an accuracy assessment of the polar mm5 snow accumulation model

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An Accuracy Assessment of the Polar MM5 Snow Accumulation Model Jared Carse Mentors: Dr. David Braaten, Dr. Claude Laird Graduate Mentors: Aaron Gilbreath, Mitch Oswald

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An Accuracy Assessment of the Polar MM5 Snow Accumulation Model. Jared Carse Mentors: Dr. David Braaten, Dr. Claude Laird Graduate Mentors: Aaron Gilbreath, Mitch Oswald. Polar MM5 Model. Fifth Generation Mesoscale Model modified for polar climates Developed by Burgess et al. - PowerPoint PPT Presentation

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Page 1: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

An Accuracy Assessment of the Polar MM5 Snow Accumulation Model

• Jared Carse• Mentors: Dr. David Braaten, Dr. Claude Laird• Graduate Mentors: Aaron Gilbreath, Mitch

Oswald

Page 2: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

Polar MM5 Model• Fifth Generation Mesoscale Model

modified for polar climates• Developed by Burgess et al.

– “A spatially calibrated model of annual accumulation rate on the Greenland Ice Sheet (1958–2007)”

• Calibrated using firn cores and meteorological station data

• Spans year 1958-2007• Raster data set

Page 3: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

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Page 4: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

Radar Traverse• 375 kilometer

traverse from NGRIP to NEEM

• Snow Accumulation Radar

• Layers traced in MatLab

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NGRIP

NEEM

Page 5: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

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Page 6: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

Converting Radar data• Extract the thickness

of between annual traced layers

• Convert the water equivalent units using ice core density profiles

• Density interpolated between NGRIP and NEEM density profiles

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1994195019061862181817741730168616420

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

NGRIP Density Profile

firn density

YearFi

rn D

ensi

ty (g

/cm

3)

Page 7: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

Import Radar Data into ArcGIS• Each layer extracted

from MatLab has Lon/Lat coordinates

• Projected into the same coordinate system that the Model raster data uses

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Page 8: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

Convert Radar Data to Raster• Same spatial

resolution is needed to accurately compare between radar and model– Mean of points that lie

in each pixel• Raster Calculator

used to form error assessment

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Page 9: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

Model Error and Bias

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1958

1961

1964

1967

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

2006

-0.06-0.04-0.02

00.020.040.060.080.1

0.12 Model Bias

bias

Wat

er e

quiv

alen

ce (m

eter

)

Average Bias =23.403 mm

1958

1961

1964

1967

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

2006

0

0.02

0.04

0.06

0.08

0.1

0.12RMSE

RMSE

Wat

er e

quiv

alen

ce (m

eter

)

Average RMSE = 40.598 mm

Page 10: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

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1958

1960

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

0.09

0.11

0.13

0.15

0.17

0.19

0.21

0.23

0.25

Radar vs. Model Average Accumulation

Radar MeanModel Mean

Year

Accu

mul

atio

n - (

w.e

. - m

eter

)

Model st. dev. = 21.834 mm

Radar st. dev. = 26.211 mm

Page 11: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

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0

0.05

0.1

0.15

0.2

0.25

Southern Third (NGRIP side)

ModelRadar

0

0.05

0.1

0.15

0.2

0.25

Middle Third

ModelRadar

1958

1962

1966

1970

1974

1978

1982

1986

1990

1994

1998

2002

2006

0

0.05

0.1

0.15

0.2

0.25

0.3

Northern Third (NEEM side)

ModelRadar

Page 12: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

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1994

1991

1988

1985

1982

1979

1976

1973

1970

1967

1964

1961

1958

0

0.05

0.1

0.15

0.2

0.25

0.3

NGRIP - Model vs. Ice Core (1958 - 1994)

ModelIce Core

Year

Accu

mul

atio

n w

ater

equ

ival

ence

(met

ers)

2003

1999

1995

1991

1987

1983

1979

1975

1971

1967

1963

1959

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

NEEM – Model vs. Ice Core (1958 - 2003)

ModelIce Core

Year

Accu

mul

atio

n –

wat

er e

quiv

alen

ce (m

eter

)

Page 13: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

NAO - Radar

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0.04

0.06

0.08 0.1 0.1

20.1

40.1

60.1

8 0.2 0.22

-4

-2

0

2

4

6

Southern Third – NGRIP side

Southern MedianLinear (Southern Median)

Accumulation

NAO

Inde

x

0.08 0.1 0.12 0.14 0.16 0.18 0.2 0.22-4-3-2-1012345

Middle Third

Middle MediansLinear (Middle Medians)

Accumulation

NAO

Inde

x

Correlation = .17264

0.08 0.1 0.120.140.160.18 0.2 0.220.240.260.28-4-3-2-1012345

Northern Third – NEEM side

Northern Me...

Accumulation

NAO

Inde

xCorrelation = .090376

Correlation = .081642

Photo extracted from /www.ldeo.columbia.edu/res/pi/NAO/

Page 14: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

NAO – Ice Cores

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0.1 0.12 0.14 0.16 0.18 0.2 0.22 0.24 0.26-4

-3

-2

-1

0

1

2

3

4

5 NGRIP Ice Core

NGRIP Ice Core

Accumulation - water equivalent (meter)

NAO

Inde

x

0.09 0.13 0.17 0.21 0.25 0.29-4

-3

-2

-1

0

1

2

3

4 NEEM Ice Core

NEEM Ice Core

Accumulation w.e (meter)

NAO

Inde

x

correlation -0.17534

Correlation0.22803

Page 15: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

Summary of NAO• From ice core data

– Negative NAO year produce higher accumulation at NEEM– Positive NAO years produce higher accumulation at NGRIP

• To be statistically significant– At alpha = 0.10– Correlation = .243– The largest correlation occurs at NGRIP ice core with

correlation = .22803– Therefore the relationship between NAO and accumulation is not

significant. A larger sample size is needed, i.e. more years need to be measured

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Page 16: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

How well does the model perform?

• Ice core bias = 17.545 mm

• Radar bias = 34.355 mm

• Model compared to both radar and ice cores, consistently over-predicts

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1994

1991

1988

1985

1982

1979

1976

1973

1970

1967

1964

1961

1958

-0.1

-0.05

0

0.05

0.1

0.15

0.2NGRIP - Bias Values

Model - Core Bias

Model - Radar Bias

Wat

er e

quiv

alen

ce (m

eter

)

Page 17: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

Future uses of model• Could be used as tool

to help trace layers– Model corresponds

with ice cores fairly well

– Large-scale coverage rather than point sources that ice cores give us

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Page 18: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

Caveats • The model accumulation is set annually,

January 1 – December 31• Radar layers can be variable

– Large storms could produce layers that appear to be annual

• Model appears to be less variable than accumulation detected through radar

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Page 19: An Accuracy Assessment of the Polar MM5  Snow  Accumulation Model

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