Retrieval of snow physical parameters with consideration of underlying vegetation 

Teruo Aoki (Meteorological Research Institute), Masahiro Hori (JAXA/EORC)Knut Stamnes, Wei Li (Stevens Institute of Technology) GLI Snow

Products

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1000

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Apr.14,2003(Barrow,GLI)

Apr.26,2003(Barrow,GLI)

Feb.24,2002(Saroma,MODIS)

Feb.5,2001(Saroma,ASTER)

Sate

llite

der

ived

sno

w g

rain

size

(μm）

Ground measured snow grain size (μ m）

Layer1(0-0.5cm) Layer2(0.5-3cm) Layer3(3-5.5cm)

Grain Size

Ground Truth vs. Satellite-derived snow grain size (left) and impurity (right)

GLI Cloud-Free Composite (April 2~30, 2003)

R:678, G:865, B:460nm

Global Imager (GLI) aboard the ADEOS-II satellite launched in December 14, 2002 observed sunlight reflection and infrared emission from the Earth's surface globally, and detected various geophysical parameters (e.g. cloud properties, surface temperature, vegetation, and snow/ice cover). Although the satellite stopped operation on October 25 due to a power source problem, GLI data obtained during the 7-month (Apr. - Oct., 2003) scientific operation phase will contribute to investigation of global hydrological cycle and radiation budget that are primal factors of the global climate change. This paper presents preliminary results of snow parameters retrieval from one-month (April 2003) GLI data. Also their initial validation results are shown.

Spatial distribution of snow grain size indicates

significant latitudinal dependence which is very much consistent with that of snow temperature. There is a belt where snow grain size rapidly increases due to high snow temperature of around the melting point of ice. Snow impurity distribution is somewhat different from those mentioned above. Greenland and the northern Canadian Arctic region are identified as the cleanest area in the Arctic, while sea ice area in the Arctic Ocean, particularly north of Siberia, is likely to be polluted by atmospheric aerosols (or covered with shallower snow).

Increase of snow grain size

Snow pollution & TAir rising

Snow warming

Snow warming

Air pollution & Global warming

Positive feedback

Acceleration of snow melting

Changes of hydrological cycle and radiation budget on the earth

VIS albedo decrease

NIR albedo decreasech19(865nm)

ch5(460nm)GLI

Positive feedback in the snow melting process

Impurity

Orange colored pixels indicate snow covered area contaminated with vegetation (positive NDVI).

Snow grain size exhibits “two-steps” dependence on snow surface temperature (moderate slope in the sintering process [T < 270K] and steep in the melting process [T > 270K]) (left figure). Snow impurity also seems to correlate with snow temperature (right figure). These dependences indicate the close connection among those parameters.

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Apr.14,2003(Barrow,GLI)

Apr.26,2003(Barrow,GLI)

Sate

llite

der

ived

sno

w impu

rity

(pp

mw）

Ground measured snow impurity (ppmw）

Impurity

In the cryospheric scientific field “snow grain size” and

“mass fraction of impurities mixed in snow layer” are to be retrieved together with the traditional “snow/sea-ice cover extent” as GLI standard products. Those snow parameters are of significant importance to understand how and where the snow melting process proceeds on the global scale being influenced by air pollution and the global warming.

Grain size & Impurity vs. Temperature

m.p.

Satellite vs. Ground truth

Temperature

Melting Snow Belt

Validation Site (April 14, 26, 2003)

Those pixels are eliminated in the following processing of the retrieval of snow parameters.

Snow pollution decreases the visible snow albedo, while the growth of snow grains decreases the albedo in the near infrared region. GLI can detect both the changes in snow layer (surface ~ 10cm in depth) by observing the top of atmosphere (TOA) reflectances of snow covered area at the wavelength of 460nm (GLI ch5) and 865nm (ch19).

Dependence of snow albedo upon impurity and grain size

Grain Size