Applications of Remote Sensing:The Cryosphere (Snow & Ice)

Applications of Remote Sensing:The Cryosphere (Snow & Ice)

Menglin Jin, San Jose Stte University

Outline Physical principles International satellite sensors enabling remote sensing of

tropospheric aerosols– ESMR, SMMR, SSM/I, AVHRR, MODIS, AMSR

Instrument characteristics– Spacecraft, spatial resolution, swath width, sensor

characteristics, and unique characteristics Sea ice and snow retrieval from existing satellite systems Future capabilities Opportunities for the future

Credit: Michael D. King, NASA GSFC

Sparsely distributed ice floes as viewed from a ship in the Bering Sea

Sea Ice of Different Forms and Perspectives

Sea Ice of Different Forms and Perspectives

Photograph courtesy of Claire Parkinson

Expansive ice field, as viewed from an aircraft in the central Arctic

Sea Ice of Different Forms and Perspectives

Sea Ice of Different Forms and Perspectives

Photograph courtesy of Claire Parkinson

Close-up of newly formed ice in the Bering Sea

Sea Ice of Different Forms and Perspectives

Sea Ice of Different Forms and Perspectives

Photograph courtesy of Claire Parkinson

Ice floes separated by a lead, as viewed from an aircraft over the central Arctic

Sea Ice of Different Forms and Perspectives

Sea Ice of Different Forms and Perspectives

Photograph courtesy of Claire Parkinson

Thin sheets of ice, as viewed from an aircraft

Sea Ice of Different Forms and Perspectives

Sea Ice of Different Forms and Perspectives

Photograph courtesy of Koni Steffen

Several-months-old ice bearing the weight of a helicopter, as viewed from ground level in the Bering Sea

Sea Ice of Different Forms and Perspectives

Sea Ice of Different Forms and Perspectives

Photograph courtesy of Claire Parkinson

Nimbus 5– Electrically Scanning Microwave Radiometer (ESMR)

» December 1972-1976» single channel (19 GHz = 1.55 cm) conically scanning

microwave radiometer Nimbus 7

– Scanning Multichannel Microwave Radiometer (SMMR)» October 1978-August 1987» 10 channel (five frequency and dual polarization) conically

scanning microwave radiometer Defense Meteorological Satellite Program (DMSP)

– Special Sensor Microwave Imager (SSM/I)» June 1987-present» 7 channel (three frequencies with both vertical and

horizontal polarization + 1 frequency with horizontal polarization only)

Remote Sensing of Sea Ice from Passive Microwave RadiometersRemote Sensing of Sea Ice from Passive Microwave Radiometers

NASA, Aqua– launches July 2001– 705 km polar orbits, ascending

(1:30 p.m.) Sensor Characteristics

– 12 channel microwave radiometer with 6 frequencies from 6.9 to 89.0 GHz with both vertical and horizontal polarization

– conical scan mirror with 55° incident angle at Earth’s surface

– Spatial resolutions:» 6 x 4 km (89.0 GHz)» 75 x 43 km (6.9 GHz)

– External cold load reflector and a warm load for calibration

» 1 K Tb accuracy

Advanced Microwave Scanning Radiometer (AMSR-E)

Advanced Microwave Scanning Radiometer (AMSR-E)

Thicker snow results in lower microwave brightness temperatures

Microwave Scattering of Snow Cover

Microwave Scattering of Snow Cover

From Parkinson, C. L., 1997: Earth from Above

Higher rate of microwave emission from sea ice than from open water

Emissivities indicated are for wavelength of 1.55 cm (19 GHz)

Satellite Detection of Sea IceSatellite Detection of Sea Ice

From Parkinson, C. L., 1997: Earth from Above

Spectra of Polar Oceanic Surfaces over the SMMR Wavelengths

Spectra of Polar Oceanic Surfaces over the SMMR Wavelengths

50

0.50.00

1.0 2.5Wavelength (cm)

Bri

gh

tness

Tem

pera

ture

(K

)

100

150

200

250FY Ice V

FY Ice H

MY Ice V

MY Ice H

Open Ocean H

1.5 2.0 3.0 3.5 4.0 4.5 5.0

Open Ocean V

March 8-10, 1974 September 16-18, 1974

<132.5 K ≥ 281.5 K200 K160 K 240 K140 K 180 K 220 K 260 K

Brightness Temperature of Polar Regions from Nimbus 5 ESMR

Brightness Temperature of Polar Regions from Nimbus 5 ESMR

Tb (19 GHz)Parkinson ( 1997)

March 1986

September 1986

100%

80%

60%

40%

20%

≤12%

Monthly Average Sea Ice Concentrations from Nimbus 7

SMMR

Monthly Average Sea Ice Concentrations from Nimbus 7

SMMR

From Parkinson, C. L., 1997: Earth from Above

March 1986 September 1986100%

80%

60%

40%

20%

≤12%

Monthly Average Sea Ice Concentrations from Nimbus 7

SMMR

Monthly Average Sea Ice Concentrations from Nimbus 7

SMMR

From Parkinson, C. L., 1997: Earth from Above

February 1999 September 1999100%

80%

60%

40%

20%

≤12%

Monthly Average Sea Ice Concentrations from SSM/IMonthly Average Sea Ice

Concentrations from SSM/I

South Polar Region

North Polar Region

Location Maps for North and South Polar Regions

Location Maps for North and South Polar Regions

From Parkinson, C. L., 1997: Earth from Above

Decreases in Arctic Sea Ice Coverage as Observed from

Satellite Observations

Decreases in Arctic Sea Ice Coverage as Observed from

Satellite Observations

C. L. Parkinson, D. J. Cavalieri, P. Gloersen, H. J. Zwally, and J. C. Comiso, 1999: J. Geophys. Res.

November 1978 - December 1996

November 1978 - December 1996

Monthly Arctic Sea Ice Extent Deviations

Monthly Arctic Sea Ice Extent Deviations

–34300 ± 3700 km2/year

C. L. Parkinson, D. J. Cavalieri, P. Gloersen, H. J. Zwally, and J. C. Comiso, 1999: J. Geophys. Res.

Yearly and Seasonal Ice Extent TrendsYearly –2.8%/decadeWinter –2.2%/decadeSpring –3.1%/decadeSummer –4.5%/decadeAutumn –1.9%/decade

Trends in Arctic Sea Ice CoverageTrends in Arctic Sea Ice Coverage

C. L. Parkinson, D. J. Cavalieri, P. Gloersen, H. J. Zwally, and J. C. Comiso, 1999: J. Geophys. Res.

Data Sources For November 1978 – August

1987, the Scanning Multichannel Microwave Radiometer (SMMR) on NASA’s Nimbus 7 satellite

Since mid-August 1987, the Special Sensor Microwave Imagers (SSM/Is) on satellites of the Defense Meteorological Satellite Program

37,000 km2/year decrease of sea ice area over a 19.4 year period observed from satellite

19,000 km2/year decrease in sea ice area over a 46 year period based on Geophysical Fluid Dynamics Laboratory (GFDL) model

Observed Northern Hemisphere Sea Ice Decreases Placed in a

Climate Context

Observed Northern Hemisphere Sea Ice Decreases Placed in a

Climate ContextProbability that an observed sea-ice-extent trend results from natural climate variability, based on a 5000-year control run of the GFDL General Circulation Model (GCM) Open Circle

– Observed 1953-1998 trend, updated from Chapman and Walsh (1993)

Open Square– Observed 1978-

1998 trend, updated from Parkinson et al. (1999)

Sea Ice TrendsSea Ice Trends

Probability that observed trends result from natural climate variability– 1953 – 1998 trend < 0.1 %– 1978 – 1998 trend < 2 %

Demonstrates how scientists have attempted to take the satellite data record and put it into context of man’s impact on climate

Vinnikov, Robock, Stouffer, Walsh, Parkinson, Cavalieri, Mitchell, Garrett, and Zakharov, published in the December 3, 1999 issue of Science

19 GHz Vertical Polarization

<132.5 K ≥ 281.5 K200 K160 K 240 K140 K 180 K 220 K 260 K

Brightness Temperature of Polar Regions from SSM/I

Brightness Temperature of Polar Regions from SSM/I

37 GHz Vertical Polarization

March 14, 1997

<132.5 K ≥ 281.5 K200 K160 K 240 K140 K 180 K 220 K 260 K

Brightness Temperature of Polar Regions from SSM/I

Brightness Temperature of Polar Regions from SSM/I

March 14, 1997

85 GHz Vertical Polarization

180

240200180 220

Brightness Temperature Scatter Diagram for Odden Region and

Greenland Sea

Brightness Temperature Scatter Diagram for Odden Region and

Greenland SeaEarly Ice Maximum Extent of

Bulge

260 240200180 220 260Brightness Temperature (V37) Brightness Temperature (V37)

Bri

gh

tness

Tem

pera

ture

(V

19

)

200

220

240

260November 21, 1996

January 18, 1997

O O

A

A

D

D

Odden

Stu

dy

Are

a

(pan

cakes

or

nilas

)

Thick ic

e

(conso

lidate

d regio

n)

180

240200180 220

Brightness Temperature Scatter Diagram for Odden Region and

Greenland Sea

Brightness Temperature Scatter Diagram for Odden Region and

Greenland SeaMaximum Extent of

TongueIce Melt & Formation of Ice

Island

260 240200180 220 260Brightness Temperature (V37) Brightness Temperature (V37)

Bri

gh

tness

Tem

pera

ture

(V

19

)

200

220

240

260March 14, 1997

April 14, 1997

Brightness Temperature of Polar Regions from SSM/I

Brightness Temperature of Polar Regions from SSM/I

February 26, 1987

SSM/I AVHRR

Brightness Temperature of Polar Regions from SSM/I

Brightness Temperature of Polar Regions from SSM/I

March 15, 1987

SSM/I AVHRR

Pucahirca, Peru– October 1991– Latitude of 9°S– Foreground altitude is

5325 m

Photograph courtesy of Lonnie Thompson

Snow Cover in the Northern AndesSnow Cover in the Northern Andes

Nimbus 7/SMMR– Uses two horizontally polarized microwave frequencies (18

and 37 GHz)» snow scatters less at the lower frequency (longer

wavelength)» the thicker the snow the greater the difference in

brightness temperature between 18 and 37 GHzz = 1.59[Tb(18 GHz) – Tb(37 GHz)]

wherez = snow thickness in cm

» restricted to ice-free land with snow thickness 5 ≤ z ≤ 70 cm

Remote Sensing of Snow Cover & Thickness from Passive Microwave

Radiometers

Remote Sensing of Snow Cover & Thickness from Passive Microwave

Radiometers

February 1986 March 1986

70 cm

55 cm

40 cm

25 cm

10 cm

≤4 cm

Monthly Average Snow Thickness from Nimbus 7 SMMR

Monthly Average Snow Thickness from Nimbus 7 SMMR

From Parkinson, C. L., 1997: Earth from Above

April 1986 May 1986

70 cm

55 cm

40 cm

25 cm

10 cm

≤4 cm

Monthly Average Snow Thickness from Nimbus 7 SMMR

Monthly Average Snow Thickness from Nimbus 7 SMMR

From Parkinson, C. L., 1997: Earth from Above

Location Map for North Polar Region

Location Map for North Polar Region

From Parkinson, C. L., 1997: Earth from Above

February 1979 February 1981

70 cm

55 cm

40 cm

25 cm

10 cm

≤4 cm

Monthly Average Snow Thickness from Nimbus 7 SMMR

Monthly Average Snow Thickness from Nimbus 7 SMMR

From Parkinson, C. L., 1997: Earth from Above

NOAA/AVHRR-3– Uses reflectance at 1.6 µm where snow and ice absorb solar

radiation much greater than water or vegetation» Advantage

• high spatial resolution (4 km GAC, 1.1 km LAC)» Disadvantage

• affected by cloud cover• observations possible only at night• difficult to detect snow in deep forests

Terra/MODIS– Uses reflectance at 1.6 µm– Higher spatial resolution of AVHRR (global at 1 km)– Makes use of better cloud mask for distinguishing clouds

from snow and land surfaces (and shadows)

Remote Sensing of Snow Cover from Shortwave Infrared

Radiometers

Remote Sensing of Snow Cover from Shortwave Infrared

Radiometers

MODIS Snow Cover Compared to Historical Snow Record

MODIS Snow Cover Compared to Historical Snow Record

(1966-present)

March Average

February Average

Cloud

March 5-12, 2000