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Remove upper_bound from smooth_minimum
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@costachris
costachris committed Nov 10, 2023
1 parent 5714eea commit 5295fbb
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Showing 6 changed files with 134 additions and 139 deletions.
1 change: 0 additions & 1 deletion driver/generate_namelist.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -103,7 +103,6 @@ function default_namelist(
namelist_defaults["turbulence"]["EDMF_PrognosticTKE"]["Ri_crit"] = 0.25
namelist_defaults["turbulence"]["EDMF_PrognosticTKE"]["Lewis_number"] = 1.0
namelist_defaults["turbulence"]["EDMF_PrognosticTKE"]["smin_ub"] = 0.1
namelist_defaults["turbulence"]["EDMF_PrognosticTKE"]["smin_rm"] = 1.5
namelist_defaults["turbulence"]["EDMF_PrognosticTKE"]["l_max"] = 1.0e6
# entrainment
namelist_defaults["turbulence"]["EDMF_PrognosticTKE"]["entrainment_factor"] = 0.13
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260 changes: 130 additions & 130 deletions post_processing/mse_tables.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -5,165 +5,165 @@
all_best_mse = OrderedCollections.OrderedDict()
#
all_best_mse["ARM_SGP"] = OrderedCollections.OrderedDict()
all_best_mse["ARM_SGP"]["qt_mean"] = 0.2554721817619923
all_best_mse["ARM_SGP"]["updraft_area"] = 327.3474673266643
all_best_mse["ARM_SGP"]["updraft_w"] = 154.35344399818703
all_best_mse["ARM_SGP"]["updraft_qt"] = 30.150851900997715
all_best_mse["ARM_SGP"]["updraft_thetal"] = 172.01178075159103
all_best_mse["ARM_SGP"]["qt_mean"] = 0.2552463890767408
all_best_mse["ARM_SGP"]["updraft_area"] = 327.3520363312712
all_best_mse["ARM_SGP"]["updraft_w"] = 154.36957785345137
all_best_mse["ARM_SGP"]["updraft_qt"] = 30.61454320120155
all_best_mse["ARM_SGP"]["updraft_thetal"] = 172.0123422125184
all_best_mse["ARM_SGP"]["u_mean"] = 1.3235797273549681e-5
all_best_mse["ARM_SGP"]["tke_mean"] = 1104.6622152226375
all_best_mse["ARM_SGP"]["temperature_mean"] = 0.00012761739499360915
all_best_mse["ARM_SGP"]["ql_mean"] = 212.28215041954877
all_best_mse["ARM_SGP"]["tke_mean"] = 1104.669205982547
all_best_mse["ARM_SGP"]["temperature_mean"] = 0.00012756357403675883
all_best_mse["ARM_SGP"]["ql_mean"] = 212.1064083740767
all_best_mse["ARM_SGP"]["qi_mean"] = "NA"
all_best_mse["ARM_SGP"]["thetal_mean"] = 0.00011940508710793993
all_best_mse["ARM_SGP"]["Hvar_mean"] = 1449.5024867351578
all_best_mse["ARM_SGP"]["QTvar_mean"] = 992.5448118267991
all_best_mse["ARM_SGP"]["thetal_mean"] = 0.00011934280706982167
all_best_mse["ARM_SGP"]["Hvar_mean"] = 1639.1273022543226
all_best_mse["ARM_SGP"]["QTvar_mean"] = 894.4270510115464
#
all_best_mse["Bomex"] = OrderedCollections.OrderedDict()
all_best_mse["Bomex"]["qt_mean"] = 0.09745746285642798
all_best_mse["Bomex"]["updraft_area"] = 127.53035805846918
all_best_mse["Bomex"]["updraft_w"] = 17.60768883839848
all_best_mse["Bomex"]["updraft_qt"] = 6.88050204822434
all_best_mse["Bomex"]["updraft_thetal"] = 69.79162133589787
all_best_mse["Bomex"]["v_mean"] = 64.95579818778579
all_best_mse["Bomex"]["u_mean"] = 0.2658131989475454
all_best_mse["Bomex"]["tke_mean"] = 70.51114148771046
all_best_mse["Bomex"]["temperature_mean"] = 3.9300658049064214e-5
all_best_mse["Bomex"]["ql_mean"] = 8.256816467784288
all_best_mse["Bomex"]["qt_mean"] = 0.09739390729999153
all_best_mse["Bomex"]["updraft_area"] = 127.52486658438369
all_best_mse["Bomex"]["updraft_w"] = 17.600460504489188
all_best_mse["Bomex"]["updraft_qt"] = 6.874952845534643
all_best_mse["Bomex"]["updraft_thetal"] = 69.79142187577207
all_best_mse["Bomex"]["v_mean"] = 64.9563162432342
all_best_mse["Bomex"]["u_mean"] = 0.26581933718389134
all_best_mse["Bomex"]["tke_mean"] = 70.51469538441916
all_best_mse["Bomex"]["temperature_mean"] = 3.926286649960636e-5
all_best_mse["Bomex"]["ql_mean"] = 8.237082183571355
all_best_mse["Bomex"]["qi_mean"] = "NA"
all_best_mse["Bomex"]["thetal_mean"] = 3.990513801679012e-5
all_best_mse["Bomex"]["Hvar_mean"] = 2644.319895527311
all_best_mse["Bomex"]["QTvar_mean"] = 974.0942622784959
all_best_mse["Bomex"]["thetal_mean"] = 3.986607753531752e-5
all_best_mse["Bomex"]["Hvar_mean"] = 3047.497956802109
all_best_mse["Bomex"]["QTvar_mean"] = 1117.6728870383952
#
all_best_mse["DryBubble"] = OrderedCollections.OrderedDict()
all_best_mse["DryBubble"]["updraft_area"] = 2202.8250933477757
all_best_mse["DryBubble"]["updraft_w"] = 304.7580908095808
all_best_mse["DryBubble"]["updraft_thetal"] = 0.00012894543028699727
all_best_mse["DryBubble"]["u_mean"] = 1.0454684082524344
all_best_mse["DryBubble"]["tke_mean"] = 134.43949823258384
all_best_mse["DryBubble"]["temperature_mean"] = 4.668325460066637e-5
all_best_mse["DryBubble"]["thetal_mean"] = 4.2309956577682094e-5
all_best_mse["DryBubble"]["Hvar_mean"] = 121.33184191421392
all_best_mse["DryBubble"]["updraft_area"] = 4.6329380448915837e-5
all_best_mse["DryBubble"]["updraft_w"] = 0.00037381367465367816
all_best_mse["DryBubble"]["updraft_thetal"] = 5.200056656308287e-13
all_best_mse["DryBubble"]["u_mean"] = 1.7011568606656658e-9
all_best_mse["DryBubble"]["tke_mean"] = 8.79488719128737e-5
all_best_mse["DryBubble"]["temperature_mean"] = 2.6855797193846195e-14
all_best_mse["DryBubble"]["thetal_mean"] = 2.042988524531394e-14
all_best_mse["DryBubble"]["Hvar_mean"] = 3.869104151246155e-6
#
all_best_mse["DYCOMS_RF01"] = OrderedCollections.OrderedDict()
all_best_mse["DYCOMS_RF01"]["qt_mean"] = 0.03222926680876207
all_best_mse["DYCOMS_RF01"]["ql_mean"] = 35.24367550027249
all_best_mse["DYCOMS_RF01"]["updraft_area"] = 29.918284618025712
all_best_mse["DYCOMS_RF01"]["updraft_w"] = 6.115951158816949
all_best_mse["DYCOMS_RF01"]["updraft_qt"] = 1.8880856409405162
all_best_mse["DYCOMS_RF01"]["updraft_thetal"] = 46.18766521884522
all_best_mse["DYCOMS_RF01"]["v_mean"] = 0.010541287036688721
all_best_mse["DYCOMS_RF01"]["u_mean"] = 0.10339578819985162
all_best_mse["DYCOMS_RF01"]["tke_mean"] = 17.149948437020576
all_best_mse["DYCOMS_RF01"]["temperature_mean"] = 9.952426550825461e-5
all_best_mse["DYCOMS_RF01"]["thetal_mean"] = 9.87217703679611e-5
all_best_mse["DYCOMS_RF01"]["Hvar_mean"] = 1280.4368757021853
all_best_mse["DYCOMS_RF01"]["QTvar_mean"] = 514.6927662562823
all_best_mse["DYCOMS_RF01"]["qt_mean"] = 0.03222926628265145
all_best_mse["DYCOMS_RF01"]["ql_mean"] = 35.24367441898816
all_best_mse["DYCOMS_RF01"]["updraft_area"] = 29.91828462584687
all_best_mse["DYCOMS_RF01"]["updraft_w"] = 6.11595116920508
all_best_mse["DYCOMS_RF01"]["updraft_qt"] = 1.8880856499695946
all_best_mse["DYCOMS_RF01"]["updraft_thetal"] = 46.187665218886046
all_best_mse["DYCOMS_RF01"]["v_mean"] = 0.010541287021836489
all_best_mse["DYCOMS_RF01"]["u_mean"] = 0.10339578823912228
all_best_mse["DYCOMS_RF01"]["tke_mean"] = 17.149948550493168
all_best_mse["DYCOMS_RF01"]["temperature_mean"] = 9.952426281664225e-5
all_best_mse["DYCOMS_RF01"]["thetal_mean"] = 9.872176762671295e-5
all_best_mse["DYCOMS_RF01"]["Hvar_mean"] = 1280.4368757405791
all_best_mse["DYCOMS_RF01"]["QTvar_mean"] = 514.6927676054853
#
all_best_mse["DYCOMS_RF02"] = OrderedCollections.OrderedDict()
all_best_mse["DYCOMS_RF02"]["qt_mean"] = 0.05056588788630901
all_best_mse["DYCOMS_RF02"]["ql_mean"] = 6.336794509488111
all_best_mse["DYCOMS_RF02"]["qr_mean"] = 19.973054743673107
all_best_mse["DYCOMS_RF02"]["updraft_area"] = 29.012403773925637
all_best_mse["DYCOMS_RF02"]["updraft_w"] = 10.13593995461283
all_best_mse["DYCOMS_RF02"]["updraft_qt"] = 4.670129974866
all_best_mse["DYCOMS_RF02"]["updraft_thetal"] = 40.54533121433962
all_best_mse["DYCOMS_RF02"]["v_mean"] = 43.26165302656899
all_best_mse["DYCOMS_RF02"]["u_mean"] = 19.893678545593183
all_best_mse["DYCOMS_RF02"]["tke_mean"] = 11.426758746065664
all_best_mse["DYCOMS_RF02"]["temperature_mean"] = 2.2694092652791435e-5
all_best_mse["DYCOMS_RF02"]["thetal_mean"] = 1.8352469201567945e-5
all_best_mse["DYCOMS_RF02"]["Hvar_mean"] = 1181.3758938793158
all_best_mse["DYCOMS_RF02"]["QTvar_mean"] = 266.5254456011906
all_best_mse["DYCOMS_RF02"]["qt_mean"] = 0.05233788915003277
all_best_mse["DYCOMS_RF02"]["ql_mean"] = 6.697294177859994
all_best_mse["DYCOMS_RF02"]["qr_mean"] = 20.281931096948025
all_best_mse["DYCOMS_RF02"]["updraft_area"] = 29.027058046698794
all_best_mse["DYCOMS_RF02"]["updraft_w"] = 9.878615074729101
all_best_mse["DYCOMS_RF02"]["updraft_qt"] = 4.690371468923403
all_best_mse["DYCOMS_RF02"]["updraft_thetal"] = 40.545366095516705
all_best_mse["DYCOMS_RF02"]["v_mean"] = 43.26323125566431
all_best_mse["DYCOMS_RF02"]["u_mean"] = 19.893392920851007
all_best_mse["DYCOMS_RF02"]["tke_mean"] = 11.975979927159647
all_best_mse["DYCOMS_RF02"]["temperature_mean"] = 2.2777109899054987e-5
all_best_mse["DYCOMS_RF02"]["thetal_mean"] = 1.828111212362259e-5
all_best_mse["DYCOMS_RF02"]["Hvar_mean"] = 1188.6712169919972
all_best_mse["DYCOMS_RF02"]["QTvar_mean"] = 264.1835681681652
#
all_best_mse["GABLS"] = OrderedCollections.OrderedDict()
all_best_mse["GABLS"]["updraft_thetal"] = 1.4983854789511822e-6
all_best_mse["GABLS"]["v_mean"] = 0.3899297585151164
all_best_mse["GABLS"]["u_mean"] = 0.07380289139361627
all_best_mse["GABLS"]["tke_mean"] = 1.8637870901761218
all_best_mse["GABLS"]["temperature_mean"] = 1.497230498695485e-6
all_best_mse["GABLS"]["thetal_mean"] = 1.491759499481575e-6
all_best_mse["GABLS"]["Hvar_mean"] = 1.7279331290340516
all_best_mse["GABLS"]["updraft_thetal"] = 5.0057325456092485e-8
all_best_mse["GABLS"]["v_mean"] = 0.005407072149739587
all_best_mse["GABLS"]["u_mean"] = 0.000308425139051942
all_best_mse["GABLS"]["tke_mean"] = 0.01232102240971516
all_best_mse["GABLS"]["temperature_mean"] = 5.007168935021533e-8
all_best_mse["GABLS"]["thetal_mean"] = 5.0057325456092485e-8
all_best_mse["GABLS"]["Hvar_mean"] = 0.09340414179438572
#
all_best_mse["life_cycle_Tan2018"] = OrderedCollections.OrderedDict()
all_best_mse["life_cycle_Tan2018"]["qt_mean"] = 0.029018253530216122
all_best_mse["life_cycle_Tan2018"]["ql_mean"] = 11.727907691184644
all_best_mse["life_cycle_Tan2018"]["updraft_area"] = 2.4648809539928003
all_best_mse["life_cycle_Tan2018"]["updraft_w"] = 1.974848229608827
all_best_mse["life_cycle_Tan2018"]["updraft_qt"] = 0.17322716942005356
all_best_mse["life_cycle_Tan2018"]["updraft_thetal"] = 0.00010118042618016142
all_best_mse["life_cycle_Tan2018"]["v_mean"] = 0.5429696584751438
all_best_mse["life_cycle_Tan2018"]["u_mean"] = 0.003664749546168708
all_best_mse["life_cycle_Tan2018"]["tke_mean"] = 0.4550819605532687
all_best_mse["life_cycle_Tan2018"]["temperature_mean"] = 1.4623184540986606e-5
all_best_mse["life_cycle_Tan2018"]["thetal_mean"] = 1.4161709371758347e-5
all_best_mse["life_cycle_Tan2018"]["Hvar_mean"] = 1295.718719387864
all_best_mse["life_cycle_Tan2018"]["QTvar_mean"] = 464.46621701576004
all_best_mse["life_cycle_Tan2018"]["qt_mean"] = 2.1980099071504733e-6
all_best_mse["life_cycle_Tan2018"]["ql_mean"] = 0.007720864286987472
all_best_mse["life_cycle_Tan2018"]["updraft_area"] = 0.003533017591198568
all_best_mse["life_cycle_Tan2018"]["updraft_w"] = 0.005830504321530831
all_best_mse["life_cycle_Tan2018"]["updraft_qt"] = 0.002239096166327306
all_best_mse["life_cycle_Tan2018"]["updraft_thetal"] = 1.2775945212521939e-6
all_best_mse["life_cycle_Tan2018"]["v_mean"] = 0.00012527220315071
all_best_mse["life_cycle_Tan2018"]["u_mean"] = 2.838533918504724e-7
all_best_mse["life_cycle_Tan2018"]["tke_mean"] = 0.000367555656715684
all_best_mse["life_cycle_Tan2018"]["temperature_mean"] = 5.085403105269906e-10
all_best_mse["life_cycle_Tan2018"]["thetal_mean"] = 5.269388688258327e-10
all_best_mse["life_cycle_Tan2018"]["Hvar_mean"] = 159.43305140611452
all_best_mse["life_cycle_Tan2018"]["QTvar_mean"] = 72.86468810491557
#
all_best_mse["Nieuwstadt"] = OrderedCollections.OrderedDict()
all_best_mse["Nieuwstadt"]["updraft_area"] = 98.84436806524585
all_best_mse["Nieuwstadt"]["updraft_w"] = 14.186333903874987
all_best_mse["Nieuwstadt"]["updraft_thetal"] = 117.60593866095171
all_best_mse["Nieuwstadt"]["u_mean"] = 13.55346827865441
all_best_mse["Nieuwstadt"]["tke_mean"] = 283.62147778030925
all_best_mse["Nieuwstadt"]["temperature_mean"] = 1.1367382778385116e-5
all_best_mse["Nieuwstadt"]["thetal_mean"] = 1.1155407047485008e-5
all_best_mse["Nieuwstadt"]["Hvar_mean"] = 718.0186300173174
all_best_mse["Nieuwstadt"]["updraft_area"] = 98.80140636900379
all_best_mse["Nieuwstadt"]["updraft_w"] = 14.173869320877497
all_best_mse["Nieuwstadt"]["updraft_thetal"] = 117.60593923755371
all_best_mse["Nieuwstadt"]["u_mean"] = 13.55387743355792
all_best_mse["Nieuwstadt"]["tke_mean"] = 283.65725551447355
all_best_mse["Nieuwstadt"]["temperature_mean"] = 1.1363361194923952e-5
all_best_mse["Nieuwstadt"]["thetal_mean"] = 1.1151563794475668e-5
all_best_mse["Nieuwstadt"]["Hvar_mean"] = 718.0543948198399
#
all_best_mse["Rico"] = OrderedCollections.OrderedDict()
all_best_mse["Rico"]["qt_mean"] = 1.1412157988433447
all_best_mse["Rico"]["updraft_area"] = 479.6068859296478
all_best_mse["Rico"]["updraft_w"] = 82.71757535256751
all_best_mse["Rico"]["updraft_qt"] = 17.17250792059662
all_best_mse["Rico"]["updraft_thetal"] = 133.87359710199806
all_best_mse["Rico"]["v_mean"] = 0.5117244529755463
all_best_mse["Rico"]["u_mean"] = 0.42436510433163455
all_best_mse["Rico"]["tke_mean"] = 155.97544483542237
all_best_mse["Rico"]["temperature_mean"] = 0.0005439954218722927
all_best_mse["Rico"]["ql_mean"] = 29244.599889781333
all_best_mse["Rico"]["qt_mean"] = 1.135326031628782
all_best_mse["Rico"]["updraft_area"] = 479.44450709772644
all_best_mse["Rico"]["updraft_w"] = 82.9293746327154
all_best_mse["Rico"]["updraft_qt"] = 17.238873618857568
all_best_mse["Rico"]["updraft_thetal"] = 133.87379116769426
all_best_mse["Rico"]["v_mean"] = 0.5144924022690499
all_best_mse["Rico"]["u_mean"] = 0.421100716597955
all_best_mse["Rico"]["tke_mean"] = 155.81504934027012
all_best_mse["Rico"]["temperature_mean"] = 0.0005444683250475638
all_best_mse["Rico"]["ql_mean"] = 28324.553421041834
all_best_mse["Rico"]["qi_mean"] = "NA"
all_best_mse["Rico"]["qr_mean"] = 668.9618659601628
all_best_mse["Rico"]["thetal_mean"] = 0.0005780905983636465
all_best_mse["Rico"]["Hvar_mean"] = 161362.1964521471
all_best_mse["Rico"]["QTvar_mean"] = 36505.695563858135
all_best_mse["Rico"]["qr_mean"] = 670.3960900621912
all_best_mse["Rico"]["thetal_mean"] = 0.0005771832405292491
all_best_mse["Rico"]["Hvar_mean"] = 154085.2917284029
all_best_mse["Rico"]["QTvar_mean"] = 34840.39704458511
#
all_best_mse["Soares"] = OrderedCollections.OrderedDict()
all_best_mse["Soares"]["qt_mean"] = 0.142219443200093
all_best_mse["Soares"]["updraft_area"] = 94.2923097607967
all_best_mse["Soares"]["updraft_w"] = 13.04176107775075
all_best_mse["Soares"]["updraft_qt"] = 23.63463116471562
all_best_mse["Soares"]["updraft_thetal"] = 65.72137555604021
all_best_mse["Soares"]["u_mean"] = 93.90032780776161
all_best_mse["Soares"]["tke_mean"] = 216.82379097833908
all_best_mse["Soares"]["temperature_mean"] = 1.3127136322547566e-5
all_best_mse["Soares"]["thetal_mean"] = 1.2051608872189155e-5
all_best_mse["Soares"]["Hvar_mean"] = 679.1402581405645
all_best_mse["Soares"]["qt_mean"] = 0.14292527789723997
all_best_mse["Soares"]["updraft_area"] = 94.35222363436445
all_best_mse["Soares"]["updraft_w"] = 13.065908605313801
all_best_mse["Soares"]["updraft_qt"] = 23.639209142240095
all_best_mse["Soares"]["updraft_thetal"] = 65.72137520255045
all_best_mse["Soares"]["u_mean"] = 93.8971313259509
all_best_mse["Soares"]["tke_mean"] = 216.61325540883917
all_best_mse["Soares"]["temperature_mean"] = 1.3148802683589108e-5
all_best_mse["Soares"]["thetal_mean"] = 1.2072841930884616e-5
all_best_mse["Soares"]["Hvar_mean"] = 680.5458129832058
#
all_best_mse["TRMM_LBA"] = OrderedCollections.OrderedDict()
all_best_mse["TRMM_LBA"]["qt_mean"] = 2.140748311962583
all_best_mse["TRMM_LBA"]["updraft_area"] = 1254.2030362859591
all_best_mse["TRMM_LBA"]["updraft_w"] = 9839.438196474672
all_best_mse["TRMM_LBA"]["updraft_qt"] = 263.65651738219054
all_best_mse["TRMM_LBA"]["updraft_thetal"] = 541.3706668645273
all_best_mse["TRMM_LBA"]["v_mean"] = 71.06040567071743
all_best_mse["TRMM_LBA"]["u_mean"] = 30.399741077951205
all_best_mse["TRMM_LBA"]["tke_mean"] = 48605.30323834375
all_best_mse["TRMM_LBA"]["temperature_mean"] = 0.0005688898055651253
all_best_mse["TRMM_LBA"]["ql_mean"] = 248042.12631836807
all_best_mse["TRMM_LBA"]["qt_mean"] = 2.1442449884684387
all_best_mse["TRMM_LBA"]["updraft_area"] = 1254.0204932517388
all_best_mse["TRMM_LBA"]["updraft_w"] = 9840.030762797738
all_best_mse["TRMM_LBA"]["updraft_qt"] = 263.6487773314778
all_best_mse["TRMM_LBA"]["updraft_thetal"] = 541.3714404624005
all_best_mse["TRMM_LBA"]["v_mean"] = 71.08717681449379
all_best_mse["TRMM_LBA"]["u_mean"] = 30.401331899246482
all_best_mse["TRMM_LBA"]["tke_mean"] = 48667.31593951556
all_best_mse["TRMM_LBA"]["temperature_mean"] = 0.0005684346487320295
all_best_mse["TRMM_LBA"]["ql_mean"] = 248342.16732818636
all_best_mse["TRMM_LBA"]["qi_mean"] = "NA"
all_best_mse["TRMM_LBA"]["qr_mean"] = "NA"
all_best_mse["TRMM_LBA"]["qs_mean"] = "NA"
all_best_mse["TRMM_LBA"]["thetal_mean"] = 0.0005009943307719285
all_best_mse["TRMM_LBA"]["Hvar_mean"] = 446334.5543949141
all_best_mse["TRMM_LBA"]["QTvar_mean"] = 6279.991116973818
all_best_mse["TRMM_LBA"]["thetal_mean"] = 0.0005004674375363604
all_best_mse["TRMM_LBA"]["Hvar_mean"] = 447022.7713463382
all_best_mse["TRMM_LBA"]["QTvar_mean"] = 6288.665467442509
#
all_best_mse["LES_driven_SCM"] = OrderedCollections.OrderedDict()
all_best_mse["LES_driven_SCM"]["qt_mean"] = 0.1809994648114718
all_best_mse["LES_driven_SCM"]["v_mean"] = 0.3230961648090686
all_best_mse["LES_driven_SCM"]["u_mean"] = 0.07553927533768831
all_best_mse["LES_driven_SCM"]["temperature_mean"] = 5.4877160276794674e-5
all_best_mse["LES_driven_SCM"]["ql_mean"] = 27438.0665544269
all_best_mse["LES_driven_SCM"]["thetal_mean"] = 5.979480643194291e-5
all_best_mse["LES_driven_SCM"]["qt_mean"] = 0.1542447335052964
all_best_mse["LES_driven_SCM"]["v_mean"] = 0.32696315559512423
all_best_mse["LES_driven_SCM"]["u_mean"] = 0.0769025499324574
all_best_mse["LES_driven_SCM"]["temperature_mean"] = 5.7834193462998045e-5
all_best_mse["LES_driven_SCM"]["ql_mean"] = 18320.242710110357
all_best_mse["LES_driven_SCM"]["thetal_mean"] = 5.255557008915138e-5
#
#################################
#################################
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2 changes: 1 addition & 1 deletion src/closures/entr_detr.jl
View file
Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@ function compute_inverse_timescale(εδ_model, b_up::FT, b_en::FT, w_up::FT, w_e
l_1 = c_λ * abs(Δb / (sqrt(abs(tke)) + eps(FT)))
l_2 = abs(Δb / Δw)
l = SA.SVector(l_1, l_2)
return lamb_smooth_minimum(l, FT(0.1), FT(0.0005))
return lamb_smooth_minimum(l, FT(0.1))
end

function get_Δw(εδ_model, w_up::FT, w_en::FT) where {FT}
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3 changes: 1 addition & 2 deletions src/closures/mixing_length.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,6 @@ function mixing_length(mix_len_params, param_set, ml_model::MinDisspLen{FT}) whe
c_m = mix_len_params.c_m
c_d = mix_len_params.c_d
smin_ub = mix_len_params.smin_ub
smin_rm = mix_len_params.smin_rm
l_max = mix_len_params.l_max
c_b = mix_len_params.c_b
g::FT = TCP.grav(param_set)
Expand Down Expand Up @@ -55,7 +54,7 @@ function mixing_length(mix_len_params, param_set, ml_model::MinDisspLen{FT}) whe

# get soft minimum
min_len, min_len_ind = findmin(l)
mix_len = lamb_smooth_minimum(l, smin_ub, smin_rm)
mix_len = lamb_smooth_minimum(l, smin_ub)
ml_ratio = mix_len / min_len
return MixLen(min_len_ind, mix_len, ml_ratio)
end
3 changes: 0 additions & 3 deletions src/types.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -215,7 +215,6 @@ Base.@kwdef struct MixingLengthParams{FT}
Ri_c::FT # critical Richardson number
Le::FT # Lewis number
smin_ub::FT # lower limit for smin function
smin_rm::FT # upper ratio limit for smin function
l_max::FT
end

Expand Down Expand Up @@ -620,7 +619,6 @@ function EDMFModel(::Type{FT}, namelist, precip_model, rain_formation_model) whe
β_lim = parse_namelist(namelist, "turbulence", "EDMF_PrognosticTKE", "area_limiter_power")
c_γ = parse_namelist(namelist, "turbulence", "EDMF_PrognosticTKE", "turbulent_entrainment_factor")
c_δ = parse_namelist(namelist, "turbulence", "EDMF_PrognosticTKE", "detrainment_factor")
smin_rm = parse_namelist(namelist, "turbulence", "EDMF_PrognosticTKE", "smin_rm")
Π_norm = parse_namelist(namelist, "turbulence", "EDMF_PrognosticTKE", "pi_norm_consts")
Π_norm = SA.SVector{length(Π_norm), FT}(Π_norm)

Expand Down Expand Up @@ -714,7 +712,6 @@ function EDMFModel(::Type{FT}, namelist, precip_model, rain_formation_model) whe
Ri_c = parse_namelist(namelist, "turbulence", "EDMF_PrognosticTKE", "Ri_crit"),
Le = parse_namelist(namelist, "turbulence", "EDMF_PrognosticTKE", "Lewis_number"; default = 1.0),
smin_ub = parse_namelist(namelist, "turbulence", "EDMF_PrognosticTKE", "smin_ub"),
smin_rm = smin_rm,
l_max = parse_namelist(namelist, "turbulence", "EDMF_PrognosticTKE", "l_max"; default = 1.0e6),
)

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