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High-resolution vertical profiles of X-band polarimetric radarobservables during snowfall in the Swiss Alps

M. Schneebeli1, N. Dawes2, M. Lehning2 and A. Berne1

1Environmental Remote Sensing Laboratory, EPFL, Lausanne, Switzerland2WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland

[email protected]

ERAD 2012 - June 26 2012

Introduction Measurements Results Conclusions

Motivation

Snow crystal habit

Can snow microphysical processesbe observed with an X-bandpolarimetric radar?

Can such a radar distinguishdifferent snow particles?

General atmospheric behavior

Do X-band polarimetric variablesexhibit a general behavior withheight?

Can such a behavior be related toatmospheric processes?

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High-resolution vertical profiles of X-band polarimetric radar observables during snowfall in the Swiss Alps


Overview

In order to properly quantify the instrumental errors, it is nec-

essary that the accuracy of the local deviation estimates is

significantly smaller than the considered errors. The first step

in checking this concerns the quality of the sun ephemeris.

) provides an accu-

racy for the sun position in azimuth and elevation with a max-

imum error of about 0.003 deg from 2003 to 2023, which is

far high enough. In order to reach this accuracy, the geo-

graphic position (referred to WGS84 ellipsoid) of the cen-

ter of rotation of the antenna has to be known with an er-

ror smaller than 0.001 deg (i.e. about 110m, reachable with

a standard GPS beacon). It must be noted that the vertical

deflection can be non-negligible, especially in mountainous

regions, and in that case must be taken into account. This

angle represents the difference at the same position between

the true zenith, which is the reference for the astronomical

Radar at 2133 m above sealevel.

Considered period: End ofFebruary to end of April2010.

Around 110 hours ofsnowfall collected abovethe melting layer.

Contrasting snow events:cold dry snow, aggregates,graupel, dendrites.

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Overview

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Radar calibration

Radar constant determined with a corner reflector.

Radar orientation determined by sun tracking.

Zdr is calibrated by rotating the antenna at 90◦ elevation.

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Experimental data (1)

Radar

RHI scan every 5 min.

150 samples per ray at 1◦ resolution.

6 vertical profiles extracted between 5and 10 km distance from the radar.

Water vapor

Water vapor path (WVP) inferredfrom GPS signal.

WVP separated into three temperaturesegments by using the humidity andtemperature measurements at differentheight levels.

-5 0 5 10 15 20

01

2

3

4

5-7.0 0.0 7.0 14.0 21.0 28.0 35.0

Reflectivity

Fri Mar 26 15:27:22 2010

Radial distance [km]

Heig

htagl[k

m]

-5 0 5 10 15 20

01

2

3

4

5-0.5 0.0 0.5 1.0 1.5 2.0 2.5

Differential reflectivity


Heig

htagl[k

m]

-5 0 5 10 15 20

01

2

3

4

50.76 0.80 0.84 0.88 0.92 0.96 1.00

Copolar correlation


Heig

htagl[k

m]

-5 0 5 10 15 20

01

2

3

4

5-0.60 0.10 0.80 1.50 2.20 2.90 3.60

Spec. differential phase shift


Heig

htagl[k

m]

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Radar

RHI scan every 5 min.

150 samples per ray at 1◦ resolution.

6 vertical profiles extracted between 5and 10 km distance from the radar.

Water vapor

Water vapor path (WVP) inferredfrom GPS signal.

WVP separated into three temperaturesegments by using the humidity andtemperature measurements at differentheight levels.

0

2

4

6

8

10

12

14

60 70 80 90 100 110 120

Day of year 2010

Integrated

water

vapor

[mm]

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Snow intensity

Snow accumulation per time inferredfrom several snow height sensors.

Temperature profile

Determination of the 0◦ level by fittingtemperature measurements at differentheight levels.

60 70 80 90 100 1100

1

2

3

4

5

Snow

rate

[cm

h−1]

Day of year 2010

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Snow intensity

Snow accumulation per time inferredfrom several snow height sensors.

Temperature profile

Determination of the 0◦ level by fittingtemperature measurements at differentheight levels.

1

1.5

2

2.5

3

3.5

-12 -10 -8 -6 -4 -2 0

Heig

ht above s

ea level [m

]

Temperatur [C]

MeasurementsFit

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Distribution of polarimetric observables

−0.5 0 0.5 1 1.5 2 2.5

5

4

3

2

1

0 0

−5

−10

−15

−20

−25

−30

−5 5 15 25 35

5

4

3

2

1

0 0

−5

−10

−15

−20

−25

−30

0

0.05

0.1

0.15

0.2

0.25

−0.5 0 0.5 1 1.5

5

4

3

2

1

0 0

−5

−10

−15

−20

−25

−30

0.75 0.8 0.85 0.9 0.95 1

5

4

3

2

1

0 0

−5

−10

−15

−20

−25

−30

Heigh

tab

ove0◦C

level[km]

Heigh

tab

ove0◦C

level[km]

Heigh

tab

ove0◦C

level[km]

Heigh

tab

ove0◦C

level[km]

Zh

[dBZ]

Zdr

[dB]Kdp

[◦ km−1]

ρhv

[-]

temperature

[◦C]

temperature

[◦C]

temperature

[◦C]

temperature

[◦C](a) (b)

(c) (d)

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Distribution of polarimetric observables

0.75 0.8 0.85 0.9 0.95 11.5

2

2.5

3

3.5

4

−10

−15

−20

−25

0.05 0.1 0.15 0.2 0.25Heigh

tab

ove0◦C

level[km]

Tem

perature

[◦C]

Zdr [dB]

Kdp[◦km−1]

Dendrification signal in Zdr and Kdp → Kennedy et al., JAMC, 2011.

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Mean Hydrometeor identification

0 0.2 0.4 0.6 0.8 10

1

2

3

4

5

0

−5

−10

−15

−20

−25

−30

Heigh

tab

ove0◦C

level[km]

fraction

Hydrometeor identification

AG CR HDG

LDG temperature

[◦C]

Hydrometeor identification with thealgorithm of Dolan and Rutledge,JTECH, 2009.

Increasing abundance of aggregatestowards higher temperatures.

Increasing abundance of graupeltowards higher temperatures.

Aggregates, Crystals, High density graupel, Low density graupel

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Polarimetric profiles as a function of humidity

0 1 2

0

-5

-10

-15

-20

-25

-30

0.8 0.9 1-0.5 0 0.50 0.5 1

0

1

2

3

4

5

-5 5 15

Heigh

tab

ove0◦C

level[km]

(a) (b) (c) (d) (e)

Zh

[dBZ]

Zdr

[dB]

Kdp

[◦ km−1]

ρhv

[-]

# of profiles

[×103]

temperature

[◦C]

low water vapor

high water vapor

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Polarimetric profiles as a function of humidity

0 0.5 10

1

2

3

4

5

0

−5

−10

−15

−20

−25

−30

0 0.5 10

1

2

3

4

5

← c

0

−5

−10

−15

−20

−25

−30

Heigh

tab

ove0◦C

level[km]

Heigh

tab

ove0◦C

level[km]

fraction

(a) (b)

fraction

Low water vapor High water vapor

temperature

[◦C]

temperature

[◦C]

Signature ofdendrification in highwater vapor conditions.

Increased abundance ofgraupel in high watervapor conditions.

Increased abundance ofcrystals in low watervapor conditions.


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Hydrometeor identification vs. snowfall rate

0 0.5 10

1

2

3

4

5

0

−5

−10

−15

−20

−25

−30

0 0.5 10

1

2

3

4

5

0

−5

−10

−15

−20

−25

−30

Heigh

tab

ove0◦

level[km]

Heigh

tab

ove0◦

level[km]

fraction

(a) (b)

fraction

Low snow accumulation High snow accumulation

temperature

[◦C]

temperature

[◦C]

Strongly increasedsignature of graupelformation for highsnowfall rates. →Harimaya and Nakai,JMSJ, 1999; Houze andMedina, JAS, 2005.

Increased abundance ofaggregates for highsnowfall rates.


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Conclusions and Outlook

Conclusions

The average behavior of around 8000 vertical polarimetric profilesmeasured with an X-band radar above the melting layer has beenstudied.

X-band polarimetric profiles as a function of the height above 0◦Care related to microphysical processes such as dendrification,aggregation and riming.

High snowfall rates are coupled to increased riming occurrence.

Outlook

Are we able to theoretically reproduce and confirm theseobservations by coupling an electrodynamical model to a snowmicrophysics model?

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