it is 0."
}
},
"equations": [
{
"lhs": "p_e",
"rhs": {
"op": "input_p_e",
"args": []
}
},
{
"lhs": "T_e",
"rhs": {
"op": "input_T_e",
"args": []
}
},
{
"lhs": "p",
"rhs": {
"op": "input_p",
"args": []
}
},
{
"lhs": "T",
"rhs": {
"op": "input_T",
"args": []
}
},
{
"lhs": "qv",
"rhs": {
"op": "input_qv",
"args": []
}
},
{
"lhs": "qc",
"rhs": {
"op": "input_qc",
"args": []
}
},
{
"lhs": "qr",
"rhs": {
"op": "input_qr",
"args": []
}
},
{
"lhs": "qi",
"rhs": {
"op": "input_qi",
"args": []
}
},
{
"lhs": "qs",
"rhs": {
"op": "input_qs",
"args": []
}
},
{
"lhs": "cldfra",
"rhs": {
"op": "input_cldfra",
"args": []
}
},
{
"lhs": "dz_m",
"rhs": {
"op": "input_dz_m",
"args": []
}
},
{
"lhs": "rho",
"rhs": {
"op": "apply_expression_template",
"args": [],
"name": "dry_air_density",
"bindings": {
"p": "p",
"T": "T",
"r_d": "wrf.r_d"
}
}
},
{
"lhs": "clwp",
"rhs": {
"op": "apply_expression_template",
"args": [],
"name": "condensate_path",
"bindings": {
"rho": "rho",
"q": "qc",
"dz": "dz_m",
"g_per_kg": "par.g_per_kg"
}
}
},
{
"lhs": "ciwp",
"rhs": {
"op": "apply_expression_template",
"args": [],
"name": "condensate_path",
"bindings": {
"rho": "rho",
"q": "qi",
"dz": "dz_m",
"g_per_kg": "par.g_per_kg"
}
}
},
{
"lhs": "plwp",
"rhs": {
"op": "apply_expression_template",
"args": [],
"name": "precipitation_path",
"bindings": {
"rho": "rho",
"q": "qr",
"dz": "dz_m",
"rho_ref": "par.rho_ref",
"g_per_kg": "par.g_per_kg"
}
}
},
{
"lhs": "piwp",
"rhs": {
"op": "apply_expression_template",
"args": [],
"name": "precipitation_path",
"bindings": {
"rho": "rho",
"q": "qs",
"dz": "dz_m",
"rho_ref": "par.rho_ref",
"g_per_kg": "par.g_per_kg"
}
}
},
{
"lhs": "tau_model",
"rhs": {
"op": "+",
"args": [
{
"op": "*",
"args": [
"par.abcw",
"clwp"
]
},
{
"op": "*",
"args": [
"par.abice",
"ciwp"
]
},
{
"op": "*",
"args": [
"par.abrn",
"plwp"
]
},
{
"op": "*",
"args": [
"par.absn",
"piwp"
]
}
]
}
},
{
"lhs": "pz",
"rhs": {
"op": "aggregate",
"output_idx": [
"j"
],
"args": [
"p_e"
],
"ranges": {
"j": {
"from": "rlev"
}
},
"expr": {
"op": "ifelse",
"args": [
{
"op": "<=",
"args": [
"j",
{
"op": "+",
"args": [
"NLEV",
1
]
}
]
},
{
"op": "/",
"args": [
{
"op": "index",
"args": [
"p_e",
{
"op": "apply_expression_template",
"args": [],
"name": "model_level_index",
"bindings": {
"j": "j"
}
}
]
},
"par.pa_per_hpa"
]
},
{
"op": "ifelse",
"args": [
{
"op": "<=",
"args": [
"j",
{
"op": "+",
"args": [
"NLEV",
"NBUF"
]
}
]
},
{
"op": "-",
"args": [
{
"op": "/",
"args": [
{
"op": "index",
"args": [
"p_e",
{
"op": "+",
"args": [
"NLEV",
1
]
}
]
},
"par.pa_per_hpa"
]
},
{
"op": "*",
"args": [
"par.deltap",
{
"op": "-",
"args": [
"j",
{
"op": "+",
"args": [
"NLEV",
1
]
}
]
}
]
}
]
},
0.0
]
}
]
}
}
},
{
"lhs": "tz",
"rhs": {
"op": "aggregate",
"output_idx": [
"j"
],
"args": [
"T_e",
"pz"
],
"ranges": {
"j": {
"from": "rlev"
}
},
"expr": {
"op": "ifelse",
"args": [
{
"op": "<=",
"args": [
"j",
{
"op": "+",
"args": [
"NLEV",
1
]
}
]
},
{
"op": "index",
"args": [
"T_e",
{
"op": "apply_expression_template",
"args": [],
"name": "model_level_index",
"bindings": {
"j": "j"
}
}
]
},
{
"op": "+",
"args": [
{
"op": "apply_expression_template",
"args": [],
"name": "standard_atmosphere_temperature",
"bindings": {
"p": {
"op": "index",
"args": [
"pz",
"j"
]
}
}
},
{
"op": "-",
"args": [
{
"op": "index",
"args": [
"T_e",
{
"op": "+",
"args": [
"NLEV",
1
]
}
]
},
{
"op": "apply_expression_template",
"args": [],
"name": "standard_atmosphere_temperature",
"bindings": {
"p": {
"op": "index",
"args": [
"pz",
{
"op": "+",
"args": [
"NLEV",
1
]
}
]
}
}
}
]
}
]
}
]
}
}
},
{
"lhs": "pavel",
"rhs": {
"op": "aggregate",
"output_idx": [
"L"
],
"args": [
"p",
"pz"
],
"ranges": {
"L": {
"from": "rlay"
}
},
"expr": {
"op": "apply_expression_template",
"args": [],
"name": "model_or_buffer_layer",
"bindings": {
"L": "L",
"model_value": {
"op": "/",
"args": [
{
"op": "index",
"args": [
"p",
{
"op": "apply_expression_template",
"args": [],
"name": "model_layer_index",
"bindings": {
"L": "L"
}
}
]
},
"par.pa_per_hpa"
]
},
"buffer_value": {
"op": "apply_expression_template",
"args": [],
"name": "level_mean",
"bindings": {
"x": "pz",
"L": "L"
}
}
}
}
}
},
{
"lhs": "tavel",
"rhs": {
"op": "aggregate",
"output_idx": [
"L"
],
"args": [
"T",
"tz"
],
"ranges": {
"L": {
"from": "rlay"
}
},
"expr": {
"op": "apply_expression_template",
"args": [],
"name": "model_or_buffer_layer",
"bindings": {
"L": "L",
"model_value": {
"op": "index",
"args": [
"T",
{
"op": "apply_expression_template",
"args": [],
"name": "model_layer_index",
"bindings": {
"L": "L"
}
}
]
},
"buffer_value": {
"op": "apply_expression_template",
"args": [],
"name": "level_mean",
"bindings": {
"x": "tz",
"L": "L"
}
}
}
}
}
},
{
"lhs": "w_h2o",
"rhs": {
"op": "aggregate",
"output_idx": [
"L"
],
"args": [
"qv"
],
"ranges": {
"L": {
"from": "rlay"
}
},
"expr": {
"op": "apply_expression_template",
"args": [],
"name": "model_or_buffer_layer",
"bindings": {
"L": "L",
"model_value": {
"op": "*",
"args": [
{
"op": "max",
"args": [
{
"op": "index",
"args": [
"qv",
{
"op": "apply_expression_template",
"args": [],
"name": "model_layer_index",
"bindings": {
"L": "L"
}
}
]
},
"par.qv_min"
]
},
"par.amdw"
]
},
"buffer_value": "par.h2ovmr_top"
}
}
}
},
{
"lhs": "amm",
"rhs": {
"op": "+",
"args": [
{
"op": "*",
"args": [
{
"op": "-",
"args": [
1.0,
"w_h2o"
]
},
"par.amd"
]
},
{
"op": "*",
"args": [
"w_h2o",
"par.amw"
]
}
]
}
},
{
"lhs": "coldry",
"rhs": {
"op": "aggregate",
"output_idx": [
"L"
],
"args": [
"pz",
"amm",
"w_h2o"
],
"ranges": {
"L": {
"from": "rlay"
}
},
"expr": {
"op": "/",
"args": [
{
"op": "*",
"args": [
{
"op": "-",
"args": [
{
"op": "index",
"args": [
"pz",
"L"
]
},
{
"op": "index",
"args": [
"pz",
{
"op": "+",
"args": [
"L",
1
]
}
]
}
]
},
"par.pa_per_hpa",
"par.g_per_kg",
"par.avgdro"
]
},
{
"op": "*",
"args": [
"wrf.g",
"par.cm2_per_m2",
{
"op": "index",
"args": [
"amm",
"L"
]
},
{
"op": "+",
"args": [
1.0,
{
"op": "index",
"args": [
"w_h2o",
"L"
]
}
]
}
]
}
]
}
}
},
{
"lhs": "colh2o",
"rhs": {
"op": "*",
"args": [
"par.col_scale",
"coldry",
"w_h2o"
]
}
},
{
"lhs": "colco2",
"rhs": {
"op": "*",
"args": [
"par.col_scale",
"coldry",
"co2vmr"
]
}
},
{
"lhs": "coln2o",
"rhs": {
"op": "*",
"args": [
"par.col_scale",
"coldry",
"n2ovmr"
]
}
},
{
"lhs": "colch4",
"rhs": {
"op": "*",
"args": [
"par.col_scale",
"coldry",
"ch4vmr"
]
}
},
{
"lhs": "taucloud",
"rhs": {
"op": "aggregate",
"output_idx": [
"L"
],
"args": [
"tau_model"
],
"ranges": {
"L": {
"from": "rlay"
}
},
"expr": {
"op": "apply_expression_template",
"args": [],
"name": "model_or_buffer_layer",
"bindings": {
"L": "L",
"model_value": {
"op": "index",
"args": [
"tau_model",
{
"op": "apply_expression_template",
"args": [],
"name": "model_layer_index",
"bindings": {
"L": "L"
}
}
]
},
"buffer_value": 0.0
}
}
}
},
{
"lhs": "cldfrac",
"rhs": {
"op": "aggregate",
"output_idx": [
"L"
],
"args": [
"cldfra",
"taucloud"
],
"ranges": {
"L": {
"from": "rlay"
}
},
"expr": {
"op": "apply_expression_template",
"args": [],
"name": "model_or_buffer_layer",
"bindings": {
"L": "L",
"model_value": {
"op": "ifelse",
"args": [
{
"op": ">",
"args": [
{
"op": "index",
"args": [
"taucloud",
"L"
]
},
"par.tau_overcast"
]
},
1.0,
{
"op": "index",
"args": [
"cldfra",
{
"op": "apply_expression_template",
"args": [],
"name": "model_layer_index",
"bindings": {
"L": "L"
}
}
]
}
]
},
"buffer_value": 0.0
}
}
}
},
{
"lhs": "tbound",
"rhs": {
"op": "ifelse",
"args": [
{
"op": ">=",
"args": [
"tsk",
"par.tbound_limit"
]
},
"par.tbound_reset",
"tsk"
]
}
},
{
"lhs": "semiss",
"rhs": {
"op": "aggregate",
"output_idx": [
"b"
],
"args": [],
"ranges": {
"b": {
"from": "bands"
}
},
"expr": "emiss"
}
},
{
"lhs": "pp_sum",
"rhs": {
"op": "*",
"args": [
"par.unit_hpa",
{
"op": "aggregate",
"args": [],
"output_idx": [
"k"
],
"ranges": {
"k": {
"from": "o3nodes"
}
},
"expr": {
"op": "index",
"args": [
{
"op": "apply_expression_template",
"args": [],
"name": "o3data_ppsum",
"bindings": {}
},
"k"
]
}
}
]
}
},
{
"lhs": "o3_sum",
"rhs": {
"op": "aggregate",
"args": [],
"output_idx": [
"k"
],
"ranges": {
"k": {
"from": "o3nodes"
}
},
"expr": {
"op": "index",
"args": [
{
"op": "apply_expression_template",
"args": [],
"name": "o3data_o3sum",
"bindings": {}
},
"k"
]
}
}
},
{
"lhs": "pp_win",
"rhs": {
"op": "*",
"args": [
"par.unit_hpa",
{
"op": "aggregate",
"args": [],
"output_idx": [
"k"
],
"ranges": {
"k": {
"from": "o3nodes"
}
},
"expr": {
"op": "index",
"args": [
{
"op": "apply_expression_template",
"args": [],
"name": "o3data_ppwin",
"bindings": {}
},
"k"
]
}
}
]
}
},
{
"lhs": "o3_win",
"rhs": {
"op": "aggregate",
"args": [],
"output_idx": [
"k"
],
"ranges": {
"k": {
"from": "o3nodes"
}
},
"expr": {
"op": "index",
"args": [
{
"op": "apply_expression_template",
"args": [],
"name": "o3data_o3win",
"bindings": {}
},
"k"
]
}
}
},
{
"lhs": "o3_ann",
"rhs": {
"op": "aggregate",
"args": [],
"output_idx": [
"k"
],
"ranges": {
"k": {
"from": "o3nodes"
}
},
"expr": {
"op": "*",
"args": [
0.5,
{
"op": "ifelse",
"args": [
{
"op": "==",
"args": [
"k",
1
]
},
{
"op": "+",
"args": [
{
"op": "index",
"args": [
"o3_sum",
1
]
},
{
"op": "index",
"args": [
"o3_win",
1
]
}
]
},
{
"op": "+",
"args": [
{
"op": "+",
"args": [
{
"op": "index",
"args": [
"o3_win",
{
"op": "max",
"args": [
{
"op": "-",
"args": [
"k",
1
]
},
1
]
}
]
},
{
"op": "*",
"args": [
{
"op": "/",
"args": [
{
"op": "-",
"args": [
{
"op": "index",
"args": [
"o3_win",
"k"
]
},
{
"op": "index",
"args": [
"o3_win",
{
"op": "max",
"args": [
{
"op": "-",
"args": [
"k",
1
]
},
1
]
}
]
}
]
},
{
"op": "-",
"args": [
{
"op": "index",
"args": [
"pp_win",
"k"
]
},
{
"op": "index",
"args": [
"pp_win",
{
"op": "max",
"args": [
{
"op": "-",
"args": [
"k",
1
]
},
1
]
}
]
}
]
}
]
},
{
"op": "-",
"args": [
{
"op": "index",
"args": [
"pp_sum",
"k"
]
},
{
"op": "index",
"args": [
"pp_win",
{
"op": "max",
"args": [
{
"op": "-",
"args": [
"k",
1
]
},
1
]
}
]
}
]
}
]
}
]
},
{
"op": "index",
"args": [
"o3_sum",
"k"
]
}
]
}
]
}
]
}
}
},
{
"lhs": "pp_half",
"rhs": {
"op": "aggregate",
"args": [],
"output_idx": [
"j"
],
"ranges": {
"j": {
"from": "o3edges"
}
},
"expr": {
"op": "ifelse",
"args": [
{
"op": "==",
"args": [
"j",
1
]
},
"par.pp_half_bottom",
{
"op": "ifelse",
"args": [
{
"op": "==",
"args": [
"j",
32
]
},
{
"op": "*",
"args": [
0.0,
"par.unit_hpa"
]
},
{
"op": "*",
"args": [
0.5,
{
"op": "+",
"args": [
{
"op": "index",
"args": [
"pp_sum",
{
"op": "min",
"args": [
"j",
31
]
}
]
},
{
"op": "index",
"args": [
"pp_sum",
{
"op": "max",
"args": [
{
"op": "-",
"args": [
"j",
1
]
},
1
]
}
]
}
]
}
]
}
]
}
]
}
}
},
{
"lhs": "o3_clim_integral",
"rhs": {
"op": "aggregate",
"args": [],
"output_idx": [
"L"
],
"ranges": {
"L": {
"from": "rlay"
},
"j": {
"from": "o3nodes"
}
},
"expr": {
"op": "apply_expression_template",
"args": [],
"name": "climatology_layer_mean",
"bindings": {
"p_bottom": {
"op": "index",
"args": [
"pz",
{
"op": "+",
"args": [
"L",
1
]
}
]
},
"p_top": {
"op": "index",
"args": [
"pz",
{
"op": "min",
"args": [
{
"op": "+",
"args": [
"L",
2
]
},
{
"op": "+",
"args": [
{
"op": "+",
"args": [
"NLEV",
"NBUF"
]
},
1
]
}
]
}
]
},
"j": "j"
}
}
}
},
{
"lhs": "o3_clim",
"rhs": {
"op": "aggregate",
"args": [],
"output_idx": [
"L"
],
"ranges": {
"L": {
"from": "rlay"
}
},
"expr": {
"op": "ifelse",
"args": [
{
"op": "<",
"args": [
"L",
{
"op": "+",
"args": [
"NLEV",
"NBUF"
]
}
]
},
{
"op": "/",
"args": [
{
"op": "index",
"args": [
"o3_clim_integral",
"L"
]
},
{
"op": "-",
"args": [
{
"op": "index",
"args": [
"pz",
{
"op": "+",
"args": [
"L",
1
]
}
]
},
{
"op": "index",
"args": [
"pz",
{
"op": "min",
"args": [
{
"op": "+",
"args": [
"L",
2
]
},
{
"op": "+",
"args": [
{
"op": "+",
"args": [
"NLEV",
"NBUF"
]
},
1
]
}
]
}
]
}
]
}
]
},
"par.o3_top"
]
}
}
},
{
"lhs": "colo3",
"rhs": {
"op": "*",
"args": [
"par.col_scale",
"coldry",
"o3_clim",
"par.amdo"
]
}
},
{
"lhs": "nbuf_wrf",
"rhs": {
"op": "floor",
"args": [
{
"op": "+",
"args": [
{
"op": "/",
"args": [
{
"op": "index",
"args": [
"p_e",
{
"op": "+",
"args": [
"NLEV",
1
]
}
]
},
{
"op": "*",
"args": [
"par.pa_per_hpa",
"par.deltap"
]
}
]
},
0.5
]
}
]
}
},
{
"lhs": "nbuf_mismatch",
"rhs": {
"op": "-",
"args": [
"nbuf_wrf",
"NBUF"
]
}
}
],
"tests": [
{
"id": "scm_call1_clear",
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"n2ovmr": 3.1900000863060995e-07,
"ch4vmr": 1.7739999975674436e-06,
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"emiss": 0.9200000166893005
},
"expression_template_imports": [
{
"ref": "./tests/scm_call1_clear_inputs.esm"
}
],
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"start": 0,
"end": 1
},
"tolerance": {
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"n2ovmr": 3.1900000863060995e-07,
"ch4vmr": 1.7739999975674436e-06,
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"description": "Reference: WRF 4.8 em_scm_xy single-column run (GNU real32 build, dt = 60 s, 59 layers, p_top = 177.6 hPa so NBUF = 44 buffer layers, mp=6 ra_lw=1 ra_sw=1 sf_sfclay=1 sf_surface=1 bl_pbl=1) dumped by the instrumented fork ctessum-claude/WRF, commit 592f693 (v4.8.0-5-g592f6931); module_esm_dump hooks in RRTMLWRAD and after RTRN inside SUBROUTINE RRTM of phys/module_ra_rrtm.F; dump scm_cloud_240.json, written by the same em_scm_xy run re-executed for 8 h with the cloudy calls added to ESM_DUMP_CALLS; the re-run reproduces the archived call 120 dump bit-for-bit, so it is the same trajectory). RRTM has no standalone real64 driver, so every expected value is the real32 in-model value of MM5ATM/SETCOEF (PAVEL, TAVEL, PZ, TZ, COLDRY, COLH2O, COLCO2, COLN2O, COLCH4, CLDFRAC, TAUCLOUD, COLO3, TBOUND, SEMISS) and the tolerance contract is rel 1e-5. Inputs are the dumped RRTMLWRAD arguments of tile column 1 (p8w, t8w, p3d, t3d, qv..qs, cldfra3d, dz8w, bottom-up) and the scalars co2vmr, n2ovmr, ch4vmr, tsk, emiss. Column assertions are Linf_error with abs tolerances of about 1e-5 of each field's column maximum (pz, pavel 1e-2 hPa; tz, tavel 3e-3 K; coldry 6e18 cm^-2; colh2o 2e-4, colco2 3e-5, coln2o 2e-8, colch4 1e-7 cm^-2; colo3 1e-7; cldfrac exactly 0), the spot checks at the lowest model layer, the top model layer, the first buffer layer and the top buffer layer use rel 2e-5 for the column amounts and rel 1e-5 otherwise, and identities on the inputs (tbound, semiss) use rel 1e-9. This regime is one of the four added on 2026-09-06 to cover MM5ATM's cloud block (phys/module_ra_rrtm.F:4252-4255): TAUCLOUD(L) = ABCW CLWP + ABICE CIWP + ABRN PLWP + ABSN PIWP on the model layers and zero on the buffer layers, and the overcast override IF (TAUCLOUD > 0.01) CLDFRC = 1, which replaces the diagnosed cloud fraction of every optically thicker layer by 1 and is the reason RTRN can only ever see 0 < CLDFRAC < 1 in a layer whose cloud optical depth is at or below 0.01. Regime: FRACTIONAL CLOUD. Call 240, 21:00 UTC (14:34 LST), the decaying cirrus deck. Layers 51-54 have TAUCLOUD 0.0728, 0.1423, 0.0709, 0.0403 and are overridden from CLDFRA 0.0542, 0.355, 0.402, 0.388 to CLDFRAC = 1, while layer 55 has TAUCLOUD = 0.009966, just below the threshold, and keeps its diagnosed CLDFRA = 0.1470 -- the largest fractional cloud fraction the scheme admits anywhere in this run, and the input of the RTRNSweep test scm_call240_fractional_cloud. Layers 56-57 are diagnosed overcast already. tsk = 285.85 K. Measured mismatch: pz and pavel to Linf 2.9e-5 hPa, tz to 2.9e-5 K and tavel to 2.0e-5 K, coldry to 9.6e17 cm^-2 and the column amounts to 1.4e-6 relative (colh2o Linf 3.3e-5, colco2 3.7e-6, coln2o 3.1e-9, colch4 1.7e-8, colo3 2.7e-8 cm^-2), CLDFRAC exactly -- including the four overridden layers and the fractional layer 55 that keeps its 0.1470 -- and TAUCLOUD to Linf 6.5e-9 on a column maximum of 0.1423, so taucloud uses abs 1e-7 (15x the measured floor).",
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"description": "Reference: WRF 4.8 idealized supercell (em_quarter_ss, Weisman-Klemp sounding, 41 x 41 x 59 mass points, dx = 2 km, dt = 6 s, ztop = 12800 m so p_top = 177.07 hPa and NBUF = nint(p_top/4 hPa) = 44 -- the same 59 + 44 = 103-layer RRTM column as the em_scm_xy regimes, because esm inline tests cannot override the NLEV/NBUF metaparameters) with mp=6 (WSM6), ra_lw=1 (RRTM), ra_sw=1 (Dudhia), radt = 5 min and no surface/PBL scheme, run for 1 h and dumped by the instrumented fork ctessum-claude/WRF, commit 5cb62da (v4.8.0-6-g5cb62da7); module_esm_dump hooks in RRTMLWRAD and after RTRN inside SUBROUTINE RRTM of phys/module_ra_rrtm.F, GNU real32 build). The RRTM hook dumps one j-row per call, so call = (nrad - 1) * 41 + j, and the new ESM_DUMP_I selector picks which tile column's MM5ATM/SETCOEF/RTRN internals are written; here column i = 20. RRTM has no standalone real64 driver, so every expected value is the real32 in-model value of MM5ATM/SETCOEF (PAVEL, TAVEL, PZ, TZ, COLDRY, COLH2O, COLCO2, COLN2O, COLCH4, COLO2, COLO3, CLDFRAC, TAUCLOUD, TBOUND, SEMISS) and the tolerance contract is rel 1e-5. Inputs are the dumped RRTMLWRAD arguments of that column (p8w, t8w, p3d, t3d, qv..qs, cldfra3d, dz8w, bottom-up) and the scalars co2vmr, n2ovmr, ch4vmr, tsk, emiss. Column assertions are Linf_error with abs tolerances of about 1e-5 of each field's column maximum (pz, pavel 1e-2 hPa; tz, tavel 3e-3 K; coldry 6e18 cm^-2; colh2o 1.5e-3 -- the supercell column holds 131 cm^-2, six times the SCM's, so this one is scaled up from the SCM regimes' 2e-4; colco2 3e-5, coln2o 2e-8, colch4 1e-7, colo3 1e-7 cm^-2; cldfrac exactly 0), and the spot checks at the lowest model layer, the top model layer, the first buffer layer and the top buffer layer use rel 2e-5 for the column amounts and rel 1e-5 otherwise. This regime exists to exercise the three terms of MM5ATM's cloud optical depth (phys/module_ra_rrtm.F:4252-4253) that the em_scm_xy reference case leaves at zero: TAUCLOUD(L) = ABCW CLWP + ABICE CIWP + ABRN PLWP + ABSN PIWP with ABCW = 0.144, ABICE = 0.0735, ABRN = 0.330e-3, ABSN = 2.34e-3 -- the SCM run is ice-only (qc = qr = qs = qg = 0 for all 59 h), so only ABICE was ever verified. Regime: WARM LIQUID CLOUD, the pure ABCW case. Call 61 (nrad = 2, model time 00:05:00, j = 20, i = 20): the first convective thermal of the run, entirely above freezing (T = 274.1-284.1 K in the cloud) and entirely liquid -- qi = qr = qs = qg = 0 EVERYWHERE in the column, qc up to 2.186e-4 kg/kg in RRTM layers 10-15, so TAUCLOUD = ABCW CLWP alone there and nowhere else. TAUCLOUD = 1.262, 3.825, 6.107, 6.430, 4.409, 1.351 in layers 10-15 and 0 in the other 97; a wrong ABCW moves every one of those six numbers proportionally, and no other coefficient can compensate. The diagnosed CLDFRA there is 0.423-0.988, all above the 0.01 optical-depth threshold, so MM5ATM's IF (TAUCLOUD > 0.01) CLDFRC = 1 override (N58) forces CLDFRAC = 1 in all six -- the liquid twin of the ice overcast regime at SCM call 120. tsk = 299.97 K, emiss = 0.85. Measured mismatch: pz and pavel to Linf 2.9e-5 hPa (the real32 Pa -> hPa division), tz to 2.3e-5 K and tavel to 1.8e-5 K, coldry to 1.1e18 cm^-2, colh2o to 1.8e-4, colco2 to 4.1e-6, coln2o to 3.6e-9, colch4 to 1.9e-8 and colo3 to 2.8e-8 cm^-2, CLDFRAC and COLO2 exactly, and TAUCLOUD to Linf 8.5e-7 on a column maximum of 6.430 (1.4e-7 relative at worst), so this regime's taucloud tolerance is abs 1e-5 -- 12x the measured floor and 1.6e-6 of the column maximum, the same fraction the SCM regimes use -- and the six per-layer spot checks use the contract rel 1e-5, 70x their measured floor.",
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"description": "Reference: WRF 4.8 idealized supercell (em_quarter_ss, Weisman-Klemp sounding, 41 x 41 x 59 mass points, dx = 2 km, dt = 6 s, ztop = 12800 m so p_top = 177.07 hPa and NBUF = nint(p_top/4 hPa) = 44 -- the same 59 + 44 = 103-layer RRTM column as the em_scm_xy regimes, because esm inline tests cannot override the NLEV/NBUF metaparameters) with mp=6 (WSM6), ra_lw=1 (RRTM), ra_sw=1 (Dudhia), radt = 5 min and no surface/PBL scheme, run for 1 h and dumped by the instrumented fork ctessum-claude/WRF, commit 5cb62da (v4.8.0-6-g5cb62da7); module_esm_dump hooks in RRTMLWRAD and after RTRN inside SUBROUTINE RRTM of phys/module_ra_rrtm.F, GNU real32 build). The RRTM hook dumps one j-row per call, so call = (nrad - 1) * 41 + j, and the new ESM_DUMP_I selector picks which tile column's MM5ATM/SETCOEF/RTRN internals are written; here column i = 20. RRTM has no standalone real64 driver, so every expected value is the real32 in-model value of MM5ATM/SETCOEF (PAVEL, TAVEL, PZ, TZ, COLDRY, COLH2O, COLCO2, COLN2O, COLCH4, COLO2, COLO3, CLDFRAC, TAUCLOUD, TBOUND, SEMISS) and the tolerance contract is rel 1e-5. Inputs are the dumped RRTMLWRAD arguments of that column (p8w, t8w, p3d, t3d, qv..qs, cldfra3d, dz8w, bottom-up) and the scalars co2vmr, n2ovmr, ch4vmr, tsk, emiss. Column assertions are Linf_error with abs tolerances of about 1e-5 of each field's column maximum (pz, pavel 1e-2 hPa; tz, tavel 3e-3 K; coldry 6e18 cm^-2; colh2o 1.5e-3 -- the supercell column holds 131 cm^-2, six times the SCM's, so this one is scaled up from the SCM regimes' 2e-4; colco2 3e-5, coln2o 2e-8, colch4 1e-7, colo3 1e-7 cm^-2; cldfrac exactly 0), and the spot checks at the lowest model layer, the top model layer, the first buffer layer and the top buffer layer use rel 2e-5 for the column amounts and rel 1e-5 otherwise. This regime exists to exercise the three terms of MM5ATM's cloud optical depth (phys/module_ra_rrtm.F:4252-4253) that the em_scm_xy reference case leaves at zero: TAUCLOUD(L) = ABCW CLWP + ABICE CIWP + ABRN PLWP + ABSN PIWP with ABCW = 0.144, ABICE = 0.0735, ABRN = 0.330e-3, ABSN = 2.34e-3 -- the SCM run is ice-only (qc = qr = qs = qg = 0 for all 59 h), so only ABICE was ever verified. Regime: MIXED-PHASE STORM COLUMN, all four terms at once. Call 268 (nrad = 7, model time 00:30:00, j = 22, i = 20): a mature supercell column, cloudy in 57 of the 59 model layers, with qc <= 8.4e-4, qr <= 1.05e-2, qi <= 1.05e-4 and qs <= 8.2e-5 kg/kg. TAUCLOUD rises to 18.74 and every one of the four terms dominates somewhere in the column, which is what makes each coefficient separately observable: layers 1-10 are pure rain (qc = qi = qs = 0, TAUCLOUD = 0.3996 at layer 1 and 2.384 at layer 8 = ABRN PLWP alone); layers 11-19 are liquid + rain (layer 12: 1.199 from ABCW and 2.329 from ABRN, TAUCLOUD = 3.528); layers 22-33 carry all four (layer 24: 17.56 + 0.0161 + 1.160 + 0.00138 = 18.73); layers 39-41 are pure ice (layer 39: 0.7676 = ABICE CIWP alone); and layers 51-54 are snow-dominated (layer 52: 5.759e-2, of which the snow term is 5.759e-2 and the ice term only 5.4e-6, i.e. 99.99 % ABSN; layer 54 splits 1.128e-2 ice against 1.253e-2 snow). Layer 56 is the one layer the CLDFRC override leaves alone (TAUCLOUD = 4.81e-3 < 0.01), so CLDFRAC = 0.0110 survives into RTRN, while layer 55 at TAUCLOUD = 1.311e-2 is forced from 0.031 to 1. tsk = 300.02 K, emiss = 0.85. Measured mismatch: pz to Linf 2.7e-5 hPa and pavel to 2.9e-5 hPa (the real32 Pa -> hPa division), tz to 2.3e-5 K and tavel to 1.8e-5 K, coldry to 1.1e18 cm^-2, colh2o to 1.8e-4, colco2 to 4.3e-6, coln2o to 3.5e-9, colch4 to 2.0e-8 and colo3 to 2.7e-8 cm^-2, CLDFRAC and COLO2 exactly, and TAUCLOUD to Linf 3.1e-6 on a column maximum of 18.74 (1.3e-7 relative at worst and <= 4.6e-8 at each of the eight spot-check layers), so this regime's taucloud tolerance is abs 3e-5 -- 10x the measured floor and 1.6e-6 of the column maximum -- and the spot checks use the contract rel 1e-5, 200x their measured floor. Graupel reaches 6.2e-4 kg/kg here and contributes nothing: MM5ATM takes QG as an argument and never uses it (EqWeFiC FORTRAN_BUGS.md N62).",
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"rlay": 103
},
"expected": 0.003980841021984816,
"tolerance": {
"rel": 1e-05
}
},
{
"variable": "o3_clim",
"time": 0.0,
"coords": {
"rlay": 59
},
"expected": 8.709451077810015e-07,
"tolerance": {
"rel": 1e-05
}
},
{
"variable": "o3_clim",
"time": 0.0,
"coords": {
"rlay": 60
},
"expected": 8.709438308289634e-07,
"tolerance": {
"rel": 1e-05
}
},
{
"variable": "o3_clim",
"time": 0.0,
"coords": {
"rlay": 90
},
"expected": 4.918447349474289e-06,
"tolerance": {
"rel": 1e-05
}
},
{
"variable": "o3_clim",
"time": 0.0,
"coords": {
"rlay": 102
},
"expected": 9.352992780375408e-06,
"tolerance": {
"rel": 1e-05
}
},
{
"variable": "o3_clim",
"time": 0.0,
"coords": {
"rlay": 103
},
"expected": 6.135000549119483e-06,
"tolerance": {
"rel": 1e-05
}
},
{
"variable": "nbuf_mismatch",
"time": 0.0,
"expected": 0.0,
"tolerance": {
"abs": 0.0
}
}
]
},
{
"id": "tbound_cap_at_table_limit",
"description": "Regression for the Planck-table cap: the scm_call1_clear column with the skin temperature set to exactly tbound_limit = 340 K. tbound must be reset to tbound_reset = 339.99 K, so that RTRN's TOTPLNK interpolation (nodes 160..340 K, reading node floor(T) - 159 and the one above it) stays inside the table. WRF's own test is TBOUND .GT. 340. and would pass 340 K through; the assertion is exact (rel 1e-9) because the cap is a plain assignment.",
"parameter_overrides": {
"co2vmr": 0.00037900000461377203,
"n2ovmr": 3.1900000863060995e-07,
"ch4vmr": 1.7739999975674436e-06,
"tsk": 340.0,
"emiss": 0.9200000166893005
},
"expression_template_imports": [
{
"ref": "./tests/scm_call1_clear_inputs.esm"
}
],
"time_span": {
"start": 0,
"end": 1
},
"tolerance": {
"rel": 1e-05
},
"assertions": [
{
"variable": "tbound",
"time": 0.0,
"expected": 339.99,
"tolerance": {
"rel": 1e-09
}
},
{
"variable": "nbuf_mismatch",
"time": 0.0,
"expected": 0.0,
"tolerance": {
"abs": 0.0
}
}
]
}
]
}