MODIS Atmosphere Data Products and Science Results

MODIS Atmosphere Data ProductsMODIS Atmosphere Data Productsand Science Resultsand Science Results

Steven Platnick 1,2

Michael D. King,2 W. Paul Menzel,3 Yoram J. Kaufman,2

Steve Ackerman,4 Didier Tanré,5 and Bo-Cai Gao,6

1 University of Maryland Baltimore County

2 NASA Goddard Space Flight Center3 NOAA/NESDIS, University of Wisconsin-Madison

4 University of Wisconsin-Madison5 Université des Sciences et Technique de Lille

6 Naval Research Laboratory

S. Platnick, Director's Seminar/Earth Sciences Directorate Briefing, 21 May 2001

OutlineOutline

• MODIS atmosphere products• Granule level (5 min.) product examples• Global examples• Summary


MODIS atmospheres

MODIS Atmosphere ProductsMODIS Atmosphere Products

• Pixel level products (Level 2)


MODIS atmospheres

– cloud masking/detection (U. Wisc.)

– clouds: optical, microphysical properties (GSFC); cloud-top properties (U. Wisc.); thin cirrus (NRL)

– aerosols: land & ocean optical properties (GSFC, U. Lille)

– clear sky: temperature, humidity, O3 (U. Wisc.)

• Gridded time-average products (Level 3)

– daily, 8 day, monthly composites– 1˚ x 1˚ equal angle grid– mean, standard deviation, marginal and joint probability distributions

MODIS atmospheres


MODIS Atmosphere Products, cont.MODIS Atmosphere Products, cont.

Applications: climate change studies and modeling, numerical weather prediction (future sensors),

fundamental research

http://modis-atmos.gsfc.nasa.gov


Global mean radiative forcing of the climate Global mean radiative forcing of the climate systemsystem

year 2000, relative to 1750year 2000, relative to 1750(IPCC assessment, Jan. 2001)(IPCC assessment, Jan. 2001)

Rad

iativ

e fo

rcin

g (W

-m-2)

Level of scientific understanding

cool

ing

war

min

g


Global mean radiative forcing of the climate Global mean radiative forcing of the climate systemsystem

year 2000, relative to 1750year 2000, relative to 1750(IPCC assessment, Jan. 2001)(IPCC assessment, Jan. 2001)

Rad

iativ

e fo

rcin

g (W

-m-2)

Level of scientific understanding

cool

ing

war

min

g

Assimilation & Numerical Weather PredictionAssimilation & Numerical Weather Prediction


• algorithms provide a heritage for Visible/Infrared Imager/Radiometer Suite (VIIRS) onboard National Polar-orbiting Operational Environmental Satellite System (NPOESS) in coming decade

• NESDIS/NCEP studying real-time MODIS uses

MODIS atmospheres

• complimentary data for other Terra/Aqua instruments,other missions (e.g., CloudSat ESSP mission,

etc.)

Other ApplicationsOther Applications


MODIS atmospheres

Cloud MaskCloud Mask((S. Ackerman, R. Frey, et al. – U. Wisconsin CIMSSS. Ackerman, R. Frey, et al. – U. Wisconsin CIMSS))

• 1 km nadir spatial resolution day & night, 250 m daytime

• 17 spectral bands (0.55-13.93 µm, incl. 1.38 µm)

– 11 spectral tests (function of 5 ecosystems)

– temporal consistency test over ocean, desert (nighttime)

– spatial variability test over ocean

• 48 bits per pixel, including individual test results, processing path. Clear sky maps.

• input to land, ocean, rest of atmosphere algorithms


Example of 1.38 µm band in cloud detectionExample of 1.38 µm band in cloud detection19 April 2000, 0510 UTC19 April 2000, 0510 UTC

true color composite (R: 0.66, G: 0.86, B: 0.46 µm)


Example of 1.38 µm band in cloud detectionExample of 1.38 µm band in cloud detection19 April 2000, 0510 UTC19 April 2000, 0510 UTC

1.38 µm bandtrue color composite (R: 0.66, G: 0.86, B: 0.46 µm)


Gobi desert dust stormGobi desert dust storm20 March 2001, 0255 UTC20 March 2001, 0255 UTC


MODIS atmospheres

Cloud Top PropertiesCloud Top Properties((P. Menzel, L. Gumley, et al. – NOAA NESDIS, U. Wisc. CIMSSP. Menzel, L. Gumley, et al. – NOAA NESDIS, U. Wisc. CIMSS))

• Cloud top pressure, temperature, effective emissivity

• 5 km spatial resolution, day & night

• CO2 Slicing technique (5 bands, 12.0-14.2 µm)

– most accurate for high and mid-level clouds

– technique previously applied to HIRS (NOAA

POES, 20 km)

MODIS 1st satellite sensor capable of

CO2 slicing at high spatial resolution


MODIS atmospheres

Cloud Optical, Microphysical PropertiesCloud Optical, Microphysical Properties((M. D. King, S. Platnick, M. Gray, E. Moody, et al. – NASA M. D. King, S. Platnick, M. Gray, E. Moody, et al. – NASA

GSFC, UMBCGSFC, UMBC))

• Optical thickness, particle size (effective radius), water path, thermodynamic phase

• 1 km spatial resolution, daytime only, liquid water and ice clouds (using individual cloud mask tests)

• Land, ocean, desert, snow/sea ice surfaces

• Solar reflectance technique VIS- MWIR ( 0.65, 0.86, 1.2, 1.6, 2.1, 3.7 µm)

MODIS 1st satellite sensor with all useful

SWIR, MWIR bands

MODIS SAFARI granule RGB compositeMODIS SAFARI granule RGB composite13 September 2000, 0925 UTC13 September 2000, 0925 UTC

Namibia

Etosha Pan

Angola

marine marine stratocumulusstratocumulus

ER-2 ground track

Namibia

Angola

Botswana

South Africa

Zambia


(>99%)

(>95%)

(>66%)






100

550

700

850

1000

190

212

233

255

320

pc (mb) Tc (K)

400

250

298

277

QuickTime™ and aCompact Video decompressor

are needed to see this picture.

Cloud-top Pressure, TemperatureCloud-top Pressure, Temperature


Cloud Optical Thickness, Effective RadiusCloud Optical Thickness, Effective Radius

0

20

30

40

50

0

10

20

30

60

10

50

40

c re (µm)




ecosystem= MOD12 ecosystem= MOD12 IGBP + USGS water + IGBP + USGS water + tundra classificationtundra classification

surface albedo = surface albedo = ecosystem + ecosystem +

MOD43 (Strahler, Schaaf, MOD43 (Strahler, Schaaf, et al.) aggregationet al.) aggregation

band1 2 5 6 7

Uncorrected Image Cirrus Image (1.38 µm) Cirrus Corrected Image

Correction of Imagery for Thin Cirrus Correction of Imagery for Thin Cirrus (B.-C. Gao, P. Yang – NRL, UMBC)(B.-C. Gao, P. Yang – NRL, UMBC)

2 September 20002 September 2000CanadaCanada


Aerosol Optical, Microphysical PropertiesAerosol Optical, Microphysical Properties(Y. Kaufman, D. Tanré, L. Remer, A. Chu, et al. – NASA GSFC, U. Lille)(Y. Kaufman, D. Tanré, L. Remer, A. Chu, et al. – NASA GSFC, U. Lille)

• 10 km spatial resolution, daytime

• Ocean: – spectral optical depth, effective radius, size distribution (fine,

coarse mode contributions)

– 0.55, 0.65, 0.86, 1.2, 1.6, 2.1 µm bands

• Land:

– optical depth over dark pixels (vegetation)

– uses correlation between visible (0.47, 0.65 µm) and 2.1 µm surface reflectance


MODIS atmospheres





2.0

1.5

1.0

0.5

0.0

aerosol optical depthaerosol optical depth

203

0 km

600 km

400 km

Venice

2330 km

2.0

1.0

0.0aerosol optical depth (0.55 µm)

Ispra

Continental to Regional Scale PollutionContinental to Regional Scale Pollutionin Northern Italyin Northern Italy


25 September 200025 September 2000


Aerosol Optical Depth, Effective Radius Aerosol Optical Depth, Effective Radius

0.0

0.2

0.3

0.4

0.5

0.0

0.6

1.2

1.8

2.4

0.1

a (0.55 µm) re(µm)



Total points = 315; excluding Venice, El Arenosillo sites

0.47 µm

R = 0.91 R = 0.85

0.66 µm

0 40 10020 60 80

Chu et al., GRL, 2001


Land retrieval Land retrieval frequency (%)frequency (%)

Global Global AERONET AERONET

comparisonscomparisons


• Moisture and temperature profiles, precipitable water, atmospheric stability indices (15 MWIR, IR bands)

• column ozone (9.6 µm band)

• 5 km spatial resolution (GOES 3x3 pix ~ 30 km min)

Atmospheric moisture, temperature, ozoneAtmospheric moisture, temperature, ozone(P. Menzel, L. Gumley – NOAA NESDIS, U. Wisconsin)

• 1 km spatial resolution (0.91, 0.94 µm water vapor bands)

• over clear sky land surface and clouds, uses correlation between NIR and 1.2 µm reflectance

MODIS atmospheres

Daytime precipitable waterDaytime precipitable water(B.-C. Gao – NRL)

R: 0.65, G: 0.86, B: 0.46

April 12, 2000

Precipitable Water Vapor (cm)

Atmospheric Water VaporAtmospheric Water Vapor


R: 0.65, G: 0.86, B: 0.46

11 May 2000upper midwest

Precipitable Water Vapor (mm)Atmospheric Water VaporAtmospheric Water Vapor


MODIS, 5 km

GOES, ~ 40 km (U. Wisc., CIMSS)

MODIS Atmosphere Web site

http://modis-atmos.gsfc.nasa.gov – Images– Validation– News– Staff– References

• ATBDs• Validation Plans• Publications (pdf)

– Tools• Granule locator tools• Spatial and dataset

subsetting• Visualization and analysis

– Data products• Format and content• Grids and mapping• Sample images• Acquiring data


SummarySummary


MODIS atmospheres

• MODIS provides an unprecedented opportunity

for atmospheric studies (36 spectral

channels, high spatial resolution)

• comprehensive set of atmospheric algorithms

• archival of pixel level retrievals, global statistics

• validation activities are high priority (ground-

based, in situ aircraft, other satellites)

• applications to climate studies, future weather

satellite sensors/algorithms and

assimilation

Documents

MODIS Atmosphere Data Products and Science Results