Update mse 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"] = 3.4761388491700224e-01
-best_mse["updraft_area"] = 1.9655632954763928e+03
-best_mse["updraft_w"] = 3.2377093752385053e+02
-best_mse["updraft_qt"] = 1.2452570404535185e+01
-best_mse["updraft_thetal"] = 2.7685659900036992e+01
-best_mse["u_mean"] = 8.7998547277817906e+01
-best_mse["tke_mean"] = 5.9501141635391093e+02
-best_mse["temperature_mean"] = 1.4210607813065063e-04
-best_mse["ql_mean"] = 2.1890556031513017e+02
-best_mse["thetal_mean"] = 1.3953340654098429e-04
-best_mse["Hvar_mean"] = 1.1148198912643536e+03
-best_mse["QTvar_mean"] = 3.0703058500395360e+02
+best_mse["qt_mean"] = 3.4297134939930601e-01
+best_mse["updraft_area"] = 1.9829008493073268e+03
+best_mse["updraft_w"] = 3.1072236638537851e+02
+best_mse["updraft_qt"] = 1.2698381273033208e+01
+best_mse["updraft_thetal"] = 2.7686390354792074e+01
+best_mse["u_mean"] = 8.7998547277817863e+01
+best_mse["tke_mean"] = 6.7319699431828644e+02
+best_mse["temperature_mean"] = 1.3960321509272764e-04
+best_mse["ql_mean"] = 2.9854035802671558e+02
+best_mse["thetal_mean"] = 1.4200441599983529e-04
+best_mse["Hvar_mean"] = 1.3755159256021079e+03
+best_mse["QTvar_mean"] = 2.6566877259844244e+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"] = 1.1068396401839847e-01
-best_mse["updraft_area"] = 7.2515940450436165e+02
-best_mse["updraft_w"] = 2.5856202193762641e+01
-best_mse["updraft_qt"] = 4.0061911576818243e+00
-best_mse["updraft_thetal"] = 2.1549386071253458e+01
-best_mse["v_mean"] = 6.5501952940732622e+01
-best_mse["u_mean"] = 5.3295928431425537e+01
-best_mse["tke_mean"] = 3.9582886707067345e+01
-best_mse["temperature_mean"] = 4.5842727523070819e-05
-best_mse["ql_mean"] = 6.5924727808279036e+00
-best_mse["thetal_mean"] = 4.6222694206747763e-05
-best_mse["Hvar_mean"] = 2.5900864672158934e+02
-best_mse["QTvar_mean"] = 4.6280994372607324e+01
+best_mse["qt_mean"] = 9.5080504754167433e-02
+best_mse["updraft_area"] = 7.2534663873051477e+02
+best_mse["updraft_w"] = 2.6358909128208378e+01
+best_mse["updraft_qt"] = 4.0334302720334296e+00
+best_mse["updraft_thetal"] = 2.1547995304586468e+01
+best_mse["v_mean"] = 6.5231550206742128e+01
+best_mse["u_mean"] = 5.3292889729286458e+01
+best_mse["tke_mean"] = 3.8860563196392924e+01
+best_mse["temperature_mean"] = 3.8436817065445734e-05
+best_mse["ql_mean"] = 3.7878522086312807e+00
+best_mse["thetal_mean"] = 3.9063754163395865e-05
+best_mse["Hvar_mean"] = 7.2639655951863034e+01
+best_mse["QTvar_mean"] = 2.2435640414468629e+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"] = 1.5987989288888820e-02
-best_mse["ql_mean"] = 5.9262500323990217e+00
-best_mse["updraft_area"] = 2.3887443639936907e+02
-best_mse["updraft_w"] = 4.3317426538007693e+00
-best_mse["updraft_qt"] = 1.1983341214387264e+00
-best_mse["updraft_thetal"] = 1.2739627177179765e+01
-best_mse["v_mean"] = 3.9736878190256498e+01
-best_mse["u_mean"] = 3.7037227839730683e+01
-best_mse["tke_mean"] = 1.4955295527017412e+01
-best_mse["temperature_mean"] = 1.6122517253407575e-05
-best_mse["thetal_mean"] = 1.7630642054888154e-05
-best_mse["Hvar_mean"] = 1.2452017842800817e+04
-best_mse["QTvar_mean"] = 7.6626218978684426e+02
+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
 
 @testset "DYCOMS_RF01" begin
     println("Running DYCOMS_RF01...")

integration_tests/GABLS.jl

@@ -12,14 +12,14 @@ using .NameList
 
 best_mse = OrderedDict()
 
-best_mse["updraft_thetal"] = 5.0248682056386063e+00
-best_mse["v_mean"] = 4.4635954562618867e+00
-best_mse["u_mean"] = 9.6412415987917157e+00
-best_mse["tke_mean"] = 2.4692059869443228e+00
-best_mse["temperature_mean"] = 8.8268614667882937e-06
-best_mse["thetal_mean"] = 8.7932314577535832e-06
-best_mse["Hvar_mean"] = 1.2890693335381430e+01
-best_mse["QTvar_mean"] = 4.4413913923170839e-01
+best_mse["updraft_thetal"] = 5.0248694008424222e+00
+best_mse["v_mean"] = 4.4630163253493214e+00
+best_mse["u_mean"] = 9.6412500983148846e+00
+best_mse["tke_mean"] = 2.4683562232142533e+00
+best_mse["temperature_mean"] = 8.8678308948818863e-06
+best_mse["thetal_mean"] = 8.7900622849842488e-06
+best_mse["Hvar_mean"] = 1.2891667586703637e+01
+best_mse["QTvar_mean"] = 4.4424755799649029e-01
 
 @testset "GABLS" begin
     println("Running GABLS...")

integration_tests/Nieuwstadt.jl

@@ -11,14 +11,14 @@ include(joinpath("utils", "compute_mse.jl"))
 using .NameList
 
 best_mse = OrderedDict()
-best_mse["updraft_area"] = 5.9103576007452034e+02
-best_mse["updraft_w"] = 2.6741082264407293e+01
-best_mse["updraft_thetal"] = 3.0475272117346940e+01
-best_mse["u_mean"] = 1.5245873874565478e+02
-best_mse["tke_mean"] = 7.3707728452173882e+01
-best_mse["temperature_mean"] = 1.2199914281992930e-05
-best_mse["thetal_mean"] = 1.2067109520894632e-05
-best_mse["Hvar_mean"] = 1.9140690462510639e+02
+best_mse["updraft_area"] = 5.9412545314262150e+02
+best_mse["updraft_w"] = 2.6952552348430249e+01
+best_mse["updraft_thetal"] = 3.0475271481866773e+01
+best_mse["u_mean"] = 1.5247657003047263e+02
+best_mse["tke_mean"] = 7.3600391357561151e+01
+best_mse["temperature_mean"] = 1.1971868506884125e-05
+best_mse["thetal_mean"] = 1.2117924470979204e-05
+best_mse["Hvar_mean"] = 1.8622261767371862e+02
 
 @testset "Nieuwstadt" begin
     println("Running Nieuwstadt...")

integration_tests/Rico.jl

@@ -11,19 +11,19 @@ include(joinpath("utils", "compute_mse.jl"))
 using .NameList
 
 best_mse = OrderedDict()
-best_mse["qt_mean"] = 4.2359420114784679e-01
-best_mse["updraft_area"] = 1.6722742675049749e+03
-best_mse["updraft_w"] = 2.8300484466673169e+02
-best_mse["updraft_qt"] = 1.7904453430368505e+01
-best_mse["updraft_thetal"] = 6.3573804437983789e+01
-best_mse["v_mean"] = 1.0634096403180666e+02
-best_mse["u_mean"] = 1.1434656097951681e+02
-best_mse["tke_mean"] = 8.6824438228445820e+02
-best_mse["temperature_mean"] = 1.2576042829475203e-04
-best_mse["ql_mean"] = 8.9402683009257942e+01
-best_mse["thetal_mean"] = 1.1896802334339157e-04
-best_mse["Hvar_mean"] = 2.0228054123757493e+03
-best_mse["QTvar_mean"] = 8.7748179858993274e+02
+best_mse["qt_mean"] = 4.2888329142054360e-01
+best_mse["updraft_area"] = 1.5804026921690113e+03
+best_mse["updraft_w"] = 3.0412249337738064e+02
+best_mse["updraft_qt"] = 1.8041619418228048e+01
+best_mse["updraft_thetal"] = 6.3565634303932690e+01
+best_mse["v_mean"] = 1.0637419570945200e+02
+best_mse["u_mean"] = 1.1444385357013196e+02
+best_mse["tke_mean"] = 8.6459012010773438e+02
+best_mse["temperature_mean"] = 1.2577596756983134e-04
+best_mse["ql_mean"] = 5.0938207504953844e+01
+best_mse["thetal_mean"] = 1.2604124901901089e-04
+best_mse["Hvar_mean"] = 1.4598483199237567e+03
+best_mse["QTvar_mean"] = 7.0850350571186209e+02
 
 @testset "Rico" begin
     println("Running Rico...")

integration_tests/Soares.jl

@@ -11,16 +11,16 @@ include(joinpath("utils", "compute_mse.jl"))
 using .NameList
 
 best_mse = OrderedDict()
-best_mse["qt_mean"] = 1.9338238625419904e-01
-best_mse["updraft_area"] = 4.8852467389339699e+02
-best_mse["updraft_w"] = 3.1250501928635639e+01
-best_mse["updraft_qt"] = 1.1136647539128006e+01
-best_mse["updraft_thetal"] = 2.2395194054335001e+01
-best_mse["u_mean"] = 7.2109940121868794e+02
-best_mse["tke_mean"] = 4.7919324815294324e+01
-best_mse["temperature_mean"] = 1.4374232147002715e-05
-best_mse["thetal_mean"] = 1.4379965874656967e-05
-best_mse["Hvar_mean"] = 2.3305425470797826e+02
+best_mse["qt_mean"] = 1.9368730351926020e-01
+best_mse["updraft_area"] = 4.8515130524256091e+02
+best_mse["updraft_w"] = 3.1260485555848359e+01
+best_mse["updraft_qt"] = 1.1137263871861222e+01
+best_mse["updraft_thetal"] = 2.2395183773350311e+01
+best_mse["u_mean"] = 7.2111916707127898e+02
+best_mse["tke_mean"] = 4.7882808390238374e+01
+best_mse["temperature_mean"] = 1.3818642271008120e-05
+best_mse["thetal_mean"] = 1.4383770217873919e-05
+best_mse["Hvar_mean"] = 2.3235278609470686e+02
 
 @testset "Soares" begin
     println("Running Soares...")

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"] = 1.7430285968163504e+00
-best_mse["updraft_area"] = 3.2545401197014067e+04
-best_mse["updraft_w"] = 9.2113782722003907e+02
-best_mse["updraft_qt"] = 3.0306781659879494e+01
-best_mse["updraft_thetal"] = 1.1108867837608678e+02
-best_mse["v_mean"] = 2.9291577336310036e+02
-best_mse["u_mean"] = 1.6874237352911189e+03
-best_mse["tke_mean"] = 1.5857027462501208e+03
-best_mse["temperature_mean"] = 6.3088676948654218e-04
-best_mse["ql_mean"] = 9.4722581733362244e+02
-best_mse["thetal_mean"] = 4.1952296308447006e-04
-best_mse["Hvar_mean"] = 8.1275664794363738e+03
-best_mse["QTvar_mean"] = 2.7043370821860535e+03
+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
 
 @testset "TRMM_LBA" begin
     println("Running TRMM_LBA...")