CORRECTABLE CORRECTABLE BC-ERRORS BC-ERRORS WITHIN MESO-MET MODELSWITHIN MESO-MET MODELS

R. BornsteinR. Bornstein

San Jose State UniversitySan Jose State University

San Jose, CASan Jose, CApblmodel@hotmail.com

Presented atPresented at86th AMS Annual Meeting, Atlanta, GA86th AMS Annual Meeting, Atlanta, GA

30 January 200630 January 2006

AcknowledgementsAcknowledgements H. Taha, Altostratus & SJSUH. Taha, Altostratus & SJSU D. Hitchock & P. Smith, D. Hitchock & P. Smith, State of TexasState of Texas D. Byun, D. Byun, U. of HoustonU. of Houston J. Ching & S. Dupont, US EPAJ. Ching & S. Dupont, US EPA S. Stetson, SWS Inc.S. Stetson, SWS Inc. S. Burian, U. of UtahS. Burian, U. of Utah D. Nowak, USFSD. Nowak, USFS Funded by:Funded by: NSF, USAID, DHS, LBL, LMMS, NSF, USAID, DHS, LBL, LMMS,

NASANASA MY M.S.MY M.S. (ex)(ex) STUDENTS:STUDENTS: J. Cheng, C. Lozej, J. Cheng, C. Lozej,

F. Freedman, T. Ghidey, K. Craig,F. Freedman, T. Ghidey, K. Craig, S. S. Kasakseh, R. Balmori Kasakseh, R. Balmori

OUTLINEOUTLINE

INTRODUCTIONINTRODUCTION SYNOPTIC FORCINGSYNOPTIC FORCING POORLY (AT BEST) KNOWN POORLY (AT BEST) KNOWN INPUT DATAINPUT DATA

DEEP SOIL TEMP IC/C DEEP SOIL TEMP IC/C SOIL MOISTURE ICSOIL MOISTURE IC SST IC/BCSST IC/BC

SFC/PBL FORCINGSFC/PBL FORCING NON-URBAN NON-URBAN URBANURBAN

CONCLUSIONCONCLUSION

Theme of Talk:Theme of Talk:MESO-MET ATM-MODELS MUST CAPTURE MESO-MET ATM-MODELS MUST CAPTURE B.C. FORCINGS IN B.C. FORCINGS IN CORRECT ORDERCORRECT ORDER (1 of (1 of

2)2)e.g., AN Oe.g., AN O33 EPISODES OCCURS ON A GIVEN DAY: EPISODES OCCURS ON A GIVEN DAY: NOT NOT FROM CHANGING: TOPOGRAPHY & EMISSIONSFROM CHANGING: TOPOGRAPHY & EMISSIONS

BUTBUT DUE TO CHANGING (UPPER-LEVEL &/OR SFC)DUE TO CHANGING (UPPER-LEVEL &/OR SFC)

GC/SYNOPTIC PRESSURE-GC/SYNOPTIC PRESSURE-PATTERNS, PATTERNS, WHICH WHICH ENTER OUR MESO-SOLUTIONSENTER OUR MESO-SOLUTIONS FROM EITHER FROM EITHER

CORRECT OR IMPRECISE CORRECT OR IMPRECISE LARGER-SCALE MODEL-LARGER-SCALE MODEL-VALUES & WHICH VALUES & WHICH

THUS ALLOWTHUS ALLOW SCF MESO THERMAL-FORCINGS SCF MESO THERMAL-FORCINGS (i.e., (i.e., UP/DOWN SLOPE, LAND/SEA, URBAN, CLOUDS/FOG) UP/DOWN SLOPE, LAND/SEA, URBAN, CLOUDS/FOG) TO DEVELOP TO DEVELOP CORRECTLY OR INCORRECTLYCORRECTLY OR INCORRECTLY

CORRECT ORDER CORRECT ORDER (2 of 2)(2 of 2)

MUST THUS MUST THUS CORRECTLY CORRECTLY REPRODUCE:REPRODUCE: UPPER-LEVEL Syn/GC FORCING UPPER-LEVEL Syn/GC FORCING FIRST FIRST

pressurepressure (the GC/Syn driver), which (the GC/Syn driver), which produces Syn/GC windsproduces Syn/GC winds

TOPOGRAPHY TOPOGRAPHY NEXTNEXTgrid spacinggrid spacing flow-channeling flow-channeling

MESO SFC-CONDITIONS MESO SFC-CONDITIONS LASTLASTtemptemp (the meso-driver) & sfc (the meso-driver) & sfc

roughness roughness Meso-windsMeso-winds

Correct GC/Synoptic forcingCorrect GC/Synoptic forcing

Methodology:Methodology: Check large-scale forcingCheck large-scale forcing before before simulations:simulations:

NWS charts vs. large-scale model input-fieldsNWS charts vs. large-scale model input-fields If correct If correct use use analysis-nudginganalysis-nudging FDDA FDDA

correct correct synoptic-trendssynoptic-trends Case studies:Case studies:

SFBA Winter SFBA Winter synoptic-storm synoptic-storm (Lozej 1996)(Lozej 1996) Atlanta Atlanta urban-thunderstormurban-thunderstorm (Craig 2000) (Craig 2000) OzoneOzone-episodes -episodes

LA (Boucouvala et al. 2003) LA (Boucouvala et al. 2003) SFBA (Ghidey 2005)SFBA (Ghidey 2005)

1996 SFBA Winter-Storm 1996 SFBA Winter-Storm (Lozej)(Lozej)

Obs stormObs storm went over SFBA went over SFBA Wrong input large-scale IC/BCWrong input large-scale IC/BC caused storm caused storm

toto move too zonally and thus too fastmove too zonally and thus too fast pass (and precipitate) too far northpass (and precipitate) too far north

Note: Note: IC/BC more important for IC/BC more important for synopticsynoptic storms than for storms than for mesomeso-systems (they are -systems (they are driven by surface-conditions)driven by surface-conditions)

Obs and MM5:Obs and MM5: next next 3 3 slidesslides

GOES IR & SFC NWS 12 March, 12 UTC:Storm over SFBA

SFBA

SFBA

NCEP(2.50)/MM5 (27 km) (solid blue) & ETA (dash pink) 500 mb heights (dam) at 12 UTC Left: slight IC/BC errors in NCEP

ETA: digs deeper vsNCEP/MM5: more zonal

Right: storm goes too far N of SFBA & moves too quickly

11 March

12 March

L

L

MM5 (upper) 3 hr precip maxis thus N of observed precip (lower) max (at 50-km S of SFBA)

SFBA

Atlanta Summer Thunderstorm Atlanta Summer Thunderstorm (Craig)(Craig)

Obs: Obs: weak-cold front N of Atlantaweak-cold front N of Atlanta Large-scale IC/BC:Large-scale IC/BC: front S of city front S of city MM5 UHI-induced thunderstorm:MM5 UHI-induced thunderstorm: 5-km 5-km

deep, wdeep, wmaxmax 6-m/s, 8-cm precip 6-m/s, 8-cm precip Should be:Should be: 9-km, 12-m/s, 14-cm 9-km, 12-m/s, 14-cm Source of problem:Source of problem:

MM5-storm formed in MM5-storm formed in stable-flow stable-flow from N & not in from N & not in unstable-flowunstable-flow from Sfrom S

Data & MM5 results:Data & MM5 results: next slide next slide

ATLANTA UHI-INITIATED STORM: OBS SAT & PRECIP (UPPER) & MM5 W & PRECIP (LOWER)

LA Summer OLA Summer O33-episode -episode (Boucouvula)(Boucouvula) Obs of large scale IC/BC:Obs of large scale IC/BC:

Shift of Shift of meso-700 hPa highmeso-700 hPa high

upper-level upper-level flow from Nflow from N

NW-moving NW-moving sea-breezesea-breeze & max-O & max-O33

was blocked by sfc-flow from Nwas blocked by sfc-flow from N stayed in San Fernando Valleystayed in San Fernando Valley

MM5:MM5: analysis nudging analysis nudging

got front and Ogot front and O33 right right (next slide) (next slide)

Upper: analysis nudging MM5 sea-breeze front (blue line) & O3-max blocked from passing to-N b/t 2 Mts by strong opposing N-S large-scale flow (as in obs)

Mt

Mt

Lower:no analysis nudging MM5 sea-breeze front & O3-max not blocked from pass-ing to North b/t 2 Mts, as N-S opposing large-scaleflow is weak

MtMt

SFBA Summer SFBA Summer OO33--episode episode ((Ghidey)) Obs: daily Obs: daily max- Omax- O33 sequentially moved from sequentially moved from

Livermore to Sacramento to SJVLivermore to Sacramento to SJV Large scale IC/BC:Large scale IC/BC:

Shifting Shifting meos-700 hPameos-700 hPa high high

shifting shifting meos-sfc lowmeos-sfc low changing sfc-flow changing sfc-flow

max-Omax-O33 changed location changed location MM5 (next 2 slides):MM5 (next 2 slides):

good good analysis-nudginganalysis-nudging good sfc-wind good sfc-wind

H

H

L

SAC episode day:SAC episode day: D-1 700 hPa Syn H moved to Utah with coastal “bulge” & L D-1 700 hPa Syn H moved to Utah with coastal “bulge” & L in S-Calin S-Calcorrect SW correct SW flow from SFBA to Sacflow from SFBA to Sac

L

H

SJV episode day:SJV episode day: D-3 700 hPa Fresno eddy moved N & H moves D-3 700 hPa Fresno eddy moved N & H moves inlandinland flow around eddy blocks SFBA flow to SAC, but forces it S into SJVflow around eddy blocks SFBA flow to SAC, but forces it S into SJV

Topographic-Channeling Topographic-Channeling (J. (J. Cheng)Cheng)

Horiz grid-spacing too-large Horiz grid-spacing too-large Mt-passes not resolved Mt-passes not resolved

flow-flow-directiondirection is wrong is wrong Mt-passes are too wide Mt-passes are too wide

speedsspeeds underestimated underestimated Solution: Solution:

decrease-spacing until wdecrease-spacing until wmax max is is unchangedunchanged

Case study (not shown): Case study (not shown): SFBA Richmond toxic-spillSFBA Richmond toxic-spill

MM5 MM5 Non-urbanNon-urban Sfc-IC/BC Issues Sfc-IC/BC Issues Deep-soil temp: BCDeep-soil temp: BC

Controls min-TControls min-T Values unknown & MM5-estimation is Values unknown & MM5-estimation is flawedflawed

Soil-moisture: ICSoil-moisture: IC Controls max-TControls max-T Values unknown & MM5-table values Values unknown & MM5-table values too specifictoo specific

SST: IC/BCSST: IC/BC Horiz coastal T-Horiz coastal T-gradgrad controls sea-breeze flow controls sea-breeze flow We usually focus only on We usually focus only on land-sfcland-sfc temptemp IC/BC SST values from IC/BC SST values from large-scale modellarge-scale model

too too coarse & not f(t) coarse & not f(t)

Summary for MM5:Summary for MM5: deep soil deep soil temptemp

Calculated as Calculated as average large-scale model average large-scale model inputinput surface-Tsurface-T during simulation-period during simulation-period

This assumes a This assumes a zero time-lagzero time-lag b/t sfc and b/t sfc and lower-level (about 1 m) soil-tempslower-level (about 1 m) soil-temps

But obs show But obs show 2-3 month time-lag b/t these 2 temps2-3 month time-lag b/t these 2 temps Larger-lag in low-conductivity dry-soilsLarger-lag in low-conductivity dry-soils

Thus MM5 min-temps will always be too-Thus MM5 min-temps will always be too-high in high in summersummer and too-low in and too-low in winterwinter

We need to We need to develop techdevelop tech (beyond current (beyond current trial and error) to account for lag: trial and error) to account for lag: next 2 next 2 slidesslides

Mid-east Obs vs. MM5: 2 m tempMid-east Obs vs. MM5: 2 m temp (Kasakech ’06 (Kasakech ’06 AMS)AMS)

July 29 August 1 August 2

July 31 Aug 1 Aug2

Standard-MM5 summer night-time min-T,

But lower input deep-soil temp better 2-m T results better winds better O3

obs

Run 1

MM5:Run 4

Obs

Run 4:ReducedSeep-soil T

First 2 days show GC/Syn trend not in MM5, as MM5-runs had no analysis nudging

SCOS96SCOS96 LA Temps (Boucouvual et LA Temps (Boucouvual et al.)al.)

RUN 1: hasNo GC warming trendWrong max and min T

3-Aug 4-Aug 5-Aug 6-Aug

RUN 5: corrected, as it used> Analysis nudging > Reduced deep-soil T

MM5 input-table values:MM5 input-table values: zz0

problemsproblems WaterWater z z0 = 0.01 cm = 0.01 cm

Only IC Only IC updatedupdated internally by eq = f(MM5 u internally by eq = f(MM5 u*)) But Eq only valid for But Eq only valid for open-seaopen-sea smooth-swell conditions smooth-swell conditions Observed values for rough-sea Observed values for rough-sea coastal-areascoastal-areas ~ 1 cm ~ 1 cm

MM5 coastal-winds are MM5 coastal-winds are over-estimatedover-estimated

UrbanUrban z z0 = 80 cm = 80 cm too low for tall cities: obs up to too low for tall cities: obs up to 3-4 m3-4 m Urban-winds: Urban-winds: too fasttoo fast Must Must adjustadjust input value or input GIS/RS f(x,y) input value or input GIS/RS f(x,y)

See See next 2 slidesnext 2 slides

25-MM5 category (USGS) vegetation categories

and physical parameters

VegetationVegetationIntegerIntegerIdentificationIdentification

VegetationVegetationDescriptionDescription

Albedo(%)Albedo(%) MoistureMoistureAvail. (%)Avail. (%)

EmissivityEmissivity(% at 9 μ m)(% at 9 μ m)

RoughnessRoughnessLength (cm)Length (cm)

Thermal InertiaThermal Inertia(cal cm-2 k-1 s-1/2)(cal cm-2 k-1 s-1/2)

Sum Sum WinWin SumSum WinWin SumSum WinWin SumSum WinWin SumSum WinWin

11 UrbanUrban 1515 1515 1010 1010 8888 8888 8080 8080 0.030.03 0.030.03

22 Drylnd Crop. Past.Drylnd Crop. Past. 1717 2323 3030 6060 98.598.5 9292 1515 55 0.040.04 0.040.04

33 Irrg. Crop. Past.Irrg. Crop. Past. 1818 2323 5050 5050 98.598.5 9292 1515 55 0.040.04 0.040.04

44 Mix. Dry/Irrg.C.P.Mix. Dry/Irrg.C.P. 1818 2323 2525 5050 98.598.5 9292 1515 55 0.040.04 0.040.04

55 Crop./Grs. MosaicCrop./Grs. Mosaic 1818 2323 2525 4040 9999 9292 1414 55 0.040.04 0.040.04

66 Crop./Wood MoscCrop./Wood Mosc 1616 2020 3535 6060 98.598.5 9393 2020 2020 0.040.04 0.040.04

77 GrasslandGrassland 1919 2323 1515 3030 98.598.5 9292 1212 1010 0.030.03 0.040.04

88 ShrublandShrubland 2222 2525 1010 2020 8888 8888 1010 1010 0.030.03 0.040.04

99 Mix Shrb./Grs.Mix Shrb./Grs. 2020 2424 1515 2525 9090 9090 1111 1010 0.030.03 0.040.04

1010 SavannaSavanna 2020 2020 1515 1515 9292 9292 1515 1515 0.030.03 0.030.03

1111 Decids. Broadlf.Decids. Broadlf. 1616 1717 3030 6060 9393 9393 5050 5050 0.040.04 0.050.05

1212 Decids. Needlf.Decids. Needlf. 1414 1515 3030 6060 9494 9393 5050 5050 0.040.04 0.050.05

1313 Evergrn. Braodlf.Evergrn. Braodlf. 1212 1212 5050 5050 9595 9595 5050 5050 0.050.05 0.050.05

1414 Evergrn. Needlf.Evergrn. Needlf. 1212 1212 3030 6060 9595 9595 5050 5050 0.040.04 0.050.05

1515 Mixed ForestMixed Forest 1313 1414 3030 6060 9494 9494 5050 5050 0.040.04 0.060.06

1616 Water BodiesWater Bodies 88 88 100100 100100 9898 9898 .01.01 .01.01 0.060.06 0.060.06

1717 Herb. WetlandHerb. Wetland 1414 1414 6060 7575 9595 9595 2020 2020 0.060.06 0.060.06

1818 Wooded wetlandWooded wetland 1414 1414 3535 7070 9595 9595 4040 4040 0.050.05 0.060.06

1919 Bar. Sparse Veg.Bar. Sparse Veg. 2525 2525 22 55 8585 8585 1010 1010 0.020.02 0.020.02

2020 Herb. TundraHerb. Tundra 1515 6060 5050 9090 9292 9292 1010 1010 0.050.05 0.050.05

2121 Wooden TundraWooden Tundra 1515 5050 5050 9090 9393 9393 3030 3030 0.050.05 0.050.05

2222 Mixed TundraMixed Tundra 15 15 5555 5050 9090 9292 9292 1515 1515 0.050.05 0.050.05

2323 Bare Grnd. Bare Grnd. TundraTundra 2525 7070 22 9595 8585 9595 1010 55 0.020.02 0.050.05

2424 Snow or IceSnow or Ice 5555 7070 9595 9595 9595 9595 55 55 0.050.05 0.050.05

2525 No dataNo data                              

S. Stetson: Houston GIS/RS zS. Stetson: Houston GIS/RS zoo input input

Values up 3 m

Importance of:Importance of: detailed SST as f(x,y,t)detailed SST as f(x,y,t)

TheoryTheoryAlong-shore winds Along-shore winds off-shore off-shore EkmanEkman ocean-transport ocean-transport cold-water cold-water upwellingupwelling atm & ocean atm & ocean cold-core Lowscold-core Lows altered atm altered atm pollutant-transport pollutant-transport

*Need:*Need: detailed satellite SST-input detailed satellite SST-input Case studies:Case studies: see next 4 slides see next 4 slides

Houston (Balmori, 2006 AMS)Houston (Balmori, 2006 AMS) NYC (Pullen et al., 2006 AMS) NYC (Pullen et al., 2006 AMS)

Houston MM5 2-m Temps at 4 PM:Houston MM5 2-m Temps at 4 PM: cold-core L from SST-eddy?cold-core L from SST-eddy?

LL

MM5 2-m cold-core L MM5 2-m cold-core L (in 3 domains)(in 3 domains)

along-shore coastal-V along-shore coastal-V Houston Houston ozone-ozone-

episodeepisodeLL

LL

D-2D-2D-1D-1

D-3D-3

NYC SST + currents:NYC SST + currents: Pullen et al. (2006 Pullen et al. (2006 AMS)AMS)

LL

Satellite SST Over Gulf of Mx:Satellite SST Over Gulf of Mx: lots of lots of detailsdetails

http://www7333.nrlssc.navy.mil/http://www7333.nrlssc.navy.mil/

Model-Urbanization Model-Urbanization TechniquesTechniques

UrbanizeUrbanize momentum, thermoynamic , & TKE momentum, thermoynamic , & TKE surface & SBL: diagnostic eqssurface & SBL: diagnostic eqs PBL: prognostic eqs PBL: prognostic eqs

From From veg-veg-canopycanopy model (Yamada 1982) model (Yamada 1982) Veg-param Veg-param replacedreplaced with GIS/RS with GIS/RS

urban-param/data urban-param/data Brown and Williams (1998)Brown and Williams (1998) Masson (2000)Masson (2000) Martilli et al. (2001) in Martilli et al. (2001) in TVM/URBMETTVM/URBMET Dupont, Ching,Dupont, Ching, et al. (2003) in et al. (2003) in EPA/MM5EPA/MM5 Taha et al. (2005), Balmori et al. (2006b) in Taha et al. (2005), Balmori et al. (2006b) in

uMM5uMM5 Detailed input urban-parameters as f(x,y) Next: 2 slides

max urban effect

Urbanized meso-met model TKE (z)

__________________________________

hc =building top

1 km 1 km uMM5 uMM5 Houston UHI: 8 PM, 21 Houston UHI: 8 PM, 21 AugAug

Upper, L:Upper, L: MM5MM5 UHI (2.0 UHI (2.0 K)K)

Upper,R: Upper,R: uMM5 uMM5 UHI (3.5 UHI (3.5 K)K)

Lower L: Lower L: (uMM5-MM5)(uMM5-MM5) UHIUHI

LU/LC errorLU/LC error

Summary of how to obtainSummary of how to obtain good meso-met model resultsgood meso-met model results

1st capture trends in large-scale forcing via 1st capture trends in large-scale forcing via validated large-scale model input validated large-scale model input analysis nudginganalysis nudging

Then simulate correct meso sfc-T via correct Then simulate correct meso sfc-T via correct IC/BC deep soil-T (for min-T) IC/BC deep soil-T (for min-T) IC soil-moisture (for max-T)IC soil-moisture (for max-T)

Get good Get good SSTs SSTs (from obs or ocean-models) (from obs or ocean-models) for good sea-breeze flowsfor good sea-breeze flows

Use good Use good urbanizations urbanizations (scheme & inputs) (scheme & inputs) for good for good temps, turbulence, & windstemps, turbulence, & winds

Overall LessonsOverall Lessons

Models can’t be assumed to be Models can’t be assumed to be perfectperfect black boxesblack boxes

If obs not available, it is OK to make If obs not available, it is OK to make reasonable educated reasonable educated estimates, e.g., forestimates, e.g., for Deep-soil tempDeep-soil temp Soil moisture Soil moisture

Need Need datadata for comparisons with simulated for comparisons with simulated fieldsfields

Need good Need good urbanization,urbanization, e.g., e.g., uMM5uMM5 Need to develop better PBLNeed to develop better PBL

parameterizationsparameterizations

Any questions?Any questions?