Merge pull request #103 from CliMA/yc/fix_buoy_extrap

set qt and h in extrap buoyancy to clear values

fix change in qt issue

use the correct qt and qv in extra bouy

update tables

fix tables

integration_tests/ARM_SGP.jl

@@ -11,18 +11,18 @@ include(joinpath("utils", "compute_mse.jl"))
 using .NameList
 
 best_mse = OrderedDict()
-best_mse["qt_mean"] = 3.4420193413687117e-01
-best_mse["updraft_area"] = 1.9818317322584239e+03
-best_mse["updraft_w"] = 3.1101869507553300e+02
-best_mse["updraft_qt"] = 1.2779005319987142e+01
-best_mse["updraft_thetal"] = 2.7687174775467490e+01
-best_mse["u_mean"] = 8.7998547277817835e+01
-best_mse["tke_mean"] = 6.7532125088372368e+02
-best_mse["temperature_mean"] = 1.3976231155597154e-04
-best_mse["ql_mean"] = 2.9406894196734129e+02
-best_mse["thetal_mean"] = 1.4216021128644291e-04
-best_mse["Hvar_mean"] = 1.4219930941047571e+03
-best_mse["QTvar_mean"] = 2.7979236616322686e+02
+best_mse["qt_mean"] = 3.5691847012203143e-01
+best_mse["updraft_area"] = 1.9645743867371027e+03
+best_mse["updraft_w"] = 3.5781735855735855e+02
+best_mse["updraft_qt"] = 1.3457137434986310e+01
+best_mse["updraft_thetal"] = 2.7680764603306077e+01
+best_mse["u_mean"] = 8.7998547277817920e+01
+best_mse["tke_mean"] = 6.3658705239459096e+02
+best_mse["temperature_mean"] = 1.3818806435138376e-04
+best_mse["ql_mean"] = 3.6220527567539864e+02
+best_mse["thetal_mean"] = 1.4145191959567767e-04
+best_mse["Hvar_mean"] = 1.5980068858564114e+03
+best_mse["QTvar_mean"] = 3.6076370680937271e+02
 
 @testset "ARM_SGP" begin
     println("Running ARM_SGP...")

integration_tests/Bomex.jl

@@ -11,19 +11,19 @@ include(joinpath("utils", "compute_mse.jl"))
 using .NameList
 
 best_mse = OrderedDict()
-best_mse["qt_mean"] = 9.5377282321874049e-02
-best_mse["updraft_area"] = 7.2522420468798543e+02
-best_mse["updraft_w"] = 2.6282677670021386e+01
-best_mse["updraft_qt"] = 4.0341139540222635e+00
-best_mse["updraft_thetal"] = 2.1548164483602367e+01
-best_mse["v_mean"] = 6.5247595142753596e+01
-best_mse["u_mean"] = 5.3292989796462209e+01
-best_mse["tke_mean"] = 3.8891129116688681e+01
-best_mse["temperature_mean"] = 3.8547176978568602e-05
-best_mse["ql_mean"] = 3.8134281154981489e+00
-best_mse["thetal_mean"] = 3.9162071364386570e-05
-best_mse["Hvar_mean"] = 7.5510623226760771e+01
-best_mse["QTvar_mean"] = 2.2962565404185188e+01
+best_mse["qt_mean"] = 9.8858939409301599e-02
+best_mse["updraft_area"] = 7.2423270403289905e+02
+best_mse["updraft_w"] = 2.7297489157558520e+01
+best_mse["updraft_qt"] = 4.0686060603282321e+00
+best_mse["updraft_thetal"] = 2.1547376374778047e+01
+best_mse["v_mean"] = 6.5159453481189033e+01
+best_mse["u_mean"] = 5.3292347667845092e+01
+best_mse["tke_mean"] = 3.8707689709123862e+01
+best_mse["temperature_mean"] = 4.0396510560887023e-05
+best_mse["ql_mean"] = 3.9678285547654855e+00
+best_mse["thetal_mean"] = 4.1130421765389724e-05
+best_mse["Hvar_mean"] = 5.9914307236483694e+01
+best_mse["QTvar_mean"] = 1.9732739289298404e+01
 
 @testset "Bomex" begin
     println("Running Bomex...")

integration_tests/DYCOMS_RF01.jl

@@ -11,19 +11,19 @@ include(joinpath("utils", "compute_mse.jl"))
 using .NameList
 
 best_mse = OrderedDict()
-best_mse["qt_mean"] = 1.6029892735513345e-02
-best_mse["ql_mean"] = 6.0295296107176544e+00
-best_mse["updraft_area"] = 2.3847762474738320e+02
-best_mse["updraft_w"] = 4.3312794675046318e+00
-best_mse["updraft_qt"] = 1.1929325513431135e+00
-best_mse["updraft_thetal"] = 1.2740562957739254e+01
-best_mse["v_mean"] = 3.9737745703044638e+01
-best_mse["u_mean"] = 3.7038099069367689e+01
-best_mse["tke_mean"] = 1.4950275863942871e+01
-best_mse["temperature_mean"] = 1.6731316538438984e-05
-best_mse["thetal_mean"] = 1.7840937307304572e-05
-best_mse["Hvar_mean"] = 1.2023987118420042e+04
-best_mse["QTvar_mean"] = 7.5103635873377698e+02
+best_mse["qt_mean"] = 1.6028016672273267e-02
+best_mse["ql_mean"] = 5.9785694176953177e+00
+best_mse["updraft_area"] = 2.3855918967670206e+02
+best_mse["updraft_w"] = 4.3334326744994369e+00
+best_mse["updraft_qt"] = 1.1941194458788802e+00
+best_mse["updraft_thetal"] = 1.2740391229155120e+01
+best_mse["v_mean"] = 3.9737974530772370e+01
+best_mse["u_mean"] = 3.7038316285893714e+01
+best_mse["tke_mean"] = 1.4893837287794840e+01
+best_mse["temperature_mean"] = 1.6663829628240641e-05
+best_mse["thetal_mean"] = 1.7779259870199484e-05
+best_mse["Hvar_mean"] = 1.1587461976732782e+04
+best_mse["QTvar_mean"] = 7.3381590514601828e+02
 
 @testset "DYCOMS_RF01" begin
     println("Running DYCOMS_RF01...")

integration_tests/Rico.jl

@@ -11,19 +11,19 @@ include(joinpath("utils", "compute_mse.jl"))
 using .NameList
 
 best_mse = OrderedDict()
-best_mse["qt_mean"] = 4.2745465446436787e-01
-best_mse["updraft_area"] = 1.5810580213880007e+03
-best_mse["updraft_w"] = 3.0293830804824944e+02
-best_mse["updraft_qt"] = 1.8036840808532091e+01
-best_mse["updraft_thetal"] = 6.3565923109974378e+01
-best_mse["v_mean"] = 1.0637284782337001e+02
-best_mse["u_mean"] = 1.1444354015737491e+02
-best_mse["tke_mean"] = 8.6553999307149547e+02
-best_mse["temperature_mean"] = 1.2540517259642333e-04
-best_mse["ql_mean"] = 5.1325163153016852e+01
-best_mse["thetal_mean"] = 1.2561593164473264e-04
-best_mse["Hvar_mean"] = 1.4739277424672016e+03
-best_mse["QTvar_mean"] = 7.1366176286414179e+02
+best_mse["qt_mean"] = 4.3104248538733420e-01
+best_mse["updraft_area"] = 1.5789778929006447e+03
+best_mse["updraft_w"] = 2.9474627527892022e+02
+best_mse["updraft_qt"] = 1.7944807685758455e+01
+best_mse["updraft_thetal"] = 6.3569098888788886e+01
+best_mse["v_mean"] = 1.0627585162881577e+02
+best_mse["u_mean"] = 1.1431212367609878e+02
+best_mse["tke_mean"] = 8.8307805728796393e+02
+best_mse["temperature_mean"] = 1.2372854790132712e-04
+best_mse["ql_mean"] = 6.9240573720579249e+01
+best_mse["thetal_mean"] = 1.2362373538586256e-04
+best_mse["Hvar_mean"] = 1.5559806585826123e+03
+best_mse["QTvar_mean"] = 7.3615953416203286e+02
 
 @testset "Rico" begin
     println("Running Rico...")

integration_tests/TRMM_LBA.jl

@@ -14,19 +14,19 @@ using .NameList
 CLIMAParameters.Planet.T_freeze(::EarthParameterSet) = 100.0
 
 best_mse = OrderedDict()
-best_mse["qt_mean"] = 1.7995063250630168e+00
-best_mse["updraft_area"] = 3.1529411391564761e+04
-best_mse["updraft_w"] = 1.0325943376733990e+03
-best_mse["updraft_qt"] = 3.1156138180627952e+01
-best_mse["updraft_thetal"] = 1.1001893832675252e+02
-best_mse["v_mean"] = 2.9275592916609139e+02
-best_mse["u_mean"] = 1.6873153880206969e+03
-best_mse["tke_mean"] = 1.3627971247685127e+03
-best_mse["temperature_mean"] = 6.8597416865395539e-04
-best_mse["ql_mean"] = 1.0669889889408917e+03
-best_mse["thetal_mean"] = 8.1757856795585861e-03
-best_mse["Hvar_mean"] = 6.8922213953686887e+03
-best_mse["QTvar_mean"] = 2.5975685843697461e+03
+best_mse["qt_mean"] = 1.6060537595282474e+00
+best_mse["updraft_area"] = 2.4326719919423565e+04
+best_mse["updraft_w"] = 8.9781354744758698e+02
+best_mse["updraft_qt"] = 2.7840588043220112e+01
+best_mse["updraft_thetal"] = 1.1000857010242179e+02
+best_mse["v_mean"] = 2.9255417406952222e+02
+best_mse["u_mean"] = 1.6872488577305783e+03
+best_mse["tke_mean"] = 1.5447663031724076e+03
+best_mse["temperature_mean"] = 6.8027838562624771e-04
+best_mse["ql_mean"] = 9.5570328764405224e+02
+best_mse["thetal_mean"] = 8.1813107572739491e-03
+best_mse["Hvar_mean"] = 6.7055563584983674e+03
+best_mse["QTvar_mean"] = 2.6582568278775302e+03
 
 @testset "TRMM_LBA" begin
     println("Running TRMM_LBA...")

src/EDMF_Updrafts.jl

@@ -357,8 +357,6 @@ function buoyancy(
     extrap::Bool,
 )
 
-    qt = 0.0
-    h = 0.0
     grid = self.Gr
     kc_surf = kc_surface(grid)
 
@@ -395,11 +393,10 @@ function buoyancy(
                     UpdVar.B.values[i, k] = buoyancy_c(self.Ref.rho0_half[k], rho)
                     UpdVar.RH.values[i, k] = relative_humidity_c(self.Ref.p0_half[k], qt, qt - qv, 0.0, t)
                 elseif UpdVar.Area.values[i, k - 1] > 0.0 && k > kc_surf
-                    # TODO: report bug:
-                    # qt and h were not defined here before the function call.
+                    qt = UpdVar.QT.values[i,k-1]
+                    h  = UpdVar.H.values[i,k-1]
                     sa = eos(self.Ref.p0_half[k], qt, h)
-                    qt -= sa.ql
-                    qv = qt
+                    qv = qt - sa.ql
                     t = sa.T
                     rho = rho_c(self.Ref.p0_half[k], t, qt, qv)
                     UpdVar.B.values[i, k] = buoyancy_c(self.Ref.rho0_half[k], rho)