11

Urban Climate Studies: Urban Climate Studies: applications for weather, air quality, applications for weather, air quality,

and climate change and climate change

Prof. Robert BornsteinProf. Robert Bornstein

Dept. of MeteorologyDept. of Meteorology

San Jose State UniversitySan Jose State University

San Jose, CA USASan Jose, CA USApblmodel@hotmail.com

Presented atPresented atTel Aviv UniversityTel Aviv University

8 Jan 20098 Jan 2009

Funding sources:Funding sources: USAID-MERC, TCEQ, NASA, NSF, USAID-MERC, TCEQ, NASA, NSF, SCUSCU

22

OVERVIEW• URBAN CLIMATEURBAN CLIMATE

– WHY STUDY IT WHY STUDY IT – ITS CAUSES ITS CAUSES – ITS IMPACTSITS IMPACTS

• CALIFORNIA COASTAL COOLINGCALIFORNIA COASTAL COOLING– DATADATA– ANALYSISANALYSIS

• URBAN ATMOSPHERIC MODELSURBAN ATMOSPHERIC MODELS– FORMULATIONFORMULATION– APPLICATIONS (HOUSTON, ATLANTA, APPLICATIONS (HOUSTON, ATLANTA, ISRAELISRAEL))

• FUTURE EFFORTSFUTURE EFFORTS

33

URBAN WEATHER ELEMENTS:URBAN WEATHER ELEMENTS:battles between conflicting battles between conflicting

effectseffects• VISIBILTITY:VISIBILTITY: decreased decreased• TURBULENCE:TURBULENCE: increased (mechanical & increased (mechanical &

thermal)thermal)• PBL NIGHT STABILITY:PBL NIGHT STABILITY: neutral neutral• FRONTS (synoptic & sea breeze):FRONTS (synoptic & sea breeze): slowed slowed• TEMP:TEMP: increased (UHI) or decreased increased (UHI) or decreased• PRECIP:PRECIP: increased (UHI) or decreased increased (UHI) or decreased• WIND SPEED (V):WIND SPEED (V): increased or decreased increased or decreased• WIND DIRECTION:WIND DIRECTION: con- or divergencecon- or divergence• THUNDERSTORMS:THUNDERSTORMS: triggered or split triggered or split

44

HUMAN-HEALTH IMPACTS OF HUMAN-HEALTH IMPACTS OF URBAN CLIMATEURBAN CLIMATE

• > UHI > UHI THERMAL STRESS THERMAL STRESS • > PRECIP ENHANCEMENT > PRECIP ENHANCEMENT FLOODSFLOODS• > URBAN INDUCED INVERSIONS > URBAN INDUCED INVERSIONS

POLLUTED LAYERSPOLLUTED LAYERS• > TRANSPORT & DIFF PATTERNS FOR> TRANSPORT & DIFF PATTERNS FOR

– POLLUTION EPISODESPOLLUTION EPISODES– EMERGENCY RESPONSE EMERGENCY RESPONSE (i.e., TOXIC (i.e., TOXIC

RELEASES)RELEASES)

55

NEW URBAN CLIMATE: CAUSESNEW URBAN CLIMATE: CAUSES

• GRASS & SOIL GRASS & SOIL

CONCRETE & BUILDINGSCONCRETE & BUILDINGS ALTERED SURFACE HEAT FLUXESALTERED SURFACE HEAT FLUXES

• FOSSIL FOSSIL FUELFUEL CONSUMPTION CONSUMPTION

ATMOSPHERIC POLLUTION AND HEATATMOSPHERIC POLLUTION AND HEAT

• ATM ATM POLLUTIONPOLLUTION

ALTERED SOLAR & IR ENERGYALTERED SOLAR & IR ENERGY

66

St. Louis St. Louis nocturnal PBL:nocturnal PBL: warm near-neutral, polluted warm near-neutral, polluted urban-plume urban-plume

vsvs. rural stable surface-inversion . rural stable surface-inversion

urban-plumeurban-plume

Clark & McElroy (1970):Clark & McElroy (1970):

inversioninversion

0FF

TTmin

TTmax

77

Urban effects on wind speedUrban effects on wind speed• FASTFAST LARGE-SCALE (i.e., SYNOPTIC) SPEEDS LARGE-SCALE (i.e., SYNOPTIC) SPEEDS

SMALL UHI SMALL UHI

URBAN SFC ROUGHNESS (ZURBAN SFC ROUGHNESS (Z00) INDUCED ) INDUCED DECELERATIONDECELERATION

• SLOW SLOW SYNOPTIC SPEEDSSYNOPTIC SPEEDSLARGE UHI LARGE UHI INWARD-DIRECTED INWARD-DIRECTED ACCELERATIONACCELERATION

• CRITICALCRITICAL SPEED SPEED ~ 3-4 m/s (FOR NYC & London)~ 3-4 m/s (FOR NYC & London)

88

NYC DAYTIME ∆V NYC DAYTIME ∆V (z)(z)

urbanurban ruralrural

99

URBAN EFFECTS ON WIND URBAN EFFECTS ON WIND DIRDIR

• FAST FAST SYNOPTIC SPEED SYNOPTIC SPEED WEAK UHI WEAK UHI

URBAN BUILDING-BARRIER EFFECT URBAN BUILDING-BARRIER EFFECT FLOW FLOW DIVERGESDIVERGES AROUND CITYAROUND CITY

• SLOW SLOW SYNOPTIC SPEED SYNOPTIC SPEED LARGE UHI LARGE UHI LOW-p LOW-p CONVERGENCECONVERGENCE INTO CITYINTO CITY

• MODERATE MODERATE SYNOPTIC SPEEDSYNOPTIC SPEED CONVERGENCE-CONVERGENCE-ZONE ADVECTED TOZONE ADVECTED TO DOWNWIND DOWNWIND URBAN-EDGEURBAN-EDGE

1010

NOCTURNAL UHI-INDUCED SFC-CONFLUENCE:NOCTURNAL UHI-INDUCED SFC-CONFLUENCE:otherwise-calm synoptic flow otherwise-calm synoptic flow

confluence-center over urban center of Frankfurt, Germanyconfluence-center over urban center of Frankfurt, Germany

1111

Weak cold-frontal (N to S) passage over NYCWeak cold-frontal (N to S) passage over NYCa.a. Hourly positions Hourly positions (left)(left)b.b. At 0800 EST (right): T, q, & SOAt 0800 EST (right): T, q, & SO2 z-profile-changes z-profile-changes

showed lowest 250 m of atm not-replaced, as front showed lowest 250 m of atm not-replaced, as front ““jumped” over cityjumped” over city

See See

1212

URBAN IMPACTS ON PRECIPURBAN IMPACTS ON PRECIP

• INITATION BY THERMODYNAMICS (at SJSU)INITATION BY THERMODYNAMICS (at SJSU)– LIFTINGLIFTING FROM FROM

•UHI CONVERGENCE UHI CONVERGENCE

•THERMAL & MECHANICAL CONVECTIONTHERMAL & MECHANICAL CONVECTION

– DIVERGENCEDIVERGENCE FROM FROM BUILDING BARRIER EFFECTBUILDING BARRIER EFFECT

• AEROSOL MICROPHYSICS AEROSOL MICROPHYSICS – SLOWER SLOWER SECONDARYSECONDARY DOWNWIND ROLE DOWNWIND ROLE – METROMEX & PROF. D. ROSENFELD (HUJI)METROMEX & PROF. D. ROSENFELD (HUJI)

1313

NYC two-summer daytime-average NYC two-summer daytime-average thunderstorm-precip radar-echoesthunderstorm-precip radar-echoes ((σσ’s from uniform-distribution) for cases: all, convective, & moving ’s from uniform-distribution) for cases: all, convective, & moving

splitting splitting casecase

Formed over cityFormed over city

Split by citySplit by city

1414

Dispersion effectsDispersion effects

• Vertical Vertical diffusiondiffusion limited by urban-induced limited by urban-induced

elevated inversions elevated inversions (next slide)(next slide)

• Transport:Transport: 3-D effects of urban-induced 3-D effects of urban-induced flow-flow- modificationsmodifications

• ConvergenceConvergence-zones-zones effects due to effects due to – Urban effectsUrban effects– Sea breezesSea breezes

1515

Urban-induced nocturnal elevated Urban-induced nocturnal elevated inversion-I trapsinversion-I traps home-heating emissions home-heating emissions Power plant plume is Power plant plume is trapped b/ttrapped b/t urban-induced inversions I & II urban-induced inversions I & II Inversion III is Inversion III is regional inversion regional inversion poor estimate of poor estimate of mixing depthmixing depth

Home-heatingSources

Plume

1616

California Coastal-Cooling California Coastal-Cooling (to appear, J. of Climate, 2009)(to appear, J. of Climate, 2009)

• Global & CA observations Global & CA observations generallygenerally show show – asymmetric warming (more warming for Tasymmetric warming (more warming for Tminmin than than

for Tfor Tmaxmax) ) (next graph)(next graph)

– acceleration since mid-1970s acceleration since mid-1970s

• CA downscaledCA downscaled global-modeling global-modeling (next map)(next map) – done onto 10 km grids done onto 10 km grids – shows summer warming that decreases towards shows summer warming that decreases towards

the coast the coast (but does not show coastal cooling)(but does not show coastal cooling)

1717

Not much change from mid-40s to mid-70s, when valuesstarted to again rapidly rise

1818

Statistically down-scaled (Prof. Maurer, Statistically down-scaled (Prof. Maurer, SCUSCU) 1950-2000 ) 1950-2000 Summer (JJA)Summer (JJA) IPCC temp-changes ( IPCC temp-changes (00C) show warming C) show warming rates that decrease towards coast; rates that decrease towards coast; red dotsred dots are COOP are COOP

sites used in present study & sites used in present study & boxesboxes are study sub-areas are study sub-areas

1919

Current HypothesisCurrent Hypothesis

INCREASEDINCREASED GHG-INDUCED GHG-INDUCED INLAND TEMPSINLAND TEMPSINCREASED (COAST TO INCREASED (COAST TO INLAND) PRESSURE & TEMP INLAND) PRESSURE & TEMP GRADIENTSGRADIENTS INCREASED INCREASED SEA BREEZESEA BREEZE FREQ, INTENSITY, FREQ, INTENSITY, PENETRATION, &/OR PENETRATION, &/OR DURATION DURATION COASTAL AREAS SHOULD COASTAL AREAS SHOULD SHOW SHOW COOLING SUMMER COOLING SUMMER DAYTIME MAX TEMPSDAYTIME MAX TEMPS (i.e., A (i.e., A REVERSE REACTION)REVERSE REACTION)

NOTE:NOTE: NOT A TOTALLY ORIGINAL NOT A TOTALLY ORIGINAL IDEA IDEA

2020

Results 1:Results 1: SoCAB 1970-2005 summer (JJA) T SoCAB 1970-2005 summer (JJA) Tmax max warming/ warming/ cooling trends (cooling trends (00C/decade); C/decade); solid, crossed, & open solid, crossed, & open

circles show stat p-values < 0.01, 0.05, & not circles show stat p-values < 0.01, 0.05, & not

significant, respectivelysignificant, respectively

??

????

2121

Results 2:Results 2: SFBA & CV 1970-2005 JJA SFBA & CV 1970-2005 JJA T Tmaxmax warming/cooling trends ( warming/cooling trends (00C/decade), as in previous C/decade), as in previous

figurefigure

??

??

??

2222

• LOWER TRENDSLOWER TRENDS FROM 1950- 70 FROM 1950- 70 (EXCEPT FOR T(EXCEPT FOR TMAX)

• Curve b:Curve b: T TMIN HAD HAD FASTEST RISE (AS FASTEST RISE (AS EXPECTED)EXPECTED)

• Curve c:Curve c: T TMAX HAD SLOWEST RISE; IT IS A SMALL-∆ B/T BIG POS VALUE & BIG NEG-VALUE (AS IN ABOVE 2 GRAPHS)

• CURVE a:CURVE a: TAVE THUS THUS ROSE AT MID RATE ROSE AT MID RATE

• Curve d:Curve d: DTR DTR (diurnal temp (diurnal temp range) THUS range) THUS

DECREASED (AS DECREASED (AS TTMAX FALLS & FALLS & TTMIN RISES)RISES)

Results 3: JJA Temp trends; all CA-sites

2323

Significance of these Significance of these all-CA all-CA TrendsTrends

• HIGHER TRENDS FROM 1970-2005 HIGHER TRENDS FROM 1970-2005 FOCUS NEEDED ON THIS PERIOD

• TTMIN HAS FASTER RISE HAS FASTER RISE

ASSYMETRIC WARMING IN LITERATUREASSYMETRIC WARMING IN LITERATURE

• BUTBUT T TMAX HAS SLOWER RISE, BECAUSE IT IS A SMALL DIFFERENCE B/T BIG POS-VALUE & BIG NEG-VALUE (AS SEEN IN ABOVE SPATIAL PLOTS)

• TAVE & DTR DTR ARE ALSO THUS ARE ALSO THUS “CONTAMINATED” “CONTAMINATED”

• NEXT 2 SLIDESNEXT 2 SLIDES THUS SHOW THUS SHOW SEPARATE SEPARATE TRENDSTRENDS FOR CA COASTAL AND INLAND AREAS FOR CA COASTAL AND INLAND AREAS

2424

Result 4: JJA TResult 4: JJA Tave, T, Tmin, T, Tmax, & DTR TRENDS FOR, & DTR TRENDS FOR

INLAND-WARMING INLAND-WARMING SITES OF SoCAB & SFBASITES OF SoCAB & SFBA

Curve b:Curve b: T TMIN

INCREASED (EXPECTED)(EXPECTED)

Curve c:Curve c: T TMAX HAD FAST RISE; (UNEXPECTED), (UNEXPECTED), COULD BE DUE TO COULD BE DUE TO INCREASED UHIs OR INCREASED UHIs OR INCREASED DOWN-INCREASED DOWN-SLOPE FLOWSSLOPE FLOWS

CURVE a:CURVE a: TAVE THUS THUS

ROSE AT MID RATEROSE AT MID RATE

Curve d:Curve d: DTR THUS DTR THUS INCREASED (AS TINCREASED (AS TMAX ROSE FASTER THAN FASTER THAN TTMIN ROSE ROSE

bb

cc

aa

dd

2525

Result 5: JJA TResult 5: JJA Tave, T, Tmin, T, Tmax, & DTR TRENDS FOR , & DTR TRENDS FOR

COASTAL-COOLINGCOASTAL-COOLING SITES OF SoCAB & SFBA SITES OF SoCAB & SFBA

Curve b:Curve b: T TMIN ROSE ROSE

(EXPECTED)(EXPECTED)

Curve c:Curve c: T TMAX HAD COOL-ING (UNEXPECTED (UNEXPECTED MAJOR MAJOR RESULTRESULT OF STUDY) OF STUDY)

CURVE a:CURVE a: TAVE THUS SHOWED ALMOST NO CHANGE, AS FOUND IN LIT.), AS RISING T AS RISING Tmin & &

FALLING TFALLING Tmax CHANGES ALMOST CANCELLED OUT

Curve d:Curve d: DTR THUS DE- DTR THUS DE-CREASED, AS TCREASED, AS TMIN ROSE &

TTMAX FELL FELL

aa

bb

cc

dd

2626

Note IPCC 2001 does show cooling over Central California!!

2727

Significance of above Significance of above Coastal-Coastal-Cooling Cooling and Inland-Warming and Inland-Warming

trendstrends• CA ASSYMETRIC WARMINGCA ASSYMETRIC WARMING IN LITERATURE IN LITERATURE

IS HEREIN SHOWN TO BE DUE TO IS HEREIN SHOWN TO BE DUE TO COOLING TTMAX IN COASTAL AREAS & CONCURRENTCONCURRENT WARMING TTMAX IN INLAND AREAS

• PREVIOUS CA STUDIESPREVIOUS CA STUDIES – DID NOT LOOK SPECIFICALLY AT DID NOT LOOK SPECIFICALLY AT SUMMER SUMMER

DAYTIME COASTAL VS. INLAND VALUESDAYTIME COASTAL VS. INLAND VALUES HAVE HAVE

– THEY THUS REPORTED THEY THUS REPORTED CONTAMINATEDCONTAMINATED T TMAX, , TTAVE, & DTR VALUES, & DTR VALUES

– THEY, HOWEVER, ARE THEY, HOWEVER, ARE NOT INCONSISTENTNOT INCONSISTENT WITH WITH CURRENT RESULTS, THEY ARE JUST NOT AS CURRENT RESULTS, THEY ARE JUST NOT AS DETAILEDDETAILED IN THEIR ANALYSES & RESULTS IN THEIR ANALYSES & RESULTS

2828

Result 6. JJA 1970-2005 2 m TResult 6. JJA 1970-2005 2 m Tmax max trends for 4 trends for 4 pairs of pairs of urban (red, solid) & rural (blue, urban (red, solid) & rural (blue,

dashed)dashed) sites sitesNotes:Notes:1.1. All sites are near the All sites are near the

cooling-warming cooling-warming borderborder

2.2. UHI-TRENDUHI-TREND (K/DECADE)(K/DECADE)

= = absolute sumabsolute sum b/t b/t warming-urban & warming-urban & cooling-rural cooling-rural trends trends

a. a. SFBASFBA sites sites > Stockton > Stockton (0.38 + 0.17 = (0.38 + 0.17 = 0.55)0.55)> Sac. (0.49)> Sac. (0.49)

b. b. SoCABSoCAB sites sites > Pasadena (0.26)> Pasadena (0.26) > S. Ana (0.12)> S. Ana (0.12)

2929

Notes on JJA daytime Notes on JJA daytime UHI-trendUHI-trend results results

• Faster growingFaster growing cities (not shown) had cities (not shown) had faster growing UHIs faster growing UHIs

• As As no coastal sitesno coastal sites showed warming showed warming TTmax values, calculations could only be values, calculations could only be done at these four pairs (at the inland done at these four pairs (at the inland boundary b/t the warming and cooling boundary b/t the warming and cooling areas)areas)

• Coastal sitesCoastal sites would have would have cooled even cooled even moremore w/o their (assumed) growing UHIs w/o their (assumed) growing UHIs

3030

BENEFICIAL IMPLICATIONS OF BENEFICIAL IMPLICATIONS OF COASTAL COOLINGCOASTAL COOLING

• NAPA WINE NAPA WINE AREAS MAY NOT GO EXTINCTAREAS MAY NOT GO EXTINCT (REALLY GOOD NEWS!) (REALLY GOOD NEWS!) (next map)(next map)

• ENERGYENERGY FOR COOLING MAY NOT INCREASE FOR COOLING MAY NOT INCREASE AS RAPIDLY AS POPULATION AS RAPIDLY AS POPULATION (next graph)(next graph)

• LOWER HUMAN LOWER HUMAN HEAT-STRESSHEAT-STRESS RATES RATES• OZONE CONCENTRATIONSOZONE CONCENTRATIONS MIGHT MIGHT

CONTINUE TO DECREASE, AS LOWER MAX-CONTINUE TO DECREASE, AS LOWER MAX-TEMPS MEAN REDUCEDTEMPS MEAN REDUCED– ANTHROPOGENIC EMISSIONSANTHROPOGENIC EMISSIONS– BIOGENIC EMISSIONSBIOGENIC EMISSIONS– PHOTOLYSIS RATESPHOTOLYSIS RATES

3131

NAPA WINE AREAS MAY NAPA WINE AREAS MAY NOT GO EXTINCTNOT GO EXTINCT DUE TO DUE TO ALLEGED RISING TALLEGED RISING TMAX VALUES, AS PREDICTED IN NAS VALUES, AS PREDICTED IN NAS

STUDYSTUDY

3232

Result 7: Peak-Summer Result 7: Peak-Summer Per-capita Per-capita Electricity-Electricity-TrendsTrends

Down-trend at Down-trend at cooling cooling Coastal: LA (blue) & Pasadena Coastal: LA (blue) & Pasadena ((pinkpink, 8.5%/decade), 8.5%/decade)

> Up-trend at warming Up-trend at warming inland Riversideinland Riverside (green)(green)

Up-trend at Up-trend at warming warming Sac & Santa ClaraSac & Santa Clara

Need:Need: detailed detailed energy-useenergy-use data for more sitesdata for more sites to consider changed to consider changed energy energy efficiency efficiency

3333

Future Coastal-Cooling EffortsFuture Coastal-Cooling Efforts (PART 1 OF (PART 1 OF 2)2)

• EXPAND EXPAND (TO ALL OF CA (TO ALL OF CA & ISRAEL?& ISRAEL?))– ANALYSIS OFANALYSIS OF OBS (IN-SITU & OBS (IN-SITU & GISGIS) ) – URBANIZED MESO-MET (MM5, RAMS, WRF) URBANIZED MESO-MET (MM5, RAMS, WRF)

MODELING MODELING

• SEPARATE INFLUENCES SEPARATE INFLUENCES OF CHANGING:OF CHANGING:– LAND-USE PATTERNS RELAND-USE PATTERNS RE

• AGRICULTURAL IRRIGATIONAGRICULTURAL IRRIGATION• URBANIZATION & UHI-MAGNITUDEURBANIZATION & UHI-MAGNITUDE

– SEA BREEZE:SEA BREEZE:INTENSITY, FREQ, DURATION, &/OR PENETRATION INTENSITY, FREQ, DURATION, &/OR PENETRATION

• DETERMINE POSSIBLE DETERMINE POSSIBLE “SATURATION”“SATURATION” OF OF SEA- BREEZE EFFECTS FROMSEA- BREEZE EFFECTS FROM

• FLOW-VELOCITY & COLD-AIR TRANSPORTFLOW-VELOCITY & COLD-AIR TRANSPORT• AND/OR STRATUS-CLOUD EFFECTS ON LONG- & SHORT-AND/OR STRATUS-CLOUD EFFECTS ON LONG- & SHORT-

WAVE RADIATIONWAVE RADIATION

3434

POSSIBLE FUTURE EFFORTS POSSIBLE FUTURE EFFORTS (PART 2 (PART 2 OF 2)OF 2)

• DETERMINE CUMULATIVE FREQ DETERMINE CUMULATIVE FREQ DISTRIBUTIONSDISTRIBUTIONS OF T OF TMAX VALUES, AS VALUES, AS– EVEN IF EVEN IF AVERAGEAVERAGE T TMAX DECREASES, DECREASES,– EXTREMEEXTREME VALUES T VALUES TMAX MAY STILL INCREASE (IN MAY STILL INCREASE (IN

INTENSITY &/OR FREQUENCY)INTENSITY &/OR FREQUENCY) • DETERMINE CHANGES IN LARGE-SCALE ATM DETERMINE CHANGES IN LARGE-SCALE ATM

FLOWS:FLOWS:– HOW DO GLOBAL CLIMATE-CHANGE EFFECT HOW DO GLOBAL CLIMATE-CHANGE EFFECT

POSITION & STRENGTH OF: POSITION & STRENGTH OF: PACIFIC HIGH & PACIFIC HIGH & THERMAL LOW?THERMAL LOW?

– THESE TYPES OF CLIMATE-CHANGES ARE THE THESE TYPES OF CLIMATE-CHANGES ARE THE ULTIMATE CAUSESULTIMATE CAUSES OF TEMP AND PRECIP CHANGES OF TEMP AND PRECIP CHANGES

3535

OUR GROUP’S MESO-MODELING EXPERIENCEOUR GROUP’S MESO-MODELING EXPERIENCE

• SJSU (MM5 & uMM5)SJSU (MM5 & uMM5)– Lozej (1999) MS: SFBA winter wave cyclone– Craig (2002) MS: Atlanta UHI-initiated thunderstorm (NASA)– Lebassi (2005) MS: Monterey sea breeze (LBNL)– Ghidey (2005) MS: SFBA/CV CCOS episode (LBNL)– Boucouvula (2006a,b) Ph.D.: SCOS96 episode (CARB)– Balmori (2006) MS: Tx2000 Houston UHI (TECQ)– Weinroth (2009) PostDoc: NYC-ER UDS urban-barrier effects (DHS))

• SCU (uRAMS)SCU (uRAMS)– Lebassi (2005): Sacramento UHI (SCU) – Lebassi (2009) Ph.D.: SFBA & SoCAB coastal-cooling (SCU)– Comarazamy (2009) Ph.D.: San Juan climate-change & UHI (NASA)

• Altostratus (uMM5 & CAMx)Altostratus (uMM5 & CAMx)– SoCAB (1996, 2008): UHI & ozone (CEC)– Houston (2008): UHI & ozone (TECQ) – Central CA (2008): UHI & ozone (CEC)– Portland (current): UHI & ozone (NSF)– Sacramento (current): UHI & ozone (SMAQMD)

3636

SJSU IDEAS ON GOOD MESO-MET SJSU IDEAS ON GOOD MESO-MET MODELINGMODELING

MUST MUST CORRECTLYCORRECTLY REPRODUCE:REPRODUCE:– UPPER-LEVEL Synoptic/GC FORCING FIRST: UPPER-LEVEL Synoptic/GC FORCING FIRST:

pressurepressure (“the” GC/Synoptic driver) (“the” GC/Synoptic driver) Synoptic/GC windsSynoptic/GC winds

– TOPOGRAPHYTOPOGRAPHY NEXT:NEXT:min horiz min horiz grid-spacinggrid-spacing flow-channeling flow-channeling

– MESO SFC-CONDITIONSMESO SFC-CONDITIONS LAST:LAST:temp temp (“the” meso-driver) & (“the” meso-driver) &

roughness roughness meso-windsmeso-winds

3737

Case 1: ATLANTA UHI-INITIATED STORM: OBS GOES & PRECIP (UPPER) & MM5 w’s & precip (LOWER)

3838

Recent Meso-met Model Urbanizations

• Need to urbanizeNeed to urbanize momentum, thermo, & TKE momentum, thermo, & TKE – Surface & SfcBL Diagnostic-Eqs.Surface & SfcBL Diagnostic-Eqs.– PBL Prognostic-Eqs. PBL Prognostic-Eqs. (not done in NCAR uWRF) (not done in NCAR uWRF)

• Start: Start: vegveg-canopy-canopy model (Yamada 1982) model (Yamada 1982)• Veg-param Veg-param replacedreplaced with GIS/RS urban-param/data with GIS/RS 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. (‘05, ‘08a,b,c)Taha et al. (‘05, ‘08a,b,c) [& Balmori et al. (‘06)]: his [& Balmori et al. (‘06)]: his

uMM5 uses uMM5 uses improved urbanimproved urban dynamics, physics, dynamics, physics, parameterizations, & inputsparameterizations, & inputs

3939

T int

Q wall

Ts roof

Drainage outside the system

Sensible heat flux

Latent heat flux

Net radiation

Storage heat flux

Anthropogenic heat flux

Precipitation

Roughness approach

Root zone layer

Infiltration

Diffusion

Deep soil layer

Drainage

Drainage network

natural soil

roof

water

Paved surface

bare soil

Surface layer

Drag-Force approach

Rn pav Hsens pav LEpav

Gs pav Ts pav

From EPA uMM5:

Mason + Martilli (by Dupont)

Within Gayno-

Seaman

PBL/TKE schemeNew

4040

But, uMM5 needs extra GIS-derived inputs as f (x, y, z, t)

land-use (38 categories) roughness heights z0 (see next slide) anthropogenic heat building heights paved-surface 2-D fractions building H to W, wall-plan, & impervious-area

2-D ratios building frontal, plan, & rooftop 3-D area densities

4141

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

Values up to 3 m

But, values are too But, values are too large, as they were large, as they were f(h) &f(h) & not not f(ơf(ơhh))

h = h = building heightbuilding height

4242

uMM5 for Houston: Balmori uMM5 for Houston: Balmori (2006)(2006)Goal:Goal: Accurate urban/rural temps & Accurate urban/rural temps &

winds for Aug 2000 Owinds for Aug 2000 O33 episode via episode via – uMM5uMM5– Houston LU/LC & urban morphology Houston LU/LC & urban morphology

parametersparameters– TexAQS2000 field-study dataTexAQS2000 field-study data– USFS urban-reforestation scenarios USFS urban-reforestation scenarios

UHI & OUHI & O33 changes changes

4343

uMM5 Simulation period: uMM5 Simulation period: 22-26 August22-26 August

20002000 • Model configuration Model configuration

– 5 domains: 108, 36, 12, 4, 5 domains: 108, 36, 12, 4, 1 km1 km– (x, y) grid points: (x, y) grid points:

(43x53, 55x55, 100x100, 136x151, 133x141(43x53, 55x55, 100x100, 136x151, 133x141– full-full- levels: 29 in D 1-4 & 49 in D-5; levels: 29 in D 1-4 & 49 in D-5; lowest ½ lowest ½

level=7 mlevel=7 m– 2-way feedback in D 1-42-way feedback in D 1-4

• Parameterizations/physics optionsParameterizations/physics options > Grell cumulus (D 1-2)> Grell cumulus (D 1-2) > ETA or MRF PBL (D 1-4)> ETA or MRF PBL (D 1-4) > > Gayno-Seaman PBLGayno-Seaman PBL (D-5) > Simple ice moisture, (D-5) > Simple ice moisture, > > urbanization moduleurbanization module NOAH LSM > RRTM radiative NOAH LSM > RRTM radiative

coolingcooling• InputsInputs

> NNRP Reanalysis fields, ADP obs data > NNRP Reanalysis fields, ADP obs data > Burian > Burian morphologymorphology from from LIDAR building-data in D-5LIDAR building-data in D-5

> LU/LC modifications (from Byun)> LU/LC modifications (from Byun)

4444

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

MM5 MM5 UHI (2.0 K) UHI (2.0 K)

uMM5uMM5 UHI UHI (3.5 K)(3.5 K)

UHI

UHIBay

Gulf

4545

UHI-Induced UHI-Induced CConvergence: obs vs. onvergence: obs vs. uMM5uMM5

Krieged ObsKrieged Obs uMM5 outputuMM5 output

C

C

C

C

4646

Base-case (current) veg-cover (0.1’s) urban min (red) rural max (green)

Modeled changes of veg-cover (0.01’s) Urban-reforestation (green)Rural-deforestation (purple)

min

maxincrease

4747

Run 12 (urban-max reforestation) minus Run 10 (base Run 12 (urban-max reforestation) minus Run 10 (base case) case)

near-sfc ∆T at 4 PM shows that:near-sfc ∆T at 4 PM shows that:reforested central urban-area cools &reforested central urban-area cools &

surrounding deforested rural-areas warmsurrounding deforested rural-areas warm

warmer

warmer

cooler

4848

UHI(t): Base-case UHI(t): Base-case minusminus Runs 15-18 Runs 15-18

• UHI =UHI = Urban-Box minus Rural-Box Urban-Box minus Rural-Box • Runs 15-18:Runs 15-18: Urban re-forestation scenarios Urban re-forestation scenarios• UHI =UHI = Run-17 UHI minus Run-13 UHI Run-17 UHI minus Run-13 UHI

max effect max effect (green line)(green line) • Reduced UHIReduced UHI lower max-Olower max-O33 (not shown) (not shown)

EPA emission-reduction credits EPA emission-reduction credits $ $ savedsaved

Max-impact of –0.9 K on a 3.5 K noon-UHI, of which1.5 K was from uMM5

URBAN

RURAL

4949

RAMS, MM5, & CAMx SIMULATIONS OF MIDDLE-EAST O3 TRANSBOUNDARY

TRANSPORT

E. WeinrothE. Weinroth1,21,2, S. Kasakseh, S. Kasakseh1,31,3

M. LuriaM. Luria2, R. Bornstein, R. Bornstein11

11San Jose State Univ. San Jose State Univ. 22Hebrew Univ. Jerusalem, IsraelHebrew Univ. Jerusalem, Israel

33Applied Research Institute Jerusalem (ARIJ), Applied Research Institute Jerusalem (ARIJ), Bethlehem, West Bank Bethlehem, West Bank

In Atmos. Environ. (2008)In Atmos. Environ. (2008)

5050

USAID-MERC USAID-MERC project (2000-)project (2000-)

• Involves scientists Involves scientists from from Palestinian Territories, Israel, Palestinian Territories, Israel, USAUSA (& now (& now Jordan and LebanonJordan and Lebanon))

• Objectives accomplished:Objectives accomplished:– InstallationInstallation of environmental stations in West Bank & Gaza of environmental stations in West Bank & Gaza

(and now Jordan & Beirut)(and now Jordan & Beirut)

– PreparationPreparation of environmental databases (SJSU web page) of environmental databases (SJSU web page)

– Field campaignsField campaigns during periods of poor air quality (Prof. Luria) during periods of poor air quality (Prof. Luria)

– Application Application of numerical models for planningof numerical models for planning

• RAMS & MM5 RAMS & MM5 (Kasakseh 2007) meso-met meso-met

• CAMxCAMx photochemical air-quality (Weinroth et al. 2007 photochemical air-quality (Weinroth et al. 2007 in in Atmos. Environ.) Atmos. Environ.)

5151

3 m /s

5 0 m2 5 0 m7 5 0 m1 0 0 0 m

Med

iterr

anea

n S e

a

3 4 .5 3 4 .8 3 5 .1 3 5 .4

L O N G IT U D E (D eg E )

1 0 m o b s sp eed (m /s) & O 3 a t 0 3 0 0 L S T o r 0 0 0 0 U T C o n 1 A u g

3 1 .5

3 1 .8

3 2 .1

3 2 .4

3 2 .7

3 3L

AT

ITU

DE

(D

eg N

)

H

Flow Dir: weak down-slope off coastal-mountains at Coastal plain: offshore (to W) from W-facing slopes Haifa Pen. (square): offshore (to E ) from E-facing slopes Inland sites: directed inland (to E) from E-facing slopes

Low-O3 generally <40 ppb)Haifa still at 51 ppb

Night obs of sfc flow: 3-AM LST (00 UTC)

L

L

H

52523 4 .5 3 4 .8 3 5 .1 3 5 .4

L O N G IT U D E (D eg E )

1 0 m o b s sp eed (m /s) a t 1 2 0 0 L S T o r 0 9 0 0 U T C o n 1 A u g

3 1 .5

3 1 .8

3 2 .1

3 2 .4

3 2 .7

3 3L

AT

ITU

DE

(D

eg N

)

3 m /s

5 0 m2 5 0 m7 5 0 m1 0 0 0 m

Med

iterr

anea

n S e

a

H

Winds: Reversed Stronger: up 6 m s-1

Coastal plain: Onshore/upwind, from SW Inland sites: Channeling (from W) in corridor (box; focus of modeling) from Tel-Aviv to J. area (at Modiin site). Higher daytime O3

max at Mappil, 66 ppb 2nd max at Modiin, 63 ppb

Day Obs: 1200 NOON LST

L

H

H

L

5353

MM5 ConfigurationMM5 Configuration

Version 3.7Version 3.7 3 domains 3 domains

– 15, 5, 15, 5, 1.67 km1.67 km Grid Spacings Grid Spacings– 59 x 61, 55 x 76, 58 x 85 Grid 59 x 61, 55 x 76, 58 x 85 Grid

PointsPoints 32 32 σσ--levelslevels

– up to 100 mbup to 100 mb– first full first full σσ--level at level at 19 m 19 m

Lambert-conformal map projection Lambert-conformal map projection (suitable for mid lat regions) (suitable for mid lat regions)

Two-way nesting Two-way nesting 5-layer soil-model5-layer soil-model Gayno-Seaman PBLGayno-Seaman PBL Simulations Simulations

– End: 00 UTC, 3 Aug End: 00 UTC, 3 Aug – Start: 00 UTC, 29 JulyStart: 00 UTC, 29 July

Single CPU , LINUX Single CPU , LINUX

5454

MM5 MM5 Domain-3 Domain-3 winds (m/s) at winds (m/s) at 11001100 LST on 1 LST on 1 Aug ‘97 Aug ‘97

red lines = topo heights (m); red lines = topo heights (m); yellow lineyellow line = = seasea breeze front; breeze front; note note reverse reverse upslopeupslope-flow & -flow &

channeling to channeling to J.J.

MaxMax

MaxMax

Sea

J.J.

5555

Same, but at Same, but at 2300 2300 LST; where LST; where yellow lineyellow line = = landland breeze front; breeze front; note down-slope note down-slope flow; still flow; still

inland directedinland directed flow in inland areas & still flow in inland areas & still

channeling to channeling to J.J.

MaxMax

MaxMax

Sea

J.J.

5656

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

5757

Obs vs. MM5: wind speed (m/s)Obs vs. MM5: wind speed (m/s)

July 31 August 1 August 2

OBS

Run 3

5858

Jerusalem

0

0-20

20-40

40-60

60-70

70-80

80-90

90-95

95-105

105-120

O3 ppb

1 Aug, 1500 LST

RAMS/CAMx (left) ORAMS/CAMx (left) O33 vs. airborne obs (right) at 300 m: vs. airborne obs (right) at 300 m:

> Secondary-max: > Secondary-max: over J. in obs; due to coastal N-S highway over J. in obs; due to coastal N-S highway > Primary-max: > Primary-max: in Jordan (no obs); due to Haderain Jordan (no obs); due to Hadera

Irbid,Jordan

Hadera Power Plant

.

Airborne obs

5959

Overall Modeling LessonsOverall Modeling Lessons• > Models can’t be > Models can’t be

– assumed to be perfect assumed to be perfect (i.e., model user vs. modeler)(i.e., model user vs. modeler)– used as black boxesused as black boxes

• > Need good > Need good large-scalelarge-scale forcing model-fields forcing model-fields

• > If obs are not available, OK to make > If obs are not available, OK to make reasonable reasonable educatededucated estimates, e.g., for estimates, e.g., for ruralrural– deep-soil tempdeep-soil temp– soil moisture soil moisture

• > Need > Need datadata to compare with simulated-fieldsto compare with simulated-fields

• > Need good > Need good urbanurban– morphological datamorphological data– urbanization schemesurbanization schemes

6060

Thanks for listening!Thanks for listening!

Questions?Questions?