Connecting Sensors: SSM/I and QuikSCAT -- the Polar A Train.

Connecting Sensors: SSM/I and QuikSCAT -- the Polar A Train

NSIDC’s 30th Anniversary, 25 October 2006

Introduction• Remote sensing in the microwave portion of the electromagnetic

spectrum have found many applications in cryospheric research.

• Nearly 30 years of continuous and consistent PM observations allow for studies on changes in several cryospheric variables. 1978 – 1987: SMMR 1987 – present: successive SSM/I 2002 – present: AMSR-E

• Active observations (e.g. scatterometers) also started in the late 1970s, but the record is not continuous or consistent. 6/78 - 9/78: SASS – Ku Band (Seasat) 6/96 – 5/97: NSCAT – Ku Band (ADEOS I) 2/92 – 1/01: EScat – C Band (ERS-1/2) 7/99 – present: SeaWinds on QuikSCAT (Ku Band) 12/02 – present: SeaWinds on ADEOS II (Ku Band)


Science with Passive Microwave

Sea ice mapping



Greenland Melt

Steffen and Huff

Since 1979, the area that experiences melt has increased at a rate of ~18%/decade.



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Significant trends in late spring and early summer indicating decreasing snow cover

Trend (million sq-km/decade)

Changes in northern hemisphere snow cover


Science with Active MicrowaveAntarctic Iceberg Tracking

• QuikSCAT tracks Antarctic icebergs (used operationally at NIC) Icebergs have high backscatter compared to sea ice and open

ocean (nearly 55% of all iceberg locations reported by NIC are based on QuikSCAT).

Iceberg Tracks from 1978 & 1992-2002

1999

Julienne Stroeve

In 1999, a large 125 x 80km iceberg designated B10A by NIC was observed in a shipping lane in the first QuikSCAT enhanced resolution scatterometer images.


Science with Active Microwave

• Time series analysis of the radar backscatter can be used to determine the onset of melt and re-freezing.

• Note: melt days over open ocean are exaggerated since as the ice edge retreats each pixel previously representing sea-ice now resides over open ocean and accumulates melt days as the summer season progresses.


Science with Active Microwave

• Ice extent is easily defined using active microwave data (and doesn’t require a tuning)

Ice Extent


Passive vs. Active• Both passive and active remote sensing offer:

Large spatial coverage; High temporal resolution; Ability to penetrate clouds; Derive similar geophysical variables (e.g. snow and ice extent,

sea surface wind vectors, melt, etc).• Passive microwave pros:

Long consistent time-series of observations.• Passive microwave cons:

Variation of surface emissivity and atmospheric water vapor create problems for algorithms.

• Active microwave pros (Scatterometers): Less sensitivity to weather effects.

• Active microwave cons (Scatterometers): Short time-scale.


Scatterometer Climate Record Pathfinder (SCP)

• SCP has been generating high resolution scatterometer imagery to support cryospheric studies from QuikSCAT, NSCAT, ERS and SASS). http://www.scp.byu.edu/

• Current products include: Global high resolution data (2.225 and 4.5 km/pixel); Antarctic ice berg tracking (daily at 2.225 km/pixel); Ice motion (daily at 25-km); Ice extent (daily at 2.225 km/pixel).

• NSIDC recently acquired sea ice extents from QuikSCAT spanning 1999-2004. Daily at 2.225 and 4.5 km/pixel for Arctic and Antarctic


REaSON CAN Project

• New research being done: Incorporation of ADEOS-II Seawinds to ensure continuous

Ku-band time-series; Addition of sea ice motion products and sea ice extent maps

derived from combined active/passive microwave data sets; Addition of seasonal melt-freeze products from combined

active/passive microwave data sets; Seasonal change maps of Greenland and Antarctica from

combined active/passive data; Integrated seasonal change maps of land ice/sea ice/cold

regions land cover; Antarctic iceberg drift database continuation.


Blending Active and Passive Microwave

• Generation of enhanced resolution SSM/I and AMSR brightness temperatures to match enhanced resolution scatterometer datasets. Enhanced resolution images are produced by

combining all passes in a single day to improve the spatial resolution of the data at the expense of temporal resolution.

NSIDC currently has enhanced resolution SSM/I data from 1995-2005 at pixel size of 8.9 km for 19-37 GHz and 4.45 km for 85 GHz.


Examples of SSM/I HIRZ

HIRZ

85V

January 1 2004


Image Artifacts

Artifacts arise from Tb changes from pass to pass during the day

7 September 2002


AMSR Local Time of Day


Animation of AMSR-E High Resolution Tbs

36.5 V

AMSR-E 36.5V from 19 June to 6 October 2002


Melt Onset/Freeze-up• Passive and active microwave

radiometers respond to liquid water content of snow Increase in passive microwave Tbs

because of decrease in volume scattering (thus increased emissivity)

Decrease in backscatter because of decrease in volume scattering

Before melt

After melt

13.9 GHz normalized radar cross section at 40o incidence angle before (top) and after (bottom) a major melt event. Note the dramatic change in backscatter over the sea ice and along the periphery of the Greenland ice sheet (http://www.scp.byu.edu).

Enhanced resolution NSCAT

May 22-27

June 18-23June 18-23


Arctic Wide Melt Onset/Freeze• B. Holt and K. McDonald are

developing melt onset/freeze-up across the polar region (includes sea ice and land) using a synthesis of Ku-band and passive microwave data.

Transect that extends from interior Alaska across the Chukchi and Beaufort Seas (inclusive of boreal forest, tundra, the Beaufort coastline, seasonal and multiyear sea ice.

2001

Melt onset

Freeze-up

Broken/thin ice floes

Brooks Range


Case Study, Antarctic Peninsula

• Study by Kunz and Long (2006) developed melt detection from QuikSCAT and compared to SSM/I

• QuickSCAT method: PR ratio (v

o – ho) together with h

o

Melt classification is determined using ML estimate of ice state

• Passive microwave method: HR = Tb(19H) – Tb(37H) (Anderson, 1987)

Tb-Tb(19V) > Tbdry + (1-)Tb

wet (Ashcroft and Long, 2006)

XPGR = Tb(19H) – Tb(37V) (Abdalati and Steffen, 2001) Tb(19H) + Tb(37V)

Julienne Stroeve

not a true PR since the vertical and horizontal polarization measurements are from different incidence angles

Julienne Stroeve

Both the HR and XPGR were developed for Greenland


Melt Detection: Antarctica

When QuikSCAT backscatter decreases, there is usually a rise in SSM/I brightness temperatures

Kunz and Long (2006)

Julienne Stroeve

HR method is not portable for use in melt detection on Antarctic ice

Julienne Stroeve

ML method appears more sensitive to melt conditions in some cases than the PM methods.For location 3, the Tb-a method does not distinguish any melt events during 2001-2002 summer.


Melt Detection: Antarctica• Melt onset dates from

QuikSCAT are usually a few days earlier than those detected by XPGR and Tb-.

• Better consistency is found between QuikSCAT and Tb-than with XPGR.

• While radiometer data tend to be more sensitive to melt onset, it easily saturates, and is sensitive to weather.

Kunz and Long (2006)


Ice Extent

• Both active and passive are useful for detecting the ice edge.

• However, passive microwave is affected by weather effects. Thus the reason for selecting thresholds for the ice edge

• Scatterometer ice edge does not require tuning but it doesn’t infer ice concentration. V/H of SeaWinds does show sensitivity to ice

concentration and ice type (at medium-to-high concentrations)

julienne

Scatterometry has imporved accuracy over passive microwave for ice/no ice discrimination during ice-edge advance due to thermodynamic ice growth.


Ice Extent Differences

QuikSCAT Ice Extent SSM/I Ice Concentration

1 January 2001


Ice Extent Differences

Seasonal difference between QuikSCAT and SSM/I ice extents – match better during austral winter

Antarctic Ice Extent (2001)

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In general, QuikSCAT shows more Antarctic sea ice (~600,000 sq-km) during austral summer and 3,000 sq-km more during austral winter.


Ice Extent Blending Ideas• Fusion of scatterometer and radiometer should

enable improved characterization of the ice edge, ice concentration and type.

• Preliminary results by D. Long suggest scatterometry has improved accuracy during ice-edge advance from thermodynamic growth.

• Scatterometer data can help define the ice edge when weather effects the passive microwave signal (make the ice edge less patchy).

• Scatterometer can detect melting well and therefore flag the use of different concentration tables for melting ice.


Ice Motion

• Work by Zhao et al. (2002) and Liu et al (1999) found that regions for which sea ice motion derived from passive microwave was erratic or impossible, ice motion could be determined with scatterometer data (and vice versa).

• Scatterometry doesn’t experience the problems caused by water vapor in SSM/I 85 GHz channel. Thus, scatterometry data can be used to fill in poorly

tracked regions.


Blended SSM/I and QuikSCAT Ice Motion

• Merged Arctic sea ice drift map Provides more

complete coverage than from a single data source

• RMS difference of satellite results from buoy speed is less than 3 cm/s

http://www.scp.byu.edu/data/Quikscat/IceMo/Quikscat_icemotion.html


Summary

• Fusion of active and passive microwave observations shows great promise in polar climate and change studies.

• This is a relatively new research area, with much work still to be done.

• The availability of enhanced resolution passive and active microwave observations will greatly facilitate research.

• Future blended products will include sea ice extent, ice type, melt onset/freeze-up and ice motion. Data will be made available at NSIDC

Connecting Sensors: SSM/I and QuikSCAT -- the Polar A Train.

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