i. matthew watson, mtu and university of bristol, uk remote sensing of volcanic emissions using...

I. Matthew Watson, MTU and University of Bristol, UK

Remote sensing of volcanic emissions using MODIS

Talk structure

• Why quantify volcanic emissions?• MODIS channels of interest• Pre-MODIS algorithms• Recent developments using MODIS

– 7.34 m channel• e.g. Hekla eruption (2000)

– Forward modeling• Water vapor correction

• Future work– Species interaction (spectral)

• Conclusions

Why quantify volcanic emissions:

• Indicators of volcanic activity

• Hazardous to population, wildlife, environment and infrastructure

• Long-lived and climatologically active

• Aircraft hazard mitigation

MODIS bands of interest

28 29 30 31 32


28 29 30 31 32

SO2 band (8.6 m)


28 29 30 31 32

SO2 band (7.3 m)


28 29 30 31 32

ash band (11 m)

MODIS channel

applications

Previous (pre-EOS) work

Species Original Sensor [and channels]

Reference Year MODIS channels

ASTER channels

AIRS channel

sets

Ash AVHRR [4,5] Prata 1989 a,b 31, 32 13, 14 12 -14

Ash AVHRR [4,5] GOES [4,5]

Wen and Rose

1994 31, 32 13, 14 12 -14

Ice AVHRR [4,5] GOES [4,5]

Rose et al., 1995 31, 32 13, 14 12 -14

SO2 TIMS [1-6] Realmuto (et al.)

(1994),1997, 2000

29 - 32 10-14 N/A

SO42- HIRS/2 [5-10] Yu and Rose 2000 30 - 34 N/A 10-15

SO2 TOVS1 [8,11,12] Prata et al., 2003 27, 28, 31

N/A 5

Applications of different retrievals for SO2

Retrieval Application Advantages Disadvantages

TOMS

0.3-0.36 m

Large scale eruptions

Spectrally independent/long

archive

Spatial resolution

AIRS

7.34 m

Large scale eruptions

High spectral resolution

Spatial resolution

MODIS/

TOVS

7.34 m

Mid scale eruptions

Climatologically active SO2

High altitude required

MODIS/ ASTER

8.6 m

Mid-scale – passive

degassing

Monitoring possible

Ash and sulfate interference

Hekla volcano, Iceland, erupted Feb 26, 2000

Hekla MODIS rgb image (7.3, 11 and 12 m)

7.34 m SO2 retrieval - Prata et al, 2004

MODIS retrieval for Hekla, Feb 26 2000 eruption

Approximate aircraft track

SOLVE (NASA DC-8) in situ SO2 measurements and MODIS retrievals show good agreement

Integrated across plume:

SOLVE=248 ppmV

MODIS=241 ppmV

Water vapor interference

The slopes of these lines are in opposition. The ‘split window’ algorithm BTD (11-12 m) is used operationally by VAACs to detect ash and by climatologists to map water vapor. Hence water vapor masks the ash signal.

Atmospheric effects of water

plume height 1.25 km, plume thickness 1.0 kmground T 300 K, NCEP_00.04.26.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

6 7 8 9 10 11 12 13 14 15 16

wavelength m

tran

smis

sion Pu'u O'o

Hekla

plume height 11km, plume thickness 2.0 kmground T 300 K, Hekla_28.02.12.

Forward model justification

• User specifies ‘external’ parameters: ground emissivity, ground temperature, atmospheric profile (water vapor, pressure and temperature as a function of height).

• User specifies ‘plume’ parameters: plume (top and base) altitude, effective radius, variance, refractive index and number density of particles

• The forward model uses MODTRAN to calculate ‘external’ effects and Mie scattering code to calculate ‘plume’ effects

• Can be used to– investigate atmospheric effects on IR retrievals– generate a LUT for multi-species spectra – genrate transmission spectra to be used to correct SO2 maps for

ash/sulftae

Forward model rationale

Forward model results – example spectra

200

210

220

230

240

250

260

270

280

290

300

7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0

wavelength (m)

brig

htne

ss te

mpe

ratu

re (

K)

5.0

6.0

7.0

8.0

9.0

10.0

11.0

12.0

13.0

14.0

15.0

bri

ghtn

ess

tem

pera

ture

(K

)

SHV 12 December

Spurr 28 June

BT difference

Mt. Spurr in tropical atmosphere

0 1

2 3

Brightness temperature

change BTD

Change in cloud area caused by water vapor interference

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

0 10 20 30 40 50 60 70 80

hours since eruption onset

area

(km

2 )

Spurr

'SHV'

Species Interference

3 m andesite

5 m ice

0.5 m 75 % H2SO4

10 g m-2 SO2

Mid-lat atmosphere

Multi-species algorithm development

• Volcanic emissions group (3 professors, 5 PhD students and 2 MS students at two universities) working on various parts of the problem.

• Empircal and theoretical approaches used– Looking at examples of ash-SO2 separation (e.g. Anatahan

2003)

– Forward modeling of multispecies clouds

– Correction of SO2 for ash and sulfate

– Multi-sensor comparisons (TOMS, AIRS, TOVS, ASTER)

• Several eruptions targeted, work in progress

Conclusions

• The development of the 7.3 m algorithm has been a significant advance in quantifying volcanic SO2 (limited species interaction, works at night).

• Hekla-DC8 interaction provides unprecedented ground-truthing opportunity.

• Forward modeling can be used to quantitatively determine the effects of different water vapor concentrations on the ‘split-window’ signal.

• Water vapor more strongly affects clouds that are optically thinner as relative proportions of signal from the underlying ground (and water vapor) increase.

• A multi-species algorithm is the holy grail of volcanic emission remote sensing. Only through MODIS’s ability to detect and quantify more than one species has the problem been (a) illuminated and (b) potentially solvable.

i. matthew watson, mtu and university of bristol, uk remote sensing of volcanic emissions using...

Documents

modis aster

modis bands

na5 slide

modis retrievals

modis channel applications

sulfate interference

hekla modis rgb image

mid scale eruptions