Mesoscale meteorology modeling and sensitivity analysis for the south of Chile

region using WRF-ARW model

Luis Alonso Díaz Robles, Joshua S. Fu, Alberto Vergara-Fernández, Norman Vergaray

Departamento de Ingeniería Química, Universidad de Santiago de Chilealonso.diaz.r@usach.cl

Very Complex Tarrainand several kindof climates

Santiago

Talca

Chillán

Rancagua

Temuco

Concepción

CoyhaiqueOsorno

19962009

2010

2007

2005

2013

2012

2012

PM10PM10

PM10

PM10

PM10

PM10PM2.5

PM10

PM10PM2.5

PM2.5

2013

Almost

9 milli

ons perso

ns expose

to w

ood smoke every

year

Health Costs

: 7 m

illions U

SD per year, A

GIES PM2.5 from D

ICTUC

ValdiviaPM2.52014

Beijing versus TemucoSaturday, January the 12th 2013

PM2.5 = 993 ug/m3PM2.5 = 300 ug/m3 24-hr

PM2.5 = 993 ug/m3PM2.5 = 291 ug/m3 24-hr

Friday, August 26th 2012

PM2.5 annual Concentration in Latin America [ug/m3]

America Socc

er Cup, C

hile 2015

90102 90601 91029 1003281008251101221106211111181204161209131302101307101312071405060

50100150200250300350400

MP2,5 Norma 24-h

Conc

entr

ation

[ug/

m3]

PM2.5 daily concentration at Temuco

PointSources

1.6%

Residential Wood Combustion 95.8%

Open Burning

2.0%

MobileSources

0.7%

PM2.5 Emission InventoryTemuco, 2012

Several of them use wood either

High PM Emissions

Incomplete combustionIncomplete combustion

Wet Wood

Poor technologyQ

Q

Poor Thermal Isolation

Uninformed consumer

Air QualityThe Problem

Fuelwood consumption per household m3 /year

ValparaisoSantiago

RancaguaLota

ChillanConcepcion

AraucaniaTemuco

VillarricaLos Lagos

ValdiviaOsorno

Rio negroLa Union

Puerto MonttAncudCastro

QuellonCoihaique

AisenPuerto Chacabuco

0 5 10 15 20 25

13

M3/year

Lenga, Ñirre

Ulmo, Luma, Tepú, Mañío

Roble, Raulí, Aromo, Eucaliptus

Hualle, Roble, Eucaliptus

Eucaliptus y frutales

12.7 m3/year (2013)

8.9 m3/year (2009)

Sout

h of

Chi

le

MP CompositionPAHs Properties

• Mutagenic and carcinogenic species

• WHO Recommendation: maximum

BaP limit (annual average) in PM10:

1 ng m-3

• EPA (1984). Health effects assessment for polycylic aromatic hydrocarbons (PAHs). U.S. Environmental Protection Agency, Cincinnati, Ohio, EPA 540/1-86-013.

• WHO (2000). Air Quality Guidelines for Europe, 2nd Ed. WHO Regional Office for Europe, Copenhagen, Publication Nº 91.

• EU (2005). Directiva 2004/107/EC del Parlamento Europeo y del Consejo, del 15 de Diciembre de 2004, relativa al arsénico, cadmio, mercurio, níquel e hidrocarburos aromático policíclicos en el aire ambiente. Diario Oficial de la Unión Europea, L 23, p. 3 (26-1-2005)

Benzo(a)pyreneBenzo(a)pyrene

FONDECYT Project 1120791, 2012-2015PAHs Modeling on WRF/SMOKE/CMAQ, Benzo(a)Pyrene

Cluster SANTA

Cluster Newton

PM2.5

PUF

PM2.5 versus Benzo[a]pyreneTemuco, Winter of 2013

5/18/2

013

5/20/2

013

5/22/2

013

5/24/2

013

5/26/2

013

5/28/2

013

5/30/2

013

6/1/2

013

6/3/2

013

6/5/2

013

6/7/2

013

6/9/2

013

6/11/2

013

6/13/2

013

6/15/2

013

6/17/2

013

6/19/2

013

6/21/2

013

6/23/2

013

6/25/2

013

6/27/2

013

6/29/2

013

7/1/2

013

7/3/2

013

7/5/2

013

7/7/2

013

7/9/2

013

7/11/2

013

7/13/2

013

7/15/2

013

7/17/2

013

7/19/2

013

7/21/2

013

7/23/2

013

7/25/2

013

7/27/2

013

7/29/2

013

7/31/2

0130.0

50.0

100.0

150.0

200.0

250.0

300.0

0.0

20.0

40.0

60.0

80.0

100.0

120.0

PM 2.5 [ug/m3] Benzo[a]pyrene [ng/m3]

WHO recommendation 1 ng/m3 annual in PM10

EPA MethodGC/MS

Modeling Nested Domain

18 6 2 km

Temuco city Location

100

200

300

400

500

Metros

100

200

300

400

500

Metros

Temuco and Padre Las Casas

Temuco urban area, Chile• Located 800 Km south of

Santiago – Chile (Latitude 38° 45’S; Longitude 72° 40’W; 100 m.a.s.l).

• 300,000 inhabitants.• 90% of the population uses

wood for heating in winter season.

Temperate cold rainy with a Mediterranean influence

Temperate warm rainy with a Mediterranean influence

Experimental Design on WRF 3.406/11/2013 to 07/01/2013

Experiment PBL Physics Option Closure Type Land Surface Model Surface Layer Scheme

bl_pbl_physics Scheme sf_surface_physics Model sf_sfclay_physics Scheme

1 7 ACM2 First-order closure 7 Pleim-Xu 7 Pleim-Xu

2 99 MRF Non-local-K mixing 2 Unified Noah LSM 1 Monin-Obukhov

3 2 MYJ TKE 1.5-order 2 Unified Noah LSM 2 Eta Similarity

4 5 MYNN2 TKE 1.5-order 2 Unified Noah LSM 5 MYNN

5 6 MYNN3 TKE 2nd-order 2 Unified Noah LSM 5 MYNN

6 4 QNSE TKE 1.5-order 2 Unified Noah LSM 4 QNSE

7 1 YSU Non-local-K mixing 2 Unified Noah LSM 1 Monin-Obukhov

mp_physics 8Thomsoncu_physics 1Kain-Fritschdiff_6th_opt 1Sixth order numerical diffusionmoist_adv_opt 1Positive definite advection of moisture and scalarsra_lw_physics 1Rapid Radiative Transfer Modelra_sw_physics 1Dudhia

ITEM D1 D2 D3Geographic Projection Lambert ConformalCell size (km) 18 6 2Number of Cells X-Y 100-106 88-94 70-79Number of Layers 39 39 39Terrain resolution 10m 5m 30s

Saide et al, 2011Land use data USGS IC/BC: WRF-FNL (Wu et al., 2002)

Atmospheric Sounding

More than 300

kms

1 9 17 25 33 41 49 57 65 73 81 89 97 105113121129137145153161169177185193201209217225233241249257265273281

-2

0

2

4

6

8

10

12

14

16

18

Observed (°C)Exp 1 (°C)Exp 2 (°C)Exp 3 (°C)Exp 4(°C)Exp 6(°C)Exp 7(°C)Te

mpe

ratu

re [°

C]Temperature Performance

2

4

6

8

10

12

14

Ob

serv

ed

(°C

)

2 4 6 8 10 12 14Exp 1 (°C)

2

4

6

8

10

12

14

Ob

serv

ed

(°C

)

0 2 4 6 8 10 12 14 16Exp 2 (°C)

2

4

6

8

10

12

14

Ob

serv

ed (

°C)

0 2 4 6 8 10 12 14 16Exp 3 (°C)

2

4

6

8

10

12

14

Obse

rved (

°C)

0 2 4 6 8 10 12 14 16Exp 4(°C)

2

4

6

8

10

12

14

Observ

ed (

°C

)

0 2 4 6 8 10 12 14 16Exp 6(°C)

2

4

6

8

10

12

14

Observ

ed (

°C)

0 2 4 6 8 10 12 14 16Exp 7(°C)

-4-3-2-101234

Ob

serv

ed

(°C

) R

esi

dua

l

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

-4-3-2-1012345

Observ

ed (

°C)

Resi

dual

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

-4-3-2-101234

Ob

serv

ed (

°C

) R

esid

ual

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

-4-3-2-101234

Obse

rved (

°C)

Resi

dual

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

-3

-2

-1

0

1

2

3

Observ

ed

(°C

) R

esi

du

al

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

-3-2-10

1234

Observ

ed (

°C)

Resid

ual

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

Residuals of the Temperature

Temperature Performance

Statistics Exp 1 Exp2 Exp3 Exp4 Exp6 Exp7RSquare 0.8237 0.7777 0.83493 0.79279 0.82113 0.77762

RSquare Adj 0.8231 0.7769 0.83435 0.79205 0.82050 0.77683

Root Mean Square Error 1.2123 1.3613 1.17303 1.31427 1.22108 1.36152

Error 414.46 522.60 388.03 487.10 420.47 522.76

Observations (or Sum Wgts) 284 284 284 284 284 284

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106 113 120 127 134 141 148 155 162 169 176 183 190 197 204 211 218 225 232 239 246 253 260 267 274 2810

2

4

6

8

10

12

14

16

18

Observed (°C) Exp 3 (°C) Exp 1 (°C)

Tem

pera

ture

[°C]

Wind Speed [m/s]

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 1061131201271341411481551621691761831901972042112182252322392462532602672742810

2

4

6

8

10

12

14

Observed (m/s) EXP 1 EXP2 EXP3EXP4 EXP6 EXP7

Win

d Sp

eed

[m/s

]

0

1

2

3

4

5O

bse

rve

d (

m/s

)

0 2 4 6 8 10EXP 1

0

1

2

3

4

5

Ob

serv

ed (

m/s

)

0 2 4 6 8 10EXP2

0

1

2

3

4

5

Ob

serv

ed

(m

/s)

0 2 4 6 8 10 12EXP3

0

1

2

3

4

5

Ob

serv

ed (

m/s

)

0 1 2 3 4 5 6 7 8 9EXP4

0

1

2

3

4

5

Ob

serv

ed

(m

/s)

0 2 4 6 8 10 12EXP6

0

1

2

3

4

5

Obse

rved

(m

/s)

0 2 4 6 8 10EXP7

-2.0-1.5-1.0-0.50.00.51.01.52.02.5

Ob

serv

ed

(m

/s)

Re

sid

ual

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

-2

-1

0

1

2

3

Ob

serv

ed

(m

/s)

Re

sid

ual

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

-2.0-1.5-1.0-0.50.00.51.01.52.02.5

Ob

serv

ed (

m/s

) R

esid

ual

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85Normal Quantile

-2.0-1.5-1.0-0.50.00.51.01.52.02.5

Ob

serv

ed

(m

/s)

Re

sid

ual

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

-2.0-1.5-1.0-0.50.00.51.01.52.02.5

Ob

serv

ed

(m

/s)

Resi

dua

l

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

-2

-1

0

1

2

3

Ob

serv

ed

(m

/s)

Resid

ual

0.0

03

0.0

15

0.0

6

0.1

2

0.2

5

0.5

0.7

5

0.8

8

0.9

4

0.9

85

Normal Quantile

Residuals of the Wind Speed

Wind Speed Performance

Statistics Exp1 Exp2 Exp3 Exp4 Exp6 Exp7

RSquare 0.5010 0.4887 0.5512 0.5100 0.5428 0.5461

RSquare Adj 0.4993 0.4869 0.5496 0.5082 0.5412 0.5445

Root Mean Square Error 0.7999 0.8097 0.7586 0.7927 0.7656 0.7629

Error 180.430 184.900 162.294 177.191 165.312 164.116

Observations (or Sum Wgts) 284 284 284 284 284 284

PBL [m]

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 1061131201271341411481551621691761831901972042112182252322392462532602672742810

1000

2000

3000

4000

5000

6000

Exp 1 Exp 2 Exp 3 Exp 4 Exp 6 Exp 7

PBL

[m]

WS versus PBL

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 1061131201271341411481551621691761831901972042112182252322392462532602672742810

2

4

6

8

10

12

14

0

500

1000

1500

2000

2500

3000

3500

Observed WS [m/s] Exp3 WS [m/s] PBL Exp3 [m]

WS

[m/s

]

June 16th at 6 AM

June 16th at 6 AM

June 16th at 6 AM

Conclusions• Problems regarding wrong predictions could be related to different

uncertainties in the model, such as the inability of the model to completely resolve the complex Andes and coast topography, and inaccuracy in meteorological initial and boundary conditions.

• At least one sounding is required closer to the polluted urban areas in Chile.

• The best experiment was the Exp3, which used MYJ as the PBL physics option (Janjic, 2002), Unified Noah LSM as land surface model, and Eta Similarity as the Surface Layer Scheme, however, the wind speed did not perform at all.

Acknowledgments

• FONDECYT Project 1120791

Thanks!!!Dr. L. Alonso Díaz Roblesalonso.diaz.r@usach.cl

ISI, Q1, índice de impacto últimos 5 años = 3.4Número de Citas = 63

ISI, Q1, índice de impacto últimos 5 años = 2.8Número de Citas = 20

ISI, Q1, índice de impacto últimos 5 años = 2.8

ISI, Q1, índice de impacto últimos 5 años = 6.4