Spatial variability of interior ice-sheet accumulation determined with an FM-CW

radar and connections to the NAO

David Braaten, Prasad Gogineni, Claude Laird, Susanne Buchardt*, and Hilary Barbour

* Centre for Ice and Climate, Univ. Copenhagen

Introduction• Snow accumulation is important in understanding ice

sheet mass balance and the accumulation/precipitation climatology.

• Detecting near-surface internal layers with radar allow regional scale assessments of snow accumulation on time scales of 1 year or less.

• Radar data permit spatial averaging to overcome local uncertainty caused by wind-generated surface features.

• Regional scale assessments of accumulation on annual time scales can lead to an understanding of links between climate indices and ice-sheet accumulation.

RadarsInstrument Measurement Freq.

BW/Res. Depth Power Altitude Antenna Installs

AccumRadar -Surface

Internal LayeringIce Thickness

1250 MHz

1500 MHz10 cm

300 m 100 mW Surface12-element Vivaldi Array

Tracked vehicle

Accum.Radar –Airborne

Internal LayeringIce Thickness

750 MHz300 MHz40 cm 300 m 10 W 20000 ft Patch Array

Vivaldi Array

Twin-OtterP-3Basler

SnowRadar

Snow CoverTopographyLayering

5 GHz6 GHz4 cm 80 m 200 mW 30000 ft Horn

P-3DC-8Basler

Ku-Band TopographyLayering 15 GHz

6 GHz4 cm 15 m 200 mW 20000 ft Horn

Twin-OtterDC-8Basler

Accumulation Radar – Surface basedFrequency 500 – 2000 MHz

Sweep Time 4 ms

PRF 0.2 kHz

Transmit Power 100 mWatt

Number of Coherent Integrations

60

Antennas 12-element Vivaldi arrays

A/D Dynamic Range 12-bit, 72 dB

Sampling Rate 10 MHz

10.5 “

16 “

Radar Range Profile

2845.01 r

r Relative Dielectric Constant

= r firn density (g cm-3)

Core density profile

Dielectric constant profile

(Kovacs et al., 1995)

The range profile is constructed as follows:

2)()1()( step

n

cnrnr

where: r(n) = depth of the nth range bintstep = time extent of 1 range bin

(Rink, 2006)

Antenna to snow surface = 2 m; er = 1

Pass 1

Pass 2

.5 m

.6 m

Depth

.7 m

.8 m

.9 m

1.0 m

Depth

1.2 m

1.3 m

1.4 m

1.5 m

1.6 m

Snow Pit

Snow Pit

1.7 km

Greenland

Summit Camp,Greenland

Tracked annual layers along traverse

375 kmIce Thickness = 3085 m Ice Thickness = 2542 m

Radar Annual Accumulation: 1889 - 2007

1.2σ

1.2σ

0.6σ

0.6σ

185 km segment - Northern

(Chen, 2013)

Radar Annual Accumulation: 1889 - 2007185 km segment - Southern

1.2σ

1.2σ

0.6σ

0.6σ

(Chen, 2013)

Climate Index - NAONorth Atlantic Oscillation: a diagnostic quantity used to characterize atmospheric circulation patterns in the North Atlantic sector: 20°- 80° N; 90° W - 40° E.

Used Hurrell and Deser (2009) principal component (PC)-based indices of the NAO that are determined by the Empirical Orthogonal Function (EOF) of sea level pressure (SLP) anomalies in the domain.

Connection between Greenland accumulation and PC-NAO?

Previous studies using ice core and model data say no.

Do the regional partitioning and spatial averaging advantages of radar determined accumulation show a connection?

The NAO shifts between a positive phase and a negative phase resulting in large changes in air temperature, storminess, winds, and precipitation.

Large pressure gradient

Weak pressure gradient

Average Accumulation

NGRIP NEEM

NAO versus Accumulation: 1958-2006

Radar annual accumulation• Gridded annual accumulation from Polar MM5

(Burgess et al., 2010)• NEEM ice core derived annual accumulations

PC-NAO time series examined:

• Annual• Winter (DJFM and DJF)• Spring (MAM) Summer (JJA)• Fall (SON)

Significant positive correlations between summer PC-NAO and 25 km-averaged

radar accumulation time series (49 years)

Summer PC-NAO and annual accumulation

r= 0.391P-value= 0.005

25 km segment

Conclusions

• Accumulation radar provides spatial averaging to overcome local redistribution of snow by wind.

• Accumulation radar provides regional coverage allowing examination of different precipitation regimes.

• Positive correlation found between summer PC-NAO and radar determined accumulation.

• Climate models show summer NAO becomes increasingly positive in a warming world (Folland et al., 2009).

• Takes us beyond the Clausius–Clapeyron equation (es(T)) to include large scale circulation for understanding future ice sheet mass balance.