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A Comparison of Passive Microwave Derive Melt extent to Melt intensity Estimated from Combined Optical and Thermal Satellite Signatures Over the Greenland Ice Sheet from 2001-2005

Derrick Lampkin1 and Unquiea Wade2

1Department of Geography , The Pennsylvania State University, University Park PA 168012Department of Math and Computer Science , Elizabeth City State University , Elizabeth City NC 27909

Changes in global climate have implications for various components in the terrestrial system. Anthropogenic climate change is primarily a response to greenhouse gases emitted into the atmosphere. Increases in the amount of atmospheric greenhouses gases are correlated with increases in the earth’s global average temperature. Assessment of the cryosphere’s response to increase in global temperatures is important to understand and predict the long-term behavior of climate change.

Continental ice sheets such as Antarctica and Greenland are vulnerable to the effects of global warming and climate variability. In particular, the Greenland ice sheet is the second largest ice sheet in the world and has a surface extent of about 1.75 x 106 km2 and an ice volume of 2.65 x 106 km3 (Van der Veen, 1991) . The Greenland ice sheet can be characterize by different snow facies or zones, which are a result of climatic differences (Benson 1962). Warming Arctic temperatures contribute to a significant increase in the magnitude of melt extent on the surface of the Greenland ice sheet. Understanding the influence of surface melting on the mass balance of the Greenland ice sheet is important and an assessment of the melt dynamics through time is vital to monitoring periodical changes of the ice sheet. The surface melt of the ice sheet can be monitored using satellites that operate across a range of the electromagnetic spectrum. Passive microwave data has been used to study the areal extent and duration of snowmelt that occurs on the Greenland ice sheet. A new approach has been developed to retrieve melt magnitude (surface liquid water fraction by volume) from satellite data that collects in the optical and thermal parts of the EM spectrum.

Background

Greenland Ice Sheet Method

When melting occurs snow changes from dry snow to wet snow and the microwave emissivity of snow increases significantly due to an raise in liquid water content which as a different dielectric constant than dry snow. This distinct change is observed in the brightness temperature (Tb) signal according to the Rayleigh Jeans approximation:

where Tb refers to the microwave brightness temperature at a particular wavelength (λ or frequency υ), ε is the microwave emissivity, and Tp is the effective physical temperature of the snow (Zwally, 1977). Increases in brightness temperature are frequency and polarization dependent (Ulaby et al., 1986). Change in TB signal are the basis behind passive microwave detection melt on the ice sheet surface.

In the past, various techniques have used to retrieve surface melt signatures. These techniques use single channel or multichannel satellite passive microwave data. Both techniques are used to classify dry and wet snow. This analysis explores the performance of two specific techniques, the Cross Polarization Gradient ratio (XPGR) which is a more traditional approach and the newer Diurnal Amplitude Variation (DAV) index:

Technique 1: XPGR[Abdalati and Steffen [1995, 1997]

Technique 2: DAV[Ramage and Isacks [2002]

The Cross Polarization Gradient Ratio is used to account for melting that occurs at various depths. This is important because the physical temperature varies with depth in the snowpack. The Diurnal Amplitude Variation Technique is used to account for melting that might occur during the evening and establishes a rule that melt is occurring when both the ascending (night time) and descending (day time) brightness temperatures are greater than the threshold values A and B.

)()(

)()(

VTHT

VTHTXPGR

BB

BB

3719

3719

AT

VV

B

B ))(T - )(abs(T DAV descendingBascendingB 3737

Introduction

Conclusion

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AVERAGE EMELT

DAV and XPGR Daily Counts

2001 Melt Occurrence vs Melt Magnitude for Composite Period 145

XPGR AVG EMELT

DAV AVG EMELT

XPGR AVG EMELT 0.02 0.09 0.1 0.1 1.22 0.13 0.1 0.13 0.11

DAV AVG EMELT 0.02 0.01 0.02 0.01 0.02 0.02 0.02 0.03 0.04

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XPGR and DAV AVERAGE EMELT

XPGR and DAV DAILY COUNTS

2001 Melt Occurrence vs Melt Magnitude for Composite Period 193

XPGR AVG EMELT

DAV AVG EMELT

XPGR AVG EMELT 0.05 0.13 0.13 0.14 0.14 0.14 0.13 0.13 0.12

DAV AVG EMELT 0.01 0.02 0.02 0.02 0.03 0.05 0.08 0.1 0.11

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DAV and XPGR AVERAGE EMELT

DAV and XPGR DAILY COUNTS

2003 Melt Occurrence vs Melt Magnitude for Composite Period 145

XPGR AVG EMELT

DAV AVG EMELT

XPGR AVG EMELT 0.03 0.1 0.11 0.12 0.12 0.14 0.14 0.14 0.14

DAV AVG EMELT 0.01 0.01 0.02 0.02 0.03 0.03 0.03 0.05 0.05

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DAV and XPGR EMELT

DAV and XPGR DAILY COUNT

2003 Melt Occurrence vs Melt Magnitude for Composite Period 193

XPGR AVG EMELT

DAV AVG EMELT

XPGR AVG EMELT 0.05 0.12 0.13 0.13 0.14 0.14 0.14 0.15 0.15

DAV AVG EMELT 0 0.01 0.02 0.03 0.03 0.04 0.07 0.1 0.12

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DAV AND XPGR AVERAGE EMELT

DAV and XPGR DAILY COUNTS

2004 Melt Occurrence vs Melt Magnitude for Composite Period 145

XPGR AVG EMELT

DAV AVG EMELT

XPGR AVG EMELT 0.03 0.11 0.13 0.15 0.14 0.15 0.14 0.15 0.16

DAV AVG EMELT 0.02 0.01 0.02 0.03 0.03 0.04 0.06 0.07 0.06

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DAV and XPGR AVG EMELT

DAV and XPGR DAILY COUNTS

2004 Melt Occurrence vs Melt Magnitude for Composite Period 193

XPGR AVG EMELT

DAV AVG EMELT

XPGR AVG EMELT 0.08 0.12 0.12 0.13 0.13 0.14 0.14 0.13 0.13

DAV AVG EMELT 0.05 0.07 0.06 0.06 0.07 0.09 0.1 0.12 0.12

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DAV and XPGR EMELT

DAV and XPGR DAILY COUNTS

2005 Melt Occurrence vs Melt Magnitude for Composite Period 145

XPGR AVG EMELT

DAV AVG EMELT

XPGR AVG EMELT 0.02 0.02 0.09 0.1 0.1 0.1 0.09 0.11 0.11

DAV AVG EMELT 0 0.02 0.01 0.01 0.02 0.03 0.02 0.05 0.04

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DAV and XPGR EMELT

DAV and XPGR DAILY COUNTS

2005 Melt Occurrence vs. Melt Magnitude for Composite Period 193

XPGR AVG EMELT

DAV AVG EMELT

XPGR AVG EMELT 0.05 0.1 0.13 0.13 0.13 0.13 0.14 0.13 0.12

DAV AVG EMELT 0.02 0.02 0.02 0.03 0.03 0.06 0.09 0.1 0.11

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DAV and XPGR Average EMELT

DAV and XPGR Daily Counts

2002 Melt Occurrence vs Melt Magnitude for Composite Period 193

XPGR AVG EMELT

DAV AVG EMELT

XPGR AVG EMELT 0.05 0.08 0.1 0.11 0.11 0.1 0.11 0.14 0.15

DAV AVG EMELT 0.02 0.02 0.02 0.02 0.03 0.04 0.07 0.09 0.1

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•The main objective of this project was to assess how surface melt occurrence derived from passive microwave techniques relates to melt magnitude (amount) derived from coupled optical/thermal measurements from MODIS over the Greenland during a period of five years. This comparison will evaluate how significant measured changes in the extent or the occurrence of melt are and ultimately how changes in surface melt influence ice sheet mass balance PB TT )(

OBJECTIVES

Surface melt extent derived from time series analysis of passive microwave data over GIS has been updated through several intervals and indicate significant changes in the extent, frequency and duration of surface melting across GIS. Abdalati and Steffen (2001) illustrate that for a 21-year record (1979-199), a positive trend in melt of approximately 1%/a, with much of this occurring in the western margin of the ice sheet. An updated analysis demonstrated a 16% increase in melt area from 1979-2002 with an anomalous melt extent during the 2002 melt season resulting in atypical extent and frequency in the north and northeast (Steffen et al., 2004). Expansion of increased melt extent was detected in 2005, with the entire southern portion of the ice sheet exhibiting 7-days of sustained melting as high as 2900 m near the South Dome GC-net station and record total melt in north-west GIS, exceeding conditions in 2002 (http://cires.colorado.edu/steffen/greenland/melt2005/). Ashcraft and Long (2006) compare multi-sensor approaches to mapping melt extent and occurrence over GIS and indicate that passive microwave based approach may underestimate melt extent. In response, Wang et al (2007) used enhanced scatterometer data from QuikSCAT (QSCAT) to estimate melt extent at a higher spatial resolution (~ 5km2) than passive microwave approaches (25km2) from 2000 through 2004. They determined that average melt duration for any given year ranged from 14.3-20.5 days with a range in proportion of area experiencing melt between 44.2 and 79.2%. Tedesco (2007) applied the diurnal amplitude variation (DAV) (Ramage and Isacks (2002, 2003) method to passive microwave data over GIS as an improved melt detection scheme from previous passive microwave techniques and demonstrated that from 1992-2005, the melt extent has increased at a rate of ~40,000 km2/a during this period.

Surface Melt Detection

Melt Magnitude

(liquid water fraction)

XPGR derived melt occurrence

(DAY 161, YEAR 2000)

BLUE = Melt Occurrence

WHITE = No Melt

DAV derived melt occurrence

(DAY 161, YEAR 2000)

BLUE = Melt Occurrence

WHITE = No Melt

Contour Map of the Greenland Ice Sheet showing location of Meteorological Stations

Melt Occurrence and Extent Retrieval

Melt Magnitude Retrieval (LWF)

Estimation of surface melt intensity has been achieved using coupled optical/thermal signatures calibrated by a modified version of the physical snowmelt model SNTHERM89 augmented to simulated snow over glacier ice. This empirical retrieval has been designated as effective melt intensity (E-melt) primarily because it represents an integrated measure of liquid water fraction over an 8-day period at 1km2 within the upper 5cm of the glacial firn

ReferencesResults indicate that DAV show a much more proportional relationship to melt magnitude than XPGR consistently during the analysis period. Both techniques show a scaled increase in melt occurrence with melt magnitude from the early part of the melt season (Day 145- May 25) than later in the melt season (Day 193-July 12). Difference in the comparison of XPGR and DAV to E-melt may be due to the ability of DAV to track more night time persistent melt, producing higher occurrences of melt. E-melt values derived from surface reflectance and temperature may be sensitive the diurnal effects as well resulting in a stronger relationship to DAV than XPGR. Further work is necessary to explain these trends.

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Benson, C. S. (1962), Stratigraphic studies in the snow and firn on the Greenland ice sheet, Res. Rep. 70, Snow, Ice, Permafrost Res. Estab.,

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Steffen, K., S.V. Nghiem, R. Huff, and G. Neumann. 2004. The melt anomaly of 2002 on the Greenland ice sheet from active and passive microwave observations, J. Geophys. Res., 31,L20402, doi:10.1029/2004GL00444.

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www.acia.uaf.edu.

Tedesco, M. 2007. Snowmelt detection over the Greenland ice sheet from SSM/I brightness temperature daily variations, Geophys. Res. Let., 34, L02504, doi:10.1029/2006GL028466.

Warrick, R., and J. Oerlemans, 1990: Sea level rise. Climate Change: The IPCC Scientific Assessment, J. T. Houghton, G. J. Jenkins, and J. J. Ephrams, Eds., Cambridge University Press, 257–282..

Ramage, J. M., and B. L. Isacks (2002), Determination of melt-onset and refreeze timing on southeast Alaskan icefields using SSM/I diurnal

amplitude variations, Ann. Glaciol., 34, 391–398.

Ramage, J. M., and B. L. Isacks (2003), Interannual variations of snowmelt and refreeze timing in southeast Alaskan iceshields using SSM/I diurnal

amplitude variations, J. Glaciol., 49, 102– 116.