Aerosol Daytime Variations over North and South America as Derived from Multiyear

AERONET Measurements

Yan Zhang1, Hongbin Yu2, Alexander Smirnov1, Tom Eck1, Mian Chin3, Lorraine Remer3, Qian Tan1, Robert Levy4

1 GESTAR/USRA, 2 ESSIC, 3 NASA/GSFC, 4 SSAI

May 12, 2011

2

Important for studies of – climate forcing– air quality– satellite data validation

Relatively under-explored over large regions– polar orbiting satellites have no capability (one daytime visit)– geo satellites have large uncertainties

Our objective:– document aerosol daytime variations in GEO-CAPE viewing

areas with high quality, multi-year measurements from AERONET

– give suggestions to GEO-CAPE requirements aspect with aerosol s

Aerosol can have a large daytime variation

AERONET Data Processing

Instantaneous measurements from 54 AERONET sites (after 1997) with more than two year active measurement period.

Hourly mean:•

Daily mean:• for days with more than five hourly

measurements

Daytime variation : for seasons DJF, MAM, JJA, and SON.

Hourly departure :*100%

We use departure (percentage) from daily mean instead of absolute value to present aerosol day time variation

4

6 8 10 12 14 16 18-15

-10

-5

0

5

10

15

20

Local Time (hours)

Rel

ativ

e A

OD

(44

0 n

m)

chan

ge

(%)

JJA

CCNY (0.438)GSFC (0.470)MD Science Center (0.487)MDSC (0.497)

6 8 10 12 14 16 18-20

-10

0

10

20

30

Local Time (hours)

AO

D (

440

nm

) D

VR

(%

)

(a) JJA

Fresno (0.154)La Jolla (0.165)Monterey (0.143)San Nicolas (0.104)

Northeastern US (JJA) West Coast US (JJA)

US: Northeast and West Coast (pollution aerosols) show opposite AOD daytime variations

Northeast: Increasing AOD over a day likely associated with strong afternoon photochemical activity

West Coast: AOD maximum in morning, decreases during day- associated with mesoscale circulations

5

4 6 8 10 12 14 16 18 20-40.0

-20.0

0.0

20.0

40.0

AO

D 4

40 n

m

DJF

AOD=0.38, AE=1.53

Mexico City

-15.0

-10.0

-5.0

0.0

5.0

10.0

AOD AE

4 6 8 10 12 14 16 18 20-40.0

-20.0

0.0

20.0

40.0MAM

AOD=0.51, AE=1.54

-15.0

-10.0

-5.0

0.0

5.0

10.0

AE

440

-870

nm

4 6 8 10 12 14 16 18 20-40.0

-20.0

0.0

20.0

40.0

AO

D 4

40 n

m

Hour

JJA

AOD=0.42, AE=1.44

-15.0

-10.0

-5.0

0.0

5.0

10.0

4 6 8 10 12 14 16 18 20-40.0

-20.0

0.0

20.0

40.0

Hour

SON

AOD=0.40, AE=1.50

-15.0

-10.0

-5.0

0.0

5.0

10.0

AE

440

-870

nm

• Rapid morning increase of AOD due to local emission.• Small afternoon AOD change due to basin ventilation by terrain-induced wind. • AE shows 15%~25% changes; noontime peaks could be related to strong

photochemistry that produces small particles.

AOD

AE

6

Abracos Hill: AOD increases during day; late afternoon maximum consistent with observed peak fire activities

Alta Floresta: AOD has morning maximum, decreases during day

Abracos Hill

Alta Floresta

Two forest sites in South America (smoke aerosols) with differing AOD daytime variations

Abracos Hill

Alta Floresta

7

Lanai

4 6 8 10 12 14 16 18 20-20.0

-10.0

0.0

10.0

20.0

30.0

AO

D 4

40 n

m

DJF

AOD=0.08, AE=0.58

Lanai

-30.0

-20.0

-10.0

0.0

10.0

20.0

30.0

AOD AE

4 6 8 10 12 14 16 18 20-20.0

-10.0

0.0

10.0

20.0

30.0MAM

AOD=0.11, AE=0.71

-30.0

-20.0

-10.0

0.0

10.0

20.0

30.0

AE

440

-870

nm

4 6 8 10 12 14 16 18 20-20.0

-10.0

0.0

10.0

20.0

30.0A

OD

440

nm

Hour

JJA

AOD=0.07, AE=0.69

-30.0

-20.0

-10.0

0.0

10.0

20.0

30.0

4 6 8 10 12 14 16 18 20-20.0

-10.0

0.0

10.0

20.0

30.0

Hour

SON

AOD=0.07, AE=0.72

-30.0

-20.0

-10.0

0.0

10.0

20.0

30.0

AE

440

-870

nm

Large AE variation could result from: 1) large uncertainties in low AOD regime; 2) photochemistry produces fine-mode sulfate aerosol at the noon.

Lanai Island (Marine aerosols), Hawaii: AOD increases during day presumably associated with sea breeze

AOD

AE

8

AOD 440nm Mean & Variation

JJA(c)

(AOD)

AE 440-870nm Mean & Variation

JJA(c)

(AE)Mean DVR

A.M.

P.M.

< 0.80.8~1.21.2~1.6 > 1.6

< 10%10%~20%20%~30%30%~50% > 50%

Mean DVR

A.M.

P.M.

< 0.10.1~0.30.3~0.5 > 0.5

< 10%10%~20%20%~30%30%~50% > 50%

Northeast US has large AOD (> 0.3) and AE (> 1.6), but small DVRsWest Coast US shows small AOD (<0.3) and AE (0.8~1.2), but AE DVR are largeMiddle US has small AOD & DVRSouth America shows large AOD (> 0.3) over Amazon region

AOD and AE variations show wide range depending on location and/or season

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Conclusions

There are a wide range of AOD and AE variations depending on location and/or season

AOD changes could be increasing or decreasing, but they are non-linear.

To capture observed AOD variations we see, at least three successful aerosol retrievals from geo satellites are needed (morning, noon, and afternoon).

Both comprehensive datasets and regional simulations are needed to better understand the observed complex daytime variations. In particular, simultaneous measurements of aerosol and precursors from GEO-CAPE would provide better insight