the retrieval of snow properties from space: theory and applications a. a. kokhanovsky 1, m. tedesco...

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The retrieval of snow properties The retrieval of snow properties from space: theory and applications from space: theory and applications A. A. Kokhanovsky 1 , M. Tedesco 2,3 , G. Heygster 1 , M. Schreier 1 , E. P. Zege 4 1) University of Bremen, Bremen, Germany 2) University of Maryland, Baltimore County, USA 3) NASA – Goddard Space Flight Center, Maryland, USA 4) Institute of Physics, Minsk, Belarus [email protected].

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Page 1: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

The retrieval of snow properties from The retrieval of snow properties from space: theory and applicationsspace: theory and applications

A. A. Kokhanovsky1 , M. Tedesco2,3, G. Heygster1 , M. Schreier1, E. P. Zege4

1) University of Bremen, Bremen, Germany2) University of Maryland, Baltimore County, USA3) NASA – Goddard Space Flight Center, Maryland, USA4) Institute of Physics, Minsk, Belarus

[email protected]

Page 2: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

IntroductionIntroduction

A new snow retrieval algorithm that makes use of visible and near-infrared measurements in which snow is modeled as a semi-infinite weakly absorbing medium is developed

The shape of grains is accounted for by means of a fractal snow grain model

The technique is applied to study the changes of snow properties before and just after snow fall in Colorado as seen by two MODIS sensors on TERRA and AQUA satellites

The snow grain size and snow albedo have been retrieved from AATSR onboard ENVISAT data over Greenland

Preliminary comparisons with ground measurements have been performed

Page 3: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

1. Snow physical model

Page 4: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

1. Snow physical model

semi-infinite horizontally homogeneousplane-parallel medium

composed of fractal ice grains suspended in air

SunSatelliteclear sky: • gases • aerosols

Page 5: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

2. Snow optical model

g=0.75 in the visible

Page 6: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

0

0 00

1-( ) ( )( , , ) , s= 4

4( ) 3 1-g ice

a b c p dR d

3. Snow radiative transfer model

0.087 0.014( ) 11.1 1.1p e e

- a=1.247, b = 1.186 and c= 5.157

- the function p is the snow grain phase function

Snow spectral reflectivity

R0 = Reflectivity of a semi-infinite snow layer at zero absorption

0 0 0 0( , , ) ( , , ) exp( 4 ( , , ))R R sf

0 0 00

0 0

( ) ( )( , , )

( , , )

K Kf

R

Escape function

Kokhanovsky and Zege, 2004; Appl. Optics

0 0 0

31 2cos

7K

cos cos

0

0

cos , cos

sin , sin

Kokhanovsky, 2006; Optics Letters(methane adsorption;Domine et al., 2006)

Page 7: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

3. Snow radiative transfer model: albedo determination

0 0 0 0( , , ) ( , , ) exp( 4 ( , , ))R R sf

exp( 4 )r s

Reflectivity:

Albedo:

0( , , )0 0 0( , , ) ( , , ) fR R r

0 0

0 0

49 ( , , ) ( , , )exp ln

9 1 cos 1 cos ( , ,clear clear

pol

R Rr

R

Page 8: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

3. Snow radiative transfer model

0 0 0

0 0

36 1 2 1 2( , , ) ( , , ) exp( )

49 ( , , ) iceR R dR

0 1

•grain size d

•spectral snow albedo r

exp 4 icer d

Page 9: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

4. Validation: Hokkaido

0 20 40 60 800.0

0.2

0.4

0.6

0.8

1.0

1.2

2210nm

1240nm

1050nm

545nm

45 degrees

refle

ctio

n fu

nct

ion

observation zenith angle, degrees

0 20 40 60 800.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

2210nm

1240nm

1050nm

545nm

90 degrees

refle

ctio

n fu

nct

ion

observation zenith angle, degrees

0 20 40 60 800.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

2210nm

1240nm

1050nm

545nm

180 degrees

refle

ctio

n fu

nct

ion

observation zenith angle, degrees

Solar zenith angle=54deg

Page 10: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

4. Validation: Hokkaido

0 20 40 60 800.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

545nm

theory

180

90 45

0

refle

ctio

n fu

nct

ion

observation angle, degrees

0 20 40 60 800.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

theory

experiment

2210nm

1240nm

1050nm

545nm

0 degrees

refle

ctio

n fu

nct

ion

observation zenith angle, degrees

Page 11: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

4. Validation: Antarctica

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.40.0

0.2

0.4

0.6

0.8

1.0

sph

eri

cal a

lbe

do

wavelength, m

0.19mm

ExperimentHudson et al., 2006JGR

Page 12: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

4. Validation: North Pole

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.60.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

R=0.94exp(-3.5(d)0.5)

refle

ctio

n fu

nct

ion

wavelength, micrometers

theory (d=0.12mm) experiment

DAMOCLES IP 2005-2009: Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies

Page 13: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.4

1

0.4

6

0.5

3

0.6

1

0.6

9

0.7

9

0.9

1

1.0

4

1.1

8

1.3

5

1.5

5

1.7

7

2.0

2

2.3

1Wavelength [micron]

Sp

he

rica

l A

lbe

do

100 micron

200 micron

400 micron

800 micron

Sensitivity of albedo to grain size

4. Satellite retrievals: grain size from MODIS data

2002

1999

Band 5Band 4

Band 6

MODIS Band 5 offers sensitivity to grain size

Page 14: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

Multi-scale, multi-sensor approach to build comprehensive data set needed to meet NASA Earth Science Enterprise science objectives.

First application to MODIS First application to MODIS data: The CLPX datasetdata: The CLPX dataset

Page 15: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

Elevation and forest cover of Elevation and forest cover of the test areathe test area

Meters

Forest cover fractionGreen very sparseBlue/Black very denseWhite no forest

Elevation [m]

ground measurements

Global Land Cover

Page 16: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

Grain size retrieval: Feb.19, Grain size retrieval: Feb.19, 20032003

TERRA (AM) AQUA (PM)

micrometers10:30am 1:30pm

cloudsnow

forest

morning: snowfall

Page 17: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

Forest effectForest effect

Grain size values retrieved from MODIS-TERRA vs. those retrieved from MODIS-AQUA on February 19, 2003

Page 18: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

Preliminary Preliminary validation(d=(a+b)/2)validation(d=(a+b)/2)

0

100

200

300

400

500

600

700

800

900

0 100 200 300 400 500 600 700 800 900

Measured grain size [micron]

Retri

eved

gra

in s

ize

[mic

ron]

CLPX-1 campaign, North Park, Colorado, USA, 2003

Terra

Aqua

Feb_21

Feb_22

elevation:2.5km

Page 19: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

5. Satellite retrievals: AATSR

-65 -63 -60 -58 -55 -53 -50

76.5

76.0

75.5

75.0

74.5

74.0

73.5

73.0

72.5

longitude, degrees

latitude, degrees

0.1 0.2 0.3 0.4 0.5

reflectance (1600nm)

-65 -63 -60 -58 -55 -53 -50

76.5

76.0

75.5

75.0

74.5

74.0

73.5

73.0

72.5

longitude, degrees

latitude, degrees

0.3 0.5 0.8 1.0

reflectance (550nm)

0.0 0.1 0.2 0.3 0.4 0.5

0

25

50

75

100

125

150

175

200

225

250

275

300

325

reflectance (1600nm)

frequency

0.3 0.5 0.8 1.0

0

250

500

750

1000

1250

1500

1750

2000

reflectance (550nm)

frequency

Reflectances

Page 20: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

5. Satellite retrievals: AATSR

-65 -63 -60 -58 -55 -53 -50

76.5

76.0

75.5

75.0

74.5

74.0

73.5

73.0

72.5

longitude, degrees

latitude, degrees

0.20 0.40 0.60 0.80 1.00

diameter(mm)

-65 -63 -60 -58 -55 -53 -50

76.5

76.0

75.5

75.0

74.5

74.0

73.5

73.0

72.5

longitude, degrees

latitude, degrees

0.0 0.2 0.4 0.6 0.8 1.0

snow albedo(550nm)

Page 21: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

5. Satellite retreivals

0.1 0.2 0.3 0.4

0

13

25

38

50

63

diameter(mm)

frequency

0.80 0.85 0.90 0.95 1.00

0

13

25

38

50

63

75

albedo (550nm)frequency

Page 22: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

6. Account for snow pollution in the visible

abs soot sootK A c 13ext iceK d c

01 abs sootsoot

ext ice

K cM d

K c

0.75g

0

0

1- s=

3 1-gsoot

sootice

cN d

c

0 0 0 0( , , ) ( , , ) exp( 4 ( , , ))R R sf

22

9, Rayleigh soot particles

2

nA

n

Page 23: The retrieval of snow properties from space: theory and applications A. A. Kokhanovsky 1, M. Tedesco 2,3, G. Heygster 1, M. Schreier 1, E. P. Zege 4 1)University

Observations and future work

A new approach is to be developed (A. Lyasputin, UMBC/NASA; von Hoyningen-Huene, University of Bremen) for simultaneous retrieval of AOT and surface BRDF. This will improve MODIS snow BRDF product.

The cloud mask must be improved. A comprehensive validation and calibration campaign is

needed. This will be performed using measurements in Greenland (M. Tedesco, PI of the Proposal submitted to NASA NNH06ZDA001N-IPY).